Multidisciplinary design optimization of vehicle body structure based on collaborative optimization and multi-objective genetic algorithm

被引：0

作者：

Wang P. ^{[1
]}

Zheng S. ^{[1
,2
]}

Wu G. ^{[1
]}

机构：

[1] College of Automotive Engineering, Tongji University

[2] School of Mechanical Engineering, University of Shanghai for Science and Technology

来源：

Jixie Gongcheng Xuebao/Journal of Mechanical Engineering | 2011年 / 47卷 / 02期

关键词：

Collaborative optimization; Lightweight; Multi-objective genetic algorithm; Multidisciplinary design optimization; Reliability-based design optimization;

D O I：

10.3901/JME.2011.02.102

中图分类号：

学科分类号：

摘要：

Multidisciplinary and multi-objective optimization design method is applied in the researches of vehicle side impact crashworthiness and NVH performances. Design of experiment(DOE) is explored to obtain the experimental scheme and perform data sampling, the response surface model (RSM) taking into account the vehicle side-impact safety, body-in-white modal frequency, static bending stiffness, torsional stiffness and lightweight is built. Determined optimization, Reliability optimization and lightweight design are operated independently on the basis of genetic algorithm. Finally, collaborative optimization which is one of the best feasible multidisciplinary design optimization approaches is combined with multi-objective genetic algorithm to carry out the optimization of vehicle body structure. Then the Pareto optimal set is obtained. The results show that the reliability optimization which considers the uncertainties of product design and production process can ensure product stability, and is more accurate than deterministic optimization. The coupling and interdisciplinary relationships of lightweight, NVH and crash safety performances are comprehensively considered during the multi-objective optimization of vehicle body structure. Thus the Pareto set is obtained and designers can choose the satisfactory optimization results according to their demands, so as to significantly reduce product development cycle and costs. © 2011 Journal of Mechanical Engineering.

引用

页码：102 / 108

页数：6

共 10 条

[1]

Kodiyalam S., Yang R.J., Gu L., Et al., Multidisciplinary design optimization of a vehicle system in a scalable, high performance computing environment, Struct. Multidisc. Optim., 26, pp. 256-263, (2004)

[2]

Yang R.J., Gu L., Tho C.H., Multidisciplinary design optimization of a full vehicle with high performance computing, The 42nd AIAA/ASME.ASCE/AHS/ASC Structures, Structural Dynamics, and Material Conference and Exhibit

[3]

Roshanian J., Keshavarz Z., Effect of variable selection on multidisciplinary design optimization: A flight vehicle example, Chinese Journal of Aeronautics, 20, pp. 86-96, (2007)

[4]

Fang H., Rais-Rohani M., Liu Z., A comparative study of metamodeling methods for multiobjective crashworthiness optimization, Computers & Structures, 82, pp. 2121-2136, (2004)

[5]

Rabeau S., Philippe D., Bennis F., Et al., Collaborative optimization of complex systems: A multidisciplinary approach, Int. J. Interact. Des. Manuf., 1, pp. 209-218, (2007)

[6]

Messac A., Ismail-Yahaya A., Multiobjective robust design using physical programming, Structural and Multidisciplinary Optimization, 23, 5, pp. 357-371, (2002)

[7]

Liu M., Wu C., Genetic algorithm using sequence rule chain for multi-objective optimization in re-entrant micro-electronic production line, Robotics and Computer-Integrated Manufacturing, 20, pp. 225-236, (2004)

[8]

Beyeng D.Y., Kyung K.C., A new response surface methodology for reliability-based design optimization, Computers & Structures, 82, pp. 241-256, (2004)

[9]

Zhang Y., He X., Liu Q., Reliability-based robust design of vehicle components with non-normal distribution parameters, Chinese Journal of Mechanical Engineering, 41, 11, pp. 102-108, (2005)

[10]

Zhang Y., Zhu P., Chen G.L., Lightweight design of automotive front side rail based on robust optimization, Thin-Walled Structures, 45, pp. 670-676, (2007)

← 1 →