KR20240078968A - Method and apparatus for detecting wrap-around in silicon solar cell - Google Patents

Abstract

A method and device for detecting wraparound in silicon solar cells are presented. A method for detecting wraparound in a silicon solar cell performed by a computer device according to an embodiment includes extracting a wraparound portion through an image filter from a captured silicon solar cell image; A step of measuring and indicating the width of the extracted wrap-around in pixels; and determining whether wrap-around detection passes or fails based on a preset pixel using the measured pixels.

Description

Method and device for detecting wrap-around in silicon solar cell {METHOD AND APPARATUS FOR DETECTING WRAP-AROUND IN SILICON SOLAR CELL}

The examples below relate to a method and device for detecting wrap-around in a silicon solar cell. More specifically, the wrap-around is detected and passed after the wrap-around removal process during the silicon solar cell process. Or it relates to a method and device for determining failure.

A solar cell is a device that converts the sun's light energy into electrical energy. It has a different structure from a chemical cell and is classified as a physical cell. It uses two types of semiconductors, a p-type semiconductor and an n-type semiconductor, to achieve the photoelectric effect. Electricity is produced through

Recently, there is an increasing demand for establishing mid- to long-term strategies in accordance with the 2050 carbon neutrality strategy and diversifying solar power locations to overcome the limitations of existing technologies. In this respect, in the case of solar power generation, demands for high efficiency and high output of cells and modules are being raised, and a shift from existing p-type crystalline silicon solar cells to n-type silicon solar cells, which are more effective in high efficiency, is being detected. .

The structure of solar cells can be broadly divided into n-type single crystal HJT (Heterojunction solar cell), IBC (Interdigitated Back Contact), and TOPCon (Tunnel Oxide Passivated Contact). , According to recent module trends, development is expected to center around HJT and TOPCon solar cells.

Korean Patent Publication No. 10-2022-0029204 relates to such a solar cell module and describes technology for a solar cell module that can obtain high output from the same light receiving area and ensure driving reliability.

Korean Patent Publication No. 10-2022-0029204

The embodiments describe a method and device for detecting wraparound in a silicon solar cell, and more specifically, remove wrap-around for unwanted wrap-around that occurs during the silicon solar cell process. It provides image judgment technology that detects wraparound through post-process image processing.

Embodiments provide a method and device for detecting wraparound in a silicon solar cell that can improve yield by detecting defective wafers for which the wraparound has not been removed before completion of the solar cell by detecting the wraparound through image reading. there is.

In addition, according to embodiments, a wraparound detection method and device in a silicon solar cell that can objectively determine defects without human intervention is provided by providing a product defect determination system through deep learning or machine learning-based image reading. It is provided.

A method for detecting wraparound in a silicon solar cell performed by a computer device according to an embodiment includes extracting a wraparound portion through an image filter from a captured image of a silicon solar cell; A step of measuring and indicating the width of the extracted wrap-around in pixels; and determining whether wrap-around detection passes or fails based on a preset pixel using the measured pixels.

It may further include taking an image of the silicon solar cell using a digital microscope.

In the step of taking an image of the silicon solar cell, the image of the silicon solar cell can be taken with a digital microscope after a wrap-around removal process for the wrap-around that occurs during the silicon solar cell process. there is.

The step of determining pass or fail for the wrap-around detection is a pass or fail for the wrap-around detection through image reading based on machine learning. Fail can be determined.

If the wrap-around detection is determined to be a failure, the method may further include etching the wrap-around portion of the solar cell using in-line wet etching equipment.

A wrap-around detection device in a silicon solar cell according to another embodiment includes a wrap-around extraction unit that extracts a wrap-around portion through an image filter from a captured image of a silicon solar cell; a pixel measurement unit that measures and indicates the width of the extracted wrap-around in pixels; and a wrap-around determination unit that uses the measured pixels to determine whether the wrap-around detection passes or fails based on a preset pixel.

It may further include an image capturing unit that captures an image of the silicon solar cell using a digital microscope.

The image capture unit may capture an image of the silicon solar cell using a digital microscope after a wrap-around removal process for the wrap-around that occurs during the silicon solar cell process.

The wrap-around determination unit may determine pass or fail for the wrap-around detection through image reading based on machine learning.

If the wrap-around detection is determined to be a failure, the solar cell may further include an etching unit for etching the wrap-around portion of the solar cell using in-line wet etching equipment. .

According to embodiments, a wrap in a silicon solar cell detects wrap-around through image processing after a wrap-around removal process for unwanted wrap-around that occurs during the silicon solar cell process. An around detection method and device can be provided.

According to embodiments, a method and device for detecting wraparound in a silicon solar cell that can improve yield by detecting defective wafers from which the wraparound has not been removed before completion of the solar cell by detecting the wraparound through image reading. can be provided.

In addition, according to embodiments, a wraparound detection method and device in a silicon solar cell that can objectively determine defects without human intervention is provided by providing a product defect determination system through deep learning or machine learning-based image reading. can be provided.

Figure 1 is a diagram showing the structure of an n-TOPCon solar cell according to an embodiment.
Figure 2 is a diagram for explaining the form of a wraparound according to an embodiment.
Figure 3 is a flowchart showing a method for detecting wraparound in a silicon solar cell according to an embodiment.
Figure 4 is a block diagram showing a wraparound detection device in a silicon solar cell according to an embodiment.
Figure 5 is a diagram illustrating a machine vision system according to an embodiment.
Figure 6 is a diagram illustrating a pass decision using a machine vision system according to an embodiment.
Figure 7 is a diagram illustrating failure determination using a machine vision system according to an embodiment.

Hereinafter, embodiments will be described with reference to the attached drawings. However, the described embodiments may be modified into various other forms, and the scope of the present invention is not limited to the embodiments described below. In addition, various embodiments are provided to more completely explain the present invention to those with average knowledge in the art. The shapes and sizes of elements in the drawings may be exaggerated for clearer explanation.

N-type solar cells have recently attracted greater attention with the possibility of mass production of TOPCon (Tunnel oxide passivated contact) structures.

The TOPCon solar cell is a structure proposed by the German research institute Fraunhofer ISE, and uses a thin tunnel oxide film and a doped polysilicon layer on the back of the solar cell. This rear structure improves the selectivity of majority carriers and minority carriers, extremely lowering the recombination speed at the rear, and as a result, can increase the open-circuit voltage of the solar cell.

In other words, in solar cells, the separation and collection of electrons and holes formed after light irradiation is important. By improving the selective collection ability of electrons and holes, that is, majority carriers and minority carriers, the recombination of electrons and holes is reduced, and through this, the open-circuit voltage of the solar cell is lowered. It is to improve efficiency.

The examples below relate to a method and device for detecting wrap-around in a silicon solar cell, and provide a wrap-around for unwanted wrap-around that occurs during the silicon solar cell process. around) provides technology to detect wraparound through image processing after the removal process and determine pass/fail.

Figure 1 is a diagram showing the structure of an n-TOPCon solar cell according to an embodiment.

Referring to FIG. 1, the n-TOPCon solar cell according to one embodiment forms a TOPCon (Tunnel Oxide Passivated Contact) structure on the rear surface to minimize recombination loss due to the rear metal electrode, thereby improving solar cell efficiency. It is an n-type solar cell.

For example, an n-TOPCon solar cell includes a semiconductor layer 110, an emitter 120 located above the semiconductor layer 110, a passivation 130 located above the emitter 120, And a first electrode 170 may be included on the upper side of the passivation 130. In addition, n-TOPCon solar cells include silicon oxide (SiOx, 140) located below the semiconductor layer 110, TOPCon (150) located below the silicon oxide (140), and passivation located below the TOPCon (150). (passivation, 160), and may include a second electrode 180 located below the passivation 160.

The semiconductor layer 110 may include silicon doped with n-type impurities. For example, the semiconductor layer 110 may be n-c-Si. The semiconductor layer 110 may be subjected to texturing to form the upper surface of the semiconductor layer 110 into a textured surface. When the surface of the semiconductor layer 110 is formed as a textured surface, light reflectivity at the light-receiving surface of the semiconductor layer 110 may decrease and light absorption may increase.

The first electrode 170 may include a conductive material. For example, the first electrode 170 may be silver (Ag). Additionally, the first electrode 170 is made of nickel (Ni), copper (Cu), silver (Ag), aluminum (Al), tin (Sn), zinc (Zn), indium (In), titanium (Ti), and gold. It may be at least one selected from the group consisting of (Au) and combinations thereof.

TOPCon 150 is configured to minimize recombination loss due to the rear metal electrode, and may be composed of, for example, polysilicon (n+-poly-Si).

