Battery electric bus transit system optimization with battery degradation and energy consumption uncertainty
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
Implementing battery electric buses (BEBs) in transit systems offers a sustainable mobility solution. However, BEB systems present challenges related to battery degradation, fluctuating energy consumption, and limited charging resources. This study develops an optimal lifecycle model for BEB system configuration, addressing charging schedules, component sizing, and resource allocation. The model incorporates battery degradation and uncertainties in energy consumption through a deterministic multi-stage optimization approach, followed by a stochastic model to account for energy consumption uncertainty. The application of a real-world transit network highlights that neglecting battery degradation and energy consumption uncertainty could lead to substantial operational disruptions. Furthermore, decisions regarding battery replacement throughout the BEB system usage lifecycle do not adhere to a standard pattern and are influenced by charging decisions. Sensitivity analysis highlights that doubling the battery degradation rate raises system costs by 20.7%, while a 30% fluctuation in battery costs substantially increases costs by up to 52.4%.
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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 | 0.001 | 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