Prediction of Energy Losses in Soft Magnetic Materials Under Arbitrary Induction Waveforms and DC Bias
| Autor: | Fausto Fiorillo, Carlo Appino, Olivier de la Barriere, Carlo Stefano Ragusa |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
010302 applied physics
Engineering business.industry 020208 electrical & electronic engineering Experimental data Magnetic hysteresis magnetic loss magnetic materials 02 engineering and technology Magnetic hysteresis 01 natural sciences Magnetic flux magnetic loss Hysteresis Control and Systems Engineering Control theory 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Electronic engineering Waveform magnetic materials Electrical and Electronic Engineering Statistical theory business Energy (signal processing) DC bias |
| Popis: | The statistical theory of losses (STL) provides a simple and general method for the interpretation and prediction of the energy losses in soft magnetic materials. One basic application consists, for example, in the prediction of the loss under arbitrary induction waveform, starting from data available from conventional measurements performed under sinusoidal flux. There are, however, persisting difficulties in assessing the loss when the induction waveform is affected by a dc bias, because this would require additional experimental data, seldom available to machine designers. In this paper, we overcome this problem applying, with suitable simplifications, the dynamic Preisach model. Here, the parameters of the STL model are obtained exploiting preemptive conventional measurements only. By this new simplified method, analytical expressions for the loss components are obtained under general supply conditions, including dc-biased induction waveforms. |
| Databáze: | OpenAIRE |
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