Citation

Lin C, Gao F, Bai Y. Int. J. Crashworthiness 2018; 23(3): 290-301.

Copyright

(Copyright © 2018, Informa - Taylor and Francis Group)

DOI

10.1080/13588265.2017.1317466

PMID

unavailable

Abstract

The determinate multiobjective optimisation (DMOO) without considering effects of uncertainties on vehicle body design may fail to satisfy the desired property in practice. In this paper, a multiobjective reliability-based design optimisation (MORBDO) procedure is proposed to perform the design for front structure of an electric vehicle. In which, body performances including full-lap frontal crashworthiness, modal characteristic and lightweight level are involved and coordinated, and the thickness of five key components with geometric tolerances are selected as design variables. Probabilistic constraint in MORBDO is addressed by Monte Carlo simulation (MCS) technique-based probabilistic sufficiency factor (PSF) method. To improve the accuracy of optimisation results, a closed-loop system named hybrid metamodel accuracy improvement strategy is presented here by organising adaptive optimum metamodel selection and the max-min distance approach-based new samples addition technique together. The optimisation problem is solved by the multiobjective particle-swarm-optimisation algorithm. The effectiveness of the proposed procedure is certified by successfully obtaining more accurate and reliable alternative optimum schemes in the design for the front body structure in comparison with DMOO, normal PSF method and safety factor method.

Language: en

Keywords

electric car body-in-white; full-lap frontal crashworthiness; metamodel accuracy improvement strategy; Multiobjective reliability-based optimisation; probabilistic sufficiency factor