An SiC-Driven Modular Step-Up Converter With Soft-Switched Module Having 1:1 Turns Ratio Multiphase Transformer for Wind Systems
Bibliographic record
Abstract
In this paper, a new step-up dc-dc converter module that consists of three resonant submodules interconnecting with 1:1 turns ratio three-phase transformer and coupled current-fed voltage doubler modules is presented for medium voltage dc converter design in wind energy application. By utilizing step-up resonant circuits with three-phase transformer and combining it with a “multistring” inverter, the proposed circuit structure completely utilizes all the switching circuits to transfer power to the output. In addition, the proposed topology is able to achieve high voltage gain without using large turns ratio high frequency step-up transformers. Zero voltage switching turn-on and near zero current switching (ZCS) turn-off are maintained for all the switches. A modular 1.5 MW, 1 kV (dc-link), 20 kV (output) converter system is presented to validate the performance of the proposed circuit. Experimental results on a laboratory-scale 2.8 kW, 0.3 kV (dc-link), 6 kV (output), prototype are provided to highlight the merits of this work. Silicon Carbide (SiC) MOSFETs and SiC Schottky diodes are utilized in both designs. Results confirm that a peak efficiency of 97.6% is achieved in the prototype.
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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 | 0.000 | 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".