%0 Conference Paper
%A Ali, Haider Adel
%A Raijmakers, Luc
%A Chayambuka, Kudakwashe
%A Danilov, Dmitri
%A Notten, Peter H. L.
%A Eichel, Rüdiger-A.
%T A Hybrid Electrochemical Multi-Particle Model for Li-ion Batteries
%M FZJ-2023-03888
%D 2023
%X 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.
%B 244th ECS Meeting
%C 8 Oct 2023 - 12 Oct 2023, Gothenburg (Sweden)
Y2 8 Oct 2023 - 12 Oct 2023
M2 Gothenburg, Sweden
%F PUB:(DE-HGF)24
%9 Poster
%U https://juser.fz-juelich.de/record/1016981