Applied Sciences (May 2022)

Noise Identification for an Automotive Wheel Bearing

  • Jaewon Kim,
  • Seongmin Kwon,
  • Seokwon Ryu,
  • Seungpyo Lee,
  • Jaeil Jeong,
  • Jintai Chung

DOI
https://doi.org/10.3390/app12115515
Journal volume & issue
Vol. 12, no. 11
p. 5515

Abstract

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In this study, we identified the noise generated from automotive wheel bearings, which has recently emerged as a new problem in electric vehicles. The wheel bearing assembly considered in this study consists of a wheel bearing, dust shield, and knuckle, which are fastened with bolts. To obtain the noise characteristics of the wheel bearing, the noise and vibration were experimentally measured when the bearing rotated. Additionally, the natural frequencies and mode shapes of the main components of the bearing were acquired via modal testing. By comparing the obtained natural frequencies with the peak frequencies of the measured noise and vibration signals, we identified where the noise radiated. To specifically identify bearing defects, a finite element analysis model was established, and the deformation of the bearing under load was analyzed. Based on the analysis, we determined that the deformation of the outer ring in an outboard row, which resulted from bolt fastening, leads to noise and vibration in the wheel bearing.

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