A comprehensive model for battery State of Charge prediction

Bart Homan, Gerardus Johannes Maria Smit, Richard Pieter van Leeuwen, Marnix Ten Kortenaar (Contributor)

    Research output: Contribution to conferencePaper

    3 Citations (Scopus)
    471 Downloads (Pure)

    Abstract

    In this paper the relatively simple model for State of Charge prediction, based on energy conservation, introduced in [1] is improved and verified. The model as introduced in [1] is verified for Pb-acid, Li-ion and Seasalt batteries. The model is further improved to accommodate the rate capacity effect and the capacity recovery effect, the improvements are verified with lead-acid batteries. For further verification the model is applied on a realistic situation and compared to measurements on the behavior of a real battery in that situation. Furthermore the results are compared to results of the well-established KiBaM model. Predictions on the SoC over time done using the proposed model closely follow the SoC over time calculated from measured data.
    The resulting improved model is both simple and effective, making it specially useful as part of smart control, and energy usage simulations.
    Original languageEnglish
    Pages1-6
    Number of pages6
    DOIs
    Publication statusPublished - 20 Jul 2017
    Event12th IEEE PES PowerTech Conference: Towards and Beyond Sustainable Energy Systems - University of Manchester, Manchester, United Kingdom
    Duration: 18 Jun 201722 Jul 2017
    Conference number: 12
    http://ieee-powertech.org/

    Conference

    Conference12th IEEE PES PowerTech Conference
    Abbreviated titlePowerTech 2017
    CountryUnited Kingdom
    CityManchester
    Period18/06/1722/07/17
    Internet address

    Fingerprint

    Lead acid batteries
    Energy conservation
    Recovery
    Acids
    Ions
    System-on-chip

    Keywords

    • Storage
    • Predictive model
    • Smart grid
    • Energy management

    Cite this

    Homan, B., Smit, G. J. M., van Leeuwen, R. P., & Ten Kortenaar, M. (2017). A comprehensive model for battery State of Charge prediction. 1-6. Paper presented at 12th IEEE PES PowerTech Conference, Manchester, United Kingdom. https://doi.org/10.1109/PTC.2017.7980943
    Homan, Bart ; Smit, Gerardus Johannes Maria ; van Leeuwen, Richard Pieter ; Ten Kortenaar, Marnix. / A comprehensive model for battery State of Charge prediction. Paper presented at 12th IEEE PES PowerTech Conference, Manchester, United Kingdom.6 p.
    @conference{a892077300d9493d8356557e2452a603,
    title = "A comprehensive model for battery State of Charge prediction",
    abstract = "In this paper the relatively simple model for State of Charge prediction, based on energy conservation, introduced in [1] is improved and verified. The model as introduced in [1] is verified for Pb-acid, Li-ion and Seasalt batteries. The model is further improved to accommodate the rate capacity effect and the capacity recovery effect, the improvements are verified with lead-acid batteries. For further verification the model is applied on a realistic situation and compared to measurements on the behavior of a real battery in that situation. Furthermore the results are compared to results of the well-established KiBaM model. Predictions on the SoC over time done using the proposed model closely follow the SoC over time calculated from measured data.The resulting improved model is both simple and effective, making it specially useful as part of smart control, and energy usage simulations.",
    keywords = "Storage, Predictive model, Smart grid, Energy management",
    author = "Bart Homan and Smit, {Gerardus Johannes Maria} and {van Leeuwen}, {Richard Pieter} and {Ten Kortenaar}, Marnix",
    year = "2017",
    month = "7",
    day = "20",
    doi = "10.1109/PTC.2017.7980943",
    language = "English",
    pages = "1--6",
    note = "12th IEEE PES PowerTech Conference : Towards and Beyond Sustainable Energy Systems, PowerTech 2017 ; Conference date: 18-06-2017 Through 22-07-2017",
    url = "http://ieee-powertech.org/",

    }

    Homan, B, Smit, GJM, van Leeuwen, RP & Ten Kortenaar, M 2017, 'A comprehensive model for battery State of Charge prediction' Paper presented at 12th IEEE PES PowerTech Conference, Manchester, United Kingdom, 18/06/17 - 22/07/17, pp. 1-6. https://doi.org/10.1109/PTC.2017.7980943

    A comprehensive model for battery State of Charge prediction. / Homan, Bart ; Smit, Gerardus Johannes Maria; van Leeuwen, Richard Pieter; Ten Kortenaar, Marnix (Contributor).

    2017. 1-6 Paper presented at 12th IEEE PES PowerTech Conference, Manchester, United Kingdom.

    Research output: Contribution to conferencePaper

    TY - CONF

    T1 - A comprehensive model for battery State of Charge prediction

    AU - Homan, Bart

    AU - Smit, Gerardus Johannes Maria

    AU - van Leeuwen, Richard Pieter

    A2 - Ten Kortenaar, Marnix

    PY - 2017/7/20

    Y1 - 2017/7/20

    N2 - In this paper the relatively simple model for State of Charge prediction, based on energy conservation, introduced in [1] is improved and verified. The model as introduced in [1] is verified for Pb-acid, Li-ion and Seasalt batteries. The model is further improved to accommodate the rate capacity effect and the capacity recovery effect, the improvements are verified with lead-acid batteries. For further verification the model is applied on a realistic situation and compared to measurements on the behavior of a real battery in that situation. Furthermore the results are compared to results of the well-established KiBaM model. Predictions on the SoC over time done using the proposed model closely follow the SoC over time calculated from measured data.The resulting improved model is both simple and effective, making it specially useful as part of smart control, and energy usage simulations.

    AB - In this paper the relatively simple model for State of Charge prediction, based on energy conservation, introduced in [1] is improved and verified. The model as introduced in [1] is verified for Pb-acid, Li-ion and Seasalt batteries. The model is further improved to accommodate the rate capacity effect and the capacity recovery effect, the improvements are verified with lead-acid batteries. For further verification the model is applied on a realistic situation and compared to measurements on the behavior of a real battery in that situation. Furthermore the results are compared to results of the well-established KiBaM model. Predictions on the SoC over time done using the proposed model closely follow the SoC over time calculated from measured data.The resulting improved model is both simple and effective, making it specially useful as part of smart control, and energy usage simulations.

    KW - Storage

    KW - Predictive model

    KW - Smart grid

    KW - Energy management

    U2 - 10.1109/PTC.2017.7980943

    DO - 10.1109/PTC.2017.7980943

    M3 - Paper

    SP - 1

    EP - 6

    ER -

    Homan B, Smit GJM, van Leeuwen RP, Ten Kortenaar M. A comprehensive model for battery State of Charge prediction. 2017. Paper presented at 12th IEEE PES PowerTech Conference, Manchester, United Kingdom. https://doi.org/10.1109/PTC.2017.7980943