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    Exploring Electrode-Level State-of-Charge and State-of-Health Dynamics in Lithium-Ion Battery Cells: Modeling and Experimental Identification

    Source: Journal of Dynamic Systems, Measurement, and Control:;2025:;volume( 147 ):;issue: 004::page 41012-1
    Author:
    Sattarzadeh, Sara
    ,
    Colclasure, Andrew M.
    ,
    Smith, Kandler
    ,
    Li, Xuemin
    ,
    Dey, Satadru
    DOI: 10.1115/1.4067951
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: A computationally efficient model serves as a critical prerequisite for battery performance analysis and advanced battery management algorithm design. Although battery models that capture cell-level behavior have been widely explored in existing literature, electrode-level battery models have received much lesser attention till to date. However, such electrode-level models can significantly increase battery performance and life by enabling electrode-level health-conscious control. Such electrode-level control can effectively expand usable energy and power limits of the battery cells by utilizing the knowledge of individual electrodes’ charge and health. In this context, this paper presents a comprehensive battery model developed with a reference electrode insertion that captures (i) electrode-level charge/discharge dynamics, (ii) stoichiometric and temporal dependencies of electrode-level resistances, (iii) solid electrolyte interface (SEI) layer growth as key degradation phenomenon, and (iv) capacity fade and resistance rise in each electrode due to nominal battery aging. The proposed model is identified, and a preliminary validation is performed utilizing terminal voltage and negative electrode potential data collected from a pouch cell under one continuous cycling and accelerated aging conditions where the cell experienced 14% capacity loss.
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      Exploring Electrode-Level State-of-Charge and State-of-Health Dynamics in Lithium-Ion Battery Cells: Modeling and Experimental Identification

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4308289
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    contributor authorSattarzadeh, Sara
    contributor authorColclasure, Andrew M.
    contributor authorSmith, Kandler
    contributor authorLi, Xuemin
    contributor authorDey, Satadru
    date accessioned2025-08-20T09:26:41Z
    date available2025-08-20T09:26:41Z
    date copyright3/28/2025 12:00:00 AM
    date issued2025
    identifier issn0022-0434
    identifier otherds_147_04_041012.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4308289
    description abstractA computationally efficient model serves as a critical prerequisite for battery performance analysis and advanced battery management algorithm design. Although battery models that capture cell-level behavior have been widely explored in existing literature, electrode-level battery models have received much lesser attention till to date. However, such electrode-level models can significantly increase battery performance and life by enabling electrode-level health-conscious control. Such electrode-level control can effectively expand usable energy and power limits of the battery cells by utilizing the knowledge of individual electrodes’ charge and health. In this context, this paper presents a comprehensive battery model developed with a reference electrode insertion that captures (i) electrode-level charge/discharge dynamics, (ii) stoichiometric and temporal dependencies of electrode-level resistances, (iii) solid electrolyte interface (SEI) layer growth as key degradation phenomenon, and (iv) capacity fade and resistance rise in each electrode due to nominal battery aging. The proposed model is identified, and a preliminary validation is performed utilizing terminal voltage and negative electrode potential data collected from a pouch cell under one continuous cycling and accelerated aging conditions where the cell experienced 14% capacity loss.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleExploring Electrode-Level State-of-Charge and State-of-Health Dynamics in Lithium-Ion Battery Cells: Modeling and Experimental Identification
    typeJournal Paper
    journal volume147
    journal issue4
    journal titleJournal of Dynamic Systems, Measurement, and Control
    identifier doi10.1115/1.4067951
    journal fristpage41012-1
    journal lastpage41012-11
    page11
    treeJournal of Dynamic Systems, Measurement, and Control:;2025:;volume( 147 ):;issue: 004
    contenttypeFulltext
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