In order to solve the reliability problem of DC-link capacitor, a capacitor active design method based on deep learning is proposed. Staring from the introduction of two test case, the electrical parameters of film capacitor are collected and the lifetime expectancy of the capacitors is solved. A deep learning network model is established through the Deep Neural Network. The model can quickly and accurately map the performance parameters of capacitors to the volume, cost and lifetime expectancy of the selected dc-link capacitors, and realize the selection and design of the DC-link film capacitor in the traction drive system.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Active Design Aided Deep Learning for Reliability of DC-Link Capacitor in Traction Drive System


    Contributors:
    Yao, Bo (author) / Ge, Xinglai (author) / Shu, Lingzhou (author) / Zhang, Yichi (author) / Wang, Huiming (author) / Gou, Bin (author)


    Publication date :

    2019-05-01


    Size :

    1333054 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    Double layer capacitor for EV hybrid traction drive

    Trippe,A.P. / Blank,E. / Maxwell Laboratories,US | Automotive engineering | 1992


    Computer-aided design system for electric-locomotive traction motors

    Sedov, V.I. / Shcherbakov, V.G. | Tema Archive | 1986


    Traction drive cooling system

    DIETRICH ROBERT ALAN / WHITE STEPHEN L / GANEV EVGENI | European Patent Office | 2022

    Free access

    Hydrostatic traction drive system

    WIERTELLOK MARKUS / KRAFT WOLFGANG | European Patent Office | 2018

    Free access