Common-Mode Noise Reduction in Full-Bridge LLC Resonant Converter with Split Primary Winding Transformer
Bibliographic record
Abstract
This paper addresses the issue of common-mode (CM) conducted electromagnetic interference (EMI) noise in full-bridge (FB) LLC resonant converters. In conventional FB LLC resonant converters, the position of the resonant tank can affect the symmetry of the entire circuit, leading to different dv/dt values at the two winding terminals of the transformer. This results in non-cancelable displacement currents generated in the parasitic interwinding capacitance of the transformer, leading to severe CM noise issues. In this paper, a low CM noise FB LLC resonant converter with the Split Primary Winding Transformer (SPWT) configuration is proposed. The transformer primary winding is split into two windings and the resonant tank is connected between these two windings. With a symmetrical winding structure, the CM noise current generated in the transformer can be canceled completely. The concept of complementary couple-turns is proposed to ensure a symmetrical winding arrangement for the planar transformer in the printed circuit board (PCB) layout stage before it is fabricated physically. A 360 W FB LLC prototype with a planar transformer is built to verify the feasibility and validity of the proposed methods. The CM noise is reduced by around 11 dBμV (a reduction of around 4 times) below 5 MHz.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".