Interturn Short-Circuit Fault Diagnosis Method of Permanent Magnet Synchronous Motor Based on Phase Current Residuals

To improve the performance of interturn short-circuit fault (ISCF) detection and location in permanent magnet synchronous motor (PMSM), this paper proposes a novel fault diagnosis method based on phase current residuals. This method diagnoses ISCF by the residuals subtracting the fault current of PMSM from the healthy current constructed by Luenberger observer, which enhances the accuracy and robustness of fault diagnosis. Considering model errors exist, the negative sequence component of current residuals is constructed, and the model parameters impact is eliminated. Then, the sliding window root mean square of the negative sequence component is calculated as the fault index, compared with the threshold to determine the fault occurrence. Moreover, since the amplitudes of the three-phase current residuals are different after the ISCF, the maximum amplitude is used to locate the faulty phase. Finally, the effectiveness of the proposed fault diagnosis method is verified through simulations under various operating conditions.

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Publication Details

Published
2024-11-26
DOI
https://doi.org/10.23919/icems60997.2024.10921083
Primary Topic
Electric Power Systems and Control
Type
article
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Interturn Short-Circuit Fault Diagnosis Method of Permanent Magnet Synchronous Motor Based on Phase Current Residuals

Peijuan Cui, Jie Fu, Zaiping Zheng, Wei Wang et al.
Electric Power Systems and Control
article

Interturn Short-Circuit Fault Diagnosis Method of Permanent Magnet Synchronous Motor Based on Phase Current Residuals

Peijuan Cui, Jie Fu, Zaiping Zheng, Wei Wang, Yao Rao
article en

Abstract

To improve the performance of interturn short-circuit fault (ISCF) detection and location in permanent magnet synchronous motor (PMSM), this paper proposes a novel fault diagnosis method based on phase current residuals. This method diagnoses ISCF by the residuals subtracting the fault current of PMSM from the healthy current constructed by Luenberger observer, which enhances the accuracy and robustness of fault diagnosis. Considering model errors exist, the negative sequence component of current residuals is constructed, and the model parameters impact is eliminated. Then, the sliding window root mean square of the negative sequence component is calculated as the fault index, compared with the threshold to determine the fault occurrence. Moreover, since the amplitudes of the three-phase current residuals are different after the ISCF, the maximum amplitude is used to locate the faulty phase. Finally, the effectiveness of the proposed fault diagnosis method is verified through simulations under various operating conditions.

Southeast University (CN)
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Electric Power Systems and Control
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