A Novel Transformer Leakage Energy Recovery Active Clamp Control Technique for High Power AC/DC Flyback Converters
Bibliographic record
Abstract
A novel twin-pulse active clamp has been proposed for flyback converters that can efficiently recover the transformer leakage energy and route it to the output with reduced clamp current ratings and clamp capacitance compared to existing active clamp methods. This extends the application power range for ac/dc flyback converters by enabling a cost-effective leakage energy recovery method for high-power applications. In the case of a 2.5 kW flyback converter, the proposed clamp offers a potential reduction of the required clamp capacitance by 500x and the clamp current by more than 2x at the expense of a higher peak switch voltage stress when compared to an equivalent conventional active clamp. The operating principle and the design criteria for the proposed clamp method are discussed. Experimental results for a 2.5 kW ac/dc flyback converter prototype with the proposed clamp have been presented, validating the clamp operation. Its performance and efficiency improvement compared to a dissipative clamp with active discharge has also been evaluated over the entire operating region.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".