为降低高速动车组（EMUs）的运行能耗，建立了准点约束条件下的EMUs惰行能耗模型。在此基础上，采用自适应遗传算法对EMUs中间运行阶段的惰行控制策略进行优化，寻找最优位置与数目的惰行关键工况转换点，确定列车运行的惰行速度曲线，从而达到准点和节能运行的效果。

In order to reduce the operation energy consumption of high-speed electric multiple units (EMUs), an energy consumption model of EMUs coasting under on-time constraints is established. On this basis, the adaptive genetic algorithm is used to optimize the coasting control strategy of EMUs in the middle operation stage, allocate the optimal position and number of key condition conversion points of coasting, and determine the coasting speed curve of train operation. As a result, the effects of the punctual and energy-saving operation are achieved.

湖南省教育厅科学研究项目(20C1216);湖南省自然科学基金项目(2022JJ60072)