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Record W3011754327 · doi:10.1109/tpel.2020.2982326

On-Board Single-Phase Integrated Electric Vehicle Charger With V2G Functionality

2020· article· en· W3011754327 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDrivetrainInverterTraction motorAutomotive engineeringElectric vehicleEngineeringElectrical engineeringSingle-phase electric powerVehicle-to-gridInduction motorAC powerVoltagePower (physics)Power factorTorquePhysics

Abstract

fetched live from OpenAlex

Mass adoption of electric vehicles (EVs) is contingent on the availability of charging infrastructure. One solution to this issue is the introduction of on-board fast chargers, but such solutions typically require the installation of additional magnetic components that increase EV mass. An alternative approach is the dynamic redeployment of drivetrain components for charging when the vehicle is stationary. This article proposes an on-board single-phase charger that reuses the traction inverter and motor. The system consists of a dual-inverter drivetrain, which affords higher voltage charging compared to conventional systems. In addition, the system is able to operate bidirectionally and operate at any power factor for grid support services with real and reactive power exchange without subjecting the motor to low frequency harmonic currents. Experimental tests demonstrated operation at 19.2 kW using a 110-kW EV motor and a full-scale, state-of-the-art, dual-inverter drive prototype. Measured peak efficiencies of over 97% demonstrate the viability of integrated charging in a real-world scenario.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.727
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.248
Teacher spread0.230 · 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