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Optimization design for vehicle front-end structures has proven rather essential and been extensively used to improve the vehicle performance. Nevertheless, the front-end structure needs to meet the requirement of both pedestrian safety and structural stiffness which are somewhat contradicting to each other. Furthermore, an optimal design could become less meaningful or even unacceptable when some uncertainties present. In the paper, a multi-objective discrete robust optimization (MODRO) algorithm is used to minimize the injury of head and maximize the structural stiffness involving uncertainties. MODRO algorithm is achieved by coupling grey relational analysis (GRA) and principal component analysis (PCA) with Taguchi method. The optimized result shows that the MODRO algorithm improved performance of pedestrian head injury and robustness of the vehicle front-end structure.

This study aims to explore the influence of a vehicle front-end shape on pedestrian and cyclist injuries. The injuries of head, upper leg and lower leg based on 50th human model are considered as design response. A multi-objective optimization approach is developed to design and optimize the front shape for minimizing injury risks of pedestrian and cyclist in this study. The numerical models of pedestrian-vehicle and cyclist-vehicle impact is constructed and validated first. Then, the optimal Latin hypercube sampling (OLHS) method is adopted for design of experiment (DOE) and the surrogate model is constructed through radial basis function (RBF). The optimal problems involving a number of objectives are solved by the multi-objective particle swarm optimization (MOPSO) algorithm in this study.