Speed Harmonic Based Decoupled Torque Ripple Minimization Control for Permanent Magnet Synchronous Machine With Minimized Loss
Bibliographic record
Abstract
This article proposes a closed-loop decoupled current control for torque ripple minimization (TRM) of permanent magnet synchronous machines (PMSMs) by using the speed measurements. In the proposed control, a decoupled scheme is developed to control the harmonic currents for TRM, in which the control of phase angle and magnitude is decoupled to simplify the controller design. The decoupled scheme consists of two PI controllers and one control rule: one PI is responsible for phase angle control, the other is responsible for magnitude control, and the control rule is responsible for coordinating the two PIs for TRM. The harmonic currents can produce additional loss, and thus this paper derives the optimal condition for TRM with minimized loss. With the derived condition, one can control q-axis current and calculate d-axis current from the derived condition, which can minimize the torque ripple with minimized loss and simplify the control structure. The proposed decoupled approach is evaluated with extensive experiments and comparative study on a laboratory PMSM drive.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".