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Information × Registration Number 0224U000304, 0124U000044 , R & D reports Title Development of physics-informed machine learning-based approaches for modelling and forecasting the state-of-health of Li-ion batteries popup.stage_title Head Druchok Maksym Yu., Кандидат фізико-математичних наук Registration Date 05-01-2024 Organization Institute of Condensed Matter Physics of the National Academy of Sciences of Ukraine popup.description2 The result of the conducted research is an implementation of a numerical approach for solving a system of equations within an electrochemical model for Li-ion batteries. The proposed approach allows for a real-time assessment of state-of-charge of batteries, as well as their state-of-health. In particular, a dependence of non-ideal component of electric voltage on the Li concentration in electrode was found, which helped reduce the number of fitting parameters of the model. The proposed solution was tested on different experimental datasets for discharge curves of 18650-type Li-ion batteries. Product Description popup.authors Demchuk Taras V. popup.nrat_date 2024-01-05 Close
R & D report
Development of physics-informed machine learning-based approaches for modelling and forecasting the state-of-health of Li-ion batteries
Head: Druchok Maksym Yu.. Development of physics-informed machine learning-based approaches for modelling and forecasting the state-of-health of Li-ion batteries. (popup.stage: ). Institute of Condensed Matter Physics of the National Academy of Sciences of Ukraine. № 0224U000304
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Updated: 2026-03-26


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