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Record W2148814990 · doi:10.1109/pes.2008.4596432

A VBR induction machine model implementation for SimPowerSystem toolbox in Matlab-Simulink

2008· article· en· W2148814990 on OpenAlexaff
Liwei Wang, Juri Jatskevich, Sina Chini Foroosh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsStatorMATLABComputer scienceInterface (matter)Variable bitrateRotor (electric)ReactanceDiscretizationToolboxElectronic engineeringEquivalent circuitInduction generatorVoltageControl theory (sociology)Control engineeringElectrical engineeringComputer hardwareEngineeringArtificial intelligenceParallel computingMathematics

Abstract

fetched live from OpenAlex

This paper presents a Voltage-Behind-Reactance (VBR) induction machine model for the Matlab-Simulink toolbox SimPowerSystem, which is widely used for simulations of power and power electronics systems. In the proposed VBR model, the three-phase stator branches are represented by decoupled and constant R-L branches behind voltage sources, which provide a direct interface of the model with the external network-circuit. The rotor subsystem is expressed in the qd coordinates resulting in a high numerical efficiency. The VBR model has full-order and is otherwise algebraically equivalent to the classical qd model. We present case studies of induction machine interfaced with resistive and inductive networks. The studies show that the proposed model significantly improves the machine-network interface and enhances the numerical accuracy and efficiency as compared with the built-in SimPowerSystem qd machine model for the discretized solution of electrical circuit.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.645
Threshold uncertainty score0.377

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 head0.023
GPT teacher head0.257
Teacher spread0.233 · 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

Citations8
Published2008
Admission routes1
Has abstractyes

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