Andrew Weng1,Peyman Mohtat1,Peter Attia2,Valentin Sulzer1,Suhak Lee1,Greg Less3,Anna Stefanopoulou1
University of Michigan–Ann Arbor1,Stanford University2,University of Michigan3
Andrew Weng1,Peyman Mohtat1,Peter Attia2,Valentin Sulzer1,Suhak Lee1,Greg Less3,Anna Stefanopoulou1
University of Michigan–Ann Arbor1,Stanford University2,University of Michigan3
Despite the important role that the solid electrolyte interface (SEI) formation process plays in determining long-term cycle life of lithium-ion batteries, accurate methods to track the quantity of lithium consumed during formation remain time-intensive and require the usage of high-precision cyclers [1]. In this work, we further investigate a scalable and facile method that was proposed in [2] to estimate the amount of lithium consumed during SEI formation based on a measurement of the full cell resistance at low states of charge (R<sub>LS</sub>). Using a model of the electrode-specific stoichiometries and resistances, we show that R<sub>LS</sub> correlates to the quantity of lithium consumed during SEI formation.<br/>To study R<sub>LS</sub> experimentally, we built and analyzed a set of forty 2.37 Ah prismatic nickel manganese cobalt (NMC) / graphite prismatic pouch cells which were formed using two different formation protocols [3] and cycled at two different temperatures. With this dataset, we demonstrate that lifetime prediction models trained using R<sub>LS</sub> are more accurate than the state-of-the-art [4] while requiring fewer cycles of data. We discuss the generalizability and limitations of applying the proposed technique towards other lithium-ion chemistries (e.g. lithium iron phosphate cathode and silicon anodes) and degradation modes (e.g. active material losses).<br/><br/>References<br/><br/>[1] Fathi, R., Burns, J.C., Stevens, D.A., Ye, H., Hu, C., Jain, G., Scott, E., Schmidt, C., and Dahn, J.R. (2014). Ultra high-precision studies of degradation mechanisms in aged LiCoO 2 /graphite Li-ion cells. J. Electrochem. Soc. 161, A1572–A1579. https://doi.org/10.1149/2. 0321410jes.<br/>[2] A. Weng, P. Mohtat, P. M. Attia, V. Sulzer, S. Lee, A. Stefanopoulou (2021). Predicting the impact of formation protocols on battery lifetime immediately after manufacturing. Joule 5, 1-22, doi: 10.1016/j.joule.2021.09.015.<br/>[3] An, S.J., Li, J., Du, Z., Daniel, C., and Wood, D.L. (2017). Fast formation cycling for lithium ion batteries. J. Power Sources 342, 846–852.<br/>[4] Severson, K.A., Attia, P.M., Jin, N., Perkins, N., Jiang, B., Yang, Z., Chen, M.H., Aykol, M., Herring, P.K., Fraggedakis, D., et al. (2019). Data-driven prediction of battery cycle life before capacity degradation. Nat. Energy 4, 383–391. https://doi.org/10.1038/s41560-019- 0356-8.