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Record W2025708707 · doi:10.1109/ias.1994.345447

A torque controlled high speed flywheel energy storage system for peak power transfer in electric vehicles

2002· article· en· W2025708707 on OpenAlexaff
U. Schaible, B. Szabados

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric Motor Design and Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsFlywheelTorqueFlywheel energy storageEnergy storageAutomotive engineeringMicrocontrollerAccelerationElectric vehicleRegenerative brakeComputer sciencePower (physics)Energy (signal processing)MagnetElectric motorElectrical engineeringEngineeringEmbedded systemBrakePhysics

Abstract

fetched live from OpenAlex

This paper provides a design outline and implementation procedure for a flywheel energy storage system using a high speed interior permanent magnet synchronous machine, torque-controlled through the use of a vector control algorithm. The proposed flywheel energy storage system can be used to meet the peak energy requirements of an electric vehicle during both acceleration and regenerative braking. By supplying the peak energy requirements from a secondary source, the life cycle of the electric vehicle's batteries may be extended considerably, A torque control algorithm is presented and preliminary implementation through a commercially available microcontroller is described. Preliminary testing of the proposed system has been very promising and has proven that bidirectional peak power transfer can be rapidly accomplished.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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 score0.953
Threshold uncertainty score0.800

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.170
Teacher spread0.164 · 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

Citations6
Published2002
Admission routes1
Has abstractyes

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