Research on lightweight and fatigue life of engine hood based on multi-objective particle swarm optimization

被引:12
|
作者
Li, Wei [1 ]
Long, Yan [2 ]
Liu, Xueqiang [2 ]
Zhang, Henghai [1 ]
Wang, Xiaojun [3 ]
机构
[1] Shandong Jiaotong Univ, Coll Automot Engn, Jinan, Peoples R China
[2] FAW Volkswagen Automot Co Ltd, Dept Tech Dev, Changchun, Peoples R China
[3] Shandong Jiaotong Univ, Sch Construct Machinery, 5001 Haitang Rd,Changqing Univ Sci Pk, Jinan 250357, Peoples R China
关键词
Multi-objective optimization; fuzzy membership functions; best compromise solution; finite element model; stiffness; COMPROMISE; DECISION;
D O I
10.1177/16878132221114210
中图分类号
O414.1 [热力学];
学科分类号
摘要
A multi-objective optimization method is presented in this paper, aiming at improving the fatigue life of the engine hood while achieving light weight. By analyzing the factors affecting the fatigue life of the engine hood, a multi-objective optimization model was established that considered five design variables including the thickness of the inner plate, the thickness of the outer plate, the stiffness of the hook, the stiffness of the sealing strip, and the height of the buffer block. Then, the multi-objective particle swarm method was used for optimization, and the optimal solution was obtained in the form of a Pareto set. The ideal compromise solution was determined from the Pareto set by using fuzzy membership functions. On this basis, the optimal solution was determined from the Pareto set by comprehensively considering the steel plate material specification, mold and cost constraints. The torsional deformation test and switch fatigue test show that for the optimized engine hood, the fatigue life is increased by 117%, the mass is reduced by 0.51 kg, and the torsional deformation of the engine hood does not increase significantly. The proposed multi-objective optimization method is proved to be feasible and effective in improving engine hood fatigue life and lightweight design.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] Research on Multi-Objective Optimization of Smart Grid Based on Particle Swarm Optimization
    Long, Fei
    Jin, Bo
    Yu, Zheng
    Xu, Huan
    Wang, Jingjing
    Bhola, Jyoti
    Shavkatovich, Shavkatov Navruzbek
    ELECTRICA, 2023, 23 (02): : 222 - 230
  • [2] Research on modified multi-objective particle swarm optimization
    College of Information Science and Engineering, Zhejiang University, Hangzhou 310027, China
    不详
    不详
    Kongzhi yu Juece Control Decis, 2009, 11 (1713-1718+1728):
  • [3] Research on Multi-Objective Multidisciplinary Design Optimization Based on Particle Swarm Optimization
    Wang, Yangyang
    Han, Minghong
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON RELIABILITY SYSTEMS ENGINEERING (ICRSE 2017), 2017,
  • [4] Multi-Objective Particle Swarm Optimization Based Transportation Problem Research
    Shen Zheyu
    Zhang Hongwei
    EBM 2010: INTERNATIONAL CONFERENCE ON ENGINEERING AND BUSINESS MANAGEMENT, VOLS 1-8, 2010, : 2798 - 2801
  • [5] Multi-objective optimization of lightweight and fatigue life for car door
    Long Y.
    Jiang L.
    Liu X.
    Xiong H.
    Chen Z.
    Zhong H.
    Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology), 2019, 50 (11): : 2732 - 2742
  • [6] Multi-Objective Particle Swarm Optimization based on particle density
    Hasegawa T.
    Ishigame A.
    Yasuda K.
    IEEJ Transactions on Electronics, Information and Systems, 2010, 130 (07) : 1207 - 1212+16
  • [7] Research on improved multi-objective particle swarm optimization algorithms
    Zhao, Duo
    Jin, Weidong
    APPLIED ARTIFICIAL INTELLIGENCE, 2006, : 231 - +
  • [8] The Research of Parallel Multi-objective Particle Swarm Optimization Algorithm
    Wu Jian
    Tang XinHua
    Cao Yong
    2014 5TH IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE (ICSESS), 2014, : 300 - 304
  • [9] Robust Lightweight Neural Network Architecture Search Based on Multi-objective Particle Swarm Optimization
    Chen, Peipei
    Yan, Li
    Du, Yi
    ADVANCES IN SWARM INTELLIGENCE, PT I, ICSI 2024, 2024, 14788 : 430 - 441
  • [10] An improved multi-objective optimization algorithm with mixed variables for automobile engine hood lightweight design
    Han Li
    Zhao Liu
    Ping Zhu
    Journal of Mechanical Science and Technology, 2021, 35 : 2073 - 2082