A fast analytical model for predicting battery performance under mixed kinetic control

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dc.citation.articleNumber102319en_US
dc.citation.issueNumber12en_US
dc.citation.journalTitleCell Reports Physical Scienceen_US
dc.citation.volumeNumber5en_US
dc.contributor.authorWang, Hongxuanen_US
dc.contributor.authorWang, Fanen_US
dc.contributor.authorTang, Mingen_US
dc.date.accessioned2025-01-09T20:16:55Zen_US
dc.date.available2025-01-09T20:16:55Zen_US
dc.date.issued2024en_US
dc.description.abstractPredicting battery rate performance traditionally relies on computation-intensive numerical simulations. Although faster, simplified analytical models exist, they usually assume a single rate-limiting process such as solid diffusion or electrolyte transport. Here, an improved analytical model, the uniform-reaction-solid-concentration (URCs) model, is developed for battery (dis)charging under mixed control of mass transport in both solid and electrolyte phases. Compared to previous single-particle models extended to incorporate electrolyte kinetics, URCs captures the impact of salt depletion on diminishing the (dis)charge capacity, a critical phenomenon for thick electrodes and/or at high rates. The model demonstrates good agreement with full-order simulations. Importantly, it is compatible with gradient-based optimization algorithms to efficiently search for the optimal battery configurations, while the numerical simulation method struggles to accurately evaluate the derivatives of the objective function and causes optimization to fail. These features allow our model to effectively complement numerical simulations as a useful computational tool for battery design.en_US
dc.identifier.citationWang, H., Wang, F., & Tang, M. (2024). A fast analytical model for predicting battery performance under mixed kinetic control. Cell Reports Physical Science, 5(12), 102319. https://doi.org/10.1016/j.xcrp.2024.102319en_US
dc.identifier.digital1-s2-0-S2666386424006337-mainen_US
dc.identifier.doihttps://doi.org/10.1016/j.xcrp.2024.102319en_US
dc.identifier.urihttps://hdl.handle.net/1911/118091en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsExcept where otherwise noted, this work is licensed under a Creative Commons Attribution-NonCommercial (CC BY-NC) license. Permission to reuse, publish, or reproduce the work beyond the terms of the license or beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/en_US
dc.subject.keywordrechargeable batteriesen_US
dc.subject.keywordlithium-ion batteriesen_US
dc.subject.keywordlithium metal anodeen_US
dc.subject.keywordthick electrodesen_US
dc.subject.keywordrate performanceen_US
dc.subject.keywordbattery modelingen_US
dc.subject.keywordanalytical modelen_US
dc.subject.keywordpseudo-2D simulationsen_US
dc.subject.keywordbattery cell designen_US
dc.subject.keywordbattery cell optimizationen_US
dc.titleA fast analytical model for predicting battery performance under mixed kinetic controlen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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