An efficient lightweight design strategy for body-in-white based on implicit parameterization technique

Abstract

In the early design phase of vehicles, performing lightweight design of body-in-white (BIW) using shape, size and topology optimization is a challenge. The large amount of design parameters including size, shape of cross-sections and positions of various parts are the main contributors to the challenge, which will lead to the huge computational cost for running a large number of finite element (FE) simulations and function evaluations. To handle this problem, an efficient lightweight design strategy which integrates implicit parameterization technique, global sensitivity analysis (GSA) and Pareto set pursuing (PSP) algorithm is proposed in this paper to explore the lightweight design of BIW. Firstly, a full parameterized model of BIW is established with implicit parametrization technique via SFE-CONCEPT. Secondly, the GSA technique is used to reduce the dimensions of design space. Finally, the parameterized model of BIW is optimized by PSP method directly in the reduced design space. It is clearly shown that the optimized BIW structure signifies the noticeable improvement from the baseline model. The results demonstrate that the proposed method is capable in generating a well-distributed Pareto optimal frontier, and can largely reduce the design complexity of BIW lightweight.