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<p>The increasing demand for electric vehicle (EV) technology and the subsequent decline in the cost of photovoltaic (PV) systems have led to the recent commercial manufacturing of solar-powered battery charging stations for EVs. Increasing environmental consciousness and technological advancements are two possible explanations for the meteoric rise in the popularity of EVs. A PV-powered off-grid EV charging station based on a 48&#xa0;V DC bus voltage is developed in this study. In addition, EV battery energy storage (EVBES) units are utilized to counteract the environment’s unpredictability. Hence, this research introduces a new and effective Lyapunov-based model reference adaptive maximum power point tracking (MPPT) controller based off-grid charging station reinforced with an EVBES. The controller is designed to accurately track and harvest solar PV system’s peak power output, even amid sudden changes in weather conditions. The inclusion of the EVBES unit further enhances the charging station’s feasibility and dependability. The proportional-integral controller is employed to optimize PV power flow to the EVBES unit, ensuring efficient utilization of PV electricity and optimal charging of the battery. The proposed system is thoroughly examined, assessed, and compared with Incremental conductance, Artificial neural networks, and Perturb and Observe MPPT strategies. The outcomes obtained indicate that the suggested control approach performs well under sudden changes in atmospheric circumstances, namely in power balance management and MPPT control. Notably, it achieves high efficiency (99.72%), minimal steady-state power oscillations (0.18&#xa0;W), and fast convergence time (0.002s). Finally, the applicability of the implemented approach in real-world scenarios is demonstrated by real-time verification on the OPAL-RT simulator.</p>

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Efficient Novel Lyapunov-MRAC Driven Maximum Power Harvesting and Control Strategy for SPV-based EV Battery Storage System

  • 期刊论文

  • 发表日期：

    2025年10月18日

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  • Saibal Manna,
  • Vivek Saxena,
  • Bhupender Sharma

摘要

The increasing demand for electric vehicle (EV) technology and the subsequent decline in the cost of photovoltaic (PV) systems have led to the recent commercial manufacturing of solar-powered battery charging stations for EVs. Increasing environmental consciousness and technological advancements are two possible explanations for the meteoric rise in the popularity of EVs. A PV-powered off-grid EV charging station based on a 48 V DC bus voltage is developed in this study. In addition, EV battery energy storage (EVBES) units are utilized to counteract the environment’s unpredictability. Hence, this research introduces a new and effective Lyapunov-based model reference adaptive maximum power point tracking (MPPT) controller based off-grid charging station reinforced with an EVBES. The controller is designed to accurately track and harvest solar PV system’s peak power output, even amid sudden changes in weather conditions. The inclusion of the EVBES unit further enhances the charging station’s feasibility and dependability. The proportional-integral controller is employed to optimize PV power flow to the EVBES unit, ensuring efficient utilization of PV electricity and optimal charging of the battery. The proposed system is thoroughly examined, assessed, and compared with Incremental conductance, Artificial neural networks, and Perturb and Observe MPPT strategies. The outcomes obtained indicate that the suggested control approach performs well under sudden changes in atmospheric circumstances, namely in power balance management and MPPT control. Notably, it achieves high efficiency (99.72%), minimal steady-state power oscillations (0.18 W), and fast convergence time (0.002s). Finally, the applicability of the implemented approach in real-world scenarios is demonstrated by real-time verification on the OPAL-RT simulator.