Robust Design of Vehicle Suspension with Uncertain Parameters Using a Polynomial Chaos Approach

The optimum design of suspension system is a subject with great importance as suspension system has a significant role in ride and handling of vehicles. Practical vehicle systems often contain some uncertainties, which should be considered in the optimum design process of suspension. In this study, a quarter-car model is used to investigate and optimize the dynamic response of cars with random uncertainty which comes from the terrain profile and the variable system parameters. In order to achieve an optimum robust design against uncertainty in reality, a new robust design approach is proposed, which is a combination of a multi-objective genetic algorithm and the generalized polynomial chaos theory. Then Pareto optimum robust design is applied to the quarter-car model with three performances criteria, related to ride comfort, suspension travel and road holding. As a result, an optimum robust design point for vehicle model is obtained by using the polynomial chaos approach. In order to validate the polynomial chaos approach, a deterministic optimization is applied for vehicle model without considering any uncertainty, and an optimum deterministic design point is obtained. By the comparison of the optimum robust design point and the optimum deterministic design point, the robust design approach using polynomial chaos is proved to be effective and useful.