Modeling and Control of Ejector-Based Hydrogen Circulation System for Proton Exchange Membrane Fuel Cell Systems
Bibliographic record
Abstract
Ejector-based proton exchange membrane fuel cells (PEMFCs) are of great interest due to their simplicity and feasibility. Thus, proton exchange membrane fuel cells are considered the most suitable technology for in-vehicle systems, industrial applications, etc. Despite the passive characteristics of the ejector, active control of the hydrogen supply system is needed to ensure sufficient hydrogen, maintain the stack pressure, and ensure effective entrainment. In this research, a novel semi-empirical model is proposed to accurately predict the entrainment performance of the ejector with an 80 kW fuel cell system. According to the precise semi-empirical model, the hydrogen supply system and the anode channel are modeled. Then, a fuzzy logic controller (FLC) is developed to supply sufficient and adequate gas flow and maintain the rapid dynamic response. Compared to the conventional proportional–integral–derivative controller, the fuzzy logic controller could reduce the anode pressure variability by 5% during a stepped case and 2% during a dynamic case.
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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".