Global Optimal Design and Dynamic Validation of an Independent Double Wishbone Air Suspension Using Genetic Algorithm

Abstract

In view of the drawbacks of the traditional optimal methods in the suspension structure optimization, this paper elaborates a genetic algorithm (GA) based global optimal design so as to improve the vehicle performance. Firstly, an independent double wishbone air suspension (IDWAS) is constructed. After defining the linkage relation of the guide mechanism of the IDWAS, the model is verified followed with the parametric design. Furthermore, in consideration of the prescribed targets of the vehicle kinematics, the wheel alignment parameters (WAPs) are selected as the objectives of the optimal design of the vehicle kinematics. Apart from the kinematic analysis of the IDWAS, dynamic analysis before and after optimization as well as the traditional independent double wishbone suspension (TIDWS) are also conducted. Numerical results show that the changes of the WAPs are within a certain range and the guide mechanism follows the prescribed constraints. Simulation results show that the IDWAS is superior to the TIDWS, while the optimized IDWAS has a slight improvement as compared to the original IDWAS in dynamic performance of the suspension.