Assessment of energy efficiency of battery electric buses in cold regions
Bibliographic record
Abstract
This study examines the energy consumption and regenerative braking efficiency of battery electric buses (BEBs) using real-world data from Montreal’s public transit network. Results show significant seasonal variations, with winter having the highest energy consumption due to heating demands and adverse road conditions, while summer has the lowest due to reduced auxiliary energy use and smoother traffic flow. Regenerative braking is most effective at mid-speed ranges (30–50 km/h), with peak efficiency in warmer months and a decline in winter, emphasizing environmental influences. Auxiliary heating and cooling demands significantly impact energy efficiency, especially in extreme climates. Cost analysis confirms BEBs’ lower operating costs compared to diesel and hybrid buses. Optimizing BEB operations requires improvements in route planning, fleet scheduling, and charging strategies. By addressing previous data limitations, this study provides insights to enhance BEB efficiency and support their broader adoption in sustainable public transit systems.
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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 | 0.001 |
| 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 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".