With the intelligent and networked vehicles, the control of fused traffic information brings new opportunities for fuel cell vehicle energy optimization. In this paper, we use the vehicle-road cooperative system to collect traffic information, adopt dynamic programming (DP) to select the optimal green light passing time, complete the global optimal planning speed based on the quadratic planning algorithm, and the lower layer adopts dynamic planning to realize the power distribution among energy sources. Simulation results show that by co-optimizing the speed planning and energy management strategies, the hydrogen consumption of the vehicle is reduced by 32.3% compared to the original strategy.


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    Titel :

    Co-optimization of intelligent connected fuel cell vehicle powertrain based on networked scenario*


    Beteiligte:
    Yu, Hanzhengnan (Autor:in) / Chang, Liang (Autor:in) / Liu, Yu (Autor:in) / Zhang, Baodi (Autor:in)


    Erscheinungsdatum :

    27.10.2023


    Format / Umfang :

    3582770 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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