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Virtual Signal Injection Maximum Torque per Ampere Control Based on Inductor Identification

Author

Listed:
  • Ning-Zhi Jin

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

  • Hong-Chao Chen

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

  • Dong-Yang Sun

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

  • Zhi-Qiang Wu

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

  • 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)

  • Long Zhang

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

Abstract

The high-frequency signal injection-type maximum torque per ampere (MTPA) algorithm is usually employed to control the operation of interior permanent magnet synchronous motors (IPMSMs). The MTPA algorithm exhibits good dynamic performance and anti-interference ability. However, due to the injection of a high-frequency current signal, problems such as torque ripple and additional loss are encountered. Therefore, in this paper, a virtual signal injection control (VSIC) method that does not require actual injection is proposed for solving the aforementioned problems while yielding good performance. However, in the control process of the proposed method, the d-axis inductance parameter affects the accuracy of the torque information, resulting in errors in the system. To solve this problem, an online identification algorithm of model reference adaptive systems (MRAS) based on the Popov super stability theory as the basis for the design of the adaptive law is proposed in this paper. The d-axis inductance parameter of the motor is obtained in real-time and then introduced into the control system by using the VSIC method. Finally, VSIC-type MTPA control based on inductance identification is realized. The proposed algorithm does not depend on the design parameters of the motor and exhibits good dynamic response and anti-interference performance.

Suggested Citation

  • Ning-Zhi Jin & Hong-Chao Chen & Dong-Yang Sun & Zhi-Qiang Wu & Kai Zhou & Long Zhang, 2022. "Virtual Signal Injection Maximum Torque per Ampere Control Based on Inductor Identification," Energies, MDPI, vol. 15(13), pages 1-21, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:13:p:4851-:d:854013
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    Cited by:

    1. Faiz Husnayain & Toshihiko Noguchi & Ryosuke Akaki & Feri Yusivar, 2023. "Improved Current and MTPA Control Characteristics Using FEM-Based Inductance Maps for Vector-Controlled IPM Motor," Energies, MDPI, vol. 16(12), pages 1-22, June.

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