Kinematic and Dynamic Analysis for a New MacPherson Strut Suspension System

The present paper undertakes kinematic and dynamic analysis of front suspension system. The investigated model is a full-scale Macpherson which is a multibody system. Two degree of freedom model is considered here to illustrate the vertical displacement of sprung mass and unsprung mass with using displacement matrix. Ride and handling parameters including displacement of sprung and unsprung masses, camber/caster angle, and track changes are derived from the relationships. Moreover, geometrical model and equations are validated by Adams/Car software. The kinematic and dynamic results have been compared in both analytical and numerical outputs for verification. The proposed analytical model shows less than 5% differences with a complicated multibody model.

Design optimization of minivan MacPherson-strut suspension system based on weighting combination method and neighborhood cultivation genetic algorithm

In this paper, the kinematic characteristic analysis and optimization design of a minivan MacPherson-strut suspension system are performed. Design requirements of a minivan suspension system are described first, and then the design process is presented. A typical MacPherson suspension model of the minivan is conducted. Through the established model, the simulation of parallel wheel travel of the suspension system of the minivan is carried out and analyzed. After initial analysis, wheel alignment parameters especially the toe angle and camber angles need to be optimized to meet the requirements of the desired design value. The characteristic curves of wheel alignment parameters are drawn and the corresponding non-ideal characteristics are found. The optimization objective is to reduce the variation of the unreasonable alignment parameters, and the design variables are given through the sensitivity analysis. The design parameters are reasonably grouped according to different kinematic characteristics, thus, a unified objective function is established by direct weighing combination method. Finally, the established objective function is optimized and designed with neighborhood cultivation genetic algorithm. By comparing the original and optimized results, the better wheel alignment parameters are obtained and the system performances of suspension are further improved.