MétaCan
Menu
Back to cohort

Utilization of Innovative Materials toward Permanent Magnet Synchronous E-Motors for Traction Application: A Review

2020· review· en· W3096205398 on OpenAlexaff
Donovan O'Donnell, Samantha Bartos, Jimi Tjong, Narayan C. Kar

Bibliographic record

Venuenot available
Typereview
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsTraction (geology)MagnetAutomotive engineeringTraction motorRotor (electric)Synchronous motorElectromagnetic coilMechanical engineeringCopper lossCore (optical fiber)Computer scienceMaterials scienceEngineeringElectrical engineeringComposite material

Abstract

fetched live from OpenAlex

This paper examines recent optimization attempts of Permanent Magnet Synchronous Machine (PMSM) design involving the utilization of innovative materials. Recent attempts at material based enhancements to PMSM design are divided into several sections based on key machine components. In the area of core design, the replacement of electromagnetic steel with new material is highlighted. With regard to winding design, several materials have been examined as replacement for the conductive copper used as the traditional winding material. The use of enhanced materials for next generation magnets is also investigated in this paper. Additionally, the utilization of novel materials for the weight intensive PMSM motor housing, cooling channels, and rotor shaft are investigated. Lastly, the utilization of enhanced materials for PMSM insulation of enhanced thermal performance is examined. Overall, this paper will highlight the strong potential of advanced materials to greatly enhance PMSM design and their viability for use in traction applications.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.052
GPT teacher head0.318
Teacher spread0.266 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations8
Published2020
Admission routes1
Has abstractyes

Explore more

Same topicElectric Motor Design and AnalysisFrench-language works237,207