Wheel slipping of four-wheel independent drive electric vehicle on slope will reduce vehicle controllability and driving stability, thereby reducing vehicle safety. In order to solve the problem of wheel slipping and optimize the speed control performance of four-wheel independent drive electric vehicle on slope, an acceleration slip regulation control strategy of slope drive is proposed in this paper. First, we design a road identification algorithm to identify the current road conditions of the four-wheel independent drive electric vehicle, and calculate the optimal slip ratio of the current road surface by curve fitting method. Then, with the optimal slip ratio as the control objective, the acceleration slip regulation control strategy is designed to maximize the utilization of wheel adhesion coefficient to prevent wheel slip. Third, a slope identification algorithm based on Luenberger state observer is designed to identify the various slopes of the uphill and downhill road, after which a torque compensation algorithm is designed according to the identification slope, to compensate for the longitudinal component of vehicle gravity at different slopes. Fourth, a slope torque distribution algorithm is proposed based on acceleration slip regulation and slope identification. Finally, through the joint simulation platform of MATLAB/Simulink and CarSim, it is shown that the proposed control strategy can better restrain wheel slipping on the uphill and downhill road, and has better dynamic characteristics and stability.


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    Titel :

    A state observation and torque compensation–based acceleration slip regulation control approach for a four-wheel independent drive electric vehicle under slope driving


    Beteiligte:
    Guo, Luole (Autor:in) / Xu, Hongbing (Autor:in) / Zou, Jianxiao (Autor:in) / Jie, Hongyu (Autor:in) / Zheng, Gang (Autor:in)


    Erscheinungsdatum :

    01.10.2020


    Format / Umfang :

    16 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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