An Instantaneous Power Balancing Control With Power Factor Correction for Single-Stage Three-Phase AC-DC Converters
Bibliographic record
Abstract
A novel inner control loop for phase-modular three-phase single-stage rectifiers is proposed in this paper to achieve both power factor correction and power balancing at the same time. The power balancing control is critical in single-stage three-phase AC-DC converters as any small voltage imbalance in the three-phase voltages reflects into the output in the form of double line frequency voltage ripple that will prohibit electrolytic capacitor less implementation. The proposed instantaneous power balancing control approach is implemented on a single-stage LLC-based three-phase AC-DC converter. Balanced and unbalanced three-phase systems are considered in computer simulations to verify the effectiveness of the proposed method in removing line frequency power decoupling from the output capacitor. Moreover, a harmonic polluted three-phase voltage is also considered in the simulation to further verify the performance under non-ideal grid conditions. Furthermore, experimental results of a digitally controlled laboratory prototype validated unity power factor correction and the effectiveness of the proposed power balancing control method in rejecting line frequency output ripple in the presence of three-phase voltage imbalances.
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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 | 0.001 | 0.000 |
| 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".