Search Results

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.

To design and optimize the vehicle driveline is necessary to decrease the fuel consumption and improve dynamic performance. This paper describes a methodology to optimize the driveline design including the axle ratio, transmission shift points and transmission shift ratios considering uncertainty. A new and flexible tool for modeling multi-domain systems, Modelica, is used to carry out the modeling and analysis of a vehicle, and the multi-domain model is developed to determine the optimum design in terms of fuel economy, with determinability. Secondly, a robust optimization is carried out to find the optimum design considering uncertainty. The results indicate that the fuel economy and dynamic performance are improved greatly.