The Research of Train Energy-Efficient Operation Strategy Based on Multi-Objective Optimization
- https://doi.org/10.2991/ecae-17.2018.33How to use a DOI?
- Multi-Objective Genetic Algorithm (MOGA); ATO (Automatic Train Operation); ATO double-level
In order to reducing the energy consumption of the train running between the stations, ensuring punctuality and the comfort of the passengers, this paper studies the train energy-efficient operation strategy. After taking account of the slope and the speed limit of the line, the model of multi-objective optimization train energy-efficient is established based on train energy consumption, running time and passenger comfort. The improved multi-objective genetic algorithm (MOGA) is used to optimize the target speed sequence to obtain the operation strategy of the train. Different from previous multi-objective optimization, the energy-efficient driving optimization method is realized by considering automatic train operation's (ATO) double-level control structure, slope equivalent strategy, and Pareto optimization in this paper. Based on the actual line data and vehicle parameters of Yizhuang line in Beijing subway, the optimization method is verified by simulation. The simulation results show that, after using the improved multi-objective genetic algorithm, the energy consumption and running time of the train in Yizhuang train station are obviously decreased, and after the train comfort is measured, the rate of change in acceleration or deceleration meet the requirements of passenger experience needs. It can be seen that the proposed algorithm can effectively reduce the energy consumption of the train, ensure the accuracy of the running time and improve the comfort of the passengers.
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yunzhen Luo AU - Mi An PY - 2017/12 DA - 2017/12 TI - The Research of Train Energy-Efficient Operation Strategy Based on Multi-Objective Optimization BT - Proceedings of the 2017 2nd International Conference on Electrical, Control and Automation Engineering (ECAE 2017) PB - Atlantis Press SP - 153 EP - 159 SN - 2352-5401 UR - https://doi.org/10.2991/ecae-17.2018.33 DO - https://doi.org/10.2991/ecae-17.2018.33 ID - Luo2017/12 ER -