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摘要: 分析了高速铁路停站方案对列车牵引能耗和旅行时间的影响, 总结了列车牵引能耗的测算方法。将列车开行班次和停站方案转化为停站次数, 并引进机械效率, 改进了基于运动做功的列车牵引能耗的测算方法。以最小列车牵引能耗和最短旅行时间为优化目标, 以既有的运输供给为约束, 建立了既有停站方案的优化模型, 并以沪杭高速铁路为例验证了模型的有效性。研究结果表明: 最小列车牵引能耗的停站方案偏向于开行直达列车, 单班列车的停站次数减少, 中间站停站次数最多为3次, 虽然旅行时间比既有方案增大14 min, 但牵引电力每天下降559 kW·h; 在最短列车旅行时间的停站方案中, 直达列车班次为0, 中间站停站1次的列车的开行班次达到了总班次的74.4%, 旅行时间比既有方案降低12 min, 但牵引电力每天增大3 299 kW·h; 最小列车牵引能耗和最短旅行时间的同时优化结果对既有停站方案的改善效果不明显。Abstract: The influences of stop schedule on traction energy consumption and travel time for high-speed railway train were analyzed. The calculating methods of estimating train traction energy consumption were summarized. The service frequency and stop schedule were converted into stop times, the mechanical efficiency was introduced, and the calculating method of estimating train traction energy consumption based on doing-work process was improved. The minimum traction energy consumption and the shortest travel time were taken as optimization objectives, the existing transportation supply was taken as constraint condition, and the optimization model of existing stop schedule was established. Huhang High-speed Railway was taken as a case, and the validity of the proposed model was verified. Reasearch result shows that the stop schedule with the minimum traction energy consumption prefers through trains, the number of stop times reduces, and the number of maximum stop times at intermediate stations is three.Although travel time increases 14 min more than existing stop schedule, traction electricity reduces by 559 kW·h per day. In the stop schedule with the shortest travel time, the number of through train is 0, but the rate of train frequencies with one stop times at intermediate stations is 74.4%. Travel time reduces by 12 min and traction electricity increases by 3 299 kW·h per day. The stop schedule with the minimum traction energy consumption and the shortest travel time has an insignificant improvement effect compared with the existing stop schedule.
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表 1 开行班次
Table 1. Service frequency
表 2 与有停站方案及优化结果
Table 2. Existing stop schedule and optimization results
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