A vehicle collision surrogate model based on numerical simulation and machine learning
CSTR:
Author:
Clc Number:

U462;U493

  • Article
  • | |
  • Metrics
  • |
  • Reference [16]
  • |
  • Related [20]
  • | | |
  • Comments
    Abstract:

    By building a three-dimensional finite element model of a pickup truck, the dynamic processes of a truck colliding against a rigid wall and the collision between two trucks are numerically simulated, and the corresponding collision force-displacement curves of the truck with different initial speeds are obtained. Taking the initial speed of the truck as the input and the collision force-displacement curve as the output, the BP neural network machine learning algorithm is used to establish the vehicle collision surrogate model in the full speed domain. The numerical simulation samples are divided into a training set and a test set. The surrogate model is trained with the training set and its accuracy is verified by the test set samples. The model can be used to predict the force-displacement curve of a vehicle at an arbitrary collision speed quickly, providing an instruction for its safety design.

    Reference
    [1] 李俊峰. 中国汽车被动安全标准探讨:浅谈汽车柱状碰撞试验[C]//市场践行标准化:第十一届中国标准化论坛论文集.成都:第十一届中国标准化论坛, 2014. Li J F. Discussion on Chinese passive safety standard for automobiles-brief talk on cylindrical collision test of automobiles[C]//Market Fulfilling Standardizaiton:Proceedings of the 11th China Standardization Forum. Chengdu:The 11th China Standardization Forum, 2014. (in Chinese)
    [2] 王婷. 我国合资汽车企业效率比较及相关因素研究[D]. 上海:东华大学, 2012. Wang T. Study on efficiency of joint ventures in automotive industry and related factors[D]. Shanghai:Donghua University, 2012. (in Chinese)
    [3] 邓子兵. 乘用车车身结构件安全性试验系统的研制[D]. 上海:上海交通大学, 2008. Deng Z B. Research and development of a safety test system for vehicle body structure[D]. Shanghai:Shanghai Jiao Tong University, 2008. (in Chinese)
    [4] 张静, 栾寅征. 那些年,"碰撞"垫底的车型[J]. 汽车观察, 2012(7):94-99. Zhang J, Luan Y Z. In those years, colliding car remains in bottom place[J]. Automotive Observer, 2012(7):94-99. (in Chinese)
    [5] 王强. 汽车追尾碰撞安全性及乘员损伤仿真分析[D]. 沈阳:东北大学, 2010. Wang Q. Simulation analysis of automobile crash at the rear end and safety of passengers[D]. Shenyang:Northeastern University, 2010. (in Chinese)
    [6] 昝竹青.冲压成型工艺对轿车车门碰撞性能的影响研究[D].哈尔滨:哈尔滨工程大学, 2013. Zan Z Q. Influence of forming result on crash behavior of car door[D]. Harbin:Harbin Engineering University, 2013. (in Chinese)
    [7] 黄金陵,贾洪波.车身碰撞仿真技术在红旗轿车车身开发中的应用[J].汽车工程,1998,20(5):257-261,301. Huang J L, Jia H B. Application of numerical simulation techniques in car body design process of "HONGQI"[J]. Automotive Engineering, 1998,20(5):257-261,301. (in Chinese)
    [8] Hu Y M, Chen W, Deng Z X. Frontal crash-worthiness simulation of the Changan S6350 using the explicit finite element method[C]//The 11th International Pacific Conference on Automotive Engineering(IPC-11), November 6-9, 2001, Shanghai, China. 2001:9.
    [9] 张晓云. 基于有限元法和神经网络技术的汽车碰撞事故再现[J]. 机械工程学报, 2007, 43(3):143-147, 153. Zhang X Y. Vehicle crash accident reconstruction based on FEM and neural networks[J]. Chinese Journal of Mechanical Engineering, 2007, 43(3):143-147, 153. (in Chinese)
    [10] 聂隐愚. 数据驱动的车辆动力学建模与仿真研究[D]. 成都:西南交通大学, 2016. Nie Y Y. Data-driven dynamics modelling and simulation research for railway vehicles[D]. Chengdu:Southwest Jiaotong University, 2016. (in Chinese)
    [11] Tang Z, Zhu Y, Nie Y, et al. Data-driven train set crash dynamics simulation[J]. Vehicle System Dynamics, 2017, 55(2):149-167.
    [12] Chen Y J, Tyan T, Farugue O. Dynamic testing and CAE modeling of engine mounts for application in vehicle crash analysis[C/OL]//SAE 2003 Warld Congress & Exhibition. USA:SAE International, 2003(2003-03-03)[2019-11-25]. https://doilorg/10.4271/2003-01-0257.
    [13] Mohri M, Rostamizadeh A, Talwalkar A. Foundations of Machine Learning[M]. The MIT Press, 2012.
    [14] Lanzi L, Bisagni C, Ricci S. Neural networks systems to reproduce crash behavior of structural components[J]. Computers & Structures, 2004, 82(1):93-108.
    [15] 张良军. Python数据分析与挖掘实战[M]. 北京:机械工业出版社, 2017. Zhang L J. Python practice of data analysis and mining[M]. Beijing:China Machine Press, 2017. (in Chinese)
    [16] Rodolfo B. Building machine learning projects with tensorflow[M]. UK:Packet Pulishing, 2016.
    Cited by
    Comments
    Comments
    分享到微博
    Submit
Get Citation

林翔,严波,牟哲岳,文楠,黄桂灶.基于数值模拟和机器学习的汽车碰撞代理模型[J].重庆大学学报,2021,44(2):86~93

Copy
Share
Article Metrics
  • Abstract:752
  • PDF: 927
  • HTML: 1166
  • Cited by: 0
History
  • Received:December 25,2019
  • Online: March 06,2021
Article QR Code