ATO (Automatic Train Operation) speed command optimization method of urban rail transit train

Abstract

The invention discloses an ATO (Automatic Train Operation) speed command optimization method of an urban rail transit train. The method comprises the following steps: establishing a data module for optimizing an ATO speed command; establishing an ATO speed command combination evaluation module to evaluate superiority-inferiority of a current ATO speed command combination; establishing a multi-objective genetic algorithm NSGA-II (Non-dominated Sorting Genetic Algorithm II)-based ATO speed command energy-saving optimization method to determine an energy-saving ATO speed command so as to finally obtain an interval energy-saving ATO speed command set. According to the method, the optimal ATO speed command set of all operation intervals of a metro line can be obtained, the optimization time is greatly shortened, off-line optimization can be performed, on-line optimization can also be performed, the metro traction power consumption is reduced, and a large amount of electric energy can be saved for the urban rail traffic system of China each year.

Description

technical field [0001] The invention relates to the technical field of urban rail transit, in particular to an ATO (Automatic Train Operation) speed command optimization method for an urban rail transit train. Background technique [0002] Due to the huge traffic volume of rail transit, excessive energy consumption is a major problem faced by urban rail transit at present. Nearly 50% of it comes from the energy consumption of train traction, which not only keeps the operating cost of urban rail transit high, but also brings a heavy burden to the urban power supply system. In the current method of saving traction energy consumption, an important entry point is to study the energy-saving driving curve of the train: when designing the train running curve between two stations, the traction characteristics of the train, the ramps, curves and speed limits of the line should be considered In other cases, the train energy-saving driving control sequence or optimization curve is des...

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Problems solved by technology

[0003] However, there are the following problems in the study of train energy-saving driving curves: (1) The track, train and driving models are simplified during the research process by numerical methods to solve the optimization, and the train running energy consumption cannot be accurately calculated; (2) The computer-aided design train operation simulation model and optimization algorithm cannot be used for the optimization of the ATO speed curve: on the one hand, the optimization of the ATO speed curve is characterized by the optimization of the ATO speed command rather than the optimization of the continuous control curve; on the other hand, the genetic optimization adapts In the process of degree function design, the weight method is used to pre-set the proportion or relationship of optimizing each goal, and the optimization strategy incorporating human preference makes the final solution have certain limitations.

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