Multiobjective reliability-based optimization for design of a vehicledoor

  • Authors:

  • Jianguang Fang;Yunkai Gao;Guangyong Sun;Qing Li

  • Affiliations:

  • School of Automotive Studies, Tongji University, Shanghai 201804, China;School of Automotive Studies, Tongji University, Shanghai 201804, China;State Key Laboratory of Advanced Design and Manufacture for Vehicle Body, Hunan University, Changsha 410082, China;School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney, Sydney, NSW 2006, Australia

  • Venue:
  • Finite Elements in Analysis and Design
  • Year:
  • 2013

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Abstract

Structural optimization for vehicle door signifies one of the key topics of research to continuously improve its performances. However, majority of the studies to date have not considered uncertainties whilst it has been known that a deterministic optimization may lead to an unreliable design in practice. In this paper, a multiobjective reliability-based design optimization (MORBDO) procedure is proposed to explore the design of vehicle door. To improve the efficiency of optimization, response surface method (RSM) is used to replace the time-consuming finite element simulations. In conjunction with Monte Carlo simulation and descriptive sampling technique, probabilistic sufficiency factor is adopted as a design constraint. The multiobjective particle swarm optimization (MOPSO) algorithm is employed to perform the optimization. The results demonstrate that the proposed optimization procedure is capable of generating a well-distributed Pareto frontier of reliable solutions, and it is suggested to select an optimum from relative insensitive regions. Moreover, the influence of varying the uncertainty and increasing the target reliability level in the optimization results is analyzed, which provided decision-makers with insightful design information.