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Record W2118089722 · doi:10.1109/ccece.2007.424

Control of a High-Inertia Flywheel As Part of a High Capacity Energy Storage System

2007· article· en· W2118089722 on OpenAlexaff
C. Chapelsky, John Salmon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMagnetic Bearings and Levitation Dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFlywheelInertiaEnergy storageFlywheel energy storageAutomotive engineeringComputer scienceControl (management)EngineeringPhysicsPower (physics)

Abstract

fetched live from OpenAlex

An alternative to high-energy capacity storage systems is described that uses a rotating high-inertia flywheel. When coupled with a synchronous machine, this system can be used to exchange electrical energy, store or retrieve, with the rotational energy of the flywheel; typically up to several kilowatts over tens of seconds can be achieved. This energy storage ability allows a flywheel to be used in a myriad of applications, including hybrid vehicle systems and wind generation. A system that improves the power conversion efficiencies using power electronics has a difficult task when considering that the electrical interface with the high speed generator has an operating frequency close to 1 kHz with a time varying voltage and frequency. This paper presents the results of a preliminary investigation into the development of a suitable control scheme for the power electronic converter that interfaces with a high speed generator mechanically coupled to a rotating flywheel. The investigation explored the possibility of operating the generator at unity power factor over a wide speed range and under constant power conditions. Simulation results show that unity-power factor operation improves the energy transfer efficiencies of the system since it minimizes the current flowing through the machine and hence minimizes the electrical losses. This is demonstrated by showing that 0.8 power factor operation results in a machine speed variation that is 300 rpm less than that obtained with unity power factor operation during an identical power removal cycle.

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: Empirical
Teacher disagreement score0.897
Threshold uncertainty score0.627

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 head0.005
GPT teacher head0.170
Teacher spread0.165 · 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

Citations7
Published2007
Admission routes1
Has abstractyes

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