Currently, traditional hybrid electric vehicles are not true clean, and more efforts are taken to develop fuel cell/battery hybrid vehicles (FCHVs). However, there are power matching problems on multi power supply system, including the degree of hybridization (DOH) design. In last decade, many research works of DOH design were devoted to optimizing the vehicle's fuel economy, but the vehicle cost and dynamic performance were mostly neglected. In this paper, a multiobjective optimization design method based on particle swarm optimization (PSO) algorithm is proposed to optimize the vehicle cost and fuel economy on the premise of meeting vehicle dynamic performance. Combined with a simulation platform, the algorithm can automatically search the optimal solution in the entire reasonable range of the DOH. As a result, an optimal hybrid scheme of the FCHV was obtained. The research results of this paper provide basis for the powertrain design of FCHVs.


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    Title :

    Degree of Hybridization Design for a Fuel Cell/Battery Hybrid Electric Vehicle Based on Multi-objective Particle Swarm Optimization


    Contributors:
    Song, Ke (author) / Liu, Luoxiang (author) / Li, Feiqiang (author) / Feng, Cong (author)


    Publication date :

    2019-09-01


    Size :

    525144 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English