Optimum Identification of Iron Loss Models in NGO Electrical Steel for Power Electronics | IEEE Conference Publication | IEEE Xplore

Optimum Identification of Iron Loss Models in NGO Electrical Steel for Power Electronics


Abstract:

Prediction and modelling of the dynamic power losses, and their decomposition into the hysteresis and eddy current contributions, in laminated ferromagnetic materials is ...Show More

Abstract:

Prediction and modelling of the dynamic power losses, and their decomposition into the hysteresis and eddy current contributions, in laminated ferromagnetic materials is not a comprehensively solved problem. This paper mostly deals with the experimental identification of Preisach-type models, aiming at an accurate and effective reproduction of the hysteresis losses. Different probability density functions are examined to approximate the distribution of the hysteresis operators. The distribution parameters are identified exploiting both a genetic algorithm, suitably developed, and the patternsearch approach. The comparison of the results obtained for a NGO electrical steel, particularly appropriate in power electronics applications, seemed to indicate a single Lorentzian function as the best-fit hysteron distribution. The hysteresis losses evaluated by the Preisach model turned out to be effective also when the material is excited by non sinusoidal polarization waveforms.
Date of Conference: 09-12 September 2019
Date Added to IEEE Xplore: 11 November 2019
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Conference Location: Florence, Italy

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