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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    Title :

    Machine Learning to optimize Permanent Magnet Synchronous Machines


    Contributors:


    Publication date :

    2020-10-14


    Size :

    409738 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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