A Robust Inverse Approach for Magnetic Material Characterization in Electromagnetic Devices With Minimum Influence of the Air-Gap Uncertainty

The material properties characterizing the magnetic circuit of an electromagnetic device can be identified by solving an inverse problem, where sets of measurements are properly interpreted using a forward numerical model of the device. The accuracy of the recovered material characteristics is, however, drastically reduced due to the geometrical uncertainties of the magnetic circuit. Specifically, the air gap has a large impact onto the inverse solution's accuracy. This paper proposes a novel inverse approach technique, in which the propagations of the uncertainties in the model are limited. The proposed methodology adapts the traditional cost function that needs to be minimized. We applied the methodology onto the identification of the magnetizing
B
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H
curve of a switched reluctance motor core material. The numerical results show a significant reduction of the recovery errors in the identified magnetic material parameter values. Moreover, the material characteristics that were recovered by using the proposed methodology starting from real measurements are closer to the actual material characteristics.