Dual-Buck Three-Phase Cyclo-Converters Without Commutation Problem
Bibliographic record
Abstract
This article proposes a novel three-phase dual-buck ac–ac converters capable of both step-up and step-down operations. They use a dual-buck structure, while effectively mitigating commutation problems and eliminating the necessity for lossy snubber circuits and complex soft commutation strategies. As a result, the output voltage with less distortion can be obtained. Also, the proposed converters provide flexibility in handling a wide range of input voltage requirements. Furthermore, they can significantly reduce the requirement for shoot-through inductors, which not only reduces component count but also enhances overall efficiency. A phase-shifted PWM strategy is utilized to enhance the effective switching frequency of inductors and capacitors while maintaining the same switching frequency of semiconductor devices while optimizing performance and reliability. Notably, the proposed converters utilize power metal-oxide-semiconductor field-effect transistors (MOSFETs) without engaging their body diodes, thereby resolving the reverse recovery issue typically associated with MOSFETs body diodes. To validate the feasibility of the proposed converters, both the simulation and experimental results of the proposed converters are presented, while demonstrating the converters superior performance and practical applicability.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".