Aluminum Cross-Car Beam is significantly lighter than the conventional steel counterpart and presents superior energy absorption characteristics. The challenge is however, its considerably higher cost, rendering it difficult for the aluminum one to compete in the automotive market. In this work, using material distribution techniques and stochastic optimization, a Multidisciplinary Design Optimization procedure is developed to optimize an existing Cross-Car Beam model with respect to the cost. Topology, Topography, and gauge optimizations are employed in the development of the optimization disciplines. Based on a qualitative cost assessment, penalty functions are designed to penalize costly designs. Noise-Vibration-Harshness (NVH) performance is the key constraint of the optimization. To fulfill this requirement, natural frequencies are obtained using modal analysis. Undesirable designs with respect to the NVH criteria are gradually eliminated from the optimization cycles. The new design is verified by static loading scenario and evaluated in terms of the cost saving it offers.

Aluminum Cross-Car Beam is significantly lighter than the conventional steel counterpart and presents superior energy absorption characteristics. The challenge is however, its considerably higher cost, rendering it difficult for the aluminum one to compete in the automotive market. In this work, using material distribution techniques and stochastic optimization, a Multidisciplinary Design Optimization procedure is developed to optimize an existing Cross-Car Beam model with respect to the cost. Topology, Topography, and gauge optimizations are employed in the development of the optimization disciplines. Based on a qualitative cost assessment, penalty functions are designed to penalize costly designs. Noise-Vibration-Harshness (NVH) performance is the key constraint of the optimization. To fulfill this requirement, natural frequencies are obtained using modal analysis. Undesirable designs with respect to the NVH criteria are gradually eliminated from the optimization cycles. The new design is verified by static loading scenario and evaluated in terms of the cost saving it offers.