常导高速磁浮列车节能速度曲线鲁棒优化研究

楚彭子; 袁建军; 陈义军

doi:10.19713/j.cnki.43-1423/u.T20222367

您当前的位置：

首页 >

文章列表页 >

常导高速磁浮列车节能速度曲线鲁棒优化研究

高速铁路技术 | 更新时间：2023-12-05

- 常导高速磁浮列车节能速度曲线鲁棒优化研究
- Robust optimization of energy-efficient speed profile for normal high-speed maglev
- 铁道科学与工程学报 2023年20卷第11期页码：4062-4073
- 作者机构：
  
  1.同济大学磁浮交通工程技术研究中心，上海 201804
  2.上海申通地铁集团有限公司技术中心，上海 201620
- 作者简介：
  
  袁建军(1974—)，男，湖南汉寿人，高级工程师，从事高速磁浮运行控制研究；E-mail：yuanjianjun@tongji.edu.cn
- 基金信息：
  
  国家重点研发计划项目(2016YFB1200602-02);上海市多网多模式轨道交通协同创新中心资助项目
- DOI：10.19713/j.cnki.43-1423/u.T20222367
  中图分类号：
扫描看全文
楚彭子,袁建军,陈义军.常导高速磁浮列车节能速度曲线鲁棒优化研究[J].铁道科学与工程学报,2023,20(11):4062-4073.

CHU Pengzi,YUAN Jianjun,CHEN Yijun.Robust optimization of energy-efficient speed profile for normal high-speed maglev[J].Journal of Railway Science and Engineering,2023,20(11):4062-4073.
楚彭子,袁建军,陈义军.常导高速磁浮列车节能速度曲线鲁棒优化研究[J].铁道科学与工程学报,2023,20(11):4062-4073. DOI： 10.19713/j.cnki.43-1423/u.T20222367.

CHU Pengzi,YUAN Jianjun,CHEN Yijun.Robust optimization of energy-efficient speed profile for normal high-speed maglev[J].Journal of Railway Science and Engineering,2023,20(11):4062-4073. DOI： 10.19713/j.cnki.43-1423/u.T20222367.

摘要

列车速度曲线的优化是轨道交通节省运营成本的重要途径之一，鲁棒优化方法有助于克服速度曲线节能优化中的不确定因素。针对常导高速磁浮列车节能速度曲线优化，首先将区间划分为若干区段，进而将列车运行控制的停车点步进机制、列车悬浮运行的阻力特性、区间限速、运行时分与乘坐舒适性要求以及列车总重的不确定性纳入鲁棒优化模型，并结合三项引理将其重构为带二次项和区间数的混合整数规划(MIP)问题。联合Gurobi求解器以及基于可接受目标函数值波动范围的鲁棒优化方法讨论求解算法。借助仿真算例检验模型与算法的有效性，分析列车总重、运行时分以及区段划分对运行能耗的影响。研究结果显示：列车总重取最大值时所得悲观速度曲线与列车总重取最小时所得乐观速度曲线存在差异，优化速度曲线时有必要考虑列车总重的不确定性；列车总重取最小与最大时，鲁棒速度曲线分别较悲观速度曲线和乐观速度曲线节能2.222%和7.087%；在大多数情况下，鲁棒速度曲线能够克服悲观速度曲线的保守特性；放松对运行时分的要求有助于降低列车运行能耗；选择合适的区段划分间隔有助于获取更优的节能速度曲线。所提出方法可为常导高速磁浮列车节能速度曲线的获取提供有效手段，对其他制式轨道交通列车速度曲线的优化也有参考价值。

Abstract

The optimization of train speed profiles is one of the important ways to save operating costs for rail transit. The robust optimization method is helpful to overcome the uncertainties in the process of energy-efficient speed profile acquisition. Aiming at the optimization of the energy-efficient speed profile for normal high-speed maglev trains, firstly, the section was divided into several segments. Then the stopping point stepping mechanism of train operation control, the resistance characteristics of train running process, maximum speed limit, requirements of ride comfort and running time at an interval. The uncertainty of train weight was included into the robust optimization model. The combining with three lemmas, the model was reconstructed as a mixed integer programming (MIP) problem with quadratic terms and an interval number. An algorithm was designed by combining the Gurobi solver and the robust optimization method based on the acceptable objective variation range. The effectiveness of the model and the algorithm was verified by a simulation study, and the influence of the train weight, running time and segment division on the energy consumption was analyzed. The results suggest that there is a difference between the pessimistic speed profile with the maximum train weight and the optimistic speed profile with the minimum train weight. It is necessary to consider the uncertainty of the train weight when optimizing train speed profiles. When the train weight is minimum and maximum, the energy consumption of the robust speed profile is 2.222% and 7.087% less than that of the pessimistic and optimistic speed profile, respectively. In most cases, the robust speed profile can overcome the conservative characteristics of pessimistic speed profile. Relaxing the requirement on running time will reduce the energy consumption. The proposed method can provide an effective way to obtain the energy-efficient speed profile for normal high-speed maglev, and also has a useful guideline to the optimization of train speed profile for rail transit systems with other types.

