Study On Target Speed Profile Of CTCS3+ATO System Based On Rolling Horizon Optimization Algorithm

In recent years,with the rapid development of high-speed railway in China,high-speed rail ATO(Automatic Train Operation)technology under CTCS3(Chinese Train Control System)system has become a hot topic,ATO system controls train operation based on target speed profile,target speed profile directly affects the effect of automatic train operation.In the process of train operation,due to the long distance and complex operation environment,higher requirements are put forward for the calculation of target speed profile,the target speed profile should not only meet the requirements of punctuality,energy saving and comfort,but also have the ability of real-time adjustment to cope with the complex and changeable operation environment.At present,scholars have done more research on the multi-objective optimization of the target speed profile under the normal operation environment,but less research on the dynamic adjustment of the target speed profile after the change of the operation environment.According to the characteristics of rolling horizon optimization,combined with bionic optimization algorithm and comfort control technology,this paper realizes the dynamic adjustment of target speed profile.Firstly,the dynamic model of high-speed train is studied.According to the operation principle of multi-level traction handle of EMU,the traction and braking force models are established and the traction calculation formula is deduced.In addition,the operation environments and corresponding driving standards of high-speed rail under CTCS3 are analyzed,and the operation environment characteristics of C3 + ATO high-speed rail are summarized.Secondly,the characteristics of rolling horizon optimization are analyzed,and the algorithm is designed according to C3 + ATO high-speed railway operation environment.The algorithm divides the whole train running process into several time windows with equal time interval,and transforms the dynamic adjustment problem into the static multi-objective optimization problem in each time window.With the continuous progress of time,when the time reaches the next time window,the optimization is carried out again,so as to realize the dynamic adjustment of target speed profile.The multi-objective optimization problem in the time window was reduced by hierarchical optimization.The energy consumption and punctuality were optimized by improved particle swarm optimization algorithm at the bottom layer,and the comfort of the acceleration part and cruise part of the train is optimized by comfort optimization idea at the top.In addition,the influence of the length of time window on the calculation effect of rolling optimization algorithm is also analyzed.Finally,according to the above research results,the rolling horizon optimization algorithm is simulated and verified based on the data of Beijing Shenyang high speed railway and CRH380 A type EMU.Simulate the dynamic adjustment of ATO target speed profile when the train operates under the conditions of normal,temporary speed limit,abnormal wireless communication interruption,recovery after abnormal wireless communication interruption and smoke alarm.The simulation results show that the algorithm can achieve the target speed profile dynamic adjustment in each operation environments,and the target speed profile calculated is more punctual,energy-saving and comfortable than the fast running strategy on the premise that the running time has margin.On the premise that the delay can not be avoided,the rolling horizon optimization algorithm increases part of the running energy consumption compared with the fast running strategy,but has higher comfort,and avoids further amplification of the delay time as much as possible.