As one of the ideal switching devices in the field of power electronics, IGBT has been widely used in many fields. However, due to the long-term operation of IGBT in high voltage, high current and high frequency switching state, IGBT power consumption and junction temperature fluctuate frequently, which leads to temperature rise and thermal stress deformation, and ultimately leads to IGBT device fatigue aging. Based on the electrothermal model of IGBT and rain flow method are used to evaluate the fatigue aging of IGBT module. Finally, the statistical characteristics of junction temperature load are obtained and the life prediction of IGBT module was completed.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    IGBT Module Life Prediction Based on Rain Flow Method and Junction Temperature Analysis


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Qin, Yong (Herausgeber:in) / Jia, Limin (Herausgeber:in) / Liang, Jianying (Herausgeber:in) / Liu, Zhigang (Herausgeber:in) / Diao, Lijun (Herausgeber:in) / An, Min (Herausgeber:in) / Li, Xiaobing (Autor:in) / Zhou, Mingchao (Autor:in)

    Kongress:

    International Conference on Electrical and Information Technologies for Rail Transportation ; 2021 October 21, 2021 - October 23, 2021



    Erscheinungsdatum :

    23.02.2022


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    IGBT Module Life Prediction Based on Rain Flow Method and Junction Temperature Analysis

    Li, Xiaobing / Zhou, Mingchao | British Library Conference Proceedings | 2022



    Junction temperature calculation method of IGBT power module, motor controller and vehicle

    HUANG HUABO / CHU KANGKANG / RUAN OU et al. | Europäisches Patentamt | 2022

    Freier Zugriff

    IGBT Life Prediction Based on CNN1D-LSTM Hybrid Model

    Liu, Qiuli / Tong, Qingbin / Wang, Lei et al. | TIBKAT | 2022


    IGBT Life Prediction Based on CNN1D-LSTM Hybrid Model

    Liu, Qiuli / Tong, Qingbin / Wang, Lei et al. | British Library Conference Proceedings | 2022