Road friendliness optimization of heavy vehicle suspension based on particle swarm algorithm

In this paper, an optimization design method based on the Particle Swarm Optimization (PSO) technique was proposed for the enhancement of the passive suspension system performance of heavy vehicles. The optimization problem based on a quarter-vehicle model aims to minimize the dynamic tire load subject to constraints on the natural frequency of the unsprung mass. PSO was applied to solve the optimization problem for obtaining optimum parameters, such as the suspension damping coefficient and spring stiffness. In order to assess the obtained design parameters, the suspension performance was estimated in time and frequency domains for different road excitations. And some essential differences between PSO and Genetic Algorithm (GA) were discussed in detail. The results show that, for the same suspension system, the proposed method can obtain the optimum designed parameters quickly compared with the previous designed parameters using the GA, which will provide important parameters for the subsequent revised design. © 2018, Editorial Office of Journal of Vibration and Shock. All right reserved.