Multi-Domain Device-Level Fuel-Cell Modeling and Real-Time Hardware Emulation for Marine Research Vessel Power System
Bibliographic record
Abstract
Marine research vessels (MRVs) are redesigned and refurbished to meet higher energy conversion efficiency and modular integration schemes while conforming to stronger environmental regulations. The proton exchange membrane fuel cell (PEMFC) is currently regarded as a potential power source for marine transportation applications due to its advantages of stability, sustainability, and zero emissions. This paper proposes a hierarchical scheme for the real-time hardware emulation of the MRV's power system and a comprehensive multi-domain model for PEMFCs. The PEMFC model is presented in the electrochemical, hydration, and thermal domains by ordinary differential equations considering the interactions and dynamics of each domain. Meanwhile, the multi-domain PEMFC model considers the implications of the fluctuating supply of the onboard hydrogen circulation system. Moreover, the dynamics of the lithium-ion battery stacks are represented by an equivalent circuit model which considers heat flux phenomena. In the case study, the DC-AC grid of the MRV's power system and electric propulsion system is configured using extensive electrification technology with an average model. The real-time hardware emulation is conducted on the Xilinx UltraScale+ VCU118 FPGA platform to execute the device-level and system-level behavior transients of the MRV. The results of the real-time hardware emulation have been validated against the full-scale hybrid MRV power system emulation over a wide operating range.
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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 | 0.001 | 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".