Research On Adaptive Optimization Algorithm Of High Speed Train Energy-saving Operation

High speed train operation is a complex control problem which focuses on safety?punctuality?energy saving and accurate parking.The performance of different operation strategies is different in the process of train operation.The optimization of train operation strategy can effectively reduce the energy consumption.However,the research on train operation strategy is mainly focused on off-line optimization.The real time optimization is still relatively scarce.In this paper,the adaptive optimization algorithm of energy saving operation of high speed train is studied based on the research of the off-line optimization algorithm of high speed train energy saving operation.This algorithm is used to adjust the train driving strategy in real time,so as to improve the energy efficiency and the train punctuality.The main contents of this paper include the following three aspects:(1)Firstly,the train dynamic model is studied,including train running particle model and train operation calculation method.Then the multi-objective optimization model which is based on running time and energy consumption of the train operation is established.On the base of these,the offline optimization algorithm of train energy saving operation based on intelligent algorithm is proposed to solve the multi-objective problem.(2)Secondly,an adaptive optimization algorithm based on the basic structure and basic principle of fuzzy control theory is proposed to improve the delay and early states of train due to uncertain factors in the actual operation.This algorithm can adjust the coast point of the optimal driving strategy of off-line selection according to the actual running state,so as to improve the energy efficiency and the train punctuality.(3)The off-line optimization algorithm of high speed train energy saving operation based on intelligent algorithm and the adaptive optimization algorithm based on fuzzy control system theory are simulated for research.In the simulation analysis,it will involve a lot of parameter settings and data updates,in order to display and analysis of the simulation results more convenient and intuitive,a simulation environment is developed.In this simulation environment,the off-line optimization algorithm of high speed train energy saving operation based on intelligent algorithm is compared and analyzed combined with the specific line data.And a group of simulation results are selected and analyzed in depth.Then,the adaptive optimization algorithm of high speed train energy saving operation based on fuzzy control theory is simulated and analyzed under the condition of delay and early scene.The simulation results show that the proposed algorithm can effectively improve the punctuality and energy-saving of the train.