IPDS 2006 Integrated Powertrain & Driveline Systems 2006
Conference Organising Committee Nick Vaughan (Chairman) Geoff Davis Chris Brace Adrian Cole Derek Eade Dave Simner Anthony Thompson
Cranfield University Ricardo UK Ltd University of Bath TIC University of Hertfordshire Cranfield University Lotus Cars
IPDS 2006 Integ rated Powertrai n & Driveline Systems 2006 14-15 June 2006 Ford Motor Company, Dunton, Essex Institution of Mechanical Engineers Automobile Division
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CRC Press Boca Raton Boston New York Washington, DC
WOODHEAD PUBLISHING LIMITED Cambridge England
Published by Woodhead Publishing Limited, Abington Hall, Abington, Cambridge CBI 6AH, England www.woodheadpublishing.com Published in North America by CRC Press LLC, 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487, USA First published 2006, Woodhead Publishing Limited and CRC Press LLC © 2006, Institution of Mechanical Engineers unless otherwise stated The authors have asserted their moral rights. This book and CD-ROM contain information obtained from authentic and highly regarded sources. Reprinted material is quoted with permission, and sources are indicated. Reasonable efforts have been made to publish reliable data and information, but the authors and the publishers cannot assume responsibility for the validity of all materials. Neither the authors nor the publishers, nor anyone else associated with this publication, shall be liable for any loss, damage or liability directly or indirectly caused or alleged to be caused by this book or CDROM. Neither this book, CD-ROM, nor any part thereof may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, microfilming and recording, or by any information storage or retrieval system, without permission in writing from Woodhead Publishing Limited. The consent of Woodhead Publishing Limited does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific permission must be obtained in writing from Woodhead Publishing Limited for such copying. Further terms and conditions concerning the CD-ROM are included on the CD-ROM. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation, without intent to infringe. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library. Library of Congress Cataloging in Publication Data A catalog record for this book is available from the Library of Congress. Woodhead Publishing ISBN-13: 978-1-84569-197-4 Woodhead Publishing ISBN-I 0: 1-84569-197-0 CRC Press ISBN-IO: 0-8493-8888-0 CRC Press order number: WP8888 Printed by Antony Rowe Limited, Chippenham, Wilts, England
CONTENTS Section 1: Transmissions The investigation of automotive transmission error characteristics subject to operating conditions G Davis, Ricardo UK Ltd, UK and P Brooks, University of Leeds, UK
3
Comparison of approximation methods applied to a complex nonlinear analytical transmission model R H Cornish and Y H Siew, Technology Innovation Centre, UK, and J A Pears, Romax Technology, UK
11
Gear teeth impacts in hydrodynamic conjunctions: idle rattle o Tangasawi, S Theodossiades and H Rahnejat, Wolfson School of Mechanical and Manufacturing Engineering, Loughborough University, UK, and P Kelly, Ford Werke AG, Germany
19
The prediction of loaded static tooth behaviour for automotive parallel axis gears A Leavitt and P Brooks, University of Leeds, UK, and D Parkin-Moore, Ricardo UK Ltd, UK
29
Boundary lubrication film formation from belt type CVT fluids K Narita, fdemitsu Kosan Company Ltd, Japan, and M Priest, Institute of Tribology, University of Leeds, UK
39
Design consideration and potential of the Milner CVT A Hunt and S Akehurst, University of Bath, UK, and S Schaaf, fntersyn Technologies, Texas, USA
51
Section 2: Concept to Market Evolution Optimum engine models for diesel automotive powertrain development processes R P Osborne and N Weaver, Ford Motor Company Ltd, UK
67
Hardware-in-the-Ioop simulation (HIL) for production engine development C Haukap, K Ropke and B Barzantny, fA V GmbH - Ingenieurgesellschaft Auto und Verkehr, Germany
77
Section 3: Powertrain Integration An integrated simulation approach: Ricardo Transmission and Driveline Dynamic Simulation Library F V Brandao and P A Harman, Ricardo UK Ltd, UK
v
87
A powertrain thermal simulation model J Hartland and A Robertson, Jaguar Cars Ltd, UK
95
Novel techniques for holistic powertrain optimisation - a hybrid vehicle case study C M Crewe, J Seabrook and F V Brandtlo, Ricardo UK Ltd, UK, and S P Edwards, Ricardo Deutschland GmbH, Germany
105
Hybridization of a small SUV and its control B Cho and N D Vaughan, Cranfield University, UK
117
Concept and potential of 'CVT-hybrid-driveline' B-R Hahn, H Pflaum and D Tomic, Gear Research Centre, Technical University Munich, Germany
127
Power combining single regime transmissions for automotive vehicles F Moeller, NexxtDrive Ltd, UK
141
Section 4: Engine Integration Driveability validation using MAHLE Powertrain's IDAA toolset D Baker, T Girling, G Kennedy, D Pates, and B Porter, MAHLE Powertrain Ltd, UK
153
The effect of exhaust aftertreatment and engine temperature on IOLs for CVT powertrains J A Gutierrez Magana and C J Brace, University of Bath, UK
169
A turbocharged diesel engine with intake air accumulator to improve torque transients in a CVT powertrain Y Rohrbacher, B Bonnet and N D Vaughan, Cranfield University
189
vi
THE INVESTIGATION OF AUTOMOTIVE TRANSMISSION ERROR CHARACTERISTICS SUBJECT TO OPERATING CONDITIONS Dr. Geoffrey Davis Ricardo UK Ltd. Midlands Technical Centre. Leamington Spa. CV32 1FQ. Email:
[email protected] Dr. Peter Brooks School of Mechanical Engineering. University Of Leeds. Leeds. LS2 9JT Email:
[email protected] ABSTRACT In the current automotive market, the increasing demand for improved vehicle refinement has led to vehicle manufacturers dedicating ever increasing budgets to the reduction of airborne and structure borne noise. Geared components of the drivetrain, specifically transmissions and final drives, can make a significant contribution to the combined noise and vibration that manifests itself externally or within the passenger compartment. It is the desire of all drivetrain engineers to reduce these sources of noise, thereby improving vehicle refinement, whilst maintaining the geared components required functionality. Despite decades of research there is still a need for improved understanding of the role that gears and the particulars of their design play in producing system excitation and therefore noise. This paper details the investigation of automotive transmission gear pair behaviour. The specific parameter of interest is transmission error, which is widely recognised as a major source of high frequency excitation in automotive transmissions, and fundamental to mesh frequency components of audible noise. Following an extensive literature review (1, 2) the authors identified the need for further experimental investigation of the behaviour of Transmission Error when subject to typical automotive operating conditions, variations in macro and micro geometry and gears of typical automotive quality. To aid investigation it was necessary to develop a suitable experimental facility. Following the development of an advanced gear pair test rig a series of extensive tests were conducted, the findings of which highlighted a series of clear trends that exist between operating conditions, changes in geometry and Transmission Error.
NOTATION Transmission Error, radians Angular rotation of the input and output gears, radians Number of teeth on the input and output gears Fp fp fi' Fi' Fp'
Cumulative pitch error, microns Adjacent pitch error, microns l/tooth Transmission Error component, microns Total composite Transmission Error, microns Cumulative working pitch error, microns
3
INTRODUCTION
The continued requirement for improved vehicle refinement has forced Ricardo's engineers to dedicate significant resource to reducing the drivetrains NVH contribution. During a specific piece of consultancy work (3) Ricardo engineers attempted to predict audible gear whine for a spur and helical geared transmission. Despite reasonable correlation the work failed to accurately predict absolute noise levels. The likeliest source of error within the analysis was deemed the accurate prediction of gear mesh based behaviour; specifically tooth contact behaviour and the resultant torsional excitement caused as a result. At the time Ricardo had no specific research programme dedicated to investigating the fundamental sources of gear mesh excitation and in particular a physical parameter known as Transmission Error (TE). A subsequent research programme in conjunction with the School of Mechanical Engineering at the University of Leeds proceeded with the goal of creating a suitable experimental test facility suitable for the measurement of TE in automotive gear pairs subject to operating conditions. An outline of the findings of this research are included in the following paper, and full details can be found in the additional work of the author. To date a significant quantity of gear noise and vibration related research has been conducted within the United Kingdom and worldwide. The early work (4) conducted at The University of Cambridge is recognised as the cornerstone of much of the research conducted since. The relevance of much of the previous work to automotive transmission applications is questionable. Despite numerous researchers modelling and experimentally investigating the effect of various geometrical parameters on TE, gear dynamic behaviour and noise, much of the correlation and investigation has occurred at inappropriate operating conditions and has been based on gears not typical of those found in the automotive environment. Thus the investigation of gear behaviour subject to typical automotive operating conditions (variable speed, variable torque, mesh misalignment) and with gears of automotive quality and dimension has seen an inadequate amount of dedicated attention since research into dynamic gear pair behaviour started some fifty years ago. AUTOMOTIVE TRANSMISSIONS, GEARS & TRANSMISSION WHINE
Transmission casings are excited by a combination of internal acoustic pressure, internal steady state wall pressure and gear mesh orientated excitation transmitted via the bearings. Numerous authors (5,6,7,8) have shown that Transmission Error (TE) is recognised as the most prominent source of gear mesh based excitation, with the time varying component periodic at mesh frequency directly related to noise. The standard definition for TE is as follows - Transmission Error is the deviation in the position of the driven gear (for any given position of the driving gear), relative to the position that the driven gear would occupy if both gears were geometrically perfect and undeformed - and can be calculated as follows: (1)
TE is caused by the non-conjugate motion of meshing gear pairs, causing high frequency vibrations that excite the gears themselves and in tum the shafts and bearings, Figure 1. Although gear body vibration generates airborne noise, the transmission
4
housing acts as a poor transmitter of sound so little of the original airborne noise reaches the external environment. The noise is predominantly structure borne and the dynamic forces generated are transmitted via the bearings which excite the housing, with the level of exciting force largely dependent on the magnitude of TE, the dynamic response of the gears and the supporting structure. The surfaces of the vibrating transmission housing act like a loudspeaker and propagate the audible noise that is heard. The vibration is also transmitted via the gearbox mounts to the chassis and enters the cabin through alternative paths.
Mesh Excitation
--+
Torsional and Lateral Vibration and Gear Blank Resonance's
L
Housing Vibration
....
Dynamic Mesh and Bearing ~ Forces
--+
BearingIHousing Interaction
-
Other ~ Generated Vibration Noise Paths
--+
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-
Figure 1. Gear noise transmission path (6). The fundamentals of TE are discussed in numerous publications (2). In essence, if the gear teeth of a meshing gear pair of identical geometry were of a perfect involute profile, rigid and correctly spaced around the base circle radius then there would be no rotational error. In practice this does not occur and it is as a result of TE. When a gear pair mesh freely under no torque and at a minimum speed, the measured TE is due to the geometrical variations from the perfect involute profile of the meshing tooth geometry. When subject to load and speed, tooth stiffuess and inertia effects are present and true representation of these effects shows clear variation with the no load TE signal. Therefore TE is considered to exist in one of three forms; static, quasi-static and dynamic. Subject to minimum torque and speed, static TE is attributed to geometrical and manufacturing deviations only. However, as the gear geometry becomes more complex additional design parameters such as helix angle actively contribute to the measured TE. Quasi-static TE is measured under sufficient load to induce mesh deformation, yet at a sufficiently low speed to render dynamic effects negligible, and with the addition of torque the contribution of mesh-stiffuess variation, gear body distortion and mesh misalignment to the TE signal can be observed. Dynamic TE is subject to operating speeds and torques and therefore considers inertia, mesh stiffness and the dynamic response of the meshing gear pair. A typical time domain static TE trace is shown in Figure 2. The TE signal consists of two fundamental components, the once per rev (llrev) and once per tooth (l/tooth) components. The lIrev component is the low frequency large amplitude signal whilst the lItooth component is the high frequency small amplitude signal that occurs at TMF. Analysis of the composite TE signal in the frequency domain enables determination of the magnitude of the IIrev and IItooth frequency components and their relative
5
hannonics. Where transmission noise, otherwise known as whine is the primary interest then the lItooth component ofTE and its hannonics are significant. Composite Transmission ElTor with l/rev component superimposed I
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Figure 2 Static composite TE trace with lIrev component filtered and superimposed. There are many operational and geometrical parameters that influence TE and therefore noise (2). In brief these include; • Operational and system parameters Mesh misalignment, gear body defonnation, lubrication regime, bearings selection and design, transmission housing optimisation. • Geometrical parameters Manufacturing errors such as pitch, profile and pressure angle errors. Optimisation of key macro and micro-geometrical design parameters, Previous research has investigated the implications of many of these parameters on TE for non-automotive applications and has also focused on the reduction of TE through optimisation of tooth geometry for set operating conditions. Despite the benefits of macro and micro geometrical optimisation being clear, the application to gears that are subject to a wide range of operating conditions and varying levels of quality requires further investigation to improve understanding.
