A Model for Predicting Capacity Fade due to SEI Formation in a Commercial Graphite/LiFePO4 Cell

By Henrik Ekström, G. Lindbergh. 2015

200 citations recorded by the source corpus.

An aging model for a negative graphite electrode in a lithium-ion battery, for moderate currents up to 1C, is derived and fitted to capacity fade experimental data. The predictive capabilities of the model, using only four fitted parameters, are demonstrated at both 25°C and 45°C. The model is based on a linear combination of two current contributions: one stemming from parts of the graphite particles covered by an intact microporous solid-electrolyte-interface (SEI) layer, and one contribution from parts of the particles were the SEI layer has cracked due to graphite expansion. Mixed kinetic and transport control is used to describe the electrode kinetics.

Subfields: Automotive Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/1c6f2a35c2c5af0d2c1d2b64cc192c9d75d40169

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Kailong Liu
2. Widanalage Dhammika Widanage
3. Yi Li
4. Billy Wu
5. Xiaosong Hu
6. Valentin Sulzer
7. Mattin Lucu

In Electrical and Electronic Engineering

1. Kailong Liu
2. Yi Li
3. Widanalage Dhammika Widanage
4. Xiaosong Hu
5. Valentin Sulzer
6. Ferran Brosa Planella
7. Billy Wu
8. Mattin Lucu

Citations in the corpus

• Gaussian Process Regression With Automatic Relevance Determination Kernel for Calendar Aging Prediction of Lithium-Ion Batteries (2020, background): “erature to explain battery calendar aging behaviors [7], [8].”
• A continuum of physics-based lithium-ion battery models reviewed (2022, background): “The modelling of particle fracture can be through empirical functions to account for the new surfaces of cracks for the additional SEI growth [34], but this kind of models is only accurate for moderate C-rates.”