a new approach to modeling vehicle dynamics system using a block-oriented structure with genetic algorithm

This paper aims to nonlinearly model a vehicle dynamics system utilizing the wiener-hammerstein structure based on a genetic ‎algorithm. system identification involves deriving mathematical models of dynamical systems from output data, test results, and ‎observations. many modern vehicle features rely on models of underlying vehicle dynamics, with the bicycle vehicle model ‎being a commonly used, relatively simple structure in the vehicle dynamics literature. this study begins with this model ‎structure and attempts to estimate the longitudinal and lateral stiffness of a tire. in recent years, block-oriented models have been ‎employed to model nonlinear systems. among these models, the wiener-hammerstein model comprises two linear blocks with ‎a static nonlinear block between them. identification was performed using simulated data with high stiffness tires and a genetic ‎algorithm. the simulation results demonstrate the high accuracy of the proposed method.‎