시계열 모델 기반의 계절성에 특화된 S-ARIMA 모델을 사용한 리튬이온 배터리의 노화 예측 및 분석 = Degradation Prediction and Analysis of Lithium-ion Battery using the S-ARIMA Model with Seasonality based on Time Series Models

다국어 초록 (Multilingual 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.

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