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Physics Informed Neural Network and RC model of Li-Ion Battery

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F22%3APU146089" target="_blank" >RIV/00216305:26220/22:PU146089 - isvavai.cz</a>

  • Result on the web

    <a href="https://aba-brno.cz/download/2022-ABAF-Proceeding.pdf" target="_blank" >https://aba-brno.cz/download/2022-ABAF-Proceeding.pdf</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Physics Informed Neural Network and RC model of Li-Ion Battery

  • Original language description

    This paper deals with simulation of Li-ion battery in the form of an equivalent RC circuit. Physics informed Neural network is used for time-dependent simulations. The article deals with the problems associated with this kind of simulation.

  • Czech name

  • Czech description

Classification

  • Type

    O - Miscellaneous

  • CEP classification

  • OECD FORD branch

    20201 - Electrical and electronic engineering

Result continuities

  • Project

    <a href="/en/project/ED0014%2F01%2F01" target="_blank" >ED0014/01/01: Research and Technology Centre of Renewable Energy Sources</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů