Abstract
Aiming at the optimization problem of subway train energy conservation, this paper proposes a train energy-saving optimization method based on parallel immune particle swarm optimization. The parallel immune particle swarm optimization algorithm is used to optimize the train energy saving in two stages: firstly, the running time of each interval is fixed, the algorithm is used to search for the optimal working condition switching point, and then, the train running time is optimized under the premise of constant running time. Finally, using the real data of Beijing Yizhuang line to simulate, verify the feasibility of the model and algorithm.
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References
Chang CS, Sim SS (1997) Optimising train movements through coast control using genetic algorithms. J IEE Proc Electr Power Appl 144(1):65–73
XiuLing H, ChangLin W (2009) Simulation on train automatic operation based on moving automatic block. J Railway Comput Appl 18(10):5–10 (in Chinese)
Xin Y, Xiang L, ZiYou G et al (2013) A cooperative scheduling model for timetable optimization in subway systems. J IEEE Trans Intell Trans Syst 14(1):438–447
WenJu T, DeQiang H, HeLiang W (2017) Research on energy-saving optimization of subway train based on immune particle swarm optimization. J Locomotive Electr Drive (2):94–95 (in Chinese)
Ping L, Qiong T (2012) Analysis of traction energy consumption of urban rail transit trains. J Shandong Sci 25(3):7–11 (in Chinese)
KunFei L (2014) Research on energy saving optimization method for multi-train collaborative control. Beijing Jiaotong University, Beijing (in Chinese)
DeChun W, KePing L, Xiang L (2012) Multi-target train energy-saving scheduling model and fuzzy optimization algorithm. J Sci Technol Eng 12:2869–2873 (in Chinese)
WengBin H, YongBo W, JianGuo L (2013) Optimize subway timetable to reduce energy consumption of train braking resistor. J Urban Rail Transit Res 11:90–94 (in Chinese)
Acknowledgements
This work is supported by National Key R&D Program of China (2017YFB1201004).
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Li, S., Dai, W., Fang, L., Zhang, Y., Xing, Z. (2020). Research on Train Energy-Saving Optimization Based on Parallel Immune Particle Swarm Optimization. In: Jia, L., Qin, Y., Liu, B., Liu, Z., Diao, L., An, M. (eds) Proceedings of the 4th International Conference on Electrical and Information Technologies for Rail Transportation (EITRT) 2019. EITRT 2019. Lecture Notes in Electrical Engineering, vol 638. Springer, Singapore. https://doi.org/10.1007/978-981-15-2862-0_4
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DOI: https://doi.org/10.1007/978-981-15-2862-0_4
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