Digitally controlled multi-phase buck-converter with merged capacitive attenuator
Bibliographic record
Abstract
This paper introduces a new topology that combines a capacitive divider and an interleaved buck to reduce the volume of multi-phase step-down converters. The size reduction is obtained with a low penalty in conduction losses, input filter size, and controller complexity. At heavy loads, the converter efficiency is comparable to that of a conventional buck and at light to medium loads it is improved. The volume reduction is obtained by utilizing the inductors of the buck stage to regulate the tap voltages of the capacitive divider. This eliminates a bulky energy transfer capacitor existing in other switch capacitor (SC) circuits, reduces the number of switches in the conduction path, and simplifies control of the converter. Experimental results obtained with a 7V-to-1V, 10A, 1 MHz prototype demonstrate that the merged capacitor converter has 15% smaller inductor, 13% reduction in output capacitor value and up to 35% reduction in power losses, and 15% faster transient response than a time-optimal controlled buck.
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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) | 0.002 | 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".