首页期刊在线 2023年（第26卷）第2期

基于蚁群算法的城市轨道交通列车节能运行优化模型仿真分析

李兰鹏

Simulation Analysis of Urban Rail Transit Train Energy-saving Operation Optimization Model Based on Ant Colony Algorithm

LI Lanpeng

作者信息:

上海申通轨道交通研究咨询有限公司， 200070，上海
Affiliation:

Shanghai Shentong Rail Transit Research & Consultancy Co., Ltd., 200070, Shanghai, China
关键词:

城市轨道交通;列车节能运行;蚁群算法
Key words:

urban rail transit;train energy-saving operation;ant colony algorithm
DOI:

10.16037/j.1007-869x.2023.02.003
中图分类号/CLCN:

TK01+8∶U27
栏目/Col:

学术专论

摘要:

对城市轨道交通列车的开行模式、牵引控制特性、驾驶策略优化算法等进行了综合分析，基于蚁群算法建立了优化求解模型匹配的列车最优运行速度曲线，采用 OPENTRACK软件对优化结果进行了仿真分析，验证了列车节能运行策略的可行性及算法优化的有效性。

Abstracts:

Comprehensive analysis is carried out on the operation mode, traction control characteristics and driving strategy optimization algorithm of urban rail transit train. Based on ant colony algorithm, an optimization solution model is established matching the optimal train running speed curve, and OPENTRACK software is used to simulate and analyze the optimization results. The feasibility of train energy-saving operation strategy and effectiveness of algorithm optimization are verified.