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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.

This article presents a new reliability-based design optimization procedure for the vertical vibration issues raised by a modified electric vehicle using fourth-moment polynomial standard transformation method. First, the fourth-moment polynomial standard transformation method with polynomial chaos expansion is used to obtain the reliability index of uncertain constraints in the reliability-based design optimization which is highly precise and saves computing time compared with other common methods. Next, the half-car model with nonlinear suspension parameters for the modified electric vehicle is investigated, and the response surface methodology is adopted to approximate the complex and time-consuming vertical vibration calculation to the polynomial expressions, and the approximation is validated for reliability-based design optimization results within permissible error level. Then, reliability-based design optimization results under both deterministic and uncertain load parameters are shown and analyzed. Unlike the traditional vertical vibration optimization that only considers one or several sets of load parameters, which lacks versatility, this article presents the reliability-based design optimization with uncertain load parameters which is more suitable for engineering. The results show that the proposed reliability-based design optimization procedure is an effective and efficient way to solve vertical vibration optimization problems for the modified electric vehicle, and the optimization statistics, including the maximum probability interval, can provide references for other suspension dynamical optimization.

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