EXPERIMENTAL TEST FACILITY DEVELOPMENT In order to meet the requirements of a dedicated research tool (1) developed exclusively for the investigation of TE in automotive transmission applications, the experimental test rig would be required to measure TE of typical automotive gears subject to a range of operating conditions. The authors developed a dedicated test rig using an existing 5 speed front wheel drive transverse transmission as a basis. The gearbox in question
6
utilised an overhung sth speed gear pair, which rendered it particularly suitable for experimental investigation of TE with optical encoders. Therefore the test rig was developed into a suitable test bed for the measurement of TE and gear pair mesh misalignment of the overhung sth speed gear pair only. The transmission casing was removed and replaced with a dedicated set of fixtures, which retained key design attributes of the original transmission such as centre distances. Only key internals (primary and main shafts, final drive and differential) were retained. All gears (except sth), synchronisers and shift system components were removed. At the input the clutch mechanism and all ancillaries were removed and replaced with a dedicated coupling and flange arrangement. Drive was transferred from the differential through a modified splined driveshaft which mated to the internal spline of the differential. A series of dedicated sth gear pair test specimens were designed and manufactured to replace the original gears and therefore enable component testing and experimental investigation. Tufnol shaft and torsionaly stiffCY coupling assembly
pair
I Removable mounting unit and encoder housing assembly
Figure 3. Optical incremental shaft encoders and accompanying shaft assembly. In order to measure TE two SV TTL 36000 line optical incremental shaft encoders were used. These were attached to the overhung Sth speed gear pair by means of a torsionally stiff shaft, bearing and coupling arrangement which isolated the optical encoders from the Sth speed gear pair mesh misalignment, Figure 3. In order to measure mesh misalignment, a series of test gear specimens were fitted with target discs. Once fitted to the gear body the measurement surface of the disc was machined true so that it was perpendicular to the longitudinal axis of the shaft. A series on non-contacting eddy current displacement transducers were located at 90° intervals around each target disc thus enabling accurate measurement of the deviation of the surface of the target disc and therefore mesh misalignment. A key requirement for the accompanying data acquisition system was the synchronous and simultaneous measurement of the rotational position of each incremental encoder and therefore gear. This system attribute was vital for accurate measurement of TE. In order to achieve this requirement a combination of dedicated counter/timer hardware (for accurate TE measurement) in conjunction with high speed AID hardware (mesh misalignment measurement and all other ancillary signals) and a dedicated PC were used (2). This enabled accurate measurement of TE and misalignment simultaneously with a TE signal resolution of ~O.l arc seconds.
7
EXPERIMENTAL INVESTIGATION During the experimental research several areas of investigation were conducted using a series of dedicated automotive gear specimens. In summary these investigations focused on the implications of gear design geometry on measured TE and the comparison between TE measured subject to static, quasi-static and dynamic conditions. The following section gives an overview of some of the key findings. Using the captured data the following plots (Figure 4 through to Figure 6) illustrate a selection of the results. Figure 4 shows the benefit of increased total contact ratio on TE for a gear pair subject to a range of applied torque under quasi static conditions. The results clearly show that for the basic gear design the amount and extent of tip relief was optimised for an applied torque of ~30Nm resulting in minimum TE at this torque, however for higher levels of torque the mesh deformation increases significantly resulting in increased TE. An increase in total contact ratio counters the increase in TE at higher torques, with the gear pair with the highest total contact resulting in the lowest amount of TE across the operating range. These results clearly indicate the benefit in maximising total contact ratio for reducing TE and therefore reducing noise. 3.0
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Torque (Nm) 1___ 3.071 ...... 3.213 ..... 3.351 -El-3.487 -&-3.621 -.!r-3.7521
Figure 4. Variation in the median value of the peak-to-peak lIper tooth component of TE, for gears subject to quasi-static operating conditions (lS0rpm) with a variation in Total Contact Ratio. Figure 5 presents test data for the same gear specimens when subject to an identical range of applied torque, but dynamic operating conditions (27S0rpm versus lS0rpm). These results show very different behaviour in terms or reduced TE for increased Total Contact Ratio. In this case the gear with the greatest value of Total Contact Ratio does not result in the least TE across the operating window. These results highlight the importance of considering system dynamics when optimising gear designs for low TE and low noise. With specific focus on contact ratio further benefits can be made by optimising the Transverse Contact Ratio and Helical Overlap Ratio independently. Use
8
of integer values and a maximum value of Total Contact Ratio will yield significant benefits in producing a low value ofTE and therefore low noise (2). 3.0
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Figure 5. Variation in the median value of the peak-to-peak lIper tooth component of TE, for gears subject to Dynamic operating conditions (2750rpm) with variation in Total Contact Ratio. 3.0
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Figure 6. Comparison of the variation in the median value of the peak-to-peak lIper tooth component of TE, for gears subject to quasi-static and dynamic operating conditions and identical values of Total Contact Ratio
9
The difference between results obtained from quasi-static and dynamic conditions is further highlighted in Figure 6 which compares quasi-static and dynamic data for two gear pairs with a similar value for Total Contact Ratio. The quasi-static data indicate a marginal improvement by increasing Total Contact Ratio. When subject to dynamic conditions, not only are the overall values of TE lower when the gear pair are subject to dynamic conditions but the benefit from a marginal increase in Total Contact Ratio is significantly greater than that shown for quasi-static operating conditions. Once again this highlights the risks associated from using knowledge gained solely through quasistatic based test data when developing low noise transmissions.
CONCLUSIONS The test results have shown that the dedicated gear pair test rig and data acquisition system has enabled accurate measurement ofTE for automotive gears subject to a range of operational conditions. From the test data shown it is clear that TE behaviour when subject to dynamic conditions differs greatly from that tested under quasi-static conditions, highlighting misleading conclusions that maybe made from quasi-static test data and any analytical approach that does not consider system dynamics. Furthermore, the results clearly show that simply increasing the Total Contact Ratio does not guarantee a low noise automotive transmission. Careful thought must be given to fine tuning the individual values of Involute and Transverse Contact Ratio to guarantee a low value ofTE and therefore noise.
REFERENCES 1. Davis, G. Brooks, P. Findlay, M. (2001), "Recent Advances in Automotive Gear Pair Dynamic Behaviour Measurement and Prediction - A Review", MPT2001 JSME International Conference on Motion and Power Transmissions, November 15-17, 2001, Fukuoka, Japan, pp.90-96, Japanese Society of Mechanical Engineers. 2. Davis, G (2004), "An Investigation of Automotive Transmission Error Characteristics, Subject To Operational Conditions", PhD Thesis, University of Leeds, England. 3. Beacham, M. R. Bell, D. J. Powell, N. N. Savage, M. T. (1999), "Development of Transmission Whine Prediction Tools", SAE Technical Paper Series, SAE 99NV - 101. 4. Harris, S. L. (1958), "Dynamic Loads on the Teeth of Spur Gears", Proceedings of the IMechE, Vol.172, No.2, pp.87-112. 5. Welbourn, D. B. (1979), "Fundamental Knowledge of Gear Noise - A Survey", Proceedings of the IMechE, Cll17179, pp.9-14, 1979, Institute of Mechanical Engineers, London. 6. Townsend, D. P. (1991), "Dudley's Gear Handbook", Second Edition, McGraw-Hill Inc, ISBN 0-07-017903-4 7. Munro, R. (1991), "An Analysis of Some of Niemann's Gear Noise Measurements of Spur Gears", MPT'91 JSME International Conference on Motion and Powertransmissions, November 23-26,1991, Hiroshima, Japan, JSME, pp.lO-14. 8. Smith, R. E. (1988), "The Relationship of Measured Gear Noise to Measured Gear Transmission Errors", Gear Technology Magazine, Jan-Feb 1988, pp.38-47. © Ricardo PIc. 2006
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Comparison of Approximation Methods Applied to a Complex NonLinear Analytical Transmission Model R. H. Cornish!, Y. H. Siew!, J. A Pears 2 I Technology Innovation Centre, Millennium Point, Curzon Street, Digbeth, Birmingham B47XG, United Kingdom 2 Romax Technology, UK Head Office, Rutherford House, Nottingham Science and Technology Park, Nottingham, Nottinghamshire, NG7 2PZ, United Kingdom
ABSTRACT This paper describes an investigation into a number of approximation methods applied to a non-linear analytical model of a truck planetary hub reduction unit. The effective transmission error of the planetary set is calculated using the proprietary transmission software, RomaxDesigner, for a range of design variants to generate a training set of data. Three approximation models are then derived to fit the training data, and the accuracy of each model assessed. The potential use of the approximation models with regard to optimisation and design sensitivity studies is discussed and the expected time savings described. INTRODUCTION Computer based simulation codes are widely used in the automotive industry for a large number of sophisticated calculations, including computational fluid dynamic analysis, finite element analysis and domain specific software packages. However, as the problems become more complex, the run-times for these analyses can be of the order of hours, or even days. It is still the case that processor speeds are exceeded by the engineering drivers. Even short run-times limit the usefulness of the simulation codes in design optimisation and tolerance sensitivity studies where many repeat runs are necessary.
Approximation methods are a useful tool in which the computationally expensive simulation code is replaced with an approximate, non-physical numerical model, which can be evaluated in a short time. This "approximation model" (sometimes called a surrogate model or metamodel) can then be used for optimisation, design space exploration and tolerance sensitivity studies etc. This paper describes an initial investigation into the application of approximation methodologies to a complex non-linear problem using the proprietary software package, RomaxDesigner. RomaxDesigner is the "best-in-class" software package for integrated gearbox and driveline engineering and is used worldwide by the majority of automotive OEMs to accelerate their design process and to simulate durability and refinement.
11
Fig. 1: A typical 4 planet epicyclic gearset
The specific engineering problem chosen for this study was the investigation of a planetary gear set in the hub reduction unit of a truck (Fig. 1). The effective transmission error of the planetary gearset is known to have a significant impact on both the gear whine noise and the dynamic behaviour of the whole driveline. It is strongly influenced by the many design parameters of the planetary gearset, and can be uniquely predicted by RomaxDesigner with a run time of approximately 5 minutes on a typical desktop PC. This run time may be reasonably short, but is sufficient to illustrate the possible advantages of using approximation methods. This academic project has been supported by Romax Technology, UK. Approximation Methods For this project, three approximation methods are used for comparison, namely Polynomial Cubic Expansion, Neural Network and Radial Basis Function. Polynomial Cubic Expansion The Polynomial model is based on ideas from the Taylor series. It is the most commonly used model in experiment design because it is easy to apply, based as it is on the relation of several input factors and one response output. Generally the polynomial has the form as shown below. y=
b o + b1Xl+ b2X2+ b3X3+ b12XIX2+ b13xlX3 + b23X2X3+ b123XIX2XJ+ b 11 X1 2+ b 22 x/+ b33X32 + e
where Y is the output response, b are the model coefficients and x is the input variable. The coefficients are chosen to minimize the error e, with the training data. The polynomial works well where the data is smooth and has no sudden changes. Neural network The idea for an Artificial Neural Network is based on the nervous system of a human brain which consists of 100 billion of cells known as neurons (Fig. 1) that are connected with each other. Generally, each neuron will be connected to about ten of thousand others. A neuron can receive multiple inputs while sending one output. The mathematical formula for one perceptron is shown below. The inputs are multiplied by weights (w) which represent the synaptic strength.
12
where Y is the response of the neuron, Wi is the weight of the ith input value, Xi is the ith input value, b is the threshold for the neuron and f is the transfer function or activation function. Radial Basis Function A radial basis function model is represented by the equation below:
i
where Y is the output response, Wi is the weight of the ith neuron, is the univariate function, X is the input n-dimensional vector, ~ is an n dimensional vector locating the radial basis centre. The modulus term represents the Euclidean distance of the input vector from the radial basis centre. The assumption is that the nearer the input vector is to the centre point of the neuron the stronger the reaction. The radial basis function is said to be advantageous compared with a multilayer neural network in having less tendency towards oscillatory behaviour. Engineering Application - Planetary Transmission Error Planetary Gears
Planetary gearsets are widely used in automatic transmission systems of cars as well as in truck wheel hubs to increase torque to the wheel, whilst keeping the torque low in the rest of the driveline. A planetary hub reduction unit is typically used in mining, logging, and heavy hauling trucks which have high gross weight requirement. This set of planetary gears is situated within the wheel hub that connects the wheel hub to the axle shaft. The sun is connected to the drive axle shaft and the ring gear is fixed to the axle housing while the planetary carrier is connected to the wheel hub as a power output. RomaxDesigner In modeling the planetary gear, the specialist transmission software RomaxDesigner has been used. It allows the design and analysis of the driveline in one package and contains a fully coupled non-linear algorithm to analyse the shaft/bearinglgearlhousing static system.
The gears, planetary gear system, bearings and shafts are modelled as analysis objects with correlation to validated tests. This makes it much easier and faster to enter these components by just keying in the design parameters and editing their attributes. RomaxDesigner can calculate all the gear meshing points, forces, load distribution and take into account all the boundary connections. The housing finite element models of planetary carriers and housings are condensed in RomaxDesigner to a reduced stiffness matrix and coupled with the internal transmission through the bearing nodes. The stiffness sub-matrix for a rolling element bearing, linking the displacements and tilts of the inner and outer raceway geometric centres, is obtained as the slope of the force versus deflection curve at the bearing's operating displacements. The stiffness terms are obtained from detailed bearing models which include the contacts of the
13
rolling elements with the raceways. The non-linear effects of internal clearance, preload and centrifugal effects in high-speed bearings are effectively modelled. The transmission system model built by this approach is very compact compared to conventional finite element models. The modelling time is significantly reduced and many possible modelling errors, which may inevitably happen in a conventional finite element approach, can be avoided. Planetary Transmission Error Prediction The model is first built in the RomaxDesigner software - for a planetary hub reduction unit such as this, this typically takes less than one day (Fig. 2). The model contains all of the information needed for the analysis, including bearing details, clearances, shaft dimensions, flexibility of housings/ring gears/planet carriers, and tooth micro-geometry details.
Fig. 2: A planetary hub reduction unit built on Romax Designer software A full system quasi-static analysis is then performed at each rotational position of the planetary unit. This analysis includes the effects of: •
Time-varying misalignment due to shaft, bearing and housing deflections.
•
Load (torque) sharing between planets. A calculation of how the torque is shared between the planets is important, this will also change with time and is dependent on many factors including the backlash of the individual gear mesh (perhaps due to manufacturing errors), and the stiffness of the gear mesh.
