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Field Weakening Operation Control Strategies of PMSM Based on Feedback Linearization

Author

Listed:
  • Kai Zhou

    (Engineering Research Center of Automotive Electronics Drive Control and System Integration, Ministry of Education. Harbin University of Science and Technology, Harbin 150080, China)

  • Min Ai

    (Engineering Research Center of Automotive Electronics Drive Control and System Integration, Ministry of Education. Harbin University of Science and Technology, Harbin 150080, China)

  • Dongyang Sun

    (Engineering Research Center of Automotive Electronics Drive Control and System Integration, Ministry of Education. Harbin University of Science and Technology, Harbin 150080, China)

  • Ningzhi Jin

    (Engineering Research Center of Automotive Electronics Drive Control and System Integration, Ministry of Education. Harbin University of Science and Technology, Harbin 150080, China)

  • Xiaogang Wu

    (Engineering Research Center of Automotive Electronics Drive Control and System Integration, Ministry of Education. Harbin University of Science and Technology, Harbin 150080, China)

Abstract

Based on current research into the mathematical model of the permanent magnet synchronous motor (PMSM) and the feedback linearization theory, a control strategy established upon feedback linearization is proposed. The Lie differential operation is performed on the output variable to obtain the state feedback of the nonlinear system, and the dynamic characteristics of the original system are transformed into linear dynamic characteristics. A current controller based on the input–output feedback linearization algorithm is designed to realize the input–output linearization control of the PMSM. The current controller decouples the d–q axis current from the flux linkage information of the motor and outputs a control voltage. When the motor speed reaches above the base speed, the field-forward and straight-axis current components are newly distributed to achieve field weakening control, which can realize the smooth transition between the constant torque region and weak magnetic region. Simulation and experimental results show the feasibility and viability of the strategy.

Suggested Citation

  • Kai Zhou & Min Ai & Dongyang Sun & Ningzhi Jin & Xiaogang Wu, 2019. "Field Weakening Operation Control Strategies of PMSM Based on Feedback Linearization," Energies, MDPI, vol. 12(23), pages 1-18, November.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:23:p:4526-:d:291700
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    References listed on IDEAS

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    1. Xin Gu & Tao Li & Xinmin Li & Guozheng Zhang & Zhiqiang Wang, 2019. "An Improved UDE-Based Flux-Weakening Control Strategy for IPMSM," Energies, MDPI, vol. 12(21), pages 1-17, October.
    2. Weiwei Gu & Xiaoyong Zhu & Li Quan & Yi Du, 2015. "Design and Optimization of Permanent Magnet Brushless Machines for Electric Vehicle Applications," Energies, MDPI, vol. 8(12), pages 1-13, December.
    3. Kai Zhou & Min Ai & Yancheng Sun & Xiaogang Wu & Ran Li, 2019. "PMSM Vector Control Strategy Based on Active Disturbance Rejection Controller," Energies, MDPI, vol. 12(20), pages 1-19, October.
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    Cited by:

    1. Jie Chen & Jiajun Wang & Bo Yan, 2022. "Simulation Research on Deadbeat Direct Torque and Flux Control of Permanent Magnet Synchronous Motor," Energies, MDPI, vol. 15(9), pages 1-15, April.
    2. Lu Liu & Yun Zeng, 2023. "Intelligent ISSA-Based Non-Singular Terminal Sliding-Mode Control of DC–DC Boost Converter Feeding a Constant Power Load System," Energies, MDPI, vol. 16(13), pages 1-23, June.
    3. Grzegorz Sieklucki & Dawid Kara, 2022. "Design and Modelling of Energy Conversion with the Two-Region Torque Control of a PMSM in an EV Powertrain," Energies, MDPI, vol. 15(13), pages 1-18, July.
    4. Yang Liu & Jin Zhao & Quan Yin, 2021. "Model-Based Predictive Rotor Field-Oriented Angle Compensation for Induction Machine Drives," Energies, MDPI, vol. 14(8), pages 1-13, April.
    5. Chao Wu & Jun Yang & Qi Li, 2020. "GPIO-Based Nonlinear Predictive Control for Flux-Weakening Current Control of the IPMSM Servo System," Energies, MDPI, vol. 13(7), pages 1-21, April.
    6. Li Yang & Fuzhao Yang & Weitao Sheng & Kun Zhou & Tianmin Huang, 2021. "Fuzzy Chaos Control of Fractional Order D-PMSG for Wind Turbine with Uncertain Parameters by State Feedback Design," Energies, MDPI, vol. 14(21), pages 1-15, November.

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