Wireless Power Transfer for Electric Vehicles with ANFIS Based MPPT for Solar System

Wireless Power Transfer (WPT) for Electric Vehicles (EVs) represents an new approach to convenient and efficient EV charging. Integrating WPT with a PV powered charging system can further enhance sustainability by reducing dependency on conventional energy sources. This paper presents a solar-based wireless charging system using an Adaptive Neuro-Fuzzy Inference System (ANFIS) for MPPT to optimize energy harvested from PV panels. ANFIS-based MPPT enables the system to dynamically adjust to changing irradiance conditions, maximizing energy transfer efficiency. The proposed scheme uses ANFIS to optimize PV panel power supply, ensuring a steady and reliable wireless charging output even in the varying environmental conditions. The results of the simulation show that this approach performs better than conventional MPPT methods, producing more efficiency and preserving ideal charging conditions. EVs may now obtain clean energy without physical connections thanks to the invention of this smart charging technology, which has potential uses in both off-grid and urban environments. Future research will concentrate on real-time deployment and investigating how environmental variables affect charging efficiency in various contexts.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-19
DOI
https://doi.org/10.5281/zenodo.14185285
Primary Topic
Wireless Power Transfer Systems
Type
article
Field-Weighted Citation Impact
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article

Wireless Power Transfer for Electric Vehicles with ANFIS Based MPPT for Solar System

Zenodo (CERN European Organization for Nuclear Research)
Wireless Power Transfer Systems
article

Wireless Power Transfer for Electric Vehicles with ANFIS Based MPPT for Solar System

article en

Abstract

Wireless Power Transfer (WPT) for Electric Vehicles (EVs) represents an new approach to convenient and efficient EV charging. Integrating WPT with a PV powered charging system can further enhance sustainability by reducing dependency on conventional energy sources. This paper presents a solar-based wireless charging system using an Adaptive Neuro-Fuzzy Inference System (ANFIS) for MPPT to optimize energy harvested from PV panels. ANFIS-based MPPT enables the system to dynamically adjust to changing irradiance conditions, maximizing energy transfer efficiency. The proposed scheme uses ANFIS to optimize PV panel power supply, ensuring a steady and reliable wireless charging output even in the varying environmental conditions. The results of the simulation show that this approach performs better than conventional MPPT methods, producing more efficiency and preserving ideal charging conditions. EVs may now obtain clean energy without physical connections thanks to the invention of this smart charging technology, which has potential uses in both off-grid and urban environments. Future research will concentrate on real-time deployment and investigating how environmental variables affect charging efficiency in various contexts.

Zenodo (CERN European Organization for Nuclear Research)
Istanbul Aydın University (TR), Univerzitet Union Nikola Tesla (RS)
Openalex Percentile: Top 68%
Wireless Power Transfer Systems
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