The backlash between engaging components in a driveline is inevitable and contributes to the nonlinearity of the driveline. The existing motor controllers of an electric vehicle usually ignore the backlash, which often brings impacts and vibration. This paper proposes an active driveline vibration controller for electric vehicles. A nonlinear driveline model considering backlash and wheel slip ratio is established in MATLAB/Simulink, and the results of bench test proved that the model could effectively reflect the transient dynamics of the electric driveline. Based on this model, a dual extended Kalman filter observer is designed to estimate both the system state variables and vehicle mass, which are essential information for the controller design. Then, a mode-switch model predictive controller based on two linearized models is proposed to alleviate the impacts and vibration caused by the transient change of motor torque. The proposed controller would identify whether the driveline is operating in “contact mode” or “backlash mode” and thus generates an optimal motor torque by solving a Quadratic Programing. Note that the control targets and model structures in two modes are different. Furthermore, a “pre-contact” method is proposed as an additional part to handle the condition when motor command torque is zero. Simulation results demonstrate that the proposed controller can effectively alleviate the impacts and vibration in the electric driveline while keeping the torque delay negligible. Moreover, the robustness of the proposed controller against estimation errors and system noises are discussed.


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    Titel :

    Mode-switch model predictive controller with “pre-contact” method for alleviating driveline vibration of electric vehicles considering backlash


    Beteiligte:
    Lu, Xingyang (Autor:in) / Lu, Tongli (Autor:in) / Chai, Benben (Autor:in)


    Erscheinungsdatum :

    2020-07-01


    Format / Umfang :

    19 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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