Design Optimization of a Composite Using Genetic Algorithms for the Manufacturing of a Single-Seater Race Car

The design of automobile chassis structures is fundamentally linked to the optimization of mass and structural robustness. While conventional chassis structures predominantly utilize metals, achieving further mass reduction and enhanced rigidity necessitates the adoption of composite sandwich materials, typically comprising carbon fiber-reinforced polymer (C.F.R.P.) laminate skins bonded to an aluminum honeycomb core. This study focuses on presenting a framework methodology for minimizing the mass of a race car chassis by calculating an optimal baseline lamination sequence through the modification of the composite material parameters on either side of the aluminum core, using an optimization algorithm (O.A.), finite element (F.E.) analysis, composite mechanics theory, and failure criteria. Optimal solutions were derived by varying the laminae orientation and sequence parameters under two scenarios: unconstrained and constrained laminae angles. The optimization results indicate that the proposed lamination scheme reduces mass by 12.36 kg (41.66%) compared to the original lamination, with constraints imposed on laminae angles having no significant impact on the ultimate optimal outcome.