A Novel Parameter Estimation Scheme for Vehicle Suspension Systems Based on Response and Test Track Prioritization

Abstract

In this paper, a system identification methodology based on vehicle response and test track prioritization is presented. The proposed method can be used to perform time-domain parameter estimation by simply driving the vehicle on different road profiles, thus eliminating the necessity of having a special test setup or excitation input feed. The method is based on exploiting the dependence of the identifiability of vehicle parameters on vehicle responses and test tracks. To prioritize the test tracks, the responses and test tracks are weighed based on their capabilities to estimate the vehicle parameters, and these weights are obtained in a preliminary analysis of a seven-degree-of-freedom ride model developed in MATLAB® (R2021b). An optimization framework based on a differential evolution scheme with an optional archive scheme (JADE) is used to estimate the twelve vehicle parameters. The proposed system identification scheme is verified on tests using a high-fidelity vehicle model developed in ADAMS® (29.2)using several tracks with different severities. Experimental validation is performed on a test vehicle, and it is demonstrated that the vehicle suspension system parameters can be identified accurately with fast convergence performance.