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A Novel Speed Sensor-less Control of a Solar-Powered PMSM Drive

2025· article· en· W4409991014 on OpenAlex
Abirami Kalathy, Arpan Laha, Praveen Jain, Majid Pahlevani

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsQueen's University
Fundersnot available
KeywordsSolar poweredElectronic speed controlAutomotive engineeringControl (management)Computer scienceTorqueControl theory (sociology)Solar energyElectrical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

This paper proposes a novel control methodology for the solar-powered motor drive of a surface-mounted Permanent Magnet Synchronous Motor (SPMSM). Standalone solar-powered motor drives face considerable challenges due to inherent PV power fluctuations and the absence of an external energy storage system. These challenges are further exacerbated with solar microinverters utilizing a low DC link capacitance due to the limited energy storage capacity of the DC link. Reliable operation under such conditions requires a control strategy that optimally utilizes fluctuating solar power while maintaining stability during input power and load transients, despite the low DC link stiffness. The proposed control strategy quickly modulates the drive frequency to follow the Maximum Torque per Ampere (MTPA) trajectory while the current reference is directly set by DC link voltage regulation. Compared to existing observer-based vector control methods, the proposed approach offers fast dynamic performance, simplified implementation, and eliminates the need for a separate startup routine.

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 score0.796
Threshold uncertainty score0.861

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 head0.205
Teacher spread0.198 · 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

Quick stats

Citations4
Published2025
Admission routes1
Has abstractyes

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