Physical Parameter Identification Method Based on Modal Analysis for Two-axis On-road Vehicles: Theory and Simulation

TLDR: In this paper, a methodology based on the State Variable Method (SVM) for physical parameter identification of two-axis on-road vehicle is presented, which can identify all physical parameters of 7-DOF vehicle model by using free-decay responses of vehicle without need to assume some physical parameters are known.

Abstract: Physical parameters are very important for vehicle dynamic modeling and analysis. However, most of physical parameter identification methods are assuming some physical parameters of vehicle are known, and the other unknown parameters can be identified. In order to identify physical parameters of vehicle in the case that all physical parameters are unknown, a methodology based on the State Variable Method(SVM) for physical parameter identification of two-axis on-road vehicle is presented. The modal parameters of the vehicle are identified by the SVM, furthermore, the physical parameters of the vehicle are estimated by least squares method. In numerical simulations, physical parameters of Ford Granada are chosen as parameters of vehicle model, and half-sine bump function is chosen to simulate tire stimulated by impulse excitation. The first numerical simulation shows that the present method can identify all of the physical parameters and the largest absolute value of percentage error of the identified physical parameter is 0.205%; and the effect of the errors of additional mass, structural parameter and measurement noise are discussed in the following simulations, the results shows that when signal contains 30 dB noise, the largest absolute value of percentage error of the identification is 3.78%. These simulations verify that the presented method is effective and accurate for physical parameter identification of two-axis on-road vehicles. The proposed methodology can identify all physical parameters of 7-DOF vehicle model by using free-decay responses of vehicle without need to assume some physical parameters are known.