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An Online Parameter Estimation Using Current Injection with Intelligent Current-Loop Control for IPMSM Drives

Author

Listed:
  • Faa-Jeng Lin

    (Department of Electrical Engineering, National Central University, Chungli 320, Taiwan)

  • Syuan-Yi Chen

    (Department of Electrical Engineering, National Taiwan Normal University, Taipei 106, Taiwan)

  • Wei-Ting Lin

    (Department of Electrical Engineering, National Central University, Chungli 320, Taiwan)

  • Chih-Wei Liu

    (Department of Electrical Engineering, National Central University, Chungli 320, Taiwan)

Abstract

An online parameter estimation methodology using the d -axis current injection, which can estimate the distorted voltage of the current-controlled voltage source inverter (CCVSI), the varying dq -axis inductances, and the rotor flux, is proposed in this study for interior permanent magnet synchronous motor (IPMSM) drives in the constant torque region. First, a d -axis current injection-based parameter estimation methodology considering the nonlinearity of a CCVSI is proposed. Then, during current injection, a simple linear model is developed to model the cross- and self-saturation of the dq -axis inductances. Since the d -axis unsaturated inductance is difficult to obtain by merely using the recursive least square (RLS) method, a novel tuning method for the d -axis unsaturated inductance is proposed by using the theory of the maximum torque per ampere (MTPA) with the combination of the RLS method. Moreover, to improve the bandwidth of the current loop, an intelligent proportional-integral-derivative (PID) neural network controller with improved online learning algorithm is adopted to replace the traditional PI controller. The estimated the dq -axis inductances and the rotor flux are adopted in the decoupled control of the current loops. Finally, the experimental results at various operating conditions of the IPMSM in the constant torque region are given.

Suggested Citation

  • Faa-Jeng Lin & Syuan-Yi Chen & Wei-Ting Lin & Chih-Wei Liu, 2021. "An Online Parameter Estimation Using Current Injection with Intelligent Current-Loop Control for IPMSM Drives," Energies, MDPI, vol. 14(23), pages 1-21, December.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:23:p:8138-:d:695154
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    References listed on IDEAS

    as
    1. Faa-Jeng Lin & Yi-Hung Liao & Jyun-Ru Lin & Wei-Ting Lin, 2021. "Interior Permanent Magnet Synchronous Motor Drive System with Machine Learning-Based Maximum Torque per Ampere and Flux-Weakening Control," Energies, MDPI, vol. 14(2), pages 1-24, January.
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    Citations

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    Cited by:

    1. Peter Stumpf & Tamás Tóth-Katona, 2023. "Recent Achievements in the Control of Interior Permanent-Magnet Synchronous Machine Drives: A Comprehensive Overview of the State of the Art," Energies, MDPI, vol. 16(13), pages 1-46, July.
    2. Feng Jiang & Fan Yang & Songjun Sun & Kai Yang, 2022. "Improved Linear Active Disturbance Rejection Control for IPMSM Drives Considering Load Inertia Mismatch," Energies, MDPI, vol. 15(3), pages 1-22, February.
    3. Hao Yu & Jiajun Wang & Zhuangzhuang Xin, 2022. "Model Predictive Control for PMSM Based on Discrete Space Vector Modulation with RLS Parameter Identification," Energies, MDPI, vol. 15(11), pages 1-16, May.

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