基于SSO算法的城轨列车速度曲线优化研究

胡融滨; 齐鲲鹏; 赵兴

doi:10.13238/j.issn.1004-2954.202407070001

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基于SSO算法的城轨列车速度曲线优化研究

规划/运输 | 更新时间：2026-06-22

- 基于SSO算法的城轨列车速度曲线优化研究
- Research on Speed Curve Optimization of Urban Rail Trains Based on SSO Algorithm
- 铁道标准设计 2026年70卷第4期页码：24-30
- 作者机构：
  
  大连交通大学机车车辆工程学院，大连　116028
- 作者简介：
  
  作者简介：胡融滨（2000—），男，工学硕士，主要从事轨道交通智能控制研究工作，E-mail:1085841665@qq. com。
  通信作者：齐鲲鹏（1976—），男，副教授，工学博士，主要从事列车运行控制、先进控制技术应用研究工作，E-mail: qikunpeng@ djtu. edu. cn。
- 基金信息：
  
  国家自然科学青年基金项目(62001079)
- DOI：10.13238/j.issn.1004-2954.202407070001
  中图分类号： U239.5
- 收稿：2024-07-07，
  
  修回：2024-09-11，
  
  纸质出版：2026-04-20
- 稿件说明：
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胡融滨, 齐鲲鹏, 赵兴. 基于SSO算法的城轨列车速度曲线优化研究[J]. 铁道标准设计, 2026,70(4):24-30.

HU Rongbin, QI Kunpeng, ZHAO Xing. Research on Speed Curve Optimization of Urban Rail Trains Based on SSO Algorithm[J]. Railway Standard Design, 2026, 70(4): 24-30.
胡融滨, 齐鲲鹏, 赵兴. 基于SSO算法的城轨列车速度曲线优化研究[J]. 铁道标准设计, 2026,70(4):24-30. DOI： 10.13238/j.issn.1004-2954.202407070001.

HU Rongbin, QI Kunpeng, ZHAO Xing. Research on Speed Curve Optimization of Urban Rail Trains Based on SSO Algorithm[J]. Railway Standard Design, 2026, 70(4): 24-30. DOI： 10.13238/j.issn.1004-2954.202407070001.

摘要

城轨列车在城市交通中发挥着越来越重要的作用，其运行性能的优劣直接关系到整个轨道交通系统的运行效率和服务质量。城轨列车速度曲线是影响列车运行性能和乘客舒适度的重要因素之一，为寻找最优列车速度曲线，提高列车运行效率、安全性和舒适性，同时降低运行能耗和停车误差，采用精子群优化算法（Sperm Swarm Optimization，SSO）进行列车速度曲线优化。首先通过对列车进行受力分析，建立动力学模型；然后建立以节能性、准时性、停车精确性、超限速误差和舒适性为优化目标的基于加权求和的多目标优化模型；最后用SSO算法求解建立的列车速度曲线优化模型，获得优化模型的最优解，生成各项指标较优的目标速度曲线。同时针对不同的运行条件和场景，设计多组对照仿真，验证算法的普适性。研究结果表明，SSO算法收敛速度快，算法性能更好，能够有效优化列车速度曲线，提高列车的运行效率、安全性和舒适性，同时降低运行能耗和停车误差，且相对于最大运行能力曲线具有更高的节能率，停车误差更小，比最大运行能力的停车误差降低57.5%。通过多组对照仿真，也验证SSO算法对更加复杂线路条件的适应性。研究结果为列车速度曲线的优化提供新的思路和方法。

Abstract

Urban rail trains play an increasingly important role in urban traffic，and their running performance is directly related to the running efficiency and service quality of the whole rail transit system. The speed curve of urban rail trains is one of the important factors that affect the running performance and passenger comfort. In order to find the optimal train speed curve，improve the running efficiency，safety and comfort of trains，and reduce the running energy consumption and stopping error，the Sperm Swarm Optimization（SSO）algorithm was used to optimize the train speed curve. Firstly，the dynamic model of the train was established through the force analysis. Then a multi-objective optimization model based on weighted summation was established，which took energy saving，punctuality，stopping accuracy，speed-limit exceedance error，and comfort as optimization objectives. Finally，the SSO algorithm was used to solve the train speed curve optimization model，obtain the optimal solution of the optimization model，and generate the target speed curve with better performance indicators. At the same time，according to different operating conditions and scenarios，multiple comparative simulations were designed to verify the universality of the algorithm. The research results showed that the SSO algorithm had fast convergence speed and better performance，which effectively optimized the train speed curve，improved the running efficiency，safety，and comfort of the train，and reduced the running energy consumption and stopping error. Compared with the maximum running capacity curve，it achieved a higher energy-saving rate，and a smaller stopping error，with a reduction of 57.5% compared to that of the maximum running capacity curve. The adaptability of the SSO algorithm to more complex line conditions was also verified by multiple comparative simulations. The research results provide a new idea and method for the optimization of train speed curve.

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references

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