Adaptive Current Source Drivers for Efficiency Optimization of High-Frequency Synchronous Buck Converters
Bibliographic record
Abstract
In this paper, the concept of the adaptive current source drivers (CSDs) is proposed for the high-frequency synchronous buck converters. Compared to the previous CSD circuits, the adaptive CSD can achieve adjustable drive current and drive voltage according to different load condition. The benefit is that higher drive current and voltage lead to lower switching loss and conduction loss when the load current increases. Therefore, the adaptive CSD is able to realize optimal design to reduce the switching loss, the gate drive loss, and the conduction loss in a wide load range. It should be noted that the adaptive concept is suitable for both the continuous and discontinuous CSDs regardless the drive circuit topologies. Through investigating the CSD circuits, one simple method to achieve the adaptive drive current based on the adaptive voltage is proposed. A 12 V input, 1.3 V output, and 1-MHz synchronous buck converter with the continuous and discontinuous CSDs was built, respectively, to verify the advantages of the proposed adaptive concept and efficiency improvement.
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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".