Impacts of blended mode and charge-sustaining mode on the battery efficiency for a serial FC-PHEV
Bibliographic record
Abstract
This paper investigates the impact of two different real-time power energy management systems on the battery used in a serial topology of a Fuel Cell Plugin Hybrid Electric Vehicle (FC-PHEV): the blended mode and the charge-sustaining mode. With the blended mode, the FC contributes to the propulsion power when the power demand is high or when the battery is depleted. The charge-sustaining mode considered for this study allows the battery to be depleted in a first step. In a second step, the FC is used to maintain the battery energy within a narrow interval. Earlier designs of the two methods for FC-PHEV put emphasis on the vehicle dynamics control and the hydrogen energy saving, neglecting to consider their impacts on the battery pack efficiency. For the same rolling conditions, the simulation results with a lead-acid battery pack suggest that the charge-sustaining mode has the potential to improve the battery pack average efficiency compared to the blended mode. However, the charge-sustaining mode may require more hydrogen to achieve this improvement than what is needed when the blended mode is used.
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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 | 0.001 | 0.001 |
| 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".