Multiobjective optimization design for vehicle occupant restraint system under frontal impact
Occupant Restraint System (ORS) can effectively protect passengers from severe injury in vehicle collision, thus its design signifies a key issue in automobile engineering. To ensure a high safety rating, e.g. five or at least four stars in the European New Car Assessment Program (Euro-NCAP) rating system, which has been widely used to rate the different vehicles from different manufacturers, design optimization becomes essential. Nevertheless, the effectiveness of conventional mathematical programming methods directly integrated with numerical simulation and sensitivity analysis for optimization is of limited practical value, due to high complexity of structures, nonlinearity of materials and deformation involved. To address the issue, this paper combines a Kriging (KRG) model with Non-dominated Sorting Genetic Algorithm II (NSGA-II) for vehicle ORS design. The ORS design of a 40% Offset Deformable Barrier (ODB) frontal impact test with the collision speed of 64 km/h is exemplified for the presented method. The results show that the KRG model can well predict the ORS responses for the design. Finally, the optimum result is verified by using sled physical tests. It is found that the ORS performance can be substantially improved for meeting product development requirements through the proposed approach.
multiobjective optimization occupant restraint systems kriging simulation analysis