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A Flying Restart Strategy for Position Sensorless PMSM Driven by Quasi-Z-Source Inverter

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  • Yanfei Cao

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Shuxin Xiao

    (School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China)

  • Zhichen Lin

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

Abstract

The accurate estimation of rotor position and speed before flying restart is of great significance to improve the operation reliability of permanent magnet synchronous motor systems. The traditional multizero vector short-circuit method can improve the estimation accuracy of speed and rotor position, but the increased number of short-circuits reduces the electromagnetic torque response speed after the power supply recovers. In order to accurately estimate the initial speed and rotor position before the flying restart and effectively improve the electromagnetic torque response speed, a shoot-through zero vector short-circuit method based on quasi-Z-source inverter (qZSI) is proposed. This method breaks the limitation of regulating DC link voltage under the normal operation of the motor in the conventional methods, and puts forward a new idea of advancing the regulation of the DC link voltage to the stage of abnormal operation before the motor restarts. By designing the insertion mode of the mixed vectors and analyzing the action time of each vector before the flying restart, the accurate estimation of position and speed is realized and, meanwhile, the boost of the qZSI’s DC link voltage is achieved, thus giving the sensorless flying restart method a faster torque response speed for the PMSM system driven by qZSIs.

Suggested Citation

  • Yanfei Cao & Shuxin Xiao & Zhichen Lin, 2022. "A Flying Restart Strategy for Position Sensorless PMSM Driven by Quasi-Z-Source Inverter," Energies, MDPI, vol. 15(9), pages 1-15, May.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3469-:d:811870
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    References listed on IDEAS

    as
    1. Marcel Nicola & Claudiu-Ionel Nicola & Dan Selișteanu, 2022. "Improvement of PMSM Sensorless Control Based on Synergetic and Sliding Mode Controllers Using a Reinforcement Learning Deep Deterministic Policy Gradient Agent," Energies, MDPI, vol. 15(6), pages 1-30, March.
    2. Mohammad Zaid & Chang-Hua Lin & Shahrukh Khan & Javed Ahmad & Mohd Tariq & Arshad Mahmood & Adil Sarwar & Basem Alamri & Ahmad Alahmadi, 2021. "A Family of Transformerless Quadratic Boost High Gain DC-DC Converters," Energies, MDPI, vol. 14(14), pages 1-25, July.
    3. Dongliang Liu & Xinhua Guo & Youjian Lei & Rongkun Wang & Ruipei Chen & Fenyu Chen & Zhongshen Li, 2022. "An Improved Control Strategy of PMSM Drive System with Integrated Bidirectional DC/DC," Energies, MDPI, vol. 15(6), pages 1-16, March.
    4. Kifayat Ullah & Jaroslaw Guzinski & Adeel Feroz Mirza, 2022. "Critical Review on Robust Speed Control Techniques for Permanent Magnet Synchronous Motor (PMSM) Speed Regulation," Energies, MDPI, vol. 15(3), pages 1-13, February.
    5. Youssouf Mini & Ngac Ky Nguyen & Eric Semail & Duc Tan Vu, 2022. "Enhancement of Sensorless Control for Non-Sinusoidal Multiphase Drives-Part I: Operation in Medium and High-Speed Range," Energies, MDPI, vol. 15(2), pages 1-25, January.
    6. Ivan Grgić & Dinko Vukadinović & Mateo Bašić & Matija Bubalo, 2021. "Efficiency Boost of a Quasi-Z-Source Inverter: A Novel Shoot-Through Injection Method with Dead-Time," Energies, MDPI, vol. 14(14), pages 1-24, July.
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