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Record W4300389867

U.S. Department of Energy -- Advanced Vehicle Testing Activity: Plug-in Hybrid Electric Vehicle Testing and Demonstration Activities

2009· paratext· en· W4300389867 on OpenAlexaboutno aff
James E Francfort, Donald Karner, John Smart

Bibliographic record

VenueUniversity of North Texas Digital Library (University of North Texas) · 2009
Typeparatext
Languageen
FieldEngineering
TopicElectric and Hybrid Vehicle Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsAutomotive engineeringPlug-inElectric vehicleHybrid vehicleEngineeringVehicle safetyComputer sciencePower (physics)Operating systemPhysics
DOInot available

Abstract

fetched live from OpenAlex

The U.S. Department of Energy’s (DOE) Advanced Vehicle Testing Activity (AVTA) tests plug-in hybrid electric vehicles (PHEV) in closed track, dynamometer and onroad testing environments. The onroad testing includes the use of dedicated drivers on repeated urban and highway driving cycles that range from 10 to 200 miles, with recharging between each loop. Fleet demonstrations with onboard data collectors are also ongoing with PHEVs operating in several dozen states and Canadian Provinces, during which trips- and miles-per-charge, charging demand and energy profiles, and miles-per-gallon and miles-per-kilowatt-hour fuel use results are all documented, allowing an understanding of fuel use when vehicles are operated in charge depleting, charge sustaining, and mixed charge modes. The intent of the PHEV testing includes documenting the petroleum reduction potential of the PHEV concept, the infrastructure requirements, and operator recharging influences and profiles. As of May 2008, the AVTA has conducted track and dynamometer testing on six PHEV conversion models and fleet testing on 70 PHEVs representing nine PHEV conversion models. A total of 150 PHEVs will be in fleet testing by the end of 2008, all with onboard data loggers. The onroad testing to date has demonstrated 100+ miles per gallon results in mostly urban applications for approximately the first 40 miles of PHEV operations. The primary goal of the AVTA is to provide advanced technology vehicle performance benchmark data for technology modelers, research and development programs, and technology goal setters. The AVTA testing results also assist fleet managers in making informed vehicle purchase, deployment and operating decisions. The AVTA is part of DOE’s Vehicle Technologies Program. These AVTA testing activities are conducted by the Idaho National Laboratory and Electric Transportation Engineering Corporation, with Argonne National Laboratory providing dynamometer testing support. The proposed paper and presentation will discuss PHEV testing activities and results. INL/CON-08-14333

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.132
Threshold uncertainty score0.263

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0580.026

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 head0.009
GPT teacher head0.162
Teacher spread0.153 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2009
Admission routes1
Has abstractyes

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