Comparative study of thermodynamic & kinetic parameters measuring techniques in lithium-ion batteries

Abstract

Quantitative analysis of the aging process of lithium-ion batteries by using electrochemical thermodynamic and kinetic parameters such as electrochemical potential, Li stoichiometry, and Li inventory loss is a key research topic in the development of Li-ion battery for electric vehicles and smart grids. It is generally known the above parameters can be acquired through the analysis of Electromotive Force (EMF) or Open-Circuit Voltage (OCV) curves. In this work, we proposed and applied five EMF measurement techniques to obtain the EMF-SoC relationships in LFP/Gr single-layer laminated pouch cells at different temperatures and States of Health (SoH), and comprehensively examined them from the viewpoints of eight evaluation dimensions. A Python program, named Degradation Modes Analysis (DMA), is used to diagnose the thermodynamic degradation modes of the battery automatically. Furthermore, electrochemical kinetic parameters were also extracted along with the depolarization process. For faster and more accurate aging diagnosis, we recommend an optimal blend of short relaxation time GITT (Short-Rest-GITT) and extrapolated EMF (Extrap-EMF) to reach the most precise EMF measurements and gain the most comprehensive information about battery thermodynamics and kinetics at the same time.