Quantitative electroluminescence measurements of PV devices

Electroluminescence (EL) imaging is a fast and comparatively low-cost method for spatially resolved analysis of photovoltaic (PV) devices. A Silicon CCD or InGaAs camera is used to capture the near infrared radiation, emitted from a forward biased PV device. EL images can be used to identify defects, like cracks and shunts but also to map physical parameters, like series resistance. The lack of suitable image processing routines often prevents automated and setup-independent quantitative analysis. This thesis provides a tool-set, rather than a specific solution to address this problem. Comprehensive and novel procedures to calibrate imaging systems, to evaluate image quality, to normalize images and to extract features are presented. For image quality measurement the signal-to-noise ratio (SNR) is obtained from a set of EL images. Its spatial average depends on the size of the background area within the EL image. In this work the SNR will be calculated spatially resolved and as (background independent) averaged parameter using only one EL image and no additional information of the imaging system. This thesis presents additional methods to measure image sharpness spatially resolved and introduces a new parameter to describe resolvable object size. This allows equalising images of different resolutions and of different sharpness allowing artefact-free comparison. The flat field image scales the emitted EL signal to the detected image intensity. It is often measured through imaging a homogeneous light source such as a red LCD screen in close distance to the camera lens. This measurement however only partially removes vignetting the main contributor to the flat field. This work quantifies the vignetting correction quality and introduces more sophisticated vignetting measurement methods. Especially outdoor EL imaging often includes perspective distortion of the measured PV device. This thesis presents methods to automatically detect and correct for this distortion. This also includes intensity correction due to different irradiance angles. Single-time-effects and hot pixels are image artefacts that can impair the EL image quality. They can conceivably be confused with cell defects. Their detection and removal is described in this thesis. The methods presented enable direct pixel-by-pixel comparison for EL images of the same device taken at different measurement and exposure times, even if imaged by different contractors. EL statistics correlating cell intensity to crack length and PV performance parameters are extracted from EL and dark I-V curves. This allows for spatially resolved performance measurement without the need for laborious flash tests to measure the light I-V- curve. This work aims to convince the EL community of certain calibration- and imaging routines, which will allow setup independent, automatable, standardised and therefore comparable results. Recognizing the benefits of EL imaging for quality control and failure detection, this work paves the way towards cheaper and more reliable PV generation. The code used in this work is made available to public as library and interactive graphical application for scientific image processing

Electroluminescence imaging of PV devices: Advanced vignetting calibration

IEEE Electroluminescence (EL) imaging is affected by off-axis illumination together with sensor and lens imperfections. The images’ spatial intensity distribution is mainly determined by the vignetting effect. For quantitative EL imaging, its correction is essential. If neglected, intensities can vary significantly (>50%) across the image. This paper introduces and tests four vignetting measurement methods. The quantitative comparison of different methods shows that vignetting should be characterized preferably in plane by the source of the same type as the photovoltaic (PV) device to be tested. A direct PV-based measurement in short distance with spatial inhomogeneity correction is proposed for general-purpose vignetting characterization. For precise vignetting characterization, vignetting-object separation using pattern recognition is proposed. The use of non-PV light sources for vignetting characterization can cause vignetting overcorrection and can even decrease the quality of the vignetting-corrected images

Influences of lamination condition on device durability for EVA-encapsulated PV modules

PV modules rely on their encapsulation to provide durability. The pottant is predominantly ethylene vinyl acetate (EVA). It is protected by foils and glass to minimise encapsulant related degradations such as delamination, decomposition and corrosion. Types of EVA and/or backsheet will influence overall durability, as has been reported frequently. The lamination process as well as material handling also contributes to overall durability, but the impact is not always obvious. This paper investigates the effect of lamination temperature on encapsulation quality and its impact on module durability in accelerated ageing tests. A series of laminations is carried out at different conditions within the typical window suggested by the manufacturer as well as slightly off specifications as could occur due to insufficient temperature control. The samples were exposed to prolonged standard ageing tests for up to 7000 hours. Use of subtractive electroluminescence (EL) images demonstrates a minimum of two different ageing mechanisms are active at different time constants and of different activation energies (Ea)

1st International round robin on EL imaging: automated camera calibration and image normalisation

Results from the first international Round Robin on electroluminescence (EL) imaging of PV devices are presented. 17 Laboratories across Europe, Asia and the US measured EL images of ten commercially available modules and five single-cell modules. This work presents a novel automated camera calibration and image scaling routine. Its performance is quantified through comparing intensity deviation of corrected images and their cell average. While manual calibration includes additional measurement of lens distortion and flat field, the automated calibration extracts camera calibration parameters (here: lens distortion, and vignetting) exclusively from EL images. Although it is shown that the presented automated calibration outperforms the manual one, the method proposed in this work uses both manual and automated calibration. 501 images from 24 cameras are corrected. Intensity deviation of cell averages of every measured device decreased from 10.3 % (results submitted by contributing labs) to 2.8 % (proposed method), For three images the image correction produced insufficient results and vignetting correction failed for one camera, known of having a non-linear camera sensor. Surprisingly, largest image quality improvements are achieved by spatially precise image alignment of the same device and not by correcting for vignetting and lens distortion. This is due to overall small lens distortion and the circumstance that, although vignetting caused intensity reduction of more than 50%, PV devices are generally positioned in the image centre in which vignetting distortion is lowest