Modifying the Properties of Low Coercive Field Magnets for Improved Performance of Variable Flux Motors
Bibliographic record
Abstract
This work suggests modifications of existing low coercivity (LC) magnets for reducing the remagnetization current of variable flux motors (VFMs) without affecting their electric and magnetic loadings. Two existing LC magnets, i.e., AlNiCo and Iron Nitride (FeN) are adopted as examples and the improvement contour regions (ICRs) are developed using a bilinear approximation (BA) model for the LC magnets. Next, few hypothetical magnets are synthesized from the ICR having lower remagnetization requirements without lowering the magnet energy product (MEP). To verify the presented analysis, two existing VFM prototypes are analyzed by replacing the existing magnets with the modified magnets. The modified magnets successfully reduced the remagnetization currents to levels below two times the rated current without significantly affecting their magnetic loadings. This paper is in response to a challenge by a magnet manufacturer to develop appropriate magnet characteristics for VFMs.
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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".