Research on the driving strategy of heavy-haul train based on improved genetic algorithm

被引:16
|
作者
Huang, Youneng [1 ,2 ]
Bai, Shuai [1 ]
Meng, Xianhong [3 ]
Yu, Huazhen [1 ]
Wang, Mingzhu [1 ]
机构
[1] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing 100044, Peoples R China
[2] Beijing Jiaotong Univ, State Key Lab Rail Traff Control & Safety, Beijing, Peoples R China
[3] Shuo Huang Railway Dev Co Ltd, Suning, Peoples R China
来源
ADVANCES IN MECHANICAL ENGINEERING | 2018年 / 10卷 / 08期
关键词
Heavy-haul train; improved genetic algorithm; driving strategy; simulation modeling; multi-particle model; SPEED; OPERATION;
D O I
10.1177/1687814018791016
中图分类号
O414.1 [热力学];
学科分类号
摘要
The driving safety of heavy-haul train is affected by the train's traction weight, the length of train, the line profile, the line speed limit, and other factors. Generally, when the train is running on a continuously long and steep downgrade line, it needs using the circulating air braking to adjust speed. When it is braking, the brake wave is transmitted non-linearly along the direction of the train. When it is relieved, it must be ensured that there is sufficient time for the train to be inflated. Therefore, it is difficult to ensure the safe operation of the heavy-haul train. In this article, a new method of the train's driving strategy based on improved genetic algorithm is proposed. First, a mathematical model for the operation of heavy-haul train is established with multiple parameters. Then, according to the improved genetic algorithm and the mathematical model of the heavy-haul train, the driving strategy of the chromosome of the train is studied. Finally, the driving curve which can ensure the safe running of the heavy-haul train can be obtained. By comparing the simulated driving curve with the actual one, the results show the effectiveness of the proposed method.
引用
收藏
页数:16
相关论文
共 50 条
  • [11] Study on curve negotiation performance of heavy-haul train
    Tian, Guang-Rong
    Zhang, Wei-Hua
    Chi, Mao-Ru
    Tiedao Xuebao/Journal of the China Railway Society, 2009, 31 (04): : 98 - 103
  • [12] High-speed Railway Train Energy Driving Strategy Based on Improved Genetic Algorithm
    Lei Yali
    Chen Yalan
    2022 34TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC, 2022, : 1649 - 1654
  • [13] An experiment-based empirical model for heavy-haul train air brake
    Jiang, Fan
    Li, Kai
    Wu, Honghua
    Luo, Shihui
    ADVANCES IN MECHANICAL ENGINEERING, 2023, 15 (05)
  • [14] Research on Heavy Haul Train Protection Algorithm Based on Online Parameter Identification
    Liu, Yu
    Wei, Guodong
    Qiao, Zheng
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND APPLICATION ENGINEERING (CSAE2018), 2018,
  • [15] Research on and implementation of intelligent control algorithm for heavy haul train
    Lu, Xiaohong
    Zheng, Muhuo
    Lin, Hongquan
    Tiedao Xuebao/Journal of the China Railway Society, 2017, 39 (01): : 11 - 18
  • [16] Operation Control of Heavy-Haul Train Based on Combination of Iterative Learning and Model Prediction
    Sun P.
    Zhang C.
    Jiang C.
    Wei M.
    Wang Q.
    Zhongguo Tiedao Kexue/China Railway Science, 2023, 44 (02): : 111 - 119
  • [17] TRAIN OPERATION STRATEGY OPTIMIZATION BASED ON IMPROVED GENETIC ALGORITHM
    Liu, Kaiwei
    Wang, Xingcheng
    Wang, Longda
    Liu, Gang
    INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2019, 15 (05): : 1947 - 1965
  • [18] Experimental research on the dynamic response characteristics of the transition subgrade induced by heavy-haul train passage
    Mei, Huihao
    Leng, Wuming
    Nie, Rusong
    Tu, Renpan
    Li, Yafeng
    Dong, Junli
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART F-JOURNAL OF RAIL AND RAPID TRANSIT, 2019, 233 (09) : 974 - 987
  • [19] Research on Braking Safety of the Triple Locomotive in a 10,000-Tonne Heavy-Haul Train
    Xu, Binjie
    Ge, Xin
    Ling, Liang
    Wang, Kaiyun
    ICRT 2021: PROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON RAIL TRANSPORTATION, 2022, : 237 - 243
  • [20] Research on emergency rescue technology and equipment for train operation accidents on a heavy-haul railway network
    Zhou, Xianping
    Wei, Xiang
    Ma, Lin
    Bai, Fuwei
    Huang, Hongwei
    TRANSPORTATION SAFETY AND ENVIRONMENT, 2020, 2 (04): : 260 - 270