Journal of the Semiconductor & Display Technology (반도체디스플레이기술학회지)

The Korean Society Of Semiconductor & Display Technology (한국반도체디스플레이기술학회)
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I-V Modeling Based on Artificial Neural Network in Anti-Reflective Coated Solar Cells

반사방지막 태양전지의 I-V특성에 대한 인공신경망 모델링

  • Hong, DaIn (Department of System Semiconductor Engineering, Sangmyung University) ;
  • Lee, Jonghwan (Department of System Semiconductor Engineering, Sangmyung University)
  • 홍다인 (상명대학교 시스템반도체공학과) ;
  • 이종환 (상명대학교 시스템반도체공학과)
  • Received : 2022.09.16
  • Accepted : 2022.09.21
  • Published : 2022.09.30
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Abstract

An anti-reflective coating is used to improve the performance of the solar cell. The anti-reflective coating changes the value of the short-circuit current about the thickness. However, the current-voltage characteristics about the anti-reflective coating are difficult to calculate without simulation tool. In this paper, a modeling technique to determine the short-circuit current value and the current-voltage characteristics in accordance with the thickness is proposed. In addition, artificial neural network is used to predict the short-circuit current with the dependence of temperature and thickness. Simulation results incorporating the artificial neural network model are obtained using MATLAB/Simulink and show the current-voltage characteristic according to the thickness of the anti-reflective coating.

Keywords

Acknowledgement

This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(No. 2022R1I1A3064285).

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