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Electric Machine Noise and Vibration Prediction and Validation Through Test

Abstract: The push toward electrification has posed new NVH challenges to the automotive industry due to the elimination of masking noise generated by the engine and exhaust system of the traditional internal combustion powertrains.  To achieve acceptable NVH quality through design optimization, developing simulation processes that facilitate systematic, fast, and accurate NVH predictions is essential.  In this presentation, a simulation process for the NVH prediction of electric motors is proposed, and the predicted noise results are validated through test results.  The proposed process first simulates the motor excitation forces using a 2D electromagnetic force model and then applies these forces to a simplified 3D motor structure model.  This simplified 3D model is validated by comparing the structural transfer functions calculated from the impact hammer test and FEA simulation.  Finally, the proposed simulation process is validated by comparing predicted sound pressure levels at different locations to an electric motor NVH test results from a semi-anechoic chamber.

Keyu Chen


Keyu Chen 

Sr. NVH Engineer, Electric Machine NVH Center of Excellence (CoE) Lead, BorgWarner 

Keyu Chen is a senior NVH engineer at BorgWarner, focused on noise and vibration control of electric machines using simulation. Chen received his Mechanical Engineering Ph.D. from the University of Kentucky in 2020 and is a native of Chongqing, China.

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