To overcome the shortcoming that vehicles with multiple steering modes need to switch steering modes at parking or very low speeds, a dynamic switch method of steering modes based on MOEA/D (Multi-objective Evolutionary Algorithm Based on Decomposition) was proposed for 4WID-4WIS (Four Wheel Independent Drive-Four Wheel Independent Steering) electric vehicle, considering the smoothness of dynamic switch, the lateral stability of the vehicle and the energy economy of tires. First of all, the vehicle model of 4WID-4WIS was established, and steering modes were introduced and analyzed. Secondly, the conditions for the dynamic switch of steering modes were designed with the goal of stability and safety. According to different constraints, the control strategy was formulated to obtain the target angle of the active wheels. Then aiming at the smoothness of the dynamic switch, the active wheel angle trajectory was constructed based on the B-spline theory. And the MOEA/D algorithm was used to carry out multi-objective optimization of the trajectory to obtain the Pareto optimal solution set. The optimal active wheel angle switch trajectory was decided by TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) decision-making model. Last but not least, in the Simulink-CarSim co-simulation environment, the results of wheel angle, yaw rate, and sideslip angle were compared under different control strategies. The proposed control strategy achieved smoother dynamic switch of steering modes and ensured better handling stability, thus verifying the effectiveness of the strategy.


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    Titel :

    Dynamic Switch Control of Steering Modes for 4WID-4WIS Electric Vehicle Based on MOEA/D Optimization


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:
    Li, Ran (Autor:in) / Chen, Xinbo (Autor:in) / Qiao, Yiran (Autor:in)

    Kongress:

    WCX SAE World Congress Experience ; 2023



    Erscheinungsdatum :

    11.04.2023




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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