Research on a Novel Hydraulic/Electric Synergy Bus
Bibliographic record
Abstract
In recent years, increasing concerns regarding environmental pollution and requirements for lower fossil fuel consumption have increased interest in alternative hybrid powertrains. As a result, this paper presents a novel hydraulic/electric synergy powertrain with multiple working modes. The three energy sources (i.e., engine, battery, and hydraulic accumulator) in this configuration are regulated by a dual planetary gear set to achieve optimal performances. This paper selects the component sizes of a hybrid electric vehicle (HEV), a hydraulic hybrid vehicle (HHV), and a hydraulic/electric synergy vehicle (HESV), based on the dynamic performance of a target vehicle (TV). In addition, this paper develops the forward simulation models of the four aforementioned vehicles in the MATLAB/Simulink/Driveline platform, in which the fuel economy simulations are carried out in relation to the Chinese urban bus cycle. The simulation results show that the fuel consumption of the three hybrid vehicles is similar, but much better than, that of the TV. Finally, based on the operating cost calculations over a five-year working period, the lowest cost ranges of the three hybrid vehicles are determined, which provides a method for choosing the optimal hybrid scheme.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".