基于自动化仿真与NSGA-Ⅱ算法的动力两轮车事故智能化重建方法研究

doi:10.3901/JME.2023.24.197

机械工程学报 ›› 2023, Vol. 59 ›› Issue (24): 197-208.doi: 10.3901/JME.2023.24.197

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基于自动化仿真与NSGA-Ⅱ算法的动力两轮车事故智能化重建方法研究

刘煜^1,2,3, 万鑫铭^1,2,3, 许伟^2,3, 石亮亮^2,3, 白中浩¹

1. 湖南大学汽车车身先进设计制造国家重点实验室长沙 410082;
2. 汽车噪声振动与安全技术国家重点实验室重庆 401122;
3. 中国汽车工程研究院股份有限公司重庆 401122

收稿日期:2023-03-12 修回日期:2023-10-20 出版日期:2023-12-20 发布日期:2024-03-05
通讯作者: 白中浩(通信作者),男,1978年出生,博士,教授,博士研究生导师。主要研究方向为智能与新能源汽车安全,汽车电子技术,自适应约束系统。E-mail:baizhonghao@hnu.edu.cn
作者简介:刘煜,男,1994年出生,博士。主要研究方向为车辆与交通安全。E-mail:ly_wen@hnu.edu.cn;万鑫铭,男,1978年出生,博士,教授,博士研究生导师。主要研究方向为汽车安全与轻量化,新能源汽车大数据与电池安全,智能网联汽车信息安全。E-mail:wanxinming@caeri.com.cn;许伟,男,1979年出生,博士,高级工程师。主要研究方向为汽车安全测评体系。E-mail:xuwei@caeri.com.cn;石亮亮,男,1988年出生,博士,工程师。主要研究方向为车辆与交通安全。E-mail:shiliangliang@caeri.com.cn
基金资助:
国家自然科学基金(51621004)、湖南省自然科学基金(2020JJ4184)和中国出行交通事故场景数据库(CPYF202004-GA-001)资助项目

Research on Intelligent Reconstruction Method for Powered Two-wheeler Accident Based on Automatic Simulation and NSGA-Ⅱ Algorithm

LIU Yu^1,2,3, WAN Xinming^1,2,3, XU Wei^2,3, SHI Liangliang^2,3, BAI Zhonghao¹

1. State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha 410082;
2. State Key Laboratory of Vehicle NVH and Safety Technology, Chongqing 401122;
3. China Automotive Engineering Research Institute Co., Ltd., Chongqing 401122

Received:2023-03-12 Revised:2023-10-20 Online:2023-12-20 Published:2024-03-05

摘要/Abstract

摘要： 基于试错法调节参数的事故重建过程高度依赖分析人员的经验和直觉，其效率低下且难以保证重建结果的精度。提出一种结合自动化仿真与多目标优化理论的动力两轮车事故智能化重建方法。基于ISIGHT多学科优化平台建立多刚体模型自动化运行框架；采用带精英策略的非支配排序遗传算法(NSGA-Ⅱ)对5个位置目标进行优化，选取12个初始碰撞参数作为设计变量，头-车碰撞位置和横向运动方向作为约束条件；通过2例动力两轮车事故重建验证方法的有效性。结果表明，24 h完成了480次仿真并找到最优解，平均重建目标误差低于5%，最大重建误差为12.4%。目标函数寻优过程、函数收敛趋势、仿真结果与事故事实的对比(如参与方停止位置、损伤情况、碰撞速度、碰撞后运动过程等)均表明了该方法的有效性。动力两轮车事故智能化重建方法实现了自动化参数调整、仿真运行、结果处理，显著提高了重建效率且保证了结果精度。结合自动化仿真与多目标优化的方法可广泛用于其他类型事故的重建。

关键词: 动力两轮车, 事故重建, 自动化仿真, 多目标优化, NSGA-Ⅱ

Abstract: Since manual accident reconstruction is strongly dependent on the experience and intuition of analysts with the trial-and-error method for parameter adjustment, the process is very time-consuming and the accuracy of results could not be guaranteed. An intelligent reconstruction approach is developed for powered two-wheelers(PTWs) combining automatic simulation and multi-objective optimization. Firstly, an automatic operation framework for multi-rigid models is established based on the ISIGHT program. Then, the non-dominated sorting genetic algorithm(NSGA-Ⅱ) with elite strategy is selected to optimize five position objectives, with 12 collisions parameters as design variables, and the head-vehicle collision area and lateral motion direction as constraints. Finally, two accident cases are reconstructed to verify effectiveness of the method. The results show that 480 simulations with the optimal solution are completed in 24 hours. The average error is below 5% with the maximum of 12.4%. Optimization process, convergence of the objective function, as well as the good consistency among the comparison between simulation and facts including the rest position, injury criteria, collision speed, kinematic response, demonstrate the effectiveness of the method. The intelligent method for PTWs accidents realizes automatic parameter adjustment, simulation operation, and result processing, which significantly improves the efficiency and ensures the accuracy of results. In general, the method coupling automatic operation and NSGA-Ⅱ algorithm can also be applied to other types of accident reconstruction.

Key words: powered two-wheeler, accident reconstruction, automatic simulation, multi-objective optimization, NSGA-Ⅱ

中图分类号:

TG156

刘煜, 万鑫铭, 许伟, 石亮亮, 白中浩. 基于自动化仿真与NSGA-Ⅱ算法的动力两轮车事故智能化重建方法研究[J]. 机械工程学报, 2023, 59(24): 197-208.

LIU Yu, WAN Xinming, XU Wei, SHI Liangliang, BAI Zhonghao. Research on Intelligent Reconstruction Method for Powered Two-wheeler Accident Based on Automatic Simulation and NSGA-Ⅱ Algorithm[J]. Journal of Mechanical Engineering, 2023, 59(24): 197-208.

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基于自动化仿真与NSGA-Ⅱ算法的动力两轮车事故智能化重建方法研究

Research on Intelligent Reconstruction Method for Powered Two-wheeler Accident Based on Automatic Simulation and NSGA-Ⅱ Algorithm

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