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Keywords

Wireless Charging, EVs, neural networks, IPT, Battery charge

Document Type

Research Paper

Abstract

This study concentrated on utilizing a neural network controller and inductive power transfer to enhance the electric vehicle charging. Electric vehicles are a key transportation system component since they lower fuel costs, noise levels, and carbon emissions. The charging duration and operational battery efficiency are the primary obstacles to wireless charging in electric vehicles. In the beginning, the system was designed. It included the primary side (grid, rectifier, DC-DC boost converter, and DC-AC high-frequency inverter), mutual inductance (one coil transmitter and six coils receiver), and secondary side (single-phase rectifier and battery pack). A neural network controller has been employed to control the current and voltage to get fast charging. The simulation design and control have been simulated using MATLAB 2022b. As a result, the DC-DC boost converter raised the transferred voltage to 800 V within 20 KHz to reduce the wave signal ripple. In comparison, a neural network controller kept the transfer voltage and constant current to 800 V and 100 A during charging from 10% to 100%. Moreover, a neural network controller worked on charging the system within 15 minutes as a fast-charging technique. Also, the behavior and value of the voltage transmitted to the battery have been verified.

References

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Highlights

Wireless charging for electric vehicles enables cable-free charging, enhancing convenience for drivers Recent advancements have significantly improved this technology, simplifying the charging process Enhancement of wireless charging efficiency for faster and more driver-friendly performance  DC-DC boost converter raised the transferred voltage to 800 V within 20 KHz to reduce the wave signal ripple.  The system's ability to charge the battery to 100% in just 900 seconds is a major advantage for wireless charging.

DOI

10.30684/etj.2025.155228.1872

First Page

631

Last Page

640

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