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为了降低城市轨道交通中列车在站间运行的能耗,研究了列车的站间节能驾驶策略,在考虑线路限速和坡度的情况下,建立了时间约束下的列车节能优化模型,采用粒子群算法优化目标速度序列得出了列车节能驾驶策略。节能驾驶优化方法通过2个阶段来实现,第1阶段在站间运行时间不变的情况下,采用粒子群算法优化了列车在站间的节能驾驶策略,得到了运行时间和能耗的关系,第2阶段在多站间总运行时间不变的前提下,将运行时间进行重新分配,得到了列车在全线运行的节能驾驶策略。以北京地铁亦庄线实际线路数据和车辆参数为基础,对优化方法进行仿真验证。仿真结果表明:经过第1阶段的优化,列车在万源街-荣京东街的单站间运行能耗降低了6.15%,经过第2阶段的优化,列车在多站间总运行能耗降低了14.77%。可见,优化模型可以有效降低列车的运行能耗,为列车时刻表的编制提供依据。
In order to reduce the energy consumption of trains running between stations in urban rail transit, the energy-saving driving strategies of trains between stations are studied. Under the circumstance of considering the line speed limit and slope gradient, a time-constrained train energy saving optimization model is established. Particle swarm optimization The algorithm optimizes the target speed sequence to get the train energy-saving driving strategy. The energy-saving driving optimization method is implemented in two phases. In the first phase, the particle swarm optimization algorithm is used to optimize the energy-saving driving strategy of the train between stations, and the relationship between running time and energy consumption is obtained. In the second stage, the total running time of multi-station is unchanged, the running time is redistributed, and the energy-saving driving strategy of the train running in all lines is obtained. Based on the actual line data and vehicle parameters of Beijing Yizhuang Railway Line, the optimization method is verified by simulation. The simulation results show that after the optimization of the first stage, the energy consumption of trains running in a single station between Wanyuan Street and Rongjing East Street has decreased by 6.15%. After the optimization of the second stage, the total energy consumption of trains in multiple stations has been reduced 14.77%. It can be seen that the optimization model can effectively reduce the train energy consumption and provide the basis for the preparation of train schedules.