A Dual Speed-curve Optimization Based Approach For Energy-Saving Operation Strategy Of High-speed Trains

High-speed train has gained more and more attention during the past decade because of its safe, comfortable and fast nature. However, the tremendous energy consumption cannot be ignored with the increase of the train running speed and the extension of running distance, thus reducing the running energy consumption effectively becomes an important issue for many scholars of domestic and foreign. The train energy is mainly used to traction running and resistance overcoming during the operation process, the running energy consumption is different due to different operation methods, which reflect on the train running speed curves. The energy-saving operation strategy of the high speed train is constructed by optimizing the running speed curve and verified through the computer simulation, which becomes an effective way to research the optimization problem without a large number of hardware devices.The special performance characteristics of a high-speed train and the rail geographical conditions are fully considered in the dynamic model in this thesis, making the model be more effective and practical. The main novelty of this optimal strategy is lies in optimizing the actual speed curve using the method of dual speed curve optimization, which contains offline global optimization and online local optimization. Different from the typical operation methods with a single global optimization or the method in which local optimization is added to global optimization process, the two energy-saving optimization processes of high-speed train in this paper is mutually independent and work sequentially, thus the effect of saving energy is more obvious. During the offline process of speed curve optimization, combinational optimization techniques, in tandem with the speed codes and subsection, are is used for solving global optimization problem with genetic algorithm. Then in the actual running process, predictive control is developed for online optimization to refine the global optimization result, more particularly, the train operation modes are switched on the base of the line slope information, making the local speed optimization more accurate. Therefore, a more energy-efficient speed trajectory is obtained under the constraints of fixed time and distance.To verify the effectiveness of the proposed strategy, two simulation cases based on the actual railway data for CHR-3 are tested. Through the simulation result comparisons between the operation strategy of the dual speed curve optimization and the general control method, the method with global speed curve optimization and the method of other scholar, which demonstrate the better energy-saving effectiveness of the operation strategy proposed in this paper. At the same time, the actual speed deviation is corrected in a timely manner, which increases the running feasibility.