基于启发式遗传算法的列车节能运行目标速度曲线优化算法研究

Translated title of the contribution: Algorithm of Target Speed Profile Optimization of Energy-efficient Train Operation Based on Improved Heuristic Genetic Algorithm

Jie Yang*, Jiayan Wu, Biao Wang, Shaofeng Lu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

In response to the shortcomings of traditional traction optimization algorithms such as poor robustness and vulnerability to fall into local optimum under limit line conditions, a new energy-saving train operation speed profile optimization algorithm based on heuristic genetic algorithm was proposed.Based on the basic model of train operation and related constraints, as well as the classical four-stage method, the outline of speed curve was planned.The cruising speed and the position of hold-coast switching point were selected as optimization variables, and were optimized by heuristic GA.The train operation was forced to run along the shortest running curve if it intersected with the shortest running curve due to the change of speed limit.The simulation results show that the algorithm has the advantages of fast convergence, high optimization accuracy and good robustness.The algorithm effectively overcomes the inherent shortcomings of the uncertainty of search results and speed fluctuation of evolutionary algorithm, has and provides good reference significance and practical value for energy-saving operation and automatic driving in this field and for other vehicles.

Translated title of the contributionAlgorithm of Target Speed Profile Optimization of Energy-efficient Train Operation Based on Improved Heuristic Genetic Algorithm
Original languageChinese (Traditional)
Pages (from-to)1-8
Number of pages8
JournalTiedao Xuebao/Journal of the China Railway Society
Volume41
Issue number8
DOIs
Publication statusPublished - 15 Aug 2019

Keywords

  • GA
  • Heuristic guidance
  • Operational energy saving
  • Traction optimization

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