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Automotive Engineering ›› 2019, Vol. 41 ›› Issue (9): 1102-1107.doi: 10.19562/j.chinasae.qcgc.2019.09.017

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Multi-objective Lightweight Optimization of Parametric FrontendBIW Structure Based on Analysis-driven Design

Zhang Shuai1, Guo Zhijun1 & Wang Chuanqing2   

  1. 1.College of Vehicle and Transportation Engineering, Henan University of Science and Technology, Luoyang 471003;
    2.Research and Design Center, BAIC Motor Co., Ltd., Beijing 101300
  • Received:2018-09-03 Revised:2018-11-25 Online:2019-09-25 Published:2019-10-12

Abstract: The parametric frontend model built with SFE-CONCEPT software and the finite element model for the rest part of body-in-white (BIW) are put together to form a complete BIW model, and the complete model of vehicle is composed by all subassemblies using modularization technique. A frontal crash safety simulation on vehicle model is conducted and its results are compared with that of real vehicle test, verifying the effectiveness of frontal crash safety simulation. The frontal crash safety parameters including acceleration peak are extracted by editing batch script file, truly embodying the concept of “analysis driven design”. Six shape variables and seven panel thicknesses in parametric frontend BIW are chosen as design variables for lightweight optimization. The optimal Latin hypercube scheme in the design of experiment is chosen to generate sample points, fulfilling the automatic construction and accuracy verification of Kriging metamodel. NSGA-II algorithm is adopted to perform optimization with compromised solution set obtained, from which the one with the minimum mass of frontend BIW is finally selected as the optimum solution. After optimization the mass of frontend BIW reduced by 7.02%, with its performances almost remain unchanged, the acceleration peak on left and right side lowers by 0.99% and 1.31%, while the average acceleration on left and right side increases by 15.41% and 8.67% respectively, and among four doors, some deformations increase and some deformations decrease with a maximum changing ratio of 10.6%.

Key words: parametric frontend BIW model, combined BIW model, multi-objective lightweight optimization, analysis-driven design