Advancing Durability Testing in Automotive Component through Prognostics and Health Management (PHM) Integration

##plugins.themes.bootstrap3.article.main##

##plugins.themes.bootstrap3.article.sidebar##

Published Jun 27, 2024
Jinwoo Song Junggyu Choi Jeongmin Shin Seungyoon Oh Seok Hyun Hong Yun Jong Lee Hae-Sung Yoon Joo-Ho Choi

Abstract

In automotive Powered Door Systems (PDS), the emergence of grinding and clicking noise over time is a common failure mode. This issue typically arises from design or assembly inconsistencies and intensifies due to wear or increased clearance at its component, becoming noticeable to passengers, and causing discomfort. Numerous automotive manufacturers conduct comprehensive durability tests to tackle such issues during the development. Conventional durability tests, however, rely on the manual effort such as visual and auditory inspection at regular intervals, hence, is subjective and inefficient. This study introduces a novel method by the prognostics and health management (PHM) approach to detect anomaly and assess its severity of the noise during the durability test of the PDS, which may improve the reliability of noise detection and reduces the test time by early termination using prognosis capability. The results demonstrate the potential, paving the way for its broader application across various domains to advance testing processes and reliability.

How to Cite

Song, J., Choi, J., Shin, J., Oh, S., Hong, S. H., Lee, Y. J., Yoon, H.-S., & Choi, J.-H. (2024). Advancing Durability Testing in Automotive Component through Prognostics and Health Management (PHM) Integration. PHM Society European Conference, 8(1), 6. https://doi.org/10.36001/phme.2024.v8i1.4089
Abstract 294 | PDF Downloads 218

##plugins.themes.bootstrap3.article.details##

Keywords

Prognostics and Health Management, Durability Test, Automotive Components

References
Cerrato-Jay, G., Gabiniewicz, J., & Gatt, J. (2001). Automatic Detection of Buzz, Squeak and Rattle Events DJ Pickering MTS Systems, Noise and Vibration Division. Choi, J.H. (2014). A review on prognostics and health management and its applications. Journal of Aerospace System Engineering, 8(4), 7–17. Honarvar, F., & Martin, H. R. (1997). New Statistical Moments for Diagnostics of Rolling Element Bearings. http://www.asme.org/about-asme/terms-of-use Sim, J., Kim, S., Park, H. J., & Choi, J. H. (2020). A tutorial for feature engineering in the prognostics and health management of gears and bearings. Applied Sciences (Switzerland), 10(16). https://doi.org/10.3390/app10165639 Zio, E. (2022). Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice. Reliability Engineering and System Safety, 218. https://doi.org/10.1016/j.ress.2021.108119
Section
Technical Papers