Low carbon design of automobile front-end structure based on Pareto mining

Abstract

In order to improve the energy saving and emission reduction effect of vehicle front-end structure, the entropy-weight technique for order preference by similarity to an ideal solution (EW-TOPSIS) method is proposed to mine the optimal solution in the non-dominated Pareto solution sets. The automobile front-end structure is designed by adopting the integrated optimisation design method with ZL205A aluminium alloy by using vacuum investment casting. A finite element model is established to construct a radial basis function (RBF) – response surface methodology (RSM) hybrid surrogate model with specific energy absorption and mass as the optimisation objectives, and a multi-objective optimisation is carried out jointly with a multi-island genetic algorithm (MIGA). The 148 Pareto solution sets are scored and ranked using the EW-TOPSIS method, and the optimal solutions are assessed for their life cycle. The results show that the optimised cast aluminium structure reduces the mass by 49.82%, improves the energy absorption by 37.70%, and reduces the energy consumption by 4776.674 MJ and greenhouse gas emissions (GHG) emission by 176.207 kg over the 300,000 km driving range.