Modeling and optimization of car suspension system in the presence of magnetorheological damper using Simulink-PSO hybrid technique

Abstract

The suspension system is one of the important parts of the vehicle, which plays a substantial role in the steering and comfort characteristics of it. In the present research work, the optimization of the suspension system parameters has been carried out with the aim of reducing the vehicle vibrations. In this study, the magnetorheological damper (MR damper) is added to the one-half car model with four degrees of freedom and the effects of improving the efficiency of the suspension system have been investigated. In order to model the vehicle system, MATLAB/Simulink software is employed. The particle swarm optimization (PSO) algorithm has been applied to optimize the variables of the suspension system in order to decrease the vehicle vibrations and passenger comfort. The optimization of suspension system variables has been done for two bond-limited white noise and sinusoidal wave inputs. The outcomes revealed that the addition of MR damper in any mode reduces the vehicle vibrations. The maximum reduction in the vehicle vibrations was related to the state where all the variables of the suspension system were optimized and the amount of the objective function in that state was improved by about 32%.