Progress in estimating the state of health using transfer learning-based electrochemical impedance spectroscopy of lithium-ion batteries

doi:10.1007/s11581-025-06065-y

	Progress in estimating the state of health using transfer learning-based electrochemical impedance spectroscopy of lithium-ion batteries
	Qi, Guangheng 1,3; Du, Guangwen 2; Wang, Kai 1,3,4
	2025-01-14
发表期刊	IONICS
ISSN	0947-7047
页码	13
摘要	With the widespread application of energy storage systems, health monitoring of lithium-ion batteries (LIBs) has become important. Transfer learning (TL) provides new ideas and methods for battery health management and life prediction in the field of battery life prediction. This article spotlights the application of TL in enhancing electrochemical impedance spectroscopy (EIS) for the state of health (SOH) estimation of LIBs. It delineates the pivotal role of TL in addressing data scarcity and domain discrepancies to refine prediction accuracy. The review synthesizes recent advancements in utilizing TL with EIS data, detailing the methodology from experimental data sourcing to feature extraction, accuracy metrics, and performance analysis. It concludes by forecasting potential research directions in leveraging TL for more precise health diagnostics of LIBs and life cycle prediction.
关键词	Transfer learning Lithium-ion batteries Electrochemical impedance spectroscopy Estimation of SOH
DOI	10.1007/s11581-025-06065-y
收录类别	SCI
语种	英语
资助项目	Youth Innovation Technology Project of Higher School in Shandong Province[2022KJ139] ; Youth Innovation Technology Project of Higher School in Shandong Province
WOS研究方向	Chemistry ; Electrochemistry ; Physics
WOS类目	Chemistry, Physical ; Electrochemistry ; Physics, Condensed Matter
WOS记录号	WOS:001395729900001
出版者	SPRINGER HEIDELBERG
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/40791
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Wang, Kai
作者单位	1.Qingdao Univ, Weihai Innovat Res Inst, Coll Elect Engn, Qingdao, Peoples R China 2.Qingdao Junray Intelligent Instrument Co Ltd, Qingdao, Peoples R China 3.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China 4.Shandong Suoxiang Intelligent Technol Co Ltd, Weifang 261101, Peoples R China
推荐引用方式 GB/T 7714	Qi, Guangheng,Du, Guangwen,Wang, Kai. Progress in estimating the state of health using transfer learning-based electrochemical impedance spectroscopy of lithium-ion batteries[J]. IONICS,2025:13.
APA	Qi, Guangheng,Du, Guangwen,&Wang, Kai.(2025).Progress in estimating the state of health using transfer learning-based electrochemical impedance spectroscopy of lithium-ion batteries.IONICS,13.
MLA	Qi, Guangheng,et al."Progress in estimating the state of health using transfer learning-based electrochemical impedance spectroscopy of lithium-ion batteries".IONICS (2025):13.