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Record W4399723469 · doi:10.1088/2634-4505/ad590a

Sufficiency of level 1 charging to meet electric vehicle charging requirements

2024· article· en· W4399723469 on OpenAlexafffundabout
Aviv Fried, Blake Shaffer, Sara Hastings‐Simon

Bibliographic record

VenueEnvironmental Research Infrastructure and Sustainability · 2024
Typearticle
Languageen
FieldEngineering
TopicElectric Vehicles and Infrastructure
Canadian institutionsUniversity of Calgary
FundersAlberta Innovates
KeywordsElectric vehicleAutomotive engineeringElectrical engineeringAeronauticsEngineeringPower (physics)Physics

Abstract

fetched live from OpenAlex

Abstract As electric vehicle (EV) deployment increases there is increasing attention to meeting charging needs. We analyze 13 months of real world driving and charging data for 129 battery electric vehicles in Calgary, Canada to evaluate the potential for home-based level 1 charging to deliver the energy needed to satisfy observed driving demand. We find that 29% of vehicles can have their energy needs met entirely with level 1 charging. A further 53% of vehicles in our sample require only occasional supplementary level 3 charges and only a small minority of vehicles require 12 or more supplementary level 3 charges across the sample period. Across all vehicles the median ratio of charge energy that can be shifted to level 1 charging is 0.99. These results challenge the assumption that level 2 charging access is required for convenient operation of EVs and offer a partial solution to enable broader EV charging access and reduce the need for near term electrical panel or distribution grid upgrades.

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)0.002
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.017
GPT teacher head0.288
Teacher spread0.271 · 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 designObservational
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

Citations0
Published2024
Admission routes3
Has abstractyes

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