Robust Design Optimization of Dynamic Performances of the Automobile Suspension with Uncertainty

This paper focuses on the methodology development and application of robust optimization of designing automotive suspension systems in frequency domain. A half-car linear model of suspension systems is used to describe the dynamic performances, such as, ride comfort, road holding and working space on roads. In the robust optimal model, the uncertain parameters, including the sprung mass, suspension stiffness damping, considered as uncertainty variables. Then, the computational expressions of the dynamic performances in frequency domain for suspension systems with uncertainty variables are obtained by means of Taguchi approaches. The design variables to be optimized for robust designing are the suspension stiffness and damping ratios. The robust optimal trade-off solution and a preference aggregation methods are used to the multi-objective problem, which is then solved using Genetic Algorithm. The robust optimal design with the stiffness and damping uncertainty of the suspension systems for a MPV is used to demonstrate the robust optimal approach. The results of the numerical simulations and the experiments in proving ground show a improvement in the dynamic performances and robustness for the suspension system compared with the reference vehicle.