4.8 Article

An iterative analytical model for aging analysis of Li-ion cells

期刊

JOURNAL OF POWER SOURCES
卷 517, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.jpowsour.2021.230667

关键词

Li-ion cell; Single particle model; SEI Formation; Green's function technique; Integral balance method

资金

  1. Purdue Polytechnic Institute Post-Doctoral Fellowship Program
  2. National Science Foundation [CBET-1554183]

向作者/读者索取更多资源

Physics-based aging models are essential for understanding capacity degradation mechanisms in Li-ion batteries. This paper introduces a technique for aging analysis of Li-ion cells due to growth of the solid electrolyte interphase (SEI) layer. By combining iterative analytical solutions, the model shows good agreement with past studies and numerical simulations, offering faster computation time for degradation modeling.
Physics-based aging models are critical for understanding capacity degradation mechanisms in Li-ion batteries. This paper presents a technique for aging analysis of a Li-ion cell due to growth of the solid electrolyte interphase (SEI) layer driven by a solvent decomposition reaction at the electrode surface. The model employs an iterative technique based on the analytical solutions of the underlying conservation equations. The single-particle model describing Li-ion intercalation and de-intercalation processes is solved analytically using Green's function technique. The SEI formation problem is solved using the integral balance method. An iterative technique that combines these analytical solutions is shown to result in a converged result within a few iterations. The model is shown to agree well with results from past studies, as well as a numerical simulation. The capacity fade of Li-ion batteries is investigated under different operating conditions and different regimes, including both cycling and storage. The present model offers much faster computation time than numerical models for modeling the degradation of Li-ion cells. Further, the iterative technique described here may serve as a framework for semianalytical solutions for other, more complicated problems. This work contributes towards improving the performance and reliability of electrochemical energy conversion and storage systems.

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