Reliability-based robust optimization design of vehicle braking systems under multiple failure modes based on high-precision surrogate models

被引:0
作者
Yang, Zhou [1 ]
Zhang, Jing [1 ]
Bai, Hui [1 ]
Wang, Hongju [1 ]
Yang, Xu [1 ]
机构
[1] Northeastern Univ, Sch Mech Engn & Automat, 11,Lane 3,Wenhua Rd,Nanhu St, Shenyang 110000, Liaoning, Peoples R China
基金
中国国家自然科学基金;
关键词
Reliability optimization; disc brake; surrogate model method; failure modes; reliability analysis; RESPONSE-SURFACE METHOD; DISC BRAKE;
D O I
10.1177/1748006X251325910
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In the process of enhancing the braking safety and performance stability of the automotive braking system, comprehensively considering the failure modes of the braking system and obtaining an accurate reliability function model are crucial for completing the reliability-based robust optimization design (RBROD) of the braking system. In engineering practice, the modal characteristics and thermal-mechanical coupling reliability robust design method under multiple failure modes encounter problems such as low computational efficiency and difficult problem-solving. To tackle these issues, this paper proposes a new method called Reliability-Based Robust Optimization Design under Multi-Failure Mode (MF-RBROD). In the proposed optimization method, the deep learning surrogate model replaces the experiments and finite element analysis (FEA) in the original adaptive process, greatly saving time and cost. The accuracy of the finite element model is determined by comparing the modal experimental results with the finite element analysis results of the disc brake. A total of 300 training samples and 50 testing samples were obtained. After establishing the reliability performance function through samples, among the four surrogate model methods, the DL-AK method with the smallest average relative error was selected to conduct a reliability sensitivity analysis of the braking system. The error of this method is only 0.01911%, which is significantly better than the other three surrogate models. The MF-RBROD model was formed by weighted transfer method. The MF-RBROD method has effectively improved the reliability of the disc brake. Specifically, the frequency reliability has been significantly enhanced from 0.9414 to 0.9971, while the thermo-mechanical coupling reliability has been raised from 0.9483 to 0.9951. At the same time, the sensitivities of various design parameters affecting the braking system reliability and the total mass of the disc brake were significantly reduced. The optimization results of the disc brake have demonstrated the effectiveness of the MF-RBROD method.
引用
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页数:20
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  • [1] Adaptive subset searching-based deep neural network method for structural reliability analysis
    Bao, Yuequan
    Xiang, Zhengliang
    Li, Hui
    [J]. RELIABILITY ENGINEERING & SYSTEM SAFETY, 2021, 213
  • [2] Thermal analysis of a solid brake disc
    Belhocine, Ali
    Bouchetara, Mostefa
    [J]. APPLIED THERMAL ENGINEERING, 2012, 32 : 59 - 67
  • [3] A New Kriging-Based Learning Function for Reliability Analysis and Its Application to Fatigue Crack Reliability
    Chai, Xiaodong
    Sun, Zhili
    Wang, Jian
    Zhang, Yibo
    Yu, Zhenliang
    [J]. IEEE ACCESS, 2019, 7 : 122811 - 122819
  • [4] Application of the response surface methods to solve inverse reliability problems with implicit response functions
    Cheng, Jin
    Li, Q. S.
    [J]. COMPUTATIONAL MECHANICS, 2009, 43 (04) : 451 - 459
  • [5] An experimental-numerical modal analysis for the study of shell-fluid interactions in a clamped hemispherical shell
    Eslaminejad, Ashkan
    Ziejewski, Mariusz
    Karami, Ghodrat
    [J]. APPLIED ACOUSTICS, 2019, 152 : 110 - 117
  • [6] Neural Networks Combined with Importance Sampling Techniques for Reliability Evaluation of Explosive Initiating Device
    Gong Qi
    Zhang Jianguo
    Tan Chunlin
    Wang Cancan
    [J]. CHINESE JOURNAL OF AERONAUTICS, 2012, 25 (02) : 208 - 215
  • [7] Efficient response surface method for high-dimensional structural reliability analysis
    Hadidi, Ali
    Azar, Bahman Farahmand
    Rafiee, Amin
    [J]. STRUCTURAL SAFETY, 2017, 68 : 15 - 27
  • [8] A new direct second-order reliability analysis method
    Huang, Xianzhen
    Li, Yuxiong
    Zhang, Yimin
    Zhang, Xufang
    [J]. APPLIED MATHEMATICAL MODELLING, 2018, 55 : 68 - 80
  • [9] Aspects of disc brake judder
    Jacobsson, H
    [J]. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING, 2003, 217 (D6) : 419 - 430
  • [10] Deep Neural Network Technique for High-Dimensional Microwave Modeling and Applications to Parameter Extraction of Microwave Filters
    Jin, Jing
    Zhang, Chao
    Feng, Feng
    Na, Weicong
    Ma, Jianguo
    Zhang, Qi-Jun
    [J]. IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, 2019, 67 (10) : 4140 - 4155