Bidirectional ZVS Buck–Boost Converter With Single Auxiliary Switch and Continuous Current at Low Voltage Source
Bibliographic record
Abstract
In this article, a bidirectional zero voltage switching buck–boost dc–dc converter with a simple auxiliary circuit is presented. The auxiliary circuit employs only a single switch and a pair of coupled inductors to provide soft switching condition in both power flow directions. Moreover, the soft switching condition is independent of the load variation and duty cycle. Energy storage devices such as batteries and super capacitors are commonly utilized in systems using bidirectional converters as the low voltage source. Batteries require continuous current to prolong their life time and overall system efficiency. The proposed converter has continuous current at low voltage side in both operating modes, unlike the similar converters, which utilize coupled inductors in order to provide soft switching condition. Fully soft switching operation including the zero current switching condition of all diodes at turn-offhas significantly contributed to the converter overall efficiency. Operating principles, mathematical derivations and the soft switching conditions of the proposed converter are analyzed in both boost and buck operating modes. Furthermore, to confirm the main converter features and the theoretical analysis, a prototype of the proposed converter is implemented at 100 W–100 kHz and the experimental results are presented.
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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 | 0.001 |
| 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) | 0.003 | 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".