The second electrode 180 may include a conductive material. For example, the second electrode 180 may be aluminum (Al). Additionally, the second electrode 180 is made of nickel (Ni), copper (Cu), silver (Ag), aluminum (Al), tin (Sn), zinc (Zn), indium (In), titanium (Ti), and gold. It may be at least one selected from the group consisting of (Au) and combinations thereof.

These TOPCon solar cells can reduce recombination current loss by inserting the TOPCon membrane. Although the expected photovoltaic efficiency of TOPCon solar cells is slightly lower than that of HJT, it is expected to be at least 1%p higher than that of single crystal PERC from 2023. In addition, TOPCon solar cells, like HJTs, prevent current loss due to recombination of electrons and holes. Additionally, by inserting a thin oxide layer using a silicon film between the silicon surface and the metal film, the recombination loss of electrons and holes is reduced. Unlike HJT, TOPCon solar cells are highly compatible with PERC equipment.

Figure 2 is a diagram for explaining the form of a wraparound according to an embodiment.

Referring to FIG. 2, an unexpected wrap-around (260) may occur during the silicon solar cell process. Here, the wrap-around (260) is an undesirable shape formed on the front edge during the process of depositing a polysilicon (n+-poly-Si) thin film 250 with a high doping concentration on the back to manufacture an n-TOPCon solar cell. This is a phenomenon in which a polysilicon (n+-poly-Si) thin film 250 is deposited.

For example, a TOPCon silicon solar cell can be manufactured on an N-type silicon substrate, and both the thin tunnel oxide layer 240 and the phosphorus-doped polycrystalline silicon (polysilicon) thin film 250 can be prepared by an LPCVD system. At this time, the polysilicon wrap around 260 can be observed on the BSG (borosilicate glass) surfaces 220 and 230. The polysilicon wrap around 260 forms a leakage current path, which may reduce the shunt resistance of the solar cell and reduce solar cell efficiency.

In this way, if the wraparound (n+) remains on the front surface, it causes a short circuit with the emitter (p+) formed on the front surface, causing the solar cell to not operate or generating leakage current even if a short circuit does not occur, lowering solar cell efficiency.

Accordingly, wraparound can be removed. For example, wraparound can be removed by etching with diluted KOH using in-line wet etching equipment.

Figure 3 is a flowchart showing a method for detecting wraparound in a silicon solar cell according to an embodiment.

Referring to FIG. 3, the wrap-around detection method in a silicon solar cell performed by a computer device according to an embodiment extracts a wrap-around portion through an image filter from a captured image of a silicon solar cell. A step (S120), a step (S130) of measuring and indicating the width of the extracted wrap-around in pixels, and wrapping-around based on a preset pixel using the measured pixels. It may include a step (S140) of determining whether detection passes or fails.

Depending on the embodiment, the step of taking an image of the silicon solar cell using a digital microscope (S110) may be further included.

In addition, if the wrap-around detection is determined to be a failure depending on the embodiment, the wrap-around portion of the solar cell is etched using in-line wet etching equipment (S150). It may further include.

Below, a method for detecting wraparound in a silicon solar cell according to an embodiment will be described in more detail.

The method for detecting wraparound in a silicon solar cell according to an embodiment can be explained by taking a wraparound detection device in a silicon solar cell according to an embodiment as an example. Meanwhile, a wraparound detection device in a silicon solar cell according to an embodiment is or may be included in a machine vision system as shown in FIG. 5.

Figure 4 is a block diagram showing a wraparound detection device in a silicon solar cell according to an embodiment.

Referring to FIG. 4, the wraparound detection device 400 in a silicon solar cell according to one embodiment includes a wraparound extraction unit 420, a pixel measurement unit 430, and a wraparound determination unit 440. You can. Additionally, depending on the embodiment, it may further include at least one of an image capturing unit 410 and an etching unit 450.

In step S110, the image capture unit 410 may capture an image of the silicon solar cell using a digital microscope.

The image capture unit 410 can capture an image of a silicon solar cell using a digital microscope after a wrap-around removal process for the wrap-around that occurs during the silicon solar cell process.

In step S120, the wrap-around extractor 420 may extract a wrap-around portion from the captured image through an image filter. For example, the wrap-around extraction unit 420 can extract only the wrap-around portion through the HSL image filter.

In step S130, the pixel measurement unit 430 may measure and represent the width of the extracted wrap-around in pixels. The pixel measurement unit 430 can measure and indicate the width of the extracted wrap-around using pixel counting, and can be expressed as, for example, 74, 93, etc.

