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Record W2005612885 · doi:10.1109/iecon.2012.6389432

Constant power loads in More Electric Vehicles - an overview

2012· article· en· W2005612885 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsConcordia University
Fundersnot available
KeywordsConvertersPower electronicsElectrical impedancePower (physics)Electrical engineeringConstant currentVoltageControl theory (sociology)EngineeringComputer sciencePhysicsControl (management)

Abstract

fetched live from OpenAlex

Power electronic converters are playing an ever increasingly important role in today's electric vehicles. These regulated power electronic converters act as Constant Power Loads (CPLs) to the converters driving them. A CPL has a negative input impedance which results in a destabilising effect on closed-loop converters driving them. The use of power electronics in More Electric Vehicles (MEVs) is discussed, along with the CPLs they present and how they are modeled. Negative impedance instability is then discussed and the stability of various DC-DC converter topologies when loaded by CPLs is analyzed in both voltage-mode and current-mode control operating in Continuous Conduction Mode (CCM) and Discontinuous Conduction Mode (DCM). Finally, the currently proposed control strategies that can stabilize a power electronic converter are discussed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.729
Threshold uncertainty score0.434

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 head0.019
GPT teacher head0.263
Teacher spread0.244 · 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

Quick stats

Citations35
Published2012
Admission routes1
Has abstractyes

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