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FE-Simulation Based Optimization of an Adaptive Restraint System Considering Multiple Front-Crash Load Cases using LS-OPT

The purpose of this paper is to explore some interesting aspects of optimization for crashworthiness occupant safety applications and to propose optimization strategies for highly nonlinear problems. With the today’s state of technology it is possible to identify specific load cases and different types of occupants in the car. System parameters of the restraint system, such as trigger time for seat-belt, airbag and steering column can be adapted to particular load cases. This is refered to an adaptive restraint system. In the first part of the paper different optimization strategies are discussed and pros and cons are compared. In addition, a methodology to get a reliable surrogate model using neural networks is introduced. The surrogate model (Meta-Model or Response Surface Model) approximates the relationship between design parameters and a physical response and can be used to visualize and explore the design space. In the second part the application of the Successive Response Surface Scheme (SRSM) for the optimization of an adaptive restraint system is conducted. For this, several front crash load cases are considered. This is performed using LS-OPT (Stander et al. [11]) as optimization software and PAM-Crash as solver for the finite element occupant safety simulations. The procedure of generating an advanced meta-model to get an approximation of the global design space using neural networks is demonstrated for this example. Furthermore, the visualization of multi-dimensional meta-models in two- and three-dimensional design space is illustrated.

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