Abstract

Despite the use of state-of-the-art thermal modeling tools in the design stage, the measured thermal behavior of prototype electrical machines can differ significantly from the modeled ones. This paper shows how a thermal model, based on the finite-element method, of an electric machine can be improved using inverse modeling techniques. In a thorough study, a forward high fidelity finite-element thermal model of a 4-kW axial flux permanent magnet (PM) machine is introduced and improved using inverse modeling techniques via noncollocated thermal sensors. Parametric model order reduction of the high fidelity finite-element thermal model based on the moment matching method is performed to make the recovery of the actual thermal parameters characterizing the thermal behavior of the axial flux PM machine tractable. Furthermore, the same reduced order model is used to identify the different power loss components in the machine. Experimental results confirm that the presented two-stage approach is capable of identifying the thermal parameters and losses with high accuracy.

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