The electric drive system relies on high-power generators to meet the electric energy required for vehicle driving and combat, which has become an important prerequisite for the development of future all-electric tanks. In this paper, the control parameters optimization research is carried out on how to improve the control accuracy and stability of the steering control strategy of electric tracked vehicles. The steering control strategy of series hybrid dual-motor coupling drive tracked vehicle based on active disturbance rejection control (ADRC) designed by myself is partially improved, and a control parameter optimization algorithm based on particle swarm optimization (PSO) is designed. The integral of time multiplied by the absolute value of error criterion (ITAE) is used as the particle swarm optimization algorithm evaluation function to optimize the key control parameters in the steering control strategy to realize the optimization output of the tracked vehicle steering control system. Matlab/Simulink and Speedgoat semi-physical simulation platform are used to verify the steering control strategy before and after parameter optimization. The comparative test results verify the effectiveness of this parameter optimization.


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    Title :

    Parameter Optimization of Tracked Vehicle Steering Control Strategy Based on Particle Swarm Optimization Algorithm


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Jia, Yingmin (editor) / Zhang, Weicun (editor) / Fu, Yongling (editor) / Wang, Jiqiang (editor) / Wang, Yunfeng (author) / Li, Hongcai (author) / Ma, Yue (author) / Hou, Xuzhao (author)

    Conference:

    Chinese Intelligent Systems Conference ; 2023 ; Ningbo, China October 14, 2023 - October 15, 2023



    Publication date :

    2023-10-08


    Size :

    15 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English