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Article

Increasing Electric Vehicles Reliability by Non-Invasive Diagnosis of Motor Winding Faults

Institute of Electrical Engineering and Electronics, Faculty of Control, Robotics and Electrical Engineering, Poznan University of Technology, Piotrowo Street, No. 3a, 60-965 Poznan, Poland
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Academic Editors: Salvatore Musumeci, Wojciech Pietrowski and Stefan Brock
Energies 2021, 14(9), 2510; https://doi.org/10.3390/en14092510
Received: 25 March 2021 / Revised: 21 April 2021 / Accepted: 24 April 2021 / Published: 27 April 2021
The article proposes a proprietary approach to the diagnosis of induction motors allowing increasing the reliability of electric vehicles. This approach makes it possible to detect damage in the form of an inter-turn short-circuit at an early stage of its occurrence. The authors of the article describe an effective diagnostic method using the extraction of diagnostic signal features using an Enhanced Empirical Wavelet Transform and an algorithm based on the method of Ensemble Bagged Trees. The article describes in detail the methodology of the carried out research, presents the method of extracting features from the diagnostic signal and describes the conclusions resulting from the research. Phase current waveforms obtained from a real object as well as simulation results based on the field-circuit model of an induction motor were used as a diagnostic signal in the research. In order to determine the accuracy of the damage classification, simple metrics such as accuracy, sensitivity, selectivity, precision as well as complex metrics weight F1 and macro F1 were used. View Full-Text
Keywords: induction motor; inter-turn short-circuit; electrical machine diagnostics; empirical wavelet transform; enhanced empirical wavelet transform; ensemble bagged trees induction motor; inter-turn short-circuit; electrical machine diagnostics; empirical wavelet transform; enhanced empirical wavelet transform; ensemble bagged trees
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MDPI and ACS Style

Górny, K.; Kuwałek, P.; Pietrowski, W. Increasing Electric Vehicles Reliability by Non-Invasive Diagnosis of Motor Winding Faults. Energies 2021, 14, 2510. https://doi.org/10.3390/en14092510

AMA Style

Górny K, Kuwałek P, Pietrowski W. Increasing Electric Vehicles Reliability by Non-Invasive Diagnosis of Motor Winding Faults. Energies. 2021; 14(9):2510. https://doi.org/10.3390/en14092510

Chicago/Turabian Style

Górny, Konrad, Piotr Kuwałek, and Wojciech Pietrowski. 2021. "Increasing Electric Vehicles Reliability by Non-Invasive Diagnosis of Motor Winding Faults" Energies 14, no. 9: 2510. https://doi.org/10.3390/en14092510

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