Multiple Reference Frame Based Torque Ripple Minimization for PMSM Drive Under Both Steady-State and Transient Conditions
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Bibliographic record
Abstract
Torque ripple has been a critical issue for high-performance applications using permanent magnet synchronous machines (PMSMs). An efficient approach to minimize torque ripple is to control the stator current to follow an optimized current reference, which will produce an extra torque ripple to cancel the existing one. This paper proposes a multiple reference frame (MRF) based controller for torque ripple minimization (TRM), in which the measured speed ripple is explored as the feedback control signal. The proposed MRF-based controller consists of a TRM controller whose task is to find the optimal current reference and a current controller whose task is to control the actual current to follow the optimized current reference. In TRM controller, the control of reference current magnitude and phase angle is decoupled, and proportional integral (PI) controller is able to achieve TRM control. In current controller, MRF is adopted to convert harmonic current control into dc current control; thus, PI controller is able to achieve harmonic current control with the use of MRF. Compared with existing approaches, the proposed controller is capable of TRM under both steady-state and transient conditions. The proposed controller is experimentally evaluated on a laboratory PMSM drive system.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it