Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)

Black Silicon Solar Cells Modeling and Model Parameters Estimation

Authors
Yongtao Li, Heng Kang, Luojun Huang, Yupeng Jin, Xiaomeng Sun, Yang Xia
Corresponding Author
Yongtao Li
Available Online March 2017.
DOI
https://doi.org/10.2991/ifmca-16.2017.79How to use a DOI?
Keywords
black silicon; modeling; model parameters; estimation.
Abstract
For the purpose of predict the electrical characteristics of black silicon solar cells, a simple lumped-parameter equivalent circuit model is proposed. This model is in the form of electrical equivalent circuit which contains one diode, one current source and two resistances. The model contains linear and nonlinear components. A method based on some simplifications and approximation to the nonlinear function has been proposed to estimate the model parameters. To verify the model and the method, two kinds of black silicon solar cells were used to measure the I-V curves and P-V curves at various irradiance conditions. Simulations and experiments have been conducted to confirm the operation of the proposed model and estimation method.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)
Series
Advances in Engineering Research
Publication Date
March 2017
ISBN
978-94-6252-307-4
ISSN
2352-5401
DOI
https://doi.org/10.2991/ifmca-16.2017.79How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yongtao Li
AU  - Heng Kang
AU  - Luojun Huang
AU  - Yupeng Jin
AU  - Xiaomeng Sun
AU  - Yang Xia
PY  - 2017/03
DA  - 2017/03
TI  - Black Silicon Solar Cells Modeling and Model Parameters Estimation
BT  - Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)
PB  - Atlantis Press
SP  - 520
EP  - 526
SN  - 2352-5401
UR  - https://doi.org/10.2991/ifmca-16.2017.79
DO  - https://doi.org/10.2991/ifmca-16.2017.79
ID  - Li2017/03
ER  -