Application of Modified K-Means Clustering Algorithm in Battery Grouping

In the production process of lithium-ion battery, the inconsistency of single cell characteristics in battery pack will seriously affect the whole life and performance of battery pack. In this paper, a lithium-ion battery grouping model is proposed, which includes a data preprocessing model and a no...

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Bibliographic Details
Published in:2018 IEEE 4th International Conference on Computer and Communications (ICCC) pp. 2007 - 2011
Main Authors: Wang, Lianjing, Tan, Jie, Man, Chuntao, Bai, Xiwei, Wang, Xuelei, Liu, Chengbao
Format: Conference Proceeding
Language:English
Published: IEEE 01.12.2018
Subjects:
Automation
Batteries
battery grouping
Clustering algorithms
Data models
Discharges (electric)
equal-number
modified K-means clustering
Production
Temperature measurement
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Summary:In the production process of lithium-ion battery, the inconsistency of single cell characteristics in battery pack will seriously affect the whole life and performance of battery pack. In this paper, a lithium-ion battery grouping model is proposed, which includes a data preprocessing model and a novel battery grouping method of K-means algorithm to meet the specific requirements. In the battery data preprocessing model, the faulty battery is removed by designing the process data preprocessing method and actual production standards. In the battery matching algorithm, an improved K-means algorithm is proposed. After the battery grouping is completed, the number of batteries in each cluster is equal. Additionally, experiments for battery grouping and method validation are designed. Compared with the actual method, the proposed method proves its effectiveness.
DOI:10.1109/CompComm.2018.8780986