Modeling and Control of Multiphase Interleaved Fuel-Cell Boost Converter Based on Hamiltonian Control Theory for Transportation Applications
Bibliographic record
Abstract
This article presents a multiphase interleaved boost converter supplied by a fuel-cell (FC)/reformer power source for highly dynamic transportation applications. A control theory based on the Hamiltonian function approach is considered. Using the port-controlled Hamiltonian system, we propose simple solutions to the dynamic performance and convergence problems when an interaction occurs between the power sources and constant power loads. To corroborate the proposed control law, an FC boost converter (2.5-kW two-phase interleaved converter) is used and investigated in the laboratory. The methanol FC system is composed of a fuel reformer reactor that transforms water and methanol liquid fuel into hydrogen gas to a polymer electrolyte membrane FC stack (2.5 kW, 50 V). The studied control approach is realized by digital calculation using a MicroLabBox controller board (dSPACE platform). The simulation using the MATLAB/Simulink program and the experimental results validate that our proposed solution is an excellent control algorithm for highly dynamic power-load cycles.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".