With the role of lithium-based batteries escalating in an increasingly electrified economy, it is critical to fully understand the factors that affect battery performance and limit battery longevity. However, the complexities of battery chemistries often lead to fundamental half-cell studies that do not fully capture the complicated interactions within the full-cell batteries powering society. This project aims to develop a non-destructive method of monitoring the performance of individual electrodes in the full-cell through experimentally-validated battery modelling. This full-cell model connects two physics-based half-cell models that disaggregates its respective electrode response into the individual solid-state reactions occurring in the electrode, which are each described by a set of thermodynamic parameters. These thermodynamic parameters enable the quantification of individual electrode contributions to the total full-cell battery response, while shifts in these parameters can describe the evolution of electrode material phase transitions, which is strongly correlated with battery degradation. This Python-based analytical tool is complementary to traditional characterization techniques and can easily be implemented in any battery group without the need of any specialty equipment or facilities.
Advisor: Daniel Schwartz – Chemical Engineering