Torque Ripple Suppression Strategy for Open-Winding PMSM With Zero-Sequence Loop Model-Free Control
Bibliographic record
Abstract
To suppress the torque ripple caused by zero-sequence loop (ZSL) in open-winding permanent magnet synchronous motors, a${q}$-axis current injection strategy has been proposed. However, in this method, the torque ripple cannot be effectively suppressed and will even be augmented when the third flux linkage mismatch occurs. First, an extended state observer (ESO) based on the ultralocal model is established in this article to address the problem. In ESO, the future zero sequence current (ZSC) and ZSL back-electromotive force (EMF) can be estimated under complex conditions; then the injected${q}$-axis current can be calculated, which addresses the problem of one-step delay and aforementioned disturbance caused by third flux linkage mismatch. Second, the desired zero-sequence voltage (ZSV) can be calculated by ESO. Then zero voltage duration ratios are adjusted in space vector pulsewidth modulation to obtain the desired ZSV to suppress ZSC. Finally, comparative simulation and experimental results have been shown to prove the effectiveness of the proposed control method.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".