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浙江大学学报(工学版)  2025, Vol. 59 Issue (2): 362-374    DOI: 10.3785/j.issn.1008-973X.2025.02.014
机械工程、能源工程     
不可避撞场景下的车辆碰撞损伤最小化策略
叶身村1(),周兵1,*(),柴天1,干年妃1,贺帅2
1. 湖南大学 汽车车身先进设计制造国家重点实验室,湖南 长沙 410082
2. 舍弗勒智能驾驶科技(长沙)有限公司,湖南 长沙 410036
Vehicle collision severity minimization strategy in unavoidable collision scenario
Shencun YE1(),Bing ZHOU1,*(),Tian CHAI1,Nianfei GAN1,Shuai HE2
1. State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha 410082, China
2. Schaeffler Intelligent Driving Technology (Changsha) Limited Company, Changsha 410036, China
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摘要:

针对不可避撞场景下如何有效地减小车辆碰撞损伤并保证响应的高实时性,提出采用决策层和运动控制层分层结构的碰撞损伤最小化策略. 考虑在车辆动力学约束的情况下通过求解最优控制问题生成离线轨迹库,通过四自由度碰撞模型和碰撞前的车辆状态来估计碰后自车失稳风险,通过碰撞损伤评估模型在线评估轨迹库中轨迹的碰撞时风险和碰后自车失稳风险,在决策时以极短时间从轨迹库中确定出最优轨迹. 在运动控制层,为了保持轨迹跟踪精度和车辆稳定性,基于模型预测控制建立轨迹跟踪与横摆稳定性协同控制器. 在不同场景下进行仿真,验证所提出的碰撞损伤最小化策略的有效性. 仿真结果表明,所提出的碰撞损伤最小化策略能够在保证不同工况下车辆稳定性的同时,有效地减小车辆碰撞损伤.

关键词: 不可避撞碰撞损伤四自由度碰撞模型轨迹跟踪横摆稳定性    
Abstract:

A collision severity minimization strategy based on hierarchical structure of decision layer and motion control layer was proposed aiming at how to effectively reduce vehicle collision severity and ensure high real-time response in unavoidable collision scenarios. The post-collision instability risk was estimated by using the four-degree-of-freedom collision model and the vehicle state before the collision by considering that the offline trajectory library was generated by solving the optimal control problem under the constraints of vehicle dynamics. The collision severity assessment model was used to evaluate the collision risk and post-collision instability risk of the trajectory library. The optimal trajectory was determined from the trajectory library in a very short time during decision making. A collaborative controller for trajectory tracking and yaw stability was established based on model predictive control in the motion control layer in order to maintain trajectory tracking accuracy and vehicle stability. The effectiveness of the proposed collision severity minimization strategy was verified by simulation in different scenarios. The simulation results show that the proposed collision severity minimization strategy can effectively reduce vehicle collision severity while ensuring vehicle stability under different working conditions.

Key words: unavoidable collision    collision severity    four-degree-of-freedom collision model    trajectory tracking    yaw stability
收稿日期: 2023-12-29 出版日期: 2025-02-11
CLC:  U 463  
基金资助: 福建省自然科学基金资助项目(2023J01245);湖南大学整车先进设计制造技术全国重点实验室开放基金资助项目(32065008).
通讯作者: 周兵     E-mail: ysc980608@163.com;zhou_bingo@163.com
作者简介: 叶身村(1998—),男,硕士生,从事车辆动力学与控制研究. orcid.org/0009-0005-7325-6335.E-mail:ysc980608@163.com
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引用本文:

叶身村,周兵,柴天,干年妃,贺帅. 不可避撞场景下的车辆碰撞损伤最小化策略[J]. 浙江大学学报(工学版), 2025, 59(2): 362-374.

Shencun YE,Bing ZHOU,Tian CHAI,Nianfei GAN,Shuai HE. Vehicle collision severity minimization strategy in unavoidable collision scenario. Journal of ZheJiang University (Engineering Science), 2025, 59(2): 362-374.

链接本文:

https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2025.02.014        https://www.zjujournals.com/eng/CN/Y2025/V59/I2/362

图 1  七自由度车辆动力学模型
参数数值参数数值参数数值
$ {a}_{0} $1.3$ {a}_{6} $0$ {b}_{3} $49.6
$ {a}_{1} $?22.1$ {a}_{7} $?0.354$ {b}_{4} $226
$ {a}_{2} $1011$ {a}_{8} $0.707$ {b}_{5} $0.069
$ {a}_{3} $1078$ {b}_{0} $1.65$ {b}_{6} $?0.069
$ {a}_{4} $1.82$ {b}_{1} $?21.5$ {b}_{7} $0.056
$ {a}_{5} $0.208$ {b}_{2} $1144$ {b}_{8} $0.486
表 1  魔术公式轮胎模型的参数
图 2  施加碰撞力的车辆模型示意图
图 3  车辆碰撞的平面图
参数数值
整车质量 m/kg1 230
簧上质量 mR/kg1 110
簧下质量 mNR/kg120
簧上质量惯量积 Ixz/(kg?m2)40
簧上质量绕$ {x} $轴转动惯量 Ixxs/(kg?m2)440.6
总悬架侧倾刚度 Ks/(N?m·rad?1)61 000
总悬架侧倾阻尼 Ds/(N?m?s·rad?1)4 120
表 2  车辆模型的部分参数
图 4  两车碰撞的仿真场景
图 5  碰后车辆状态的对比
图 6  碰撞损伤最小化策略的结构图
图 7  15 m/s初速度下的轨迹库
图 8  不同初速度下的轨迹库
图 9  车身划分的示意图
图 10  P2碰撞位置的示意图
碰撞位置碰撞损伤CSI(P)
5(F1)1
10(F2)2
3或7(P2)3
2或8(P1)4
4或6(B0)5
1、2或8、9(Y1)6
1或9(F0)7
3、4或6、7(Z1)8
2、3、4或6、7、8(Z0)9
1、2、3、4或6、7、8、9(D0)10
2、3或7、8(P0)11
1、2、3或7、8、9(Y0)12
表 3  与碰撞位置相关的碰撞损伤
图 11  T型路口的两车碰撞场景
图 12  两车场景下的碰撞预测结果
轨迹编号碰撞位置$ {k}_{1}{\rm{CSI}}\left(P\right) $$ {k}_{2}\Delta V $$ {k}_{3}{\rm{CSI}}\left(\omega \right) $$ {\rm{CSI}} $
56(B0)200156.6113.1469.7
447(P2)120147.293.3360.5
897、8(P0)440126.473.6640
1368(P1)160103.779.8343.5
1969(F0)28098.394.5472.8
表 4  两车场景下的碰撞损伤结果
图 13  两车场景下的仿真结果
图 14  十字交叉路口的多车碰撞场景
图 15  多车场景下的碰撞预测结果
轨迹编号碰撞位置$ {k}_{1}{\rm{CSI}}\left(P\right) $$ {k}_{2}\Delta V $$ {k}_{3}{\rm{CSI}}\left(\omega \right) $$ {\rm{CSI}} $
787(P2)12078.361.7260.0
968(P1)1608463.1307.1
1239(F0)2809173.2444.2
1876(B0)200109.568.5378.0
2307(P2)120113.258.4291.6
表 5  多车场景下的碰撞损伤结果
图 16  多车场景下的仿真结果
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