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Record W2198652754 · doi:10.1115/omae2015-41955

Analysis of a Hysteresis IPM Motor Drive for Electric Submersible Pumps in Harsh Atlantic Offshore Environments

2015· article· en· W2198652754 on OpenAlexaffabout
S. F. Rabbi, Mejbahul Sarker, Geoff Rideout, Stephen Butt, M.A. Rahman

Bibliographic record

VenueVolume 10: Petroleum Technology · 2015
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsAutomotive engineeringElectric motorRotor (electric)Synchronous motorHysteresisTorqueControl theory (sociology)EngineeringMarine engineeringMechanical engineeringComputer scienceElectrical engineeringPhysicsControl (management)

Abstract

fetched live from OpenAlex

This paper presents the analysis of a hysteresis interior permanent magnet (IPM) motor drive for electric submersible pumps. A hysteresis IPM motor is a self-starting solid rotor hybrid synchronous motor. Its rotor has a cylindrical ring made of composite materials with high degree of hysteresis energy. The rare earth permanent magnets are buried inside the hysteresis ring. A hysteresis IPM motor can self-start without the need of additional position sensors and complex control techniques. It does not have any slip power losses in the rotor at steady state which results in less heat dissipation and low electrical losses. When used in an electric submersible pump (ESP) for oil production, it has the ability to automatically adapt itself to the changes in well conditions. In this paper, a bond graph model of a hysteresis IPM motor ESP drive is used to predict the effect of pump shaft geometry on transient behaviour of the drive during start-up. Simulation results show that the hysteresis IPM motor drive has high efficiency, and is better able to maintain its speed during changes in load. Due to increased efficiency and simplified controller requirements, the hysteresis IPM motor is proposed as a replacement for the standard induction motor currently used for downhole ESPs. This is expected to improve ESP performance and reliability which are critical requirements for use in harsh offshore environments such as Atlantic Canada.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.726
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
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 head0.010
GPT teacher head0.211
Teacher spread0.201 · 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 designObservational
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

Citations4
Published2015
Admission routes2
Has abstractyes

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