Interior noise and vibration prediction of permanent magnet synchronous motor

22Citations
Citations of this article
22Readers
Mendeley users who have this article in their library.

Abstract

Electric vehicles (EV) are considerably quieter than internal combustion engine (ICE) powered vehicles, because noise of ICE is eliminated. However, the interior noise of an EV usually contains significant high-frequency noise components caused by electrical motor, which can be subjectively perceived as annoying and unpleasant. This paper describes a numerical model to predict interior acoustic noise caused by electromagnetic forces in permanent magnet synchronous motor (PMSM) for electric vehicles. Firstly, the principle of the multiphysics method is to establish a complete 3Dstructural finite element model (FEM) of motor. Based on FEM, natural frequency and modal shape were calculated by modal analysis. Secondly, using an electromagnetic finite element solver, the excitation due to electromagnetic phenomena is obtained. This excitation is then projected onto the structure mesh of motor in order to calculate the dynamic response. Thirdly, radiated electromagnetic vibration acceleration on the surface of the motor is calculated with modal superposition method. Compared with experimental test results, the creditability of motor electromagnetic vibration simulation is proved. Finally, by combining with transfer path analysis (TPA) techniques, interior electromagnetic noise of electric vehicles is accurately predicted. According to contribution analysis, motor surface zones and transfer paths contributing largely to the interior motor electromagnetic noise are identified. The results play a significant guiding role in both electric vehicle and permanent magnet synchronous motor for noise control and analysis.

Cite

CITATION STYLE

APA

Qian, K., Wang, J., Gao, Y., Sun, Q., & Liang, J. (2018). Interior noise and vibration prediction of permanent magnet synchronous motor. Journal of Vibroengineering, 20(5), 2225–2236. https://doi.org/10.21595/jve.2018.18605

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free