Reliability analysis of automotive body-door subsystem

This paper proposes an efficient method for the reliability analysis of a vehicle body-door subsystem with respect to one of the important quality issues—the door closing energy. The developed method combines optimization-based and simulation-based approaches and is particularly applicable for problems with highly non-linear and implicit limit state functions. The proposed approach consists of two major parts. In the first part, an optimization-based method is used to search for the most probable point (MPP) on the limit state. This is achieved by using an adaptive response surface constructed through an optimal symmetric Latin hypercube design of experiments. In the second part, a multi-modal adaptive importance sampling method is proposed using the MPP information from the first part as the starting point. It is demonstrated through numerical examples that the proposed method is superior to existing methods in terms of efficiency and accuracy. The proposed method is illustrated for application to the reliability estimation with respect to the door closing energy problem. A generalized framework for reliability estimation is then established for problems with large numbers of random variables and complicated limit states.