The importance of degradation mode analysis in parameterising lifetime prediction models of lithium-ion battery degradation

Ruihe Li, Niall D. Kirkaldy, Fabian F. Oehler, Monica Marinescu, Gregory J. Offer () and Simon E. J. O’Kane
Additional contact information
Ruihe Li: Imperial College London
Niall D. Kirkaldy: Imperial College London
Fabian F. Oehler: Arcisstr. 21
Monica Marinescu: Imperial College London
Gregory J. Offer: Imperial College London
Simon E. J. O’Kane: Imperial College London

Nature Communications, 2025, vol. 16, issue 1, 1-10

Abstract: Abstract Predicting lithium-ion battery lifetime remains a critical and challenging issue in battery research right now. Recent years have witnessed a surge in lifetime prediction papers using physics-based, empirical, or data-driven models, most of which have been validated against the remaining capacity (capacity fade) and sometimes resistance (power fade). However, there are many different combinations of degradation mechanisms in lithium-ion batteries that can result in the same patterns of capacity and power fade, making it impossible to find a unique validated solution. Experimentally, degradation mode analysis involving measuring the loss of lithium inventory, loss of active material at both electrodes, and electrode drift/slippage has emerged as a state-of-the-art requirement for cell degradation studies. This work represents the integration of five distinct degradation mechanisms. We show how three models with different levels of complexity can all fit the remaining capacity and resistance well, but only the model with five coupled degradation mechanisms could also fit the degradation modes at three temperatures. This work proves that parameterizing using only capacity and power fade is no longer sufficient, and experimental and modelling degradation studies should include degradation mode analysis for parameterization in the future.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-025-57968-3 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-57968-3

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-025-57968-3

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().