Dynamic modelling and simulation of a multi-regime hybrid vehicle powertrain architecture
Bibliographic record
Abstract
In this work, the dynamic model of a multi-regime hybrid vehicle powertrain architecture is presented. The study focuses on the formulae governing the operation of the planetary gear systems in the powertrain and on the performance of a more complex heavy-duty vehicle with varying loading conditions. The model is compared with models of the Toyota Hybrid System, a generic full-parallel design, and a conventional powertrain, all implemented for a commercial delivery vehicle in the ADVISOR simulation software. Computer simulations in ADVISOR compare the performance of the various designs, using fuel consumption as the performance metric, for four different drive cycles common for this vehicular application. The results demonstrate that the multi regime architecture provides significantly improved performance to that of the conventional and THS design and comparable performance to that of the full parallel hybrid design. The study confirms that the multi-regime architecture presents unique advantages for wide-ranging road loads and vehicle payloads and that multi-regime designs likely represent the future of hybrid vehicle technology.
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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 | 0.000 | 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".