Common-Mode Voltage Reduction for Back-to-Back Two-Level Converters Based on Zero-Sequence Voltage Injection
Bibliographic record
Abstract
High frequency and high amplitude common-mode voltage (CMV) can induce a number of problems on the reliable operations of back-to-back two-level converters, such as shaft voltages and bearing currents. To restrain the CMV for back-to-back two-level converters, a simple and effective CMV reduction method based on zero-sequence voltage (ZSV) injection is proposed in this article. By injecting the optimal amount of ZSV on either the rectifier-side or the inverter-side, the corresponding pulse overlapping areas that result in high CMV amplitudes can be eliminated with the proposed method, then the amplitude of CMV can be reduced by half, and the pulse edges of CMV can be reduced by one-third. Simulation and experimental results are presented to verify the effectiveness of the proposed method in CMV reduction, while some comparisons are also conducted to demonstrate the superiority of the proposed method.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".