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Record W2200664647 · doi:10.1109/vppc.2015.7352925

Design of a Power Electronic Emulator for Series Hybrid Electric Vehicle Powertrains

2015· article· en· W2200664647 on OpenAlexaff
Hesam Akbarian, Pragasen Pillay, Luiz A. C. Lopes

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric and Hybrid Vehicle Technologies
Canadian institutionsConcordia University
Fundersnot available
KeywordsPowertrainDSPACEAutomotive engineeringElectric vehicleGenerator (circuit theory)Series (stratigraphy)Internal combustion engineEngineeringPower (physics)Controller (irrigation)InverterComputer scienceSeries and parallel circuitsVoltageElectrical engineeringTorqueAlgorithm

Abstract

fetched live from OpenAlex

A voltage source inverter is designed and controlled in such a way to emulate similar characteristics of a series hybrid electric vehicle powertrain. The major mechanical and electrical parts of a typical series HEV are modeled mathematically and the model is fed to the VSI as reference signals to produce the same output power characteristics as in a real HEV, while more emphasis is on electric power generation characteristics. A synchronous generator-coupled with the internal combustion engine-is modeled represented by model 2.1 of the IEEE Std. 1110-2002. For experimental validation, the algorithm is implemented in dSpace using the DS-1103 controller.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score0.690

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 head0.217
Teacher spread0.198 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

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