Parameter Estimation for IPMSMs Considering Eddy Current Based on Joule Heating Effects and VMC Theory from Multi-State Measurements
Bibliographic record
Abstract
Accurate parameters are critical for efficient operation, optimizing performance, and detecting faults of the interior permanent magnet synchronous machines (IPMSMs). Eddy current is one of the key factors affecting parameter estimation accuracy, because eddy current can affect both the equivalent electric circuit and flux linkage in IPMSMs. Achieving a balance between the accuracy of the core loss model and engineering feasibility is a challenge in parameter estimation. Recently, a vector magnetic circuit (VMC) theory has been proposed to accurately analyze the influence of eddy current on the magnetic circuit of electric machine (EM), which can help develop a more precise IPMSM model. This paper proposes a parameter estimation method for improving inductance estimation accuracy considering the Joule heating effect and the impact on magnetic circuits of eddy current.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".