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Record W2111786104 · doi:10.1109/vppc.2008.4677547

Design and development of a plug-in by-wire(less) hydrogen internal combustion engine extended range electric vehicle

2008· article· en· W2111786104 on OpenAlexaff
Matt Van Wieringen, Mark Bernacki, Remon Pop‐Iliev

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric and Hybrid Vehicle Technologies
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsHydrogen vehicleAutomotive industryAutomotive engineeringZero emissionInternal combustion engineMiles per gallon gasoline equivalentGreen vehicleElectric vehicleContext (archaeology)Original equipment manufacturerAutomotive engineCombustionFuel efficiencyPropulsionDriving rangeRange (aeronautics)Environmental scienceHydrogen fuelEngineeringComputer scienceFuel cellsElectrical engineeringAerospace engineeringPower (physics)

Abstract

fetched live from OpenAlex

In recent decades there has been a growing global concern with regards to vehicle-generated green house gas (GHG) emissions and the resulting air pollution. In response, automotive OEMs focus their efforts on developing ldquogreenerrdquo propulsion solutions in order to meet the societal demand and ecological need for clean transportation. Although many automotive experts continue to believe that the hydrogen economy is the future of transportation, there are a number of problems that must be first solved, such as for example a method for clean hydrogen generation, an infrastructure for fuel distribution, and a reduction in costs of hydrogen fuel cells. In this context, our project aims to develop a vehicle which would effectively combine the benefits of plug-in electric vehicle technology such as drive-by-wire capabilities, regenerative braking and electric hub motors with the cleaner burning characteristics of a hydrogen internal combustion engine (H-ICE) based range extender. The hydrogen ICE is advantageous when compared to a hydrogen fuel cell in that it costs significantly less. As such the hydrogen ICE and the extended range electric vehicle (E-REV) architecture are well suited to meet the needs of the automotive industry in the near term by reducing overall GHG emissions, allowing for zero emissions travel during short trips, and by offering a feasible cost effective alternative to the waning supply of petroleum based fuels. The vehiclepsilas electrical systems such as steering, braking, and acceleration will operate wirelessly where possible with a redundant wired connection.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.601
Threshold uncertainty score0.510

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 head0.016
GPT teacher head0.195
Teacher spread0.180 · 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 designBench or experimental
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

Citations5
Published2008
Admission routes1
Has abstractyes

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