Investigation of Consistency of Aging Mechanism inside a Batch of Commercial 18650 Cells

Battery performance and its degradation have significant consequence on reliability and safety of a battery system’s functions. To understand battery degradation mechanisms of different battery chemistries within a clear cause-and-consequence context clearly identified remains very challenging today. Such a long struggle in the research community is likely due to the lack of simple and effective diagnostic tools to characterize degradation in situ through aging.

Postmortem analyses might reveal the cause of degradation and failure of a battery, but they are not useful to provide temporal resolution for practical battery monitoring, protection, and diagnosis during operation, nor can they provide useful information for prognosis. In our view, an effective battery diagnosis needs two major elements: a reliable method to determine the state of the battery and a high-fidelity toolbox to analyze the complex but crucial voltage changes with current and temperature within the cell.

To achieve such a goal, we developed a method that allows emulating different “what if” scenarios and simulating the corresponding voltage response versus cell operating parameters such as current, capacity, or other relevant information. This new analysis toolbox is based on a synthetic model that we developed and presented recently in the literature [1].

The “what if” scenarios correspond to a variety of operating and aging conditions to emulate the impacts of one or several known degradation modes such as loss of lithium inventory (LLI), loss of active materials (LAM) or impedance increases. Comparing the outputs of the simulation with the experimental data allows a unique quantification of cause-and-consequence results from cell aging with unprecedented accuracy and fidelity to allow diagnoses of the impacts from each of those degradation modes on the tested cell.

Consumer electronics, power tools, grid-scale storage, and transportation applications are driving the advanced battery technologies moving toward increasing the energy density of Li-ion cells and systems. Recently, access to electrode materials from commercial sources becomes more readily available. Such access provides great opportunities to study the materials and electrodes in terms of performance characteristics for laboratory-scale evaluation.

Here, we present results from a cycle-life study of a batch of commercial GIC || NMC high-energy 18650 cells with an end-of-charge voltage (EOCV) cut-off set at 4.35 V per manufacturer’s recommendations. Initial characterization of the batch revealed a high quality cell production with good consistency in the initial cell performance, including information derived from test results such as mass of active material, loading ratio of the negative versus positives electrodes and initial loading offset resulting from the formation of the SEI layer in the first cycle of activation. Subsequently, nine cells from this batch have been simultaneously subjected to cycle-life testing using a multi-channel Arbin test station and a climate chamber. We investigate the consistency of the aging behavior among these cells via the observation of the capacity fade with cycle number. Such an assessment of consistency is the first step toward a more systematic and quantitative approach to analyze cell impacts on pack performance, which is crucial in designing battery packs for long cycle-life applications [2-6].

Deviations from the mean of the batch are quantified and, whenever possible, their origins are traced back to the three degradation modes: loss of active material (LAM) from either one of the electrodes, loss of lithium inventory (LLI) as a result of side reactions consuming Li⁺ions or reaction kinetics degradation (RKD) resulting from changes at the interface or within the electrodes.

References:

[1] M. Dubarry, C. Truchot, B.Y. Liaw, J. Power Sources, 219 (2012) 204-216.

[2] Dubarry, M.; Vuillaume, N. & Liaw, B. Y., International Journal of Energy Research, John Wiley & Sons, Ltd., 2010, 34, 216-231.

[3] Gering, K. L.; Sazhin, S. V.; Jamison, D. K.; Michelbacher, C. J.; Liaw, B. Y.; Dubarry, M. & Cugnet, M., Journal of Power Sources, 2011, 196, 3395 - 3403.

[4] Dubarry, M.; Truchot, C.; Cugnet, M.; Liaw, B. Y.; Gering, K.; Sazhin, S.; Jamison, D. & Michelbacher, C., Journal of Power Sources, 2011, 196, 10328 - 10335.

[5] Dubarry, M.; Truchot, C.; Liaw, B. Y.; Gering, K.; Sazhin, S.; Jamison, D. & Michelbacher, C., Journal of Power Sources, 2011, 196, 10336 - 10343.

[6] Baumhöfer, T.; Brühl, M.; Rothgang, S. & Sauer, D. U., Journal of Power Sources , 2014, 247, 332 - 33.