A Model for Temperature-Dependent Degradation in Lithium-Ion Batteries: Correlating Electrochemical Phenomena with Cell-Level Performance Parameters

Abstract

Significant progress has been made in developing lithium-ion battery models that incorporate transport phenomena, electrochemical kinetics, and thermodynamics. While these models have been used to produce reliable results for initial performance, they lack the ability to predict capacity degradation during cycling. The prediction of key performance parameters like battery lifetime and capacity is vital for the design and thermal management of the batteries. There is often a complex interplay of simultaneous degradation mechanisms with the electrochemical dynamics of the cell. These phenomena in turn influence trends in cell-level parameters of interest, namely cell capacity and voltage response. Degradation modeling is an active research area where several works have attempted to augment state-of-the-art electrochemical models with those of various degradation mechanisms.1 In this work, we aim to develop a detailed and efficient physics-based model which couples temperature gradients within the battery with the standard models for electrochemical SEI formation.2 The model inputs for temperature can be obtained experimentally or using a detailed thermal model for the battery. There have been past attempts to combine one or multiple degradation mechanisms.3 While these works provide valuable insight, a more comprehensive picture requires consideration of electrolyte dynamics and temperature variations within the battery. The poor predictions for battery degradation are related to spatial non-uniformities and difficulties in uniform thermal management, whether due to cost or performance constraints. There is also a significant variation in parameters, mechanisms, and predictive capability of the models in the literature. The present model will consider simultaneous battery degradation due to the SEI layer growth with temperature effects and will be integrated into state-of-the-art electrochemical models like the classic pseudo-two-dimensional (p2D) model4 to be able to present a comprehensive analysis of the battery performance parameters. In order to check for the computational challenges, the integration of fade and thermal models will be performed in two different solver environments to ensure accuracy and mitigate any convergence issues.The ultimate goal is a simple and efficient numerical framework for fast and robust simulations such that the developed model would be able to generate cell-level signatures of degradation over a wide range of operating conditions and temperatures. This tailor-made model can also be combined with available experimental data for an improved qualitative understanding, as well as quantitative prediction of the different stages of battery degradation. References Edge, J. S., O'Kane, S., Prosser, R., Kirkaldy, N. D., Patel, A. N., Hales, A., Ghosh, A., Ai, W., Chen, J., Jiang, J. and Li, S., Chem. Chem. Phys. (2021) DOI: 10.1039/D1CP00359C.Safari, M., Morcrette, M., Teyssot, A., and Delacourt, C., Electrochem. Soc., 156, A145 (2009).Reniers, J. M., Mulder, G. and Howey, D. A., Electrochem. Soc, 166(14), A3189 (2019).Fuller, T. F., Doyle, M., and Newman, J., J. Electrochem. Soc., 141, 1 (1994).