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Frequency-Selective Grounding for Permanent Magnet Synchronous Motor Frequency Drives

2024· article· en· W4411272055 on OpenAlexaff
S. A. Saleh, A. Jee, Julian Meng, E. Ozkop, Razzaqul Ahshan, Babak Nahid‐Mobarakeh, Sergio Panetta, Daleep Mohla

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsMcMaster UniversityUniversity of New Brunswick
Fundersnot available
KeywordsGroundSynchronous motorMagnetPermanent magnet synchronous generatorElectrical engineeringAC motorPermanent magnet synchronous motorComputer sciencePhysicsEngineeringElectric motor

Abstract

fetched live from OpenAlex

Variable frequency drives (VFDs), including permanent magnet synchronous motor (PMSM) VFDs, have to be grounded in order to improve their operation and protection. In PMSM-VFDs, an adequate grounding can help in reducing common-mode voltages (CMVs), improving personnel safety, and limiting ground fault currents. Several standards and industrial codes have addressed the adequate grounding systems for VFDs, including PMSM-VFDs. This paper presents the design and performance assessment of the new frequency-selective grounding (FSG), when utilized in a PMSM-VFD. The design of the FSG is based on a parallel <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$R-C$</tex> circuit, which behaves as a very low impedance for high frequency voltages and a low-resistance for low frequency voltages. Such functions of the FSG can significantly reduce common-mode voltages (CMVs) in PMSMVFDs, thus minimizing their adverse impacts on the drive and its components. The performance of the proposed FSG in PMSMVFDs is experimentally tested using a <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$5 h p, 3 \phi$</tex> PMSM-VFD for different operating conditions. Experimental test results discussed and presented in this paper demonstrate the significant reductions in CMVs, along with negligible sensitivity to the operating speed and/or loading level of the PMSM-VFD.

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: Empirical · Consensus signal: none
Teacher disagreement score0.924
Threshold uncertainty score0.824

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 head0.008
GPT teacher head0.220
Teacher spread0.212 · 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
GenreEmpirical

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

Citations5
Published2024
Admission routes1
Has abstractyes

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