RT Journal Article
T1 Non-intrusive determination of shock absorber characteristic curves by means of evolutionary algorithms
A1 Carabias-Acosta, Enrique
A1 Cabrera-Carrillo, Juan Antonio
A1 Castillo-Aguilar, Juan Jesús
A1 Pérez-Fernández, Javier
A1 Alcázar-Vargas, Manuel Gonzalo
K1 Computación evolutiva
AB The fault detection in the components of the suspension system of road vehicles is of great importance. The optimal performance of the suspension system has a big influence on the safety and stability of a vehicle. Vehicle inspection services make use of different methods of fault diagnosis of shock absorbers without the need to remove them from the vehicle. These methods generally provide an average value of the damping coefficient or a value related to the efficiency of the damper. Next, acceptance or rejection criteria are used to evaluate the condition of the damper. Consequently, there is currently no objective criterion for detecting the malfunctioning or faulty condition of shock absorbers. In this work, a novel methodology capable of obtaining the complete force–velocity characteristic curve of the shock absorber is proposed. For this purpose, the importance of using an appropriate tyre model to obtain the suspension parameters is first studied. In addition, the displacements of the sprung and unsprung masses and the excitation of the system are obtained experimentally. Next, the points that model the complete characteristic curve of a shock absorber are obtained by means of an optimization method based on evolutionary algorithms. Real tests have been conducted on a complete vehicle suspension test bench to verify the effectiveness of the proposed methodology.
PB Elsevier
YR 2023
FD 2023-01-01
LK https://hdl.handle.net/10630/24829
UL https://hdl.handle.net/10630/24829
LA spa
NO E. Carabias, J.A. Cabrera, J.J. Castillo, J. Pérez, M. Alcázar, Non-intrusive determination of shock absorber characteristic curves by means of evolutionary algorithms, Mechanical Systems and Signal Processing, Volume 182, 2023, 109583, ISSN 0888-3270,  https://doi.org/10.1016/j.ymssp.2022.109583
NO This work was supported in part by the Spanish Innovation Science Ministry under Grant PID2019-105572RB-I00. Funding for open access charge: Universidad de Málaga.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 13 abr 2026