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    Short Circuit Estimation in Lithium-Ion Batteries Using Moving Horizon Estimation1

    Source: ASME Letters in Dynamic Systems and Control:;2024:;volume( 004 ):;issue: 004::page 41004-1
    Author:
    Moon, Jihoon
    ,
    Bhaskar, Kiran
    ,
    Rahn, Christopher D.
    DOI: 10.1115/1.4066515
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This paper proposes rapid and accurate short circuit estimation under resting condition using joint moving horizon estimation (MHE). The use of lithium-ion batteries (LiBs) in electric vehicles (EVs) has been increasing, leading to heightened concerns regarding the safety of LiBs. Detecting a short circuit, which is a major cause of safety incidents, is challenging when it is in its early stages. Therefore, short circuits should be detected swiftly and accurately to prevent thermal runaway and potential fires, property damage, injuries, and mortalities. During leak testing of new cells or often an EV crash, applied current may be zero and parameters unknown. The presented work addresses these challenges through the application of a joint MHE approach, to estimate both short circuit current and battery capacity. The proposed approach is evaluated through extensive simulations involving various short circuit scenarios and is compared to a joint extended Kalman filter and joint unscented Kalman filter. Experimental data are also used to validate the effectiveness of states and parameters estimation.
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      Short Circuit Estimation in Lithium-Ion Batteries Using Moving Horizon Estimation1

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    contributor authorMoon, Jihoon
    contributor authorBhaskar, Kiran
    contributor authorRahn, Christopher D.
    date accessioned2025-04-21T10:36:12Z
    date available2025-04-21T10:36:12Z
    date copyright9/27/2024 12:00:00 AM
    date issued2024
    identifier issn2689-6117
    identifier otheraldsc_4_4_041004.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4306533
    description abstractThis paper proposes rapid and accurate short circuit estimation under resting condition using joint moving horizon estimation (MHE). The use of lithium-ion batteries (LiBs) in electric vehicles (EVs) has been increasing, leading to heightened concerns regarding the safety of LiBs. Detecting a short circuit, which is a major cause of safety incidents, is challenging when it is in its early stages. Therefore, short circuits should be detected swiftly and accurately to prevent thermal runaway and potential fires, property damage, injuries, and mortalities. During leak testing of new cells or often an EV crash, applied current may be zero and parameters unknown. The presented work addresses these challenges through the application of a joint MHE approach, to estimate both short circuit current and battery capacity. The proposed approach is evaluated through extensive simulations involving various short circuit scenarios and is compared to a joint extended Kalman filter and joint unscented Kalman filter. Experimental data are also used to validate the effectiveness of states and parameters estimation.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleShort Circuit Estimation in Lithium-Ion Batteries Using Moving Horizon Estimation1
    typeJournal Paper
    journal volume4
    journal issue4
    journal titleASME Letters in Dynamic Systems and Control
    identifier doi10.1115/1.4066515
    journal fristpage41004-1
    journal lastpage41004-5
    page5
    treeASME Letters in Dynamic Systems and Control:;2024:;volume( 004 ):;issue: 004
    contenttypeFulltext
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