Effect of Driving Cycles on Emissions from On-Road Motorcycles
Bibliographic record
Abstract
Chassis dynamometer testing was conducted with three on-highway motorcycles produced for the North American market with engine displacements of 296 cc, 749 cc and 1198 cc to better inform criteria pollutant emissions inventories. The motorcycles were tested using US Tier 2 certification fuel over the Federal Test Procedure (FTP), World Motorcycle Test Cycle (WMTC) and a cycle based on a sample of real-world motorcycle driving, informally referred to as the ‘Real World Driving Cycle’ (RWDC). Emissions characterization includes composite, individual test phase and 1Hz cumulative results for various criteria pollutants for each test cycle. Overall, it was found that the higher peak speed rates and peak torque levels observed during the RWDC are more fully represented in the WMTC than the FTP. The use of the WMTC and RWDC cycles generally translated into higher emissions rates compared to the FTP and in particular for nitrogen oxides and carbon monoxide. As well, the three test drive cycles used different shift schedules which in addition to the different characteristics of the drive cycles also had an impact on emissions.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".