Research On Energy-saving Optimization Of Train Traction Based On Speed Curve Optimization

With the features of safety,efficiency,punctuality and fast speed,urban rail transit has undertaken a large amount of passenger flow in urban transportation and make people travel more easily.However,when urban rail transit operates,it consumes huge amount of energy,which causes expensive cost and restricts the development of urban rail transit.How to reasonably reduce the energy consumption during urban rail transit operation has become an urgent problem to be solved.This paper optimizes the train speed curve in single and multiple sections to reduce the energy consumption of train traction by using an improved genetic algorithm.What’s more,the deviation of the train speed curve due to the change of the basic resistance parameters of the train is discussed and analyzed,and the corresponding correction scheme is proposed.The main work in this dissertation is as follows:(1)The working conditions and forces of the train when it operates in the section are analyzed,and the train dynamics model is constructed.Based on these,the energy consumption of train when it operates in the section is analyzed,and it is pointed out that reducing the energy consumption of train traction can effectively reduce the energy consumption of train operation,and the recursive formula for calculating the energy consumption of train traction is given,and the influence of the change of basic resistance parameters on the energy consumption of train traction is analyzed.(2)Using the maximum principle,the optimal control strategy of "maximum tractioncruising-coasting-maximum braking" is determined with the objective of minimizing the energy consumption of train traction.Based on this strategy,a fixed time energy saving optimization model of one train in single section is established,and the optimized train speed curve is obtained by using an improved genetic algorithm.Based on the single section energy saving optimization,the multi sections energy saving optimization problem is simplified from the perspective of train traction energy consumption and section running time,and transformed into an allocation problem of redundancy time of the line,and a fixed time energy saving optimization model of one train in multi sections is constructed,and the optimized section running time and train speed curve of each section are obtained by using the improved genetic algorithm.(3)When the basic resistance parameters of train change due to external factors,the basic resistance parameters of train need to be re-identified and the train speed curve need to be corrected.Based on the coasting control strategy of Automatic Train Operation(ATO)and parameter identification theory,the result of the least squares method and improved genetic algorithm for parameter identification is compared and analyzed,then a train speed curve correction scheme is proposed when the basic resistance parameters of train change.(4)Finally,the train data and line parameters of a city metro are used to simulate and analyze the fixed time energy-saving optimization models of single section and multi sections and the correction scheme of speed curve.The simulation results show that the traction energy consumption is reduced by 8.18% in the fixed time energy-saving optimization of single section and 17.6% in the fixed time energy-saving optimization of multi sections compared with the original scheme,and the traction energy consumption in the once-traction/braking scheme in the correction scheme is lower and more suitable with the urban rail transit operation requirements.