Controlled Auxiliary Circuit with Measured Response for Reduction of Output Voltage Overshoot in Buck Converters
Bibliographic record
Abstract
In order to adhere to voltage regulation criteria, capacitor selection of a Buck converter must be based on the worst possible scenario. It is well known that, for a low duty cycle Buck converter, the output voltage deviation of a Buck converter undergoing an unloading transient will be significantly larger than that of a corresponding loading transient of equal magnitude. Therefore, in this paper, an auxiliary circuit and corresponding control method is presented to reduce the output voltage overshoot of a Buck converter undergoing an unloading transient. The proposed auxiliary circuit diverts a constant controlled current from the output of the converter to the input of the converter thereby significantly reducing the output voltage overshoot. In addition, the proposed auxiliary controller estimates the magnitude of the unloading transient and sets the auxiliary current to an appropriate level based on a pre-defined set of criteria. This allows for greater design flexibility and increases the auxiliary circuit efficiency for unloading transients of lesser magnitude. As demonstrated through simulation and experimental results, the proposed converter successfully estimates the unloading transient magnitude and diverts a proportional amount of current from the converter output.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| 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".