Accomplishing realistic worldwide market adoption of electric vehicles requires a reduction in current recharge times compared to the fast refueling time of combustion engine vehicles counterparts. Unfortunately, fast charging at rates above 1C aggressively accelerates degradation through structural damage induced by increases in local temperature and inhomogeneous transport of charge within the architectures. At the micron scale, the first indication of damage is irreversible expansion and contraction of the electrode layers indicating irreversible lithium intercalation and reduced coulombic efficiency. The damage induced to the electrode often involves void formation between the active material and conductive-binder matrix and delamination from the current collecting foil. Quantification of this evolution must be carried out in real time and, thus, non-destructively. In this study, we report the operando X-ray microtomography measurements of cylindrical cells used in EVs under simulated fast charge and drive cycles. Two 18650 batteries were measured during cycling after antecedent fast charging cycles; the 3rd, 81st and 82nd cycles to track morphological damage at different points of battery life. We employed a deep learning segmentation method using the U-Net convolutional neural network to track objectively the spatial degradation of both the anode and cathode structures. Using a Euclidean Distance Transform Mapping method, reversible and irreversible dilation and voids were spatially resolved in three dimensions within the electrode coating layers. Insight into how fast charging induces structural damage will better inform research into fast-charge protocols and new battery chemistries for electrolytes, electrolyte additives, and novel electrode architectures.

Spatial quantification of microstructural degradation during fast charge in 18650 Lithium-Ion Batteries through Operando X-Ray Micro Tomography and Euclidean distance mapping

Fall 2022 abstracts, posters, and presentations will launch in mid-September.

ACS Fall 2022

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.