The use of lithium batteries for power and energy-hungry applications has risen drastically in recent years. For such applications, it is necessary to connect the batteries in large assemblies of cells in series and parallel. With a large number of cells operating together, it is necessary to understand their intrinsic variabilities, not only at the initial stage but also upon aging. In this study, we studied a batch of commercial cells to address their initial cell-to-cell variations and also the variations induced by cycling. To do so, we not only tracked several metrics associated with cell performance, the maximum capacity, the resistance, and the rate capability but also the degradation mechanism via a non-invasive quantification of the loss of lithium inventory (LLI), the loss of active material (LAM) and the kinetic degradation on both electrodes. We found that, even with small initial cell-to-cell variations, significant variations will be observed upon aging because the cells degrade at a different pace. We also observed that these variations were not correlated with the initial variations.

Vehicle-to-grid (V2G) and grid-to-vehicle (G2V) strategies are considered to help stabilize the electric grid but their true impact on battery degradation is still unknown. The intention of this study is to test the impact of such strategies on the degradation of commercial Li-ion batteries. This first part looks into the preliminary testing performed prior to the start of degradation studies to ensure that the selected cells are compatible. Both the thermodynamic and kinetic cell-to-cell variation within the selected batch and the diagnostic-ability of the cells were investigated. The cells were found to have low cell-to-cell variations and are thus consistent. Moreover, the emulation of the full cell from the half-cell data prepared from harvested electrodes was successful and the degradation forecast showed that the main degradation modes can be differentiated.

With the deployment of more and more large batteries on the grid addressing different applications, it is essential to better understand their degradation pattern and to accurately forecast their durability. In this work, the electrochemical data from a laboratory testing experiment replicating real usage was extensively investigated using incremental capacity and variance analyses. Results showed that the degradation of these cells is much more complex than what the capacity loss and the resistance increase indicated. A significant amount of “silent” degradation was uncovered. This silent degradation was quantified and forecasted to induce, in some cases, an acceleration of the capacity loss.