The Engineering Meetings Board has approved this paper for publication. It has successfully completed SAE’s peer review process under the supervision of the session organizer. This process requires a minimum of three (3) reviews by industry experts. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form o r by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of SAE. ISSN 0148-7191 Positions and opinions advanced in this paper are those of the author(s) and not necessarily those of SAE. The author is solely responsible for the content of the paper. SAE Customer Service: Tel: 877-606-7323 (inside USA and Canada) Tel: 724-776-4970 (outside USA) Fax: 724-776-0790 Email: [email protected] SAE Web Address: http://www.sae.org Printed in USA Copyright © 2009 SAE International ABSRATCT To design and optimize the vehicle driveline is necessary to decrease the fuel consumption and improve dynamic performance. This paper describes a methodology to optimize the driveline design including the axle ratio, transmission shift points and transmission shift ratios considering uncertainty. A new and flexible tool for modeling multi-domain systems, Modelica, is used to carry out the modeling and analysis of a vehicle, and the multi-domain model is developed to determine the optimum design in terms of fuel economy, with determinability. Secondly, a robust optimization is carried out to find the optimum design considering uncertainty. The results indicate that the fuel economy and dynamic performance are improved greatly. INTRODUCTION Fuel consumption and vehicle performance have been a core consideration since the beginning of the transportation era. The engine performance and driveline configuration directly affect the fuel economy and dynamic performance of a vehicle. Many researches have been done to optimize the driveline to meet the specified vehicle performance criteria. The optimization are always carried out based on mathematic model and consider all the parameters of the vehicle are certain. In [1, 2], the transmission ge ar ratios were optimized for fuel economy, vertical acceleration, and acceleration performance measures for a class VI truck. The study did not optimize the axle ratio, transmission shift points, and did not include uncertainty. An accurate vehicle performance model is report ed in [3]. However, an optimization was not performed and the impact to fuel economy not considered. The inputs to the model were varied manually in order to observe sensitivities. The transmission gear ratios were optimized in [4, 5] for acceleration performance an d fuel economy without optimizing the axle ratio and transmission shift points and without including uncertainty. To improve modeling accuracy, a new and more flexible tool for modeling multi-physics systems, Modelica is used to carry out the modeling and analysis of a complete vehicle model. The model is developed to determine the optimum design in terms of fuel economy, without considering variations or illegibilities. Secondly, a deterministic based design op timization is carried out to find the optimum design in the presence of uncertainty. The optimization was carried out by iSight, which is developed by Engineous Software, Inc. The results indicate that the fuel economy and dynamic performance are improved greatly. DESCRIPTION OF TECHNICAL MODELS Modelica is a standardized modeling language built around acausal modeling with mathematical equations[6]. The Modelica language is being constructed by the Modelica Association. The aim is to construct a standard language for describing muti-domain models. Because the language is not built around assignment, the