Chebyshev neural network-based model for dual-junction solar cells

DSpace/Manakin Repository


Search DR-NTU

Advanced Search Subject Search


My Account

Chebyshev neural network-based model for dual-junction solar cells

Show full item record

Title: Chebyshev neural network-based model for dual-junction solar cells
Author: Patra, Jagdish Chandra
Copyright year: 2011
Abstract: Design and development process of solar cells can be greatly enhanced by using accurate models that can predict their behavior accurately. Recently, there has been a surge in research efforts in multijunction (MJ) solar cells to improve the conversion efficiency. Modeling of MJ solar cells poses greater challenges because their characteristics depend on the complex photovoltaic phenomena and properties of the materials used. Currently, several commercial complex device modeling software packages, e.g., ATLAS, are available. But these software packages have limitations in predicting the behavior of MJ solar cells because of several assumptions made on the physical properties and complex interactions. Artificial neural networks have the ability to effectively model any nonlinear system with complex mapping between its input and output spaces. In this paper, we proposed a novel Chebyshev neural network (ChNN) to model a dual-junction (DJ) GaInP/GaAs solar cell. Using the ChNN, we have modeled the tunnel junction characteristics and developed models to predict the external quantum efficiency, and I-V characteristics both at one sun and at dark levels. We have shown that the ChNN-based models perform better than the commercial software, ATLAS, in predicting the DJ solar cell characteristics.
Subject: DRNTU::Engineering::Computer science and engineering::Computer applications::Physical sciences and engineering.
Type: Journal Article
Series/ Journal Title: IEEE transactions on energy conversion
School: School of Computer Engineering
Rights: © 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [DOI: http://dx.doi.org/10.1109/TEC.2010.2079935].
Version: Accepted version

Files in this item

Files Size Format View
61.Chebyshev Ne ... l-Junction Solar Cells.pdf 916.4Kb PDF View/Open

DOI Query

- Get published version (via Digital Object Identifier)

This item appears in the following Collection(s)

Show full item record


Total views

All Items Views
Chebyshev neural network-based model for dual-junction solar cells 659

Total downloads

All Bitstreams Views
61.Chebyshev Neural Network-Based Model for Dual-Junction Solar Cells.pdf 439
2011_IEEETEC_ChebyNN_DJSolarCell.pdf 11

Top country downloads

Country Code Views
United States of America 117
China 79
Singapore 53
Algeria 30
India 23

Top city downloads

city Views
Mountain View 72
Singapore 53
Beijing 30
Tabriz 14
Biskra 12