•
Relative phasing of planetary gear meshes, including the phasing between the various sun-planet meshes, phasing between the various ring-planet meshes, and phasing between the ring-planet and sun-planet meshes of a given planet.
It is important to note that the analyses are solved simultaneously. For example, it is not possible to solve the shaft-bearing system to predict the mesh misalignment, then use this misalignment to predict the transmission error at the gear mesh. This is because the details of the tooth contact are not only influenced by the misalignment, but the misalignment is influenced by the tooth contact.
14
The effective transmission error is then the relative rotational position of the input to the system (in this case, the sun shaft) and the output of the system (the planet carrier), as the system rotates. The input parameters of interest in the model were: Gear micro geometry: •
Sun gear lead crown
•
Sun gear lead slope
•
Planet gear lead crown
•
Planet gear lead slope
Planet spacing: •
Rotational position of planet gear one and three
Bearing Clearances: •
Radial internal clearance of needle roller bearings under planet gears
The output result of interest was the first harmonic of the effective transmission error trace, that is, the magnitude of the rotational displacement difference at the tooth meshing frequency. This analysis typically takes approximately five minutes. Calculation of Approximation Models To produce the approximation models, the "exact solution" (i.e. the RomaxDesigner analysis) has to be evaluated for a range of input parameters to produce a "training set" of data. The sampling of the design space to produce the training set of data can be performed by a number of methods. In this case, 115 design points were manually selected. The range of modifications covered is shown below in Table 1.
The design data points were defined in Microsoft Excel and then imported into RomaxDesigner for automatic batch running analysis. To evaluate the 125 design point training set took approximately 10 hours, and the results exported as a text file. The training set data was then imported into Matlab's Model Base Calibration toolbox to calculate the three approximation models. Each of these were each calculated in less than 3 minutes. The polynomial model was 3rd order with 2 levels of interaction, the radial basis function model was multi-quadratic and the neural network model had 2 hidden layers, with 10 neurons in layer 1 and 5 in layer 2. To evaluate the accuracy of the approximation models, a validation set of 20 design points (all different to the training set) was evaluated in RomaxDesigner and also in the three approximation models. Each evaluation in RomaxDesigner took approximately five minutes, each evaluation using an approximation method took less than 1 second. RESULTS The calculated results for the validation points are shown below for the "exact solution" calculated in RomaxDesigner and for each of the approximation methods. The mean and standard deviation of the absolute values of the errors for each of the approximation methods are shown in Table 3 below.
15
DISCUSSION From the results obtained from the analysis, it can be seen that the prediction levels portray an excellent level of prediction accuracy of less than 1% of error for the neural network model. This is significantly better than the accuracy of both the polynomial cubic expansion and the radial basis function models. The total time to generate this model is approximately ten hours to generate the training set of data, followed by less than 5 minutes to produce the neural network model. Each evaluation of the model then takes less than 0.5 s. Further work is needed to investigate the accuracy of the model over the whole design space, as it is important that there are not areas where there is large divergence from the correct data. This is a possibility, particularly at the extremities of the design space of the training set data. If this was the case, it may be prudent to increase the range of the input parameters used in the training set data, to cover a larger design space than will be evaluated using the approximation model. Refinement of the approximation model settings would also be possible, and may give even more improvement in the accuracy of the model. Assuming that the model fits the data well over the entire design space, the approximation model can then be used for optimisation and design sensitivity studies. It is estimated that the time to perform an optimisation will be reduced by at least 95% by using the approximation model, compared to using the complete RomaxDesigner analysis (not including the overhead of producing the training set of data - however, this is something that can be completed overnight with no user intervention). This reduction in run-time will be of great benefit to the user. It will enable the effects of more design parameters to be investigated, the effects of tolerances to be studied in more detail and ultimately lead to a better understanding of the overall behaviour of the system. Further work is needed to investigate the best method of selecting the training set design points. This is likely to become more critical when an analysis that takes significantly longer than the planetary TE analysis (5 minutes) is approximated, as fewer training set design points will be able to be analysed in a given time, or when more design variables are included.
CONCLUSIONS This paper has described an investigation into a number of approximation methods applied to a non-linear analytical model of a truck planetary hub reduction unit. The proprietary software package, RomaxDesigner has been described and the hub reduction unit modelled. The effective transmission error of the planetary set was then calculated using the software for a range of design variants to generate a set of "training data". Three approximation models were then fitted to this "training data" and the accuracy of the data, and the accuracy of each model assessed. The Neural Network model was significantly more accurate (around 1% error) than the Polynomial Cubic and the Radial Basis Functions models (4-6% error). More work is required to further validate the approximation models, but this initial investigation suggests that the Neural Network approximation method will be a useful tool for software packages such as RomaxDesigner.
16
USEFUL REFERENCES NISTISEMATECH e-Handbook of Statistical Methods :Engineering statistic (online) available from http://www.itl.nist.gov/div898Ihandbook/index.htm Practical experimental designs for engineers and scientists 3rd edition. William J Diamond Artificial neural network technology- introduction and purpose available from http://www.dacs.dtic.mil/techs/neural/neuraI1.html Crash introduction to artificial neural network by Ivan Galkin, U. MASS Lowell available from http://ulcar.uml.edu/~iag/CS/lntro-to-ANN.html International symposium and workshop advance training workshop Design exploration practical tips and trick. DR Therese Polito NAFEMS 2005: Modeling and analysis of a modem automatic transmission Gearbox Y Song. A Tylee-Birdshall, E Roeloffzen 'A software tool for Prediction of Planetary Gear Transmission Error', Dr Jamie Pears, Andrew Smith, Dr Sarah Curtis.
Table 1: Generation of the training data Parameter for modification
Range of modification
Sun gear Lead crown
±20um
Sun gear lead slope
±20um
Planet gear lead crown
±20 urn
Planet gear lead slope
±20um
Rotational position of planet gear one and three
± 0.5 degree
Radial Internal Clearance of needle roller bearings under planet gears
± 100 urn
17
Table 2: Observation value of transmission error and prediction model and percentage of error TE 1st Harmonic Prediction Validation point number
1 2 3 4 5 6 7 8 9 10
11 12 13 14 15 16 17 18 19 20
Value
%error
Approximation Radial Basis Function Value %error
Value
% error
0.83 0.58 0.82 0.75 0.85 0.56 0.97 1.02 0.6
0.8149 0.6602 0.8404 0.7716 0.892 0.6228 0.9488 0.9485 0.6086
1.82 -13.83 -2.49 -2.88 -4.94 -11.21 2.19 7.01 -1.43
0.827 0.6101 0.8473 0.7467 0.8541 0.5796 0.8868 0.9113 0.5657
0.36 -5.19 -3.33 0.44 -0.48 -3.5 8.58 10.66 5.72
0.8509 0.5913 0.8201 0.7589 0.855 0.5715 0.9735 1.015 0.6113
-2.52 -1.95 -0.01 -1.19 -0.59 -2.05 -0.36 0.49 -1.13
0.96 0.7 0.64 0.77 0.52 0.74 0.81 0.78 0.74 1.02
0.9262 0.7461 0.6448 0.8037 0.6039 0.8028 0.8559 0.8329 0.7035 0.967
3.52 -6.59 -0.75 -4.38 -16.13 -8.47 -5.67 -6.78 4.93 5.2
0.9249 0.7243 0.6507 0.7906 0.4843 0.7883 0.8361 0.7792 0.7361 0.932
3.66 -3.47 -1.67 -3.38 6.86 -6.52 3.22 0.1 0.53 8.63
0.9711 0.6971 0.634 0.7721 0.5364 0.7297 0.8168 0.7808 0.7398 1.009
-1.16 0.41 0.94 -0.27 -3.15 1.39 -0.84 -0.1 0.02 1.08
0.97
0.904
6.8
0.8792
9.36
0.9654
0.47
Calculation RomaxDesigner
Polynomial Cubic
Table 3: Measures of error in approximations Model Poly-cubic
RBF Neural net
Mean Absolute Error 5.9% 4.3% 1.0%
18
Std Dev Absolute Error 4.1% 3.3% 0.9%
Neural Network
GEAR TEETH IMPACTS IN HYDRODYNAMIC CONJUNCTIONS: IDLE RATTLE
o. Tangasawi l , S. Theodossiades l , H. Rahnejat l and P. Kelly 1 Wolfson School ofMechanical & Manufacturing Engineering, Loughborough University, Loughborough, UK 2 Powertrain Engineering, Ford Werke AG, Cologne, Germany ABSTRACT In the last decade, idle rattle in automotive transmissions has become a major concern in powertrain engineering. Palliative methods such as the Dual Mass Flywheel (DMF) have produced encouraging results in attenuating gear rattle with high cost implications. Fundamental and economic solutions can only source from root cause investigations. This paper introduces a new approach to study gear rattle from a tribo-impact perspective; gear impacts causing rattle are treated as lubricated conjunctions rather than following the conventional assumption of dry contacts. It was found that depending on the forcing conditions and the geometric/viscous characteristics of the system, various pairs of gear teeth could be excited, exhibiting a different system response. NOTATION C
Clearance between gear and shaft
I j (i=1.2.3.4.5.6) Moment of inertia of the i 'h gear I prey Moment of inertia of reverse pinion I wrev
Moment of inertia of reverse wheel
L
Length of contact line
II rc
Length of contact line in conformal contact between gear and shaft Radial distance of pinion and wheel contact point
req
The equivalent curvature radius of two teeth surfaces at their contact point
ros
Radius of output shaft Rolling velocity of gear teeth during meshing action
u Us
v an
f3
Sliding velocity of meshing gear tooth surfaces Tangential velocity between idle gear and supporting shaft Normal pressure angle
170
Pitch circle helix angle Dynamic viscosity
({Jj(i=2 .. 6)
Angular displacement of 2nd , 3"\ 41h, 51h and 6th idle wheels
't'1,prev
m
Angular displacement of the 1sl speed gear and reverse pinion
({Jwrev
Angular displacement of the reverse speed gear
(jJ,n(t)
Angular displacement of the input shaft
W Fj
Lubricant reaction Hydrodynamic load on the tooth flank
rw
Contact radii of gear wheels
rpm
Contact radius for the reverse speed pinion 19
TjW
Flank friction torque
I;ractw
Tractive torque between the output shaft and idle gear wheel Lubricant film thickness Petroff friction force
h F Subscripts P
prev w
wrev
Pinion Pinion of reverse gear Wheel Wheel of reverse gear
INTRODUCTION Idle gear rattle is associated with the characteristic noise that unselected impacting gears radiate to the environment (1). It is induced by engine order vibration in the presence of backlash in meshing pairs, particularly troublesome in vehicles with diesel engines (2). The system energy manifests itself in torsional vibrations at harmonics of the engine speed, a part of which is transmitted through the bearing mounts and transmission shafts to the gearbox housing and radiated to the environment as noise (2, 3). Transmission rattle has come to the forefront of noise and vibration issues for the automotive industry due to the attenuation of engine noise during the last decades (3). PalIiative measures have been extensively used to reduce the undesired effects of rattle. The increment of the engine idling speed (4), the use of dual mass flywheel system (5) and the tuning of the clutch pre-damper and hysteresis characteristics (4) are typical palliatives. Moreover, increasing drag torque has been found to be a low-cost option (6), which also increases the frictional losses and the transmission operating temperature. The use of backlash eliminators has the drawbacks of increasing friction losses and generating unacceptable heat (7). A number of investigations on gear rattle have been reported in literature, where the driveline has been modelIed as a lumped mass parameter system with hysteresis. The gear backlash is usualIy included using the dead space function (6) while the clutch stiffness and hysteresis have been modelIed as piece-wise linear functions (6, 8). Drag torque is usualIy added proportionalIy to the rotational speed (6) or temperature dependent (7). The gear tooth stiffness has been included as constant (6) or using timevarying contact stiffness coefficients (9, 10). GeneralIy, dry gear teeth impacts have been considered in rattle investigations. The effect of lubricant has not been included in fulI transmission models to keep the problem simple. Nevertheless, a lubricated contact model that assumes the presence of a hydrodynamic film in simplified non-varying gear teeth contacts was proposed by (11) for lightly loaded idle rattle conditions. Thus, a hydrodynamic rather than an elastic force is applied between the gear surfaces, which depends on the lubricant entrainment speed, the contact geometry, and the approach velocity between the teeth. This paper presents a numerical investigation of a front wheel drive six-speed manual transmission system under idle rattle conditions. The dynamic model includes the kinematics of teeth contact and their geometrical characteristics variation, hydrodynamic lubricant film formation and the effect of lubricant rheology. The numerical results are compared to experimental measurements from a vehicle and the main frequencies of the system response are identified, revealing the validity of the proposed methodology. 20
~
~
an
RaY.
