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Record W2889164443 · doi:10.1109/wow.2018.8450895

A Wireless Power Transfer System with Reduced Output Voltage Sensitivity for EV Applications

2018· article· en· W2889164443 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsMcMaster University
Fundersnot available
KeywordsWireless power transferSensitivity (control systems)VoltageMaximum power transfer theoremElectronic engineeringElectrical engineeringCompensation (psychology)ConvertersPower (physics)InverterEngineeringComputer sciencePhysicsElectromagnetic coil

Abstract

fetched live from OpenAlex

This paper presents a design procedure for LCC-Series compensation network for Wireless Power Transfer (WPT) system for Electric Vehicle (EV) applications. DC-link voltage variations is common in the gird connected power converters due to using diode rectification. These voltage variations could be reflected to the load side in a WPT system. The main focus of this paper is to design the resonant circuit to minimize the output voltage sensitivity respect to the input voltage variations. The resonant network is also tuned to realize Zero Voltage Switching (ZVS) for the primary side inverter to minimize the switching losses. Furthermore, a Finite Element Analysis (FEA) is performed to calculate self and mutual inductances as well as core losses for magnetic couplers. In order to validate the feasibility of the proposed design, a 22 kW/85 kHz WPT system with circular magnetic couplers is simulated. According to the frequency domain analysis the proposed circuit has 32% less sensitivity to the input voltage variations in comparison with the conventional design.

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.

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: none
Teacher disagreement score0.828
Threshold uncertainty score0.988

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 head0.009
GPT teacher head0.203
Teacher spread0.194 · 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

Quick stats

Citations10
Published2018
Admission routes1
Has abstractyes

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