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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Veröffentlicht in:2018 IEEE 4th International Conference on Computer and Communications (ICCC) S. 2007 - 2011
Hauptverfasser: Wang, Lianjing, Tan, Jie, Man, Chuntao, Bai, Xiwei, Wang, Xuelei, Liu, Chengbao
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.12.2018
Schlagworte:
Automation
Batteries
battery grouping
Clustering algorithms
Data models
Discharges (electric)
equal-number
modified K-means clustering
Production
Temperature measurement
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Abstract 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.
AbstractList 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.
Author Wang, Lianjing
Bai, Xiwei
Wang, Xuelei
Man, Chuntao
Tan, Jie
Liu, Chengbao
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  givenname: Lianjing
  surname: Wang
  fullname: Wang, Lianjing
  organization: School of Automation, Harbin University of Science and Technology, Harbin, China
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  givenname: Jie
  surname: Tan
  fullname: Tan, Jie
  organization: Institute of Automation, Chinese Academy of Sciences, Beijing, China
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  givenname: Chuntao
  surname: Man
  fullname: Man, Chuntao
  organization: School of Automation, Harbin University of Science and Technology, Harbin, China
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  givenname: Xiwei
  surname: Bai
  fullname: Bai, Xiwei
  organization: Institute of Automation, Chinese Academy of Sciences, Beijing, China
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  givenname: Xuelei
  surname: Wang
  fullname: Wang, Xuelei
  organization: Institute of Automation, Chinese Academy of Sciences, Beijing, China
– sequence: 6
  givenname: Chengbao
  surname: Liu
  fullname: Liu, Chengbao
  organization: Institute of Automation, Chinese Academy of Sciences, Beijing, China
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Snippet In the production process of lithium-ion battery, the inconsistency of single cell characteristics in battery pack will seriously affect the whole life and...
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StartPage 2007
SubjectTerms Automation
Batteries
battery grouping
Clustering algorithms
Data models
Discharges (electric)
equal-number
modified K-means clustering
Production
Temperature measurement
Title Application of Modified K-Means Clustering Algorithm in Battery Grouping
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