A solar cell testing method and system

Abstract

The application discloses a solar cell testing method and system, and aims to solve the problem of how to improve testing accuracy. The solar cell testing method comprises the following steps: providing a cell piece; testing the cell piece by a non-contact testing method to obtain a light energy image; measuring original light emission intensity of the light energy image; performing dark field calibration and / or plane field calibration on the original light emission intensity to obtain calibrated light emission intensity; and calculating performance parameters of the cell piece according to the calibrated light emission intensity. The dark field calibration can eliminate the influence of the electric signal caused by the light energy capturing device itself. In addition, the plane field calibration on the light energy image can reduce the adverse effects caused by lens vignetting and non-uniform response of the sensor on the test solution, and improve the testing accuracy.

Description

Technical Field

[0001] This invention relates to the field of solar cell testing technology, and in particular to a solar cell testing method and system. Background Technology

[0002] Non-contact IV testing of solar cells involves irradiating the cells with light to obtain a light intensity image. This image is then processed to calculate the IV electrical performance of the solar cell. The testing process does not require contact with the cells, reducing damage and eliminating the limitations imposed by the cell grid lines. However, the accuracy of existing non-contact IV testing methods for solar cells needs further improvement. Summary of the Invention

[0003] The purpose of this invention is to provide a solar cell testing method and system to improve the accuracy of test results.

[0004] In a first aspect, the present invention provides a method for testing solar cells, comprising: A solar cell is provided, the solar cell having opposing first and second sides; Solar cells were tested using a non-contact testing method to obtain light energy images; The raw luminous intensity of the light energy image was measured; The raw luminescence intensity of the light energy image is calibrated by dark field calibration and / or planar field calibration to obtain the calibrated luminescence intensity; The performance parameters of the solar cell are calculated based on the calibrated luminous intensity.

[0005] When using the above technical solution, during the testing of the solar cell using a non-contact testing method, the original luminous intensity of the measured light energy image is calibrated in a dark field and / or a planar field, and the performance parameters of the solar cell are calculated using the calibrated luminous intensity. The applicant found that the main reason for the need to improve the accuracy of the test results using existing non-contact testing methods is that: when testing the solar cell under weak light illumination, the thermal effect electrical signal (i.e., dark current background noise) generated by the sensor of the light energy harvesting device increases significantly compared to the weak effective signal emitted after the solar cell is excited. This background noise, when superimposed on the effective signal, severely interferes with the signal-to-noise ratio. Secondly, due to the low intensity of the excited weak light signal itself, system errors such as edge light flux attenuation caused by lens vignetting of the light energy harvesting device and non-uniform response between sensor pixels are further amplified under weak light illumination, causing the luminous intensity distribution of the light energy image to fail to accurately reflect the luminous state of the solar cell.

[0006] Therefore, this application, through the above-described technical solution, improves accuracy by performing at least the following calibration steps when testing solar cells under weak light: Firstly, dark-field calibration subtracts background electrical signals generated by sensor thermal effects, eliminating noise interference from the signal source. Secondly, planar-field calibration normalizes the light energy image, effectively compensating for spatial response inconsistencies caused by lens vignetting and sensor non-uniformity. Through this dual calibration mechanism, even when testing solar cells under weak light, a calibrated luminous intensity accurately reflecting the state of the solar cells can be obtained, significantly improving the accuracy of subsequent calculations of solar cell performance parameters.

[0007] In some possible implementations, the raw luminous intensity of the light energy image is measured, including: Divide the light energy image into partitions; The original luminous intensity of each region of the light energy image is obtained by measuring the light energy image. The original luminous intensity of each region is combined to obtain the original luminous intensity matrix of the light energy image. Perform dark-field calibration and / or planar-field calibration on the raw luminescence intensity of the light energy image to obtain the calibrated luminescence intensity, including: Dark field calibration and / or planar field calibration are performed on the original luminous intensity of each region of the light energy image to obtain the calibrated luminous intensity of each region, and the calibrated luminous intensity matrix is ​​obtained by combining them.

[0008] By employing the above technical solution, dividing the light energy image into partitions allows for more precise and refined individual processing of each partition, further improving the accuracy of the test.

[0009] In some possible implementations, a partition comprises one or more pixels of the light energy image. Thus, partitioning according to the pixels of the light energy image allows for pixel-level processing of the image, resulting in more refined processing and further improving the accuracy of the test.

