Optimization of Automobile Suspension System Using Hybrid GSA Algorithm

Abstract

In this paper Hybrid Genetic- Simulated Annealing Algorithm (GSA) is studied and applied to the suspension system of an automobile with two different case studies. Mathematical modelling of an automobile is done for passive suspension system. GA, SA and GSA were simulated using programming in MATLAB. First case study is based on the data of researcher in the field where GA was applied for optimization of automobile suspension system. Here SA, as well as Hybrid GSA are applied and compared with the results of GA. Convergences of the three methods are also plotted. In second case study an automobile model MARUTI 800 is considered. All the necessary parameters are calculated through measurements. The results shows required seat acceleration for current available springs of the automobile in field. For both the case studies the Hybrid GSA shows best results among the three. This can be performed before actual manufacturing of springs and automobile to check whether desired seat acceleration and ride comfort will achieve or not. If it is satisfied with the value of seat acceleration, decision would be made regarding manufacturing of springs with those values of stiffness and damping constants.