Iron Loss Calculation of AC Filter Inductor for Three‐Phase PWM Inverters
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- Hiroaki Matsumori
- Power electronics Labs Tokyo Metropolitan University Japan
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- Toshihisa Shimizu
- Power electronics Labs Tokyo Metropolitan University Japan
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- Koushi Takano
- Iwatsu Test Instruments Corp Japan
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- Hitoshi Ishii
- Iwatsu Test Instruments Corp Japan
抄録
<jats:title>SUMMARY</jats:title><jats:p>In recent years, remarkable advancement of new power semiconductor devices, such as SiC and GaN, enables the increase of switching frequency of power converters, and hence the volume of passive components, such as ac filters and transformers, can be reduced. However, temperature rise caused by the inductor loss is increasing, and hence iron loss evaluation of the inductor is one of the most important issues to realize high power density converters. Conventionally, an improved generalized Steinmetz equation (iGSE) has proposed in order to calculate the iron loss under a pulse voltage magnetizing condition. However, accurate iron loss calculation of the ac filter inductor used in a PWM inverter cannot be realized. The authors have proposed two methods of iron loss evaluation of ac filter inductors. The first one is a loss map method which can calculate the iron loss without using a real PWM inverter. Another one is an ILA (Inductor Loss Analyzer) which can measure the iron loss in every switching period in a real PWM inverter. In this paper, comparisons of the iron loss between the ILA and the loss map method on both the single‐phase and three‐phase inverters are studied. It is found that iron loss of the ac filter inductor in the three‐phase PWM inverter which is calculated by the loss map method cause a large error on a specific condition. In order to prevent the calculation error, the authors proposed a revised loss map method and proved the effectiveness of the method.</jats:p>
収録刊行物
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- Electrical Engineering in Japan
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Electrical Engineering in Japan 190 (2), 57-71, 2014-10-13
Wiley
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詳細情報 詳細情報について
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- CRID
- 1363949023322747392
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- NII論文ID
- 210000184604
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- ISSN
- 15206416
- 04247760
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- データソース種別
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