~~nft.D"l.R""".l.~"~I~~
1
~\/ \\\
F; ~ 3d
\ \\F \
..:;/
~'i
-'/F; 5h
1111
rev
~~
-_
1st~stat.)..i)"-.D..l .....1/ F'z '"
'l
'"
\\\\
0dl
4h Figure 1: Front wheel drive transmission layout. ANALYSIS
The layout of the front wheel drive gearbox examined is shown in figure 1. An input shaft transmits the engine torque to the two output shafts and from there to the front wheels via the differential unit. The angular displacement o4----I
20
1-~----+_---------I~~ill1
Poor film formation
0.9
0.09
0.095
0.1
0.105
0.11
Friction coefficient in Tribometer
10
15
20 Load(N)
25
30
35
Fig.7 Relationship between torque capacity ani fiiction ooefIicient Fig.8 Fihn fonnatioo wi1h anti-wear adlitives 53 Instantaneous lubricant film fonnation characteristics Measurements of instantaneous film formation at a step load were carried out by collecting the data at a rate of! OOOHz. Fig.9 (a) shows instantaneous friction cbmacteristics withAWI, primaIy type ZnD1P The moment the applied load was increased fiom 12 to 13N, at 200msec elapsed, the contact resistance instantaneously decreased despite keeping good film formation at a steady load of 12N. The resistance reached the minimmn level at lOOOmsec and the values at ttuning points dropped to 0, which means disappearance of lubricant films at the contact points where slipping tangential velocity is O. The resistance started to be regained at 2000msec and then it grndually increased with the time, finally reaching almost 100010 at 5500msec. It took a slipping distance of605mm (22Hz x 5mmx 5.5sec) for AWl to completely be refonn boundruy lubricant film. Film fonnation fiom AW2 with secondruy ZnDTP is shown in Fig.9 (b). AW2 demonstrated stable film formation the moment the load was instantaneously increased at 200msec. The reason for this difference in instantaneous film formation with ZnDTPs type could be based on the difference in decomposition temperature of each additive. Decomposition temperatures of primaIy and secondruy type are detennined at 235 and 207 °C, respectively. The vcry moment the applied load was increased from 12 to 13N, the contact width estimated by Hetzian elastic equation was widened by 3 IW in diameter. In case
47
ofAWl, prirnruy type ZnDTP seemed not to chemically react on the newly widened contact region at that moment due to higher decomposition tempernture. 5.4 Comparison of friction coefficient with each anti-wear additive As proposed in a previous study [8], higher torque capacity fluids potentially have an advantage in improving overall transmission efficiency tlrrough the reduction of oil pump load. Therefore, the peIfonnance of Belt CVT lubricants should be focused on giving higher torque capacity. The choice of anti-wear additive giving higher friction coefficient between metal-metal interfaces is a key oil fonnuJation technology forthe improvement oftorque capacity. Fig.lO shows a comparison of averaged friction coefficient tlrroughout the tests with each anti-wear additive. The friction coefficient ofAW3, myl type ZnDTPwas the highest ofall tested samples. In addition, the standanl deviation of measured friction coefficients was f01.111d to be within ±O.OO4. The difference in friction between AW3 and other test oils except for AW4 can be regarded as significant There is little difference between AWl, 2, and 5. Fig.ll shows comparison of composite roughness on post test contacting surfaces. The post surface roughness with AW3 was significantly higher than those of other samples. Moreover, the rougher surface tends to produce higher friction coefficient From these results, friction coefficient was related to ll1OIphology of1he worn surface influenced by the lubricants film formation process. There is little difference in friction coefficient under conditions that lubricant films from anti-wear additive are fanned completely. 0.12 I Standard deviation J3N , _ ,. r :_ _ _ _ _ _ 12N __ =4~ _ .~
rrr:TI!IOOnM j t 'Iri M h rI 11 I
~::.
0.11
~ ~
g
~
S
~ ~
.::
~
!
j=:~G]
0.10
I--
i+- --
I
T --
I--
+
TI ..... C""' ___ )
;GD .. u
0.09 AWl
~-
AW2
AW3
AW4
AWS
Fig.! 0 Comparison ofaveraged fiiction coefficient
!:~ ~ wOh.,._",,: ~ ~_ u
-:000
_~oQ
__ 0 0
.~DO
• •00
I
I'
---Ini'ial
_400
"T'"I ...... C ..... _ _ _ )
E
StarlClard deviation
::t.
(a)AWI:ZnDTP(Primary alkyl)
- ~ --- F ------ -- --- -- -=': I--
AWl
(b)AW2:ZnDTP(Sccondary alkyl)
Fig.9 Instantaneous film formation process at step load
--
AW2
I--
--
AW3
AW4
AWS
Fig.!1 Comparison ofroughness on post -surface with anti-wear adlitives
(Strdre=5rrnn, Frequency=22Hz)
48
6 Conclusions Metal-metal tnbological properties on fue transmittable torque capacity of a metal V-belt type continuously variable transmission (B-CVI) were experimentally investigated using a ball on plate type tnbometer (plint 1E77 ), which enables film formation to be monitored during rubbing tests. In addition, fue effects ofanti-wear additive used in B-CVT fluids on bOlmdary film formation were examined.
(I) The contact region between fue belt and pulley in fue CVT was found to be in boundary lubrication regime. It is vital for higher torque capacity to give higher fiction coefficient and to demonstrate good lubricants film formation on the contact regions. The tnbometer used in 1his study was proved to be a relevant test method to evaluate totqUe capacity ofthe CVT. (2) There was a significant difference in instantaneous films formation between primary type and secondary type ZnDTP at the moment of increasing step load. In the case of aryl ZnDTP, 1he films started to fann at a load of ISN and fuen demonstrated complete film fonnation above 2SN. These phenomena were caused by fue variation of decomposition temperattrre of different ZnDTPs. The films produced by phosphoric ester stabilized during rubbing tests more 1han ZnDTPs. (3) Aryl ZnDTP gave higher fiction coefficient 1han ofuer samples. The rougher worn surfuce tends to produce higher fiction Friction coefficient was related to mmphology offue worn surfuce, influenced by fue lubricant film formation process. REFERENCES
1 http:wwwJatco.coJplGANOINAIGAll-l1M 2 Mitsui,H. Trends and requirements of fluids for metal pushing belt type CVTs. Journal of Japanese society oftnbologists,2000,45-6,13-18. 3 Ishikawa,T.,Murakami,Y., Yautibara,R. and Sano,A. The effect of belt drive CVT fluid on fue fiction coefficient between metal components. SAE PapeI972921,1997. 4 Spikes, H.A. History ofZDDP Tnbology letter, 2004,17, 46S. 5 Wada,R and Iwanami,L Xanes study on boundary lubrication films generated from belt-drive CVT fluids. Synopses ofIntemational Tnbology Conference,Kobe,200S,319. 6 Micklem, JD., Longmore,D.K. and Burrows,C.R. Modelling of fue steel pushing V-belt continuously variable 1rnnsmission. Pro.Inst.MechEngrs, 1994,208,13-27. 7 Ide,T. Metal V-belt used for continuously variable transmission for passenger car. Journal of SAE of Japan, 2000,544,4-9. 8 Narita.K., and Priest, M Metal-metal fiction characteristics on fue transmission efficiency of a metal V-Belt type continuously variable transmission. Submitted to Journal ofFngineering Tnbology, 200S 9 Narita,K., Abe,A., Desbimam,J., and Hara,S. Improvement of torque capacity of metal V-belt type CVT fluids. SAE Paper 2003-01-1997,2003. 10 Furey,MJ. Metallic contact and fiction between sliding surfuces. AS.L.E Trans, 1961,4-11. 11 Stolarski, T.A. Tribology in Machine Design BatteJworth-Heinemann, 1990, 128-129. 12 Katsuya, A., Sato,T. and Kurimoto,K. Tnbology in Analysis of behaviour of CVT belt Proceedings ofSAE ofJapan Conference, I989-S, 891,13-18. 13 Takahara, R and Abo, K Heat generation analysis of a metal V-belt for CVTs. Journal ofSAE of Japan, 2000, 54-4,16-20.
49
Design Consideration and Potential of the Milner CVT
(1)
Adrian Hunt(l), Sam Akehurst(l), Stuart Schaat C> ~
=. co 0
~ E :::>
In
co 0
t)
a;
:::> LL
6.5 I)
5;5 5 4.5 4 3.5 3 2.5 2 1,5 1 0,5 0
D
Reference Vehicle Manual Transmission Simulation Reference Vehicle Automatic Transmission Simulation Prototypical Vehicle Autarc Hybrid Simulation Prototypical Vehicle Autarc Hybrid In-vehicle Testing TFM Electric Motor
Figure 1 Fuel saving potential of the Autarc Hybrid in comparison to the reference vehicle (NEDC) However the figure shows also that the theoretically achievable fuel saving potential cannot be fully realized. This is due to the increased weight of the vehicle, lack of complete recuperation of braking energy and necessary compromises concerning the combustion engine operation (for drivability, long starting procedures). Small parasitic effects on some subsystems led to a less than optimal result in regards to fuel consumption [3]. Within the succeeding project "Transferbereich 38 - Optimized Drivetrain" the improvement potentials from the SFB were identified and are to be utilized. A transfer of the technology with its results into industry is to be realized in collaboration with the GM Powertrain Europe, ZF Sachs AG, ZF Friedrichshafen AG and EPCOS AG. Another important requirement for this technology to be transferable to the industry is to keep the overall costs comparable to those of current production vehicles. CONCEPT OF THE CVT-HYBRID POWERTRAIN Tests with the "Autarc Hybrid" (SFB 365) on the dynamometer and in the prototype vehicle showed that surplus weight and high electric energy consumption for hydraulics and auxiliary components nullified remarkable shares of the saving potential of hybrid concepts. Furthermore the complexity of the F-transmission with its extensive hydraulic system was criticized by the automotive industry. Starting from these insights and the requirements, the concept of the Autarc Hybrid was conceived. Research on the Autarc Hybrid has shown that the maximum overdrive transmission ratio of the F-transmission within drive operation and within norm cycles is only used rarely. Due to this the positive effects concerning fuel consumption are relatively small. By abandoning part of the transmission ratio range the complexity of the transmission can be noticeably reduced. The iJi -transmission is the result of this simplification. This transmission works with one shaft less than the i2-transmission, furthermore the new transmission can do with 2 clutches fewer than its predecessor (see Figure 2). The shifting procedure is carried out by just 2 synchronized clutches. This not only means
128
less manufacturing expenses and part costs, it also reduces the complexity of the hydraulic system. In addition to the reduction of drag and friction torques by having fewer clutches, it increases the mechanical efficiency of the transmission. Also the amount of oil leakage and therefore the hydraulic losses is reduced to a minimum. Overall it means reduced costs and weight, better driving performance and less fuel consumption. i~i-transmission
P-transmission
l2
K1
Figure 2 Comparison of concepts: il B i~i transmissions
Another important starting point in this concept is to go without a mlmmum electrical range. The Autarc Hybrid was designed to have an electrical range of 30 kIn. In the meantime, a noticeably improvement in emissions reduction has been developed, which has eased the emission problems in congested areas. Based on these boundary conditions, the heavy battery can be replaced by an ultra capacitor stack. An accumulator, which is slightly larger dimensionally, is on 12V-basis and serves as a charger for the ultracaps if they have a low charge. This reduces the surplus weight of the vehicle from 170 to 25 kg. Besides this noticeable weight reduction, which has an advantageous effect on fuel consumption and driving performance, the costs are also significantly lower as well as the increase in storage efficiency. Furthermore there is no need for a complex cooling mechanism and battery management including auxiliary electrical consumption for the controller and fan because the efficiency of the ultra cap stack is more efficient than a conventional battery. Practical tests with the Autarc Hybrid have shown that the starting procedure of the combustion engine with a conventional starter has less than optimal. By the implementation of a kick start principle which uses the inertia of the electric motor and the transmission for acceleration of the combustion engine by the principle of a fast shifting procedure the starter can be abandoned. An optimized starting procedure concerning fuel and electric energy consumption is to be introduced (see Figure 2). The optimized CVT-Hybrid-Driveline
The elementary conception of the Autarc Hybrid as a parallel-hybrid is retained. The driveline combines again a small efficient electric motor with a series production combustion engine (see Figure 3). 129
D motor
Figure 3 The CVT-driveline The core piece of the new hybrid vehicle is the continuously variable iJi transmission which is based on a CVT chain converter such as the one in the i2 transmission. It uses the ratio range of the chain converter twice through a shifting mechanism. Figure 4 shows schematically the configuration of the iJi transmission in mode VI (low velocity mode) and V2 (high velocity mode). In contrast to the F transmission the electric motor and the combustion engine are not placed on one shaft but instead located on two opposite shafts of the CVT (see Figure 4: WI, W2). The combustion engine is engaged by a clutch LK on shaft WI. In mode VI the clutch KI is closed whereby K2 is opened. In this mode the electric motor powers W2 and through the CVT WI while the transmission can be adjusted continuously variable. At low driving speed where an optimal pull-away and recuperation can be realized whereas the combustion engine is not in operation in this mode normally. V2
VI
LK
LK
V'Mo~tr ~I ~W1 ;_13
~r--+-...:;W:::;3_---0;1 E-Motor
Figure 4 Structure and principle of the
iJi -transmission
Depending on the power demand of the driver, the combustion engine is engaged and started at driving speeds between 7 and 20 kmIh. This shift from mode VI to V2 occurs without torque interruption. In mode V2 (see Figure 4, right) the clutch K2 is closed and Kl is open. The electric motor is then coupled directly to the output over gear i23 . The combustion engine is at that point able to operate over WI and the CVT on W2 while the transmission can be adjusted continuously variable. While in mode V2 it is possible to operate the
130
combustion engine with a high efficiency. The electric motor can also, if necessary, work as a generator and charge ultracaps and battery or supply the on-board electrical system. Also it can be used to support the combustion engine by boosting. As the storage capacity of the ultracaps is limited, they are mainly charged during recuperation phases. The starting procedure of the combustion engine is induced by engaging the multiple disc clutch LK and by that it is connected to the turning shaft WI. To assure that this procedure is imperceptible for the driver a traction force loss has to be avoided. Therefore it is necessary to provide additional power from the drivetrain which is realized by a fast adjustment of the CVT so that the flywheel mass of electric motor and shaft W2 is decelerated. As far as possible the electric motor continues to power. By this CVT-supported starting procedure it is possible to realize very short starting durations. The concept of the electrical system is shown in Figure 5.
