Chayratsami, Pornpimon

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Chayratsami, Pornpimon
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Chayratsami, Pompimon
Chayratsami, Potnpimon
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pornpimon.ch@kmitl.ac.th

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    Hysteresis modeling of lithium-silicon half cells using discrete preisach model
    (2019-04-08)
    Chayratsami, Potnpimon
    ;
    Plett, Gregory L.
    Battery-cell hysteresis has crucial impact to battery-management system (BMS) performance. Improved hysteresis modeling accuracy can improve state-of-charge (SOC) estimation. This paper proposed using a linear least-squares method to identify a Preisach weight function and using the discrete Preisach model to estimate hysteresis for a Li//Si half cell. We found that the discrete Preisach model gives acceptable hysteresis-error estimates within 5% with resonable levels of discretization of 50.
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    Hysteresis Modeling of Lithium-Silicon Half Cells Using Extended Preisach Model
    (2018-12-18)
    Chayratsami, Pompimon
    ;
    Plett, Gregory L.
    Battery-cell voltage hysteresis is a phenomenon that impacts battery-management system (BMS) performance. It is important to model this hysteresis accurately to improve state-of-charge (SOC) estimation. This paper proposed using the extended Preisach model to estimate hysteresis for a lithium-silicon half cell. We find that the extended Preisach model, which can be found directly from a set of measured data, gives acceptable hysteresis-error estimates with simple calculation.
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    Hysteresis Modeling of Lithium-Silicon Half Cells Using Krasnosel'skii-Pokrovskii Model
    (2019-08-01)
    Chayratsami, Pornpimon
    ;
    Plett, Gregory L.
    Unmodeled battery-cell voltage hysteresis can cause state-of-charge (SOC) estimation error in a battery-management system (BMS) of an EV system. To improve BMS performance, hysteresis voltage must be modeled correctly. This paper presents the use of linear least-squares identification of a Krasnosel'skii-Pokrovskii (KP) model to estimate hysteresis for a Li//Si half cell. We find that the KP model provides good estimates and has lower root-mean-squared estimation error than a classical discrete Preisach model with the same degree of discretization.
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    Hysteresis Modeling of Lithium-Silicon Half Cells Using Prandtl-Ishlinskii Model
    (2020-10-09)
    Chayratsami, Pornpimon
    ;
    Plett, Gregory L.
    State-of-charge (SOC)-estimation accuracy is critical to battery management in electric-vehicle (EV) applications. SOC-estimation error can arise from unmodeled nonlinear battery hysteresis; so to enhance performance, it is necessary to model hysteresis voltage. This paper presents results from applying three kinds of Prandtl-Ishlinskii (PI) model to a Li//Si half cell: classical PI (CPI), generalized PI (GPI), and modified generalized PI (mGPI). The performance comparison among these models and also comparisons to the Preisach and Krasnosel'skii-Pokrovskii (KP) models are made. It is found that the mGPI provides best performance among all models having the same level of calculation.