Wireless Opportunity Charging as an Enabling Technology for EV Battery Size Reduction and Range Extension: Analysis of an Urban Drive Cycle Scenario
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Opportunity charging of electric vehicles (EVs) during brief stops is an important application of wireless power transfer (WPT). Irrespective of the specific WPT technology used, it is possible to quantify the effect of opportunity charging on EVs using energy calculations. This paper presents an analysis of the potential reduction in battery size and extension in EV range enabled by opportunity charging, using urban driving cycle data and various charging power levels. Traction power expended for acceleration, and to overcome air drag and rolling friction are considered. Depending on the extent of opportunity charging, battery size reduction from 6% to 85% is possible. Alternatively, retaining the battery size at its base value, a range extension between 7% and 600% is realizable. Although the results are shown for a particular velocity profile, the generalized analysis method presented in this paper can cater to various types of driving cycles.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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