Modelling of a large-format lithium-iron-phosphate-based lithium-ion battery cell with neural ordinary differential equations
- Lithium-ion batteries show strongly nonlinear behaviour regarding the battery current and state of charge. Therefore, the modelling of lithium-ion batteries is complex. Combining physical and data-driven models in a grey-box model can simplify the modelling. Our focus is on using neural networks, especially neural ordinary differential equations, for grey-box modelling of lithium-ion batteries. ALithium-ion batteries show strongly nonlinear behaviour regarding the battery current and state of charge. Therefore, the modelling of lithium-ion batteries is complex. Combining physical and data-driven models in a grey-box model can simplify the modelling. Our focus is on using neural networks, especially neural ordinary differential equations, for grey-box modelling of lithium-ion batteries. A simple equivalent circuit model serves as a basis for the grey-box model. Unknown parameters and dependencies are then replaced by learnable parameters and neural networks. We use experimental full-cycle data and data from pulse tests of a lithium iron phosphate cell to train the model. Finally, we test the model against two dynamic load profiles: one consisting of half cycles and one dynamic load profile representing a home-storage system. The dynamic response of the battery is well captured by the model.…
Document Type: | Conference Proceeding |
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Conference Type: | Konferenzartikel |
Zitierlink: | https://opus.hs-offenburg.de/6230 | Bibliografische Angaben |
Title (English): | Modelling of a large-format lithium-iron-phosphate-based lithium-ion battery cell with neural ordinary differential equations |
Conference: | The Upper-Rhine Artificial Intelligence Symposium (4th UR-AI Symposium), Villingen-Schwenningen, 19 October 2022 |
Author: | Jennifer BruckerStaff MemberORCiD, Wolfgang G. BesslerStaff MemberORCiDGND, Rainer GasperStaff MemberGND |
Year of Publication: | 2022 |
First Page: | 41 |
Last Page: | 50 |
Parent Title (English): | The Upper-Rhine Artificial Intelligence Symposium (UR-AI 2022) : AI Applications in Medicine and Manufacturing |
Editor: | Christoph Reich, Ulrich Mescheder |
ISBN: | 978-3-00-073638-4 (e-ISBN) |
ISSN: | 978-3-00-073637-7 (Print) |
URL: | https://www.researchgate.net/publication/364343172 |
Language: | English | Inhaltliche Informationen |
Institutes: | Forschung / INES - Institut für nachhaltige Energiesysteme |
Fakultät Maschinenbau und Verfahrenstechnik (M+V) | |
Institutes: | Bibliografie |
Tag: | equivalent circuit model; grey-box model; lithium-ion battery; neural ordinary differential equations | Formale Angaben |
Relevance: | Konferenzbeitrag: h5-Index < 30 |
Open Access: | Open Access |
Diamond | |
Licence (German): | Creative Commons - CC BY - Namensnennung 4.0 International |