Application of Electrochemical Impedance Spectroscopy to Degradation and Aging Research of Lithium-Ion Batteries

An in-depth understanding of battery degradation and aging in-Operando not only plays a vital role in the design of battery managing systems but also helps to ensure safe use and manufacturing optimization of lithium-ion batteries (LIBs) in large-scale applications. Electrochemical impedance spectroscopy (EIS) is a nondestructive method which unravels electrode kinetic processes inside the batteries in different time domains, including charge-transfer reactions, interfacial evolutions, and mass diffusions. It has become a powerful diagnosis and pre/prognosis tool in battery aging research, as it provides important insight into the changes of internal electrochemical processes by correlating the impedance evolution to degradation mechanisms. This review gives a critical overview on rapidly developing impedance techniques for degradation and aging investigation of Li-ion batteries. The EIS variations of LIBs at different aging conditions of calendar aging and accelerated aging are systematically summarized. In addition, the working principles, data validation, and modeling methods, including equivalent circuit model (ECM), distribution of relaxation times (DRT), and transmission line model (TLM), of classical EIS and dynamic EIS are elaborately concluded. Finally, the challenges and perspectives of further application of EIS in the aging research of LIBs are presented.

Automated summary

An in-depth understanding of battery degradation and aging is crucial for the design of battery management systems and the safe use and optimization of lithium-ion batteries (LIBs) in large-scale applications. Electrochemical impedance spectroscopy (EIS) is a powerful tool for battery aging research, providing insight into the changes of internal electrochemical processes and degradation mechanisms. This review critically evaluates impedance techniques for degradation and aging investigation of Li-ion batteries, summarizing the EIS variations at different aging conditions and discussing the principles, validation, and modeling methods of classical and dynamic EIS. Challenges and perspectives for further application of EIS in LIB aging research are also presented.