Diagnostic and Prognostic Health Management of Electric Vehicle Powertrains: An Empirical Methodology for Induction Motor Analysis-Reference-Cited by-同舟云学术

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Diagnostic and Prognostic Health Management of Electric Vehicle Powertrains: An Empirical Methodology for Induction Motor Analysis

Published:2023-06-14 Issue: Volume: Page:
ISSN:
Container-title:2023 5th Global Power, Energy and Communication Conference (GPECOM)
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Author:

Hadraoui Hicham El¹,Laayati Oussama²,Maghraoui Adila El¹,Sabani Erroumayssae³,Zegrari Mourad⁴,Chebak Ahmed¹

Affiliation:

1. Green Tech Institute, Mohammed VI Polytechnic University,Benguerir,Morocco

2. Green Tech Institute, UM6P,Benguerir, HassanI University,Settat,Morocco

3. Chouaib Doukkali University,Laboratory of Engineering Sciences for Energy (LabSIPE), National School of Applied Sciences,El jadida,Morocco

4. Green Tech Institute, UM6P,Benguerir, Hassan II University of Casablanca,Morocco

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10175636/10175666/10175674.pdf?arnumber=10175674

Reference34 articles.

1. Stability of feature selection algorithm: A review

2. Classification and Authentication of Induction Motor Faults using Time and Frequency Feature Dependent Probabilistic Neural Network Model

3. Frequency Occurrence Plot-Based Convolutional Neural Network for Motor Fault Diagnosis

4. The Edge Application of Machine Learning Techniques for Fault Diagnosis in Electrical Machines

5. Novel feature extraction method for signal analysis based on independent component analysis and wavelet transform

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