STOCHASTIC OPTIMIZATION APPLICATION FOR VEHICLE STRUCTURES

摘要

With the continuous improvement of powerful computers, vehicle structural designs have been addressed using computational methods, resulting in more efficient development of new vehicles. Most simulation-based optimization generates deterministic optimal designs without considering variability effects in modeling, simulation, and/or manufacturing. This paper presents an application of a new stochastic optimization method for vehicle side impact design. Nonlinear response surface models are employed for approximations of the side impact related test performance functions to conduct this study. The main goal is to maintain or enhance the vehicle side impact test performance while minimizing the vehicle weight under various uncertainties. The new algorithm alleviates the computational burden of excessive model evaluations by estimating the objective and constraint functions during the optimization process through a reweighting method. The efficiency and accuracy of this algorithm is presented through an actual vehicle safety design problem.