Hybrid-Timescale Physics-Informed Neural Network for Electrical Equivalent Impedance Identification in Induction Heating Systems

This article introduces a hybrid variant of a physics-informed neural network (PINN) that is designed to effectively capture both the rapid dynamics of electrical variables and the slower dynamics of state parameters in a domestic induction heating system. By utilizing observable variables, specific...

Ausführliche Beschreibung

Bibliografische Detailangaben

Hauptverfasser:	Oscar Lahuerta, Claudio Carretero, Luis Angel Barragan, Denis Navarro, Jesus Acero
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	IEEE 2026-01-01
Schriftenreihe:	IEEE Open Journal of the Industrial Electronics Society
Schlagworte:	Home appliances induction heating (IH) physics-informed machine learning system identification
Online-Zugang:	https://ieeexplore.ieee.org/document/11393584/
Tags:	Tag hinzufügen Keine Tags, Fügen Sie das erste Tag hinzu!