Energy-Efficient Speed Profile Approximation: An Optimal Switching Region-Based Approach with Adaptive Resolution
作者： Jie Yang , Limin Jia , Shaofeng Lu , Yunxiao Fu , Ji Ge
DOI: 10.3390/EN9100762
关键词:
摘要: Speed profile optimization plays an important role in optimal train control. Considering the characteristics of electrical locomotive with regenerative braking, this paper proposes a new algorithm for target speed approximation. This makes following three contributions: First, it proves that under certain calculation precision, there is coast-brake switching region—not just point where should be switched from coasting mode to braking mode. very useful engineering applications. Second, analyzes influence on region and approximate linear relationship between regeneration efficiency. Third, presents average equivalent local steep sections. In addition, simplifies proof optimality smooth running non-steep track two steps. The effects energy consumption factors (optimal coast time) are systematically analyzed. Extensive simulations verify these points view demonstrate proposed approximation approach computationally efficient achieves sufficient accuracy.
mdpi.com
core.ac.uk
sci-hub.se 参考文章(21)
Shaofeng Lu, Optimising power management strategies for railway traction systems University of Birmingham. ,(2011)
Phil Howlett, The Optimal Control of a Train Annals of Operations Research. ,vol. 98, pp. 65- 87 ,(2000) , 10.1023/A:1019235819716
Amie Albrecht, Phil Howlett, Peter Pudney, Xuan Vu, Peng Zhou, The key principles of optimal train control—Part 1: Formulation of the model, strategies of optimal type, evolutionary lines, location of optimal switching points Transportation Research Part B-methodological. ,vol. 94, pp. 482- 508 ,(2016) , 10.1016/J.TRB.2015.07.023
Amie Albrecht, Phil Howlett, Peter Pudney, Xuan Vu, Peng Zhou, The key principles of optimal train control—Part 2: Existence of an optimal strategy, the local energy minimization principle, uniqueness, computational techniques Transportation Research Part B-methodological. ,vol. 94, pp. 509- 538 ,(2016) , 10.1016/J.TRB.2015.07.024
María Domínguez, Antonio Fernández-Cardador, Asunción P. Cucala, Tad Gonsalves, Adrián Fernández, Multi objective particle swarm optimization algorithm for the design of efficient ATO speed profiles in metro lines Engineering Applications of Artificial Intelligence. ,vol. 29, pp. 43- 53 ,(2014) , 10.1016/J.ENGAPPAI.2013.12.015
Rongfang (Rachel) Liu, Iakov M. Golovitcher, Energy-efficient operation of rail vehicles Transportation Research Part A-policy and Practice. ,vol. 37, pp. 917- 932 ,(2003) , 10.1016/J.TRA.2003.07.001
Xiang Li, Hong K. Lo, An energy-efficient scheduling and speed control approach for metro rail operations Transportation Research Part B-methodological. ,vol. 64, pp. 73- 89 ,(2014) , 10.1016/J.TRB.2014.03.006
Jiateng Yin, Dewang Chen, Lingxi Li, Intelligent Train Operation Algorithms for Subway by Expert System and Reinforcement Learning IEEE Transactions on Intelligent Transportation Systems. ,vol. 15, pp. 2561- 2571 ,(2014) , 10.1109/TITS.2014.2320757
Jih-Wen Sheu, Wei-Song Lin, Energy-Saving Automatic Train Regulation Using Dual Heuristic Programming IEEE Transactions on Vehicular Technology. ,vol. 61, pp. 1503- 1514 ,(2012) , 10.1109/TVT.2012.2187225
K. K. Wong *, T. K. Ho, Dynamic coast control of train movement with genetic algorithm International Journal of Systems Science. ,vol. 35, pp. 835- 846 ,(2004) , 10.1080/00207720412331203633