[0010] In some possible implementations, the performance parameter is the series resistance; The solar cells were tested using a non-contact testing method to obtain light energy images, including: By illuminating different positions on the first surface at least twice with a light source, light-receiving areas and non-light-receiving areas corresponding to different positions are formed on the first surface; Multiple local photoluminescence images generated by the illuminated area and multiple local electroluminescence images generated by the non-illuminated area are captured using a light energy capture device at different locations. Multiple local photoluminescence images are stitched together to obtain a photoluminescence image characterizing the solar cell, and multiple local electroluminescence images are stitched together to obtain an electroluminescence image characterizing the solar cell. The raw luminous intensity of the obtained light energy image includes: The original photoluminescence intensity of the photoluminescence image and the original electroluminescence intensity of the electroluminescence image were measured. Perform dark-field calibration and / or planar-field calibration on the raw luminescence intensity of the light energy image to obtain the calibrated luminescence intensity, including: The original photoluminescence intensity is calibrated by dark field calibration and / or plane field calibration to obtain the calibrated photoluminescence intensity; the original electroluminescence intensity is calibrated by dark field calibration and / or plane field calibration to obtain the calibrated electroluminescence intensity. The performance parameters of the solar cell are calculated based on the calibrated luminous intensity, including: Substitute the calibrated photoluminescence intensity and the calibrated electroluminescence intensity into Formula 1 to calculate the series resistance; Formula 1; Among them, V t For thermal voltage, R s For series resistance, A and B are both fitting linearity coefficients, PL is the calibration photoluminescence intensity, and EL is the calibration electroluminescence intensity.

[0011] Using the above technical solution, the series resistance of a solar cell is tested by illuminating the cell with a light source. Local photoluminescence images are obtained in the illuminated area, and local electroluminescence images are obtained in the non-illuminated areas on either side of the illuminated area. These local photoluminescence images are stitched together to form a photoluminescence image characterizing the solar cell, and the electroluminescence images are stitched together to form an electroluminescence image characterizing the solar cell. The original photoluminescence intensity and the original electroluminescence intensity of the electroluminescence image are measured separately. After calibrating the original photoluminescence intensity and the original electroluminescence intensity, the calibrated photoluminescence intensity and the calibrated electroluminescence intensity are substituted into Formula 1 to calculate the series resistance. Using the calibrated light intensity for processing improves the accuracy of the series resistance test.

[0012] In some possible implementations, after partitioning the light energy image, both the photoluminescence image and the electroluminescence image have multiple partitions. The performance parameters of the solar cell are calculated based on the calibrated luminescence intensity, including: The calibrated photoluminescence intensity of each region of the photoluminescence image is combined to obtain the calibrated photoluminescence intensity matrix characterizing the first surface; The calibrated electroluminescence intensity of each region of the electroluminescent image is combined to obtain the calibrated electroluminescence intensity matrix characterizing the first surface; Substituting the calibration photoluminescence intensity matrix and the calibration electroluminescence intensity matrix into Formula 2, the series resistance matrix is ​​calculated. Formula 2; The series resistance is obtained by averaging the series resistance matrix. Among them, V t For thermal voltage, R s（x，y） For the series resistance matrix, A and B are both fitting linear coefficients, PL （x，y） To calibrate the photoluminescence intensity matrix, EL （x，y） To calibrate the electroluminescence intensity matrix.

[0013] Using the above technical solution, the solar energy image is partitioned to achieve a fine calculation of the series resistance of each partition. Finally, the average is calculated to obtain the series resistance of the solar cell, which further improves the accuracy of the series resistance.

[0014] In some possible implementations, the optical energy image includes multiple regions of interest and multiple pseudo-main grid regions, with the regions of interest and pseudo-main grid regions alternately arranged along a first direction; The series resistance is obtained by averaging the series resistance matrix, including: Multiple series resistors corresponding to multiple regions of interest are selected in the series resistance matrix, and their average value is calculated to obtain the series resistance of the solar cell.

[0015] When using the above technical solution, since the optical energy image is composed of images from multiple different regions stitched together, there are overlapping parts at the stitching points. The overlapping parts cannot accurately reflect the luminous intensity of the optical energy image. Therefore, the image stitching position can be called the pseudo-main grid region, and the region between adjacent stitching positions is the region of interest. The region of interest can more accurately reflect the luminous intensity of the optical energy image. Therefore, when calculating the series resistance, the accuracy of the series resistance can be improved by averaging the series resistances of multiple regions of interest in the obtained series resistance matrix.

