Otimização do peso de roda de material compósito sob impacto lateral

Abstract

The application of composite materials in the automotive industry is motivated by the improvement of vehicle performance and energy efficiency. In this context, numerical simulation and optimization techniques become essential for the design of increasingly lightweight structures. This work proposes a methodology for minimizing the weight of composite wheels considering lateral impact requirements, through the optimization of the number of plies and their orientations. Stiffness reduction is adopted as a design constraint, considering the damage to the plies after impact. Since impact simulations demand extensive time and computational resources, the optimization is based on surrogate modeling, using radial basis functions with sequential refinement. To enable the use of surrogate models with variable number of plies, the optimization problem is formulated in terms of lamination parameters. Stacking sequence retrieval from a set of lamination parameters is performed using a genetic algorithm to minimize the mean square error. The optimization methodology was validated using test functions and a laminated composite plate problem involving buckling, for which the analytical solution is known. In the wheel optimization, using surrogate modeling, 58 evaluations of the high-fidelity model (developed in the commercial software Ansys LS-DYNA) were necessary for the optimization process to converge. This optimization resulted in a 7.51 kg wheel, representing a 27% reduction compared to a non-optimized wheel (reference design). Comparison with commercial wheels showed that the obtained wheel is 23% and 5% lighter than aluminum and composite wheels, respectively. In addition to the weight reduction, it was possible to maximize post-impact stiffness for the optimal number of plies.