A battery pack capacity detection system based on combined neural network

A technology of capacity detection and neural network, which is applied in the direction of biological neural network model, measurement of electrical variables, neural learning methods, etc., to achieve good stability, improve use efficiency, and achieve optimal use effects

Active Publication Date: 2017-07-11
DALIAN UNIV OF TECH
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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

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  • A battery pack capacity detection system based on combined neural network
  • A battery pack capacity detection system based on combined neural network
  • A battery pack capacity detection system based on combined neural network

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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...

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Abstract

A battery pack capacity detection system based on combined neural network is characterized by being composed of a battery pack capacity detection training system and a battery pack capacity detection working system. The combined neural network in the battery pack capacity detection working system is composed of one BP network detection unit and three ELM network detection units. Each neural network detection unit is obtained by the battery pack capacity detection training system through training with sample data. They are respectively suitable for capacity detection in different ranges. When applied, they can be appropriately combined according to the intermediate results, which can learn from each other and optimize the final detection results: when performing capacity detection on a battery pack to be tested, first use the BP network detection unit to perform the detection. In the primary detection, the range of the capacity of the battery pack to be tested is determined; then the ELM network detection unit suitable for the range is selected for the secondary detection, so that more accurate detection results can be obtained.

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

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/36G06N3/08
Inventor 郭成安潘贵财
Owner DALIAN UNIV OF TECH
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