Investigation of the impact of rotor shaping on the torque and radial force harmonics of a V‐shape interior permanent magnet synchronous machine
Bibliographic record
Abstract
Abstract This paper introduces a technique aimed at improving the performance of an interior permanent magnet synchronous machine (IPMSM) by reducing torque ripple and radial force harmonics. Unlike conventional IPMSMs, the proposed method employs a variable airgap length that is defined by a mathematical function. Two distinct rotor shapes are investigated to determine the most efficient design. Finite Element Analysis is employed to assess both the electromagnetic and mechanical attributes of the proposed motors. It compares the results for three operating points of the shaped motor with those of a conventional one. The investigation delves into the influence of rotor geometry on key output parameters, including Back Electromotive Force (back‐EMF) harmonics, average torque, cogging torque, torque ripple, efficiency, power factor, and radial force harmonics. The findings indicate that optimising rotor shape can significantly enhance IPMSM performance by reducing torque ripples and radial force harmonics, while simultaneously increasing average torque and efficiency at different operating points.
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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 | 0.000 |
| Open science | 0.000 | 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".