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Adaptive Maximum Torque per Ampere Control of Sensorless Permanent Magnet Motor Drives

Author

Listed:
  • Anton Dianov

    (Home Appliances Division, Samsung Electronics, Suwon 16677, Korea)

  • Alecksey Anuchin

    (Electric Drives Department, Moscow Power Engineering Institute, 111250 Moscow, Russia)

Abstract

Interior permanent magnet synchronous motor (IPMSM) efficiency can be improved by using maximum torque per ampere control (MTPA). MTPA control utilizes both alignment and reluctance torques and usually requires information about the magnetization map of the electrical machine. This paper proposes an adaptive MTPA algorithm for sensorless control systems of IPMSM drives, which is applicable in industrial and commercial drives. This algorithm enhances conventional control schemes, where the output of the speed controller is the commanded stator current and the direct current is calculated using an MTPA equation; therefore, it can be easily implemented in the previously developed drives. The proposed algorithm does not use any motor parameters for the calculation of the MTPA trajectory, which is important for systems operating in changing environmental conditions, because motor inductances and flux linkage strongly depend on the stator current and the rotor temperature, respectively. The proposed algorithm continuously varies the current phase and in such a way it tries to minimize the magnitude of the stator current at the applied load torque. The main contribution of this paper is the development of a technique to overcome the main disadvantage of seeking algorithms–the necessity of a precision information about the rotor position. The proposed method was verified experimentally.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:19:p:5071-:d:420533
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    References listed on IDEAS

    as
    1. Mengting Ye & Tingna Shi & Huimin Wang & Xinmin Li & Changliang Xia, 2019. "Sensorless-MTPA Control of Permanent Magnet Synchronous Motor Based on an Adaptive Sliding Mode Observer," Energies, MDPI, vol. 12(19), pages 1-15, October.
    2. Jianxia Sun & Cheng Lin & Jilei Xing & Xiongwei Jiang, 2019. "Online MTPA Trajectory Tracking of IPMSM Based on a Novel Torque Control Strategy," Energies, MDPI, vol. 12(17), pages 1-10, August.
    3. 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.
    4. Seung-Koo Baek & Hyuck-Keun Oh & Joon-Hyuk Park & Yu-Jeong Shin & Seog-Won Kim, 2019. "Evaluation of Efficient Operation for Electromechanical Brake Using Maximum Torque per Ampere Control," Energies, MDPI, vol. 12(10), pages 1-13, May.
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    Cited by:

    1. Anton Dianov & Alecksey Anuchin, 2021. "Design of Constraints for Seeking Maximum Torque per Ampere Techniques in an Interior Permanent Magnet Synchronous Motor Control," Mathematics, MDPI, vol. 9(21), pages 1-21, November.
    2. 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.
    3. Anton Rassõlkin & Kari Tammi & Galina Demidova & Hassan HosseinNia, 2022. "Mechatronics Technology and Transportation Sustainability," Sustainability, MDPI, vol. 14(3), pages 1-3, January.
    4. Marcin Jastrzębski & Jacek Kabziński, 2021. "Approximation of Permanent Magnet Motor Flux Distribution by Partially Informed Neural Networks," Energies, MDPI, vol. 14(18), pages 1-21, September.

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