[0016] In some possible implementations, in the first direction, the width of the region of interest is 0.01 to 0.99 times the distance between two adjacent pseudo-gate regions. This allows the width of the region of interest to more comprehensively characterize the overall area of ​​the solar cell without including unrealistic luminous intensity, thereby improving the accuracy of series resistance testing.

[0017] In some possible implementations, dark field calibration includes: Dark-field images are obtained using a completely light-blocking light-capturing device, and the dark-field luminescence intensity matrix of the dark-field images is measured. The original luminous intensity matrix of the light energy image is subtracted from the dark field luminous intensity matrix of the dark field image to obtain the calibrated luminous intensity matrix after dark field calibration.

[0018] When the above technical solution is adopted, with the light-harvesting device completely shielded from light, the device acquires a dark-field image. After partitioning the dark-field image, the dark-field luminous intensity of each partition is measured and combined to obtain a dark-field luminous intensity matrix. Subtracting the dark-field luminous intensity matrix from the original luminous intensity matrix of the measured solar cell image yields the calibrated luminous intensity of each partition after dark-field calibration. This calibrated luminous intensity matrix is ​​then combined to form the calibration luminous intensity matrix, thereby eliminating the influence of the electrical signals generated by the light-harvesting device itself during operation on the test results and improving test accuracy.

[0019] In some possible implementations, planar field calibration includes: Select sample solar cells that have a uniform response to the light source; Illuminate one entire side of the sample solar cell to obtain a planar field image of the sample solar cell, and measure the original planar field luminescence intensity matrix of the planar field image; The average luminous intensity matrix of the planar field is obtained from the original planar field luminous intensity matrix; The plane field average luminous intensity matrix is ​​divided by the original plane field luminous intensity matrix to obtain the plane field correction coefficient matrix; The original luminous intensity matrix of the light energy image is multiplied by the planar field correction coefficient matrix to obtain the calibrated luminous intensity matrix after planar field correction.

[0020] By employing the above technical solution, illuminating the entire surface of a sample battery cell with a uniform response to the light source can eliminate the influence of non-uniform light source response. Multiplying the original planar field luminous intensity matrix of the planar field image by the planar field correction coefficient matrix eliminates lens vignetting caused by the light-capturing device's lens and the non-uniform response of the sensor, resulting in a calibrated luminous intensity matrix after planar correction. This calibrated luminous intensity matrix improves the accuracy of parameter calculations.

[0021] In some possible implementations, dark-field calibration and planar-field calibration are performed on the raw luminescence intensity of the light energy image, including: Dark-field images are obtained using a completely light-blocking light-capturing device, and the dark-field luminescence intensity matrix of the dark-field images is measured. The difference between the original luminous intensity matrix of the light energy image and the dark field luminous intensity matrix of the dark field image is used to obtain the calibrated luminous intensity matrix after dark field calibration. The net planar field luminescence intensity matrix is ​​obtained by subtracting the original planar field luminescence intensity matrix of the planar field image from the dark field luminescence intensity matrix of the dark field image. The average luminous intensity matrix of the planar field is obtained from the net planar field luminous intensity matrix. The plane field average luminous intensity matrix is ​​divided by the net plane field luminous intensity matrix to obtain the plane field correction coefficient matrix; Multiply the calibration luminescence intensity matrix after dark field calibration by the plane field correction coefficient matrix to obtain the calibration luminescence intensity matrix after dark field calibration and plane field calibration.

[0022] By adopting the above technical solution, dark field calibration and planar field calibration are performed on the original luminous intensity matrix of the light energy image. At the same time, the influence of the electrical signal generated by the light energy capturing device itself during operation on the test results is eliminated, as well as the lens vignetting caused by the lens of the light energy capturing device and the non-uniform response of the sensor, which further improves the accuracy of the test.

[0023] In some possible implementations, the performance parameter is the parallel resistance. When testing the solar cell using a non-contact testing method to obtain a light energy image, the first surface is illuminated with a low-intensity light source, and the light energy image is calibrated in a dark field. Thus, dark field calibration can improve the accuracy of the non-contact method for testing the parallel resistance of the solar cell.

[0024] In a second aspect, the present invention also provides a solar cell testing system, which employs the solar cell testing method described in any of the above claims. The solar cell testing system includes a light source, a light energy capture device, a luminous intensity measuring device, and an image processing device. The light source is used to illuminate the solar cells and sample solar cells; The light energy capturing device is used to obtain the light energy image generated after the first surface is irradiated, to obtain the dark field image of the light energy capturing device, and to obtain the planar field image of the sample battery cell; The luminous intensity measurement device is used to measure the original luminous intensity of the light energy image, the dark field luminous intensity matrix of the dark field image, and the original planar field luminous intensity matrix of the planar field image; The image processing device is used to perform dark field calibration and / or planar field calibration on the raw luminous intensity of the light energy image to obtain the calibrated luminous intensity, and to calculate the performance parameters of the solar cell based on the calibrated luminous intensity.

