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

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 pho-tovoltaic parameters of semiconductor p–n junctions through dual-platform modeling using MATLAB and Python. Employing experimentally measured current–voltage (I–V) charac-teristics obtained via Sinton Instrument Suns-Voc measurements from 5×5 cm² monocrys-talline silicon test samples, the research investigates the influence of ideality factor varia-tions (n=1.0 –5.0 ) on device performance within the single-diode equivalent circuit frame-work. Newton's iterative method was implemented in MATLAB to resolve the implicit tran-scendental I–V equation, enabling precise quantification of current dependencies on series resistance (Rs=1 –3 Ω ), parallel resistance (Rp=200 –1000 Ω ), photocurrent (IL=0.03 –0.04 A), and saturation current (Is=10−12 –10−8 A) under varying diode ideality factors. Concur-rently, Python-based simulations facilitated three-dimensional surface mapping of maxi-mum power point (Pmax ) degradation as a function of temperature (T=22°C–80°C) and ide-ality factor, complemented by comparative analysis of monocrystalline versus polycrystal-line silicon technologies. Results demonstrate that increasing the ideality factor from 1.0 to 5.0 precipitates substantial reductions in fill factor and Pmax , with monocrystalline cells ex-hibiting superior baseline efficiency but greater sensitivity to elevated n values compared to polycrystalline counterparts. Notably, polycrystalline cells displayed inherently higher ide-ality factors (n≈1.3 –1.5 ) attributed to grain-boundary recombination, yet demonstrated at-tenuated temperature-induced degradation relative to monocrystalline devices. The devel-oped models achieved validation against manufacturer specifications with high fidelity, ac-curately reproducing Isc , Voc , and power output dependencies across diverse operating con-ditions. These findings elucidate the quantitative distinctions between silicon technologies under non-ideal diode behavior and provide a robust computational foundation for optimiz-ing solar cell design, predictive maintenance, and educational modeling tools.

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