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State-Space Approach for SPMSM Sensorless Passive Algorithm Tuning

Author

Listed:
  • Lorenzo Carbone

    (Department of Electrical, Electronic, Tlc Engineering and Naval Architecture (DITEN), University of Genova, Via all’Opera Pia 11a, 16145 Genova, Italy)

  • Simone Cosso

    (Department of Electrical, Electronic, Tlc Engineering and Naval Architecture (DITEN), University of Genova, Via all’Opera Pia 11a, 16145 Genova, Italy)

  • Mario Marchesoni

    (Department of Electrical, Electronic, Tlc Engineering and Naval Architecture (DITEN), University of Genova, Via all’Opera Pia 11a, 16145 Genova, Italy)

  • Massimiliano Passalacqua

    (Department of Electrical, Electronic, Tlc Engineering and Naval Architecture (DITEN), University of Genova, Via all’Opera Pia 11a, 16145 Genova, Italy)

  • Luis Vaccaro

    (Department of Electrical, Electronic, Tlc Engineering and Naval Architecture (DITEN), University of Genova, Via all’Opera Pia 11a, 16145 Genova, Italy)

Abstract

Sensorless algorithms for Permanent Magnet Synchronous Motors (PMSM) have achieved increasing interest in the technical literature over the last few years. They can be divided into active methods and passive methods: the first inject high-frequency signals exploiting rotor anisotropy, whereas the second are based on observers. Recently, a sensorless control based on a rotor flux observer has been presented in the technical literature, which gives very accurate results in terms of rotor position estimation and robustness. In this paper, the aforementioned observer is considered and a procedure for choosing stabilizing gains of the observer is proposed. The contribution of the paper is three-fold: the mathematical modelling of the rotor flux observer, the methodology for the definition of the observer gains, and the presentation of the experimental results.

Suggested Citation

  • Lorenzo Carbone & Simone Cosso & Mario Marchesoni & Massimiliano Passalacqua & Luis Vaccaro, 2021. "State-Space Approach for SPMSM Sensorless Passive Algorithm Tuning," Energies, MDPI, vol. 14(21), pages 1-11, November.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:21:p:7180-:d:670293
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    References listed on IDEAS

    as
    1. Justas Dilys & Voitech Stankevič & Krzysztof Łuksza, 2021. "Implementation of Extended Kalman Filter with Optimized Execution Time for Sensorless Control of a PMSM Using ARM Cortex-M3 Microcontroller," Energies, MDPI, vol. 14(12), pages 1-16, June.
    2. Danyang Bao & Huiming Wu & Ruiqi Wang & Fei Zhao & Xuewei Pan, 2020. "Full-Order Sliding Mode Observer Based on Synchronous Frequency Tracking Filter for High-Speed Interior PMSM Sensorless Drives," Energies, MDPI, vol. 13(24), pages 1-19, December.
    3. Jaime Pando-Acedo & Enrique Romero-Cadaval & Maria Isabel Milanes-Montero & Fermin Barrero-Gonzalez, 2020. "Improvements on a Sensorless Scheme for a Surface-Mounted Permanent Magnet Synchronous Motor Using Very Low Voltage Injection," Energies, MDPI, vol. 13(11), pages 1-17, May.
    4. Michal Gierczynski & Lech M. Grzesiak, 2021. "Comparative Analysis of the Steady-State Model Including Non-Linear Flux Linkage Surfaces and the Simplified Linearized Model when Applied to a Highly-Saturated Permanent Magnet Synchronous Machine—Ev," Energies, MDPI, vol. 14(9), pages 1-20, April.
    Full references (including those not matched with items on IDEAS)

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