scholarly journals Review of intelligent fault diagnosis for permanent magnet synchronous motors in electric vehicles

2020 ◽  
Vol 12 (7) ◽  
pp. 168781402094432
Author(s):  
Xiaowei Xu ◽  
Xue Qiao ◽  
Nan Zhang ◽  
Jingyi Feng ◽  
Xiaoqing Wang

Permanent magnet synchronous motors are the main power output components of electric vehicles. Once a failure occurs, it will affect the vehicle’s power, stability, and safety. While as a complex field-circuit coupling system composed of machine-electric-magnetic-thermal, the permanent magnet synchronous motor of electric vehicle has various operating conditions and complicated condition environment. There are various forms of failure, and the signs of failure are crossed or overlapped. Randomness, secondary, concurrency, and communication characteristics make it difficult to diagnose faults. Based on the research of a list of related references, this article reviews the methods of intelligent fault diagnosis for electric vehicle permanent magnet synchronous motors. The research status and development trend of fault diagnosis are analyzed. It provides theoretical basis for motor fault diagnosis and health management in multi-variable working conditions and multi-physics environment.

Machines ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 4 ◽  
Author(s):  
Luqman S. Maraaba ◽  
Zakariya M. Al-Hamouz ◽  
Abdulaziz S. Milhem ◽  
Ssennoga Twaha

The application of line-start permanent magnet synchronous motors (LSPMSMs) is rapidly spreading due to their advantages of high efficiency, high operational power factor, being self-starting, rendering them as highly needed in many applications in recent years. Although there have been standard methods for the identification of parameters of synchronous and induction machines, most of them do not apply to LSPMSMs. This paper presents a study and analysis of different parameter identification methods for interior mount LSPMSM. Experimental tests have been performed in the laboratory on a 1-hp interior mount LSPMSM. The measurements have been validated by investigating the performance of the machine under different operating conditions using a developed qd0 mathematical model and an experimental setup. The dynamic and steady-state performance analyses have been performed using the determined parameters. It is found that the experimental results are close to the mathematical model results, confirming the accuracy of the studied test methods. Therefore, the output of this study will help in selecting the proper test method for LSPMSM.


2019 ◽  
Vol 34 (2) ◽  
pp. 761-772 ◽  
Author(s):  
Mehrdad Heydarzadeh ◽  
Mohsen Zafarani ◽  
Mehrdad Nourani ◽  
Bilal Akin

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