Multi objective optimization of vehicle suspension design

This paper demonstrates the applicability of a multi objective genetic algorithm to analyze the effect of suspension parameters on the ride comfort and road holding capability of vehicles. The maximum vertical acceleration at driver's seat and maximum roll angle are minimized, keeping the suspension working space constrained. The effect of seat position is also considered in the optimization. An 8-degree of freedom (DOF) vehicle model with different suspension systems, such as passive, active and semi active is used for the present study. The optimization is carried out using Non-Dominated Sorting Genetic Algorithm (NSGA-II), developed by Deb (2001). Deterministic road input is applied to the vehicle model. A good pareto optimal solution is achieved in the optimization for all three suspension systems. The results show that the use of active and semi active suspensions is beneficial compared to passive suspension system.