Resumen
Currently, there are few analyses available to quantitatively uncover the effects of cycling-induced damage in silicon-based batteries on the stress evolution and capacity loss. We develop a comprehensive model to address this issue. The comparisons between numerical and experimental results validate the proposed model and illustrate the damage effects on the decrease of structural stiffness and the stress evolution. In contrast to the common perception that damage is unfavorable to batteries, we propose a concept of training of batteries which introduces sufficient damage to batteries to improve retention performance. The training process is implemented by electrochemical cycling under a large C-rate, and its merit is validated experimentally. We also discuss optimization of the training method.
| Idioma original | English |
|---|---|
| Número de artículo | 107660 |
| Publicación | International Journal of Fatigue |
| Volumen | 172 |
| DOI | |
| Estado | Published - jul 2023 |
Nota bibliográfica
Publisher Copyright:© 2023 Elsevier Ltd
Financiación
K.Z. is grateful for the supports from the National Natural Science Foundation of China under grant No. 11902222 , and the Fundamental Research Funds for the Central Universities, Tongji University under grant No. 22120210527. Y.L. thanks the support from the National Natural Science Foundation of China under grant No. 11902073 .
| Financiadores | Número del financiador |
|---|---|
| National Natural Science Foundation of China (NSFC) | 11902222 |
| Tongji University | 22120210527, 11902073 |
| Fundamental Research Funds for the Central Universities |
ODS de las Naciones Unidas
Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible
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Affordable and clean energy
ASJC Scopus subject areas
- Modeling and Simulation
- General Materials Science
- Mechanics of Materials
- Mechanical Engineering
- Industrial and Manufacturing Engineering
Huella
Profundice en los temas de investigación de 'Cycling-induced damage of silicon-based lithium-ion batteries: Modeling and experimental validation'. En conjunto forman una huella única.Citar esto
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