12V battery
Figure 5 The electric system For safety reasons the size of the ultra cap stack is designed to make at least 3 pullaway and starting procedures possible without having to recharge them. The ultracaps have to be then recharged by the battery. The capacity of the ultracaps has to be sufficient for a full energy recuperation when breaking from 50 to 0 kmIh. To be able to provide an electric start even after a long standing time of the vehicle, it is necessary to charge the ultracaps over a DC -DC conversion from the 12 volt battery (see Figure 5). The battery also feeds the onboard electrical system as well as the auxiliary components which are necessary for the controllers, pumps etc. When the combustion engine is running the electric motor can be used as a generator. The controller layout used in the SFB 365 is enhanced with the aim to reduce electrical power consumption as well as costs. The controller layout is described in Figure 6. Possibilities to combine functions of each controller subsystem are being developed. The operating strategy which was developed and verified for the Autarc Hybrid is being modified, customized and extended for the new drive train. Especially the limited ultracaps storage capacity and the different controllability of combustion engine and electric motor in the modes VI and V2 must to receive particular attention.
131
r-------------------- --------------------_---------___ i
.~~~
I
main controlleF-
i: :
I .-----~----~
I i
electric motor controller
:______ ,
" "- ... .... -
! transmission controller
,.'---~--
measurement controller
!
i
__________________________l
\
~--~ motor
Figure 6 Controller structure for the CVT-Hybrid driveline The prototype vehicle is based on a current Opel Vectra. The following table shows the main data of the CVT-Hybrid driveline.
Table 1 Benchmark figures of the technical data of the CVT-Hybrid driveline Vehicle Basis Vehicle Curb weight of production vehicle Maximum permissible weight
Opel Vectra 1556 kg 1995 kg
Engine Engine Marking Maximum torque Maximum power
Diesel direct injection Z19DT 280 Nm /2000 - 2750 min-' 88 kW /3500 - 4000 min-'
iJi Transimission Ratio Range of CVT
iJi
Ratio range of -transmission Overdrive Start transmission
6 14.3 1.83 26.3
Electric Motor Electric Motor Maximum power Nominal speed Operational voltage
Permanent magnet synchronous machine 14kW 1500 min-' 26 ... 52 V
Energy storage Storage type Capacity
Ultra capacitors 225 Farad - usable 220 kJ
132
THE OPERATING STRATEGY The development of an intelligent operating strategy for this hybrid concept is crucial for ensuring the functionality of the power train. This will ensure maximizing fuel saving potential in any driving situation and system state.
Starting procedure The basic principle concerning the starting procedure has been described in the operating strategy. In principle the vehicle pull-away by the electric motor if system state and boundary conditions allow it. In all other cases, special strategies come into operation (i.e. low ultra cap charge, start on a hill, etc.). At the beginning the power train is in start-up position, i.e. the transmission is in mode VI and the CVT provides the maximum ratio for the electric motor. Depending on the power demand of the driver the electric motor provides the torque for acceleration of the vehicle. This procedure is described in Figure 7 by highlighting the power flow through the drive train. LK
Figure 7 Electromotive start in VI Clutch KI is engaged and the electric motor is powering over CVT and shafts WI and W3. The gear ratio ofthe CVT is kept constant until shaft W2 achieves a sufficient speed. The kinetic energy of the rotor, shaft and variator discs has to be high enough to compensate the drag toque of the combustion engine when it is coupled and the fast adjustment of the CVT is started by which the flywheel masses are decelerated is executed. By this mechanism there is no traction force loss at the output and the combustion engine is started unnoticed to the driver (see Figure 8).
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LK
Figure 8 Accelerating the combustion engine by quick ratio change of the CVT
As soon as the combustion engine has reached a minimum speed it is started and it begins to power the drive train. After the CVT has adjusted the UD ratio by which synchronization for a shift into mode V2 is established clutch K2 closes while Kl opens simultaneously; the ratio of gears il3 and b3 is designed that way that there is no differential speed in both clutches Kl and K2 for UD ratio of the CVT (see Figure 9). In mode V2 the whole ratio range of the CVT is available again for the combustion engine. LK
Figure 9 Drive by combustion engine in V2 Driving with constant speed in V2
In mode V2 the optimal operation point of the drive train depending on the velocity of the vehicle is adjusted by the CVT. The main aim is to operate the combustion engine and the drivetrain at a point at which the overall efficiency is the highest. Accelerating in V2
Depending on the power demand of the driver, speed and torque of the combustion engine are adjusted by the CVT. This operation is carried out so that the operation point stays at the optimal point which is minimum current fuel consumption. For example if 134
the driver demands maximum power, the CVT adjusts the speed of the combustion engine into this point. When the vehicle starts accelerating the CVT adjusts its ratio continuously so that the combustion engine stays in this point until the driver stops his power demand. In the case of kick-down the electric motor can boost additionally. The drive train is then able to provide a maximum power of Pcombustion engine + P electric motor = 102 kW.
Decelerating in V2 When changing from drive mode to coast mode by releasing the throttle the combustion engine is disengaged and turned off to save fuel. The electric motor starts generating a drag torque simulating the drag of the combustion engine. The generated energy is saved by the ultracaps. If the driver starts braking additional recuperation power from the electric motor is generated up to a maximum while the mechanical brakes also come into operation if necessary. To drag along the combustion engine without shock, if the driver wants to start accelerating again, the electric motor switches into drive mode again. If the velocity of the vehicle falls below 10 kmlh, the transmission shifts back into mode VI. If the ultracaps are not fully charged, the recuperation continues in VI.
Pull-away on a hill The pull-away.strategy described before is not applicable for a starting procedure on a hill if the slope exceeds a certain limit. The main reason is that in the given configuration the power ofthe electric motor is not high enough to start a pull-away and drag along the combustion engine simultaneously. For an uphill gradient higher than 12 % another pull-away strategy is applied although theoretically an uphill gradient of up to 20 % can be achieved with the strategy explained above. This alternative strategy is combustion engine-powered pull-away. For this the combustion engine is dragged along by the electric motor while the drive train is open, i.e. the clutches Kl and K2 are uncoupled (see Figure 10). LK
W3 K1
~~Ht--~I=-i:8J'-::
Hir Differential
Figure 10 Start ofthe combustion engine within the open drive train As soon as the combustion engine is started clutch LK is disengaged and Kl is closed (mode VI). By a controlled engagement of LK the vehicle is accelerated. To
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keep the thermal load of the dutch low the electric motor supports this acceleration procedure (see Figure 11). LK
Figure 11 Start strategy uphill By the given configuration of the drive train a slope of up to 30% at fully loaded vehicle can be accomplished. Depending on the equipment the uphill grade can be detected by a sensor. Alternatively the driver can set the uphill mode manually. Strategy for uncharged ultracaps If through disadvantageous conditions, for example stop-and-go traffic, the charge of the ultracaps falls below a limit and a standard pull-away is not possible, the remaining energy in the ultracaps is used to start the combustion engine while the drive train is open, i.e. the clutches K1 and K2 are disengaged (see Figure 10). As soon as the combustion engine is started the electric motor starts working as a generator and charges the ultracaps. RESULTS FROM SIMULATION A complete simulation model of the drive train was built up within the simulation software ITI-Sim. This made it possible to research the behaviour of the drive train in all simulated situations, to optimize the operating strategy within the conception stage and to support construction and design. Under the given boundary conditions a pull-away on a plane ground with a power demand of 100 % shows the following behaviour of the drivetrain (see Figure 12).
136
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3000
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400
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4
Figure 12 Start 100% throttle Figure 12 shows output torque (T), vehicle velocity (v), speed of the combustion engine (n) and ratio of CVT (i). Additionally the input torque of both engines is shown in the lower diagram. As can be derived out of the diagrams the electric motor powers the drive train at pull-away. After t "'" 1.4 s the electric motor reaches its field weakening range wherefore its torque decreases along the power hyperbola. At t "'" 1.8 s the combustion engine is getting coupled in and dragged along. Also the quick adjustment of the CVT is lead in to get an additional torque from the deceleration of the electric motor and shaft W2 (JdJ). At t "'" 2.2 s the combustion engine is started and powers the drive train while the electric motor turns off. For description of an uphill pull-away the following diagram shows the behaviour of the drive train in the extreme case of having an uphill gradient of 30% and fully loaded (see Figure 12). At the beginning the combustion engine is already on and starts powering the drive train immediately. The electric motor supports the combustion engine as described above. Figure 13 displays the speed of the combustion engine in comparison to the speed of shaft WI as well as the velocity of the vehicle (v).
137
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Figure 13 Hill start (uphill grade 30%)
After t "" 2.7 s the speed of the combustion engine and the speed of shaft WI are equal and the clutch is closed. The thermal load of the clutch until this point adds up to 1.4 J/mm2 and is unproblematic even under these extreme conditions. After 2.8 s the acceleration of the vehicle declines. The reason is that after the clutch LK closes the electric motor boost stops. This is necessary to keep enough energy in the ultracaps for eventually upcoming new starts. CONCLUSION
The described concept of the "CVT-Hybrid-Driveline" is a further development of the hybrid drivetrain (i2 transmission) from the so called "Sonderforschungsbereich 365" under consideration of changed requirements. Simplification of the transmission was a basic requirement for a transfer of the project's results into industry. Simulations show that this simplification and its consequences on the transmission's ratio range does not mean higher fuel consumption under operating conditions. Reduction of vehicle weight through substitution of a heavy battery by ultracaps even increases the fuel saving potential. First results from simulation show fuel consumption of the current concept of 5.52 111 OOkm within NEDC. This also means the fuel saving potential compared to the adequate series-production vehicle which is equipped with a conventional manual transmission adds up to over 10%. It is shown that the very wide ratio range of the Autarc Hybrid transmission in practice has no major effect on fuel consumption as overdrive operation points are rare. Another advantage of the new concept is the optimized operation strategy and controller layout. Results from the simulation also prove full functionality even under extreme conditions as well as the dynamics of the CVT-Hybrid-Driveline. LITERATURE 1 D Schroder, 'Hybrid und Diesel favorisiert', Automobilwoche 7, 2004, p.15. 2 B R Hohn and B Pinnekamp, 'The Autarc Hybrid: A Universal Power Train Concept for Passenger Cars', International Gearing Conference, Newcastle Upon Tyne, England, 7.-9. September1994.
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3 B R H6hn, H Pflaum, P Guttenberg, 'Experiences of the Autarc Hybrid Drive Line on Test Rig', EVS 18, Berlin, Germany, 20-24. October 2001, Proceedings, p. 217.
ACKNOWLEDGEMENT The authors would like to thank the DFG (Deutsche Forschungsgemeinschaft) as well as the participating companies EPCOS AG, GM Powertrain Europe, ZF Friedrichshafen AG and ZF SACHS AG for their financial and professional support.
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Power combining single regime transmissions for automotive vehicles Frank Moeller NexxtDrive Ltd (www.nexxtdrive.com)
INTRODUCTION
There is a high level of interest in hybrid transmission designs that combine inputs from an internal combustion engine and one or more electric motors, despite the fact that the high cost premium of current production units cannot be rationally justified by the relatively modest consumption improvements. But there are new transmission designs which can offer significant further improvements in fuel economy and emissions reduction, together with vehicle performance benefits, at a cost comparable to a conventional automatic transmission. The field of automotive vehicle main drive transmissions includes applications from 250 W to 1000 kW, to suit light electric vehicles, mopeds, scooters, motorcycles, cars, trucks, buses and off-highway vehicles. This paper discusses four types of 'Power Combining Technology' (PCT) which will be key enablers for the hybrid operation of such vehicles.
2
3 4
The 3 branch electric powersplit transmission directly mounted to the engine, as pioneered by Toyota; The 3 branch electric PCT with 1 motor/generator contained in each drive hub, the second motor/generator and a brake being coupled directly to the prime mover as proposed by NexxtDrive; The 3 branch electric PCT with 2 motor/generators contained in each drive hub of small 2, 3 and 4 wheelers as proposed by NexxtDrive; The engine-mounted efficient 4 branch electric PCT as proposed by NexxtDrive under the name of "DualDrive".
These transmissions are suitable for hybrid and non-hybrid vehicles. No clutches or couplings are required in the drive train and the integrated electrical machines can drive the vehicles purely electrically and can also act as starter motors and battery charging generators. They all are fully automatic, stepless and can make the vehicles considerably more efficient than any conventional drivetrains. The paper will classify the various applications, show detailed layouts and explain their function and features.
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1
POWER COMBINING TECHNOLOGIES
Power Combining Technologies (PCT) are transmission designs which make use of both a mechanical power source (usually from an internal combustion engine) and an electrical power source in combination with electric motor! generators. The drive systems can include electrical energy storage, as in the many 'hybrid' vehicle designs on the market or under development today, or the transmissions can be entirely selfcontained. Such transmissions are fully automatic, stepless and highly efficient compared with conventional vehicle drivetrains. They can eliminate the need for a variety of conventional transmission components including alternators, starter motors and clutches. Opportunities for PCT reach far beyond automotive primary powertrain applications, to include PTOs and supercharger drives, electric bicycles, locomotives, ships and wind turbines. The PCTs under discussion here make use of epicyclic gear trains to combine the inputs from engine and electric motors. The three branch epicyclic transmission developed by Toyota - the 'Powersplit' drive - is well known and will only be used for reference here. Three other drivetrain configurations will be discussed, however, each of which offers significant advantages in specific vehicle applications. 1.1
Efficiency
Continuously variable transmissions (CVTs) theoretically allow engines to operate at their most efficient speed for any given power output. Unfortunately the durability of mechanical CVTs is reduced because their systems rely on friction between two surfaces moving at slightly different speeds. PCT systems use efficient epicyclic gears to transmit their power and are combined with two motor ! generators. Generating electricity in one place and using it to power a nearby motor is relatively inefficient, around 80 percent compared with 98 percent for a typical epicyclic gear train, but the best PCT designs ensure that a low percentage of the total power is transferred via the electrical path. This results in much higher overall efficiencies. 2
SINGLE MOTOR HUB TRANSMISSION
The space within the hub of a vehicle is generally largely empty and it would be highly desirable if this space could be used to accommodate the power combining device of a hybrid vehicle. This would comprise a 3 branch epicyclic gearset with a sun gear, a set of planets on a carrier arm and an outer ring gear, along with a single reversible machine.
