留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

前馈多源信息下异构动力学卡车队列协同控制系统

吴超仲 杨鑫炜 贺宜 LUXiao-yun

吴超仲, 杨鑫炜, 贺宜, LUXiao-yun. 前馈多源信息下异构动力学卡车队列协同控制系统[J]. 交通运输工程学报, 2023, 23(1): 256-266. doi: 10.19818/j.cnki.1671-1637.2023.01.019
引用本文: 吴超仲, 杨鑫炜, 贺宜, LUXiao-yun. 前馈多源信息下异构动力学卡车队列协同控制系统[J]. 交通运输工程学报, 2023, 23(1): 256-266. doi: 10.19818/j.cnki.1671-1637.2023.01.019
WU Chao-zhong, YANG Xin-wei, HE Yi, LU Xiao-yun. Cooperative control system of truck platoon with heterogeneous dynamics under feedforward multi-source information[J]. Journal of Traffic and Transportation Engineering, 2023, 23(1): 256-266. doi: 10.19818/j.cnki.1671-1637.2023.01.019
Citation: WU Chao-zhong, YANG Xin-wei, HE Yi, LU Xiao-yun. Cooperative control system of truck platoon with heterogeneous dynamics under feedforward multi-source information[J]. Journal of Traffic and Transportation Engineering, 2023, 23(1): 256-266. doi: 10.19818/j.cnki.1671-1637.2023.01.019

前馈多源信息下异构动力学卡车队列协同控制系统

doi: 10.19818/j.cnki.1671-1637.2023.01.019
基金项目: 

国家自然科学基金项目 52072292

详细信息
    作者简介:

    吴超仲(1972-),男,湖北天门人,武汉理工大学教授,工学博士,从事交通安全、智能交通、车路协同与智能网联汽车研究

    通讯作者:

    贺宜(1986-),男,江西萍乡人,武汉理工大学副研究员,工学博士

  • 中图分类号: U461

Cooperative control system of truck platoon with heterogeneous dynamics under feedforward multi-source information

Funds: 

National Natural Science Foundation of China 52072292

More Information
  • 摘要: 针对目前卡车队列动力学异构性所导致的系统弦稳定性、内部稳定性以及队列耦合性降低的问题,提出了一种异构协同自适应巡航系统控制器设计方法,建立了基于前馈多源信息的异构动力学卡车队列闭环耦合系统;考虑由异构车型所构成的卡车队列存在发动机执行器的饱和态异构问题,建立了发动机饱和性和状态约束条件;在上层协同控制器的基础上,建立了一种非线性下层异构发动机扭矩输出控制模型,用于控制车辆动力学仿真软件TruckSim中的真实车辆模型;建立了基于三维燃油特性图的车辆能耗模型,用于计算实时车辆油耗和节能性分析;通过频域分析法,结合已知异构动力学参数量化标定了协同自适应巡航系统控制器的增益,确保系统满足弦稳定条件。分析结果表明:相比同构动力学控制器,异构协同自适应巡航系统控制器可以确保距离误差在-0.01~0.15 m内,优于同构控制器作用下的-0.3~0.5 m,且当领航车进入匀速行驶状态时,跟随车辆能立刻收敛至相同的行驶状态,收敛性能优于同构协同自适应巡航控制系统;卡车队列节油率最大可达8.15%,随着车头时距减小至0.5 s,平均节油率最大可达8.10%。由此可见,多源前馈信息异构控制系统能有效降低车辆的状态误差传递,设计的前馈多源信息下异构动力学卡车队列协同控制系统能提升队列的弦稳定性,也能保证系统的燃油经济性。

     

  • 图  1  基于PLF通信拓扑的卡车队列

    Figure  1.  Truck platoon based on PLF communication topology

    图  2  CACC系统架构

    Figure  2.  CACC system architecture

    图  3  发动机燃油特性

    Figure  3.  Engine fuel characteristics

    图  4  货车模型

    Figure  4.  Truck model

    图  5  CACC系统参考输入

    Figure  5.  Referenced input of CACC system

    图  6  同构动力学控制器和异构动力学控制器所得车辆距离误差

    Figure  6.  Distance errors of vehicles obtained by homogeneous dynamics controller and heterogeneous dynamics controller

