Analysis and Design of a Single-Phase Bridgeless Cuk-based PFC Converter as On-Board Charger with Reduced Number of Components and Losses
Bibliographic record
Abstract
In this paper, a new single-phase bridgeless Cuk-based power factor corrected (PFC) converter with reduced number of components for on-board charging application is presented. The converter is operated in discontinuous current conduction mode to achieve natural PFC at AC input, and thereby sensing of input voltage and input current is avoided, which makes the converter operation cost-effective, and increases the converter robustness to high-frequency noise. The converter control is quite simple, and requires only one control loop, and one sensor. The proposed converter requires less components, and the components voltage stress is less when compared to the conventional Cuk converter, which reduces the components switching losses and enhances the converter efficiency. Further, only one semiconductor is in current flowing path for throughout the converter operation. Thus, this will reduce the conduction losses, and further it eases the converter thermal management. The converter detailed steady state operation for one switching cycle is presented, and the design expressions for each passive component are derived to simplify the converter design. The proposed converter analysis and the design are confirmed with the simulation results from PSIM software.
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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 | 0.000 |
| 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 | 0.001 | 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".