2019 21st European Conference on Power Electronics and Applications (EPE '19 ECCE Europe) 2019
DOI: 10.23919/epe.2019.8915174
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Validation of Inductor Analytical Loss Models under Saturation Conditions for PWM inverter

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Cited by 4 publications
(4 citation statements)
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“…It is evaluate both losses models and a global thermal model. For core losses, IGSE [20] was u winding AC and DC losses, the simple formula from [21] was chosen, even if method could have been used as in [22]. Knowing the losses, the inductor geom material data, a 2D thermal model [23,24] (Figure 9) helps to obtain the inductor h temperature, which has to stay below a certain limit.…”
Section: Phase Inductor Constraints Evaluationmentioning
confidence: 99%
“…It is evaluate both losses models and a global thermal model. For core losses, IGSE [20] was u winding AC and DC losses, the simple formula from [21] was chosen, even if method could have been used as in [22]. Knowing the losses, the inductor geom material data, a 2D thermal model [23,24] (Figure 9) helps to obtain the inductor h temperature, which has to stay below a certain limit.…”
Section: Phase Inductor Constraints Evaluationmentioning
confidence: 99%
“…For example, the inductor can saturate during the peak current over a low frequency period, leading to an increased ripple, but with a smaller core area, thus reduced mass. The complete method is given in [20], and consists in computing the magnetic flux ripple with Lenz law and the B(H) curve of the material. The time-domain variation of flux is then used to compute iron losses with improved Steinmetz equation (iGSE) [21].…”
Section: Passive Component Designmentioning
confidence: 99%
“…The time-domain variation of flux is then used to compute iron losses with improved Steinmetz equation (iGSE) [21]. Equation ( 5) is an analytical version of iGSE described in [20] using the switching time of the PWM scheme 𝑡 𝑜𝑓𝑓 and 𝑡 𝑜𝑛 function of j the discretization index from 0 to m. These calculations make it possible to compute also copper losses, and some spectral analysis elements described previously.…”
Section: Passive Component Designmentioning
confidence: 99%
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