142
eltctriClllnpUl
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Figure 1 Hub with externally mounted motor / generator The machine in the hub could be a hydraulic motor, but is more likely to be an electric machine for ease of control and easy integration with electric-hybrid schemes. The machine might be mounted externally to the hub (figure I), or fully integrated within it. The system would be constructed so that the sun gear rotates with the input from the vehicle's engine, while the electric motor powers either the planet carrier or the ring gear, depending on the application, with the hub body connected to the other member. By altering the speed and power absorbed or output by the electric motor, the effective transmission ratio between the input shaft and the hub will be altered, giving full, independent control over both speed and torque at the vehicle wheel.
2.1
Vehicle weight implications
The hubs of a vehicle are basically unsprung. It is undesirable to increase the unsprung weight of a vehicle because this severely impairs the road handling characteristics and driveability of the vehicle. To minimise unsprung weight, the gearset can be designed so that the motor operates at high speed, allowing it to be small and light. Additionally, as the electric motor in the transmission is reversible and can also absorb power, the motor can serve as a brake, eliminating the need for a heavy separate mechanical brake in each wheel. Energy absorbed by the motors during braking can be fed to the vehicle's battery or storage capacitors, delivering fuel economy benefits through reuse to aid acceleration later. In emergency stop situations, however, it is likely that the electrical system's ability to absorb energy will be overwhelmed. By installing a single central mechanical brake, connected to the vehicle's driveshaft close to the engine, sufficient power for emergency braking can be delivered without adding unsprung weight (figure 2, figure 3). Distribution of this braking force can be controlled via inputs to the hub motors, allowing vehicle stability to be maintained. 143
...._...........-..........
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Single Matur Wheel Hulls
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Figure 2 Four wheel drive arrangement with single motor hubs In use in a vehicle, electrical power for the hub motor or motors would be provided by a second reversible electric machine coupled directly to the engine output. This machine could also replace the vehicle's starter and alternator. As the final gearing is provided in the hubs, the vehicle's driveshafts can rotate faster than is conventional; allowing them to be of lighter construction, with smaller associated gears. As the drive system allows independent control of speed and torque at the hub, it eliminates the need for mechanical clutches when the vehicle is stationary. Together, these effects will allow overall vehicle weight to be reduced substantially, with commensurate benefits in efficiency, performance and economy. (Battery)
Engine Motor I Generator Single Motor Wheel Hubs
Figure 3 Complete 2 wheel drive axle with concentric engine, motor generator, brake and 2 single motor hubs in wheels
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Figure 4 Two motor hub for light electric vehicles and micro-hybrid vehicles
In a configuration with multiple driven wheels, each containing such a motor and gearset combination, the speed and torque at each wheel can be controlled independently, eliminating the need for one or more differential gearsets or LSD's, allowing the vehicle designer precise control over power distribution to manage wheel slip and stability in demanding conditions.
3
TWO MOTOR HUB
In this design, rather than relying on electrical energy generated by a second machine external to the hub, two electrical machines can be integrated with the epicyclic gearset within the hub body itself (figure 4). In use, one of the motor/generators generally acts as a generator and transmits electrical power to the other motor/generator, which acts as motor. The amount of electrical power so transmitted may be selectively varied by means of the controller, also altering the speed ratio of the system. Power is transmitted through the system both mechanically and electrically, in proportions which vary with ratio and electrical input from the energy storage device. 4
DUALDRIVE
While all the preceding transmission configurations were three branch designs, it is possible to add an additional degree of freedom to a system with two electric machines, allowing them both to be controlled independently of the rotation of the mechanical input and output. The DualDrive system has been designed as an automotive transmission system that operates on this principle. The epicyclic gear train used in the DualDrive system is unusual in that it has no outer ring gear. Instead, three sets of planet gears are mounted on a single planet carrier. Each set of planet gears engages with its own central sun gear. All the planet gear sets rotate on common shafts and are keyed to those shafts so that they must rotate at the same speed. The first and third planets sets mesh directly with their respective suns. The second set of planets meshes with a set of idler gears, also mounted on the planet carrier, that reverse its direction of rotation with respect to its sun (figure 5).
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Figure 5 The DualDrive operating concept
The vehicle's engine rotates the planet carrier. The first, 'high torque' motor / generator drives the sun of the gear set 1, which in turn drives the first set of planet gears. The second, 'high speed' motor / generator drives the sun of gear set 2, which in tum drives the middle set of planet gears, via the idler gears on the planet carrier. The vehicle's driveshaft is connected to the sun of gear set 3, which is driven by the third and final set of planet gears. The high torque motor / generator can be used to generate power to drive the high speed motor / generator (and vice-versa). The combined motions of the planet carrier (defined by engine speed) and the planets (defined by the sum of the torques from the two electric machines) define the speed of the vehicle's driveshaft. If neither electric motor is transmitting any torque, the engine is free to idle without turning the wheels - obviating the need for a clutch. Different gear ratios are achieved by altering the relative torques applied by the two motor generators. By holding one or other of the electric machines stationary and allowing the other to spin freely, two separate gear ratios are achieved when the system is operating at the full efficiency of the mechanical gearbox. Between these fixed points, electric inputs are minimised - less than half the amount of electric power rating is required compared to "three branch" epicyclic transmissions. This means that the electric machines are extremely compact and low in cost. For hybrid operation, it also means a smaller, lighter, cheaper and more compact battery can be used. There are two ratios at which the electrical path transmits no electric power. The system is sized so that these ratios occur at common operating speeds. In this way, overall efficiency is maximised.
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Figure 6 The DualDrive 4 branch transmission 4.1
Compact packaging
Packaging considerations are critical for any automotive transmission design. DualDrive is designed to fit into the volume of a conventional manual transmission. The compact nature of the epicyclic gear train and the absence of clutches or torque converters provide space for the two electric motors. While their power outputs are the same, the torque requirements for the system's two motor! generators are quite different. As torque defines motor size, this allows the second motor generator to be positioned concentrically inside the first, reducing the overall size of the device (figure 6). The absence of ring gears also reduces the size of the mechanical element of the transmission, as well as reducing overall cost by eliminating these large, high-precision components. Overall, the small size of the DualDrive system allows it to be substituted directly for a conventional transmission in many applications. Alternative configurations will even allow its use in applications where packaging constraints preclude the use of a conventional hydraulic automatic gearbox. Two such configurations are shown below (figure 7, figure 8)
147
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Figure 7 DualDrive configured as a front wheel drive transmission
Figure 8 A compact 2 wheel drive axle with transverse engine and, 2 DualDrive transmissions including concentric final drives, overall length = 600 mm The compact size of the DuaIDrive system offers designers additional flexibility in drivetrain design for larger vehicles. Multiple DuaIDrive systems may be installed in the drivetrain of large all-wheel drive vehicles, for example, allowing full control of speed and torque at each wheel. Such a configuration is shown below (figure 9).
148
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Figure 9 A DualDrive configuration for a large Hybrid or non Hybrid SUV or off road vehicle, allowing independent control of driven wheels 4.2 Power requirements Because the electrical load path only transmits a fraction of the power, in the base case of a 100kW engine for a C-class vehicle for instance, the electric machines in the DualDrive system would need to be rated at 26.3kW max - less than half the electrical power requirements of a three branch transmission. The relatively small electrical contribution is an important factor in delivering the system's high overall efficiency. 70
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Figure 10 Comparative electrical power requirements ofthe DualDrive 4 branch transmission, a three branch transmission and a series electric powertrain DualDrive's low electric power requirement also reduces the size of the electrical machines, their controllers and the necessary battery size for hybrid operation, by approximately 50 per cent compared to 3 branch solutions, delivering considerable savings in cost and weight. Figure 11 shows a comparison of complexity and electrical power requirements for a selection of hybrid powertrain solutions,
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Figure 11 Comparative complexity and electrical power requirements of different hybrid powertrain solutions. (Source: FEV GmbH) 4.3
Reliability
Like any well-designed electric motor and gear combination, DualDrive will deliver an extremely long service life. The absence of clutches and friction materials in the device eliminates a key set of wear parts and also means that the need for transmission oil changes is removed, since the oil is not contaminated by wear particles.
4.4
C02 reduction
Simulations demonstrate that DualDrive could reduce vehicle C02 output by up to 20 percent in conventional drive trains and at least 35 percent as part of a hybrid configuration. In addition to the benefits provided by hybridisation, these reductions will be achieved by a combination of factors. Like all CVT approaches, DualDrive allows the vehicle's engine to operate at its most efficient speed for any given power requirement. But DualDrive provides high overall efficiency - compared with alternative CVT solutions, DualDrive is extremely efficient, minimising C02 generated to overcome transmission losses The DualDrive system can be used to provide a stop-start capability, shutting off the engine when the vehicle is stationary or coasting, restarting it in fractions of a second when power is required. This can deliver more emissions and fuel savings in everyday use, and can be applied to non-hybrid applications of the system. Because DualDrive always allows the engine to operate at its most efficient speed, further CO 2 benefits can be obtained through engine downsizing.
5
CONCLUSION
Power Combining Transmissions offer a wide range of benefits for vehicle designers. The uptake of these technologies is aided by recent advances in electric motor, power electronics, super capacitor and battery technology. Interest in their use is being driven by legislative and consumer pressure on vehicle manufacturers to improve efficiency and reduce emissions. New opportunities to exploit such technologies are emerging, thanks to demand for new classes of lightweight, efficient vehicles to fill specific niches in the transportation infrastructure of the industrialised world and to assist in the provision of mass mobility in developing nations. It is expected that these drivers will lead to mass production applications of the technologies discussed in this paper within a very short time. © NexxtDrive Ltd.
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DRIVEABILITY VALIDATION USING MAHLE POWERTRAIN'S IDAA TOOLSET D Baker, T Girling, G Kennedy, D Pates, and B Porter MAHLE Powertrain Ltd., UK ABSTRACT
Validation of complex systems is a constant problem for vehicle manufacturers. The key to eliminating unacceptable behaviour is in the way the engineering experience is captured and incorporated into the validation test process. The developer must be able to look at the 'right' things in the 'right' way - and ideally as many of these as possible. Recognising the problems and shortcomings of available tools for assessing real world operation, MAHLE Powertrain Ltd developed its Integrated Data Acquisition and Analysis software toolset (IDAA), with the aim of maximising the effectiveness of validation data collected; maximising function coverage against channels logged; combined with powerful analysis capability. Originally developed to assist in the validation of robust On Board Diagnostics (OBD) systems, IDAA effectively enabled engineers to take control with only minimal additional resource and no need for specialist resource (eg. MatIab specialists). Use of the tools enabled engineers to take an integrated approach to the typically fragmented tasks of logging, data processing and reporting. This paper reviews the recent application of IDAA to validating driveability. Using quantifiable Measures of Success established from vehicle development experience, IDAA has been used to effectively assess and report on key driveability areas often associated with customer complaints, including starting, idle control and transient response. IDAA has not only been effectively used to validate mainstream programmes; it has also been successfully applied to programmes destined for emerging markets including China and South America where environmental conditions, customer usage patterns, and fuels can also affect driveability performance.
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INTRODUCTION Background to driveability and driveability assessment
Driveability has historically been one of the most subjective parts of the calibration process and is very difficult to consistently develop, appraise and validate. The basic principle of driveability is that of a subjective feeling in many cases and much work has gone into developing these subjective ratings into more objective and repeatable results. At a basic level some aspects of driveability are associated with the functionality of the vehicle - starting, idle control, smooth response to throttle changes, e.t.c, whilst at a more detailed level they help define the characteristics of the vehicle, often referred to as the vehicle's 'DNA'. Typically manufacturers will identify various high level/subjective and low level/objective driveability targets for an application and will have their own assessment and testing procedures to measure their performance against these. Subjective ratings, typically using a scale of one to ten, are used to assess key areas of driveability for which it would be difficult to assign and assess objectively. The assessment criteria, or Measures of Success (MoS), will have been developed by teams of experienced calibration engineers in order to characterise some of the main areas of driveability: • Start Constant Load (road load and crowds) • • In Vehicle Transient (including open/closing throttle, fuel cut) • Idle • Speed Limiting • Transmission Shifts The aim of driveability development and validation is to ensure that the driveability responses of the powertrain system are robust to driver inputs, environmental conditions, market fuels, drive styles and driver 'abuses' that the vehicle is likely to encounter. To assess and validate the driveability calibration three methods are typically used: 1. Structured test track based driver assessments A prescribed set of tests is carried out to cover the operating envelope of the vehicle. The use of a structured and controlled test approach improves the accuracy and repeatability (and hence objectivity) of the subjective assessments. Both subjective and objective data may be collected for each test condition. Typically the objective data will only be used to assess some specific driveability measures, e.g. start times, and in the investigation of any issues identified from the subjective data. 2. Subjective driver assessments and feedback Subjective ratings are recorded for different operating conditions that replicate real world use as closely as possible. The rating data and comments can be recorded in a database that allows reporting and analysis of the results. 3. Validation testing performed in territories A mixture of structured and unstructured testing will be carried out in territory with the aim of assessing driveability performance under a range of extreme or limit market conditions. Data can be processed locally or sent back to the
154
engineering centre for processing and analysis as part of the development programme.
