A Single-Phase Six-Switch AC-AC Converter With Highly-Efficient Bipolar Buck and Boost Operations
Bibliographic record
Abstract
This paper proposes a highly-efficient bipolar buck boost AC-AC converter featuring a reduced number of active switches. By employing only six active switches, the proposed converter facilitates efficient symmetric-bipolar buck and boost operations, characterized by lower component voltage/current stress and ripples, features absent in existing AC-AC converters. Additionally, the converter offers the capability to adjust the output voltage frequency in discrete steps. Moreover, it employs only two inductors and filter capacitors, thereby providing second order input and output filters. Consequently, the converter ensures a continuous and low-ripple supply of input/output currents while eliminating the need for additional LC filters. Furthermore, due to the absence of bidirectional AC switches, the proposed converter mitigates device voltage or current overshoots during switching transitions, thus avoiding commutation issues without the necessity for lossy snubbers or safe-commutation algorithms. The paper explains the circuit operations of the proposed converter, based on developed PWM switch modulations, deriving various theoretical relations, and discussing component design. A comprehensive comparative evaluation against state-of-the-art bipolar AC-AC converters proves its superiority in terms of smaller voltage/current and power ratings of switching devices, reduced voltage/current ripples of passive components, minimized volume of passive components, and improved power conversion efficiency. Finally, experimental results from a laboratory-built prototype validate the theoretical analysis.
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How this classification was reachedexpand
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".