关键词

轨道交通高速磁浮节能速度曲线鲁棒优化混合整数规划

Keywords

rail transithigh-speed maglevenergy-efficient speed profilerobust optimizationmixed integer programming

references

李蔚, 刘高峰, 赵思哲, 等. 基于不同速度控制模式的列车驾驶策略优化研究[J]. 铁道科学与工程学报, 2022, 19(8): 2169-2181.

LI Wei, LIU Gaofeng, ZHAO Sizhe, et al. Research on the optimization of train driving strategy based on different speed control modes[J]. Journal of Railway Science and Engineering, 2022, 19(8): 2169-2181.

麻存瑞, 毛保华, 柏赟, 等. 高速列车多区间节能操纵优化研究[J]. 交通运输系统工程与信息, 2018, 18(5): 178-183.

MA Cunrui, MAO Baohua, BAI Yun, et al. Energy-saving operation optimization for high-speed train in multi-interstation[J]. Journal of Transportation Systems Engineering and Information Technology, 2018, 18(5): 178-183.

WEI Guodong, ZHU Songwei, WANG Yihui, et al. Energy-efficient automatic train operation for high-speed railways: Considering discrete notches and neutral sections[J]. Transportation Research Part C: Emerging Technologies, 2022, 145: 103884.

杨彦强, 刘海东, 麻存瑞, 等. 列车节能运行目标速度控制优化研究[J]. 交通运输系统工程与信息, 2019, 19(1): 138-144.

YANG Yanqiang, LIU Haidong, MA Cunrui, et al. Target speed control optimization of train movement for saving energy[J]. Journal of Transportation Systems Engineering and Information Technology, 2019, 19(1): 138-144.

唐涛, 荀径, 曹芳, 等. 北京地铁亦庄线列车节能驾驶研究[J]. 北京交通大学学报, 2016, 40(4): 19-24.

TANG Tao, XUN Jing, CAO Fang, et al. Research on energy-efficient driving strategy in Beijing Yizhuang line[J]. Journal of Beijing Jiaotong University, 2016, 40(4): 19-24.

徐凯, 杨飞凤, 涂永超, 等. 基于多粒子群协同的城轨列车速度曲线多目标优化[J]. 铁道学报, 2021, 43(2): 95-102.

XU Kai, YANG Feifeng, TU Yongchao, et al. Multi-objective optimization of speed profile of urban rail train based on multiple particle swarms Co-evolutionary[J]. Journal of the China Railway Society, 2021, 43(2): 95-102.

WANG Li, YANG Lixing, GAO Ziyou, et al. Robust train speed trajectory optimization: A stochastic constrained shortest path approach[J]. Frontiers of Engineering Management, 2017, 4(4): 408.

YANG Xin, CHEN A, NING Bin, et al. A stochastic model for the integrated optimization on metro timetable and speed profile with uncertain train mass[J]. Transportation Research Part B: Methodological, 2016, 91: 424-445.

FERNANDEZ-RODRIGUEZ A, FERNANDEZ-CARDADOR A, CUCALA A P, et al. Design of robust and energy-efficient ATO speed profiles of metropolitan lines considering train load variations and delays[J]. IEEE Transactions on Intelligent Transportation Systems, 2015, 16(4): 2061-2071.

CHENG Yu, YIN Jiateng, YANG Lixing. Robust energy-efficient train speed profile optimization in a scenario-based position—time—speed network[J]. Frontiers of Engineering Management, 2021, 8(4): 595-614.

ZHANG Chunyang, CHEN Dewang, YIN Jiateng, et al. A flexible and robust train operation model based on expert knowledge and online adjustment[J]. International Journal of Wavelets, Multiresolution and Information Processing, 2017, 15(3): 1750023.

杨光. 高速磁浮列车最优速度曲线及其跟踪控制研究[D]. 北京: 北京交通大学, 2007.

YANG Guang. Research on optimal speed curve and tracking control of high-speed maglev train[D]. Beijing: Beijing Jiaotong University, 2007.

柴晓凤, 刘军, 赖晴鹰, 等. 考虑辅助停车区约束的中速磁浮列车速度曲线节能优化方法[J]. 中南大学学报(自然科学版), 2019, 50(6): 1499-1506.

CHAI Xiaofeng, LIU Jun, LAI Qingying, et al. Optimal energy-efficient trajectory planning for middle-speed maglev considering constraint of auxiliary stopping area[J]. Journal of Central South University (Science and Technology), 2019, 50(6): 1499-1506.

赖晴鹰, 刘军, 赵若愚, 等. 基于变间距动态规划的中高速磁悬浮列车速度曲线优化[J]. 吉林大学学报(工学版), 2019, 49(3): 749-756.

