Two-Stage Optimization Method of Train Energy-Efficient Operation Based on Dynamic Programming

Focusing on the problem of train energy-efficient operation between multi-sections in urban rail transit, a two-stage optimization method was proposed by integrating the processes of energy-efficient driving optimization and timetable optimization. To obtain the optimum train driving strategy between multi-sections, each process was solved with global optimum solutions, respectively. First, to realize energy saving and time saving, a multi-objective energy-efficient driving model was constructed. Utilizing the multistage-based dynamic programming searching approach, a series of sub-stage models that contain multiple objects and constrains were constructed. The Pareto front of the optimum driving strategy was generated by inverse order method. Then, a timetable optimization model was constructed, in which the Pareto front of sections was applied, and the optimum running time allocation of multi-sections was searched by dynamic programming approach. A case study of Yizhuang urban rail line in Beijing was conducted to verify the effectiveness and efficiency of the two-stage optimization method. Compared with the flat-out running strategy, the optimization of two stages resulted in 53.87% and 54.69% energy saving improvement respectively; the calculation time of two process was 258.90 s and 0.08 s respectively.