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A practical application of the Target Cascading scheme for the development of the front bumper system of a passenger car is investigated in this paper. The Target cascading in the crash performance of vehicle developments requires a systematic approach, propagating from the desired vehicle-level performance target to appropriate specifications in a system- and/or component-level. To define the values of design specification in the front bumper system, three physical variables are derived by analyzing the vehicle-level performance of the frontal impact under the high-speed (56kph NCAP frontal impact) and the low-speed (15kph RCAR structural test) crash conditions. To ensure the sequential deformation in the high-speed frontal impact and to minimize the damage of the structural member in the low-speed crash, the maximum collapse load of a crash box should be smaller than the collapse load of a front side member.

This paper is concerned with the energy management strategy of hybrid electric vehicle using stochastic dynamic programming. The aim is the control strategy of the power distribution for hybrid electric vehicle powertrains to minimize fuel consumption while maintaining drivability. The fuel economy of hybrid electric vehicle is strongly influenced by power management control strategy. Rule-based control strategy is popular strategy thanks to its effectiveness in real-time implementation, but rule should be designed and efficiency of entire drive trains is not optimized. Dynamic programming, one of optimization-based control strategy presents outstanding performance, but cannot be used as real-time control strategy directly, since its non-causal property and drawback that global optimal solution can only be obtained for specific driving cycle. In this paper, stochastic dynamic programming is applied to parallel hybrid electric vehicle to optimize vehicle performance in average sense.