Study On Energy-Saving Control For Train Based On Genetic Algorithm

With the short of energy, as the foundation of social economy development, the railroaddeparment takes large quantity of energy consumption, the rearch in economy has becomeimportant. Under the given performance diagram and train group, the only locomotivecompleted the same distance at the same time also has different operation methods anddifferent energy consumption, therefore it gradually become the actual project.In the foundation of Hauling computation regulations and Movement dynamic equation,linking the command of movement, the train energy conservation model aim at to satisfythe energy consumption, time-sharing error, regulating is built, which use the real geneticalgorithm and software programs. The main contents are:Firstly how to make sure that the train runs on schedule safely in the energy short timesto achieve the minimum of energy is turned into a significant task., then introduce therearch background to discuss the feasibility results of real genetic algorithm.Secondly discussing the economy and safety of train, including the smooth start,movement and parking break to realize the optimization.Thirdly dicussing the basic principle and method of algorithm in the article, theastringency of arithmetic is proved by Pattern theorem, the real genetic algorithm'sastringency which retains the best individual mechanism and Heredity oerator are alsointroduced.Based on the knowledge of Traction calculation, the strategy of Energy-saving control isput up to establish the model, at the same time the related parameters are also discussed. Theline simplifies module, parking brake computation module, traction calculation model, forceof traction, dynamic braking, fuel hold-up curve module, sufficiency computation module,duplication module, choice module and variation module are involed in the solutionprogress. The innovation lies in the paper:the improved real genetic algorithm could insurethe converquence of the entire process and the procedures support the arbitary lengh linescurve optimization. Considering a fairly comprehensive constrains, the introduction of thepunitive mathematical function method, in accordance with the different correspondingpunishment to reflect their function in the taeget weight. Compared with other procedureswhich applicated the genetic algotithns, the dynamic braking conditions is considered whichcould reflect a more comprehensive of driver'control. It should be mentioned that the procedures could be used in the complex ramp.Finally, the compution of energy-saving modle is conducted.In this part,the sequencemanipulation, initial iteration, the crossover probability, the mutation probability and otherfactors are dicessed to analys their inpact on the process of energy-saving,the verificationexamples are also given.