    图  7  同构动力学控制器和异构动力学控制器所得车辆加速度

    Figure  7.  Accelerations of vehicles obtained by homogeneous dynamics controller and heterogeneous dynamics controller

    图  8  同构动力学控制器和异构动力学控制器所得车速

    Figure  8.  Velocities of vehicles obtained by homogeneous dynamics controller and heterogeneous dynamics controller

    图  9  同构动力学控制器和异构动力学控制器所得车辆发动机扭矩

    Figure  9.  Engine torques of vehicles obtained by homogeneous dynamics controller and heterogeneous dynamics controller

    图  10  领航车车速

    Figure  10.  Velocity of leading vehicle

    图  11  不同车辆数量下卡车队列油耗

    Figure  11.  Fuel consumptions of truck platoon under different vehicles numbers

    图  12  节油率与车头时距间的关系

    Figure  12.  Relationship between fuel-saving rate and headway

    表  1  仿真参数设定

    Table  1.   Simulation parameters setting

    车辆编号 车身长度/m 质量/kg 空气动力学系数 发动机时滞/s 发动机传动效能 比例增益 微分增益
    0 5.0 6 600 0.4 0.1 1.00 1.5 1.0
    1 4.5 7 740 0.3 0.1 1.00 1.5 1.5
    2 4.5 7 000 0.3 0.3 0.90 2.0 0.5
    3 5.0 6 900 0.6 0.4 0.88 5.0 6.0
    4 5.0 6 800 0.4 0.5 0.85 4.0 5.0
    下载: 导出CSV

    表  2  节油率

    Table  2.   Fuel-saving rates

    油耗指标 2车队列 3车队列 4车队列 5车队列 6车队列
    总油耗/kg 0.256 0.379 0.498 0.620 0.742
    无风阻效应油耗/kg 0.270 0.405 0.540 0.675 0.810
    节油率/% 5.19 6.42 7.78 8.15 8.40
    下载: 导出CSV
  • [1] DEY K C, YAN Li, WANG Xu-jie, et al. A review of communication, driver characteristics, and controls aspects of cooperative adaptive cruise control (CACC)[J]. IEEE Transactions on Intelligent Transportation Systems, 2015, 17: 491-509.
    [2] 秦严严, 王昊, 王炜, 等. 自适应巡航控制车辆跟驰模型综述[J]. 交通运输工程学报, 2017, 17(3): 121-130. doi: 10.3969/j.issn.1671-1637.2017.03.013

