A Model-Based Strategy for Interturn Short-Circuit Fault Diagnosis in PMSM

A model-based method for interturn short-circuit fault detection and isolation in permanent magnet synchronous machines (PMSMs) is proposed in this paper. The fault detection is realized based on a residual current vector (RCV) generated by the difference between the measured stator currents and the...

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Bibliographic Details
Published inIEEE transactions on industrial electronics (1982) Vol. 64; no. 9; pp. 7218 - 7228
Main Authors Mazzoletti, Manuel A., Bossio, Guillermo R., De Angelo, Cristian H., Espinoza-Trejo, Diego R.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.09.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Summary:A model-based method for interturn short-circuit fault detection and isolation in permanent magnet synchronous machines (PMSMs) is proposed in this paper. The fault detection is realized based on a residual current vector (RCV) generated by the difference between the measured stator currents and the stator currents estimated by a state observer. In order to avoid false alarms due to possible undesired perturbations, the sequence decomposition of the RCV is performed by employing different reference-frames. Thus, the proposed RCV allows the correct detection of interturn short-circuit faults and quantification of the fault severity in any faulty stator-phase winding. Moreover, since the back-EMF generated by the magnets is proportional to the rotor shaft speed, the electrical angular speed is estimated through the stator voltages measurement, without using a speed sensor. Simulation results from the three-phase PMSM dynamic model that allows considering the interturn short-circuit fault in any stator phase-windings are presented. The proposed method is validated using a three-phase PMSM prototype with modified stator windings. The robustness and the reliability of the proposal was tested for several interturn fault conditions under transient conditions including different disturbances.
ISSN:0278-0046
1557-9948
DOI:10.1109/TIE.2017.2688973