Problems with conventional driveability assessment approaches These assessment approaches go some way towards providing the clear understanding of the powertrain's response to the range of customer and market conditions that is required. But they fall short in a number of areas: • Reliance on subjective assessments • Limits accuracy • Comparisons difficult • Key opinion leaders can influence ratings • Detailed track assessments are very limited • Assessments carried out infrequently • Only in prevailing conditions • Many conditions not tested in detail • Limited use of objective data in assessment criteria • Subjective assessments can be broken down into objective measures • Potential data collection opportunities not realised • Objective measures can be applied to any recorded data • If all vehicle drives were logged then there would be a vast resource of driveability data Ideally the driveability engineer should have the capability to analyse any response of the system across any vehicle at any location in order to assess the performance. Additionally the engineer should also be able to assess his data coverage, i.e. which conditions haven't been tested. Until now there has not been a practical solution available to the engineer to provide this capability.
Application of integrated data acquisition and analysis (lDAA) To respond to this requirement, the data handling and analysis toolset for the acquisition and automated analysis of data, known as Integrated Data Acquisition and Analysis (IDAA), was developed. This toolset has been successfully implemented on a number of calibration features predominantly for On Board Diagnostics (OBD) development and validation. Through the use of automated high-resolution data loggers it is now possible to gain real world high resolution data from vehicles operating at locations throughout the world. Processing the resulting large quantity of data and presenting the data in the ways that will be of use and of interest to the engineer requires an automated and intelligent processing approach.
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IDAA approach IDAA automates the traditional data analysis approach, allowing engineers to focus in greater detail on the real issues. Complex datasets from multiple engines/vehicles can be automatically processed, analysed and easy to understand reports generated. The automatic processing is supported by configuration tools, which are simple for any engineer to use. Using the configuration tools the engineer will define the way the data is to be processed and the way the processed data should be presented. An overview of the toolset is shown in Figure 1.
Reports
Applications experience Quality Guidelines Performance Targets Previous I Library
Figure 1: System overview diagram The module responsible for the analysis contains a script called a Data Specification Document (DSD) which is a self contained set of processing instructions together with information on the logging channels to extract from the datalog and the output signals required to produce a report. To effectively analyse the recorded data the DSD is defined using previous engineering experience of the event being assessed and an understanding of the objective measures which characterise that event. The DSD analysis capability supports complex processing approaches - the actual processing is performed using a 'Matlab' processing engine. The DSD analysis can be set up with appropriate trigger conditions, e.g. engine start analysis is performed at start, or trigger repeatably throughout the datalog for examples such as returning to idle and tip-in analysis. The development of the DSD defines which Engine Management System (EMS) signals are to be recorded and their acquisition rate. To prove the DSD's robustness and validate any modifications or changes to the IDAA toolset, a library of datalogs with known characteristics is used. These have been processed using the DSD and then correlated against a manual assessment of the same data using traditional techniques. The IDAA reporting tool provides several formats for viewing the data, the most common being the trend and distribution views, see figure 2. Trend views provide the traditional XY scatter plot and can support several channels of data with upper and
156
lower thresholds on a single plot. Distribution views allow the spread of data to be presented for the operating region, again with upper and lower thresholds displayed. In addition, distribution views have the ability to provide a statistical analysis of the spread of data against the limit value(s), giving a confidence measure for that data.
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I Cok = 0.817 Trend Plots display quantities of interest against vehicle mileage • Trends may be identified • 'Deep dive' into Individual trips
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"end-on" view of data Statistical measures applied to distributions
Figure 2: Example data presentation OBJECTIVE This paper demonstrates the application of the IDAA toolset to vehicle driveability validation. It covers the processing of data using driveability specific script files, analysing this data against defined measures, and then generating reports from generic templates that allow driveability perfonnance to be clearly assessed. ENGINE START ANALYSIS
Measures of success for engine start Figure 3 highlights some features of engine starts from different example engine speed profiles. • Start time - battery voltage drop to engine speed reaching target idle speed • Run-up rate - average gradient of engine speed from crank to target idle speed • Number of stumbles - rate of engine speed becomes negative • Flare speed - maximum engine speed reached above target idle speed
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Figure 3: Example engine speed profiles Definition of DSD - analysis scripting This start DSD includes a number of user definable thresholds to allow modification to the detection of specific conditions. These have initially been set using engineering judgment for the demonstration vehicle but may be easily modified for other applications. From the raw data inputs a number of further channels are calculated and a number of predefined conditions identified. These conditions divide the start into six main sections, pre-crank, cranking, run-up, flare, post-flare and stable idle. These are then broken down into further subsections associated with each specific MoS. Additional calculations are performed to identify if any external or driver induced conditions occur, which could affect the measured start characteristics. For example, on a manual vehicle if the driver was to engage a gear and release the clutch immediately after start then it is important that any resultant engine speed dip (or even stall) is not attributed to the start performance. The outputs from the start DSD can be divided into two categories, measurable signals which can occur multiple times in each data log, for example the flare speed of every start, or significant events which are identified and counted, for example crank and no start conditions. Each of these calculated values or counters can be associated with an upper and lower limit, these can be fixed values, a table versus another calculated channel or a threshold extracted from the EMS calibration. For calibration development where individual starts are analysed and processed, the results can be analysed in comparison to a limit. However, when analysing large quantities of data collected over a range of conditions, especially where the limit varies over these conditions, it is often more appropriate to normalise the data against the limit thus making it easier to identify trends and headroom against a changing target.
158
Reporting of IDAA analysis data
Figure 4 shows an example of the way that one of the key measures would be reviewed on a regular basis. Time interval from initial crank to reaching target speed is plotted against coolant temperature, vehicle odometer, time, barometric pressure and precranking battery voltage. Typically the acceptable limit for this time interval is dependent upon coolant temperature and changes significantly at low coolant temperatures, as shown in the plot of start time versus coolant temperature.
159
mRHLE Trend and Headroom Analysis Report Engine Start Crank To Target Speed Analysis vs Coolant Temperature
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160
SURGE ANALYSIS Measures of success for surge Surge is defined as an engine speed oscillation around the moving average engine speed. Figure 5 demonstrates this during a constant load acceleration. Engine Speed Response Plot
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Figure 5: Surge condition Definition of DSD - analysis scripting To effectively analyse vehicle surge, it is first necessary to identify the operating condition where it can be robustly measured. For example, to detect surge in a 'crowd' condition (driving with relatively constant intake manifold pressure) the DSD uses an algorithm to analyse driver's pedal input and engine load, waits for this condition to stabilise for a user defined time period and then analyses the engine speed trace to calculate a measure of surging. The DSD compares the instantaneous engine speed with a moving average engine speed and then performs a standard deviation calculation on the absolute value of this difference to define a surge measure. The operating conditions for the crowd are recorded in terms of engine speed and load and other relevant EMS parameters, e.g. ignition timing and coolant temperature. Further in depth analysis can be conducted using Fast Fourier Transforms to identify the frequency characteristics of the surge condition. As the DSD is able to identify any number of surge conditions throughout the datalog it can be used to analyse real world driving in addition to specific drive cycles. IDAA is particularly suitable to this real world situation as the incidences of crowd conditions over a wide speed / load range will be relatively low. Therefore it may take a significant time or distance to acquire sufficient data to cover the speed load range to be assessed.
161
Reporting of IDAA analysis data Figure 6 shows an analysis of two calibrations for surge in a crowd condition. The first is an existing production calibration with subjectively undetectable levels of surge at lower engine speeds moving to borderline acceptable at engine speeds greater than 4500rpm. The second calibration is based upon the first with some changes for demonstration purposes to induce surge in the 2000 to 3000rpm region at all loads. Subjectively this second calibration exhibited unacceptable levels of surge in the modified region. Figure 6 breaks down a specific area of concern into a range of measurement types including frequency analysis and also includes a section of the original data log associated with the concern. In the example differences between the two conditions can be seen in each of the graphs. The frequency distribution and peak power density analysis clearly shows the magnitude of excitations in the critical, for driver feel, range around 4Hz. There are clearly a number of objective measures that we can generate from the collected data which can be used to supplement the subjective judgements. In the longer term these measures may be correlated against the subjective judgement criteria so that the data can be presented in a more traditional format. In a real world situation the areas of surge may be more difficult to spot. Surge may only occur when specific operating conditions exist, for example during warm-up, with catalyst heating active, at certain speeds and loads or at a combination of conditions. The automated assessment approach outlined here means that all of the vehicle logs can be processed and any traces of surge under any conditions can be identified and analysed. To assist in the analysis of the surge data the reports can be easily modified to look at the data in a number of different ways. Alternatively the data can be filtered for specific conditions, for example the surge analysis could be reported against speed and load with and without catalyst heating active.
162
Standard deviation of engine speed difference from moving average shows a relatively constant trend for the original calibration and a peak around 2500rpm for the demo calibration
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IDLE STABILITY ANALYSIS Measures of success for idle stability We define base idle stability as the difference between engine speed and target idle speed in an idle condition without any external inputs. Figure 7 identifies some typical examples of idle instability.
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Figure 7: Examples of idle instability Definition of DSD - analysis scripting In contrast to long duration crowd conditions, idle conditions will tend to be encountered more frequently during real world driving and will be less influenced by driving style. Traditionally this would present the engineer with a huge quantity of idle data with reliance on the driver reporting the occurrence of idle stability concerns. For automated idle stability analysis the DSD initially searches through the entire datalog to identify each section of data where the engine is in an idle condition as defined by the EMS. In order to only analyse stable idle conditions without any transient effects associated with external or driver inputs, the DSD then applies a number of filters and timers. Similarly the transient condition of having just returned to idle can be excluded from the analysis. These stable idle periods are divided up into user definable fixed length intervals, for example 15 seconds. A further constraint is imposed upon the data in the 15 second window in that the engine load must remain within a threshold from the mean engine load; this allows the data to be rejected if uncompensated load changes occur on the engine which are not visible directly through the EMS. Once a valid 15 second window is identified the standard deviation of EMS calculated engine roughness and the corresponding mean load, engine speed, temperature, e.t.c. are recorded to produce a set of data for that 15 second period. Reporting of IDAA analysis data Figure 8 shows an example report format for idle stability using standard deviation of calculated engine roughness. In addition to reporting the roughness on a mileage and time basis, the analysis is also performed against oil temperature, coolant temperature, barometric pressure, engine load, ignition timing, catalyst heating status, air conditioning status and in either neutral or drive.
164
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165
Drive
DISCUSSION This paper demonstrates the potential analysis capabilities available to the engineer using the IDAA toolset. Processing large quantities of complex datasets using conventional tools is very time consuming and therefore unrealistic, even for the skilled Matlab operator. Because of the difficulties in processing the data files the automated driveability analysis presented in this report would not normally be possible. This makes it difficult to compare IDAA to traditional approaches directly, clearly using IDAA it is now possible to make this kind of detailed analysis on an ongoing basis. To illustrate the efficiency gains of this technique we can compare the time taken to analyse 25 measurable characteristics from ten engine starts, each on separate datalogs, which in total takes under 20 minutes with the IDAA approach without user intervention. Manual assessment of the same data and outputs has been estimated to take over three hours of focused engineer's time. Another significant advantage with IDAA is the possibility to automatically analyse and generate reports from a large number of data files from various data sources. With the processing automated the engineer is able to invest time into defining new, more effective, ways of objectively looking at the system performance. In this example we were looking at the assessment of driveability data. In the introduction shortfalls to conventional driveability assessment were identified: • Reliance on sUbjective assessments • Limits accuracy • Comparisons difficult • Key opinion leaders influence ratings • Detailed objective assessments are very limited • Detailed track assessments carried out infrequently • Only in prevailing conditions • Many conditions not tested in detail • Limited use of objective data in assessment criteria • Subjective assessments can be broken down into objective measures • Potential assessment data collection opportunities not realised • Objective measures can be applied to any recorded data • If all vehicle drives were logged then there would be a vast resource of driveability data Using the IDAA toolset and high resolution data logging it is possible to take a significant step forward and to address these issues. Objective measures can be established to define the required output responses or performance requirements of the powertrain system. The benefits are clear for applying objective assessment criteria and automatically processing all of the data files available. The IDAA toolset has been successfully applied to a number of projects. The original application was for OBD fleet robustness, where it was used for validation. Several issues were identified, investigated and resolved that may otherwise have gone undetected. Some of these issues did not set fault codes, but were identified because the data showed they were approaching the operating or OBD thresholds.
166
CONCLUSIONS Validation of complex systems is a constant problem for vehicle manufacturers. The key to eliminating unexpected or undesirable behaviour is in the effective application of engineering experience during development and validation. The developer must be able to look at the 'right' things in the 'right' way. IDAA provides engineers the tools that allow them to look at as many functional performance measures as possible in the right way, and to do this consistently across projects. Using quantifiable Measures of Success established from vehicle development experience, IDAA has been used to effectively assess and report on key driveability areas often associated with customer complaints, including starting, idle control and transient response. © MAHLE Powertrain Ltd.
