State-of-health estimation of lithium-ion batteries based on electrochemical impedance spectroscopy: a review

Yanshuo Liu; Licheng Wang; Dezhi Li; Kai Wang

doi:10.1186/s41601-023-00314-w

English Version Journal Login

您当前的位置：

首页 >

文章列表页 >

State-of-health estimation of lithium-ion batteries based on electrochemical impedance spectroscopy: a review

Review | 更新时间：2026-09-30

- State-of-health estimation of lithium-ion batteries based on electrochemical impedance spectroscopy: a review
- Protection and Control of Modern Power Systems Vol. 8, Issue 3, Pages: 1-17(2023)
- 作者机构：
  
  1. School of Electrical Engineering, Weihai Innovation Research Institute, Qingdao University,Qingdao,China
  2. School of Information Engineering, Zhejiang University of Technology,Hangzhou,China
- 作者简介：
- 基金信息：
- DOI：10.1186/s41601-023-00314-w
  CLC：
- Published：01 July 2023
- 稿件说明：
移动端阅览
Yanshuo Liu, Licheng Wang, Dezhi Li, et al. State-of-health estimation of lithium-ion batteries based on electrochemical impedance spectroscopy: a review[J]. Protection and Control of Modern Power Systems, 2023, 8(3): 1-17.
DOI：

Yanshuo Liu, Licheng Wang, Dezhi Li, et al. State-of-health estimation of lithium-ion batteries based on electrochemical impedance spectroscopy: a review[J]. Protection and Control of Modern Power Systems, 2023, 8(3): 1-17. DOI： 10.1186/s41601-023-00314-w.

摘要

Lithium-ion batteries (LIBs) are crucial for the large-scale utilization of clean energy. However

because of the complexity and real-time nature of internal reactions

the mechanism of capacity decline in LIBs is still unclear. This has become a bottleneck restricting their promotion and application. Electrochemical impedance spectroscopy (EIS) contains rich electrochemical connotations and significant application prospects

and has attracted widespread attention and research on efficient energy storage systems. Compared to traditional voltage and current data

the state-of-health (SOH) estimation model based on EIS has higher accuracy. This paper categorizes EIS measurement methods based on different principles

introduces the relationship between LIBs aging mechanism and SOH

and compares the advantages of different SOH estimation methods. After a detailed analysis of the latest technologies

a review is given. The insights of this review can deepen the understanding of the relationship between EIS and the aging effect mechanism of LIBs

and promote the development of new energy storage devices and evaluation methods.

Abstract

Lithium-ion batteries (LIBs) are crucial for the large-scale utilization of clean energy. However

because of the complexity and real-time nature of internal reactions

and has attracted widespread attention and research on efcient energy storage systems. Compared to traditional voltage and current data

the state-of-health (SOH) estimation model based on EIS has higher accuracy. This paper categorizes EIS measurement methods based on diferent principles

introduces the relationship between LIBs aging mechanism and SOH

and compares the advantages of diferent SOH estimation methods. After a detailed analysis of the latest technologies

a review is given. The insights of this review can deepen the understanding of the relationship between EIS and the aging efect mechanism of LIBs

and promote the development of new energy storage devices and evaluation methods.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Online estimation of SOH for lithium-ion battery based on SSA-Elman neural network

Out-of-distribution Detection for Power System Text Data by Enhanced Mahalanobis Distance with Calibration

Improved Multiple Feature-Electrochemical Thermal Coupling Modeling of Lithium-Ion Batteries at Low-Temperature with Real-Time Coefficient Correction

A new protection scheme for PV-wind based DC-ring microgrid by using modified multifractal detrended fluctuation analysis

A novel method for locating the source ofsustained oscillation in power system usingsynchrophasors data

Related Author

Yu Guo

Dongfang Yang

Yang Zhang

Yixiang Zhang

Huifang Wang

Yuzhen Zheng

Zhengming Fei

Hui Zhou

Related Institution

Xi'an Traffic Engineering Institute

Strategic Research Institute, State Power Investment Corporation

Electric Power Research Institute of State Grid Zhejiang Electric Power Co., Ltd.

College of Electrical Engineering, Zhejiang University

State Grid Zhejiang Electric Power Co., Ltd.

AI问答

⁰