MODULE INSPECTION USING LINE SCANNING ...

32nd European Photovoltaic Solar Energy Conference and Exhibition

MODULE INSPECTION USING LINE SCANNING PHOTOLUMINESCENCE IMAGING

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Iskra Zafirovska1, Mattias K. Juhl1, Jürgen W. Weber2, Oliver Kunz1, and Thorsten Trupke1,2 School of Photovoltaic and Renewable Energy Engineering, The University of New South Wales, Sydney, Australia 2 BT Imaging Pty Ltd, Sydney, Australia

ABSTRACT: A custom built laboratory scale tool that enables line scanning photoluminescence (PL) imaging of full size photovoltaic modules was demonstrated for the purpose of manufacturing quality control. The tool allows fast onthe-fly acquisition with exceptional image quality, and can identify series resistance faults without making contact to a sample. This is due to the use of localised line illumination for photoexcitation, which induces lateral current flow between the illuminated and non-illuminated regions in a sample. We show that line scanning PL allows a more reliable differentiation of failure mechanisms than the electroluminescence (EL) imaging systems currently favoured by the industry. Keywords: PV Module, Photoluminescence, Electroluminescence, Characterisation, Silicon

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INTRODUCTION

imaging system that could be mounted within a robotic cleaning device used to maintain modules once installed in the field. The system used an Andor iKon-M series siliconCCD area camera, particularly because of its low noise and NIR responsivity. However, it images modules on a cell by cell basis, as both illumination and detection is restricted to a 6 inch region. A line scanning approach requires use of a line scan camera, in which the sensor is reduced to a single line of pixels rather than a 2D matrix. Imaging involves moving a sample through the field of view, whilst the camera continuously acquires line images in sync with the sample motion. The line images are then assembled to form the final image. The illumination source for photoexcitation can also be reduced to a line. This allows for imaging at higher carrier injection and has the additional benefit of allowing current extraction during image acquisition, despite the cells being under open circuit conditions externally, i.e. zero current between the cell’s terminals. Excess carriers are only generated within the illuminated line, forming a voltage difference between illuminated and nonilluminated regions that is the driving force for lateral currents. This effect is demonstrated in Figure 1, which shows a snapshot in time of the luminescence distribution across a uniform silicon solar cell during line scanning PL acquisition, simulated with the solar cell finite-element model program Griddler [8]. The line width is strongly exaggerated here for demonstration purposes. As can be seen in the horizontal cross-section plot, the nonilluminated areas outside of the red dashed lines emit a luminescence signal due to lateral current flow induced by the voltage difference. In this case, the luminescence intensity from the non-illuminated regions is almost identical to the intensity from illuminated cell areas, demonstrating the effectiveness of the lateral currents. Note that at each point in time the line scan camera inspects the illuminated area, from which current is extracted. The final PL image is therefore expected to resemble a conventional PL image that is measured with current extraction.

Silicon Photovoltaic (PV) module manufacturing is prone to a number of efficiency limiting defects, manufacturing faults and degradation mechanisms, including material and process induced defects and series resistance (Rs) faults. For example, the high temperature interconnection (soldering) and lamination processes create thermo-mechanical stress in the module, due to the differing thermal expansion coefficients of the materials present [1]. These stresses can form cracks in the cells or metallisation of the module, which have been shown to act as starting points for defect propagation during accelerated stress testing [2]. These faults pose significant reliability risk once a module is exposed to the environmental pressures in the field. Most module faults are highly localised, and cannot reliably be identified by a final IV test or by visual inspection. In response to this, manufacturers have begun to use electroluminescence (EL) imaging [3], due to its simplicity in acquiring spatially resolved quality information. EL measurements require a dark environment and electrical contact to the module. Such contacting increases complexity, risk of mechanical damage to a sample [4] and can have a negative impact on production throughput. A faster, more robust and more versatile imaging approach that does not significantly affect the production throughput or the time required to complete the production process would be beneficial. Photoluminescence (PL) imaging [5] applied using a line scanning methodology can fulfil these requirements, since it is contactless and allows on-the-fly inspection at inline manufacturing belt speeds. Line scanning PL imaging systems are used in production today for the inspection of as-cut silicon wafers. This paper demonstrates line scanning PL images of silicon modules, and exposes some fundamental differences between PL and EL for module manufacturing quality control.

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BACKGROUND

PL imaging on modules was first demonstrated by Ebner, et al. [6] with a system that utilised a silicon-CCD area camera. The system was designed for and tested on thin film modules (a-Si, CIS and CdTe) in a laboratory setting. Peng, et al. [7] developed an experimental PL

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32nd European Photovoltaic Solar Energy Conference and Exhibition

Figure 1: (a) PL intensity from a monocrystalline cell simulated with Griddler, applying 0.05 Suns illumination intensity within the red dashed lines (width exaggerated). (b) Horizontal cross-section of (a).

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EXPERIMENTAL SETUP

A custom built laboratory scale automated line scanning PL imaging tool was developed, capable of measuring individual silicon cells and mini modules as well as full size industrial silicon modules . A schematic of the tool and its main components is shown in Figure 2. Photoexcitation is achieved using a high-powered illumination source that was focused parallel to the short edge of modules. A line scanning silicon-CCD camera with an enhanced NIR response sensor is used for detection. Specialised optics were added to the camera to prevent both the detection of spurious luminescence (for example from encapsulation material) and detection of excitation illumination. The sample stage consists of a support frame, which is conveyed underneath the camera to mimic movement of modules on a manufacturing line. All images presented in this paper were both flat-field and background corrected.

