Electroluminescence imaging and automatic cell classification in mass production of silicon solar cells

Alt, Milan; Fischer, Sabine; Schenk, Stefan; Zimmermann, S.; Ramspeck, K.; Meixner, Michael

doi:10.1109/pvsc.2018.8547983

Cited by 13 publications

(8 citation statements)

References 3 publications

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“…In addition, the forward current was injected by a current‐voltage source (Keithley 2400) at room temperature, and the captured EL images were displayed immediately on a computer. Absolute EL images were further calibrated with the use of a standard planar LED, and the uncertainty of the calibration was estimated to be less than 10% …”

Section: Experiments and Simulationsmentioning

confidence: 99%

Absolute electroluminescence imaging with distributed circuit modeling: Excellent for solar‐cell defect diagnosis

Hong

Wang

Chen

et al. 2019

Progress in Photovoltaics

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Spatially resolved absolute electroluminescence (EL) imaging demonstrates the localized EL intensity and the uniformity of solar cells. Combined with two‐dimensional (2‐D) distributed circuit network modeling, detailed and important information that is contained in experimental data can be extracted for in‐depth understanding of solar cell performances. Herein, we measured the absolute EL images of three different solar cells (Si, GaAs, and Cu (In,Ga)Se2 (CIGS)) and observed the different injection‐current‐dependent EL intensities of the defect points (dark or bright) on the solar cells. The origins of these defects were attributed to different defect types according to our established 2‐D distributed equivalent circuit model. The results demonstrated that the combination of absolute EL imaging and distributed circuit modeling yielded accurate quantitative diagnoses of the electrical defects in solar cells.

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Section: Experiments and Simulationsmentioning

confidence: 99%

Absolute electroluminescence imaging with distributed circuit modeling: Excellent for solar‐cell defect diagnosis

Hong

Wang

Chen

et al. 2019

Progress in Photovoltaics

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“…The EL test is to apply a forward bias voltage to the crystalline silicon solar cell, the photons will be emitted by the solar cell according to the principle of electroluminescence, which will be captured by a CCD camera, and then processed by a computer to display the EL image of the solar cell [19] [20]. Since the electroluminescence brightness of a solar cell is proportional to the diffusion length of electrons and the current density, for those places where exist defects, the lower minority carrier diffusion length results in darker image brightness, which not only facilitates the identification of defects through visual inspection, but also facilitates the identification using the most advanced automated solution [21] [22].…”

Section: El Test Principlementioning

confidence: 99%

Design of EL defect detection system for photovoltaic power station modules

Fan

Yan

et al. 2022

J. Phys.: Conf. Ser.

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In recent years, the photovoltaic power generation industry has been vigorously promoted and developed, while the solar cell as its core component may have micro-crack defects, which directly affect the power generation efficiency and stability of the photovoltaic system. Therefore, it is necessary to adopt a low-cost, efficient and flexible method to detect defects in solar cells. At present, most of the existing micro-cracks detection is carried out in the laboratory, and there is no EL micro-cracks detection in the actual photovoltaic power station. The main purpose of this paper is to design a set of EL defect detection system that can be used for actual photovoltaic power station modules, which is different from the traditional laboratory-level or module-level defect detection, and to carry the designed detection algorithm to the integrated device to operate. Experiments have shown that the system can perform real-time detection of photovoltaic module defects based on the string level, which improves the detection efficiency while saving time and cost, and shows good performance.

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“…In this work, we address the challenges of electroluminescence imaging systems on a high throughput level. Electroluminescence measurements allow for localized defect detections with algorithms such as [1,2]. With the current state-of-the-art inline characterization, a throughput of >4500 samples per hour can be achieved [2].…”

Section: Introductionmentioning

confidence: 99%

“…Electroluminescence measurements allow for localized defect detections with algorithms such as [1,2]. With the current state-of-the-art inline characterization, a throughput of >4500 samples per hour can be achieved [2]. To increase the throughput, the contacting/decontacting station and measurement setup need to be adapted.…”

Section: Introductionmentioning

confidence: 99%

Every cell needs a beautiful image: on-the-fly contacting measurements for high-throughput production

Kurumundayil

Ramspeck²,

Rein

et al. 2023

EPJ Photovolt.

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The future of the energy transition will lead to a terrawatt-scale photovoltaic market, which can be served cost-effectively primarily by means of high-throughput production of solar cells. In addition to high-throughput production, characterization must be adapted to highest cycle times. Therefore, we present an innovative approach to detect image defects in solar cells using on-the-fly electroluminescence measurements. When a solar cell passes a standard current–voltage (I–V) unit, the cell is stopped, contacted, measured, released, and afterwards again accelerated. In contrast to this, contacting and measuring the sample on-the-fly saves a lot of time. Yet, the resulting images are blurred due to high-speed motion. For the development of such an on-the-fly contact measurement tool, a deblurring method is developed in this work. Our deep-learning-based deblurring model enables to present a clean EL image of the solar cell to the human operator and allows for a proper defect detection, reaching a correlation coefficient of 0.84.

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Electroluminescence imaging and automatic cell classification in mass production of silicon solar cells

Cited by 13 publications

References 3 publications

Absolute electroluminescence imaging with distributed circuit modeling: Excellent for solar‐cell defect diagnosis

Absolute electroluminescence imaging with distributed circuit modeling: Excellent for solar‐cell defect diagnosis

Design of EL defect detection system for photovoltaic power station modules

Every cell needs a beautiful image: on-the-fly contacting measurements for high-throughput production

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