Considering the fact that the existing fault diagnosis algorithms for modular multilevel converter (MMC) have drawbacks in the measurement interference and large requirement for sensors, the fault diagnosis algorithm for sub-module open-circuit fault in MMC on the basis of model prediction is studied in this paper. On analyzing the fault characteristics, two different prediction models are established to predict the output voltage of bridge arms according to the current signal measured by two current sensors in MMC. And the residual between the predicted voltage values of two models is used for fault detection. Then, by combining the periodic trends in open-circuit fault characteristics with the statistical analysis of switch state sequence, a fault location method is proposed. Finally, the effectiveness and feasibility of the proposed fault diagnosis method are verified by simulation and low-power MMC experimental system testing.


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    Titel :

    IGBT Open-Circuit Fault Diagnosis for MMC Based on Model Prediction


    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) / Zhu, Qinyue (Autor:in) / Li, Daquan (Autor:in) / Tan, Xitang (Autor:in) / Huang, Xiuhan (Autor:in)

    Kongress:

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



    Erscheinungsdatum :

    2022-02-23


    Format / Umfang :

    11 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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