Optimal Battery Control and Performance Enhancement with Fuzzy Logic Maximum Power Point Tracking in Solar PV System

The amount of electric power generated by a solar photovoltaic system depends on various interconnected factors, such as the levels of solar irradiance and the operating temperature of the cells. Consequently, the implementation of maximum power point tracking technique (MPPT) is essential to attain the highest PV system power output, independent of environmental variations. This research suggests a fuzzy charge controller based on a maximum power point tracking (MPPT) for power extraction from a solar photovoltaic (PV) to efficiently charge a battery storage system. The study explores a photovoltaic system with solar panels, MPPT technique, and a DC–DC buck converter utilizing the fuzzy logic control (FLC) algorithm to charge a 48 V battery. The research involves a comparative analysis between two MPPT techniques, namely Perturb and Observe (P&O) and FLC algorithm along with battery charge controllers. Simulation results reveal that the FLC algorithm demonstrates the fastest response time under standard and variable test conditions, minimal start-up fluctuations, and the highest overall efficiency.