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A method for energy-saving optimization of train speed curve based on particle swarm optimization

A technology of particle swarm algorithm and running speed, which is applied in control/regulation systems, instruments, simulators, etc., can solve problems such as insufficient global search, adapt to changes in the external environment, overcome slow calculation speed, and achieve simple effects

Inactive Publication Date: 2018-11-23
BEIJING JIAOTONG UNIV
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

However, the intelligent algorithm has the problem that it is easy to fall into a local optimum and cannot fully perform a global search.

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  • A method for energy-saving optimization of train speed curve based on particle swarm optimization
  • A method for energy-saving optimization of train speed curve based on particle swarm optimization
  • A method for energy-saving optimization of train speed curve based on particle swarm optimization

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Embodiment Construction

[0028] In order to illustrate the present invention more clearly, the present invention will be further described below in conjunction with preferred embodiments and accompanying drawings. Similar parts in the figures are denoted by the same reference numerals. Those skilled in the art should understand that the content specifically described below is illustrative rather than restrictive, and should not limit the protection scope of the present invention.

[0029] The method for energy-saving optimization of train running speed curve based on particle swarm optimization algorithm provided in this embodiment is realized based on components such as computer, train running control recording device LKJ, GPS, train speed sensor, etc., wherein, the computer and LKJ are set in the train control room, and GPS is set in the train control room. In the train equipment room, the train speed sensor is arranged on the train axle box. The computer performs energy-saving optimization of the ...

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Abstract

The invention discloses a train operation speed curve energy saving optimization method based on a particle swarm algorithm. The method comprises the steps that S1, line data and train parameters are set, a current speed limit instruction is acquired and discretization processing is performed on the line data so that all line nodes are obtained; S2, discretization is performed on the corresponding speed range of each line node according to the line data, and a speed association sparse matrix and corresponding energy consumption and time sparse matrixes are established; S3, an energy consumption matrix is generated according to the experience of the train energy saving theory; and S4, energy saving simulation optimization is performed on a train operation speed curve by utilizing the self-adaptive particle swarm algorithm. Train energy saving optimization precision and optimization speed can be effectively enhanced.

Description

technical field [0001] The invention relates to the technical field of train operation control. More specifically, it relates to a particle swarm algorithm-based energy-saving optimization method for train speed curves. Background technique [0002] Railway transportation is one of the most important modes of transportation in my country, and it undertakes important tasks related to national economic and social development. With the vigorous development of railway construction, the energy consumption of railway transportation also shows an overall upward trend, among which the energy consumption of locomotive traction accounts for 60% to 70% of the energy consumption of railway transportation. Therefore, the energy saving and efficiency improvement of the locomotive traction system is of great significance to the energy saving of railway transportation. On the premise of punctuality and safe operation of trains, under certain conditions of lines, locomotives and vehicles, ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B17/02
CPCG05B17/02
Inventor 魏秀琨李卓玥贾利民朱明张晓中王腾腾贺延芳张靖林闫冬吕又冉
Owner BEIJING JIAOTONG UNIV