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Development of a Series Hybrid Multirotor

2024· article· en· W4392740715 on OpenAlexaff
Nicholas Castellani, Francisco Pedrosa, Jay Matlock, Krzysztof Łowczycki, Patryk Widera, Kamil Zawadzki, Afzal Suleman

Bibliographic record

VenueJournal of Physics Conference Series · 2024
Typearticle
Languageen
FieldEngineering
TopicEngineering Applied Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMultirotorSeries (stratigraphy)Computer scienceEngineeringAerospace engineeringGeology

Abstract

fetched live from OpenAlex

Abstract Hybrid-electric power is an appealing technology for multirotor platforms due to its ability to enhance the range of the vehicle while providing low emissions and the precise thrust control required for vehicle stability. The development of a multirotor utilizing hybrid propulsion is an essential step for CfAR as it will be the basis of research on this technology in flight. The designed multirotor, MIMIQ (Modular Inertia Matching Quadcopter), is a 32kg quadcopter with a motor-to-motor diameter of 2.7m which will require a total of 3,700W of power to hover. This demand is primarily met by the series hybrid generator onboard which requires the battery to only supplement a portion of that power. At peak thrust however, the motors will demand 12,000W from the system. During these rapid bursts of energy the battery plays a critical roll in providing an immediate response to the power demand which the generator would not be able to provide otherwise. This multirotor is designed to accommodate a wide range of propulsion configurations to optimize performance. In addition, the mechanical characteristics are also intended to be easily adjustable. Parameters such as center of mass, inertia, and motor distance can be adjusted to mimic characteristics of future flight vehicles that implement hybrid systems. Before integration, ground tests were performed on various off-the-shelf hybrid generators in order to evaluate their performance and reliability to ensure that they are well suited for the MIMIQ. To characterize the different modes of operation an extensive performance map was pursued. A number of parameters were measured over time with the most important being load, power, and fuel consumption. It has been proven that at low loads the generator can provide power to the propulsion system while charging the onboard batteries. However, at higher loads both the generator and the battery pack are required to provide power. The tests demonstrated that the integration of a hybrid system into MIMIQ is possible. It was also verified that when the engine is integrated into MIMIQ, both the generator and batteries have to provide power simultaneously in all flight phases.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.004

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 head0.251
Teacher spread0.228 · 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 designBench or experimental
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

Citations2
Published2024
Admission routes1
Has abstractyes

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