A Study on the System Imbalance of the Single-Switch Converter for the Conductive Common Mode Noise Reduction(Electromagnetic Compatibility (EMC))
スポンサーリンク
概要
- 論文の詳細を見る
This paper reduces system imbalance by replacing the single-switch converter with a synchronized double-switch converter based on two active switches technique and hybrid balance technique, including active balance and passive balance for common mode noise reduction. The system balance is experimentally evaluated by the common mode rejection ratio (CMRR). Finally, examples show that the CMRR of the single-switch converter is improved from 1.67dB to 32.04dB when the double-converter with two active switches technique is applied and to 41.5dB when the double-switch converter with hybrid balance technique is applied.
- 社団法人電子情報通信学会の論文
- 2007-08-01
著者
-
PREMPRANEERACH Yothin
Faculty of Engineering, King Mongkuts Institute of Technology Ladkrabang
-
NITTA Shuichi
Salasiean Polytechnic
-
BOONPIROM Nimit
Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang
-
PAITHOONWATANAKIJ Kitti
Faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang
-
AUNCHALEEVARAPAN Kraison
Electrical and Electronic Products Testing Center (PTEC)
-
Paithoonwatanakij Kitti
Faculty Of Engineering King Mongkut's Institute Of Technology Ladkrabang
-
Boonpirom Nimit
Faculty Of Engineering King Mongkut's Institute Of Technology Ladkrabang
-
Prempraneerach Yothin
King Mongkut's Inst. Of Technol. Ladkrabang Bangkok Tha
-
Prempraneerach Yothin
Faculty Of Engineering King Mongkut's Institute Of Technology Ladkrabang
関連論文
- A Current Mode Analysis on Ground Leakage Current Noise Generation in Unbalanced and Balanced Switching Converters
- A Current Mode Analysis on Ground Leakage Current Noise Generation in Unbalanced and Balanced Switching Converters
- A Study on the System Imbalance of the Single-Switch Converter for the Conductive Common Mode Noise Reduction(Electromagnetic Compatibility (EMC))
- Novel Method for Predicting PCB Configurations for Near-Field and Far-Field Radiated EMI Using a Neural Network