The fault diagnosis of an automotive suspension can become ambiguous because there is no general methodology to detect suspension problems. The main purpose of this work is to introduce a numerical analysis to determinate the state of a suspension system which is meant to be developed in future works for its practical application. It is considered that the spring and damper are the elements of the suspension that deteriorate the most over time, causing greater inconvenience to the driving experience, also, it is worth mentioning that being the main components of the suspension, these are the ones that most affect the system at the time of failure. The methodology to find suspension failures presented in this paper is based on the modal analysis of the frequency response of a quarter of vehicle model. To validate the methodology, different vehicles will be used to identify a pattern in the behavior that allows to generalize the appropriate response in a vehicle. The condition of the suspension can be determined by a graphical inspection of the frequency response: As the damper is tailing, the magnitude in the resonance frequency tends to ∞ . On the other hand, as the spring fails, the resonance frequency tends to zero, independently of the damper state, allowing to isolate the fault.
|Title of host publication
|Advances in Automation and Robotics Research - Proceedings of the 3rd Latin American Congress on Automation and Robotics, LACAR 2021
|Subtitle of host publication
|Advances in Automation and Robotics Research. LACAR 2021.
|Héctor A. Moreno, Isela G. Carrera, Ricardo A. Ramírez-Mendoza, José Baca, Ilka A. Banfield
|Springer Science and Business Media Deutschland GmbH
|Number of pages
|Published - 2022
|3rd Latin American Congress on Automation and Robotics, LACAR 2021 - Virtual, Online
Duration: 17 Nov 2021 → 19 Nov 2021
|Lecture Notes in Networks and Systems
|3rd Latin American Congress on Automation and Robotics, LACAR 2021
|17/11/21 → 19/11/21
Bibliographical notePublisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Signal Processing
- Computer Networks and Communications