The purpose of this paper is to present modelling of power losses dependences on temperature in soft magnetic materials exposed to non-sinusoidal flux waveforms and DC bias condition.
Scaling theory allows the power loss density to be derived in the form of a general homogeneous function, which depends on the peak-to-peak of the magnetic inductance ΔB, frequency f, DC bias HDC and temperature T. The form of this function has been generated through the Maclaurin expansion with respect to scaled frequency, which suit very much for the Bertotti decomposition. The parameters of the model consist of expansion coefficients, scaling exponents, parameters of DC bias mapping, parameters of temperature factor and tuning exponents. Values of these model parameters were estimated on the basis of measured data of total power density losses.
The main finding of the paper is a unified methodology for the derivation of a mathematical model which satisfactorily describes the total power density losses versus ΔB, f, HDC, and T in soft magnetic devices.
Still the derived method does not describe dependences of the power density loss on shape and size of considered sample.
The most important achievement is of the practical use. The paper is useful for device designers.
This paper presents the algorithm which enables us to calculate core losses while the temperature is changing. Moreover, this method is effective regardless of soft magnetic material type and the flux waveforms as well as the DC bias condition. The application of scaling theory in the description of energy losses in soft magnetic materials justifies that soft magnetic materials are scaling invariant systems.
Ruszczyk, A. and Sokalski, K. (2015), "Unified model of temperature dependence of core losses in soft magnetic materials exposed to non-sinusoidal flux waveforms and DC bias condition", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 34 No. 1, pp. 371-379. https://doi.org/10.1108/COMPEL-11-2013-0407
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