Statistical modeling of solar cell using Taguchi method and TCAD tool

• Main Authors: Bahrudin M.S., Abdullah S.F., Ahmad I.
• Other Authors: 55603412800
• Format: Conference paper
• Published: 2023
• Subjects: ion-implantation and Silvaco TCAD software; PN-junction; Solar cell; Taguchi Optimization Method; Boron; Computer simulation; Experiments; Optimization; Phosphorus; Semiconductor doping; Signal to noise ratio; Silicon solar cells; Solar cells; Taguchi methods; Testing; Best value; Doping concentration; Electrical testing; Fill factor; Junction depth; Noise factor; Orthogonal array; P-n junction; Recombination process; Shallow junction; Silicon-based; Silvaco; Simulation environment; Solar cell fabrication; Statistical modeling; Taguchi optimization method; TCAD software; Semiconductor junctions

This paper focuses on optimizing silicon based solar cell fabrication using Taguchi Optimization Method (TOM). Optimization focused on 3 parameters namely doping concentration of boron, creating phosphorus PN-junction and energy used for ion-implantation with 2 noise factors, Diffuse time and diffuse temperature. The aim is to have a shallow junction in order to decrease the recombination process but higher fill factor (FF) for better efficiency. Fabricating are done in computer simulation environment by Silvaco TCAD software that also conducting an electrical testing for measurement. Each factor (product from the parameters through TOM) has 2 levels of best values taken from the previous researches. In this research, L8 orthogonal array consists of 8 set of different combination of experiment has been done. Optimized values are analyzed by finding Signal to Noise Ratio (SNR) of each experiment and applied it on Larger the Better (LTB) for highest FF and Smaller the Better (STB) for shallowest junction depth. Result reveal that boron at concentration of 5.0�10 15 cm-3, phosphorus at concentration of 2.0�10 16 cm-3, and energy at 10 keV gave a result of 0.3 um ? 0.5 um for junction depth and stable FF value of 0.8 at any noise factor contributing efficiency of 15% to 16%. As a conclusion, TOM has achieved predicting the best solution for optimizing silicon solar cell fabrication. � 2012 IEEE.