Optimal slip ratio estimator for traction control system of electric vehicle based on fuzzy inference

被引:23
|
作者
Kataoka, H [1 ]
Sado, H [1 ]
Sakai, S [1 ]
Hori, Y [1 ]
机构
[1] Univ Tokyo, Tokyo, Japan
关键词
electric vehicle (EV); driving force; traction control system (TCS); optimal slip ratio control; gradient method; fuzzy inference;
D O I
10.1002/eej.1033
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper we propose an optimal slip ratio estimation method based on fuzzy inference. One of the major advantages of electric vehicles is the quick and precise torque response of the electric motor, which realizes a novel traction control system. To prevent skidding, optimal slip ratio control has been successfully developed. It maintains the slip ratio at the optimum value that gives the maximum driving force. The remaining problem is how to generate the optimal slip ratio command sent to the controller. First we show that effective estimation of the optimal slip ratio is difficult to perform by the simple gradient method, which is a well-known optimization method. But various experimentally obtained data can be easily incorporated into fuzzy inference, and therefore its estimation performance can be easily improved by the accumulation of human experience. This is a major advantage in the nonlinear estimation of real road-tire characteristics. The effectiveness of the proposed estimation and control methods is confirmed by numerical simulation. (C) 2001 Scripta Technica.
引用
收藏
页码:56 / 63
页数:8
相关论文
共 50 条
  • [21] An Optimal Slip Ratio-Based Revised Regenerative Braking Control Strategy of Range-Extended Electric Vehicle
    Liu, Hanwu
    Lei, Yulong
    Fu, Yao
    Li, Xingzhong
    ENERGIES, 2020, 13 (06)
  • [22] Analysis of Sensorless Traction Control System for Electric Vehicle
    Montonen, Jan-Henri
    Lindh, Tuomo
    2014 16TH EUROPEAN CONFERENCE ON POWER ELECTRONICS AND APPLICATIONS (EPE'14-ECCE EUROPE), 2014,
  • [23] Implementation of vector control on electric vehicle traction system
    Nady Ibrahim
    Mohamed Abdelaziz
    Maged Ghoneima
    Sherif Hammad
    Bulletin of the National Research Centre, 44 (1)
  • [24] Slip rate identification and traction control of 4WD electric vehicle
    Zhou, Si-Jia
    Luo, Yu-Tao
    Huang, Xiang-Dong
    Fu, Xing-Feng
    Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science), 2008, 36 (06): : 95 - 100
  • [25] MPC-Based Slip Ratio Control for Electric Vehicle Considering Road Roughness
    Ma, Yan
    Zhao, Jinyang
    Zhao, Haiyan
    Lu, Chao
    Chen, Hong
    IEEE ACCESS, 2019, 7 : 52405 - 52413
  • [26] Slip ratio adaptive control for distributed drive electric vehicle based on wheel speed
    Chen, Qiping
    Huang, Liang
    Gan, Lu
    Kang, Sheng
    Wan, Rui
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2024, 238 (12) : 3499 - 3511
  • [27] Fuzzy anti-slip control based on optimal slip control
    Feng, Yanbiao
    Yang, Jue
    Ji, Zhiyi
    Zhang, Wenming
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2015, 31 (08): : 119 - 125
  • [28] A New Slip Ratio Observer and Its Application in Electric Vehicle Wheel Slip Control
    Liang, Bo-Rong
    Lin, Wei-Song
    PROCEEDINGS 2012 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2012, : 41 - 46
  • [29] Traction control of an electric vehicle based on nonlinear observers
    Aligia, Diego A.
    Magallan, Guillermo A.
    De Angelo, Cristian H.
    REVISTA IBEROAMERICANA DE AUTOMATICA E INFORMATICA INDUSTRIAL, 2018, 15 (01): : 112 - 123
  • [30] Enhanced Fuzzy-MFC-based Traction Control System for Electric Vehicles
    Nguyen, Nam T.
    Ta, Minh C.
    Thanh Vo-Duy
    Ivanov, Valentin
    2023 IEEE VEHICLE POWER AND PROPULSION CONFERENCE, VPPC, 2023,