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Record W2170795006 · doi:10.1109/tvt.2010.2045522

Simulation Model of a Military HEV With a Highly Redundant Architecture

2010· article· en· W2170795006 on OpenAlexaff
Loïc Boulon, Daniel Hissel, Alain Bouscayrol, Olivier Pape, Marie Péra

Bibliographic record

VenueIEEE Transactions on Vehicular Technology · 2010
Typearticle
Languageen
FieldEngineering
TopicElectric and Hybrid Vehicle Technologies
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsRedundancy (engineering)PropulsionArchitectureReliability (semiconductor)Electric vehicleEngineeringComputer scienceControl engineeringEnergy managementModeling and simulationSimulationPower (physics)Reliability engineeringEnergy (signal processing)Aerospace engineering

Abstract

fetched live from OpenAlex

The six-driven-wheel Electric Propulsion Demonstrator (DPE 6 × 6) is a military hybrid vehicle. Due to reliability demands, high redundancy is required, and the architecture is quite complex. A simulation model of this vehicle is proposed in this paper. The simulation model must allow the analysis of various power flows of the system. Moreover, this model has to be used to develop an efficient energy-management strategy. For these reasons, a graphical description [energetic macroscopic representation (EMR)] is used to develop the model in a systemic approach. The simulation model is, thus, described and validated from experimental results.

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: Empirical
Teacher disagreement score0.475
Threshold uncertainty score0.768

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.006
GPT teacher head0.198
Teacher spread0.192 · 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

Citations45
Published2010
Admission routes1
Has abstractyes

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