Computationally Efficient Quasi-3D Model of a Secondary Electrode Particle for Enhanced Prediction Capability of the Porous Electrode Model
Author(s) -
Klemen Zelič,
Tomaž Katrašnik
Publication year - 2022
Publication title -
journal of the electrochemical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.258
H-Index - 271
eISSN - 1945-7111
pISSN - 0013-4651
DOI - 10.1149/1945-7111/ac6323
Subject(s) - electrode , materials science , porosity , computer science , biological system , nanotechnology , chemistry , composite material , biology
Models of Li-ion batteries addressing a particular scale—from atomistic to continuum—have reached a certain level of maturity. Meanwhile, consistent multi-scale modelling approaches are still in their infancy despite their large potential to boost the accuracy and prediction capability of Li-ion battery models. As an answer to this challenge, the paper presents an advanced quasi-3D model of the active electrode material that tackles one of the main deficiencies of the porous-electrode theory (PET) based models which arises from a poor representation of the electrode topology. It is hypothesised that there exists a quasi-3D modelling representation of the active electrode material that adequately virtually replicates intra primary particle Li-distribution and features significantly shorter computational times compared to models featuring a fully 3D meshed electrode topology, which enables its full integration into the porous electrode model. An advanced quasi-3D model is constructed by the integration of the concentration and the chemical potential in each primary particle across its volume and by the introduction of the permeability parameter at the interfaces. Besides compatibility with PET and acceptable computational times, the model also exhibits results that are in good agreement with measured lithium concentration profiles inside secondary particles published in literature.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom