Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Scale-up of Physics-based Models for Predicting Degradation of Large Lithium Ion Batteries

Version 1 : Received: 17 September 2020 / Approved: 18 September 2020 / Online: 18 September 2020 (04:29:49 CEST)

A peer-reviewed article of this Preprint also exists.

Kim, H.-K.; Lee, K.-J. Scale-Up of Physics-Based Models for Predicting Degradation of Large Lithium Ion Batteries. Sustainability 2020, 12, 8544. Kim, H.-K.; Lee, K.-J. Scale-Up of Physics-Based Models for Predicting Degradation of Large Lithium Ion Batteries. Sustainability 2020, 12, 8544.

Journal reference: Sustainability 2020, 12, 8544
DOI: 10.3390/su12208544

Abstract

Large lithium-ion batteries (LIBs) in electric vehicles and energy storage systems demonstrate different performance and lifetime compared to small LIB cells, owing to the size effects generated by the electrical configuration and property imbalance. However, the calculation time for performing life predictions with three-dimensional (3D) cell models is undesirably long. In this paper, a lumped cell model with equivalent resistances (LER cell model) is proposed as a reduced order model of the 3D cell model, which enables accurate and fast life predictions of large LIBs. The developed LER cell model is validated via the comparisons with results of the 3D cell models by simulating a 20-Ah commercial pouch cell (NCM/graphite) and the experimental values. In addition, the LER cell models are applied to different cell types and sizes, such as a 20-Ah cylindrical cell and a 60-Ah pouch cell.

Subject Areas

large sized lithium-ion battery; physic-based model; life prediction; scale-up model; reduced order cell model; electric vehicles

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.