Fault Diagnosis in Electrical Machines for Traction Applications: Current Trends and Challenges

被引：0

作者：

Pastura, Marco ^{[1
]}

Zigliotto, Mauro ^{[1
]}

机构：

[1] Univ Padua, Dept Engn & Management DTG, I-36100 Vicenza, Italy

来源：

ENERGIES | 2024年 / 17卷 / 21期

关键词：

fault detection; review; electric vehicle; traction application; condition monitoring; machine learning; permanent magnet machines; induction machines; multi-phase machines; OPEN-CIRCUIT FAULTS; OPEN-SWITCH FAULT; INDUCTION-MOTOR; DEMAGNETIZATION FAULT; WAVELET TRANSFORM; INTERTURN FAULTS; TURN FAULTS; ROTOR FAULT; STATOR; ECCENTRICITY;

D O I：

10.3390/en17215440

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

The widespread diffusion of electric vehicles poses new challenges in the field of fault diagnostics. Past studies have been focused mainly on machines designed for industrial applications, where the operating conditions and requirements are significantly different. This work presents a review of the most recent studies about fault diagnosis techniques in electrical machines feasible for traction applications, with a focus on the most adopted approaches of the last years and on the latest trends. Considerations about their applicability for electric vehicle purposes, along with some areas that require further research, are also provided.

引用

页数：20

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