Leveraging normal distribution and fuzzy <i>S</i> -function approaches for solar cell electrical characteristic optimization

Abstract This study evaluates the performance of a silicon-based solar cell across a range of temperatures (5, 15, 30, 50, 60, and 70°C) to understand the impact of temperature variation on its electrical parameters. Key performance indicators such as current density ( J sc ), open-circuit voltage ( V oc ), fill factor (FF), and efficiency ( η ) were measured at each temperature. The results show that the solar cell operates most efficiently at lower temperatures, with a peak efficiency of 0.55% at 5°C. As temperature increases, there is a noticeable decline in performance, with the efficiency dropping to 0.41% at 70°C. Current density values range from 3.52 mA/cm² at 5°C to 2.50 mA/cm² at 70°C, while open-circuit voltage decreases from 2.10 V at 5°C to 1.90 V at 70°C. Fill factor also exhibits a downward trend, reflecting the decreasing performance with higher temperatures. A statistical analysis using Statistical Package for the Social Sciences revealed mean values of 4.45 mA/cm² for current density, 1.93 V for voltage, and 3.87 for fill factor, with corresponding standard deviations and variances. Furthermore, a fuzzy S -function model was applied to account for uncertainty and variability in real-world conditions. The fuzzy model indicated an optimal efficiency of 0.89%, a lower efficiency bound of 0.47%, and an average efficiency of 0.43%. This combined approach, using both statistical and fuzzy analysis, provides valuable insights into the temperature sensitivity of silicon-based solar cells and underscores the importance of temperature management for maximizing efficiency.