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Record W2156460414 · doi:10.1109/iecon.2005.1569080

Design of an efficient fuel cell vehicle drivetrain, featuring a novel boost converter

2005· article· en· W2156460414 on OpenAlexafffund
J. Marshall, Mehrdad Kazerani

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDrivetrainAutomotive engineeringInternal combustion engineHydrogen fuelEnergy managementFuel cellsHybrid vehicleComputer scienceEnergy storageHydrogen vehiclePower (physics)TorqueEngineeringEnergy (signal processing)

Abstract

fetched live from OpenAlex

Most automobile manufacturers have invested in the development of fuel cell vehicles. The motivation behind this has been the escalating concerns about energy security, dwindling fossil fuel reserves, and adverse environmental effects of operating internal combustion engine vehicles. The cost of fuel cell vehicles has to be dramatically reduced and many technical problems in hydrogen storage, fuel cell reliability, and power management have to be solved before fuel cell vehicles can be commercially available. In this paper, a design process for developing a highly efficient power management system for a cell-powered small SUV is documented. An analytic approach is used to select the optimal energy storage system for a fuel cell SUV. Also, a novel high-efficiency DC/DC converter for the fuel cell vehicle is introduced. Simulation and experimental results are presented to prove the concept.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.636
Threshold uncertainty score0.508

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 head0.019
GPT teacher head0.242
Teacher spread0.223 · 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

Citations43
Published2005
Admission routes2
Has abstractyes

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