Assessing the impact of an electric bus duty cycle on battery pack life span
Bibliographic record
Abstract
A methodology to assess the capacity fade due to battery degradation for electric buses with an in-depot charging strategy is proposed in this paper. An electrochemical model of an electric bus battery pack is used to evaluate the degradation associated with the change in lithium concentration at the negative electrode as a function of battery utilization for a given cycle. The battery utilization is calculated through a power consumption model from a typical bus driving pattern. In order to show the impact of degradation on the battery state-of-charge, two scenarios emulating a fully loaded and an unloaded electric bus are simulated. It is estimated that operating the E-buses fully loaded shortens the battery lifetime by 104 days over 7.6 years compared to an unloaded case, with both scenarios using the same route and driving conditions. Battery degradation is shown to have a significant impact on the battery state-of-charge, and accounting for it is crucial in long-term charging infrastructure planning.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".