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Record W2033509089 · doi:10.1504/ijpelec.2012.052427

Development of a generic fuel cell model: application to a fuel cell vehicle simulation

2012· article· en· W2033509089 on OpenAlex

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

VenueInternational Journal of Power Electronics · 2012
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsAutomotive engineeringFuel cellsHydrogen vehicleStack (abstract data type)Fuel efficiencyDriving rangeRange (aeronautics)DatasheetAccelerationEngineeringSimulationComputer scienceHydrogen fuelElectric vehiclePower (physics)Aerospace engineeringElectrical engineering

Abstract

fetched live from OpenAlex

In this paper, a novel approach to fuel cell modelling is proposed. The model is obtained from manufacturer datasheets and is able to represent the behaviour of any hydrogen fuel cells. The simulation results are as expected with an error in the range of ±1%, provided a controlled stack internal humidity. The procedure to extract data from fuel cells datasheet is described along with the method to estimate cell’s parameters. The model is integrated in SimPowerSystems (SPS) and used in the simulation of a fuel cell vehicle. The vehicle is modelled with the same characteristics as the Honda FCX-Clarity. The performance obtained from the vehicle model is close to reality in terms of fuel consumption, maximum speed and acceleration.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score0.428

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 head0.233
Teacher spread0.226 · 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