Spatially and spectrally resolved electroluminescence measurement system for photovoltaic characterisation

Abstract

A system that combines the advantages of fast global electroluminescence (EL) imaging and detailed spectrally resolved EL measurements is presented. A charge-coupled device camera-based EL imaging system is used to measure the intensity of radiative recombination of the photovoltaic (PV) device spatially resolved over its full area. A monochromator-based system is utilised to measure localised emission spectra at given points of interest. Measurements of multi-crystalline and amorphous silicon PV devices demonstrate the potential to investigate radiative defects and reveal performance variations and non-uniformities. This links inhomogeneities much closer to device physics than using camera-based EL only.

Mechanically stacked 4-terminal III-V/Si tandem solar cells

“…STE statistics and removal using a conditional minimum is detailed in [23]. [7,13,[24][25][26] As for EL images, these background images are prone to noise and STE decreasing the quality of EL images after subtraction. Both problems can be significantly reduced by taking at least two background images for different exposure times as input to solve ( ) = • + .…”

“…Their selection using a spatial standard deviation is described in [24,25]. However, a higher stability towards outliers can be reached using a threshold median [13]. For this purpose a median filtered image is created.…”

“…For common image processing problems such as geometric measurements, filtering and edge detection imageJ, a Java based open source program, is often used [8][9][10]. Others have created own routines based on 'MATLAB' [11] or LabView [12,13].…”

Electroluminescence imaging of PV devices: Camera calibration and image correction

“…[7,13,[24][25][26] These background images are prone to noise and STE decreasing the quality of EL images after subtraction. For consistent light conditions, both problems can be significantly reduced by taking at least two background images for different exposure times as input to solve ( ) = • + .…”

“…For common image processing problems such as geometric measurements, filtering and edge detection a Java based open source program, imageJ, is used frequently [8][9][10]. Others have created own routines based on MATLAB [11] or LabView [12,13]. These software tools are very useful but common imaging artefacts are often not corrected, limiting comparability between different setups and even different relative positions of the sample and the camera.…”