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Record W4229453180 · doi:10.1155/2022/5769224

Design of Coupling Coil Parameters for Wireless Charging Tram Based on Electromagnetic Safety

2022· article· en· W4229453180 on OpenAlexvenueno aff
Sanmu Xiu, Wenmei Hao, Zhou Ying, Fengyu Leng

Bibliographic record

VenueJournal of Advanced Transportation · 2022
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsnot available
FundersNational Key Research and Development Program of China
KeywordsCatenaryElectromagnetic coilWirelessElectromagnetic radiationElectromagnetic fieldElectromagnetic environmentPower transmissionElectrical engineeringCoupling (piping)Electromagnetic pulseTransmission (telecommunications)EngineeringElectromagnetic compatibilityComputer scienceElectronic engineeringPower (physics)TelecommunicationsPhysicsMechanical engineering

Abstract

fetched live from OpenAlex

As a new type of urban rail transit tram, wireless charging tram uses high frequency electromagnetic field to conduct inductive power transmission, which gets rid of the traditional overhead catenary network, but inevitably causes electromagnetic radiation to the surrounding environment. Research shows that excessive electromagnetic radiation will affect the normal operation of equipment and the safety of human body. This paper analyzes the structure and coil configuration of the dynamic charging system for wireless charging tram. Aiming at the problem of electromagnetic radiation, a mathematical model with minimum electromagnetic radiation as the target and system parameters as the constraint condition is established. Finally, the system parameters of the electromagnetic coupling mechanism of the wireless charging tram are designed and optimized. The simulation and experimental results show that the method can meet the operating requirements of the system and reduce the electromagnetic radiation to the surrounding environment.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.694

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 head0.010
GPT teacher head0.214
Teacher spread0.204 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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