被动信号优先策略下现代有轨电车站间协调能耗优化*
欧冬秀1,3闫黄2阳扬4
Optimization of Inter-station Coordinated Energy Consumption under Tram Passive Priority Strategy
OU DongxiuYAN HuangYANG Yang
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作者信息:1.同济大学道路与交通工程教育部重点实验室，201804，上海；
2.同济大学经济与管理学院，200092，上海；
3.上海市轨道交通结构耐久与系统安全重点实验室，201804，上海；
4.卡斯柯信号有限公司，200071，上海
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Affiliation:Key Laboratory of Road and Traffic Engineering of the Ministry of Education，Tongji University，201804，Shanghai，China
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关键词:
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Key words:
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DOI:10.16037/j.1007-869x.2019.06.006
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中图分类号/CLCN:U482.1
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栏目/Col:研究报告
摘要:
为了降低半独立路权现代有轨电车线路运行的能 耗，基于现代有轨电车系统的运行特性和线路特征，提出了半独立路权现代有轨电车线路的区段划分方法；并结合现代有轨电车列车运行模式，推算出了单区段现代有轨电车能耗优化速度曲线。 在沿线交叉口已经考虑被动信号优先配时策略的基础上，以区段运行时间、距离、限速及交叉口信号状态等为约束条件，建立了基于站间协调控制的现代有轨电车全线能耗优化模型。 选取国内某城市实际现代有轨电车线路为 例，对比分析仿真速度曲线与模型求解速度曲线,结果显示该能耗优化速度曲线能有效降低现代有轨电车运行能耗。
Abstracts:
To reduce the operation energy consumption of modern tram with semi-closed road right，a section division method of tram system with semi-closed road right is provided based on the operating and rail line characteristics. Then，combined with tram operation mode，the speed curve of energy consumption optimization in single tram section is calculated. In the condition of signal priority configuration policy adopted at intersections，a whole line optimization model of tram energy consumption based on inter-station cooperating control is established with constraints like running time，distance，speed limitation and crossing signal status. Taking the tram line in a Chinese city as example，the simulation velocity curve and model solution velocity curve are comparatively analyzed. The result shows that the energy consumption of tram system is effectively reduced by using the optimized velocity curve of energy consumption.
引文 / Ref:
欧冬秀，闫黄，阳扬.被动信号优先策略下现代有轨电车站间协调能耗优化[J].城市轨道交通研究，2019，22(06):24.
OU Dongxiu，YAN Huang，YANG Yang.Optimization of Inter-station Coordinated Energy Consumption under Tram Passive Priority Strategy[J].Urban Mass Transit，2019，22(06)：24.
OU Dongxiu，YAN Huang，YANG Yang.Optimization of Inter-station Coordinated Energy Consumption under Tram Passive Priority Strategy[J].Urban Mass Transit，2019，22(06)：24.
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