Hybrid SHM-PWM for Common-Mode Voltage Reduction in Three-Phase Three-Level NPC Inverter
Bibliographic record
Abstract
This article proposes hybrid selective harmonic mitigation (SHM)-pulsewidth modulation (PWM) that is characterized by both features harmonic mitigation and elimination aimed to reduce the common-mode voltage (CMV) and to mitigate the selected nontriplen harmonics in a three-phase neutral-point-clamped (NPC) inverter. As CMV harmonic modeling only shows triplens, the specified triplens are eliminated using the selective harmonic elimination (SHE) operation to control CMV pulsewidths and consequently to mitigate CMV magnitude that appears as its root-mean-square (rms) reduction. The determined nontriplen harmonics are also mitigated using the SHM approach by the same cost function. The proposed hybrid SHM-PWM empowered by both harmonic elimination and mitigation is implemented on a three-phase NPC inverter to confirm its performance on reducing CMV through experimental and theoretical analyses. It is shown that hybrid SHM is superior over pure SHE or SHM in dealing with multiobjective system, including CMV reduction and no ntriplen harmonics mitigation.
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".