High-Efficiency Energy Conversion Using QESCI Converter and ANN-EGTO-Based MPPT Strategy for Propulsion of EV System

The purpose of the current study is to suggest a novel energy conversion system for Electric Vehicles (EVs) incorporating a Quadratic Enhanced SEPIC with Switched Coupled Inductor (QESSCI) converter and a Brushless DC (BLDC) motor drive. The QESSCI converter is used to boost the low and fluctuating output of a Photovoltaic (PV) array to a constant high-voltage DC supply and, therefore, solves the uncertainty of the output. For improved energy harvesting, an Enhanced Gorilla Troops Optimization (EGTO) algorithm is coupled with an Artificial Neural Network (ANN) based Maximum Power Point Tracking (MPPT) controller, resulting in rapid tracking with high precision to the desired operating point while experiencing changing weather conditions.

The BLDC motor is driven via a Three-Phase Voltage Source Inverter (3VSI) with a PI controller that is responsible for ensuring accurate speed control. Additionally, a bidirectional DC-DC converter is designed to efficiently control power flow between the DC bus and the energy storage battery system. When there is PV surplus energy generation, it enables energy storage, and when there is a deficiency of solar energy, it supplies power. In this way, the proposed method increases the reliability and efficiency of the system. The proposed configuration aims to enhance the performance and sustainability of the propulsion systems of EVs.

Message: Hi FE, I need help with “High-Efficiency Energy Conversion Using QESCI Converter and ANN-EGTO-Based MPPT Strategy for Propulsion of EV System” in “Electrical Engineering”