Theory of SEI Formation in Rechargeable Batteries: Capacity Fade, Accelerated Aging and Lifetime Prediction

TL;DR

This paper develops a mathematical model based on SEI growth to predict capacity fade and lifetime in rechargeable batteries, validated with experimental data for graphite and silicon anodes, improving understanding of degradation mechanisms.

Contribution

It introduces a simple single-particle model for SEI growth that accurately predicts capacity fade and lifetime, extending to porous electrodes and high-rate conditions.

Findings

Model accurately explains capacity fade in graphite batteries.

Predicts battery lifetime from accelerated aging data.

Extends to silicon anodes with large volume changes.

Abstract

Cycle life is critically important in applications of rechargeable batteries, but lifetime prediction is mostly based on empirical trends, rather than mathematical models. In practical lithium-ion batteries, capacity fade occurs over thousands of cycles, limited by slow electrochemical processes, such as the formation of a solid-electrolyte interphase (SEI) in the negative electrode, which compete with reversible lithium intercalation. Focusing on SEI growth as the canonical degradation mechanism, we show that a simple single-particle model can accurately explain experimentally observed capacity fade in commercial cells with graphite anodes, and predict future fade based on limited accelerated aging data for short times and elevated temperatures. The theory is extended to porous electrodes, predicting that SEI growth is essentially homogeneous throughout the electrode, even at high rates. The lifetime distribution for a sample of batteries is found to be consistent with Gaussian statistics, as predicted by the single-particle model. We also extend the theory to rapidly degrading anodes, such as nanostructured silicon, which exhibit large expansion on ion intercalation. In such cases, large area changes during cycling promote SEI loss and faster SEI growth. Our simple models are able to accurately fit a variety of published experimental data for graphite and silicon anodes.