Mitigating the dead-time effects on harmonics spectrum of inverter waveform by the confined band VSFPWM technique
Bibliographic record
Abstract
The dead-time is necessary to be inserted between the gates drive pulses of the two power electronic switches in a one leg of any inverter to avoid a short circuit in the leg and the DC supply as well. However, adding the dead-time increases the low order harmonics of the output voltage/current waveform of the inverter. This paper investigates the positive effects of decreasing the pulse width modulation (PWM) drive pulses number per fundamental period on the current low order harmonics. In addition, this paper evaluates the impact of the confined band variable switching frequency pulse width modulation (CB-VSFPWM) technique on inverter performance in terms of dead-time mitigating, and consequenctely lowering the low order harmonics. CB-VSFPWM technique reduces the total harmonic distortion (THD) levels in the inverter output current as well. Theoretical analysis of the CB-VSFPWM effectiveness in reducing the negative effect of the dead-time has explained in this study and confirmed by the MATLAB/Simulink simulation results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".