Analysis and Design of Three-Phase Interleaved Buck-Boost Derived PFC Converter
Bibliographic record
Abstract
A three-phase interleaved two-channel buck-boost derived power factor correction (PFC) converter for more electric aircraft application (MEA) is presented in this paper. Typically, the converters operated in continuous conduction mode (CCM) require two control loops (inner current, outer voltage), and five sensors to implement PFC control algorithm. As the supply frequency in MEA is variable, the controller has to be designed for a wider bandwidth, which complicates the controller design, and also complicates the phase-locked-loop (PLL) design. On the other hand, the discontinuous conduction mode (DCM) operation realizes the natural power factor correction at mains supply without any current control loop. Further, the DCM operation eliminates four sensors, and makes the system more reliable and robust. Hence, the proposed converter is designed to operate in DCM. A simple voltage control is implemented for output voltage regulation. The converter steady state operation and its design are presented in detail. The converter analysis and design are validated with the simulation results from PSIM. Further, the advantages of the proposed converter are demonstrated by comparing the proposed interleaved two-channel converter with single-channel three-phase buck-boost derived PFC converter.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".