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Power battery pack inconsistency diagnosis method and system based on K-means clustering

A technology for power battery packs and diagnostic methods, which is applied in the direction of measuring electricity, electric vehicles, and measuring electrical variables, etc., can solve problems such as high cost, difficult application, complex modeling, etc., to prolong service life, improve performance and safety Effect

Pending Publication Date: 2022-08-02
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The inventors found that most of the inconsistency diagnosis methods for power battery packs are based on the battery model. This method needs to establish an accurate and reliable battery model, and perform inconsistency diagnosis by comparing the measured value with the predicted value of the battery model. The cost of complex modeling is high, and on the other hand, it is difficult to apply in engineering

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  • Power battery pack inconsistency diagnosis method and system based on K-means clustering
  • Power battery pack inconsistency diagnosis method and system based on K-means clustering
  • Power battery pack inconsistency diagnosis method and system based on K-means clustering

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Embodiment 1

[0048]The purpose of this embodiment is to provide a power battery pack inconsistency diagnosis method based on K-means clustering.

[0049] A power battery pack inconsistency diagnosis method based on K-means clustering, comprising:

[0050] Obtain the voltage mean and standard deviation of each battery cell;

[0051] Taking the voltage mean and standard deviation of each battery cell as a data set, the data set is clustered into several clusters based on the K-means clustering algorithm; wherein the voltage mean and standard deviation of each battery cell are used as a data point coordinate value;

[0052] Calculate the distance from the data point formed by each battery cell to the center of the cluster to which it belongs;

[0053] Based on the comparison result between the distance value and the preset threshold value, it is determined whether the current battery cell is abnormal, so as to realize the inconsistency diagnosis of the power battery pack.

[0054] Further,...

Embodiment 2

[0082] The purpose of this embodiment is to provide a power battery pack inconsistency diagnosis system based on K-means clustering.

[0083] A power battery pack inconsistency diagnosis system based on K-means clustering, comprising:

[0084] a data acquisition unit, which is used to acquire the voltage mean and standard deviation of each battery cell;

[0085] The clustering unit is used to use the voltage mean and standard deviation of each battery cell as a data set, and cluster the data set into several clusters based on the K-means clustering algorithm; wherein, the voltage mean value of each battery cell is and standard deviation as a data point coordinate value;

[0086] A distance calculation unit, which is used to calculate the distance from the data point formed by each battery cell to the center of the cluster to which it belongs;

[0087] An abnormality diagnosis unit, which is configured to determine whether the current battery cell is abnormal based on the com...

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Abstract

The invention provides a power battery pack inconsistency diagnosis method and system based on K-means clustering, and belongs to the technical field of power battery packs, and the method comprises the steps: obtaining a voltage mean value and a standard deviation of each single battery; taking the voltage mean value and the standard deviation of each battery monomer as a data set, and clustering the data set into a plurality of clusters based on a K-means clustering algorithm; wherein the voltage mean value and the standard deviation of each battery monomer serve as a data point coordinate value; calculating the distance from a data point formed by each single battery to the center of the cluster to which the single battery belongs; and based on a comparison result of the distance value and a preset threshold value, judging whether the current single battery is abnormal or not, and realizing inconsistency diagnosis of the power battery pack.

Description

technical field [0001] The present disclosure belongs to the technical field of power battery packs, and in particular, relates to a method and system for diagnosing inconsistency of power battery packs based on K-means clustering. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] In the actual use process of power batteries, in order to meet the needs of power and energy, batteries are usually used in series and parallel groups. During the use of the battery pack, there are differences in the performance parameters such as voltage, internal resistance, capacity, temperature and other performance parameters of each cell and the working state such as SOC and SOH, which is the inconsistency of the battery pack. The reasons for the inconsistency of power battery packs mainly come from two aspects, which can be summarized as internal and exter...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01R31/367G01R31/396G06K9/62
CPCG01R31/367G01R31/396G06F18/23213Y02T10/70
Inventor 李岩刘振宇张承慧康永哲
Owner SHANDONG UNIV