Evaluation and optimization of a hybrid urban Microbus
Bibliographic record
Abstract
Urban buses have nowadays an important challenge which is to respect the local nuisances such as air pollution and noise while offering to their passengers a high level of accessibility and comfort. Hybrid drivelines are one potential alternative to respond to these constraints. In that context, the Transport and Environment Laboratory (LTE) of the INRETS is collaborating with an urban buses manufacturer with the aim to develop and optimize a 5.5 m, 22 passenger series hybrid plug in microbus. This paper presents the first phases of our research. Firstly, the microbus components description, the actual energy management and the traction motor working are presented. Secondly, the measurement phase carried out on the GRUAU's test bus site in Laval elaborates a start point to understand the various energy flows. After that, the model of the microbus's processing is developed using the LTE library VEHLIB and validated with measurements. Thus, some suggestions about new energy management laws are proposed in order to optimize the consumption of the internal combustion engine together with the battery behavior.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".