Inferring electrochemical performance and parameters of Li-ion batteries based on deep operator networks

6 May 2022

Papers citing "Inferring electrochemical performance and parameters of Li-ion batteries based on deep operator networks"

4 / 4 papers shown

Title
On-site estimation of battery electrochemical parameters via transfer learning based physics-informed neural network approach Josu Yeregui Iker Lopetegi Sergio Fernandez Erik Garayalde Unai Iraola 32 0 0 28 Mar 2025
PINN surrogate of Li-ion battery models for parameter inference. Part II: Regularization and application of the pseudo-2D model M. Hassanaly Peter J. Weddle Ryan N. King Subhayan De Alireza Doostan Corey R. Randall Eric J. Dufek Andrew M. Colclasure Kandler Smith 25 6 0 28 Dec 2023
PINN surrogate of Li-ion battery models for parameter inference. Part I: Implementation and multi-fidelity hierarchies for the single-particle model M. Hassanaly Peter J. Weddle Ryan N. King Subhayan De Alireza Doostan Corey R. Randall Eric J. Dufek Andrew M. Colclasure Kandler Smith 26 7 0 28 Dec 2023
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 256 2,298 0 18 Oct 2020