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Novel Current Injection Based Multi-Parameter Estimation Technique for Dual Three-Phase PMSMs

2020· article· en· W3115038976 on OpenAlexaff
Ze Li, Pengzhao Song, Bradley Sato, Wenlong Li, Himavarsha Dhulipati, Narayan C. Kar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMultilevel Inverters and Converters
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsControl theory (sociology)StatorMagnetSubspace topologyTorqueSaturation (graph theory)Harmonic analysisFlux linkageEstimation theoryHarmonicPhase (matter)Computer sciencePhysicsEngineeringMathematicsElectronic engineeringAlgorithmDirect torque controlVoltageAcousticsInduction motor

Abstract

fetched live from OpenAlex

This paper investigates a novel current injection-based multi-parameter estimation technique for dual three-phase permanent magnet synchronous machine (PMSM) considering the magnetic saturation and temperature effects simultaneously. One set of currents is injected in harmonic subspace, which does not interfere with average torque production in the fundamental subspace to obtain the stator resistance under different temperature conditions. For each injection operation, the temperature effects on the resistance and permanent magnet flux linkage are considered and modelled. Meanwhile, this proposed method employs high order polynomial surface to fit the self-and cross-saturation effects. The analytical model achieved from the proposed estimation scheme satisfies both the light and heavy saturation regions. The proposed approach is validated through experimental studies on a laboratory dual three-phase interior PMSM.

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: Methods · Consensus signal: none
Teacher disagreement score0.883
Threshold uncertainty score0.583

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 head0.067
GPT teacher head0.296
Teacher spread0.229 · 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
GenreMethods

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
Published2020
Admission routes1
Has abstractyes

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