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<p>Electric vehicles (EVs) are being increasingly recognized for their sustainability, but their charging is still problematic. The need for renewable energy to support EV charging and optimize grid performance is becoming increasingly critical. Henceforth, in this work, Photovoltaic (PV) system based Improved Trans Quasi-Z Source (ITQ-ZS) Boost converter with coupled inductor is proposed for effective charging of EV and providing sustainable energy to grid. A Modified Hermit Crab Optimized Recurrent Neural Network Maximum Power Point Tracking (MPPT) algorithm is employed to ensure supreme power extraction from PV under varying environmental conditions. Also, to boostthe output of PV into requirement level of EV battery and grid, a novel ITQ-ZS Boost Converter with coupled inductor is developed, facilitating seamless energy flow with higher efficiency. To manage the EV battery's charging and discharging processes, a Bidirectional DC-DC Converter is incorporated, regulated by a PI Controller for enhanced operational stability. For evaluating the performance of proposed converter and optimized MPPT approach in EV, MATLAB/Similink and experimental analysis are performed. From the findings it is known that with the aid of designed topology, higher efficiency of 95.2%, minimized losses and higher tracking efficiency of 99.6% are accomplished. Thereby, it offers a sustainable solution for EVs and grid, while ensuring improved efficiency and reduced environmental impact.</p>

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Optimized RNN MPPT-Controlled PV-Grid-Tied EV Charging Station Using Improved Trans Quasi Z-Source Boost Converter

  • 期刊论文

  • 发表日期：

    2025年4月23日

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  • J. Nivedita,
  • P. S. Manoharan

摘要

Electric vehicles (EVs) are being increasingly recognized for their sustainability, but their charging is still problematic. The need for renewable energy to support EV charging and optimize grid performance is becoming increasingly critical. Henceforth, in this work, Photovoltaic (PV) system based Improved Trans Quasi-Z Source (ITQ-ZS) Boost converter with coupled inductor is proposed for effective charging of EV and providing sustainable energy to grid. A Modified Hermit Crab Optimized Recurrent Neural Network Maximum Power Point Tracking (MPPT) algorithm is employed to ensure supreme power extraction from PV under varying environmental conditions. Also, to boostthe output of PV into requirement level of EV battery and grid, a novel ITQ-ZS Boost Converter with coupled inductor is developed, facilitating seamless energy flow with higher efficiency. To manage the EV battery's charging and discharging processes, a Bidirectional DC-DC Converter is incorporated, regulated by a PI Controller for enhanced operational stability. For evaluating the performance of proposed converter and optimized MPPT approach in EV, MATLAB/Similink and experimental analysis are performed. From the findings it is known that with the aid of designed topology, higher efficiency of 95.2%, minimized losses and higher tracking efficiency of 99.6% are accomplished. Thereby, it offers a sustainable solution for EVs and grid, while ensuring improved efficiency and reduced environmental impact.