Anti-idling systems for service vehicles: Modeling and experiments
Bibliographic record
Abstract
Vehicles are a major source of fuel consumption and air pollution. Any improvement in their efficiency impacts the environment and economy positively. Service vehicles such as food delivery trucks have many loading and unloading stops during their daily work cycle. In these stops, their auxiliary devices need to be active and hence the engines run at its idling speed resulting in extremely low fuel efficiency. A regenerative auxiliary power system is proposed for anti-idling of service vehicles. This system reduces the engine idling and maximizes the regenerative braking energy by utilizing an additional battery. In this paper, different system configurations and possible options for integration of regenerative auxiliary power system to the vehicle powertrain are studied. Backward-looking scalable powertrain components modeling approach is utilized to create a flexible system model which can be easily modified for different vehicles. The full system model has scalability and composability features. A library for common components used in service vehicles is developed for ease of development of such anti-idling systems. Hardware-in-the-loop tests and a prototype model of regenerative auxiliary power system have been utilized for the laboratory evaluation in order to validate the model and characterize the regenerative auxiliary power system components.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".