    QIN Yan-yan, WANG Hao, WANG Wei, et al. Review of car-following models of adaptive cruise control[J]. Journal of Traffic and Transportation Engineering, 2017, 17(3): 121-130. (in Chinese) doi: 10.3969/j.issn.1671-1637.2017.03.013
    [3] MILANÉS V, SHLADOVER S E. Modeling cooperative and autonomous adaptive cruise control dynamic responses using experimental data[J]. Transportation Research Part C: Emerging Technologies, 2014, 48: 285-300. doi: 10.1016/j.trc.2014.09.001
    [4] WANG, Zi-ran, BIAN You-gang, SHLADOVER S E, et al. A survey on cooperative longitudinal motion control of multiple connected and automated vehicles[J]. IEEE Intelligent Transportation Systems Magazine, 2020, 12(1): 4-24. doi: 10.1109/MITS.2019.2953562
    [5] LU X Y, SHLADOVER S, HEDRICK J K. Heavy-duty truck control: short inter-vehicle distance following[C]//IEEE. Proceedings of the 2004 American Control Conference. New York: IEEE, 2004: 4722-4727.
    [6] MILANÉS V, SHLADOVER S E, SPRING J, et al. Cooperative adaptive cruise control in real traffic situations[J]. IEEE Transactions on Intelligent Transportation Systems, 2013, 15(1): 296-305.
    [7] LU Xiao-yun, SHLADOVER S. Integrated ACC and CACC development for heavy-duty truck partial automation[C]//IEEE. 2017 American Control Conference (ACC). New York: IEEE, 2017: 4938-4945.
    [8] TSUGAWA S, JESCHKE S, SHLADOVER S E. A review of truck platooning projects for energy savings[J]. IEEE Transactions on Intelligent Vehicles, 2016, 1(1): 68-77. doi: 10.1109/TIV.2016.2577499
    [9] BHOOPALAM A K, NIELS AGATZ N, ZUIDWIJK R. Planning of truck platoons: a literature review and directions for future research[J]. Transportation Research Part B: Methodological, 2018, 107: 212-228. doi: 10.1016/j.trb.2017.10.016
    [10] LU X Y, SHLADOVER S, BERGQUIST S. Truck CACC implementation and test to verify control performance[J]. Transportation Research Record, 2019, 2673(8): 353-364. doi: 10.1177/0361198119842122
    [11] LI S E, GAO Feng, LI Ke-qiang, et al. Robust longitudinal control of multi-vehicle systems—a distributed H-infinity method[J]. IEEE Transactions on Intelligent Transportation Systems, 2017, 19(9): 2779-2788.
    [12] PLOEG J, SHUKLA D P, VAN DE WOUW N, et al. Controller synthesis for string stability of vehicle platoons[J]. IEEE Transactions on Intelligent Transportation Systems, 2014, 15(2): 854-865. doi: 10.1109/TITS.2013.2291493
    [13] PLOEG J, VAN DE WOUW N, NIJMEIJER H. Lp string stability of cascaded systems: application to vehicle platooning[J]. IEEE Transactions on Control Systems Technology, 2013, 22(2): 786-793.
    [14] NAUS G J L, VUGTS R P A, PLOEG J, et al. String-stable CACC design and experimental validation: a frequency-domain approach[J]. IEEE Transactions on Vehicular Technology, 2010, 59(9): 4268-4279. doi: 10.1109/TVT.2010.2076320
    [15] 邹存名, 单慧, 李洪兴. 基于模型预测的车辆协同编队控制[J]. 控制工程, 2022, 29(7): 1295-1301. doi: 10.14107/j.cnki.kzgc.20200251

    ZOU Cun-ming, SHAN Hui, LI Hong-xing. Vehicle cooperative formation control based on model prediction[J]. Control Engineering of China, 2022, 29(7): 1295-1301. (in Chinese) doi: 10.14107/j.cnki.kzgc.20200251
    [16] 马芳武, 王佳伟, 杨昱, 等. 网联车辆协同编队控制系统研究[J]. 汽车工程, 2020, 42(7): 860-866, 873. doi: 10.19562/j.chinasae.qcgc.2020.07.003

    MA Fang-wu, WANG Jia-wei, YANG Yu, et al. Research on networked-vehicle cooperative platoon control system[J]. Automotive Engineering, 2020, 42(7): 860-866, 873. (in Chinese) doi: 10.19562/j.chinasae.qcgc.2020.07.003
    [17] SAKHDARI B, AZAD N L. A distributed reference governor approach to ecological cooperative adaptive cruise control[J]. IEEE Transactions on Intelligent Transportation Systems, 2018, 19(5): 1496-1507. doi: 10.1109/TITS.2017.2735380
    [18] 秦晓辉, 王建强, 谢伯元, 等. 非匀质车辆队列的分布式控制[J]. 汽车工程, 2017, 39(1): 73-78, 106. https://www.cnki.com.cn/Article/CJFDTOTAL-QCGC201701012.htm

