Energy Consumption Analysis of High-Speed Trains under Real Vehicle Test Conditions
Bibliographic record
Abstract
The study collected statistics on the actual operation of national railway electric multiple units (EMUs) and compared the energy consumption of different EMU models at different speed levels. An important method for studying the relationship between speed and energy consumption of EMUs has been constructed based on group method of data handling to reflect how the energy consumption of different EMU models changes with speed. The energy consumption of CRH2 and CRH380A EMUs on flat and sloping lines was compared. Moreover, the start-up energy consumption of CRH2 and CRH380A EMUs was compared. The effect of the number of stops of CRH2 and CRH3 EMUs on energy consumption was analyzed. Furthermore, an idea for improving the general expression and calculation methods of traction energy consumption of EMUs was proposed. Finally, suggestions on the construction of a traction energy consumption information system were provided, and the selection of different high-speed EMU models and the reasonable determination of the operating speed were discussed.
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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 | 0.001 |
| 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 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".