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RLS-Based Algorithm for Detecting Partial Demagnetization under Both Stationary and Nonstationary Conditions

Author

Listed:
  • Ze Jiang

    (Zhejiang Provincial Key Laboratory of Electrical Machine Systems, College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
    Wolong Electric Group Co., Ltd., Shaoxing 312300, China)

  • Xiaoyan Huang

    (Zhejiang Provincial Key Laboratory of Electrical Machine Systems, College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Wenping Cao

    (School of Electrical Engineering and Automation, Anhui Unsiversity, Hefei 230039, China)

Abstract

An algorithm was developed detect the partial demagnetization of permanent-magnet synchronous motors (PMSMs) under both stationary and nonstationary conditions. On the basis of the recursive least-squares (RLS) method, the vital component of fault-related harmonics in the current could be extracted on the line, and its proportion to fundamental component could be regarded as the indicator of partial demagnetization faults. The proposed algorithm is fairly easy to realize and could substitute conventional and complicated signal processing methods such as Fourier transform and wavelet transform when detecting partial demagnetization. Experiments with inverter-fed healthy and partially demagnetized PMSMs are carried out to substantiate the effectiveness of proposed algorithm under both stationary and nonstationary conditions. At the end, a way to eliminate the impact of eccentricity fault on the partial demagnetization diagnosis is given.

Suggested Citation

  • Ze Jiang & Xiaoyan Huang & Wenping Cao, 2022. "RLS-Based Algorithm for Detecting Partial Demagnetization under Both Stationary and Nonstationary Conditions," Energies, MDPI, vol. 15(10), pages 1-17, May.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:10:p:3509-:d:813065
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    References listed on IDEAS

    as
    1. Pierpaolo Dini & Sergio Saponara, 2019. "Cogging Torque Reduction in Brushless Motors by a Nonlinear Control Technique," Energies, MDPI, vol. 12(11), pages 1-20, June.
    2. Cinzia Bernardeschi & Pierpaolo Dini & Andrea Domenici & Maurizio Palmieri & Sergio Saponara, 2020. "Formal Verification and Co-Simulation in the Design of a Synchronous Motor Control Algorithm," Energies, MDPI, vol. 13(16), pages 1-23, August.
    3. Pierpaolo Dini & Sergio Saponara, 2020. "Design of Adaptive Controller Exploiting Learning Concepts Applied to a BLDC-Based Drive System," Energies, MDPI, vol. 13(10), pages 1-20, May.
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