Speed Harmonic Based Saturation Free Inductance Modeling and Estimation of Interior PMSM Using Measurements Under One Load Condition
Bibliographic record
Abstract
For permanent magnet synchronous machines (PMSMs), accurate inductance is critical for control design and condition monitoring. Owing to magnetic saturation, existing methods require nonlinear saturation model and measurements from multiple load/current conditions, and the estimation is relying on the accuracy of saturation model and other machine parameters in the model. Speed harmonic produced by harmonic currents is inductance-dependent, and thus this paper explores the use of magnitude and phase angle of the speed harmonic for accurate inductance estimation. Two estimation models are built based on either the magnitude or phase angle, and the inductances can be from d-axis voltage and the magnitude or phase angle, in which the filter influence in harmonic extraction is considered to ensure the estimation performance. The inductances can be estimated from the measurements under one load condition, which is free of saturation model. Moreover, the inductance estimation is robust to the change of other machine parameters. The proposed approach can effectively improve estimation accuracy especially under the condition with low current magnitude. Experiments and comparisons are conducted on a test PMSM to validate the proposed approach.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".