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As conventional vehicle design is adjusted to suit the needs of all-electric, hybrid, and fuel-cell powered vehicles, designers are seeking new methods to improve system-level design and enhance structural efficiency; here, multi-material optimization is suggested as the leading method for developing these novel architectures. Currently, diverse materials such as composites, high strength steels, aluminum and magnesium are all considered candidates for advanced chassis and body structures. By utilizing various combinations and material arrangements, the application of multi-material design has helped designers achieve lightweighting targets while maintaining structural performance requirements. Unlike manual approaches, the multi-material topology optimization (MMTO) methodology and computational tool described in this paper demonstrates a practical approach to obtaining the optimum material selection and distribution of materials within a complex automotive structure.

As automakers continue to develop new lightweight vehicles, the application of multi-material parts, assemblies and systems is needed to enhance overall performance and safety of new and emerging architectures. To achieve these goals conventional material selection and design strategies may be employed, such as standard material performance indices or full-combinatorial substitution studies. While these detailed processes exist, they often succeed at only suggesting one material per component, and cannot consider a clean-slate design; here, multi-material topology optimization (MMTO) is suggested as an effective computational tool for performing large-scale combined multi-material selection and design. Unlike previous manual methods, MMTO provides an efficient method for simultaneously determining material existence and distribution within a predefined design domain from a library of material options.