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Nonlinear Modelling, Flatness-Based Current Control, and Torque Ripple Compensation for Interior Permanent Magnet Synchronous Machines

Author

Listed:
  • Felix Veeser

    (Commercial Vehicle Technology, ZF Friedrichshafen AG, 88045 Friedrichshafen, Germany
    These authors contributed equally to this work.)

  • Tristan Braun

    (Corporate Research and Development, ZF Friedrichshafen AG, 88046 Friedrichshafen, Germany
    These authors contributed equally to this work.)

  • Lothar Kiltz

    (Corporate Research and Development, ZF Friedrichshafen AG, 88046 Friedrichshafen, Germany
    These authors contributed equally to this work.)

  • Johannes Reuter

    (Institute of System Dynamics (ISD), HTWG Konstanz—University of Applied Sciences, 78462 Konstanz, Germany)

Abstract

A nonlinear mathematical model for the dynamics of permanent magnet synchronous machines with interior magnets is discussed. The model of the current dynamics captures saturation and dependency on the rotor angle. Based on the model, a flatness-based field-oriented closed-loop controller and a feed-forward compensation of torque ripples are derived. Effectiveness and robustness of the proposed algorithms are demonstrated by simulation results.

Suggested Citation

  • Felix Veeser & Tristan Braun & Lothar Kiltz & Johannes Reuter, 2021. "Nonlinear Modelling, Flatness-Based Current Control, and Torque Ripple Compensation for Interior Permanent Magnet Synchronous Machines," Energies, MDPI, vol. 14(6), pages 1-14, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:6:p:1590-:d:516149
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    References listed on IDEAS

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    1. Myeong-Hwan Hwang & Jong-Ho Han & Dong-Hyun Kim & Hyun-Rok Cha, 2018. "Design and Analysis of Rotor Shapes for IPM Motors in EV Power Traction Platforms," Energies, MDPI, vol. 11(10), pages 1-12, September.
    2. Gorazd Štumberger & Bojan Štumberger & Tine Marčič, 2019. "Magnetically Nonlinear Dynamic Models of Synchronous Machines and Experimental Methods for Determining Their Parameters," Energies, MDPI, vol. 12(18), pages 1-22, September.
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    Cited by:

    1. Marcin Jastrzębski & Jacek Kabziński, 2021. "Approximation of Permanent Magnet Motor Flux Distribution by Partially Informed Neural Networks," Energies, MDPI, vol. 14(18), pages 1-21, September.
    2. Songklod Sriprang & Nitchamon Poonnoy & Damien Guilbert & Babak Nahid-Mobarakeh & Noureddine Takorabet & Nicu Bizon & Phatiphat Thounthong, 2021. "Design, Modeling, and Differential Flatness Based Control of Permanent Magnet-Assisted Synchronous Reluctance Motor for e-Vehicle Applications," Sustainability, MDPI, vol. 13(17), pages 1-19, August.

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