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Hydroformed components are replacing stamped parts in automotive frames and front end and roof structures to improve the crash performance of vehicles. Due to the increasing application of hydroformed components, a better understanding of the crash behavior of these parts is necessary to improve the correlation between full-vehicle crash tests and FEM analysis. Accurately predicting the performance of hydroformed components will reduce the amount of physical crash testing necessary to develop the new components and new vehicles as well as reduce cycle time. Virgin material properties are commonly used in FEM analysis of hydroformed components, which leads to erroneous prediction of the full-vehicle crash response. Changes in gauge and material properties during the hydroforming process are intuitive and can be reasonably predicted by using forming simulations. The effects of the forming process have been investigated in the FEA models that are created for crash analyses.

The optimization method and CAE analysis have been widely used in structure design for crash safety. Combining the CAE analysis and optimization approach, vehicle structure design for crash can be implemented more efficiently. One of the recent safety desirables in structure design is to reduce vehicle pitch and drop. At frontal impact tests with unbelted occupants, the interaction between occupant's head and interior header/sun visor, which is caused by excessive vehicle pitch and drop, is not desired in vehicle crash development. In order to comply with the federal frontal crash requirements for unbelted occupant, it is necessary to manage the vehicle pitch and drop by improving structure design. In this paper, a systematic process of CAE analysis with optimization approach is applied for discovering the major structural components affecting vehicle pitch and drop.

The objective of this study is to verify the performance of a target vehicle model in vehicle-to-vehicle impact applications. In some vehicle-to-vehicle tests, the target vehicle stays the same and the bullet vehicle changes from test to test depending on the programs under evaluation. To obtain reasonable crash pulse predictions in vehicle-to-vehicle impacts, it was decided to develop an accurate and robust target vehicle model first. The development of the target vehicle model was divided into two phases, rigid barrier and vehicle-to-vehicle impacts. Twelve rigid barrier tests, including full rigid barriers, angular rigid barriers, offset rigid barriers, and fixed rigid poles were adopted in the first phase of the study to calibrate the target vehicle model. The results of the study have been reported [1]. This paper focuses on the verification of vehicle-to-vehicle impacts.

The objective of this study is to develop a target vehicle model for vehicle-to-vehicle impact applications. In order to provide reasonable predictions for crash pulses in vehicle-to-vehicle impacts, an accurate and robust target vehicle model was developed first. An ideal target vehicle model should be able to provide reasonable results when hit by different bullet vehicles at different impact speeds and under different impact conditions. This was achieved by calibrating the target vehicle model against different vehicle crash tests, which include full rigid barriers, angular rigid barriers, offset rigid barriers, and fixed rigid poles. Twelve rigid barrier tests were adopted in this study to calibrate the target vehicle model. During the calibration process, some of the vehicle structures were examined and remodeled carefully for their properties and mesh quality.