Automated generation of physical surrogate vehicle models for crash optimization

Abstract

A challenge in the design and optimization of vehicle structures is the high computational costs required for crash analysis. In this paper an automated model generation for simplified vehicle crash models is presented. The considered crash load cases are the US NCAP (100 %, 56 km/h), the Euro NCAP (40 %, 64 km/h) and the IIHS Small Overlap (25 %, 64 km/h). The generation of the physical surrogate vehicle models is based on different sub-steps which were automated using a process chain. With this process chain it is possible to evaluate very efficiently the influence of structural modifications on the global crash behavior. During the model generation the crash behavior of the surrogate model is directly compared with the full vehicle model to enable a direct assessment of the model quality. Since the interface, where the model is cut, is an important factor for the obtained correlation, different interface positions were analysed. With obtained solutions it is possible to identify the interface position, which fulfils the required correlation by a given computational time. Additionally, the interface discretisation is analyzed to identify the model configuration with the highest correlation. This investigation was performed for three different vehicle models.