基于粒子群算法的高速列车节能研究

On energy-efficient operation for high-speed trains by particle swarm optimization

针对高速列车在多站间运行中的节能优化问题,对基于时刻表优化的冗余时间分配策略进行研究。根据列车的动力学模型和列车站间节能运行,建立以准点和能耗为目标的优化模型,利用粒子群算法对总的冗余时间进行合理分配,并根据适应度函数值变化进行迭代寻优。利用京沈线辽宁段实际的线路数据进行仿真计算,给出列车运行速度、能耗关于距离的曲线图,并与其他的冗余时间分配策略进行比较,结果表明,本文提出的算法可以在保证列车准点的情况下,降低整体运行能耗,证明了算法的有效性,为列车运行图的编制提供参考。

In order to solve the problem of energy-efficient operation between multiple stations for high-speed trains, this paper investigates the anocation strategy of redundant time based on timetable optimization. According to train dynamic model and energy-efficient operation strategy, we proposed an optimization model aiming at punctuality and energy consumption. Then, Particle Swarm Algorithm was applied to allocate the redundant time reasonably and search the optimal solution iteratively based on the fitness value. According to the real geographical data of Beijing-Shenyang high-speed railway, we simulated the profiles of speed--distance and energy consumption--distance. Comparing to other allocation strategy of redundant time, the proposed algorithm can reduce the total energy consumption by ensuring the punctuality. The effectiveness of the proposed algorithm was verified. And it provides a reference for the train working diagram.