The Control Strategy Research Of High Speed Emus Energy Saving Operation

The railway transportation sector is one of the largest units of energy consumption in thenational economy, which has great significance to carry study on energy-saving. The energyconsumption of railway transportation is related to many factors, in a certain hardwareconditions and established operation management situation, improve the control method oflocomotive to realize energy saving operation,which is an economic and effective and feasibleways of energy saving. The study on optimal operation of high-speed train, which canimprove control level, save energy consumption, improve punctuality, reduce stop error andprovides more comfort to passengers. The optimal operation control curve of train providesguidance for the train driver’s driving operation, to ensure train operation control system thatcan form optimal control strategy and the safe efficient operation. Based on the theory of highspeed train’s control mode curve, and focus on the energy saving, train punctual and safeoperation method, the main content of this paper includes the establish of train’s energyconsumption model and the optimal operation method of train which is based on intelligentalgorithms. The research not only has important practical meaning for improving the train’ssafety, energy saving and punctuality rate, but also provides an important theoreticalfoundation that supports for the study of the optimum control of energy saving operation andmulti-objective train’s operation control model of high speed trains energy.Based on the train’s traction&braking characteristic curve and the operating data of thesystem, this paper use the data driving modeling method, establish the multi-mode brakingmodel of train’s braking process. Specific content are as follows:(1) According to the operation characteristics and traction characteristic curve of bullettrains, and put forward several energy consumption estimating model of bullet trains, use RBFdata driving energy model to approximate the train’s energy consumption and operation time,which used as a basis for the bullet train’s optimization model.(2) According to the energy saving strategy of coasting control, genetic algorithm is usedto optimize the bullet train’s coasting control point, according to the coasting model toestablish coasting control mode which is based on genetic optimal algorithm, improve the traditional genetic algorithm, use adaptive genetic algorithm to adaptively select algorithm’scrossover probability and mutation probability, which can avoid the algorithm trap into a localoptimum and improve the algorithm’s running and optimization efficiency.(3) In order to verify the validity of this method, according to the data samples of actualoperation of CRH380AL bullet trains in the running process from Ji’nan to Tai’an station, weestablish RBF data driving model of energy consumption, and optimize the coasting controlbased on adaptive genetic algorithm, at last we get a speed optimization setting curve basedon multi-objective requirements which can meet the safety, energy saving, punctuality needs.