A Comprehensive Review on Research Methods for Lithium-ion Battery of State of Health Estimation and End of Life Prediction: Methods, Properties, and Prospects

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Abstract
Recently, lithium-ion batteries (LIBs) have become the leading energy storage solution for electric vehicles, thanks to their high energy density and extended lifespan. Examining the health condition of LIBs is essential for their safe and reliable operation. This paper thoroughly outlines the most recent researches on techniques for forecasting the health of LIBs, scrutinizes the properties of diverse methodologies, and proposes future development directions. First, the aging mechanism of lithium-ion batteries is introduced and the factors affecting battery aging are explored. Then, based on different prediction objectives, the prediction of lithium-ion battery health is divided into state of health (SOH) estimation and end of life (EOL) prediction. The SOH estimation methods are introduced respectively from model-based and data-driven methodologies, while the EOL prediction is mainly focused on the data-driven methods. Finally, the future development direction of LIB health prediction is identified, and four new potential topics on battery prediction are proposed.
Funding Information
  • Youth Innovation Technology Project of Higher School in Shandong Province (2022KJ139)

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