Target Speed Control Optimization of Train Movement for Saving Energy

被引：0
|
作者：
Yang Y.-Q. [1 ]
Liu H.-D. [1 ]
Ma C.-R. [1 ]
Xu L. [1 ]
机构：
[1] MOE Key Laboratory for Urban Transportation Complex Systems Theory & Technology, Beijing Jiaotong University, Beijing
来源：
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2019年 / 19卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Energy saving train operation; Genetic algorithm; Simulation; Target speed control; Urban traffic;
D O I：
10.16097/j.cnki.1009-6744.2019.01.021
中图分类号：
学科分类号：
摘要：
The paper studies the problem of urban rail transit train energy-saving operation control, proposes a discrete target speed control strategy, and takes the target speed parameters (velocity values, range of velocity bound and scale of cover mileage) as control variables. Then, an optimization model with timing constraints is established for efficient operation. To solve the model, a real coded genetic algorithm with a double punishment mechanism (DPM) is designed, and the DPM is applied to punish overtime scheme and non-energy-saving scheme so as to improve the convergence rate. The simulation results indicate that, the optimal target speed schemes obtained by this method are well adapted to the line conditions, and effectively avoid the train braking on the lower ramp. Compared with the results obtained by the heuristic algorithm, the average energy- efficient ratio under different rich time is 22.2%. Copyright © 2019 by Science Press.
引用
收藏
页码：138 / 144
页数：6
相关论文
共 11 条
  • [1] Asnis I.A., Dmitruk A.V., Osmolovskii N.P., Solution of the problem of the energetically optimal control of the motion of a train by the maximum principle, Ussr Computational Mathematics and Mathematical Physics, 25, 6, pp. 37-44, (1985)
  • [2] Howlett P.G., The optimal control of a train, Annals of Operations Research, 98, pp. 65-87, (2000)
  • [3] Wang Z.L., An optimal operating method of train running for saving energy, Journal of Southwest Jiaotong University, 29, 3, pp. 275-280, (1994)
  • [4] Chang C.S., Sim S.S., Optimising train movements through coast control using genetic algotithms, 144, 1, pp. 65-73, (1997)
  • [5] Jin W.D., Wang Z.L., Li C.W., Et al., Study on optimization method of train operation for saving energy, Journal of the China Railway Society, 19, 6, pp. 58-62, (1997)
  • [6] Ding Y., Mao B.H., Liu H.D., Et al., An algorithm for energy-efficient train operation simulation with fixed running time, Journal of System Simulation, 16, 10, pp. 2241-2244, (2004)
  • [7] Bai Y., Mao B.H., Zhou F.M., Et al., Energy-efficient driving strategy for freight trains based on power consumption analysis, Journal of Transportation Systems Engineering and Information Technology, 9, 3, pp. 43-50, (2009)
  • [8] Mao B.H., Ho T.J., Yuan Z.Z., Et al., A general-purposed simulation system on train movement, Journal of the China Railway Society, 22, 1, pp. 1-6, (2000)
  • [9] Mao B.H., Li X.M., Train Movement Calculation And Design(The Second Edition), (2013)
  • [10] Ma C.Y., Mao B.H., Liang X., Et al., Coast control of urban train movement for energy efficiency, Journal of Transport Information and Safety, 28, 2, pp. 7-42, (2010)
12