design and performance analysis of fuzzy logic controller for solar photovoltaic system

This study presents a fuzzy logic controller (flc)-based maximum power point tracking (mppt) system for solar photovoltaic (pv) setups, integrating pv panels, a boost converter, and battery storage. while flc is known for its robustness in pv systems, challenges in battery charging and discharging efficiency can affect performance. the research addresses these challenges by optimizing battery charging, preventing overcharging, and enhancing overall system efficiency. the flc mppt system is designed to regulate the battery’s state of charge (soc) while evaluating system performance under varying solar irradiance and temperature conditions. the system is modeled and simulated using matlab/simulink, incorporating the pv system, mppt algorithm, and models for the pv module and boost converter. system efficiency is assessed under different scenarios, with results showing 97.92% efficiency under standard test conditions (stc) at 1000 w/m² and 25°c. additionally, mean efficiencies of 97.13% and 96.13% are observed under varying irradiance and temperature, demonstrating the effectiveness of the flc mppt in regulating output. the system also extends battery life by optimizing power transfer between the pv module, boost converter, and battery, ensuring regulated soc.