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An FPGA-based Real-Time Simulation of a Hybrid Fuel Cell/Battery Source

2021· preprint· en· W3209241263 on OpenAlexaff
Karim Meddah, Tarek Ould‐Bachir, Mohamed Becherif, Amel Benmouna

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsField-programmable gate arrayComputer scienceBattery (electricity)Representation (politics)Real-time simulationRange (aeronautics)Euler methodBackward Euler methodDifferential equationPower (physics)Computational scienceEuler's formulaEuler equationsSimulationEmbedded systemMathematicsEngineering

Abstract

fetched live from OpenAlex

This paper presents a new approach for the modeling and real-time simulation of an embedded hybrid power source comprised of a fuel cell (FC) and a battery. The proposed modeling is based on a state-space-like representation of the system equations obtained from the modified-augmented nodal analysis. Systematic formulation of system equations is presented and the solution to the non-linear equations are discussed. The proposed model was implemented on an entry level Field Programmable Gate Array (FPGA), and demonstrates sub-microsecond simulation time-step capability. The real-time solution is obtained by precomputing the system equations for all switch state combinations, and using the backward Euler integration scheme for solving differential equations. A fixed point number representation is utilized for speed and reduced configurable resource utilization. Our results show a high fidelity of the proposed model over a wide range of simulation time-steps and switching frequencies.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.523
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.226
Teacher spread0.217 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2021
Admission routes1
Has abstractyes

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