A method for identifying abnormal batteries in battery systems based on autoencoders

A self-encoder and battery system technology, applied in the direction of instruments, measuring electricity, measuring electrical variables, etc., can solve difficult problems and achieve high reliability and strong user-friendliness

Active Publication Date: 2021-12-14
SHANGHAI INT AUTOMOBILE CITY GRP CO LTD +1
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Problems solved by technology

However, how to rationally use the measured voltage time series data to mine the intrinsic parameter differences between single batteries and realize the effective identification of abnormal batteries in battery packs is very difficult, and new methods need to be developed

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  • A method for identifying abnormal batteries in battery systems based on autoencoders
  • A method for identifying abnormal batteries in battery systems based on autoencoders
  • A method for identifying abnormal batteries in battery systems based on autoencoders

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Embodiment Construction

[0077] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0078] Such as figure 1 Shown is an autoencoder-based battery system abnormal battery identification method of the present invention, which includes six steps in total, which are:

[0079] Step 1: Online measurement of the voltage of each single battery during charging and discharging;

[0080] Step 2: performing data compression on the voltage curve;

[0081] Step 3: Feature extraction based on the autoencoder network;

[0082] Step 4: Construct the ce...

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Abstract

The invention relates to a method for identifying abnormal batteries in a battery system based on an autoencoder, comprising the following steps: Step 1: online measurement of the voltage of each single battery in the process of charging and discharging; Step 2: performing data compression on the voltage curve; Three: Feature extraction based on the autoencoder network; Step four: Construct the central normalized feature matrix; Step five: Calculate the mean and covariance matrix of the central normalized feature matrix; Step six: Identify abnormal batteries based on the feature matrix. Compared with the prior art, the present invention has the advantages of better visualization of battery characteristics, deeper excavation of internal characteristic change mechanism of abnormal batteries, and the like.

Description

technical field [0001] The invention relates to a battery system identification method, in particular to an autoencoder-based battery system abnormal battery identification method. Background technique [0002] Lithium-ion batteries with green environmental protection, high energy density and long service life are increasingly used in new energy vehicles, smart grids and other fields. In practical applications, abnormal batteries are common in lithium-ion battery packs. Each process of manufacturing lithium-ion batteries may affect the performance of the battery, such as affecting particle size distribution, specific surface area, conductivity, and electrode thickness. The accumulation of errors in each process is the main source of the performance difference of a single battery. In addition, the difference in the working environment of the battery will also cause abnormalities in some batteries. Abnormal batteries in the battery pack will reduce the capacity and life of t...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/396G01R31/3835
CPCG01R31/3648
Inventor 王伟平金勇贺益君
Owner SHANGHAI INT AUTOMOBILE CITY GRP CO LTD
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