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Suspension design is one of important technique to develop automobile. Since suspension system has strong non-linearity, it is difficult to optimize the suspension system by Gradient Based Method. Authors discussed the benefit of Genetic Algorithms to optimize the suspension system in this paper. Prototype of optimization system for suspension systems based on Genetic Algorithms was developed. In this system, the suspension system was analyzed and evaluated by Mechanical System Simulation Software ADAMS. The validity of the optimization system was clarified through the two case studies focusing on toe curve and lateral stiffness. Typical double wishbone type rear suspension with twenty design variables was analyzed and optimized by the optimization system.

CAE technology has been applied for the crash safety design of vehicles, however, the optimum design has not been completed for the crash behavior of the vehicles. The authors have proposed a Statistical Design Support System (SDSS), and brought forward that the SDSS is one of the available optimal approaches for the nonlinear and dynamic phenomena. In this study, the SDSS was applied for the multi-objective optimization design of the reinforced members of a vehicle, where the weight, cabin deformation, and collision acceleration were chosen as the objective functions, and the simultaneous optimization for the functions was carried out. It was shown that the SDSS could be used as a practical multi-objective optimization tool for the crash safety design of vehicles.

Currently, car bodies require further weight reduction in order to support increasing fuel economy requirements. An efficient way for light weight body design is to include body member size as a design variable in addition to part thickness. However it is currently difficult for finite element (FE) models to change member size even using current morphing techniques. To break through this challenge, a hybrid modeling approach was developed which combines shell and beam element representations of body structural members. The original member shell element thickness was decreased by 40%. Then the stiffness reduction caused by this change is offset by beam elements incorporated inside these members. These beams can represent the stiffness change due to new cross sectional dimensions or orientations without changing the original shell elements, thus avoiding modeling instabilities that can occur from morphing.

The “Statistical Design Support System” produces a new practical optimal design method. It can be used even on nonlinear behavior. The optimization can be carried out with this system using a small number of calculation results. The authors applied it to the design optimization of the occupant restraint system in order to reduce the injury criteria based on the crash simulation. In line with growing interest and improvements in technology on vehicle safety, it will be necessary to consider some different crash situations simultaneously. The authors made an optimal design taking into account the different collision conditions. This paper describes the effectivity analysis and the optimization.