Diagnosis of the Electric Vehicles Synchronous Motors Faults Using Signal Analysis Techniques | ||
| Engineering Research Journal | ||
| Volume 182, Issue 2, June 2024, Pages 195-208 PDF (835.85 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/erj.2024.358547 | ||
| Authors | ||
| Mohamed A. E. Badawy* 1; Mostafa M. A. Mohamed2; Ahmed A. A. Saad3 | ||
| 1Researcher, Automotive Eng. Department, Faculty of Engineering, Helwan University, Egypt | ||
| 2lecturer of Automotive Eng. Department, Faculty of Engineering, Helwan University, Egypt. | ||
| 3Professor of Automotive Eng. Department, Faculty of Engineering, Helwan University, Egypt. | ||
| Abstract | ||
| There is no doubt that electric vehicles (EV), are gaining huge popularity, this is due to the significant advantages of electric vehicles when compared to an ICE vehicle. These advantages include the quietness, the friendly usage, low pollution emission and low maintenance cost. On the other hand, and as electric vehicles are still machine, the EVs have several components that can be faulty and affect the vehicle performance and maybe in some stages lead to severe failures or life threatening. These components are mainly the battery, electric motor and controllers. So, many studies focused on studying the electric vehicles components fault detection in the early stages. This paper will focus on one of the most common motor types, the permanent magnet synchronous motors. One of the common PMSM faults related to the rotor is the demagnetization. This fault will be extensively studied using two of the signal analysis method techniques: the output torque and the stator current signal analysis. Using the MATLAB Simulink, a complete model of the PMSM will be built and the uniform demagnetization fault will be introduced. Then, a comparison between both torque and current signatures will be presented to put our hands on the ability of these techniques to identify the uniform demagnetization fault. | ||
| Keywords | ||
| Electric Vehicles; PMSM; MCSA; Demagnetization; Fault detection | ||
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