2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551)
DOI: 10.1109/pesc.2004.1355351
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A conducted EMI model for an industrial power supply full bridge

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Cited by 9 publications
(6 citation statements)
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“…Without the noise source impedances, the important EMI noise characteristics will be missing. Some of the previous researches also showed that the inaccurate modeling of device module parasitics would result in prediction errors in high frequency range ( 5 MHz) [13]. Note also that in Figs.…”
Section: Discussionmentioning
confidence: 83%
“…Without the noise source impedances, the important EMI noise characteristics will be missing. Some of the previous researches also showed that the inaccurate modeling of device module parasitics would result in prediction errors in high frequency range ( 5 MHz) [13]. Note also that in Figs.…”
Section: Discussionmentioning
confidence: 83%
“…With this in mind many efforts have been made to model and characterize (EMI) noise emissions of a particular device or system in power electronics [1,. However, there is still no definitive way for a unified approach of The modeling of EMI can generally be broken down into two categories: detailed, physics based modeling [21][22][23][24][25][26][27][28][29][30] and behavioral modeling [31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47][48][49]. Either method can be used to model the EMI propagation path or the noise source.…”
Section: Literature Reviewmentioning
confidence: 99%
“…When the noise impedance is the focus of a particular work an idealized noise source is used [39,[45][46][47][48]. This is usually of the form of a pulsed voltage source that mimics the switched voltage across a switch.…”
Section: Behavioral (Terminal) Modeling Approachmentioning
confidence: 99%
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“…The output stage is an inverter in series with a transformer and a rectifier. The full system was supplied through a compliant LISN that was also considered in the EMI modeling [2] [3]. In Figure 1 we also show the filtering components before the optimization.…”
Section: Introductionmentioning
confidence: 99%