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Record W2804114825 · doi:10.3390/wevj2010066

Sorting Through the Many Total-Energy-Cycle Pathways Possible with Early Plug-In Hybrids

2008· article· en· W2804114825 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueWorld Electric Vehicle Journal · 2008
Typearticle
Languageen
FieldEnergy
TopicHybrid Renewable Energy Systems
Canadian institutionsnot available
Fundersnot available
KeywordsNatural gasEnvironmental scienceWaste managementMiles per gallon gasoline equivalentCoalDiesel fuelBiofuelFossil fuelGreen vehicleEngineeringAutomotive engineeringFuel efficiency

Abstract

fetched live from OpenAlex

Using the “total energy cycle” methodology, we compare U.S. near term (to ~ 2015) alternative pathways for converting energy to light-duty vehicle kilometers of travel (VKT) in plug-in hybrids (PHEVs), hybrids (HEVs), and conventional vehicles (CVs). For PHEVs, we present total energy-per-unit-of-VKT information two ways (1) energy from the grid during charge depletion (CD); (2) energy from stored on-board fossil fuel when charge sustaining (CS). We examine “incremental” sources of supply of liquid fuel such as (a) oil sands from Canada, (b) Fischer-Tropsch diesel via natural gas imported by LNG tanker, and (c) ethanol from cellulosic biomass. We compare such fuel pathways to various possible power converters producing electricity, including (i) new coal boilers, (ii) new integrated, gasified coal combined cycle (IGCC), (iii) existing natural gas fueled combined cycle (NGCC), (iv) existing natural gas combustion turbines, (v) wood-to-electricity, and (vi) wind/solar. We simulate a fuel cell HEV and also consider the possibility of a plug-in hybrid fuel cell vehicle (FCV). For the simulated FCV our results address the merits of converting some fuels to hydrogen to power the fuel cell vs. conversion of those same fuels to electricity to charge the PHEV battery. The investigation is confined to a U.S. compact sized car (i.e. a world passenger car). Where most other studies have focused on emissions (greenhouse gases and conventional air pollutants), this study focuses on identification of the pathway providing the most vehicle kilometers from each of five feedstocks examined. The GREET 1.7 fuel cycle model and the new GREET 2.7 vehicle cycle model were used as the foundation for this study. Total energy, energy by fuel type, total greenhouse gases (GHGs), volatile organic compounds (VOC), carbon monoxide (CO), nitrogen oxides (NOx), fine particulate (PM2.5) and sulfur oxides (SOx) values are presented. We also isolate the PHEV emissions contribution from varying kWh storage capability of battery packs in HEVs and PHEVs from ~ 16 to 64 km of charge depleting distance. Sensitivity analysis is conducted with respect to the effect of replacing the battery once during the vehicle’s life. The paper includes one appendix that examines several recent studies of interactions of PHEVs with patterns of electric generation and one that provides definitions, acronyms, and fuel consumption estimation steps.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.494
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.204
Teacher spread0.191 · 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