[0025] Since the solar cell testing system adopts the solar cell testing method described above, it has the same beneficial effects as those described above, and will not be repeated here. Attached Figure Description

[0026] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a schematic flowchart of a solar cell testing method provided in an embodiment of the present invention; Figure 2 A schematic diagram of a solar cell testing method provided in an embodiment of the present invention, showing a light energy image obtained. Figure 3 A comparison chart of series resistance data obtained by different testing methods.

[0027] Figure labels: 100 represents the region of interest, and 200 represents the pseudo-main grid region. Detailed Implementation

[0028] To make the technical problems to be solved, the technical solutions, and the beneficial effects of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present invention and are not intended to limit the present invention.

[0029] It should be noted that when a component is referred to as being "fixed to" or "set on" another component, it can be directly on or indirectly on that other component. When a component is referred to as being "connected to" another component, it can be directly connected to or indirectly connected to that other component.

[0030] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified. "Several" means one or more, unless otherwise explicitly specified.

[0031] In the description of this invention, it should be understood that the terms "upper", "lower", "front", "rear", "left", "right", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0032] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0033] Please see Figure 1 and Figure 2 As shown, this embodiment of the invention provides a solar cell testing method, including the following steps: Step S100: A battery cell is provided, the battery cell having a first side and a second side facing each other.

[0034] The solar cell has electrodes on at least its first surface. The electrodes can be grid electrodes, which may include main grid electrodes and / or fine grid electrodes.

[0035] Step S200: Test the solar cell using a non-contact testing method to obtain a light energy image.

[0036] Non-contact testing involves irradiating the solar cell with light, exciting it to produce photoluminescence or fluorescence at a specific wavelength corresponding to the excitation intensity. This photoluminescence or fluorescence can be captured by a light-harvesting device to obtain a light image. By processing this light image, the IV electrical performance of the solar cell can be calculated. Non-contact testing methods do not require clamps to contact the solar cell, reducing damage and eliminating the limitations imposed by grid electrodes.

[0037] Step S300: Measure the original luminous intensity of the light energy image. That is, after measuring the light intensity of the light energy image, the original luminous intensity is obtained.

[0038] Step S400: Perform dark-field calibration and / or planar field calibration on the original luminous intensity of the light energy image to obtain the calibrated luminous intensity. Dark-field calibration can be performed only on the original luminous intensity, or planar field calibration can be performed only on the original luminous intensity, or both dark-field and planar field calibrations can be performed on the original luminous intensity to obtain the calibrated luminous intensity after different calibration methods.

[0039] Step S500: Calculate the performance parameters of the solar cell based on the calibrated luminous intensity. Performance parameters include the cell's series resistance, parallel resistance, short-circuit current, open-circuit voltage, and fill factor.

[0040] When using the above technical solution, during non-contact testing of the solar cell, the original luminous intensity of the measured light energy image is calibrated in a dark field and / or a planar field, and the performance parameters of the solar cell are calculated using the calibrated luminous intensity. The applicant found that the accuracy of the test results using existing non-contact testing methods needs improvement because, when testing the solar cell under weak light illumination, the thermal effect electrical signal (i.e., dark current background noise) generated by the sensor of the light energy harvesting device increases significantly compared to the weak effective signal emitted after the solar cell is excited. This background noise, when superimposed on the effective signal, severely interferes with the signal-to-noise ratio. Secondly, due to the low intensity of the excited weak light signal itself, errors such as edge light flux attenuation caused by lens vignetting of the light energy harvesting device, non-uniform response between sensor pixels, and non-uniform response of the solar cell to the light source are further amplified under weak light conditions, causing the luminous intensity distribution of the light energy image to fail to accurately reflect the luminous state of the solar cell.

[0041] Therefore, this application, through the above-described technical solution, performs at least the following calibration steps to improve accuracy when testing solar cells under weak light: Firstly, dark-field calibration subtracts background electrical signals generated by sensor thermal effects, eliminating noise interference from the signal source. Secondly, planar-field calibration normalizes the light energy image, effectively compensating for spatial response inconsistencies caused by lens vignetting, sensor non-uniform response, and the solar cell's non-uniform response to the light source. Through this dual calibration mechanism, even when testing solar cells under weak light, a calibrated luminous intensity accurately reflecting the solar cell's state can be obtained, significantly improving the accuracy of subsequent calculations of solar cell performance parameters.

