The Transactions of the Korean Institute of Power Electronics (전력전자학회논문지)

The Korean Institute of Power Electronics (전력전자학회)
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Machine Learning-based Screening Algorithm for Energy Storage System Using Retired Lithium-ion Batteries

에너지 저장 시스템 적용을 위한 머신러닝 기반의 폐배터리 스크리닝 알고리즘

  • Han, Eui-Seong (Dept. of Electrical and Computer Engineering, Sungkyunkwan University) ;
  • Lim, Je-Yeong (Dept. of Electrical and Computer Engineering, Sungkyunkwan University) ;
  • Lee, Hyeon-Ho (Dept. of Electrical and Computer Engineering, Sungkyunkwan University) ;
  • Kim, Dong-Hwan (Dept. of Electrical and Computer Engineering, Sungkyunkwan University) ;
  • Noh, Tae-Won (Dept. of Electrical and Computer Engineering, Sungkyunkwan University) ;
  • Lee, Byoung-Kuk (Dept. of Electrical Engineering, Sungkyunkwan University)
  • Received : 2022.01.28
  • Accepted : 2022.04.04
  • Published : 2022.06.20
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Abstract

This paper proposes a machine learning-based screening algorithm to build the retired battery pack of the energy storage system. The proposed algorithm creates the dataset of various performance parameters of the retired battery, and this dataset is preprocessed through a principal component analysis to reduce the overfitting problem. The retried batteries with a large deviation are excluded in the dataset through a density-based spatial clustering of applications with noise, and the K-means clustering method is formulated to select the group of the retired batteries to satisfy the deviation requirement conditions. The performance of the proposed algorithm is verified based on NASA and Oxford datasets.

Keywords

Acknowledgement

이 성과는 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임 (No. 2020R1A2C2003445).

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