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Online MTPA Trajectory Tracking of IPMSM Based on a Novel Torque Control Strategy

Author

Listed:
  • Jianxia Sun

    (School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China)

  • Cheng Lin

    (School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China)

  • Jilei Xing

    (School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China)

  • Xiongwei Jiang

    (School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China)

Abstract

The maximum-torque-per-ampere (MTPA) scheme is widely used in the interior permanent magnet synchronous machine (IPMSM) drive system to reduce copper losses. However, MTPA trajectory is complicated to solve analytically. In order to realize online MTPA trajectory tracking, this paper proposes a novel torque control strategy. The torque control is designed to be closed form. Considering the machine reluctance torque as the torque feedback, when this is compared with the torque reference, then the excitation torque reference can be obtained. Since the excitation torque is proportional to the q-axis current, the q-axis current reference can be fed by the excitation torque reference through a proportional regulator. Once the q-axis current reference is given, the d-axis current reference can be calculated based on the per-unit model, which aims to simplify the calculation and make the control strategy independent of machine parameters. In this paper, the stability of the control system is demonstrated. Meanwhile, simulation and experiment results show this torque control strategy can realize MTPA trajectory tracking online and have success in transients.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:17:p:3261-:d:260563
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    Citations

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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. 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.
    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. Pedram Asef & Ramon Bargallo & Andrew Lapthorn & Davide Tavernini & Lingyun Shao & Aldo Sorniotti, 2021. "Assessment of the Energy Consumption and Drivability Performance of an IPMSM-Driven Electric Vehicle Using Different Buried Magnet Arrangements," Energies, MDPI, vol. 14(5), pages 1-22, March.
    5. Massimo Caruso & Antonino Oscar Di Tommaso & Giuseppe Lisciandrello & Rosa Anna Mastromauro & Rosario Miceli & Claudio Nevoloso & Ciro Spataro & Marco Trapanese, 2020. "A General and Accurate Measurement Procedure for the Detection of Power Losses Variations in Permanent Magnet Synchronous Motor Drives," Energies, MDPI, vol. 13(21), pages 1-19, November.

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