A robust series-connected diode model tailored for perovskite solar cells

Accurate modeling of photovoltaic (PV) cells is essential for reliable predictions and the optimal design of hybrid energy systems. Although single diode, double diode, and triple diode models are effective for conventional solar cells, these models often fail when applied to perovskite solar cells (PSCs). This limitation results in a physically unrealistic diode ideality factor that exceeds the classical limit of 2. To address this issue, this study proposes a robust two-diode series-connected model specifically designed for PSCs to effectively capture their unique recombination phenomena while adhering to physical constraints. Parameters for the proposed model were rigorously extracted using hybrid metaheuristic optimization algorithms. Validation against multiple experimental datasets demonstrated significant improvements in accuracy, with the proposed model markedly outperforming traditional diode models in representing PSC I-V characteristics. Statistical validation using ANOVA and Tukey’s HSD confirmed the superiority of the proposed model, highlighting its enhanced predictive accuracy and practical suitability for PSC characterization.