Predicting Iron Losses in Laminated Steel with Given Non-Sinusoidal Waveforms of Flux Density

Wei Chen, Jien Ma, Xiaoyan Huang and Youtong Fang
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Wei Chen: College of Electrical Engineering, Zhejiang University, Hangzhou 310058, China
Jien Ma: College of Electrical Engineering, Zhejiang University, Hangzhou 310058, China
Xiaoyan Huang: College of Electrical Engineering, Zhejiang University, Hangzhou 310058, China
Youtong Fang: College of Electrical Engineering, Zhejiang University, Hangzhou 310058, China

Energies, 2015, vol. 8, issue 12, 1-15

Abstract: In electrical machines, iron losses are essential for electromagnetic and thermal designs and analyses. Although many models have been proposed to predict iron losses in magnetic materials, the calculation of iron losses under non-sinusoidal excitations is still an open field. Most works concern the influences of the value, the change rate or the frequency of flux density in the frequency domain. In this paper, we propose an engineering model for predicting loss characteristics with given waveforms of flux density in the time domain. The characteristics are collected from the knowledge of the iron loss in a laminated ring-shaped transformer. In the proposed model, we derive mathematical formulas for exciting currents in terms of flux density by describing the function methods through multi-frequency tests with sinusoidal excitations. The non-linearity of the material is interpreted by branches of conductances accounting for hysteresis and eddy-current losses. Then, iron losses are calculated based on the law of conservation of energy. An experimental system was built to evaluate the magnetic properties and iron losses under sinusoidal and non-sinusoidal excitations. Actual measurement results verify the effectiveness of the proposed model.

Keywords: iron losses; engineering model; non-sinusoidal; waveforms of flux density (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2015
References: View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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