Lithium Battery Allocation Decision-Making Scheme Based on K-Means Algorithm

Lithium-ion batteries, the core components of electric vehicles, have received unprecedented attention and undergone development in the era of huge energy demand. The traditional clustering algorithm cannot meet the requirement of the consistency of lithium battery distribution. In this study, we pr...

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Bibliographic Details
Published inMathematical problems in engineering Vol. 2022; pp. 1 - 9
Main Authors Ma, Dandan, Qin, Xiangge
Format Journal Article
LanguageEnglish
Published New York Hindawi 20.06.2022
Hindawi Limited
Subjects
Aging
Algorithms
Clustering
Data processing
Decision making
Efficiency
Electric vehicles
Electrodes
Electrolytes
Energy
Engineering
Factories
Lithium
Lithium batteries
Lithium-ion batteries
Manufacturing
Rechargeable batteries
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Summary:Lithium-ion batteries, the core components of electric vehicles, have received unprecedented attention and undergone development in the era of huge energy demand. The traditional clustering algorithm cannot meet the requirement of the consistency of lithium battery distribution. In this study, we provide an improved K-means algorithm to meet the battery distribution needs of enterprises and combine it with reality. This model includes an early data processing model and a battery comparison method based on the new K-means algorithm. In the battery data processing model, the preprocessing process approach and actual production standards preclude problematic batteries. In the battery comparison algorithm, the number of batteries in each cluster becomes equal after the battery comparison. The algorithm can ensure the internal characteristics of lithium-ion power batteries, and, at the same time, after the matching is completed, the number of lithium batteries in each cluster is equal.
ISSN:1024-123X
1563-5147
DOI:10.1155/2022/7920727