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Record W4251072609 · doi:10.32920/ryerson.14663187

Essence Electrical Power System Modelling & Simulation

2021· preprint· en· W4251072609 on OpenAlexaff
Ijaz Mansoor Qureshi

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicSpacecraft Design and Technology
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBattery (electricity)Photovoltaic systemPower (physics)Electric power systemState of chargeSolar irradianceElectric powerElectrical engineeringComputer scienceAutomotive engineeringAerospace engineeringEnvironmental scienceEngineeringMeteorologyPhysics

Abstract

fetched live from OpenAlex

The following paper outlines and details both the modelling and simulation of the electrical power system employed on ESSENCE. ESSENCE is a low earth orbiting 3U CubeSat with GOMSPACE P110 PV cells as the primary source of power generation. The PV cells are analyzed under varying ambient conditions and resulting output parameters are identified and recorded. Each step of the modelling process is documented as well as reporting of assumptions made and resulting errors that are identified. A solar irradiance model is also developed to determine solar radiation that is incident upon the PV cell surface. With the radiation model and PV model, simulations are ran to determine power generation capabilities through orbit using pre-built simulations. The final stage to the electrical system that is analyzed includes power management and power storage onboard ESSENCE. A power distribution unit is developed to either charge or discharge the battery as loads are varied and finally, a battery state of charge and charge level model is built. Integrations tests are conducted to determine net power draws, both generation and loads through multiple orbits. The resultant battery state is reported upon conclusion of simulation.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.014
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.002

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 head0.023
GPT teacher head0.234
Teacher spread0.211 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2021
Admission routes1
Has abstractyes

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Same topicSpacecraft Design and TechnologyFrench-language works237,207