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• W2781908066 abstract "The performance of electrical machines is highly dependent on the temperature. Overheating for instance leads to failure of the machine. Heating of the critical components sets a limit to the maximum allowed power and torque density. Having a high fidelity thermal model is essential for safe operation safeguarding maximum efficiency. This paper shows how the thermal models, based on the finite element method, of an electric machine can be improved using inverse modeling techniques. We studied in depth an axial permanent magnet motor and improved the thermal model using inverse modeling techniques via non-collocated thermal sensors. Model order reduction enabled the significant reduction of the computational effort that is required to recover the actual thermal parameters characterizing the thermal properties of an electric machine. These techniques were as well employed for determining the power losses and the air gap convection within the axial flux permanent magnet motor. The results of the developed techniques show that the material properties can deviate from the theoretical ones, and that in this way the material imperfections can be revealed." @default.
• W2781908066 created "2018-01-12" @default.
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• W2781908066 date "2017-10-01" @default.
• W2781908066 modified "2023-09-26" @default.
• W2781908066 title "Thermal parameter identification of an electrical machine using inverse modelling and non-collocated thermal sensors" @default.
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• W2781908066 doi "https://doi.org/10.1109/icsens.2017.8234194" @default.
• W2781908066 hasPublicationYear "2017" @default.
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