In step S140, the wrap-around determination unit 440 may use the measured pixels to determine whether the wrap-around detection passes or fails based on a preset pixel. For example, if the preset pixel standard is 80, a pass decision can be made when the result measured by pixel counting is 74. Additionally, if the preset pixel standard is 80, a failure decision can be made when the result measured by pixel counting is 93.

At this time, the wrap-around determination unit 440 can determine pass or fail for wrap-around detection through image reading based on machine learning or deep learning.

In addition, at least one of the components of the wrap-around detection device 400 in a silicon solar cell according to an embodiment passes the wrap-around detection through image reading based on machine learning or deep learning ( Pass or Fail can be determined. That is, at least one of the image capturing unit 410, the wraparound extraction unit 420, the pixel measurement unit 430, the wraparound determination unit 440, and the etching unit 450 is based on machine learning or deep learning. Through image reading, it is possible to determine pass or fail for wrap-around detection. Accordingly, it is possible to determine pass or fail for wrap-around detection through image reading based on machine learning or deep learning.

Meanwhile, in step S150, if the etch unit 450 is determined to have failed in the wrap-around detection, the wrap-around portion of the solar cell is removed using in-line wet etching equipment. It can be etched using

For example, the etch portion 450 may etch the wrap-around portion of the solar cell with diluted KOH.

Below, the manufacturing process of a TOPCon solar cell is explained as an example.

After boron diffusion, a cross-sectional etching process may be performed to remove the boron diffusion layer on the back of the silicon wafer. An ultrathin tunnel oxide layer ~1.5 nm and a 100 nm doped polycrystalline silicon layer can then be successively deposited via an LPCVD system. Afterwards, N ₂ annealing can be performed in an inert atmosphere at 850°C to promote excellent passivation quality and dopant activation. After the wrap-around poly-Si is removed, 4 nm Al2O3/80 to 90 nm SiNx and SiNx can be deposited on the front and back sides, respectively. Finally, screen printing and co-firing can be performed to form metal contacts.

According to embodiments, defects can be objectively determined without human intervention. Additionally, according to embodiments, a system for determining product defects through image reading based on deep learning or machine learning can be provided.

Figure 5 is a diagram showing a machine vision system according to an embodiment.

Referring to Figure 5, a self-produced machine vision system is shown. Using this machine vision system, after the wrap-around removal process, the wrap-around can be detected through image processing and pass/fail can be determined.

For example, a machine vision system according to one embodiment may include a sample stage, a digital microscope, and operating software running on a computer device. A silicon solar cell can be placed on the sample stage, and the silicon solar cell placed on the sample stage can be moved using an X-axis linear actuator and a Y-axis linear actuator. At this time, LEDs, etc. can be operated. And images of the silicon solar cell can be taken through a digital microscope with a zoom lens placed on the top of the sample stage. Thereafter, the captured image of the silicon solar cell can be transferred to operating software running on a computer device.

Here, the operating software executed in the computer device may include the wraparound extraction unit 420, the pixel measurement unit 430, and the wraparound determination unit 440 described in FIG. 4. Accordingly, the wrap-around part can be extracted from the captured image through an image filter, the width of the extracted wrap-around can be measured and expressed in pixels, and the measured pixels can be used. Thus, it is possible to determine pass or fail for wrap-around detection based on a preset pixel.

FIG. 6 is a diagram illustrating a pass determination using a machine vision system according to an embodiment, and FIG. 7 is a diagram illustrating a failure determination using a machine vision system according to an embodiment.

Referring to Figures 6 and 7, when the pass/fail standard is set to Pixel 80 using the machine vision system according to an embodiment, a pass decision and a fail upper decision are made. indicates.

Here, (A) is the result of taking an image with a digital microscope, (B) is the result of extracting only the wraparound part through the HSL image filter, and (C) is the result of extracting the width of the extracted wraparound using pixel counting. This is the result of measurement, and (D) represents the result of judging Pass/Fail based on a set pixel.

As described above, according to the embodiments, the yield can be improved by detecting defective wafers from which the wraparound has not been removed before the solar cell is completed.

In addition, according to embodiments, non-destructive inspection of defective wafers can be performed in real time, and costs are reduced by reducing unnecessary material consumption.

