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Record W2968386903 · doi:10.1109/itec.2019.8790494

An Integrated Modular Converter for Switched Reluctance Motor Drives in Range-Extended Electric Vehicles

2019· article· en· W2968386903 on OpenAlexaff
Zekun Xia, Jennifer Bauman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSwitched reluctance motorGenerator (circuit theory)Battery (electricity)Modular designElectrical engineeringElectromagnetic coilComputer scienceElectric vehicleTorqueAutomotive engineeringReluctance motorVoltageEngineeringRotor (electric)Power (physics)Physics

Abstract

fetched live from OpenAlex

In this paper, a highly integrated modular converter for switched reluctance machines (SRMs) for range-extended electric vehicle (REEV) is proposed. The converter can be implemented by standard industrial switch modules, and the energy conversion among the SRM, battery, generator, and external ac source can be flexibly achieved with the front-end circuit. In battery driving mode, the capacitor paralleling with the generator is naturally charged and discharged which elevates the phase voltage, so the excitation and demagnetization processes of SRM are accelerated which improves the torque capability. In generator driving mode, the battery is also involved inherently for the fast excitation and demagnetization. The energy stored in the phase windings is automatically recovered back to the battery during demagnetization procedure under all the driving modes, and the battery can be also charged directly by the external ac source. The effectiveness of the proposed converter is verified by simulation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.961
Threshold uncertainty score0.674

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 integrity0.0000.000
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 head0.006
GPT teacher head0.206
Teacher spread0.200 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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