Unlock instant, AI-driven research and patent intelligence for your innovation.

Charging pile technical condition diagnosis method and system based on deep neural network

A deep neural network and state-of-the-art technology, applied in electric vehicle charging technology, biological neural network models, charging stations, etc., can solve problems such as serious consequences and many failures, and achieve the effect of avoiding serious consequences

Active Publication Date: 2019-12-27
NARI NANJING CONTROL SYST +7
View PDF5 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Aiming at the deficiencies of the prior art, the purpose of the present invention is to provide a method and system for diagnosing the technical status of charging piles based on a deep neural network, so as to solve the problems of charging piles in the prior art caused by open circuit or short circuit of power devices. The technical problems with the most serious consequences and cannot be assessed and predicted in advance

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Charging pile technical condition diagnosis method and system based on deep neural network
  • Charging pile technical condition diagnosis method and system based on deep neural network
  • Charging pile technical condition diagnosis method and system based on deep neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0040] The present invention will be further described below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solution of the present invention more clearly, but not to limit the protection scope of the present invention.

[0041] The specific embodiment of the present invention provides a method for diagnosing the technical status of charging piles based on a deep neural network. value and ripple characteristics) to diagnose the operating status of the power devices in the charging pile.

[0042] The power module of the DC charging pile mainly includes three links: PWM rectification, filtering and high-frequency DC / DC power conversion, such as figure 1 As shown, it is a schematic diagram of the topology principle of the three-phase PWM rectifier circuit in the embodiment of the present invention. In the figure, T 1 ~T 6 is the power device, U a , U b , U c is the three-phase input voltage, L a , L b , L c...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a charging pile technical condition diagnosis method and system based on a deep neural network in the technical field of fault detection, and aims to solve the technical problems of most faults, most serious consequences and incapability of evaluating and predicting in advance caused by open circuit or short circuit of a power device of a charging pile in the prior art. Themethod comprises the following steps: acquiring a voltage signal of a direct current side of a target charging pile; and inputting the voltage signal into a pre-trained deep neural network, and obtaining the fault probability of the power device in the target charging pile.

Description

technical field [0001] The invention relates to a method and system for diagnosing technical conditions of charging piles based on a deep neural network, and belongs to the technical field of fault detection. Background technique [0002] With the increasing maturity of power battery and fast charging technology, electric vehicles have become an important part of the automotive market. Electric vehicles convert electrical energy into mechanical energy to provide power, thereby replacing or partially replacing fossil energy, which is conducive to reducing dependence on oil resources, reducing exhaust pollution, improving the atmospheric environment, and reducing carbon dioxide emissions. Due to the high power density and energy density of lithium-ion batteries, they are often used as power batteries for electric vehicles. Among them, lithium iron phosphate batteries have excellent cycle stability, and 72% of power batteries on the market use lithium iron phosphate batteries. ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04B60L53/62G01R31/379
CPCB60L53/62G01R31/379G06N3/045G06F2218/12G06F18/2415Y02T90/12
Inventor 陈良亮张浩张卫国杨凤坤郑红娟邵军军周静李化周材李明贞周承科
Owner NARI NANJING CONTROL SYST