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Key Issues in Real-time Optimization of Braking Performance for Urban Rail Transit Trains
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Ke YU1, Xuannan ZHANG2, Hui ZHANG3
Urban Rapid Rail Transit | 2024, 37(4) : 52 - 59
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Urban Rapid Rail Transit | 2024, 37(4): 52-59
• Academic Discussion •
Key Issues in Real-time Optimization of Braking Performance for Urban Rail Transit Trains
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Ke YU1, Xuannan ZHANG2, Hui ZHANG3
Affiliations
  • 1 Beijing Subway Limited Beijing 100044
  • 2 School of Electronic and Information Engineering Beijing Jiaotong University Beijing 100044
  • 3 Beijing Technology Development Limited Beijing 100044
doi: 10.3969/j.issn.1672-6073.2024.04.008
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To address the shortage of realtime data and the accuracy limitations of existing automatic line control systems, we propose an intelligent upgrade scheme for train control systems. First, considering the distinct characteristics of electric and air braking in train operations, we developed accurate braking models for both systems, incorporating the switch between electric and air braking. Next, we optimized the ATO controller and applied a sliding mode adaptive robust control strategy. This strategy adjusts the controller in real time, enhancing its robustness and adaptability to varying vehicle parameters and external environmental interferences. Using Beijing Metro Line 5 as a case study, we simulated the precise train braking model and the sliding mode adaptive robust controller to calculate the stopping accuracy and speed error of the train. The results demonstrate that, compared to proportionalintegralderivative (PID) control and sliding mode control, the proposed control algorithm significantly reduces parking accuracy and speed errors. Specifically, the average parking accuracy achieved is less than 8 cm.

urban rail transit  /  braking performance optimization  /  SMARC control  /  electro-pneumatic braking  /  controller optimization
Ke YU, Xuannan ZHANG, Hui ZHANG. Key Issues in Real-time Optimization of Braking Performance for Urban Rail Transit Trains[J]. Urban Rapid Rail Transit, 2024 , 37 (4) : 52 -59 . DOI: 10.3969/j.issn.1672-6073.2024.04.008
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Year 2024 volume 37 Issue 4
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Article Info
doi: 10.3969/j.issn.1672-6073.2024.04.008
  • Receive Date：2024-01-22
  • Online Date：2025-07-09
Article Data
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History
  • Received：2024-01-22
  • Revised：2024-04-03
Funding
Affiliations
    1 Beijing Subway Limited Beijing 100044
    2 School of Electronic and Information Engineering Beijing Jiaotong University Beijing 100044
    3 Beijing Technology Development Limited Beijing 100044
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