Select the second option (Obtain batch parameters from external file) and use the Open button to load the file generated by this webpage. Load the appropriate PC1D simulation file and select the menu option Compute - Batch, this will launch the Quick Batch window. To use the files created on this page you should first save them into a directory on your local machine. For a p-type monocrystalline silicon wafer, with an area of 10 Г— 10 10times 10 cm2 and a thickness of 300 m, initial simulation shows a 12.10 efficient solar cell. The impact of different solar cell parameters, with their effects on power and efficiency, has been investigated. Please note that to prevent overuse of the web server we currently have a 3000 line limit on the generated files. In this paper, simulation of a monocrystalline silicon solar cell was done using PC1D software. When there is more than one input, it is possible to create permutations of input sweeps in the same manner as the quick batch mode in PC1D by checking the P checkbox. These steps can have either linear or logarithmic intervals. For each input, select the parameter type, the region (if required), the input parameter, the lower and upper limits to the sweep range, and the number of steps. There is a limit in PC1D of 30 for the combined total of inputs and outputs. The generated file is a tab-delimited text file in the format required by PC1D. To create an external batch file, first define the PC1D inputs you wish to vary, then the PC1D outputs you wish to monitor, and then press the Create batch file button. All of parameters available in PC1D batch mode are available here. In this study, the influence of various parameters like the thickness of the absorber or wafer, doping concentration, bulk resistivity, lifetime, and doping levels of the emitter and back surface field, along with the surface recombination velocity (front and back) on solar cell efficiency was investigated using PC1D simulation software. With an external batch file you can vary a large number of input parameters and monitor a variety of outputs.

, it is shown that the ANN-based models provide a better estimate of the EQE than the PC1D model in terms of mean square error and correlation coefficient.This page is used to generate external batch files for use in PC1D simulations. Using the experimental data from Sato etВ al. In this paper we propose an artificial neural network (ANN)-based model to estimate the EQE performance of triple-junction InGaP/GaAs/Ge solar cells under the influence of a wide range of charged particles. However, the accuracy of these models may be limited due to complex phenomena and interactions occurring between the junctions of the solar cells and the nonlinear influence of charged particles. Only file required to run the program is PC1D.exe. Usually numerical model based software, e.g., PC1D, are used to estimate the EQE and fitted with the measured EQE to obtain degradation performance of space solar cells. PC1D solves the fully coupled non-linear equations for the quasi-1-d transport of electrons & holes in crystalline semiconductor devices, with emphasis on photovoltaic devices. One can so reliably model with PC1D the optical performance of textured thin devices at standard Lambertian regimen ( 60 at all wavelengths, ) that starts at either the first or the second pass of trapped light. The EQE of solar cells for space applications is adversely affected by the influence of charged particles in space. External quantum efficiency (EQE) of a solar cell provides information on the internal operations of the solar cells which can be used in optimization of solar cell design.

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