Train Speed Trajectory Optimization using Dynamic Programming with speed modes decomposition

2019 2nd International Conference on Advanced Materials, Intelligent Manufacturing and Automation

Wang, Pu^1 ; Peng, Yi^2 ; Gao, Xue-Jin^3 ; Gao, Hui-Hui^4

Faculty of Information Technology, Beijing University of Technology, Beijing

100124, China^1

Engineering Research Center of Digital Community, Ministry of Education, Beijing

100124, China^2

Beijing Laboratory for Urban Mass Transit, Beijing

100124, China^3

Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing

100124, China^4

关键词: Calculation time;    Dynamic programming algorithm;    Energy-saving effect;    Optimization algorithms;    Optimization effects;    Optimization modeling;    Traction energy consumption;    Uniform discretization;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/569/4/042019/pdf
DOI  :  10.1088/1757-899X/569/4/042019

来源: IOP

【 摘 要 】

When applying a dynamic programming algorithm to train speed trajectory optimization, there is a problem of too many discrete points which leading to dimension disaster. Different from using uniform discretization of the time and space by previous research, In this paper, a train operation model is proposed based on conditions (speed limit and slope change) and described in the network diagram. Armed with this model, through the pre-planning of the line, the optimization model of train operation is established, and the dynamic programming algorithm is utilized to find the global optimal value of train traction energy consumption. Taking Beijing Yizhuang line as a simulation case, the validity of the proposed model is verified by comparing common optimization algorithms. The results demonstrate that the proposed model can effectively reduce the calculation time of the dynamic programming algorithm by 95.06%, and has better optimization effect. The energy-saving effect reaches 6.0806%.