    QIN Xiao-hui, WANG Jian-qiang, XIE Bo-yuan, et al. Distributed control of heterogeneous vehicular platoons[J]. Automotive Engineering, 2017, 39(1): 73-78, 106. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-QCGC201701012.htm
    [19] GAO Feng, HU Xiao-song, LI S E, et al. Distributed adaptive sliding mode control of vehicular platoon with uncertain interaction topology[J]. IEEE Transactions on Industrial Electronics, 2018, 65(8): 6352-6361. doi: 10.1109/TIE.2017.2787574
    [20] KWON J W, CHWA D. Adaptive bidirectional platoon control using a coupled sliding mode control method[J]. IEEE Transactions on Intelligent Transportation Systems, 2014, 15(5): 2040-2048. doi: 10.1109/TITS.2014.2308535
    [21] BALDI S, LIU Di, JAIN V, et al. Establishing platoons of bidirectional cooperative vehicles with engine limits and uncertain dynamics[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 22(5): 2679-2691.
    [22] ABOU H Y, YUAN Shuai, BALDI S. An adaptive switched control approach to heterogeneous platooning with intervehicle communication losses[J]. IEEE Transactions on Control of Network Systems, 2017, 5(3): 1434-1444.
    [23] ZHU Yang, WU Jun, SU Hong-ye. V2V-based cooperative control of uncertain, disturbed and constrained nonlinear CAVs platoon[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(3): 1796-1806. doi: 10.1109/TITS.2020.3026877
    [24] 于晓海, 郭戈. 车队控制中的一种通用可变时距策略[J]. 自动化学报, 2019, 45(7): 1335-1343. https://www.cnki.com.cn/Article/CJFDTOTAL-MOTO201907010.htm

    YU Xiao-hai, GUO Ge. A general variable time headway policy in platoon control[J]. Acta Automatica Sinica, 2019, 45(7): 1335-1343. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-MOTO201907010.htm
    [25] 郭景华, 王班, 王靖瑶, 等. 智能网联混合动力汽车队列模型预测分层控制[J]. 汽车工程, 2020, 42(10): 1293-1301, 1334. https://www.cnki.com.cn/Article/CJFDTOTAL-QCGC202010001.htm

    GUO Jing-hua, WANG Ban, WANG Jing-yao, et al. Hierarchical model predictive control of intelligent and connected hybrid electric vehicles platooning[J]. Automotive Engineering, 2020, 42(10): 1293-1301, 1334. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-QCGC202010001.htm
    [26] 唐小林, 李珊珊, 王红, 等. 网联环境下基于分层式模型预测控制的车队能量控制策略研究[J]. 机械工程学报, 2020, 56(14): 119-128. https://www.cnki.com.cn/Article/CJFDTOTAL-JXXB202014011.htm

    TANG Xiao-lin, LI Shan-shan, WANG Hong, et al. Research on energy control strategy based on hierarchical model predictive control in connected environment[J]. Journal of Mechanical Engineering, 2020, 56(14): 119-128. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JXXB202014011.htm
    [27] DARBHA S, KONDURI S, PAGILLA P R. Vehicle platooning with constant spacing strategies and multiple vehicle look ahead information[J]. IET Intelligent Transport Systems, 2020, 14(6): 589-600.
    [28] COOK P A. Conditions for string stability[J]. Systems and Control Letters, 2005, 54(10): 991-998.
    [29] SHLADOVER S E, NOWAKOWSKI C, LU Xiao-yun, et al. Cooperative adaptive cruise control: definitions and operating concepts[J]. Transportation Research Record, 2015(2489): 145-152.
    [30] PLOEG J, SCHEPERS B T M, VAN NUNEN E, et al. Design and experimental evaluation of cooperative adaptive cruise control[C]//IEEE. 14th International IEEE Conference on Intelligent Transportation Systems (ITSC). New York: IEEE, 2011: 260-265.
  • 加载中
图(12) / 表(2)
计量
  • 文章访问数:  379
  • HTML全文浏览量:  85
  • PDF下载量:  86
  • 被引次数: 0
出版历程
  • 收稿日期:  2022-08-03
  • 网络出版日期:  2023-03-08
  • 刊出日期:  2023-02-25

目录

    /

    返回文章
    返回