Multi-condition and multi-objective conceptual optimization design of automotive front subframe

The lightweight design of the automotive front subframe was performed by combining multi-condition topology optimization and multi-objective optimization approaches. Firstly, to avoid the singularity of the research condition, a rigid-flexible coupled multibody dynamic model of the front suspension was established to extract the loads at articulation points of the subframe under typical working conditions. Then, a finite element model of the front subframe was constructed for strength and modal analysis. Multi-condition topology optimization of the front subframe envelope was performed utilizing the compromise programming approach. The subframe was redesigned according to the optimization results to establish an explicit parametric model, which avoided the blindness of optimization. Three approximate models were established through the optimal Latin hypercube test method to improve the efficiency of subsequent optimization. Furthermore, three algorithms were employed for multi-objective optimization based on the approximate model with the highest accuracy. To enhance the reliability of the optimization results, a comparison of the lightweighting effect of the three algorithms was performed, and the NSGA-II algorithm was determined as the final algorithm due to its greater effectiveness in lightweighting. The optimized front subframe has met various performance specifications while increasing the first-order frequency by 10 Hz and reducing weight by 3.27 kg.