A Detailed Study on Effects of Demagnetization on the Performance of IPMSM
Bibliographic record
Abstract
Interior Permanent Magnet Synchronous Motors (IPMSMs) are commonly used in electric vehicles (EVs) because of their high torque density and efficiency. However, permanent magnet (PM) demagnetization remains a significant challenge [1]. This can arise when the motor experiences temperatures higher than normal operating conditions, where residual magnetic flux density decreases, possibly causing irreversible demagnetization [2]. This work analyzes fault conditions contributing to PM demagnetization in an 8-pole, 48-slot, 3-phase, wye-connected IPMSM, specifically addressing single-phase and three-phase stator winding short-circuits, eddy currents, and thermal stress on PMs. ANSYS Maxwell simulations replicate short-circuit conditions, assessing high-impact currents and temperature effects through incremental magnetization curves. The research quantifies effects on motor performance parameters, including output torque, torque ripple, electromagnetic noise and vibration, efficiency, and flux linkage. These results provide quantitative data for motor design, thermal management optimization, and development of diagnostic models for fault detection in EV applications.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".