Physics-Informed Neural Networks for State and Parameter Estimation of Li-Ion Batteries
Combining machine learning with physics is a trending approach for discovering unknown dynamics, and one of the most intensively studied frameworks is the physics-informed neural network (PINN). However, PINN often fails to optimize the network due to its difficulty in concurrently minimizing multip...
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| Veröffentlicht in: | Meeting abstracts (Electrochemical Society) 2024-11, Vol.MA2024-02 (10), p.4956-4956 |
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| Format: | Artikel |
| Sprache: | eng |
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