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Stability Enhancement of Hybrid Fuel Cell-Battery-Supercapacitor Systems Using a Hamiltonian Control Approach

2025· article· W7127300998 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicControl and Stability of Dynamical Systems
Canadian institutionsMcMaster University
Fundersnot available
KeywordsControl theory (sociology)Test benchNonlinear systemTransient (computer programming)Electric power systemEnergy storageHamiltonian systemEnergy managementHybrid systemNonlinear control

Abstract

fetched live from OpenAlex

This paper presents a Hamiltonian control law to enhance the stability and performance of a hybrid energy storage system (HESS) composed of a proton exchange membrane (PEM) fuel cell, lithium-ion battery, and supercapacitor. The control design is based on port-Hamiltonian system theory, enabling dynamic energy management among sources while maintaining global system stability. A nonlinear control law is developed using damping-injection techniques to regulate the DC bus voltage, ensure optimal power sharing, and respect power and energy constraints of each component. The strategy allocates fast dynamics to the supercapacitor, medium response to the battery, and slow dynamics to the fuel cell, achieving efficient energy coordination. Experimental validation is performed using a dSPACE controlled test bench with real-time monitoring. Results confirm that the proposed method ensures fast transient response, smooth voltage regulation, and robust operation under sudden load variations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.797
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.206
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it