LLC synchronous rectification using homopolarity cycle modulation
Bibliographic record
Abstract
In order to enhance the efficiency of LLC resonant converters, a new synchronous rectification modulation technique, called homopolarity cycle modulation, is proposed. The proposed modulation technique answers the main challenge in synchronizing the LLC converter's rectifier, which is detecting the conduction angle. By observing the polarities of the inverter voltage and secondary voltage of the transformer and mapping them in the homopolarity plane, the conduction angle of the synchronous rectifiers (SRs) is obtained. The homopolarity cycle is defined and used in the LLC converter's time domain equations to mathematically calculate the gain and the SRs' conduction angle. The theoretical analyses have resulted in a very simple control law with low-cost implementation requirements. Since the amplitudes of the signals used in the proposed control law are not important, the modulation technique's noise immunity is considerable. The maximum efficiency of the LLC converter using the proposed homopolarity cycle modulation technique is measured as 97.9%, which is 4% higher than the efficiency rate of a conventional LLC converter.
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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 | 0.000 | 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".