High‐voltage conversion ratio dual‐input DC–DC converter operating in a wide duty cycle range and canceling input current ripple
Bibliographic record
Abstract
Abstract This paper proposes a new nonisolated dual‐input, single‐output (DISO) DC–DC converter. In the proposed converter, by utilizing two three‐winding coupled inductors at the primary of each input ports, the capabilities of high‐voltage conversion ratio and elimination of input current ripple are achieved for all range of duty cycles (0 < D < 1). Therefore, the proposed converter is applicable in renewable energy systems. The voltage conversion ratio can be increased without selecting high duty cycles for the switches or by using a high number of components. Also, the voltage stresses on switches of the proposed converter are in low level. The proposed converter has simple switching pattern and the two switches turn on/off inversely. Unlike the interleaved converters, the proposed converter has a single conversion ratio for all adopted duty cycles of the switches (0 < D < 1). In this study, the proposed converter is analyzed and the required conditions for eliminating input current ripple, the voltage and current stress on the semiconductors, and the voltage gain are calculated. To confirm the theoretical results, experimental results are extracted for a 14‐V/19‐V input and 400‐V output voltages for the operating power of 350 W.
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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) | 0.000 | 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 | 0.000 |
| 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".