Predictive modeling of mixed halide perovskite cell using hybrid L27 OA Taguchi-based GA-MLR-GA approach

Perovskite photovoltaic cell is regarded as an alternative configuration for the conventional photovoltaic cells predominantly due to its high efficiency. In this paper, a predictive modeling using a hybrid L27 orthogonal array (OA) Taguchi-based Grey relational analysis (GRA), multiple linear regre...

Full description

Saved in:
Bibliographic Details
Main Authors: Salehuddin, Fauziyah, Kaharudin, Khairil Ezwan
Format: Article
Language:English
Published: Penerbit UTM Press 2021
Online Access:http://eprints.utem.edu.my/id/eprint/26638/2/15550
http://eprints.utem.edu.my/id/eprint/26638/
https://journals.utm.my/jurnalteknologi/article/view/15550/7794
https://doi.org/10.11113/jurnalteknologi.v84.15550
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Teknikal Malaysia Melaka
Language: English
id my.utem.eprints.26638
record_format eprints
spelling my.utem.eprints.266382024-03-08T11:54:40Z http://eprints.utem.edu.my/id/eprint/26638/ Predictive modeling of mixed halide perovskite cell using hybrid L27 OA Taguchi-based GA-MLR-GA approach Salehuddin, Fauziyah Kaharudin, Khairil Ezwan Perovskite photovoltaic cell is regarded as an alternative configuration for the conventional photovoltaic cells predominantly due to its high efficiency. In this paper, a predictive modeling using a hybrid L27 orthogonal array (OA) Taguchi-based Grey relational analysis (GRA), multiple linear regression (MLR) and genetic algorithm (GA) was proposed to optimize the device parameters for better overall performance. The Perovskite photovoltaic cell model is initially constructed and simulated using solar cell capacitance simulator (SCAPS). The final results reveal that the proposed hybrid L27 OA Taguchi-based GRA-MLR-GA approach has effectively optimized the device parameters in which SnO2:F thickness, SnO2:F donor density, ZnO thickness, ZnO donor density, CH3NH3PbI3-xClx thickness, CH3NH3PbI3-xClx donor density, Spiro-OMeTAD thickness and Spiro-OMeTAD acceptor density are predictively tuned at 0.198 μm, 8.973 x 1018 cm-3, 0.039 μm, 8.827 x 1017 cm-3, 0.386 μm, 1.929 x 1013 cm-3, 0.233 μm and 8.984 x 1018 cm-3 respectively. After the predictive modeling, both FF and PCE of the perovskite photovoltaic cell have been improved for ~5.93% and ~5.78% respectively. Penerbit UTM Press 2021-12 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/26638/2/15550 Salehuddin, Fauziyah and Kaharudin, Khairil Ezwan (2021) Predictive modeling of mixed halide perovskite cell using hybrid L27 OA Taguchi-based GA-MLR-GA approach. Jurnal Teknologi, 84 (1). pp. 1-9. ISSN 2180–3722 https://journals.utm.my/jurnalteknologi/article/view/15550/7794 https://doi.org/10.11113/jurnalteknologi.v84.15550
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description Perovskite photovoltaic cell is regarded as an alternative configuration for the conventional photovoltaic cells predominantly due to its high efficiency. In this paper, a predictive modeling using a hybrid L27 orthogonal array (OA) Taguchi-based Grey relational analysis (GRA), multiple linear regression (MLR) and genetic algorithm (GA) was proposed to optimize the device parameters for better overall performance. The Perovskite photovoltaic cell model is initially constructed and simulated using solar cell capacitance simulator (SCAPS). The final results reveal that the proposed hybrid L27 OA Taguchi-based GRA-MLR-GA approach has effectively optimized the device parameters in which SnO2:F thickness, SnO2:F donor density, ZnO thickness, ZnO donor density, CH3NH3PbI3-xClx thickness, CH3NH3PbI3-xClx donor density, Spiro-OMeTAD thickness and Spiro-OMeTAD acceptor density are predictively tuned at 0.198 μm, 8.973 x 1018 cm-3, 0.039 μm, 8.827 x 1017 cm-3, 0.386 μm, 1.929 x 1013 cm-3, 0.233 μm and 8.984 x 1018 cm-3 respectively. After the predictive modeling, both FF and PCE of the perovskite photovoltaic cell have been improved for ~5.93% and ~5.78% respectively.
format Article
author Salehuddin, Fauziyah
Kaharudin, Khairil Ezwan
spellingShingle Salehuddin, Fauziyah
Kaharudin, Khairil Ezwan
Predictive modeling of mixed halide perovskite cell using hybrid L27 OA Taguchi-based GA-MLR-GA approach
author_facet Salehuddin, Fauziyah
Kaharudin, Khairil Ezwan
author_sort Salehuddin, Fauziyah
title Predictive modeling of mixed halide perovskite cell using hybrid L27 OA Taguchi-based GA-MLR-GA approach
title_short Predictive modeling of mixed halide perovskite cell using hybrid L27 OA Taguchi-based GA-MLR-GA approach
title_full Predictive modeling of mixed halide perovskite cell using hybrid L27 OA Taguchi-based GA-MLR-GA approach
title_fullStr Predictive modeling of mixed halide perovskite cell using hybrid L27 OA Taguchi-based GA-MLR-GA approach
title_full_unstemmed Predictive modeling of mixed halide perovskite cell using hybrid L27 OA Taguchi-based GA-MLR-GA approach
title_sort predictive modeling of mixed halide perovskite cell using hybrid l27 oa taguchi-based ga-mlr-ga approach
publisher Penerbit UTM Press
publishDate 2021
url http://eprints.utem.edu.my/id/eprint/26638/2/15550
http://eprints.utem.edu.my/id/eprint/26638/
https://journals.utm.my/jurnalteknologi/article/view/15550/7794
https://doi.org/10.11113/jurnalteknologi.v84.15550
_version_ 1793162590239588352