Design and Development of a Smart Control Strategy for Plug-In Hybrid Vehicles Including Vehicle-to-Home Functionality
Why this work is in the frame
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Bibliographic record
Abstract
Plug-in hybrid electric vehicles (PHEVs) are seen to be a step forward in transportation electrification, to replace internal combustion engine (ICE)-based conventional vehicles. However, to consider the vehicle-to-home (V2H) and home-tovehicle (H2V) capabilities, new energy control strategy has to be developed to avoid new peaks consumption. This paper presents a novel controller based on fuzzy logic, which integrates an objective state-of-charge (SoC) for V2H application. The V2H capability is used when the PHEV is connected to the home to help the grid to meet the household loads during peak period. The SoC objective is the minimum SoC that the PHEV has to have when the driver connects the PHEV to the home. The proposed controller is applied on fourth different scenario.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it