Direct PWM Synchronization Using An All Digital Phase-Locked Loop for High Power Grid-Interfacing Converters
Bibliographic record
Abstract
For medium voltage high power grid-interfacing converters, the operating switching frequency is often around several hundred Hz to reduce the switching power losses. Therefore, to eliminate the even order harmonics and non-characteristic harmonics and to minimize the beat phenomenon, synchronous PWM techniques are desired for the high power low-switching converters. In this paper, a direct PWM synchronization method using an all digital phase-locked loop (ADPLL) is proposed for the grid-connected converter implementation. The control method is realized using a designed DSP-FPGA control system. The proposed ADPLL implemented in the FPGA has wide track-in range and fast pull-in time with an input frequency feed-forward loop. The phase error and pulse jitter is minimized by selecting a high clock frequency (150MHz). The synchronous PWM waveform can be generated effectively and conveniently by the ADPLL through external synchronized interrupt from FPGA to DSP at the desired sampling angle and switching frame starting angle. The proposed ADPLL synchronized PWM strategy has been verified experimentally using a 10kVA grid-connected PWM current source rectifier prototype.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 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".