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Record W1524997825 · doi:10.1109/apec.2015.7104520

Ultracapacitor/battery hybrid energy storage system with real-time power-mix control validated experimentally in a custom electric vehicle

2015· article· en· W1524997825 on OpenAlexafffund
Leonard Shao, Mazhar Moshirvaziri, Christo Malherbe, Andishe Moshirvaziri, Aliakbar Eski, Steve Dallas, Feisal Hurzook, Olivier Trescases

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectric and Hybrid Vehicle Technologies
Canadian institutionsGeneral Electric (Canada)University of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRegenerative brakeBattery (electricity)SupercapacitorAutomotive engineeringElectric vehicleEnergy storageBattery packElectrical engineeringAutomotive batteryPower (physics)Lithium iron phosphateTrickle chargingEngineeringPower densityComputer scienceBrakePhysicsElectrode

Abstract

fetched live from OpenAlex

This paper experimentally demonstrates the benefits of integrating ultracapacitors (u-cap) into a custom electric vehicle. The new hybrid energy storage system (HESS) includes a 25 kW four-phase dc-dc converter connected in between the 33.8 kWh lithium phosphate battery pack and the u-caps. By combining the high energy-density of the battery and the high power-density and cycle-life of u-caps, the HESS delivers high power while minimizing peak battery current during acceleration and regenerative braking. Real-time power-mix control within the HESS using the dc-dc converter is the main challenge addressed in this project. In one experimental test-drive, the HESS not only improves the maximum power of the EV from 38 kW (50 hp) to 52 kW (70 hp), but also captures the majority of the regenerative braking energy, greatly reducing the stress on the battery pack.

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 categoriesMeta-epidemiology (narrow)
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 score0.275
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.182
Teacher spread0.176 · 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.

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

Citations11
Published2015
Admission routes2
Has abstractyes

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