Research On Energy Saving Control Of Rail Train Based On Passenger Flow Prediction

With the increasingly prominent problem of ground traffic congestion,more and more people choose urban rail transit.Urban rail transit not only relieves the congestion of ground traffic,but also brings huge energy consumption.In order to meet the concept of "low carbon" social development,based on the passenger flow forecast,it has become an important content of sustainable development of rail transit to study the energy saving strategy of single train and multi train operation to reduce the traction energy consumption of rail transit.In this paper,through the investigation of the passenger flow in and out of the rail transit station,based on the change point algorithm and wavelet transform,the arma-rbf combined prediction algorithm is constructed to predict the passenger flow in and out of the station;then,the force and operation conditions of the train are analyzed,and the traction energy consumption calculation model of single train is constructed with the goal of low traction energy consumption and less average waiting time of passengers;on this basis,multiple trains are considered In order to reduce the overall traction energy consumption and reduce the average waiting time of passengers in the process of multi train operation,a multi vehicle coordinated energy-saving control model is established.The main contents are as follows:(1)Forecast the passenger flow in and out of the station: the time series of passenger flow changes due to the different purpose and time of people’s travel,which is random.When there is a big fluctuation,it will affect the prediction accuracy.For the inbound passenger flow,this paper proposes ARMA-RBF prediction algorithm.The turning point of time series curve is found by using the change point algorithm to form the change point set.There will be turning points due to the survey method in the change point concentration.These turning points will be eliminated by wavelet change to ensure the authenticity of the data.ARMA-RBF passenger flow prediction algorithm is constructed,and three methods of ARMA-RBF,ARMA and RBF are used to predict passenger flow.(2)Research on energy-saving control of single train: firstly,analyze the force of single train to find the relationship between force and force.This paper studies the working condition conversion and the force change between the switching stations,determines the composition of the working condition of the train,and obtains the calculation model of energy consumption of a single train;and establishes the combined optimization model with the two control objectives of less average waiting time of passengers and low energy consumption of train traction,and solves the double-layer planning model by using genetic algorithm,and obtains the energy-saving control of a single train Run the policy.(3)Aiming at the problem of multi train coordinated energy-saving control,the queuing theory is introduced to analyze the change of passenger waiting time under different arrival intervals of multiple trains,and the calculation formula of passenger waiting time,arrival interval and train stop time is established.Considering the conditions of safe train operation interval and speed limit,the traction energy consumption of multiple trains is low on the basis of single train energy-saving model In order to reduce the average waiting time of passengers,a multi vehicle coordinated energy-saving control model is established,and the dragonfly algorithm is used to solve the multi vehicle model,and the operation strategy of multi vehicle collaborative energy-saving control is obtained.Taking Beijing Metro Line 4 as an example,anylogic software is used for simulation verification.By changing the arrival interval time,the change trend of the objective function is analyzed.The results show that the multi vehicle coordinated energy-saving control strategy is effective.The method proposed in this paper has certain reference value for reducing train traction energy consumption,and can provide support for formulating more effective rail transit operation plan.