87 citations · 89 across the 3 of their papers we have counts for
4 papers
A Data-Driven, Gain-Scheduled Equivalent Circuit for the B-H Behavior of Power Ferrites
Wilhelm Kirchgässner
An equivalent circuit for the dynamic B-H behavior of power ferrites is identified from measured transients. It consists of classical elements of hysteresis modeling: a nonlinear i…
RHINO-MAG: Recursive H-Field Inference based on Observed Magnetic Flux Density under Dynamic Excitation
Hendrik Vater, Oliver Schweins, Lukas Hölsch +3
Driven by the MagNet Challenge 2025 (MC2), increased research interest is directed towards modeling transient magnetic fields within ferrite materials. An accurate time-resolved an…
HARDCORE: H-field and power loss estimation for arbitrary waveforms with residual, dilated convolutional neural networks in ferrite cores
Wilhelm Kirchgässner, Nikolas Förster, Till Piepenbrock +2
The MagNet Challenge 2023 calls upon competitors to develop data-driven models for the material-specific, waveform-agnostic estimation of steady-state power losses in toroidal ferr…
Thermal Neural Networks: Lumped-Parameter Thermal Modeling With State-Space Machine Learning
Wilhelm Kirchgässner, Oliver Wallscheid, Joachim Böcker
With electric power systems becoming more compact and increasingly powerful, the relevance of thermal stress especially during overload operation is expected to increase ceaselessl…