MétaCan
Menu
Back to cohort

Novel Integrated Electrical Architecture for Solar-Charged Electric Vehicles

2022· article· en· W4284892634 on OpenAlexaff
Danial Sadeghpour, Jennifer Bauman

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Battery Technologies Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPhotovoltaic systemElectrical engineeringVoltageCapacitorBattery (electricity)Electric vehicleComputer scienceEngineeringAutomotive engineeringTopology (electrical circuits)Power (physics)Physics

Abstract

fetched live from OpenAlex

Electric vehicles with on-board solar generation can offer extended driving range and lower grid charging needs than their standard electric vehicle counterparts. The main power electronic challenge in solar-charged electric vehicles (SEVs) is efficiently boosting the low solar voltage to the much higher traction battery voltage. This paper proposes a novel integrated electric architecture for SEVs which relies on a flying capacitor topology for both battery charging and driving the motor. The onboard solar energy is used to solve the common problem of balancing the flying capacitors, which at the same time helps the solar voltage boost problem since the solar power no longer needs to be boosted to the full battery voltage. Simulation results are presented for a 2.2 kW charging system with 150 V rms input voltage and maximum of 600 W available solar power. The current THD reduces from 1.37% to 0.36% when the PV structure integrates with the flying capacitor topology.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.015
GPT teacher head0.250
Teacher spread0.235 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same topicAdvanced Battery Technologies ResearchFrench-language works237,207