Physics-Informed Neural Networks for State of Health Estimation in Lithium-Ion Batteries

One of the most challenging tasks of modern battery management systems is the accurate state of health estimation. While physico-chemical models are accurate, they have high computational cost. Neural networks lack physical interpretability but are efficient. Physics-informed neural networks tackle...

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Veröffentlicht in:	Journal of the Electrochemical Society 2023-09, Vol.170 (9), p.90524
Hauptverfasser:	Hofmann, Tobias, Hamar, Jacob, Rogge, Marcel, Zoerr, Christoph, Erhard, Simon, Philipp Schmidt, Jan
Format:	Artikel
Sprache:	eng
Schlagworte:	Batteries—Li-ion Machine Learning P2D Model Physics-Informed Neural Network State-of-Health Estimation Theory and Modelling
Online-Zugang:	Volltext
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