Power Adapter with Line Voltage Control for USB Power Delivery
Bibliographic record
Abstract
The demand for high-power-density high-efficiency power adapters is increasing due to the wide adopt of the USB Power Delivery as the charging protocol in consumer electronics. Flyback converters have conventionally prevailed for such applications. To further improve the power density of power adapters, an increase in switching frequency is required. However, this will increase the burden of the EMI filter, and the heat will be difficult to manage as the loss increases when size is reduced. Resonant converters have long been used for high frequency applications due to the easily-implemented soft switching and low current stresses. With the development of faster switching devices and new ferrites, the switching frequency of resonant converters is pushed as high as megahertz with acceptable thermal performance. In this paper, a series resonant converter is combined with the proposed line voltage control circuit to accommodate both the 120 VAC and the 220 VAC lines, as well as the wide output voltage range from 5 V to 20 V required by the USB Power Delivery. In the 60 W prototype, peak 94% efficiency is achieved at 1 MHz operation enabled by a budget MCU.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".