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<p>As the world seeks for transition to sustainable energy sources, Photovoltaic (PV) systems have become central to renewable energy advantages. Integrating PV technology with Electric Vehicle (EV) charging infrastructure and grid systems is seen as a potential solution for reducing greenhouse gas emissions. This paper addresses these challenges by developing an advanced PV power management system that combines innovative power electronics and intelligent control technique. A novel Active Quadratic Switched Inductor DualFlex Boost (AQSIDFB) converter is designed to enhance voltage of PV with high gain, improve conversion efficiency, under varying load and weather conditions. To further optimize energy extraction from PV array, the system incorporates an Improved Snake Optimized Recurrent Neural Network (RNN) algorithm, for accurately locating the MPP. For EV charging, the PV-generated power is processed through a three-phase Voltage Source Inverter (VSI), which drives the Brushless DC (BLDC) motor of EV. A Proportional-Integral (PI) controller manages motor, providing precise and efficient energy utilization. Moreover, grid and storage integration supports in dynamically managing the power flow to ensure stable operation of the EV motor. Also, for managing the power flow of battery, the bidirectional battery is integrated, which charge and discharge according to the battery requirement. The validation of developed work is performed using MATLAB and the findings prove that the designed converter accomplishes higher efficiency of (96.16%) with tracking accuracy of (98.5%) with assistance of optimized RNN based MPPT.</p>

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PV and Grid-Integrated Power System for Electric Vehicle Motor Using Advanced Dualflex Boost Converter

  • 期刊论文

  • 发表日期：

    2025年12月3日

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  • D. Karthikeyan,
  • Vinod Kumar Shukla,
  • S. Sreedevi

摘要

As the world seeks for transition to sustainable energy sources, Photovoltaic (PV) systems have become central to renewable energy advantages. Integrating PV technology with Electric Vehicle (EV) charging infrastructure and grid systems is seen as a potential solution for reducing greenhouse gas emissions. This paper addresses these challenges by developing an advanced PV power management system that combines innovative power electronics and intelligent control technique. A novel Active Quadratic Switched Inductor DualFlex Boost (AQSIDFB) converter is designed to enhance voltage of PV with high gain, improve conversion efficiency, under varying load and weather conditions. To further optimize energy extraction from PV array, the system incorporates an Improved Snake Optimized Recurrent Neural Network (RNN) algorithm, for accurately locating the MPP. For EV charging, the PV-generated power is processed through a three-phase Voltage Source Inverter (VSI), which drives the Brushless DC (BLDC) motor of EV. A Proportional-Integral (PI) controller manages motor, providing precise and efficient energy utilization. Moreover, grid and storage integration supports in dynamically managing the power flow to ensure stable operation of the EV motor. Also, for managing the power flow of battery, the bidirectional battery is integrated, which charge and discharge according to the battery requirement. The validation of developed work is performed using MATLAB and the findings prove that the designed converter accomplishes higher efficiency of (96.16%) with tracking accuracy of (98.5%) with assistance of optimized RNN based MPPT.