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Record W2919294406 · doi:10.1049/pbpo115e_ch13

DC-based EVs and hybrid EVs

2018· book-chapter· en· W2919294406 on OpenAlexaff
Ruoyu Hou, Jing Guo, Ali Emadi

Bibliographic record

VenueInstitution of Engineering and Technology eBooks · 2018
Typebook-chapter
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsConvertersCommercializationCapacitorDual (grammatical number)EngineeringElectrical engineeringPower (physics)InverterDual modeNetwork topologyComputer sciencePower electronicsElectronicsElectronic engineeringAutomotive engineeringComputer networkVoltageBusiness

Abstract

fetched live from OpenAlex

In this chapter, the power electronics converters and inverter in vehicle application are introduced. Several possible topologies for PFC, isolated DC/DC converter, APM, and APF are presented. The practical design of DC bus bars and the selection of power switch devices and DC-link capacitors are given. Finally, the state-of-theart topological reconfigurations of DC systems in electrified vehicles are presented. One of the biggest challenges for the next generation of power electronic systems in vehicle application will be the cost reduction to provide more affordable solutions. This has become one of the major barriers for electrified vehicle for mass commercialization. These dual-mode integration approaches are dedicated to vehicle application and can reduce the cost, size, and weight of the system. Therefore, they will also help promoting and accelerating the paradigm shift to the transportation 2.0.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.026
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0260.010

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 head0.011
GPT teacher head0.215
Teacher spread0.204 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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