How degradation of lithium-ion batteries impacts capacity fade and resistance increase: A systematic, correlative analysis

Abstract

Lithium-ion batteries play an essential role in a wide range of applications. It is, therefore, crucial to accurately determine their state of health, which is characterized by capacity fade and resistance increase. Their interdependency has received limited attention and this study places special emphasis on their linkage. We analyzed aging studies incorporating over 814 cells featuring NMC, NCA, and LFP chemistries and found a strong negative Pearson’s correlation coefficient ($r<-0.8$) for capacity fade and resistance increase in over 97 % of the cells investigated. This confirms that aging mechanisms affect both indicators simultaneously. We developed a power-law fit that accurately captures capacity fade with root mean square errors below $\pm$2.5 % up to at least a state-of-health of 70 %. Additionally, our findings integrate multiple aging pathways into a single analytical framework, offering a practical tool for determining battery life and improving reliability in modern power applications. We show that both resistance and impedance are closely related to aging. Therefore, evaluating either one of them in experimental studies for performance analysis and incorporating them into machine learning feature sets should be mandatory for a comprehensive investigation of battery aging.