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Record W2479259601 · doi:10.1109/itec-ap.2016.7512961

C++ based dynamic model of AC induction motor in discrete time domain

2016· article· en· W2479259601 on OpenAlexaff
JongKwang Kim, Eunseok Cho, YongKeun Lee, JangWook Lee, JangHyeon Lee

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsCoquitlam CollegeBurnaby Hospital
Fundersnot available
KeywordsInduction motorStatorStationary Reference FrameComputer scienceTorqueAC motorVector controlReference frameControl theory (sociology)Frame (networking)Control engineeringEngineeringElectric motorControl (management)VoltageElectrical engineeringArtificial intelligencePhysics

Abstract

fetched live from OpenAlex

Three-phase AC Induction (ACI) motor's dynamic model in a stationary reference frame is coded in C++ programming language and verified. Three-phase ACI motor model is compared with commercial models such as Simulink model and found to work properly on any PC platforms. Most of the model simulation tests are passed successfully such as the torque/speed test and the stator flux versus the back emf. Its coding is concisely done based on the circuit equivalent to the generalized induction motor model. It is designed to replace a high-end and expensive commercial induction motor model for induction motor control algorithm developments and various educational teaching purposes at the college level.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.934
Threshold uncertainty score0.306

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 head0.005
GPT teacher head0.186
Teacher spread0.181 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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