Multi-objective Suspension Optimization of a 5-DOF Vehicle Vibration Model Excited by Random Road Profile

Abstract

The vehicle driving comfort has become one of the important factors of vehicle quality and receives increasing attention. In this paper, optimal points of vehicle suspension parameters are generated using modified non-dominated sorting genetic algorithm (NSGA-II) for Pareto optimization of 5-degree of freedom vehicle vibration model considering three conflicting functions simultaneously. In this way random profile is considered for the road excitation. Objective functions are vertical acceleration of seat, relative displacement between sprung mass and forward tire and relative displacement between sprung mass and rear tire. Results are compared with the previous works. Such comparison shows good behaviour of the optimum design points proposed in this work.