400 Commonwealth Drive, Warrendale, PA 15096-0001 U.S.A. Tel: (724) 776-4841 Fax: (724) 776-0790 Web: www.sae.org SAE TECHNICAL PAPER SERIES 2008-01-0605 Longitudinal Velocity Estimation of Electric Vehicle with 4 In-wheel Motors Xiaojie Gao, Zhuoping Yu and Tifan Xu Tongji University Reprinted From: Vehicle Dynamics and Simulation, 2008 (SP-2157) 2008 World Congress Detroit, Michigan April 14-17, 2008 Downloaded from SAE International by American Univ of Beirut, Sunday, July 29, 2018By mandate of the Engin eering Meetings Board, th is paper has been approved for SAE publication upon completion of a peer review process by a minimum of three (3) industry experts under the supervision of the session organizer. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise,without the prior written permission of SAE. For permission and licensing requests contact: SAE Permissions 400 Commonwealth DriveWarrendale, PA 15096-0001-USAEmail: [email protected]: 724-772-4028Fax: 724-776-3036 For multiple print copies contact: SAE Customer ServiceTel: 877-606-7323 (inside USA and Canada)Tel: 724-776-4970 (outside USA)Fax: 724-776-0790Email: Customer [email protected] ISSN 0148-7191Copyright © 2008 SAE InternationalPositions 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. A process is available by which discussions will be printed with the pap er if it is publishe d in SAE Transactions. Persons wishing to submit papers to be considered for presentation or publication by SAE should send themanuscript or a 300 word abstract of a proposed manuscript to: Secretary, Engineering Meetings Board, SAE. Printed in USADownloaded from SAE International by American Univ of Beirut, Sunday, July 29, 2018ABSTRACT This paper describes a methodology to estimate longitudinal velocity of a 4-wheel-drive electric vehicle, in which wheel driven torque can be independently controlled by electric motor. Without non-driven wheels it would be difficult to estimat e the vehicle longitudinal velocity precisely, especially when all of four wheels have large slip ratio. Theref ore, an estimation methodology based on fuzzy logic is put forward, which uses four wheel speed and longitudinal acceleration as input signals. However, this method works not very well when two or more wheels have large slip ratio. In order to improve estimation effect, a state variable filter is designed to calculate wheel acceleration signals, which are used as additional signals to the fuzzy logic observer. Furthermore, the possibility of using four wheel driving torque signals to improve the estimation precision is also discussed. INTRODUCTION Nowadays with the development of automotive industry and increasingly high requirement of vehicle safety, active safety control system has become more and more important. Vehicle driving state can be recognized through onboard sensors and then vehicle can be controlled stably according to respective algorithm. Longitudinal velocity is one of the most important signals for ABS (Anti Lock Brake System), ASR (Anti-slip Regulation System) and ESP (Electronic Stability System) and it can be used to calculate reference slip ratio or identify vehicle state. However, up to now sensors which can directly measure vehicle velocity (by using micro-wave or GPS principle) are not available to production cars due to high cost or installation problem. Thus it is necessary to design estimation algorithm to obtain exact vehicle longitudinal velocity which is necessary for active control system. Vehicle velocity estimation algorithm generally can be divided into two categories: the regression method based on wheel speed information and the calculation method based on vehicle model. T