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<p>This paper investigates the implementation of an integrated shunt active power filter (SAPF) to enhance power quality in solar-powered electric vehicles (EV<sub>s</sub>) charging stations by reducing harmonics generated during EV<sub>s</sub> charging. By lowering greenhouse gas emissions, solar-powered battery electric vehicles (BEV<sub>s</sub>) provide an eco-friendly option. The paper provides a technical overview of the evolution, current developments, and future prospects of solar BEV<sub>s</sub> charging infrastructure, addressing a critical gap in existing research. Despite their potential, these systems face challenges such as energy storage limitations, carbon emissions, and solar array maintenance. A comprehensive analysis of current solar EV<sub>s</sub> charging systems is presented, highlighting their benefits and drawbacks. The proposed system uses a radial basis function neural network (RBFNN)-based battery charge controller integrated with synchronous reference frame theory. Performance is evaluated using RBFNN and proportional–integral controllers. Results show that the RBFNN effectively reduces total harmonic distortion to 2.85%, improving overall power quality.</p>

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Solar electric vehicles charging station status: green charging station design to improve distribution system power quality

  • 期刊论文

  • 发表日期：

    2025年6月9日

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  • Ravinder Kumar

摘要

This paper investigates the implementation of an integrated shunt active power filter (SAPF) to enhance power quality in solar-powered electric vehicles (EVs) charging stations by reducing harmonics generated during EVs charging. By lowering greenhouse gas emissions, solar-powered battery electric vehicles (BEVs) provide an eco-friendly option. The paper provides a technical overview of the evolution, current developments, and future prospects of solar BEVs charging infrastructure, addressing a critical gap in existing research. Despite their potential, these systems face challenges such as energy storage limitations, carbon emissions, and solar array maintenance. A comprehensive analysis of current solar EVs charging systems is presented, highlighting their benefits and drawbacks. The proposed system uses a radial basis function neural network (RBFNN)-based battery charge controller integrated with synchronous reference frame theory. Performance is evaluated using RBFNN and proportional–integral controllers. Results show that the RBFNN effectively reduces total harmonic distortion to 2.85%, improving overall power quality.