Figure 3: Line scanning PL image of an industrial multicrystalline silicon PV module taken on-the-fly with approximately 4 Suns illumination intensity. Three triangular regions of interest are highlighted by red boxes. 4.2 Comparison to EL imaging The prototype line scanning PL tool is capable of acquiring EL images, when an external DC power supply is connected for excitation. An EL image of the same module is shown in Figure 4. In both images areas of high recombination such as grain boundaries and dislocation clusters appear dark, but a reverse in contrast is observed when comparing high Rs regions. Regions of high Rs appear darker than their surroundings in the EL, and brighter than their surroundings in PL with current extraction [9]. As an example we can identify three triangular regions in the EL image (Figure 4), which appear entirely black due to the fact that the current flow into those regions is impeded by local interrupts in the metal fingers caused by large cell cracks. In contrast, the same regions appear brighter than their surroundings in the PL image (Figure 3). This is expected from the previous discussion, since areas with enhanced series resistance remain at a higher local voltage due to the restrictions on local current extraction. Differentiation of failure mechanisms, specifically the distinction of recombination sites from series resistance problems is therefore more reliable when using line scanning PL imaging, since defects attributed to high recombination and those attributed to high Rs appear with inverted contrast, whereas in an EL image all defects appear dark. This is highlighted in Figure 5, which compares PL and EL images of the specific cell highlighted in colour in Figure 4. These images were taken directly from the full module images and highlights the

Figure 2: Schematic of prototype line scanning PL imaging tool used in this study.

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RESULTS AND DISCUSSION

4.1 Line scanning PL module imaging The performance of the prototype tool was evaluated by imaging a commercial module consisting of 60 multicrystalline silicon 156 mm x 156 mm cells. The module has a rated power output (Pmax) of 260 W. A PL image of this module acquired with the prototype tool is shown in Figure 3. A number of cells in the central region of the module contain many irregularly shaped dark regions originating from a busbar, which correspond to cell cracks in Chaturvedi, et al. [1]. In this specific module these cracks were induced during prior mechanical load testing.

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exceptional image quality that our prototype system enables.

on a BT Imaging LIS-R1 tool. The LIS-R1 uses a conventional area scanning (2D) camera and full area illumination. Images acquired on a 125 mm x 125 mm CZ silicon p-type cell, that has a finger interruption near the busbar, are shown in Figure 6.

Figure 6: Luminescence images of a monocrystalline silicon solar cell. (a) line scanning PL image taken with approximately 4 Suns illumination intensity at a measurement speed of 135 mm/s. (b) conventional open circuit PL image. (c) PL image with current extraction at 0.55V. (d) EL image with forward bias of 0.625 V. The impact of a finger break is highlighted by the black box. As expected the finger disconnection highlighted by the black box has similar contrast in the line scanning PL and in the PL image taken with current extraction, whereas it appears as a dark line in the EL image. In the conventional open circuit PL image the defect is not visible, since no current flows across the finger break. Finally, the impact of the finger disconnection is confirmed by the quantitative Rs image shown in Figure 7 [10]. The affected area has an elevated average Rs value of 1.12 Ωcm2 whilst the surrounding unaffected cell area has an average Rs value of 0.64 Ωcm2.

Figure 4: EL image of the module shown in Figure 3, taken with forward bias of 39.5 V (equivalent to 1.045 x Voc). Three triangular regions of interest are highlighted by red boxes.

Figure 5: (a) Close up of the cell highlighted in colour in Figure 4. (b) Line scanning PL image of the same cell.

Figure 7: Quantitative Rs image of the cell shown in Figure 6. The white box highlights the impact of a finger disconnect. Scale in Ωcm2.

Finger disconnections create areas of increased Rs, which are identified as regularly shaped rectangles extending from the affected busbar [1]. In the PL image these broken finger patterns appear bright and clearly discernible from the neighbouring dark cell cracks, whilst in the EL image they are dark and hence blend in. In addition the PL image provides information on the electrically isolated region in the top right of the cell, whilst in the EL image it emits no signal.

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CONCLUSION

The use of line scanning PL imaging was demonstrated on a full size commercial multicrystalline silicon PV module using a prototype system. Images of exceptional quality can be acquired on-the-fly for quality control in a manufacturing setting. PL images exhibit a local current extraction effect due to localised line illumination. This image acquisition mode and the resulting image features are expected to be more effective than EL imaging in discerning Rs effects from recombination effects, particularly when automated image

4.3 Local current extraction To emphasise the effect of local current extraction in an image acquired with an on-the-fly line scanning PL tool, we compare luminescence image data from the PL line scanning system with conventional images measured

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32nd European Photovoltaic Solar Energy Conference and Exhibition

pattern recognition techniques are applied. This technology has the potential to become a key application in commercial module quality control, which is of increasing relevance in an ever-growing and highly competitive market.

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ACKNOWLEDGEMENTS The authors would like to thank Dr Johnson Wong for support with Griddler simulations. This program has been supported by the Australian Government through the Australian Renewable Energy Agency (ARENA) grants 7-F008 and RND009. Responsibility for the views, information or advice expressed herein is not accepted by the Australian Government.

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