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Record W1996361377 · doi:10.1115/imece2010-38380

Vibration-Based Electromagnetic Energy Harvester

2010· article· en· W1996361377 on OpenAlexaff
Farid Ullah Khan, Farrokh Sassani, Boris Stoeber

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInnovative Energy Harvesting Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLIGAMultiphysicsMagnetMaterials sciencePlanarVibrationAcousticsVoltageElectrical engineeringFabricationPhysicsEngineeringFinite element methodStructural engineeringComputer science

Abstract

fetched live from OpenAlex

This paper presents the simulation, fabrication, and experimental results of a vibration-based electromagnetic power (EMPG) generator. A novel, low cost, one mask technique is used to fabricate the planar coils and the planar spring. This fabrication technique can provide an alternative for processes such as Lithographie Galvanoformung Abformung (LIGA) or SU-8 molding and MEMS electroplating. Commercially available copper foils of 20 μm and 350 μm thicknesses are used for the planar coils and planar spring, respectively. The design with planar coils on either side of the magnets provides enhanced power generation for the same footprint of the device. The device overall size is 1 cm3. Simulations of the modal analysis of the spring-mass system and the magnetostatic analysis of the magnetic field generated by the magnets are performed with COMSOL multiphysics®. Excitation of the EMPG at the fundamental frequency of 371 Hz and at 13.5 g base acceleration (base amplitude 24.4 μm) yields an open circuit voltage of 60.1 mV, as well as 46.3 mV load voltage and 10.7 μW power for a 100 Ω load resistance. At matching impedance of 7.5 Ω the device produced a maximum power of 23.56 μW and a power density of 23.56 μW/cm3.

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 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: Empirical
Teacher disagreement score0.360
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.179
Teacher spread0.174 · 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.

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

Citations3
Published2010
Admission routes1
Has abstractyes

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