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New Reduced‐Order Lithium‐Ion Battery Model to Account for the Local Fluctuations in the Porous Electrodes
Author(s) -
Traskunov Igor,
Latz Arnulf
Publication year - 2021
Publication title -
energy technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.91
H-Index - 44
eISSN - 2194-4296
pISSN - 2194-4288
DOI - 10.1002/ente.202000861
Subject(s) - battery (electricity) , porosity , lithium (medication) , representation (politics) , mechanics , statistical physics , materials science , electrode , porous medium , lithium ion battery , macroscopic scale , microstructure , microscopic scale , scale (ratio) , chemical physics , physics , thermodynamics , chemistry , composite material , medicine , power (physics) , optics , quantum mechanics , politics , political science , law , endocrinology
Numerical simulations of microscopic transport processes in porous electrodes of lithium‐ion batteries demonstrate the presence of spatially localized fluctuations of physical quantities on the microstructure scale. They can influence the macroscopic battery characteristics (for example, the degradation rates). These fluctuations cannot be captured in a straightforward manner by the widely used porous electrode theory by Doyle, Fuller, and Newman (DFN model). The latter treats the porous electrodes as macroscopically homogeneous composite materials; it reduces the computational costs of numerical simulations. Herein, a modification of the DFN model that incorporates the local fluctuations but preserves the computational efficiency is proposed. Numerical simulation examples are presented that test the accuracy of the reproduction of the local fluctuations. The main new feature lies in the mathematical representation of the slow transport processes in the active material and their influence on the macroscopic reaction rates. The model is rooted in the rigorous mathematical analysis of the transition from a microscopic, microstructure‐resolving transport and reaction description to a macroscopic, volume averaging‐based one. The model construction methodology is open for further modifications for the applications in which some of the assumptions should be dropped, or description of new processes, reactions, phases, etc. should be incorporated.