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Record W2624677949 · doi:10.1109/tmech.2017.2715502

Current Sensorless MTPA for IPMSM Drives

2017· article· en· W2624677949 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

VenueIEEE/ASME Transactions on Mechatronics · 2017
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsCarleton University
Fundersnot available
KeywordsAmpereControl theory (sociology)StatorController (irrigation)VoltageCurrent loopTorqueComputer scienceVector controlCurrent (fluid)Control (management)EngineeringPhysicsInduction motor

Abstract

fetched live from OpenAlex

In this paper, a maximum torque per ampere (MTPA) control strategy is presented for interior permanent magnet synchronous machines (IPMSMs) without current sensing or regulation. The developed control scheme achieves MTPA using a direct voltage control method, which varies the machine's stator voltage amplitude and angle. As such, no explicit current loop regulation is needed, which simplifies the control structure and unlike other control strategies, no parameter knowledge, voltage, or current transducer is required. Experimental comparison against the well-known MTPA vector control highlights the performance of the proposed controller in various conditions. Moreover, quantitative efficiency metrics are provided to better illustrate the MTPA trajectory tracking performance. Furthermore, the simplicity of the control scheme makes it a good candidate for low-cost implementation of real-time IPMSM drives.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.903
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.264
Teacher spread0.245 · 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