This title appears in the Scientific Report :
2023
A Hybrid Electrochemical Multi-Particle Model for Li-ion Batteries
A Hybrid Electrochemical Multi-Particle Model for Li-ion Batteries
Physics-based models have proven to be effective tools for understanding the behavior of Li-ion batteries, which is essential for improving their design and performance. Among the various physics-based models, the Doyle-Fuller-Newman (DFN) model has emerged as the most widely used due to its accurat...
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Personal Name(s): | Ali, Haider Adel (Corresponding author) |
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Raijmakers, Luc / Chayambuka, Kudakwashe / Danilov, Dmitri / Notten, Peter H. L. / Eichel, Rüdiger-A. | |
Contributing Institute: |
Grundlagen der Elektrochemie; IEK-9 |
Imprint: |
2023
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Conference: | 244th ECS Meeting, Gothenburg (Sweden), 2023-10-08 - 2023-10-12 |
Document Type: |
Poster |
Research Program: |
LLEC::VxG - Integration von "Vehicle-to-grid" Batteries in Application |
Publikationsportal JuSER |
Physics-based models have proven to be effective tools for understanding the behavior of Li-ion batteries, which is essential for improving their design and performance. Among the various physics-based models, the Doyle-Fuller-Newman (DFN) model has emerged as the most widely used due to its accurate simulation of battery behavior. To address certain limitations, the Multiple-Particle DFN (MP-DFN) model was introduced. The MP-DFN model employs multiple electrode particle sizes to account for internal concentration heterogeneities and accurately capture slow diffusion processes. However, it is worth noting that the MP-DFN model comes with a relatively high computational cost. To overcome these challenges, this study has developed a Hybrid-Multiple-Particle DFN (HMP-DFN) model. |