IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 15, No 4: August 2026

Hybrid optimization of dual-port converter for electric vehicles

Vidhya Kuruvilla (Karunya Institute of Technology and Sciences)
Immanuel Selvakumar (Karunya Institute of Technology and Sciences)
Pandiyan Venkatesh Kumar (Vel Tech MultiTech Dr. Rangarajan Dr. Sakunthala Engineering College)



Article Info

Publish Date
01 Aug 2026

Abstract

Vehicle-to-grid (V2G) technology, which cuts peak loads, levels load, and modulates voltages but generates power system instability, accelerated by the growing popularity of electric-powered vehicles. This research suggests a unique three-level full-bridge non-isolated buck-boost bidirectional direct current (DC)-DC converter that integrates solar (photovoltaic (PV)) systems, vehicle batteries, and the power grid to charge plug-in electric vehicles (EVs). This converter is combined with hybrid Tasmanian-hawk optimization (HTHO). By enabling EV batteries to be charged concurrently from PV systems and the grid, the converter improves charging flexibility and efficiency. The exploration and exploitation phases of HTHO, a new method that combines elements of the Harris hawks and Tasmanian devil algorithms for optimization. Using a 69-node test system, the suggested methodology, which is implemented in MATLAB/Simulink, evaluates power quality improvements in controlled and bidirectional charging operations. At a total harmonic distortion (THD) value of 1.768%, which indicates minimal harmonic distortion in the signal and exceeds conventional optimization techniques, the suggested converter, which integrates with HTHO, enhances charging flexibility and efficiency and helps to preserve overall power system stability. The research strengthens EV charging infrastructure through the seamless integration of natural renewable resources, multi-method optimization, and efficient grid operation strategies.

Copyrights © 2026






Journal Info

Abbrev

IJAI

Publisher

Subject

Computer Science & IT Engineering

Description

IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like ...