A Simplified Time-Domain Model-Based Maximum Efficiency Tracking-Aided Synchronous Rectification Strategy for <i>CLLC</i> Chargers
Bibliographic record
Abstract
Synchronous rectification (SR), achieved by replacing secondary-side diodes with active <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">mosfet</small> channels, is crucial for reducing conduction losses in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">CLLC</i> converters. Traditional SR methods, however, either entail costly and bulky hardware or rely on complex mathematical models. This article introduces a simplified time-domain model (STDM) that utilizes mathematical principles and detailed operational assumptions to provide initial duty cycles and gate signal phases for SR under various frequencies and load conditions. However, the STDM's overall accuracy is compromised by parasitic parameters and parameter tolerance of the resonant tank. Directly employing the STDM-based SR method may lead to hard-switching of <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">mosfet</small>s or increased circulating current, reducing system efficiency. To mitigate this issue, a maximum efficiency tracking (MET)-aided SR signal adjustment method is proposed, which further modifies the duty cycle and phase shift to minimize the current passing through the diodes. This STDM-MET-SR approach does not necessitate high-bandwidth sensors or complex control algorithms while offering immunity to parasitic parameters and system parameter variations. Experimental results demonstrate that the STDM-MET generated SR signals contain negligible errors compared to the required SR signals, and the efficiency of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">CLLC</i> converter with STDM-MET-SR implemented is significantly improved compared to those of diode rectification. Overall, the proposed STDM-MET-SR approach offers a cost-effective and efficient solution to reduce conduction losses in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">CLLC</i> converters.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".