As a new force in the automotive industry, new energy electric vehicles are deeply loved by the broad masses of the people. As the "heart" of electric vehicles and the power core of automobile driving, the performance of the drive motor system is directly or indirectly related to travel safety and has a negative impact on individuals and society. Based on BP neural network algorithm, this paper studies the fault diagnosis of electric vehicle drive motor system and realizes the identification and judgment of fault mode of drive motor system through BP neural network algorithm, so as to improve the efficiency of fault diagnosis. And it can realize fault early warning to a certain extent, detect faults in time at the beginning of the fault, and then reduce unnecessary losses.


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    Titel :

    Fault diagnosis of electric vehicle drive motor system based on BP neural network algorithm


    Beteiligte:
    Khan, Zeashan Hameed (Herausgeber:in) / Balas, Valentina E. (Herausgeber:in) / Luo, Dengming (Autor:in) / Gao, Yanan (Autor:in) / Xia, Faying (Autor:in)

    Kongress:

    International Conference on Electronic Information Engineering and Data Processing (EIEDP 2023) ; 2023 ; Nanchang, China


    Erschienen in:

    Proc. SPIE ; 12700


    Erscheinungsdatum :

    26.05.2023





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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