In the above, when a component is referred to as being “connected” or “connected” to another component, it may be directly connected to or connected to the other component, but other components may exist in between. It must be understood that there is. On the other hand, when it is mentioned that a component is “directly connected” or “directly connected” to another component, it should be understood that there are no other components in between.

The terms used in this specification are merely used to describe specific embodiments and are not intended to limit the invention. Singular expressions include plural expressions unless the context clearly dictates otherwise. In this specification, terms such as “comprise” or “have” are intended to designate the presence of features, numbers, steps, operations, components, parts, or combinations thereof described in the specification, but are not intended to indicate the presence of one or more other features. It should be understood that this does not exclude in advance the possibility of the existence or addition of elements, numbers, steps, operations, components, parts, or combinations thereof.

Terms such as first, second, etc. may be used to describe various components, but the components should not be limited by the terms. The above terms are used only for the purpose of distinguishing one component from another.

In addition, terms such as “…unit” and “…module” used in the specification refer to a unit that processes at least one function or operation, and may be implemented as hardware, software, or a combination of hardware and software.

In addition, the components of the embodiments described with reference to each drawing are not limited to the corresponding embodiments, and may be implemented to be included in other embodiments within the scope of maintaining the technical spirit of the present invention, and may also be included in separate embodiments. Even if the description is omitted, it is natural that a plurality of embodiments may be re-implemented as a single integrated embodiment.

In addition, when describing with reference to the accompanying drawings, identical or related reference numerals will be given to identical or related elements regardless of the reference numerals, and overlapping descriptions thereof will be omitted. In describing the present invention, if it is determined that a detailed description of related known technologies may unnecessarily obscure the gist of the present invention, the detailed description will be omitted.

As described above, although the embodiments have been described with limited examples and drawings, various modifications and variations can be made by those skilled in the art from the above description. For example, the described techniques are performed in a different order than the described method, and/or components of the described system, structure, device, circuit, etc. are combined or combined in a different form than the described method, or other components are used. Alternatively, appropriate results may be achieved even if substituted or substituted by an equivalent.

Therefore, other implementations, other embodiments, and equivalents of the claims also fall within the scope of the claims described below.

Claims (10)

In a method of detecting wraparound in a silicon solar cell performed by a computer device,
Extracting a wrap-around portion from a photographed image of a silicon solar cell through an image filter;
A step of measuring and indicating the width of the extracted wrap-around in pixels; and
A step of determining pass or fail for wrap-around detection based on a preset pixel using the measured pixel.
Wraparound detection method in a silicon solar cell, including. According to paragraph 1,
Taking an image of the silicon solar cell with a digital microscope
A wraparound detection method in a silicon solar cell, further comprising: According to paragraph 2,
The step of taking an image of the silicon solar cell is,
After the wrap-around removal process occurs during the silicon solar cell process, images of the silicon solar cell are taken using a digital microscope.
A wraparound detection method in a silicon solar cell, characterized by: According to paragraph 1,
The step of determining pass or fail for the wrap-around detection is,
Determining pass or fail for the wrap-around detection through image reading based on machine learning
A wraparound detection method in a silicon solar cell, characterized by: According to paragraph 1,
If the wrap-around detection is determined to be a failure, etching the wrap-around portion of the solar cell using in-line wet etching equipment.
A wraparound detection method in a silicon solar cell, further comprising: A wrap-around extraction unit that extracts the wrap-around portion from the captured solar cell image through an image filter;
a pixel measurement unit that measures and indicates the width of the extracted wrap-around in pixels; and
A wrap-around determination unit that uses the measured pixels to determine pass or fail for wrap-around detection based on a preset pixel.
A wraparound detection device in a silicon solar cell, including a wraparound detection device. According to clause 6,
Image capture unit that captures images of the silicon solar cell using a digital microscope
Wraparound detection device in a silicon solar cell, further comprising: In clause 7,
The image capture unit,
After the wrap-around removal process occurs during the silicon solar cell process, images of the silicon solar cell are taken using a digital microscope.
A wraparound detection device in a silicon solar cell, characterized by: According to clause 6,
The wraparound determination unit,
Determining pass or fail for the wrap-around detection through image reading based on machine learning
A wraparound detection device in a silicon solar cell, characterized by: According to clause 6,
If the wrap-around detection is determined to be a failure, an etch unit to etch the wrap-around portion of the solar cell using in-line wet etching equipment.
Wraparound detection device in a silicon solar cell, further comprising: