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Record W2609114836 · doi:10.1109/tec.2017.2697758

Key Issues in Design and Manufacture of Magnetic-Geared Dual-Rotor Motor for Hybrid Vehicles

2017· article· en· W2609114836 on OpenAlexaff
Le Sun, Ming Cheng, Minghao Tong

Bibliographic record

VenueIEEE Transactions on Energy Conversion · 2017
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPowertrainTorqueTorque rippleRotor (electric)Automotive engineeringEngineeringMagnetic flux leakageMagnetic bearingMagnetTest benchElectric motorMechanical engineeringComputer scienceDirect torque controlInduction motorElectrical engineeringVoltage

Abstract

fetched live from OpenAlex

This paper presents a practical design guide for the magnetic-geared dual-rotor motor (MGDRM), which is one of the candidates of the power split device in hybrid electric vehicles. The spoke-type permanent magnet rotor and simplified complementary structure are first used to form a new MGDRM, which exhibits less flux leakage, less cost, and less torque ripple. Based on this structure, an FEA aided key dimensions design technique, considering the height of the outer rotor, is developed with the goal of generating maximum torque for a given motor volume. The method also takes the core saturation into consideration. Moreover, to enhance the manufacturability of the complimentary MGDRM, a unique technique is proposed to implement the dual rotor structure with simple components. A prototype of 16 kW is designed and manufactured. Experiments are carried out on a hybrid powertrain test bench, verifying the proposed design and manufacture technique.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.817
Threshold uncertainty score0.569

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.011
GPT teacher head0.209
Teacher spread0.198 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations26
Published2017
Admission routes1
Has abstractyes

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