A novel grain oriented lamination rotor core assembly for a synchronous reluctance traction motor with reduced torque ripple
Bibliographic record
Abstract
High torque density and low torque ripple are crucial for traction applications. These allow the electrified powertrains to perform properly during start-up, acceleration, and cruising. Achieving these goals requires improvement to the saliency of the rotor geometry which means higher magnetization in the flux carriers and lower magnetization through the flux barriers. Recent advantages of high quality anisotropic magnetic materials such as cold rolled grain oriented electrical steels is a potential for achieving energy efficient, compact, and high performance synchronous reluctance machines. However, the cylindrical geometry of the rotor is an obstacle to utilizing these materials for rotor lamination with number of poles higher than two. This paper presents an innovative rotor lamination design and assembly using cold rolled grain oriented electrical steel along with a new analytical approach for rotor flux barrier design for achieving a higher torque density and lower torque ripple for a 4-pole synchronous reluctance motor. The design methods and prototyping process are discussed, finite element analyses and experimental examinations are carried out and the results are compared to verify and validate the proposed methods.
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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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".