Identification and Extraction of Electrophysical Parameters for Solar Cell Models by Experimental Data
( Pp. 144-160)

More about authors
Dolgopolov Mikhail V. Candidate of Physics and Mathematics, Associate Professor; associate professor at the Department of Higher Mathematics, Head of the joint Research Laboratory of Mathematical Physics NIL-319; Samara National Research University named after Academician S.P. Korolev; ­
Samara State Technical University
Samara, Russian Federation Chipura Alexander S. lecturer; Samara Technical University; student,
Samara National Research University named after Academician S.P. Korolev
Samara, Russian Federation Shishkin Ivan A. postgraduate student; Samara National Research University named after Academician S.P. Korolev; Samara, Russian Federation­
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The article summarizes the methodology of identification and extraction of electrophysical characteristics of solar cells for various models based on experimental data and equivalent one-, two-, three-diode circuits. A technique based on computer modeling in the Wolfram Mathematica analytical system and in the Mathcad computer algebra system is proposed. The technique allows to compare theoretical and experimental data and deal with different models in both directions – from experiment to theory and vice versa. Experimental work was also carried out to create solar cells based on porous silicon with antireflection coatings (ZnS, DyF3, ZnS + DyF3) and with SiC/Si heterojunctions. Measurements of the I-V and P-V of experimental photoconverters, as well as their surface resistances from the sides of phosphorus and boron doping on the formation of the p-n-junction, were carried out. The main purpose of the study is to develop a methodology for optimizing solar cells and to present modeling and analysis methods that can be used in the development of photobetaconverters to ensure maximum power.
How to Cite:
Dolgopolov M.V., Chipura A.S., Shishkin I.A. Identification and Extraction of Electrophysical Parameters for Solar Cell Models by Experimental Data. Computational Nanotechnology. 2023. Vol. 10. No. 3. Pp. 144–160. (In Rus.) DOI: 10.33693/2313-223X-2023-10-3-144-160. EDN: TAGTVX
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current-voltage characteristic, parameter extraction, solar cells, silicon carbide, porous silicon, single crystal module, mathematical modeling, monocrystalline module, photovoltaic cell, photovoltaic system, energy efficiency, optimization, adaptive control, maximum power point tracking, GMPPT, partial shading condition, extremum seeking control, equivalent circuit.

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