Fault Diagnostics and Prognostics for Vehicle Springs and Stablizer Bar
##plugins.themes.bootstrap3.article.main##
##plugins.themes.bootstrap3.article.sidebar##
Abstract
Vehicle springs and stabilizer bar are critical suspension components impacting vehicle riding and handling experience. Diagnostics and prognostics of springs and stabilizer bar can improve customer perceived quality, reduce repair cost and increase up-time for fleet vehicles. It’s even more important for autonomous vehicles, since there is no human driver to sense fault symptoms. Currently, there is no production solution to automatically diagnose and prognose spring and stabilizer bar failures, and most research work is suffered by various noise factors. In this work, a novel solution based on static ramp test is proposed to isolate and localize spring and stabilizer bar faults. With limited number of longitudinal and lateral acceleration measurements, the solution can quickly and effectively isolate faulty spring, disconnected stabilizer bar, loose bushing and loose end link. The validation results from a MY17 Bolt EV demonstrate the effectiveness and robustness of the proposed solution.
How to Cite
##plugins.themes.bootstrap3.article.details##
spring, stabilizer bar, prognostics
This work is licensed under a Creative Commons Attribution 3.0 Unported License.
The Prognostic and Health Management Society advocates open-access to scientific data and uses a Creative Commons license for publishing and distributing any papers. A Creative Commons license does not relinquish the author’s copyright; rather it allows them to share some of their rights with any member of the public under certain conditions whilst enjoying full legal protection. By submitting an article to the International Conference of the Prognostics and Health Management Society, the authors agree to be bound by the associated terms and conditions including the following:
As the author, you retain the copyright to your Work. By submitting your Work, you are granting anybody the right to copy, distribute and transmit your Work and to adapt your Work with proper attribution under the terms of the Creative Commons Attribution 3.0 United States license. You assign rights to the Prognostics and Health Management Society to publish and disseminate your Work through electronic and print media if it is accepted for publication. A license note citing the Creative Commons Attribution 3.0 United States License as shown below needs to be placed in the footnote on the first page of the article.
First Author et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.