Authors: Xingtao Liao Qing Li Xujing Yang Weigang Zhang Wei Li
Publish Date: 2007/11/20
Volume: 35, Issue: 6, Pages: 561-569
Abstract
In automotive industry structural optimization for crashworthiness criteria is of special importance Due to the high nonlinearities however there exists substantial difficulty to obtain accurate continuum or discrete sensitivities For this reason metamodel or surrogate model methods have been extensively employed in vehicle design with industry interest This paper presents a multiobjective optimization procedure for the vehicle design where the weight acceleration characteristics and toeboard intrusion are considered as the design objectives The response surface method with linear and quadratic basis functions is employed to formulate these objectives in which optimal Latin hypercube sampling and stepwise regression techniques are implemented In this study a nondominated sorting genetic algorithm is employed to search for Pareto solution to a fullscale vehicle design problem that undergoes both the full frontal and 40 offsetfrontal crashes The results demonstrate the capability and potential of this procedure in solving the crashworthiness design of vehicles
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