LAI Qingying, LIU Jun, ZHAO Ruoyu, et al. Optimal trajectory planning for middle-to-high speed maglev based on dynamic programming with mutative spacing[J]. Journal of Jilin University (Engineering and Technology Edition), 2019, 49(3): 749-756.

LAI Qingying, LIU Jun, HAGHANI A, et al. Energy-efficient speed profile optimization for medium-speed maglev trains[J]. Transportation Research Part E: Logistics and Transportation Review, 2020, 141: 102007.

王盼盼, 杨杰, 邹吉强, 等. 基于改进自抗扰控制器的磁浮列车速度跟踪控制研究[J]. 铁道科学与工程学报, 2023, 20(1): 310-320.

WANG Panpan, YANG Jie, ZOU Jiqiang, et al. Design maglev train speed tracking system based on improved active disturbance rejection controller[J]. Journal of Railway Science and Engineering, 2023, 20(1): 310-320.

SCHACH R, JEHLE P, NAUMANN R. Transrapid und Rad-Schiene-Hochgeschwindigkeitsbahn:Eingesamth-eitlicher Systemvergleich[M]. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006.

卞建光. 磁浮列车运行控制系统相关性质及辅助停车区特性研究[D]. 杭州: 浙江大学, 2006.

BIAN Jianguang. Study on the related properties of maglev train operation control system and the characteristics of auxiliary parking area[D]. Hangzhou: Zhejiang University, 2006.

虞翊, 姜西, 林辉, 等. 基于防护速度的高速磁浮辅助停车区设置[J]. 同济大学学报(自然科学版), 2019, 47(9): 1310-1316.

YU Yi, JIANG Xi, LIN Hui, et al. Setting method of auxiliary stopping area for high-speed maglev based on protection speed[J]. Journal of Tongji University (Natural Science), 2019, 47(9): 1310-1316.

YU Yi, CHU Pengzi, DONG Danyang, et al. Auxiliary stopping area layout method for high-speed maglev operated bidirectionally on single track[J]. Journal of Advanced Transportation, 2021, 2021: 1-15.

CHINNECK J W, RAMADAN K. Linear programming with interval coefficients[J]. The Journal of the Operational Research Society, 2000, 51(2): 209-220.

LI Mian, GABRIEL S A, SHIM Y, et al. Interval uncertainty-based robust optimization for convex and non-convex quadratic programs with applications in network infrastructure planning[J]. Networks and Spatial Economics, 2011, 11(1): 159-191.

楚彭子, 虞翊, 董丹阳, 等. 基于场景划分的常导高速磁浮辅助停车区布置优化[J]. 吉林大学学报(工学版), 2022, 52(12): 2864-2873.

CHU Pengzi, YU Yi, DONG Danyang, et al. Layout optimization of auxiliary stopping areas for normal high-speed maglev based on scenario division[J]. Journal of Jilin University (Engineering and Technology Edition), 2022, 52(12): 2864-2873.

姜西, 虞翊, 邓志翔, 等. 考虑追踪运行的高速磁浮辅助停车区设置优化[J]. 铁道科学与工程学报, 2021, 18(2): 325-333.

JIANG Xi, YU Yi, DENG Zhixiang, et al. Setting optimization of auxiliary stopping area for high-speed maglev considering train tracking operation[J]. Journal of Railway Science and Engineering, 2021, 18(2): 325-333.

国家铁路局. 磁浮铁路技术标准(试行): TB 10630―2019[S]. 北京: 中国铁道出版社, 2019.

National Railway Administration of the People’s Republic of China. Standard for technology of maglev railway (trial): TB 10630―2019[S]. Beijing: China Railway Press, 2019.

中华人民共和国住房和城乡建设部. 高速磁浮交通车辆通用技术条件: CJ/T 367—2011[S]. 北京: 中国标准出版社, 2011.

Ministry of Housing and Urban-Rural Development of the People’s Republic of China. General techinical specification for high speed maglev vehicles: CJ/T 367—2011[S]. Beijing: Standards Press of China, 2011.

中华人民共和国住房和城乡建设部, 国家质量监督检验检疫总局. 高速磁浮交通建设标准: 建标 161—2012[S]. 北京: 中国计划出版社, 2012.

Ministry of Housing and Urban-Rural Development of the People’s Republic of China, General Administration of Quality Supervision, Inspection and Quarantine of the People’s Republic of China. Standard for high-speed maglev traffic construction: Construction standard 161—2012[S]. Beijing: China Planning Press, 2012.

吴祥明. 磁浮列车[M]. 上海: 上海科学技术出版社, 2003.

WU Xiangming. Maglev train[M]. Shanghai: Shanghai Scientific & Technical Press, 2003.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

考虑行程时间波动的干线信号协调控制鲁棒优化模型

轨道交通复杂网络演化对城市社区划分的影响研究

基于性能的巴基斯坦橙线地铁桥梁安全运维体系研究

基于多日需求情景的高铁列车开行方案鲁棒优化

枢纽拥堵状况下绿色多式联运路径选择不确定性研究