Journal of South China University of Technology (Natural Science Edition) ›› 2014, Vol. 42 ›› Issue (8): 129-135.doi: 10.3969/j.issn.1000-565X.2014.08.020

• Traffic & Transportation Engineering • Previous Articles     Next Articles

Estimation of Vehicle State and Ｒoad Adhesion Coefficient Based on Kalman Filter

Li Gang1 Xie Ｒui-chun2 Li Ning2 Zong Chang-fu1   

  1. 1.State Key Laboratory of Automotive Simulation and Control,Jilin University,Changchun 130025,Jilin,China;2.College of Automobile ＆ Transportating Engineering,Liaoning University of Technology,Jinzhou 121001,Liaoning,China
  • Received:2014-04-08 Revised:2014-07-14 Online:2014-08-25 Published:2014-07-01
  • Contact: 宗长富(1962-)，男，教授，博士生导师，主要从事汽车动态仿真与控制研究． E-mail:378811297@qq.com
  • About author:李刚(1979-)，男，博士生，辽宁工业大学副教授，主要从事汽车动态仿真与控制研究． E-mail:lnitligang@126．com
  • Supported by:

    国家自然科学基金青年基金资助项目( E51305190) ; 辽宁省教育厅项目( L2013253) ; 吉林大学汽车仿真与控制国家重点实验室开放基金资助项目( 20111104)

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Abstract:

First,a three-degrees-of-freedom nonlinear estimation model for vehicles is established based on theDugoff tire model.Then,a vehicle driving state estimation algorithm based on the federal Kalman filter and a roadadhesion coefficient estimation algorithm based on the extended Kalman filter are designed to bring about the closedloopfeedback and the linkages between the vehicle state estimation and the road adhesion coefficient estimation.Finally,the estimation algorithms of vehicle driving state and road adhesion are verified by adopting a typical situationbased on Carsim and Matlab /Simulink co-simulation.The results show that the proposed algorithms can accuratelyestimate the vehicle state and the road adhesion coefficient.

Key words: federal Kalman filter, Dugoff tire model, vehicle state estimation, road adhesion coefficient

CLC Number: