High-Efficiency Energy Conversion Using QESCI Converter and ANN-EGTO-Based MPPT Strategy for Propulsion of EV System
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The rising demand for sustainable and efficient Electric Vehicles (EVs) propulsion systems has accelerated the improvement of smart power conversion and control schemes for solar-powered applications. Hence, this work proposes an advanced energy conversion system for EVs that integrates a Quadratic Enhanced SEPIC with Switched Coupled Inductor (QESSCI) converter and a Brushless DC (BLDC) motor drive. The QESSCI converter is utilized for stepping up the inherently low and fluctuating output of the Photovoltaic (PV) array into a stable high-voltage DC supply. An Enhanced Gorilla Troops Optimization (EGTO), combined with an Artificial Neural Network (ANN)-Maximum Power Point Tracking (MPPT) controller is utilized for fast and accurate tracking of the ideal operating point in variable climate circumstances. The speed of the BLDC motor is driven via a Three-Phase Voltage Source Inverter (3
VSI) while implementing a Proportional Integral (PI) controller for regulating the BLDC motor speed. Furthermore, a bidirectional DC-DC converter is employed to manage power flow among the DC bus and the battery, allowing energy storage during surplus PV generation and supplying power when solar energy is insufficient. The proposed architecture using MATLAB/Simulink demonstrate high converter efficiency of 95.62%, accurate tracking of PV output, energy management, and overall improvement in the overall system performance efficiency.
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