Efficiency enhancement and EMI suppression via dynamically adjustable gate driving strength
Bibliographic record
Abstract
In this paper, a gate driver IC with dynamically adjustable driving strength is introduced with the goal of improving light load efficiency and conducted electromagnetic interference (CEMI). By continuously adapting the gate driving strength to the output current load of the converter, it is possible to minimize the combined effects of the gate drive loss and the converters switching loss. Furthermore, by dynamically adjusting the gate driving strength (and subsequently the output resistance, Rout) at the arrival of each gate pulse, a reduction in conducted EMI can be realized with little degradation in converter efficiency. A segmented gate driver is designed and fabricated in the AMS 0.35μm 40V HVCMOS process. A 3.5% efficiency improvement at light load is achieved. Further experimental results indicate up to a 7dBμV improvement in peak CEMI between 20MHz and 30MHz.
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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) | 0.002 | 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 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".