In order to enhance the performance of Hybrid Energy Storage Systems (HESS) for electric vehicles, an energy management strategy based on intelligent algorithm optimization rules is proposed in this paper. Firstly, the battery charging state and energy allocation rules, which are extracted from engineering experience and technical requirements, are regarded as the most significant factors in setting the thresholds. Secondly, given that fixed rules may not be suitable for complex and varied driving environments and vehicle states, the Particle Swarm Optimization (PSO) is introduced in this paper to dynamically adjust and optimize the threshold parameters in the initial rules. The combination of threshold parameters to optimize the performance of the system was found by an iterative search of the PSO. Finally, to verify the effectiveness of the proposed energy management strategy, we conducted simulation comparisons under various standard driving conditions. The results show that the energy management strategy based on intelligent algorithm optimization rules proposed in this paper can further improve the overall performance of electric vehicles. The energy economy of the electric vehicle is improved by 2.07%.


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    Title :

    Energy Management Strategy of Hybrid Energy Storage System Based on Intelligent Algorithm Optimization Rules


    Contributors:
    Mou, Hailan (author) / Wang, Chun (author) / Liu, Zijian (author)


    Publication date :

    2024-10-10


    Size :

    671945 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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