A Coupled-Inductor-Based Buck–Boost AC–DC Converter With Balanced DC Output Voltages
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Bibliographic record
Abstract
With the development of distributed power generation sources and the widely used dc characterized loads, the dc nanogrid becomes more and more attractive and the converters with three terminal outputs are increasingly studied. Considering the costs, the efficiency, and also the safety, the grounding configuration needs to be addressed when designing the ac-dc converter for a dc nanogrid system. An ac-dc converter with three terminal outputs has been presented for the united grounding configuration based dc nanogrid. Nevertheless, for this type of converters, the output voltages are unbalanced in case of unequal dc loads. This paper proposes a novel buck-boost ac-dc converter with the capacity of output voltages self-balancing by using a coupled inductor. The operation of this converter will be presented in details through analyzing its equivalent circuits. The small signal model of the system in different working modes is given, and the whole system control diagram shows how to balance the dc output voltages. A 220 V/50 Hz/1.5 kW prototype has been developed. Experiments are carried out to verify the effectiveness of the coupled-inductor-based converter.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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