%0 Journal Article
%T 基于2阶段优化的高速列车节能运行仿真研究<br>Research on simulation for energy-saving operation of high-speed trains based on two-stage optimization
%A 曹佳峰
%A 刘斌&lt
%A br&gt
%A CAO Jiafeng
%A LIU Bin
%J 铁道科学与工程学报
%D 2018
%X 以高速列车牵引计算为基础，节能运行为目标，充分考虑实际运行线路条件，提出包含坡道运行优化和全线惰行优化的两阶段优化方法，分别构建定时约束下的列车节能模型。第1阶段，将线路坡道离散化，使用遗传算法搜索列车运行能耗最小时的速度组合序列，将模型求解转化为最优化问题，获得列车速度运行曲线；第2阶段，通过遗传算法在列车的中间运行阶段选择合理的惰行位置和惰行区间速度，再次优化列车速度曲线。以济南—泰安为站间实例进行仿真，经过2阶段优化后，CRH3型高速列车节能效果达11.63%。<br>According to high-speed train traction calculation, the two-stage optimization method for ramp operation optimization and whole coasting optimization was proposed. The train energy-saving model under the constraint of timing was constructed, by taking energy-saving operation as the goal and considering the actual running condition of the ramp. In the first stage, the railway line ramp was discretized, and the genetic algorithm was employed to search the speed combination sequence of the energy consumption of the train. The model was transformed into an optimization problem, and the train speed curve was obtained. In the second stage, the genetic algorithm was used to select the coasting position and the reasonable interval of coasting speed in the middle stage of the train running, and the train speed curve was optimized again. Taking Jinan-Tai’an high-speed railway station as an example, after two-stage optimization, the energy-saving effect of CRH3 high-speed train is 11.63%
%K 高速列车
%K 节能运行
%K 2阶段优化
%K 遗传算法
%K 仿真&lt
%K br&gt
%K high-speed train
%K energy-saving operation
%K two-stage optimization
%K genetic algorithm
%K simulation
%U http://www.jrse.cn/paper/paperView.aspx?id=paper_317749