[1]马晓娜,朱爱红,段玉琼.采用萤火虫算法的高速列车节能运行优化[J].华侨大学学报(自然科学版),2019,40(4):452-456.[doi:10.11830/ISSN.1000-5013.201809020]
　MA Xiaona,ZHU Aihong,DUAN Yuqiong.Energy-Saving Operation Optimization of High-Speed Trains Using Firefly Algorithm[J].Journal of Huaqiao University(Natural Science),2019,40(4):452-456.[doi:10.11830/ISSN.1000-5013.201809020]
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采用萤火虫算法的高速列车节能运行优化()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第40卷
期数:
2019年第4期
页码:
452-456
栏目:
出版日期:
2019-07-10

文章信息/Info

Title:
Energy-Saving Operation Optimization of High-Speed Trains Using Firefly Algorithm
文章编号:
1000-5013(2019)04-0452-05
作者:
马晓娜;  朱爱红;  段玉琼
兰州交通大学 自动化与电气工程学院, 甘肃 兰州 730070
Author(s):
MA Xiaona;  ZHU Aihong;  DUAN Yuqiong
School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
关键词:
高速列车;  运行能耗;  萤火虫算法;  节能运行曲线;  工况转换速度序列
Keywords:
high-speed train;  operation energy consumption;  firefly algorithm;  energy-saving operation curve;  condition conversion speed sequence
分类号:
U248.48
DOI:
10.11830/ISSN.1000-5013.201809020
文献标志码:
A
摘要:
智能算法可以通过优化列车运行曲线达到节能降耗的目的.将列车运行能耗作为目标函数,以限速、时间和距离为约束条件,建立优化模型.以CRH3型动车组和武广客运专线中某段线路为基础,进行仿真实验.运用萤火虫算法,搜索能耗最低时的一组列车工况转换速度序列.仿真结果表明:列车运行能耗指标降低14.33%,且满足停车精确性与准时到站的要求.
Abstract:
Intelligent algorithms can be used to optimize train operation curve to achieve energy saving and consumption reduction. Train consumption was taken as the objective function, and the optimization model was established with the speed limit, time and distance as the constraints. The simulation experiment was carried out based on the CRH3 electric multiple units running on a certain train line from the Wuhan to Guangzhou stations. The firefly algorithm was used to search for a set of train operating speed conversion sequences with the lowest energy consumption. The simulation results showed that the energy consumption index of the train was reduced by 14.33%, and the parking accuracy and on-time arrival requirements were met.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2018-09-12
通信作者: 朱爱红(1969-),女,副教授,主要从事交通信息工程及控制的研究.E-mail:791338890@qq.com.
基金项目: 国家自然科学基金资助项目(61661027)
更新日期/Last Update: 2019-07-20