Teardown analysis and characterization of a commercial lithium-ion battery for advanced in electric vehicles

In recent years, in-depth analysis of the manifold properties of commercial lithium-ion batteries has gained increasing attention, as it fosters optimized design and operational strategies of battery-powered applications such as battery electric vehicles. However, various properties are not easily accessible and experimental determination requires intensive efforts in the battery lab. In this study, we have performed a tear-down analysis of a commercially available lithium-ion cell with a silicon-doped graphite anode and a Ni-rich NCA cathode. Enhanced by computed tomography (CT) scans, we reveal the cell's internal geometrical properties. Furthermore, mini pouch half cells of the anode and cathode have been built to examine their electrochemical properties in context with full cell measurements. In particular, we examined the open circuit voltage with different measurement methods and for different temperatures and performed reconstruction of the full cell via fitting of electrode potentials. We give detailed insights into the kinetics of the cell by analyzing the distribution of relaxation times (DRT) calculated from electrochemical impedance spectroscopy (EIS). Individual loss processes are assigned to either electrode and their polarization resistances and time constants are quantified over a large SOC and temperature range. A comprehensive open-source dataset of the investigated cell is provided to propel international research activities in the development of advanced models and algorithms for lithium-ion batteries.

Automated summary

In this study, a commercially available lithium-ion cell was analyzed through tear-down analysis and computed tomography scans. The electrochemical properties of the anode and cathode were examined using mini pouch half cells, and detailed insights into the kinetics of the cell were obtained. A comprehensive open-source dataset of the investigated cell was provided, fostering research in advanced models and algorithms for lithium-ion batteries.