Application of Genetic Algorithms in Optimal Design of a Passive Suspension System a Vehicle Subjected to Random Excitations of Actual Road

Vehicles are subject to random road excitations due to road unevenness and variable velocity which causes ride discomfort and fatigue. Ride comfort could be improved by decreasing vehicle accelerations. In this paper, to evaluate the vehicle ride comfort, root mean square acceleration response (RMSAR) is calculated using power spectral density (PSD) of road excitations and these quantities are compared with the ISO2631 boundary values. Then by considering ISO2631, the vehicle’s RMSAR is minimized by optimal design of vehicle suspension viscous damping and stiffness parameters. To solve this nonlinear constrained optimization problem, we utilize genetic algorithms. Also, in the design process the physical restrictions are included. Obtained results demonstrate a considerable improvement of vehicle ride comfort and its dynamic response as a result of reduced accelerations. Comparing the obtained results with those obtained by method of nonlinear programming confirms the supremacy of genetic algorithms.