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arXiv Machine Learning By Gift Modekwe, Qiugang Lu

Physics-Informed Neural Network with Transfer Learning for State Estimation in Lithium-Ion Batteries using the Single Particle Model with Electrolyte

Read the original on arXiv Machine Learning →

arXiv:2606. 28220v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving nonlinear partial differential equations (PDEs), including battery electrochemical models.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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