A segmented output stage H-bridge IC with tunable gate driver
Bibliographic record
Abstract
In this paper, an integrated EDMOS H-bridge that incorporates both segmented output transistors and segmented gate drivers is presented. This fully segmented design approach allows the output resistance of the H-bridge and the output resistance of the gate drivers to be dynamically adjusted. Dynamic adjustment of these parameters allows for the continuous optimization of the power conversion efficiency of the H-bridge over a wide range of output currents. The IC chip is fabricated using TSMC's 0.18 μm BCD Gen-2 process technology. The H-bridge is operated with a 10 V input, 2 V output and a load current between 0.02 A and 4 A. The presented design achieves power conversion efficiency improvements of 32% and 8% at light load current and heavy load current, respectively, when compared to traditional fixed power transistor designs. Furthermore, the dynamically adjustable output resistance of the gate drivers allows for suppression of switching node ringing and conducted EMI (CEMI) by 5.5 dB with no a significant reduction in efficiency.
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 | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".