Identification of low order vehicle handling models from multibody vehicle dynamics models

Abstract

Vehicle handling models are commonly used in the design and analysis of vehicle dynamics. Advances in vehicle control systems increase the need for accurate and simple vehicle handling models. These models have parameters, some of which are known or easily obtainable, yet some of which are unknown or difficult to obtain. These parameters may be obtained by system identification. In this study, vehicle handling models are identified based on data obtained from the simulation of ADAMS vehicle models representing the complex vehicle dynamics and a general methodology has been developed. Three degree of freedom two-track model which includes roll degree of freedom and the Magic Formula tire model is selected for identification. The parameters of the test input used in the ADAMS simulation have been obtained by a sensitivity analysis. In sensitivity analysis, changes in the sensitivity of the model outputs to model parameters with the steering input frequency and the longitudinal velocity of the vehicle have been determined. To decide whether the identified parameters are unique or not, a detailed structural identifiability analysis has been performed and the uniqueness of the identified parameters have been guaranteed. After the sensitivity and identifiability studies, unknown model parameters have been estimated by minimizing the difference between simulation data of the simple model and complex multibody dynamics vehicle model using mathematical optimization methods. By model validation, it has been shown that identified handling model simulates the vehicle dynamics successfully.