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Record W2221089868 · doi:10.1109/vppc.2015.7353033

Three Phase High Power Integrated Battery Charger for Plugin Electric Vehicles

2015· article· en· W2221089868 on OpenAlexafffund
Syed Qaseem Ali, Diego Mascarella, G. Joós, Tony Coulombe, Jean-Marc Cyr

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAutomotive engineeringTraction motorBattery (electricity)Electrical engineeringElectromagnetic coilElectric vehicleRotor (electric)Battery chargerThree-phaseTorqueAutomotive batteryComputer scienceEngineeringPower (physics)VoltagePhysics

Abstract

fetched live from OpenAlex

Battery chargers for plugin electric vehicles can be costly and add to the weight and volume of the vehicle when designed to be on-board. Conversely, integrated battery chargers not only re-use the already available components on-board but also provide a higher charging power capability than their dedicated counterparts. Such chargers use the traction motor's windings as input filter when connected to the three-phase supply. Surface mounted permanent magnet motors have not been used for integrated battery chargers for the apparent risk of rotor movement while charging. This paper demonstrates the use of a surface mounted permanent magnet motor to charge the battery while identifying the limiting factors of its implementation. The maximum torque (70Nm) developed on the rotor while charging is calculated using an FEA model of the motor and is found to be within the limits that a vehicle can withstand. Efficiencies up to 97% with an acceptable THD was achieved with a scaled down power version of the charger.

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 score0.544
Threshold uncertainty score0.618

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 head0.034
GPT teacher head0.293
Teacher spread0.258 · 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

Citations22
Published2015
Admission routes2
Has abstractyes

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