Research on virtual coupling technology based on probability distribution of communication delay
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摘要: 轨道交通车车通信作为列车虚拟编组系统中的关键环节，深刻影响着虚拟编组状态下列车间的协调运行。在分析通信时延概率分布特征的基础上，探讨了通信延误对列车虚拟编组的影响，为车车通信系统性能设计提供理论支撑。提出一种列车动力学模型，利用模型预测控制（MPC）的方法实现多列车间的虚拟编组协调运行控制。通过该模型仿真实验分析不同概率分布情况下的通信时延对虚拟编组列车控制系统的影响。实验结果表明，较大的通信时延扰动将加剧虚拟编组系统的振荡，这些问题将给列车的平稳运行与节能带来挑战。Abstract: As a key part of virtual coupling system, rail transit vehicle-to-vehicle communication has a profound impact on the coordinated operation of virtually coupled train formation. Based on the analysis of the probability distribution characteristics of communication delays, this study explores the impact of communication delays on the virtual coupling of trains, providing theoretical support for the design of vehicle-to-vehicle communication system performance. The article first proposes a train dynamics model and uses model predictive control (MPC) to achieve coordinated operation control between multiple trains in the virtual coupling. Through simulation experiments with different probability distribution scenarios of communication delays, the study analyzes the impact of communication delays on the virtual coupling control system for trains. The experimental results show that larger communication delay disturbances exacerbate oscillations in the virtual coupling system. These issues pose challenges to the smooth operation and energy efficiency of trains.
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图 6 基于随机通信延迟的列车控制系统结构图
Figure 6. Structural diagram of train control system with communication delay
图 7 无通信时延下的系统运行状态
Figure 7. The operating state of the system without communication delay
图 8 均值为50 ms时，受时变通信时延影响下的系统运行状态
Figure 8. The operating state of the system under the influence of time-varying communication delay when the mean value is 50 ms
图 9 均值为200 ms时，受时变通信时延影响下的系统运行状态
Figure 9. The operating state of the system under the influence of time-varying communication delay when the mean value is 200 ms
表 1 仿真参数
Table 1. Simulation parameters
参数 数值 列车长度/m 120 限速/（km·h–1） 160 加速度上限/（m·s–2） 0.9 加速度下限/（m·s–2） –1.25 期望车距/m 20 预测时域/s 2 控制时域/s 0.1 
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[1] 何彬,顾保南. 中国内地城市快速轨道交通线路换乘系数统计分析:基于中国城市轨道交通协会数据分析的研究报告[J]. 城市轨道交通研究,2020,23(5): 1-5. doi: 10.16037/j.1007-869x.2020.05.001 [2] BOCK U,BIKKER G. Design and development of a future freight train concept : virtually coupled train formations[J]. IFAC Proceedings Volumes,2000,33(9): 395-400. doi: 10.1016/S1474-6670(17)38176-4 [3] 李建雄. 面向动态编组和紧密追踪的虚拟编组列控方法研究 ［D］. 北京: 北京交通大学, 2022. [4] 杨中平,游婷,束天成. 列车虚拟编组技术的研究现状及发展[J]. 都市快轨交通,2023,36(1): 14-21. [5] FELEZ J,KIM Y,BORRELLI F. A model predictive control approach for virtual coupling in railways[J]. IEEE Transactions on Intelligent Transportation Systems,2019,20(7): 2728-39. doi: 10.1109/TITS.2019.2914910 [6] LUO X,TANG T,LIU H,et al. An adaptive model predictive control system for virtual coupling in metros[J]. Actuators,2021,10(8): 0178. doi: 10.3390/act10080178 [7] CHAI M, SU H, LIU H. Long short-term memory-based model predictive control for virtual coupling in railways ［J］. Wireless Communications and Mobile Computing, 2022, 1859709. [8] WANG H,ZHAO Q,LIN S,et al. A reinforcement learning empowered cooperative control approach for iiot-based virtually coupled train sets[J]. IEEE Transactions on Industrial Informatics,2021,17(7): 4935-4945. doi: 10.1109/TII.2020.3024946 [9] WU C, GAO S, ZHAO N, et al. Distributed fixed-time cooperative cruise control for train formation ［C］// Proceedings of the 2020 Chinese Automation Congress （CAC）. Shanghai: ［s. n. ］, 2020. 6350-6354. [10] SHI L,WANG J. Reliability analysis on the train control system in the CTCS-3 operating mode[J]. Smart and Resilient Transportation,2021,3(1): 25-36. doi: 10.1108/SRT-10-2020-0019 [11] 杨博,魏路平,占震滨. 基于概率分布的广域测量系统时延特性分析[J]. 电力系统自动化,2015,39(12): 38-43. doi: 10.7500/AEPS20140831006 [12] MAYNE D Q,RAWLINGS J B,RAO C V,et al. Constrained model predictive control:stability and optimality[J]. Automatica,2000,36(6): 789-814. doi: 10.1016/S0005-1098(99)00214-9 [13] 张小林,赵磊. 模型预测控制在轨道交通虚拟耦合列控系统中的应用[J]. 城市轨道交通研究,2021,24(10): 233-237. doi: 10.16037/j.1007-869x.2021.10.048 [14] 杨一鸣. 基于动态风险分析的虚拟编组场景安全研究 ［D］. 北京: 北京交通大学, 2023. [15] 刘冰. 基于列车时空轨迹预测的虚拟编组安全防护方法研究 ［D］. 北京: 北京交通大学, 2023. [16] BU B,YU F R,TANG T,et al. Performance improvements of communication-based train control (CBTC) systems with unreliable wireless networks[J]. Wireless Networks,2014,20(1): 53-71. doi: 10.1007/s11276-013-0590-0 -
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