Permanent magnet synchronous machines (PMSM) are widely used in the automobile industry (E.g. EV&HEV, EPS). However, an important problem of PMSMs is that its parasitic torques may degrade the performances of the drive system. In the vehicle, they bring uncomfortable feelings to passengers. These torque ripples generally vary periodically with the rotor position and lead to speed ripple. To suppress these speed ripples, an iterative learning control (ILC) is used, because it is a good candidate for dealing with periodical errors. In this paper, a new technique called "intelligent sensor bearing" is proposed and analyzed. Compared to the existed torque ripple reduction approaches which implement the current compensation calculation in the controller, this technique is realized by modifying the feedback speed information of sensor. ILC is integrated into this technique for computing the modified speed information. Simulation and experiment are used to check the effectiveness of this approach. Results prove this intelligent sensor technique has a good performance.


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    Titel :

    Intelligent Sensor Bearing for Torque Ripple Reduction


    Beteiligte:
    Yuan, Yi (Autor:in) / Hubert, Mathieu (Autor:in) / Moisy, Stephane (Autor:in) / Auger, Francois (Autor:in) / Loron, Luc (Autor:in)


    Erscheinungsdatum :

    2012


    Format / Umfang :

    10 Seiten





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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