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Record W2997405347 · doi:10.1109/tte.2019.2962333

Noninvasive and Improved Torque and Efficiency Calculation Toward Current Advance Angle Determination for Maximum Efficiency Control of PMSM

2019· article· en· W2997405347 on OpenAlex
Aiswarya Balamurali, Guodong Feng, Animesh Kundu, Himavarsha Dhulipati, Narayan C. Kar

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

VenueIEEE Transactions on Transportation Electrification · 2019
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsControl theory (sociology)TorqueStatorInductanceVoltageCurrent (fluid)OvermodulationController (irrigation)Direct torque controlRotor (electric)Computer scienceInverterEngineeringInduction motorPhysicsControl (management)Mechanical engineeringElectrical engineering

Abstract

fetched live from OpenAlex

This article proposes improved mathematical models for torque and system efficiency used toward obtaining accurate current advance angle for maximizing the efficiency of an interior permanent magnet (IPM) synchronous motor. First, improved torque and efficiency calculation procedure that consider the effects of parameter variations, such as inductance, stator resistance and PM flux linkage simultaneously, and motor and inverter losses, have been developed from a combination of analytical models and practical experiments. Subsequently, an offline search procedure has been utilized to determine the optimal current angle using the improved dq-axis-based models. The novelty of the efficiency model is that the method uses preliminary noninvasive experimental tests to consider the saturation and temperature effects simultaneously and successfully determine the relationship between stator and rotor temperatures by using only controller command voltages and currents. Experimental investigations are performed on a laboratory IPM for validating the developed control method through interpolation of improved look-up tables with the derived current angle values for varying speed, torque, and temperature conditions. The effectiveness of the proposed method in improving efficiency is also verified and compared with maximum efficiency and maximum torque per ampere methods using experimental sweep tests.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.735
Threshold uncertainty score0.756

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 head0.007
GPT teacher head0.221
Teacher spread0.215 · 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