Universal Input AC Three-Phase Power Factor Correction With Adaptive Intermediate Bus Voltage to Optimize Efficiency
Bibliographic record
Abstract
This paper proposes an adaptive intermediate bus voltage solution to optimize efficiency in a universal three-phase ac input (200-480 V) cascaded buck-follows-boost power factor corrected (PFC) converter with a 400-V dc output voltage. With this application and architecture, the output voltage of the boost converter needs to be higher than the peak ac input voltage to maintain PFC and regulation. The conventional approach would regulate the intermediate bus voltage to near 800-V dc; this allows for 480-V ac high line input, plus allowable overvoltage tolerance and margin for regulation, but it incurs heavy losses at low line input. This paper proposes to adaptively change the bus voltage between the boost and buck stages, based on the value of the ac input voltage, and the use of a relay to bypass the buck stage for low ac line input conditions in order to maximize efficiency. A loss analysis is included to show the significant loss savings and efficiency improvement using the proposed method. Experimental results are presented for a 5-kW silicon-carbide-based prototype. The proposed method demonstrates up to a 4.4 percentage point increase in efficiency (220-W decrease in loss) at low ac line input compared to the conventional PFC approach with an 800-V dc intermediate bus voltage.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".