Optimization of Vehicle Suspension System Using Genetic Algorithm

The vehicle suspension system is one of the main design factors in the automobile industry that can exponentially increase the level of customers comport and satisfaction. Various design strategies can be used to get optimum values for the various parameters in the suspension system. In this paper, a passive vehicle suspension system was modeled, and the system was optimized using Genetic Algorithm (GA) optimization technique. The GA is based on natural evolution and is successfully applied to various real-world problems. The variance of the dynamic load resulting from the vibrating vehicle is taken as the performance measure (i.e., objective function) of the suspension system. During the application of GA, first appropriate mutation rate, crossover rate, and population size were evaluated which were used to calculate optimum values for the parameters in the suspension system. The optimum values for the suspension system correspond to minimum values of the settling time and maximum overshoot and thus helps in decreasing the effect of the dynamic loads by reducing the vehicle vibration.