A transformerless modular step‐up dc–dc converter for high power applications
Why this work is in the frame
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Bibliographic record
Abstract
This study presents a new step‐up dc–dc converter topology suitable for medium voltage, megawatt scale applications. The proposed converter interconnects unipolar or bipolar dc networks using a single inductor and a modular active switching network. The active switching network contains multiple series‐connected identical converter modules. Each module consists of four switches and one capacitor. The modular nature of the switching network allows scalable implementation of the converter, and utilisation of low‐voltage switches and capacitors. The proposed converter avoids the use of medium‐frequency isolation transformers. Soft switching is utilised to reduce the converter's switching losses. An analytical model of the converter is developed to facilitate converter design. Theoretical predictions are supported by a 7.6 kW scaled laboratory prototype achieving an efficiency of as high as 93.2%.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it