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

The Korean Institute of Power Electronics (전력전자학회)
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Degradation Prediction and Analysis of Lithium-ion Battery using the S-ARIMA Model with Seasonality based on Time Series Models

시계열 모델 기반의 계절성에 특화된 S-ARIMA 모델을 사용한 리튬이온 배터리의 노화 예측 및 분석

  • Kim, Seungwoo (Department of Electrical Engineering, Chungnam National University) ;
  • Lee, Pyeong-Yeon (Department of Electrical Engineering, Chungnam National University) ;
  • Kwon, Sanguk (Department of Electrical Engineering, Chungnam National University) ;
  • Kim, Jonghoon (Dept. of Electrical Engineering, Chungnam National University)
  • Received : 2021.10.20
  • Accepted : 2022.01.27
  • Published : 2022.08.20
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Abstract

This paper uses seasonal auto-regressive integrated moving average (S-ARIMA), which is efficient in seasonality between time-series models, to predict the degradation tendency for lithium-ion batteries and study a method for improving the predictive performance. The proposed method analyzes the degradation tendency and extracted factors through an electrical characteristic experiment of lithium-ion batteries, and verifies whether time-series data are suitable for the S-ARIMA model through several statistical analysis techniques. Finally, prediction of battery aging is performed through S-ARIMA, and performance of the model is verified through error comparison of predictions through mean absolute error.

Keywords

Acknowledgement

본 논문은 2021년도 정부(산업통상자원부)의 재원으로 한국에너지기술평가원의 지원(20210501010020)과 한국전력공사의 2021년 선정 기초연구개발 과제 연구비 지원(R21XO01-3)을 받아 수행되었음.

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