Journal of South China University of Technology (Natural Science Edition) ›› 2016, Vol. 44 ›› Issue (3): 76-80,88.doi: 10.3969/j.issn.1000-565X.2016.03.011

• Automotive Engineering • Previous Articles     Next Articles

Estimation of Vehicle State Parameters Based on Unscented Kalman Filtering

ZHAO Wan-zhong1,2 ZHANG Han1 WANG Chun-yan1   

  1. 1.College of Energy and Power Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,Jiangsu,China; 2.State Key Laboratory of Mechanical System and Vibration,Shanghai Jiaotong University,Shanghai 200240,China
  • Received:2015-04-28 Revised:2015-09-09 Online:2016-03-25 Published:2016-02-02
  • Contact: 赵万忠(1982-)，男，博士，教授，主要从事汽车系统动力学及控制研究． E-mail:zhaowanzhong@126.com
  • About author:赵万忠(1982-)，男，博士，教授，主要从事汽车系统动力学及控制研究．
  • Supported by:
    Supported by the National Natural Science Foundation of China(51375007)

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Abstract: In order to improve the estimation accuracy of some vehicle state parameters that can not be obtained by sensors directly and thus to estimate the state variation of running vehicles accurately,a method on the basis of un- scented Kalman filtering (UKF) is proposed,which helps enhance the robustness of vehicle control system.In this method,an UKF algorithm on the basis of traditional Kalman filtering is developed to estimate such vehicle state parameters as side slip angle,yaw rate and road adhesion coefficient,and a simulation by using both Simulink and Carsim software is carried out.The results indicate that the proposed UKF is superior to the extended Kalman filte- ring for its short response time and high estimation accuracy.Thus，it can meet the requirements of advanced dy- namic control system of vehicles.

Key words: unscented Kalman filtering, parameter estimation, side slip angle, yaw rate, road adhesion coefficient