[0042] In some embodiments, the measurement of the original luminous intensity of the light energy image in step S300 above specifically includes the following steps: Step S301: Divide the light energy image into partitions. The light energy image can be partitioned in a rectangular array manner to obtain multiple partitions arranged in a horizontal and vertical matrix.

[0043] Step S302: Measure the light energy image to obtain the original luminous intensity of each region of the light energy image, and combine the original luminous intensities of each region to obtain the original luminous intensity matrix of the light energy image. By measuring each region of the light energy image to obtain the original luminous intensity of each region, the original luminous intensities of each region are statistically analyzed according to the horizontal and vertical matrix arrangement of each region, and combined to obtain the original luminous intensity matrix of the entire light energy image.

[0044] Based on this, the original luminous intensity of the light energy image in step S400 above is calibrated in the dark field and / or in the plane field to obtain the calibrated luminous intensity, specifically including the following steps: Step S401 involves performing dark-field calibration and / or planar field calibration on the original luminous intensity of each region of the optical energy image to obtain the calibrated luminous intensity of each region, and combining these calibrated luminous intensity values ​​to obtain a calibration luminous intensity matrix. In other words, the original luminous intensity of each region of the optical energy image is individually calibrated using the same method: either dark-field calibration, planar field calibration, or both. This yields the calibrated luminous intensity corresponding to each region. These calibrated luminous intensities are then statistically analyzed according to the matrix arrangement of each region and combined to obtain the calibration luminous intensity matrix of the entire optical energy image. Alternatively, this can be understood as performing the same calibration operation on each original luminous intensity in the original luminous intensity matrix to obtain the calibration luminous intensity matrix.

[0045] By employing the above technical solution, dividing the light energy image into partitions and measuring and calibrating each partition separately, more precise and refined individual processing of each partition can be achieved. Finally, the results of each partition are averaged, further improving the accuracy of the test results.

[0046] In other embodiments, besides partitioning the light energy image before measurement and calibration, the entire light energy image can also be measured and calibrated. This involves measuring the total raw luminous intensity of the entire light energy image, followed by overall dark-field calibration and / or planar field calibration of the total raw luminous intensity. This overall measurement and calibration method can also improve the accuracy of the test results compared to uncalibrated test results.

[0047] In some embodiments, a partition of the light energy image includes one or more pixels of the light energy image. Different light energy capturing devices produce different numbers of pixels in their resulting light energy images. If a partition includes only one pixel, the number of partitions is determined by the number of pixels in the light energy image obtained by the light energy capturing device itself. Therefore, when measuring and calibrating the raw luminous intensity of each partition, each pixel is measured and calibrated individually. Both the resulting raw luminous intensity matrix and the calibrated luminous intensity matrix contain the same number of data points as the pixels in the light energy image, achieving pixel-level fine-grained processing of the light energy image and further improving the accuracy of the test results.

[0048] When a partition comprises multiple pixels, it can include any number of adjacent pixels. A region consisting of multiple pixels is considered a partition. The number of pixels in different partitions can be the same or different. For ease of statistical calculation, the number of pixels in each partition is preferably the same, and the partitions are arranged in a rectangular array. Correspondingly, the fewer pixels a partition has, the more partitions are obtained, resulting in more refined processing of the light energy image; conversely, the more pixels a partition has, the fewer partitions are obtained. The original luminous intensity of a partition is the sum of the original luminous intensities of all pixels within that partition. When measuring and calibrating the original luminous intensity of each partition, measuring and calibrating each partition as a whole allows for refined processing and calculation, improving the accuracy of the test results.

[0049] In some embodiments, when the performance parameter being tested is series resistance, the step S200 above, which involves testing the solar cell using a non-contact testing method to obtain a light energy image, includes the following steps S201 to S203: In step S201, the light source illuminates different positions of the first surface at least twice to form light-receiving areas and non-light-receiving areas corresponding to different positions on the first surface.

