Hauptseite > Publikationsdatenbank > A Hybrid Electrochemical Multi-Particle Model for Li-ion Batteries > print

001     1016981
005     20240709081918.0
037 _ _ |a FZJ-2023-03888
041 _ _ |a English
100 1 _ |a Ali, Haider Adel
|0 P:(DE-Juel1)190784
|b 0
|e Corresponding author
111 2 _ |a 244th ECS Meeting
|c Gothenburg
|d 2023-10-08 - 2023-10-12
|w Sweden
245 _ _ |a A Hybrid Electrochemical Multi-Particle Model for Li-ion Batteries
260 _ _ |c 2023
336 7 _ |a Conference Paper
|0 33
|2 EndNote
336 7 _ |a INPROCEEDINGS
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520 _ _ |a 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.
536 _ _ |a 1223 - Batteries in Application (POF4-122)
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536 _ _ |a LLEC::VxG - Integration von "Vehicle-to-grid" (BMBF-03SF0628)
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700 1 _ |a Raijmakers, Luc
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|b 1
700 1 _ |a Chayambuka, Kudakwashe
|0 P:(DE-Juel1)186070
|b 2
700 1 _ |a Danilov, Dmitri
|0 P:(DE-Juel1)173719
|b 3
700 1 _ |a Notten, Peter H. L.
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|b 4
700 1 _ |a Eichel, Rüdiger-A.
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913 1 _ |a DE-HGF
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