Work

Enhanced wireless power transfer for electric vehicles: A 7.2 kW ANN-based MPPT approach with LCC-LCC compensation topology

Year: 2025

Type: article

Abstract: Optimizing electric vehicle charging via wireless power transfer is achievable through various control strategies. One effective method involves integrating an Artificial Neural Network based Maximum Power Point Tracking controller with a double-sided LCC compensation topology. This system, designed for a 7.2 kW inductive power transfer operating at 80 kHz , harnesses solar energy as its primary input. The ANN-based MPPT controller is trained to establish the optimal duty cycle for the DC-DC converter. It accomplishes this by learning the intricate relationship between photovoltaic voltage , current, and the maximum power point. This approach ensures robust MPP tracking performance even in diverse environmental conditions, including partial shading and noise. Furthermore, the double-sided LCC compensation network significantly boosts the system's power transfer capability and overall efficiency. The proposed system was meticulously modeled and simulated using MATLAB/Simulink . Simulation outcomes confirm that the combined ANN-based MPPT controller and double-sided LCC compensation deliver superior power transfer efficiency and enhanced output performance when compared to conventional WPT systems used for EV charging.

Source: Energy Reports

DOI: 10.1016/j.egyr.2025.08.039

Authors: Bachhati Latha, Mohammad Mujahid Irfan, Butukuri Koti Reddy

Institution: SR University

Language: English

Topic: Wireless Power Transfer Systems

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $3,040