Digitally Controlled Low-Power DC-DC Converter with Instantaneous On-Line Efficiency Optimization
Bibliographic record
Abstract
This paper introduces a digital controller and a segmented power stage that dynamically change mode of operation to maximize power processing efficiency when highly dynamic loads are supplied. The controller operates as a mixed-signal peak current program mode voltage regulator, where a digital current reference is created and used for the efficiency optimization. The losses of the power stage are minimized by combining power stage segmentation and gate swing variation. Based on the current reference, in each switching cycle, the optimal number of power switch segments and gate drive voltages are set through a sequence controller and a novel dual-output switch-capacitor circuit. The effectiveness of the system is verified on a 1.8 V, 5 W, 1 MHz buck converter prototype. The results show that the on-line optimization raises and flattens the efficiency curve and that, for dynamic loads, improves energy utilization by up to 20%.
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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 | 0.000 |
| 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".