Bibliographic record
Abstract
Sinusoidal Pulse Width Modulation (SPWM) technique has been a powerful method to generate sine waveform at inverter output from a fixed dc link input.Similarly, space vector modulation (SVM) has been widely adopted to produce the three-phase sine AC output from a fixed dc link.These two modulation techniques are implemented on 3-phase 3-leg (6 switches) six-step inverter topology if the dc link voltage is much higher than desired three-phase rms output.However, if the source/dc link voltage is lower or much lower than ac rms output, then frond-end dc/dc converters becomes necessary.To implement existing SVM or carrier based modulation, traditionally large number of semiconductor devices, three-phase magnetics, and bulky unreliable electrolytic capacitor are employed to develop a high voltage dc link at inverter input.Novel Single-reference-Six-Pulse Modulation (SRSPM) substantially reduces the number of semiconductor devices and magnetics and eliminates the dc link electrolytic capacitor allowing pulsating dc link voltage waveform at the inverter input.It significantly reduces the cost, size, and weight and improves reliability of the system.The control complexity is much simplified because of the reduced reference signals generation and gate driving requirements .This novel SRSPM is simple and results in saving of 87% switching losses.The concept has been experimentally implemented and demonstrated with closed loop control to achieve 97% efficiency at low voltage high current specifications.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.647 | 0.430 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".