Research on Lightweight Multi-objective Optimization for Closed Body-in-White Structure

摘要

The 100% frontal crash and side impact performances of a passenger car are analyzed and compared with tests. The structural optimization of the Closed Body-in-White (BIW) is divided into two stages which are 100% frontal crash safe part optimization and side impact safe part optimization. Use the Optimal Latin hypercube (Opt LHD) design method to generate sample points. Take the Radial Basis Functions (RBF) neural network method to establish optimization approximation model. The non-dominated sorting genetic algorithm (NSGA-II) was used to conduct multi-objective collaborative optimization design. The results show that the total mass of the closed BIW is reduced 9.745 kg; the light weight rate was 10.27%. The Crashworthiness performance of the closed BIW does not change obviously.