When a suitable external power supply is connected to the solar cell, it starts emitting electromagnetic radiation. Imaging this phenomenon, called electroluminescence (EL), is useful for spatially resolved characterisation of solar cells. As the imaging process is in some cases time-consuming, it was necessary to automate it. The project was carried out at the Laboratory of Photovoltaics and Optoelectronics (LPVO) at the Faculty of Electrical Engineering (FE) in Ljubljana.
The upgrade of the imaging system consisted mainly of replacing the camera holder with a three-axis system and developing a new program to control the imaging process. The three-axis system is a system similar to a 3D printer. As it proved uneconomical to modify the latter in-house, we outsourced the construction of the new three-axis system to a 3D printer manufacturer.
An existing imaging control program written in MATLAB was the basis for a new program written in Python. The new program used the PyQt5 module to develop the graphical user interface and the threading module to perform concurrent tasks. The program controls the camera, the three-axis system and the power supply. In addition to the 14 Python modules, its directory contains files with graphical user interface definitions, a dynamic link library used for controlling the camera and a few other files and folders. In addition to these files, a program called Keysight Connection Expert is required for full operation.
The newly developed program allows the EL imaging process to be planned and partially automated. For full automation, an image focusing mechanism has to be developed. The modular design of the program should allow the programmer to quickly review existing functions and easily start the upgrade process.
|
