Comparison of Different Demagnetization Models of Permanent Magnet in Machines for Electric Vehicle Application
Bibliographic record
Abstract
The knee point in the B-H curve of a permanent magnet (PM) is considered crucial in electric motor applications. In the case of severe fault conditions, such as overheating or a short circuit in electric motors, the working point might fall below the knee point causing irreversible demagnetization of the PM. Hence, the remanence flux decreases and the motor operation would be reduced or stalled. In this paper, two demagnetization models of PMs are investigated, i.e., a linear model and an exponential model. Demagnetization curves for NdFeB were measured at temperatures varying from room temperature to 180°C. It was found that all the parameters in the exponential model, including Br, Hjc, μr, and the fitting parameter K1, are temperature dependent. Therefore, an exponential model can be developed as a function of temperature which allows a more efficient implementation within electric motor applications using PMs. However, comparison of the exponential and linear models indicates that the latter has a better accuracy near the knee point for the demagnetization curves of NdFeB magnets.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".