Magnetic Field Conforming Formulations for Foil Windings
Louis Denis, Elias Paakkunainen, Paavo Rasilo, Sebastian Schöps, Benoît Vanderheyden, Christophe Geuzaine
TL;DR
This work extends foil-winding homogenization to magnetic field conforming formulations for both frequency- and time-domain FE analyses. It introduces full-$h$ and $h$-$\phi$ magnetic field conforming formulations, with the latter leveraging a magnetic scalar potential in non-conducting regions and a single global cut to enforce current conservation, complemented by an alternative $t$-$\omega$ discretization that uses isotropic resistivity. The proposed methods reproduce results from established $a$-$v$ FW and resolved models while dramatically reducing the number of degrees of freedom, achieving up to about $75\%$ DoF reduction in 3-D problems, and they are validated on 2-D axisymmetric and 3-D benchmark problems, as well as a nonlinear transient HTS coil scenario. This approach enables efficient, accurate modeling of large-scale foil-winding inductors and HTS coils using open-source FE tools, with demonstrated robustness across linear and nonlinear regimes.
Abstract
We extend the foil winding homogenization method to magnetic field conforming formulations. We first propose a full magnetic field foil winding formulation by analogy with magnetic flux density conforming formulations. We then introduce the magnetic scalar potential in non-conducting regions to improve the efficiency of the model. This leads to a significant reduction in the number of degrees of freedom, particularly in 3-D applications. The proposed models are verified on two frequency-domain benchmark problems: a 2-D axisymmetric problem and a 3-D problem. They reproduce results obtained with magnetic flux density conforming formulations and with resolved conductor models that explicitly discretize all turns. Moreover, the models are applied in the transient simulation of a high-temperature superconducting coil. In all investigated configurations, the proposed models provide reliable results while considerably reducing the size of the numerical problem to be solved.
