The complicated nature of the physical crash processes of complex vehicle structures makes design optimization for crashworthiness a very challenging task. Moreover, large scale and highly nonlinear nature of crashworthiness simulations of vehicle structure make it impractical to conduct direct optimization on the full nonlinear model of the structure. The main objective of the thesis is to present a systematic and practical methodology to conduct vehicle crashworthiness design optimization efficiently at early stages of design. The thesis includes four main parts. In the first part, an efficient and practical methodology for design optimization of vehicle structures under frontal impact for crashworthiness improvement is presented. The proposed methodology is based on identifying the main vehicle structural part contributing most to the total amount of impact energy absorbed in the whole vehicle structure. The computationally efficient surrogate model of expensive nonlinear finite element simulation of this major vehicle part is developed and then integrated with gradient based optimization algorithm to maximize its absorbed impact energy while guarding against increase in its weight. In the second part, a methodology for deriving the important relation between minimum structural weight and maximum impact energy is presented. The proposed methodology is based on the principle of the Pareto front and multiobjective optimization. The methodology enables the designer to evaluate the crashworthiness performance of any suggested design easily and effectively. Moreover, the methodology provides different optimum designs from which the designer can easily select the optimum design variables to improve the performance of the initial design. In the third part, the crashworthiness behavior of simple thin walled structures and vehicle structural components made of magnesium due to its light weight is examined and a new methodology for material design optimization is presented. The proposed methodology adds material type as design variables to formal size design variables. Direct optimization using the genetic algorithm is conducted to find the optimum material combination and part's thicknesses to improve the crashworthiness performance of the vehicle structure. Finally in the fourth part, the effect of imperfection on crush elements performance is studied. Different imperfection configurations are proposed to improve the crashworthiness performance of crush elements. The genetic algorithm is directly combined with nonlinear finite elements models to search for optimum imperfection values. The results show that the crashworthiness performance of crush elements can be greatly improved through introduction of proper imperfection. Using the proposed methodologies, the current research presents a fundamental and systematic study to conduct design optimization of vehicle structures practically and efficiently
