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A robust design procedure is applied to achieve improved vehicle handling performance as an integral part of simulation-based vehicle design. This paper presents a hybrid robust design method, the robust design process strategy (RDPS), which makes full use of the intense complementary action of characteristics between the Response Surface Methodology (RSM) and the Taguchi method, to get the robust design of the vehicle handling performance. The vehicle multi-body dynamic model is built in the platform that is constructed by the software of iSIGHT, ADAMS/CAR, and MATLAB. The design-of-experiment method of the Latin Hypercube (LHC) is used to obtain the approximate area values, and then the RDPS is utilized to achieve improved vehicle handling performance results. The validation is made by the Monte Carlo Simulation Technique (MCST) in terms of the effectiveness of the RDPS in solving robust design problems.

This paper investigates a hierarchical optimization procedure for the optimum synthesis of a double-axle steering mechanism by considering the dynamic load of a vehicle which is seldom discussed in the previous literature. Firstly, a multi-body model of double-axle steering is presented by characterizing the detailed leaf spring effect. Accordingly, the influences of dynamic load including the motion interference of steering linkage resulted from the elastic deformation of leaf spring, and the effects of wheel slip angle and the position discrepancy of wheel speed rotation centers are explored systematically. And then, a hierarchical optimization method based on target cascading methodology is proposed to classify the design variables of double-axle steering mechanism into four levels. At last, a double-axle steering mechanism of a heavy-duty truck is utilized to demonstrate the validity of this method.

Due to the influence of non-linear dynamic characteristic of clutch, time-delays, external disturbance and parameter uncertainty, it is difficult to control the automated clutch precisely during the engaging process of the automated clutch for automatic mechanical transmission (AMT) vehicles. Here, an enhanced fuzzy sliding mode controller (EFSMC) has been proposed to control the automated clutch. To meet the real-time requirement of the automated clutch, the region-wise linear technology is adapted to reduce the fuzzy rules of the EFSMC. The simulation results have shown that the proposed controller can achieve a higher performance with minimum reaching time and smooth control actions. In addition, it shows that the controller is effective and robust to the parametric variation and external disturbance.