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Record W2204087705 · doi:10.1109/vppc.2015.7352979

Motor Drive with Halbach Permanent Magnet Array for Urban Electric Vehicle Concept

2015· article· en· W2204087705 on OpenAlexaff
Maxime R. Dubois, João Pedro F. Trovão

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsHalbach arrayHarmonicsAutomotive engineeringMagnetTraction motorStatorElectrical engineeringSynchronous motorBattery (electricity)Power (physics)EngineeringPhysicsVoltage

Abstract

fetched live from OpenAlex

Permanent Magnet Synchronous Motor (PMSM) with Halbach array increases the fundamental component of the electromotive force, while decreasing the higher harmonics of the PM flux. This allows motors with lower copper losses and lower iron losses due to the absence of higher harmonics in the stator core. Reduction of the no-load losses is of particular high interest for traction applications where a vehicle runs at a rather constant speed. The Urban Vehicle (UV) concept is a one-seater vehicle with light chassis and solar panels. The solar panels allow substantial reduction of the battery size. In UV running at vehicle speeds in the 30 - 50 km/h range, the PMSM iron losses become one of the main contributors of losses and special attention must be paid to the reduction of no-load losses in the motor. In the paper, a PMSM motor with Halbach rotor is built and tested for one-seater vehicle of 90 kg mass and a 0.6 m2 solar panel. At 30 km/h, the power provided by the 0.9 kg Li-Po battery is 78 W and the power consumed by the PMSM with Halbach array is 47 W. Special attention is given in the paper to the no-load losses in the PMSM with Halbach array.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.788
Threshold uncertainty score0.517

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 head0.010
GPT teacher head0.195
Teacher spread0.186 · 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 designSimulation or modeling
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

Citations4
Published2015
Admission routes1
Has abstractyes

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