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Sensorless Control for IPMSM Based on Adaptive Super-Twisting Sliding-Mode Observer and Improved Phase-Locked Loop

Author

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  • Shuo Chen

    (School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221116, China)

  • Xiao Zhang

    (School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221116, China)

  • Xiang Wu

    (School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221116, China)

  • Guojun Tan

    (School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221116, China)

  • Xianchao Chen

    (Xuzhou Yirui Construction Machinery Co. Ltd., Xuzhou 221000, China)

Abstract

In traditional sensorless control of the interior permanent magnet synchronous motors (IPMSMs) for medium and high speed domains, a control strategy based on a sliding-mode observer (SMO) and phase-locked loop (PLL) is widely applied. A new strategy for IPMSM sensorless control based on an adaptive super-twisting sliding-mode observer and improved phase-locked loop is proposed in this paper. A super-twisting sliding-mode observer (STO) can eliminate the chattering problem without low-pass filters (LPFs), which is an effective method to obtain the estimated back electromotive forces (EMFs). However, the constant sliding-mode gains in STO may cause instability in the high speed domain and chattering in the low speed domain. The speed-related adaptive gains are proposed to achieve the accurate estimation of the observer in wide speed range and the corresponding stability is proved. When the speed of IPMSM is reversed, the traditional PLL will lose its accuracy, resulting in a position estimation error of 180°. The improved PLL based on a simple strategy for signal reconstruction of back EMF is proposed to ensure that the motor can realize the direction switching of speed stably. The proposed strategy is verified by experimental testing with a 60-kW IPMSM sensorless drive.

Suggested Citation

  • Shuo Chen & Xiao Zhang & Xiang Wu & Guojun Tan & Xianchao Chen, 2019. "Sensorless Control for IPMSM Based on Adaptive Super-Twisting Sliding-Mode Observer and Improved Phase-Locked Loop," Energies, MDPI, vol. 12(7), pages 1-19, March.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:7:p:1225-:d:218359
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    References listed on IDEAS

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    1. Ming-Shyan Wang & Tse-Ming Tsai, 2017. "Sliding Mode and Neural Network Control of Sensorless PMSM Controlled System for Power Consumption and Performance Improvement," Energies, MDPI, vol. 10(11), pages 1-15, November.
    2. Lisi Tian & Jin Zhao & Jiajiang Sun, 2016. "Sensorless Control of Interior Permanent Magnet Synchronous Motor in Low-Speed Region Using Novel Adaptive Filter," Energies, MDPI, vol. 9(12), pages 1-18, December.
    3. Yuanlin Wang & Xiaocan Wang & Wei Xie & Manfeng Dou, 2018. "Full-Speed Range Encoderless Control for Salient-Pole PMSM with a Novel Full-Order SMO," Energies, MDPI, vol. 11(9), pages 1-14, September.
    4. Shun Li & Xinxiu Zhou, 2018. "Sensorless Energy Conservation Control for Permanent Magnet Synchronous Motors Based on a Novel Hybrid Observer Applied in Coal Conveyer Systems," Energies, MDPI, vol. 11(10), pages 1-23, September.
    5. Kyoung Jin Joo & Joon Sung Park & Ju Lee, 2018. "Study on Reduced Cost of Non-Salient Machine System Using MTPA Angle Pre-Compensation Method Based on EEMF Sensorless Control," Energies, MDPI, vol. 11(6), pages 1-14, June.
    6. Tae-Uk Jung & Jung-Hoon Jang & Chang-Seok Park, 2017. "A Back-EMF Estimation Error Compensation Method for Accurate Rotor Position Estimation of Surface Mounted Permanent Magnet Synchronous Motors," Energies, MDPI, vol. 10(8), pages 1-16, August.
    7. Younghoon Cho, 2016. "Improved Sensorless Control of Interior Permanent Magnet Sensorless Motors Using an Active Damping Control Strategy," Energies, MDPI, vol. 9(3), pages 1-15, February.
    8. Joon B. Park & Xin Wang, 2018. "Sensorless Direct Torque Control of Surface-Mounted Permanent Magnet Synchronous Motors with Nonlinear Kalman Filtering," Energies, MDPI, vol. 11(4), pages 1-19, April.
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    Cited by:

    1. Junlei Chen & Shuo Chen & Xiang Wu & Guojun Tan & Jianqi Hao, 2019. "A Super-Twisting Sliding-Mode Stator Flux Observer for Sensorless Direct Torque and Flux Control of IPMSM," Energies, MDPI, vol. 12(13), pages 1-17, July.
    2. Michał Gwóźdź & Łukasz Ciepliński, 2021. "An Algorithm for Calculation and Extraction of the Grid Voltage Component," Energies, MDPI, vol. 14(16), pages 1-12, August.
    3. Jongwon Choi, 2021. "Regression Model-Based Flux Observer for IPMSM Sensorless Control with Wide Speed Range," Energies, MDPI, vol. 14(19), pages 1-18, October.
    4. Yujiao Zhao & Haisheng Yu & Shixian Wang, 2021. "An Improved Super-Twisting High-Order Sliding Mode Observer for Sensorless Control of Permanent Magnet Synchronous Motor," Energies, MDPI, vol. 14(19), pages 1-18, September.
    5. Habib Benbouhenni & Nicu Bizon, 2021. "Third-Order Sliding Mode Applied to the Direct Field-Oriented Control of the Asynchronous Generator for Variable-Speed Contra-Rotating Wind Turbine Generation Systems," Energies, MDPI, vol. 14(18), pages 1-20, September.

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