Comprehensive Parametric Analysis of Silicon Solar Cell Performance Through Computational Modelling: A Comparative Study of Monocrystalline and Polycrystalline Devices Using MATLAB and Python

Resumo

Accurate characterization of the diode ideality factor (n ) is fundamental to understanding recombination mechanisms and performance limitations in crystalline silicon solar cells. This study presents a comprehensive computational framework for analyzing the main photovoltaic parameters of semiconductor p–n junctions through dual-platform modeling using MATLAB and Python. Employing experimentally measured current–voltage (I–V) characteristics obtained via Sinton Instrument Suns-V_oc measurements from 5×5 cm² monocrystalline silicon test samples, the research investigates the influence of ideality factor variations (n=1.0 –5.0 ) on device performance within the single-diode equivalent circuit framework. Newton's iterative method was implemented in MATLAB to resolve the implicit transcendental I–V equation, enabling precise quantification of current dependencies on series resistance (R_s​=1 –3 Ω ), parallel resistance (R_p​=200 –1000 Ω ), photocurrent (I_L​=0.03 –0.04 A), and saturation current (I_s​=10⁻¹² –10⁻⁸ A) under varying diode ideality factors. Concurrently, Python-based simulations facilitated three-dimensional surface mapping of maximum power point (P_max​ ) degradation as a function of temperature (T=22°C–80°C) and ideality factor, complemented by comparative analysis of monocrystalline versus polycrystalline silicon technologies. Results demonstrate that increasing the ideality factor from 1.0 to 5.0 precipitates substantial reductions in fill factor and P_max​ , with monocrystalline cells exhibiting superior baseline efficiency but greater sensitivity to elevated n values compared to polycrystalline counterparts. Notably, polycrystalline cells displayed inherently higher ideality factors (n≈1.3 –1.5 ) attributed to grain-boundary recombination, yet demonstrated attenuated temperature-induced degradation relative to monocrystalline devices. The developed models achieved validation against manufacturer specifications with high fidelity, accurately reproducing I_sc​ , V_oc​ , and power output dependencies across diverse operating conditions. These findings elucidate the quantitative distinctions between silicon technologies under non-ideal diode behavior and provide a robust computational foundation for optimizing solar cell design, predictive maintenance, and educational modeling tools.