It is difficult to obtain state variables accurately or economically while vehicle is moving, however these state variables are significant for chassis control. Although many researches have been done, a complex model always leads to a control system with poor real-time performance, while simple model cannot show the real characteristics. So, in order to estimate the value of yaw rate and side slip angle accurately and sententiously, an Extended Kalman Filter (EKF) observer is proposed, which is based on an ameliorated 2-DOF “bicycle model”. The EKF algorithm is achieved numerically and verified by the results from the real field test.


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    Title :

    Numerical Achieved Extended Kalman Filter State Observer Design Based on a Vehicle Model Containing UniTire Model


    Additional title:

    Sae Technical Papers


    Contributors:
    Zong, Changfu (author) / Hu, Dan (author) / Zheng, Hongyu (author) / Wu, Kan (author) / Zhao, Pan (author)

    Conference:

    2008 SAE International Powertrains, Fuels and Lubricants Congress ; 2008



    Publication date :

    2008-06-23




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English





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