Torque Ripple Minimization for Interior PMSM with Consideration of Magnetic Saturation Incorporating Online Parameter Identification
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Bibliographic record
Abstract
In this paper, an analytical torque ripple model for interior permanent magnet synchronous machine (IPMSM) is introduced at first, which can be used to estimate the torque ripple. Then, the inductance variation due to magnetic saturation is analyzed through experimental investigations, which demonstrates that magnetic saturation has a great influence on the inductances, and hence the torque ripple minimization performance. Thus, this paper proposes an online parameter identification approach to estimate the inductances and incorporates them into the torque ripple minimization. The proposed parameter identification approach can estimate the dq-axis inductances accurately such that it brings significant torque ripple minimization improvement for IPMSMs. Numerical and experimental investigations have been conducted to validate the proposed approach based on a laboratory IPMSM.
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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