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    State of Charge and State of Health Estimation of Lithium-Ion Battery Packs With Inconsistent Internal Parameters Using Dual Extended Kalman Filter

    Source: Journal of Electrochemical Energy Conversion and Storage:;2023:;volume( 021 ):;issue: 001::page 11004-1
    Author:
    Yang, Fan
    ,
    Xu, Yuxuan
    ,
    Su, Lei
    ,
    Yang, Zhichun
    ,
    Feng, Yu
    ,
    Zhang, Cheng
    ,
    Shao, Tao
    DOI: 10.1115/1.4062319
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The internal battery parameters of the lithium-ion battery energy storage system may be inconsistent due to different aging degrees during the operation, and the thermal effect can also threaten the safety of the system. In this paper, based on the second-order resistor–capacitor equivalent circuit model and the dual extended Kalman filter (DEKF) algorithm, an electrical simulation model of a LIB pack with inconsistent parameters considering the thermal effect is established, in which state of charge (SOC) and state of health (SOH) are estimated using DEKF, while the temperature is calculated by a thermal module. The simulation results show that the DEKF algorithm has a good effect on battery state and parameter estimation, with the root-mean-square error of voltage is lower than 0.01 V and SOC mean absolute error (MAE) is below 1.50%, while SOH error is 3.37%. In addition, the thermal module can provide an accurate estimation of the inconsistent temperature rise of the battery pack, and the MAE between the model-calculated temperature and the experiment is no more than 6.60%. The results provide the basic data for the scale-up of the electrothermal co-simulation model of the LIB energy storage system.
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      State of Charge and State of Health Estimation of Lithium-Ion Battery Packs With Inconsistent Internal Parameters Using Dual Extended Kalman Filter

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4292074
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    • Journal of Electrochemical Energy Conversion and Storage

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    contributor authorYang, Fan
    contributor authorXu, Yuxuan
    contributor authorSu, Lei
    contributor authorYang, Zhichun
    contributor authorFeng, Yu
    contributor authorZhang, Cheng
    contributor authorShao, Tao
    date accessioned2023-08-16T18:31:00Z
    date available2023-08-16T18:31:00Z
    date copyright4/27/2023 12:00:00 AM
    date issued2023
    identifier issn2381-6872
    identifier otherjeecs_21_1_011004.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4292074
    description abstractThe internal battery parameters of the lithium-ion battery energy storage system may be inconsistent due to different aging degrees during the operation, and the thermal effect can also threaten the safety of the system. In this paper, based on the second-order resistor–capacitor equivalent circuit model and the dual extended Kalman filter (DEKF) algorithm, an electrical simulation model of a LIB pack with inconsistent parameters considering the thermal effect is established, in which state of charge (SOC) and state of health (SOH) are estimated using DEKF, while the temperature is calculated by a thermal module. The simulation results show that the DEKF algorithm has a good effect on battery state and parameter estimation, with the root-mean-square error of voltage is lower than 0.01 V and SOC mean absolute error (MAE) is below 1.50%, while SOH error is 3.37%. In addition, the thermal module can provide an accurate estimation of the inconsistent temperature rise of the battery pack, and the MAE between the model-calculated temperature and the experiment is no more than 6.60%. The results provide the basic data for the scale-up of the electrothermal co-simulation model of the LIB energy storage system.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleState of Charge and State of Health Estimation of Lithium-Ion Battery Packs With Inconsistent Internal Parameters Using Dual Extended Kalman Filter
    typeJournal Paper
    journal volume21
    journal issue1
    journal titleJournal of Electrochemical Energy Conversion and Storage
    identifier doi10.1115/1.4062319
    journal fristpage11004-1
    journal lastpage11004-10
    page10
    treeJournal of Electrochemical Energy Conversion and Storage:;2023:;volume( 021 ):;issue: 001
    contenttypeFulltext
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