Train timing energy-saving running method based on Pareto multi-target genetic algorithm

Abstract

The invention provides a train timing energy-saving running method based on a Pareto multi-target genetic algorithm. The train timing energy-saving running method based on a Pareto multi-target genetic algorithm includes steps: establishing a train running energy consumption calculation model by setting the line data and train parameters for train running; taking train traction energy consumption and section travel time as the optimization target, establishing a timing energy-saving optimization model for train running, and using the Pareto multi-target genetic algorithm to solve the optimization model to obtain the non-dominated solution set of a group of train running strategy; and according to the set train section travel time, selecting the punctual and the most energy saving train running strategy, and obtaining the corresponding speed curve and the energy consumption curve. The train timing energy-saving running method based on a Pareto multi-target genetic algorithm can effectively improve the accuracy for train timing energy saving optimization, and is high in the optimization speed, and also has the advantages of being wide in the optimal solution searching scope, reducing the energy consumption of the train, and improving the punctuality for train running.

Description

technical field [0001] The invention belongs to the technical field of train operation control, in particular to a train timing energy-saving operation method based on Pareto multi-objective genetic algorithm. Background technique [0002] In recent years, with the rapid development of my country's social economy and the continuous advancement of urbanization, urban subways have also developed rapidly, and the resulting energy consumption of urban rail transit has also increased. How to more effectively improve energy utilization and reduce operating costs on the basis of satisfying the punctual operation of trains is of great significance to the development of my country's railway industry. [0003] Train energy-saving operation control is a typical multi-objective and multi-constraint optimal control problem, and it is difficult to establish an accurate mathematical model to describe the train operation process. Traditional mathematical methods, such as numerical analysis...

AI Technical Summary

Problems solved by technology

[0003] Train energy-saving operation control is a typical multi-objective and multi-constraint optimization control problem, and it is difficult to establish an accurate mathematical model to describe the train operation process

Traditional mathematical methods, such as numerical analysis, optimal control theory, etc., are difficult to obtain the exact solution of the model, even if the iterative method is used, only the approximate solution of the model can be obtained, and it is easy to fall into local optimum

The current method to deal with multi-objective and multi-constrained optimization problems of train energy saving is mainly to convert multi-objectives into single-objective optimization by weighting multiple optimization objectives. Local optimization, only one set of solutions can be obtained, and the optimization speed is slow

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