Ruihe Li, Niall D. Kirkaldy, Fabian F. Oehler, Monica Marinescu, Gregory J. Offer, Simon E. J. O’Kane
{"title":"The importance of degradation mode analysis in parameterising lifetime prediction models of lithium-ion battery degradation","authors":"Ruihe Li, Niall D. Kirkaldy, Fabian F. Oehler, Monica Marinescu, Gregory J. Offer, Simon E. J. O’Kane","doi":"10.1038/s41467-025-57968-3","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":19066,"journal":{"name":"Nature Communications","volume":"18 1","pages":""},"PeriodicalIF":14.7000,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Communications","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41467-025-57968-3","RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
Nature Communications, an open-access journal, publishes high-quality research spanning all areas of the natural sciences. Papers featured in the journal showcase significant advances relevant to specialists in each respective field. With a 2-year impact factor of 16.6 (2022) and a median time of 8 days from submission to the first editorial decision, Nature Communications is committed to rapid dissemination of research findings. As a multidisciplinary journal, it welcomes contributions from biological, health, physical, chemical, Earth, social, mathematical, applied, and engineering sciences, aiming to highlight important breakthroughs within each domain.