Low Output Current Ripple Ultra High Step-Down Two-Phase Buck Converter With Low Switching Losses
Bibliographic record
Abstract
This article introduces a new two-switch step-down dc–dc converter. By integrating Valley-Fill circuit with coupled inductors, and using the cross-coupled inductor technique, the proposed converter achieves a substantial reduction in the output current ripple. This configuration not only improves the voltage gain of the converter but also alleviates voltage stress on diodes. Employing dual magnetic elements provides the realization of a dual-phase buck mechanism, enhancing converter efficiency. Moreover, the converter demonstrates ripple cancellation capabilities. One switch in the proposed converter turns on under zero current switching conditions, while the other incurs minimal switching losses due to its low drain-source voltage, which reduces both switching losses and the capacitive turn-on loss. Detailed analysis and design guidelines are presented to validate the performance of the proposed converter. Experimental validation is provided through a 300 to 24 V 120 W prototype converter, which affirms the circuit's operational integrity and theoretical analysis.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".