Range and Battery Depletion Concerns with Electric Vehicles
Bibliographic record
Abstract
This study investigates the effects of the range of a battery electric vehicle (EV) by using questionnaire data. The concern about battery depletion changes according to charging station deployment. Firstly, the methodology for deriving the probabilistic distribution of the daily travel distance is developed, which enables us to analyze people’s tolerance of the risk of battery depletion. Secondly, the desired range of an EV is modeled. This model considers the effect of changing charging station deployment and can analyze the variation in the desired range. Then, the intention of a household to purchase an EV is analyzed by incorporating range-related variables. The results show that people can live with a risk of battery depletion of around 2% to 5%. The deployment of charging stations at large retail facilities and/or workplace parking spaces reduces the desired range of an EV. Finally, the answers to the questionnaire show that the probability of battery depletion on a driving day has little effect on the intention to purchase an EV. Instead, people tend to evaluate the range by itself or directly compare it with their desired range.
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 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".