In this paper, we offer a possible approach to estimating motor parameters: Machine Learning. We begin with a simulation of a Permanent Magnet Synchronous Motor (PMSM) model using MATLAB and Simulink. We measure the voltage and current and then send the data to a machine learning model (TensorFlow). From there, we discuss the accuracy of the estimations and future stages of the project. We also use machine learning method to estimate position and speed.


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    Titel :

    Machine Learning to optimize Permanent Magnet Synchronous Machines


    Beteiligte:
    Ma, Zhuoren (Autor:in) / Arteaga, Ryan (Autor:in) / Wang, Muxuan (Autor:in) / Silveira, Christine (Autor:in)


    Erscheinungsdatum :

    14.10.2020


    Format / Umfang :

    409738 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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