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Keywords

Wireless Charging, Electric Vehicle (EV), ANFIS, Battery Charging, Intelligent control

Document Type

Research Paper

Abstract

Wireless charging of electric vehicles (EVs) poses issues like power ripples that reduce battery lifetime. This study proposes a four-quadrant DC/DC chopper controlled by an adaptive neuro-fuzzy controller (ANFIS) for wireless EV charging. The system is modeled and simulated in Matlab/Simulink. Compared to a PI-PSO controller, the proposed ANFIS control reduced the ripple factor in power over half to about 0.7% and optimized stability and efficiency. Though settling time increased, the difference in rise time was negligible. Future work will improve dynamic response. The ANFIS-controlled DC/DC chopper enhances wireless charging performance with minimal power ripples for safe, efficient EV power transfer.

References

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Highlights

Wireless charging for electric vehicles presents notable advantages and associated challenges The technology minimizes reliance on cables, enhancing convenience for users By improving the overall experience, it may encourage wider adoption of electric vehicles Electric vehicles have varying charging rates, impacting recharge durations and capacities Techniques like fuzzy logic and genetic algorithms are used to refine the charging process

DOI

10.30684/etj.2024.146136.1673

First Page

1122

Last Page

1137

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