167
THE EFFECT OF EXHAUST AFTERTREATMENT AND ENGINE TEMPERATURE ON IOLS FOR CVT POWERTRAINS J A Gutierrez Magana and C J Brace Department of Mechanical Engineering, University of Bath
ABSTRACT An investigation has been conducted into the scope for Ideal Operating Lines (IOLs) to improve fuel consumption and CO, HC, NOx and PM emissions of a vehicle equipped with a CVT. This simulation was performed using the ADVISOR code within the MATLAB/Simulink environment. The ADVISOR code was modified to investigate the effect of a range of IOLs on a vehicle equipped with either a Spark Ignition (SI) or Diesel engine coupled to a CVT. The work addresses two issues often neglected during the calibration process due to the complex interactions involved. The work seeks to demonstrate that a simple simulation based tool is able to inform the calibration process at an early stage of vehicle development. First, the effect of the exhaust aftertreatment device on engine-out emissions for differing IOLs was analysed. In the case of the SI engine it was found that internal catalyst temperature increased more rapidly with the IOLs for HC and NOx. Consequently, maximum conversion efficiencies were reached more quickly than with the IOLs for fuel consumption and CO. As a result, IOLs derived with reference to engine-out emissions were unable to deliver the lowest tailpipe emissions results in some cases. Simulation of the entire system as demonstrated here is able to address this deficiency. The second area discussed is the analysis of fuel usage and emissions production as a function of engine temperature. An IOL-based optimisation approach is proposed to improve fuel consumption and NOx and PM emissions during the engine's warm up period. The approach was compared to a common technique of using IOLs calculated for hot operation and it was found that improvements of around 5% can be obtained for emissions. However, the scope for optimisation of fuel consumption was negligible due to the relatively stable fuel consumption characteristic during warm up.
INTRODUCTION The implementation of directives with the objective of limiting vehicles' emission levels has led to develop more sophisticated powertrains. As a part of this, development control strategies have been designed which allow the powertrain operation to emit less pollution and reduce fuel consumption, thus contributing to a reduction in the environmental impact caused by vehicles. The use of IOLs within the control strategy has long been shown to allow optimum fuel consumption to be achieved by CVT powertrains (1). It has further been shown that IOLs can be generated for other optimisation goals, such as exhaust emissions (2, 3, 4). Commonly, the effect of adherence to an IOL on driveability is neglected, which must be overcome in realistic control strategies. IOLs therefore are of most benefit in steady or near steady driving. A further aspect that is often overlooked is the effect of the exhaust aftertreatment device and the engine warm up characteristic.
169
This work is part of an investigation (5) into the scope of Ideal Operating Lines to improve the performance of CVT powertrains by addressing these shortcomings. In particular, this paper reports on a study into the effect of the exhaust afiertreatment device on emissions produced by the SI engine, and the effect of engine temperature on emissions and fuel consumption with regard to a Diesel engine. The simulation was performed in ADVISOR, which runs in the Matlab/Simulink environment. In addition, the work sets out to determine whether a relatively simple simulation approach can result in useful information to guide the calibration process. Such data would allow the calibration time to be reduced as iterative emissions testing could be minimised.
ADVISOR, SIMULATION PARAMETERS AND DESCRIPTION OF THE PLANT This section describes the main characteristics of ADVISOR and the models used in the simulations. Both spark ignition and Diesel engines were coupled to the same transmission and the same powertrain controller was used, with appropriate recalibration. Appropriate exhaust afiertreatment devices were selected for each engine type.
Advisor The 'ADvanced VehIcle SimulatOR' was developed by the National Renewable Energy Laboratory and it is a virtual tool designed to analyse performance and fuel economy of a wide range of vehicle types (6) including hybrid and conventional powertrains. ADVISOR version 3.2 was used for the work described in this paper. The simulator runs in the Matlab/Simulink environment and includes a graphical user interface which allows the vehicle's parameters and simulation characteristics to be defined. Vehicle systems and components models are included as code- and block-based Matlab and Simulink files respectively. It is possible to modify these models and adapt them to the objectives of a particular study. ADVISOR uses forward- and backwards-facing simulation approaches (6). The latter first calculates the requested road load and converts it into a set of requested torque and speed values through the wheels and the drivetrain components. This approach provides the basis to allow the powertrain operation to follow a particular IOL. The data set produced by the simulation includes a significant number of variables related to the vehicle's operation, allowing subsequent analysis. Simulation for this study was based on spark ignition and Diesel engine models coupled to a CVT, which are described later in this paper. A number of elements of the simulation are relevant to the work described here and are introduced below.
Vehicle and simulation parameters Simulation parameters include the characteristics of the vehicle, its accessories and cargo load, and the drive cycle employed to run the tests. The chosen vehicle model is based on a hypothetical small vehicle and approximates a 1994 Saturn SLl car, one of the standard models provided within the ADVISOR suite oftools. 170
The chosen wheel/axle model defines tyre, wheel, and axle assembly parameters for the specified vehicle type. Accessories load is defined by a model which defines a standard load drawn from the engine. Cargo load is set manually, and was defined as 80kg assuming that the vehicle would be driven by a medium-sized person. The EeE + EUDC drive cycle was chosen to perform all the tests in this study. ADVISOR models Spark ignition and Diesel engines
The selected SI engine model corresponds to a 1991 Oeo Metro 1.01 engine, for which fuel consumption and emissions data are available within ADVISOR. Maximum power and torque ratings are 41kW and 80.9Nm. Hot operating temperature is defined by the thermostat setting at 96° C and cold operation at 20° C. The model contains hot fuel consumption data and engine-out emissions maps in g/kWh and g/s units for HC, CO, and NOx. A 1999 VW 1.9L TDI engine model was selected for the Diesel engine Data for this engine is provided withint he ADVISOR suite. Maximum power and torque values are rated at 70kWand 217.2Nm. Hot and cold operating temperatures are defined as 99° C and 20° C. Hot and cold fuel usage and engine-out emissions maps in g/kWh and g/s for HC, CO, NOx, PM, and 02 are included. The model also contains cold and hot data for exhaust gas temperature in °C, total exhaust flow in gis, and total volume exhaust flow in m 3/s.
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Figure 1 Original and revised L TCs - VW Diesel engine The Limiting Torque Curve (LTC) of this engine exhibited a steep droop approaching maximum rated speed resulting in maximum power being achieved at somewhat less than maximum speed. As shown in figure 1, the LTC was revised slightly such that maximum power was achieved at maximum engine speed. This task was performed in order to better design and implement IOLs within the CVT powertrain control model, and was achieved by adapting the curve of a 92kW Diesel engine model through scaling and interpolation processes in order to keep maximum power and torque ratings at their original values.
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Engine temperature prediction
As discussed in ADVISOR's fuel converter documentation (6), the engine's thermal model comprises cylinder, engine block, exterior accessories, and under bonnet temperatures. The model is a simple lumped parameter analytical representation of the engine in which the combustion generates heat, which is conducted through the engine block, and dissipated through liquid cooling, conduction, natural convection, and radiation. Engine coolant temperature is sensed and controlled by a thermostat, whose set point is user-definable. For the purpose of calculating the cylinder and engine block temperatures an energy balance is performed. The heat input to the engine is the remainder after the usable power and heat contained in the exhaust are subtracted from the energy contained in the fuel used. Heat is dissipated from the cylinder to the engine block by conduction. The conductance value is user-definable. A portion of the heat input is dissipated to the engine accessories through conduction. The remaining heat passed into the engine block is absorbed into the coolant fluid. Some of this heat can be used by the cabin heater and the remainder is dissipated by the radiator. A complete description of the engine temperature prediction is included in ADVISOR's documentation (6). Exhaust aftertreatment devices for SI and Diesel engines
Exhaust aftertreatment was accomplished with models which correspond to closecoupled conventional converters for hypothetical vehicles with SI and Compression Ignition (CI) engines. Both models include a scaling algorithm which scales the size of the catalyst as a function of maximum engine power. Zero-efficiency versions of these models were also created in order to obtain engine-out emissions. This emulates the use of unreactive converters experimentally for the same reason. 0.9 0 .•
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Figure 3 Warm up model of the catalytic converter for CI engines The catalyst for SI engines operates within a temperature range of -40 0 C to 12000 C. As shown in figure 2, which shows the catalyst's wann up model; maximum conversion efficiencies are 95% for CO, 85% for HC, and 91 % for NOx, and they are all achieved at 5500 C. In the case of the latter, an efficiency value of 90.09% is achieved at 415 0 c. The catalyst for CI engines operates within the same temperature range as for the previous converter although in use the exhaust temperatures observed are considerably lower. As can be seen from figure 3, maximum conversion efficiencies are 95% for CO, 91 % for HC, 45% for NOx, and 40% for PM. Maximum conversion efficiencies are achieved at 3000 C for CO and PM, 4500 C for HC, and 2000 C for NOx. Note that the conversion efficiency for NOx tails off at higher catalyst temperatures as the conditions needed for NOx conversion are not generally present in an oxidising exhaust stream (7). This simple model is not able to represent the chemical effects necessary to achieve passive NOx conversion in an oxidation catalyst, which depends on the quantity of stored HC on the catalyst as well as the temperature. The efficiency curve presented gives a fair approximation to the effect, however. Exhaust temperature prediction
As described in ADVISOR's exhaust system documentation (6), the exhaust system model is used to simulate an engine exhaust afiertreatment system, and consists of the exhaust manifold, downpipe, catalyst, and silencer. One of the outputs of the exhaust system model is the temperature of the components of the exhaust system and exhaust gas. The temperature of the catalyst is calculated through a lumped-capacitance approach. Mass and heat capacities are assigned to components such as the monolith, exterior shell, manifold and downpipe. Convective heat transfer coefficients from the hot exhaust gas to the components and consecutively to ambient air are calculated through heat transfer correlations. The heat released by exothennic reactions within the catalyst is estimated as a function of the mass of each emission component (HC, CO, NOx, and PM) being catalyzed and the conversion efficiency. This heat adds to the rate of converter wannup. Equations related to exhaust system modelling are shown below, a complete description can be found in ADVISOR's documentation (6): •
Change in temperature with time = [net heatflow] / [(mass)*(heat capacity)] 173
where net heat flow can be the sum of some or all of the following paths: • • • •
Convective = (heat transfer coefficient)*(surface area)*(surface-to-fluid temperature difference) Conductive = (thermal conductance)*(surface-to-surface temperature difference) Radiative = (emissivity)*(surface area)*(StefJan-Boltzman constant)*(bonnet temperature4 - cylinder temperature4) Exothermic = I(emission component mass flow) *(conversion efficiency)*(calorific value)
Continuously Variable Transmission
The CVT model chosen corresponds to a Subaru lusty Electronic VDT type Continuously Variable Transmission. Its rated speed and torque inputs are 5000rpm and 95Nm and peak efficiency is 95%. The transmission includes data at five pulley ratios, which are 2.5, 2, 1.5, I, and 0.5. The final drive ratio has a value of 5.83. Scaling factors for input speed and torque are included and were modified in order to match the transmission with the characteristics of each engine type. The factors were obtained by dividing maximum engine speed and torque values between maximum transmission's speed and torque inputs. Another modification required was the modification of the final drive ratio in order to better match the transmission to the Diesel engine. This adaptation was performed because the powertrain was unable to achieve the operating points required to follow an IOL. A 'trial-and-error' approach was used for this purpose and the best solution was obtained by dividing the final drive ratio by the torque scaling factor. Powertrain control
Powertrain control was carried out by means of a model designed to control the operation of an advanced conventional vehicle with a CVT. The model defines all powertrain control parameters, including gearbox, clutch, and engine controls. Transmission control starts by creating a vector defining a CVT power locus based on engine torque and speed ranges, and maximum power. This is followed by a series of computations which process a chosen engine map (normally fuel usage) and generate a vector defining the required CVT speed locus to minimise the engine map values at each point on the power vector. This CVT speed vector is termed a 'design curve' which is the basis ofthe control strategy for the powertrain and is actually an IOL. In practice this method generates very erratic IOLs as it is based on a simple minimisation of the desired engine map. This deficiency renders the use of automatically generated IOLs of limited use as their use in a vehicle would result in erratic driveability and would be impossible for the powertrain to follow due to the rate of engine speed change specified. As a result a key requirement for this work was the modification of the ADVISOR code to allow the generation and use of manually designed lines as described below.
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IDEAL OPERATING LINE DESIGN IOLs for fuel consumption, CO, HC, and NOx were designed for the SI engine and IOLs for fuel consumption, NOx, and PM were designed for the Diesel engine. For this purpose, the respective maps included in the engine models were plotted as contour graphs in g/kWh units. ADVISOR's code was employed to define six contour levels, starting from the lowest value and ending up with a medium-range one. The maps are indexed by engine torque and engine speed, and the engine's LTC was included. Lines of constant power were also added, moving between zero and the maximum available power in twenty steps. Note that only ten lines of constant power are shown on figures for clarity. Following this approach, each constant power line represents increments of 4.1 kW and 7kWfor the SI and Diesel engine maps respectively. Drawing IOLs on engine maps A design tool was created in Matlab and was employed to graphically design the IOLs. This tool plots each engine map with the characteristics previously described and allows the designer to select the location of the points of a particular IOL. Once the points are located, they are joined together and their speed and torque coordinates saved as data vectors, which were later input to the control strategy. Each one of the points that constitute an IOL is located on a line of constant power. Because of this, more rounded shapes were achieved using twenty lines since smoothness was considered explicitly during the design process. All the IOLs were designed such that their last point is located at engine's maximum power point, which is located at the right end of the LTCs. As shown in figures 4 and 5, each IOL point was located by manually moving it along each line of constant power, labelled in figure 4 according to their values in watts and shown only as contours in figure 5. The best location was selected by placing each point inside the least-possible emissions or fuel consumption contour value as shown in figure 5 for the case ofNOx. Applied rigidly, however, this design approach would not produce a smooth trace because some emissions maps present very irregular contour shapes. In this case, compromises were made while locating the points in order to achieve a soft-rounded trace and some points were not placed on the best location. 90
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Figure 4 IOL point along a line of constant power
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Figure 5 IOL for NOx on NOx emissions map - Geo SI engine
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