Battery pack capacity detection system based on combined neural network

A technology of capacity detection and neural network, applied in biological neural network models, measuring electrical variables, neural learning methods, etc., to achieve strong generalization ability, good stability, and improved use efficiency

Active Publication Date: 2015-08-19
DALIAN UNIV OF TECH
View PDF10 Cites 19 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The present invention proposes a battery pack capacity detection system based on a combined neural network, which is used to solve the detection problem of the remaining capacity of the battery pack of a communication station, thereby obtaining a more accurate detection result, and providing a guarantee for the performance and optimal use of the battery pack during work. A reliable detection technique

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
  • Battery pack capacity detection system based on combined neural network
  • Battery pack capacity detection system based on combined neural network
  • Battery pack capacity detection system based on combined neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0020] Specific embodiments of the present invention will be described in detail below in conjunction with technical solutions and accompanying drawings.

[0021] Taking a 24V7Ah Ni-MH battery pack used in a communication station as an example, a battery pack capacity detection method based on a combined neural network is implemented. For lithium batteries, this embodiment is also applicable. The specific implementation steps are as follows:

[0022] Step 1: Obtain and construct a training sample set for training the combined neural network battery pack capacity detection system.

[0023] (1.1) Press figure 1The shown structure is based on the combined neural network battery pack capacity detection training system. A 24V 7Ah Ni-MH battery pack in a fully charged state is selected as the sample to be tested. figure 1 The battery pack charge and discharge and voltage detectors in accordance with Figure 5 The shown sample battery pack voltage data cycle collection process pe...

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 relates to a battery pack capacity detection system based on a combined neural network, which is characterized by comprising a battery pack capacity detection training system and a battery pack capacity detection work system. A combined neural network in the battery pack capacity detection work system is composed of a BP network detection unit and three ELM network detection units, wherein each neural network detection unit is acquired by the battery pack capacity detection training system through using sample data, and the neural network detection units are applicable to different ranges of capacity detection and carry out appropriate combination in application according to an intermediate result, thereby being capable of playing a role of taking advantages to offset disadvantages and optimizing a final detection result. When capacity detection is carried out on a battery pack to be detected, the BP network detection unit is used at first to carry out primary detection, and a range where the capacity of the battery pack to be detected is determined; and then the ELM network detection unit which is suitable for the range is selected to carry out secondary detection, thereby being capable of acquiring a more accurate detection result.

Description

technical field [0001] The invention belongs to the technical field of battery capacity detection, and relates to a battery pack capacity detection system that uses a combined neural network. Background technique [0002] The battery pack in the communication radio station is one of the key components to ensure the normal operation of the communication equipment. The performance and remaining capacity of the battery pack directly affect the performance of the radio station, which is related to the normal operation of the equipment and the smooth communication. [0003] The following problems exist in the use of communication station battery packs: maintain the battery packs with a lot of remaining charge or have not reached the maintenance cycle; continue to use the battery packs with poor charge performance or failure. The above problems will affect the cycle life of the battery pack and the normal use of the equipment. The existing technical means to detect the state of c...

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): G01R31/36G06N3/08
Inventor 郭成安潘贵财
Owner DALIAN UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products