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Record W2971502107 · doi:10.1049/iet-est.2018.5097

ICE/HPM generator range extender for a series hybrid EV powertrain

2019· article· en· W2971502107 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIET Electrical Systems in Transportation · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsMagna International (Canada)
Fundersnot available
KeywordsPrime moverAutomotive engineeringGenerator (circuit theory)Range (aeronautics)Battery (electricity)PowertrainBattery packHybrid powerAuxiliary power unitElectric generatorEngineeringRectifier (neural networks)Permanent magnet synchronous generatorPower (physics)Electrical engineeringMechanical engineeringComputer scienceTorqueMagnetAerospace engineeringVoltagePhysics

Abstract

fetched live from OpenAlex

This study discusses an optimised auxiliary power unit for applications in series hybrid electric vehicles (SHEVs). The auxiliary power source consists of an internal combustion engine (ICE) and a hybrid permanent magnet (HPM) generator. The ICE acts as a prime mover to the HPM generator the electrical output of which is connected to the vehicle DC‐link via a passive rectifier. The vehicle primary energy is supplied by a ZEBRA battery system while the ICE/HPM generator provides a range extension. The SHEV performance is evaluated over some driving cycles using performance indicators such as driving range, fuel consumption, emissions and, battery utilisation. A dynamic model of the ICE/HPM generator system is developed and a vehicle range, with consideration of the battery dynamics, is numerically evaluated via a simulation platform. The predicted results are compared with measurements from a laboratory prototype HPM generator system, which shows a good agreement hence validating the models and simulation platform.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.298
Threshold uncertainty score0.752

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 head0.012
GPT teacher head0.245
Teacher spread0.233 · 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