Pareto-optimal Of Suspension Parameters For Multi-objective Optimization

Multi-objective optimization means the optimization objective function is not single in optimization process. The objective functions are mutually contradictory under normal circumstances. Therefore, the "absolutely optimal solution" does not existing, only the "satisfactory solution set" could be obtained. And then one definite solution is selected according to the design requirements from the satisfactory solution set.In the optimization process of suspension parameters, the body vertical acceleration and suspension working space is a pair of conflicting objective functions. Therefore, the optimal solutions are locally optimal if the traditional single-objective optimization and multi-objective optimization methods are used. In this thesis, the Pareto-optimal theory was applied to suspension optimization process. The Pareto-optimal solution was obtained, which provided the restraint relationship of the objective functions under different parameters. Based on the obtained Pareto-optimal solution set, the suspension parameters such as suspension stiffness and damping were obtained. The research showed this method can be applied to semi-active or active suspension optimization design effectively.Main contents of this paper are as followings:1. The theory and application of multi-objective optimization of suspension system was discussed. The application of multi-objective Pareto-optimal theory was proposed. Pareto-optimal front was obtained through numerical simulation method. The Pareto-optimal results were compared with the traditional optimal solutions and proved to be effective.2. Motion equations with Four DOFs and its MATLAB model were established, and then the random road excitation was imposed on it. Traditional optimization methods, such as the main object method and linear weighted sum method, were applied on suspension optimization. Based on this, a new method for computing weighting coefficients was raised.3. The body vertical acceleration, body pitch angular acceleration, and suspension working space were analyzed as objective functions. A method, combining m language programs and SIMULINK model, was adopted. The relationship between objective functions and the value of each objective function were obtained. Based on the concept of Pareto-optimal, the Pareto-optimal set was obtained by programming, and also the corresponding suspension parameters. The constrained Pareto-optimal solution was obtained based on the unconstrained Pareto-optimal solution.