Hamiltonian-Based Approach to Enhance the Stability of Hybrid Fuel Cell and Supercapacitor Sources
Bibliographic record
Abstract
This paper aims to study an improved large-signal stability for fuel cell (FC) and supercapacitor (SC) hybrid sources, employing the enhanced Hamiltonian control law. This novel approach addresses the inherent challenges in the dynamic operation of such hybrid systems, characterized by rapid load changes [i.e., constant power load (CPL)] and energy fluctuations. Grounded in energy-based control theory, the Hamiltonian control law accurately manages the energy exchange between the FC, SC, and external load aiming to improve system stability and response efficiency. A comprehensive test bench setup, including a real FC, an SC bank, and programmable loads to simulate the electrical load [i.e., CPL, constant resistive load (CRL), and constant current load (CCL)], was developed to evaluate performance under various operational conditions. The results demonstrate that Hamiltonian-based control significantly enhances the system's damping properties, ensuring a smoother response to load variations and enhanced stability across different scenarios.
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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 | 0.000 |
| 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) | 0.001 | 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".