A Concept of Accelerating the Demagnetization of Switched Reluctance Motor
Bibliographic record
Abstract
The demagnetization of switched reluctance motor (SRM) is usually a nonnegligible problem as the speed increases due to large back electromotive force (EMF). A slow demagnetization causes long tail current and negative torque, which reduces the efficiency and the output capability of SRM. In the conventional SRM design method, the inductance slope is normally designed to be high. However, it causes the problems of slow demagnetization in the negative torque region and low utilization efficiency of the torque-generative region. This article proposed a totally contrary way of SRM design, a small value of the inductance slope is chosen. Therefore, the effect of the back EMF can be diminished and the demagnetization is improved. The utilization of the torque-generative region is also improved due to the delayed turn-off angle. Simulation results are provided to verify the advantages of the proposed idea compared with the conventional one.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".