3 papers
physics.data-an2026
Neural posterior estimation for scalable and accurate inverse parameter inference in Li-ion batteries
Malik Hassanaly, Corey R. Randall, Peter J. Weddle +4
Diagnosing the internal state of Li-ion batteries is critical for battery research, operation of real-world systems, and prognostic evaluation of remaining lifetime. By using physi…
cs.LG2023
PINN surrogate of Li-ion battery models for parameter inference. Part II: Regularization and application of the pseudo-2D model
Malik Hassanaly, Peter J. Weddle, Ryan N. King +6
Bayesian parameter inference is useful to improve Li-ion battery diagnostics and can help formulate battery aging models. However, it is computationally intensive and cannot be eas…
cs.LG2023
PINN surrogate of Li-ion battery models for parameter inference. Part I: Implementation and multi-fidelity hierarchies for the single-particle model
Malik Hassanaly, Peter J. Weddle, Ryan N. King +6
To plan and optimize energy storage demands that account for Li-ion battery aging dynamics, techniques need to be developed to diagnose battery internal states accurately and rapid…