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 conferencePaperpeer-review

    9 Citations (Scopus)
    1620 Downloads (Pure)


    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
    Number of pages6
    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


    Conference12th IEEE PES PowerTech Conference
    Abbreviated titlePowerTech 2017
    Country/TerritoryUnited Kingdom
    Internet address


    • Storage
    • Predictive model
    • Smart grid
    • Energy management


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