MétaCan
Menu
Back to cohort
Record W2795532366 · doi:10.1109/tvt.2018.2823538

Current Sensorless MTPA Operation of Interior PMSM Drives for Vehicular Applications

2018· article· en· W2795532366 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 Transactions on Vehicular Technology · 2018
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsCarleton University
Fundersnot available
KeywordsControl theory (sociology)AmpereVoltageTorqueTrajectoryCurrent loopMachine controlEngineeringComputer scienceControl (management)Control engineeringElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

This paper presents a direct voltage control method for interior permanent magnet synchronous motors (IPMSMs) with a single speed regulator. The method achieves maximum torque per ampere (MTPA) operation by controlling the magnitude and the angle of the voltage vector. For that, the mathematical model for the MTPA trajectory of the IPMSM is derived in the voltage plane. As such, no current sensor is needed, which makes the proposed strategy tolerant to current sensors failure unlike cascaded control loop based methodologies. Although no current sensor is used, the control strategy tracks MTPA trajectory by taking into account both voltage and current limits of the machine. The complete MTPA derivation in the voltage plane is presented in this paper; but, only the final solution is needed for real-time implementation. Henceforth, the simplicity of the control scheme combined with its current sensor dependence free characteristics make it a good candidate for real-time implementation in vehicular applications. The concept is developed and evaluated experimentally on a 10-HP IPMSM.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.759
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
Bibliometrics0.0010.001
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 head0.008
GPT teacher head0.241
Teacher spread0.232 · 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