Optimisation and comparison of different powertrain layouts for parallel hybrid electric vehicles equipped with continuous transmission
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The development of an efficient hybrid electric vehicle (HEV) platform needs an optimal design of its powertrain layout. This study is concerned with parallel HEVs (PHEVs) equipped with continuous transmission. First, different types of continuous transmissions, including continuously variable transmission (CVT), power-split CVT (PS-CVT) and multi-fixed ratio PS-CVT (MF-CVT), are discussed and their simulation models are presented. Also, various combinations of these continuous transmissions with PHEV configurations (namely, pre-transmission and post-transmission configurations) are introduced. Then, for a given PHEV model, several powertrain layouts resulting from combining the considered continuous transmissions and PHEV configurations are optimised over a standard drive cycle. The optimised powertrain layouts are compared from different perspectives, for instance the vehicle fuel consumption, emissions and some dynamic performance measures. In particular, the sensitivity of the PHEV performance characteristics to the driving cycle pattern, when it is equipped with each optimised layout, is investigated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 it