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    A Computationally Efficient Approach for Optimizing Lithium Ion Battery Charging

    Source: Journal of Dynamic Systems, Measurement, and Control:;2016:;volume( 138 ):;issue: 002::page 21009
    Author:
    Liu, Ji
    ,
    Li, Guang
    ,
    Fathy, Hosam K.
    DOI: 10.1115/1.4032066
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This paper presents a framework for optimizing lithiumion battery charging, subject to side reaction constraints. Such healthconscious control can improve battery performance significantly, while avoiding damage phenomena, such as lithium plating. Battery trajectory optimization problems are computationally challenging because the problems are often nonlinear, nonconvex, and highorder. We address this challenge by exploiting: (i) timescale separation, (ii) orthogonal projectionbased model reformulation, (iii) the differential flatness of solidphase diffusion dynamics, and (iv) pseudospectral trajectory optimization. The above tools exist individually in the literature. For example, the literature examines battery model reformulation and the pseudospectral optimization of battery charging. However, this paper is the first to combine these four tools into a unified framework for battery management and also the first work to exploit differential flatness in battery trajectory optimization. A simulation study reveals that the proposed framework can be five times more computationally efficient than pseudospectral optimization alone.
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      A Computationally Efficient Approach for Optimizing Lithium Ion Battery Charging

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    http://yetl.yabesh.ir/yetl1/handle/yetl/160640
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    contributor authorLiu, Ji
    contributor authorLi, Guang
    contributor authorFathy, Hosam K.
    date accessioned2017-05-09T01:26:54Z
    date available2017-05-09T01:26:54Z
    date issued2016
    identifier issn0022-0434
    identifier otherds_138_02_021009.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/160640
    description abstractThis paper presents a framework for optimizing lithiumion battery charging, subject to side reaction constraints. Such healthconscious control can improve battery performance significantly, while avoiding damage phenomena, such as lithium plating. Battery trajectory optimization problems are computationally challenging because the problems are often nonlinear, nonconvex, and highorder. We address this challenge by exploiting: (i) timescale separation, (ii) orthogonal projectionbased model reformulation, (iii) the differential flatness of solidphase diffusion dynamics, and (iv) pseudospectral trajectory optimization. The above tools exist individually in the literature. For example, the literature examines battery model reformulation and the pseudospectral optimization of battery charging. However, this paper is the first to combine these four tools into a unified framework for battery management and also the first work to exploit differential flatness in battery trajectory optimization. A simulation study reveals that the proposed framework can be five times more computationally efficient than pseudospectral optimization alone.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleA Computationally Efficient Approach for Optimizing Lithium Ion Battery Charging
    typeJournal Paper
    journal volume138
    journal issue2
    journal titleJournal of Dynamic Systems, Measurement, and Control
    identifier doi10.1115/1.4032066
    journal fristpage21009
    journal lastpage21009
    identifier eissn1528-9028
    treeJournal of Dynamic Systems, Measurement, and Control:;2016:;volume( 138 ):;issue: 002
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian