The critical conduction mode (CRM) power factor correction converters (PFC) are widely used in industry for low power offline switching mode power supplies. For the CRM PFC, the main advantage is to reduce turn-on loss of the main switch. However, the large inductor current ripple in CRM PFC creates huge DM EMI noise, which requires a big EMI filter. The switching frequency of the CRM PFC is variable in half line cycle which makes the EMI characteristics of the CRM PFC are not clear and have not been carefully investigated. The worst case of the EMI noise, which is the baseline to design the EMI filter, is difficult to be identified. In this paper, an approximate mathematical EMI noise model based on the investigation of the principle of the quasi-peak detection is proposed to predict the DM EMI noise of the CRM PFC. The developed prediction method is verified by measurement results and the predicted DM EMI noise is good to evaluate the EMI performance. Based on the noise prediction, the worst case analysis of the DM EMI noise in the CRM PFC is applied and the worst case can be found at some line and load condition, which will be a great help to the EMI filter design and meanwhile leave an opportunity for the optimization of the whole converter design.
What is more, the worst case analysis can be extended to 2-channel interleaved CRM PFC and some interesting characteristics can be observed. For example, the great EMI performance improvement through ripple current cancellation in traditional constant frequency PFC by using interleaving techniques will not directly apply to the CRM PFC due to its variable switching frequency. More research needs to be done to abstract some design criteria for the boost inductor and EMI filter in the interleaved CRM PFC. / Master of Science
Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/32719 |
Date | 11 June 2010 |
Creators | Wang, Zijian |
Contributors | Electrical and Computer Engineering, Lee, Fred C., Boroyevich, Dushan, Wang, Shuo |
Publisher | Virginia Tech |
Source Sets | Virginia Tech Theses and Dissertation |
Detected Language | English |
Type | Thesis |
Format | application/pdf |
Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
Relation | Wang_Z_T_2010.pdf |
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