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Research on a Variable-Leakage-Flux Permanent Magnet Motor Control System Based on an Adaptive Tracking Estimator

Author

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  • Xiaolei Cai

    (School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China)

  • Qixuan Wang

    (School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China)

  • Yucheng Wang

    (State Grid Zhenjiang Power Supply Company, Zhenjiang 212013, China)

  • Li Zhang

    (School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, China)

Abstract

Due to the characteristics of inductance parameter mismatch and back electromotive force harmonics caused by novel leakage flux branches and other non-ideal factors for the variable-leakage-flux permanent magnet (VLF-PM) motor, its control system suffers from a deteriorated performance of the rotor position estimation. To overcome the problems mentioned above, an adaptive tracking estimator of the rotor position is proposed in this paper for the VLF-PM motor control system. First, the proposed method simplifies the VLF-PM motor mathematical model and reduces the effect of inductance parameter variations according to the active flux concept. Then, robust and gradient descent algorithms are utilized to maintain the robustness of inductance parameter variations and eliminate the specific order harmonics owing to the novel leakage flux branches. Meanwhile, the accuracy and stability are enhanced. Furthermore, the position compensation based on the current adaptive tracking strategy is proposed to compensate the rotor position error caused by other non-ideal factors. Finally, the feasibility of the proposed estimated system is verified.

Suggested Citation

  • Xiaolei Cai & Qixuan Wang & Yucheng Wang & Li Zhang, 2023. "Research on a Variable-Leakage-Flux Permanent Magnet Motor Control System Based on an Adaptive Tracking Estimator," Energies, MDPI, vol. 16(2), pages 1-16, January.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:2:p:587-:d:1024659
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    References listed on IDEAS

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    1. Shuang Wang & Jianfei Zhao & Kang Yang, 2019. "High Frequency Square-Wave Voltage Injection Scheme-Based Position Sensorless Control of IPMSM in the Low- and Zero- Speed Range," Energies, MDPI, vol. 12(24), pages 1-21, December.
    2. Qiushi Zhang & Ying Fan, 2022. "The Online Parameter Identification Method of Permanent Magnet Synchronous Machine under Low-Speed Region Considering the Inverter Nonlinearity," Energies, MDPI, vol. 15(12), pages 1-17, June.
    3. Anton Dianov & Alecksey Anuchin, 2020. "Adaptive Maximum Torque per Ampere Control of Sensorless Permanent Magnet Motor Drives," Energies, MDPI, vol. 13(19), pages 1-13, September.
    4. Yubo Liu & Junlong Fang & Kezhu Tan & Boyan Huang & Wenshuai He, 2020. "Sliding Mode Observer with Adaptive Parameter Estimation for Sensorless Control of IPMSM," Energies, MDPI, vol. 13(22), pages 1-18, November.
    5. Zhiyong Li & Xin Wang & Guohang Huang & Hui Wan & Yougen Chen, 2020. "Ripple Analysis and Suppression Method Research of Direct Drive Permanent Magnet Synchronous Wind Turbine under Wind Shear," Energies, MDPI, vol. 13(19), pages 1-15, September.
    6. Yunfei Zhang & Can Zhao & Bin Dai & Zhiheng Li, 2022. "Dynamic Simulation of Permanent Magnet Synchronous Motor (PMSM) Electric Vehicle Based on Simulink," Energies, MDPI, vol. 15(3), pages 1-16, February.
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    Cited by:

    1. Tayyaba Nosheen & Ahsan Ali & Muhammad Umar Chaudhry & Dmitry Nazarenko & Inam ul Hasan Shaikh & Vadim Bolshev & Muhammad Munwar Iqbal & Sohail Khalid & Vladimir Panchenko, 2023. "A Fractional Order Controller for Sensorless Speed Control of an Induction Motor," Energies, MDPI, vol. 16(4), pages 1-15, February.

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