Volume 40 Issue 6
Dec.  2022
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GE Xin, ZHANG Yuzhao. An Energy-saving Method Based on Optimized Timetable for High-speed Trains Considering Driving Strategy[J]. Journal of Transport Information and Safety, 2022, 40(6): 118-126. doi: 10.3963/j.jssn.1674-4861.2022.06.012
Citation: GE Xin, ZHANG Yuzhao. An Energy-saving Method Based on Optimized Timetable for High-speed Trains Considering Driving Strategy[J]. Journal of Transport Information and Safety, 2022, 40(6): 118-126. doi: 10.3963/j.jssn.1674-4861.2022.06.012

An Energy-saving Method Based on Optimized Timetable for High-speed Trains Considering Driving Strategy

doi: 10.3963/j.jssn.1674-4861.2022.06.012
  • Received Date: 2022-04-22
    Available Online: 2023-03-27
  • In order to reduce the traction-energy consumption for high-speed trains running from the origin station to the destination station, an energy-saving optimization method for train timetable was proposed considering synchronous allocation of the travel time between stations for multiple trains. Firstly, a set of driving strategies are developed based on the "four-stage" maneuvering strategy adopted by high-speed trains. In addition, taking traction distance and cruising distance as change factors, traction energy consumption and travel time between stations are divided into calculation objectives, and the linear relationship between traction energy consumption and travel time between stations in the optimal driving strategy set was solved. Finally, with the goal of minimizing the traction-energy consumption, an energy-saving timetable model for high-speed trains is developed based on the optimal allocation of travel time between stations. The model considers the constraints of the multiple trains' total travel time, variable value range constraints and safety interval time constraints of the train timetable. In terms of model estimation, Lagrange relaxation algorithm is used. The original problem is decomposed into several sub-problems that could be solved independently in each section by relaxing complex constraints into the objective function. Therefore, the exact solution is obtained by subgradient optimization, and the model achieve the goal of synchronous allocation of travel time between stations for multiple trains. In the end, the validity of the proposed model is further examined by a case study of Baoji-Lanzhou high-speed railway corridor. The results show that the 10 trains totally saved 595.958 traction-energy and the average energy-saving rate reached 1.2% by re-allocating the travel time between stations. From the perspective of timetable, the energy saving method by adjusting the travel time between stations is of great practical significance with the reason that it has a small impact on the magnitude of the adjustment of train timetable. In addition, the calculation time of the proposed model and algorithm is 10 s, which can effectively improve the solving efficiency for the high-speed railway with a large number of trains

     

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