基于时间逼近搜索算法的城轨列车运行节能优化研究

刘炜; 王栋; 李群湛; 崔梦雨

doi:10.3969/j.issn.0258-2724.2016.05.014

基于时间逼近搜索算法的城轨列车运行节能优化研究

doi: 10.3969/j.issn.0258-2724.2016.05.014

基金项目:

国家自然科学基金资助项目（51607148）

中国铁路总公司科技研究开发计划资助项目（2014J009-B）

详细信息

作者简介:
刘炜(1982-),男,副教授,博士,研究方向为列车运行优化、牵引供电系统仿真,E-mail:liuwei_8208@swjtu.cn

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- 文章访问数: 588
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出版历程
- 收稿日期: 2015-06-24
- 刊出日期: 2016-10-25

A Novel Time-Approaching Search Algorithm for Energy-Saving Optimization of Urban Rail Train

摘要

摘要: 针对地铁列车准点节能运行，提出了基于时间逼近搜索的列车节能优化算法。首先建立城市轨道列车在满足定时运行条件下的节能控制模型，通过庞特利亚金最大值原理得到了列车节能最优控制工况集；其次，推导了列车在不同节能运行模式下的能耗差异；在此基础上，提出了一种将列车运行区间进行分段优化的方法，采用时间逼近搜索求解列车工况转换点的位置，最终达到定时节能运行的目的。以上海地铁3号线铁力路至友谊路线路为算例，与实测负荷过程对比，列车采用本文算法优化后可节能12.5%。
- 城市轨道 /
- 节能控制 /
- 时间逼近 /
- 优化
Abstract: To ensure energy-saving and punctual operation of urban railway, a time-approaching search method was proposed. The energy-saving control model of urban railway that satisfies timing running was established . A set of optimal conditions for energy-saving control was derived according to the Pontryagin maximum principle. The energy consumption of a train under different energy-saving operations was calculated . On this basis, we presented an optimization method of dividing the train operation period into sections. The change point of train operation is determined using time-approaching search method to meet the requirements of energy-saving and timing. A section from Tieli Road to Youyi Road of Shanghai Metro Line 3 is taken as an example. Compared with measurement results in the practical loading process, the energy comsuption is reduced by 12.5% using time-approaching search algorithm.
- Urban rail transit /
- energy saving control /
- time-approach /
- optimization

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参考文献(16)

唐海川,王青元,冯晓云. 地铁列车追踪运行的节能控制与分析[J]. 铁道学报,2015,37(1): 37-43. TANG Haichuan, WANG Qingyuan, FENG Xiaoyun. Energy saving control of metro train tracing operation[J]. Journal of the China Railway Society, 2015, 37(1): 37-43.

LIU R R, GOLOVITCHER I M. Energy-efficient operation of rail vehicles[J]. Transportation Research Part A: Policy and Practice, 2003, 37(10): 917-932.

LU S, HILLMANSEN S, HO T K, et al. Single-train trajectory optimization[J]. Intelligent Transportation Systems, IEEE Transactions on, 2013, 14(2): 743-750.

KO H, KOSEKI T, MIYATAKE M. Application of dynamic programming to optimization of running profile of a train[J]. Computers in Railways IX, 2004(15): 103-112.

BOCHARNIKOV Y V, TOBIAS A M, ROBERTS C, et al. Optimal driving strategy for traction energy saving on DC suburban railways[J]. Electric Power Applications, IETE, 2007, 1(5): 675-682.

CHUANG H J, CHEN C S, LIN C H, et al. Design of optimal coasting speed for saving social cost in mass rapid transit systems[C]//Proceedings of the Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Piscataway: IEEE Press, 2008: 2833-2839.

ACIKBAS S, SYLEMEZ M T. Coasting point optimization for mass rail transit lines using artificial neural networks and genetic algorithms[J]. Electric Power Applications, IET, 2008, 2(3): 172-182.

CHEVRIER R, MARLIEERE G, VULTURESCU B, et al. Multi-objective evolutionary algorithm for speed tuning optimization with energy saving in railway: application and case study.(2011-01-01)[2015-05-22]. https://www.researchgate.net/publication/50365605.

杨利军,胡用生,孙丽霞. 城市轨道交通节能线路仿真算法[J]. 同济大学学报:自然科学版,2012,40(2): 235-240. YANG Lijun, HU Yongsheng, SUN Lixia. Energy-saving track profile of urban mass transit[J]. Journal of Tongji University: Natural Science, 2012, 40(2): 235-240.

WANG Penling, LIN Xuan, LI Yuezong. Optimization analysis on the energy saving control for trains with adaptive genetic algorithm[C]//Systems and Informatics (ICSAI), 2012 International Conference on. Yantai: IEEE, 2012: 439-443.

王鹏玲,林轩,李跃宗,等. 自适应遗传算法在列车节能优化中的应用[J]. 计算机仿真,2012,29(11): 350-354. WANG Pengling, LIN Xuan, LI Yuezong, et al. Energy saving train operation optimization with adaptive genetic algorithm[J]. Computer Simulation, 2012, 29(11): 350-354.

刘炜,李群湛,郭蕾,等. 基于多种群遗传算法的城轨列车节能运行优化研究[J]. 系统仿真学报,2010,22(4): 921-925. LIU Wei, LI Qunzhan, GUO Lei, et al. Study of urban railway energy saving train control optimization based on multi-population genetic algorithm[J]. Journal of System Simulation, 2010, 22(4): 921-925.

饶忠. 列车牵引计算[M]. 北京:中国铁道出版社,2006: 48-53.

GU Qing, TANG Tao, GAO Fang, et al. Energy-efficient train operation in urban rail transit using real-time traffic information[J]. Intelligent Transportation Systems, IEEE Transactions on, 2014, 15(3): 1216-1233.

王青元,冯晓云. 考虑再生制动能量利用的高速列车节能最优控制仿真研究[J]. 中国铁道科学,2015,36(1): 96-103. WANG Qingyuan, FENG Xiaoyun. Simulation study on optimal energy-efficient control of high speed train considering regenerative brake energy[J]. China Railway Science, 2015, 36(1): 96-103.

韩蕙心,吴鹏,吴杰,等. 基于多目标差分进化算法的列车惰行控制[J]. 计算机应用,2013,33(增刊2): 286-289. HAN Huixin, WU Peng, WU Jie, et al. Coast control of urban train based on multi-objective differential evolution algorithm[J]. Journal of Computer Applications, 2013, 33(Sup.2): 286-289.

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文章访问数: 588
HTML全文浏览量: 86
PDF下载量: 259
被引次数: 0

基于时间逼近搜索算法的城轨列车运行节能优化研究

doi: 10.3969/j.issn.0258-2724.2016.05.014

作者简介: 刘炜(1982-),男,副教授,博士,研究方向为列车运行优化、牵引供电系统仿真,E-mail:liuwei_8208@swjtu.cn

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出版历程

A Novel Time-Approaching Search Algorithm for Energy-Saving Optimization of Urban Rail Train

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出版历程

目录

作者简介:
刘炜(1982-),男,副教授,博士,研究方向为列车运行优化、牵引供电系统仿真,E-mail:liuwei_8208@swjtu.cn