[0050] For example, by successively approaching different masking areas of the first surface using at least one mask, the unmasked areas of the first surface are illuminated under the same lighting conditions. That is, by bringing the mask close to the first surface of the solar cell, masked and unmasked areas are formed on the first surface. When a light source illuminates the entire first surface of the solar cell, the light only shines on the unmasked areas of the solar cell, which become the illuminated areas, while the masked areas become the unilluminated areas. Since the cutout areas of different masks are different and do not overlap, the corresponding masked and unmasked areas formed on the solar cell are different and do not overlap, meaning the illuminated areas do not overlap. It should be noted that at least one mask can be used, or one or more masks can be used; when there is only one mask, it can either approach and mask one masking area of ​​the first surface only once, or it can approach and mask different masking areas of the first surface multiple times. When multiple photomasks are used (at least two), each photomask performs one masking operation. These photomasks can successively mask different areas of the first surface. This method directly masks the solar cell using photomasks. Because the photomasks are close to the solar cell, the accuracy of the masking pattern is easy to control. It is suitable for various types of light, such as parallel or diffused light, and is less likely to illuminate the solar cell outside the cutout area of ​​the photomask.

[0051] In another example, at least one mask can be used to successively block the light source, allowing the light emitted by the light source under the same illumination conditions to pass through the perforated pattern of the mask and illuminate different positions on the first surface. In other words, the light source is directly blocked by the mask to adjust the range of the emitted light, ensuring that the light passes through the perforated pattern of the mask and illuminates different positions on the solar cell. This light source is preferably a planar laser light source, emitting parallel light. This method can be simply referred to as the grating method. It should be noted that at least one mask can be used, or one or more masks. When there is only one mask, the light source is blocked by multiple successive proximity blocks at different positions, allowing the light to pass through the perforated pattern and illuminate different positions on the first surface. When there are multiple masks, i.e., at least two, each mask blocks the light source once, and these masks can be used multiple successive proximity blocks at different positions, allowing the light to pass through the perforated pattern and illuminate different positions on the first surface.

[0052] In another example, a different method is provided for illuminating different areas of the first surface of the solar cell. Specifically, by successively adjusting the range of the emitted light from the light source, the emitted light is successively illuminating different positions on the first surface. That is, instead of adjusting the illuminated area on the solar cell using a mask, the range of its emitted light is adjusted by the light source itself, such as through line laser scanning. This is equivalent to creating a local shading effect on the solar cell, resulting in illuminated and unilluminated areas. It should be noted that the range of the emitted light from the light source can be adjusted multiple times.

[0053] It should be noted that the sum of the irradiated areas of the solar cell from at least two illuminations is greater than or equal to the total area of ​​the first surface of the solar cell. The irradiated areas at different positions on the first surface overlap or are seamlessly connected. The areas from at least two illuminations can be pieced together to form the entire first surface of the solar cell. In other words, the sum of the irradiated areas of the multiple irradiated areas formed after at least two illuminations is greater than or equal to the total area of ​​the first surface, ensuring that the irradiated areas from at least two illuminations cover the entire first surface. By irradiating the entire first surface from at least two different positions, a light energy image of the entire solar cell can be obtained, leading to more comprehensive and accurate test results.

[0054] Step S202: Use a light energy capture device to capture multiple local photoluminescence images generated by the light-receiving area and multiple local electroluminescence images generated by the non-light-receiving area at different locations.

[0055] In this process, under each illumination, a light-receiving area formed at a location on the solar cell absorbs photons and enters an excited state. These excited electrons are metastable and, within a short time, return to their ground state, emitting light of a specific wavelength—this is photoluminescence, producing a localized photoluminescence image in the light-receiving area. Photogenerated carriers in the light-receiving area then propagate laterally to the non-light-receiving areas on either side, forming an induced current. This current excites electroluminescence at localized locations in the non-light-receiving areas near the light-receiving area, resulting in a first and a second localized electroluminescence image located on either side of the localized photoluminescence image. The widths of the first and second localized electroluminescence images are approximately the same as the width of the overall localized photoluminescence image.

[0056] Step S203: stitch together multiple local photoluminescence images to obtain a photoluminescence image characterizing the solar cell, and stitch together multiple local electroluminescence images to obtain an electroluminescence image characterizing the solar cell.

[0057] Based on the obtained photoluminescence and electroluminescence images, the measurement of the original luminescence intensity of the light energy image in step 300 above includes the following steps: Step S311: Measure the original photoluminescence intensity of the photoluminescence image and the original electroluminescence intensity of the electroluminescence image. It should be noted that the order in which the original photoluminescence intensity and the original electroluminescence intensity are measured is not limited, and they can be measured simultaneously.

[0058] Next, the original luminous intensity of the light energy image in step S400 above is calibrated in the dark field and / or in the plane field to obtain the calibrated luminous intensity, including the following steps: Step S411: Perform dark-field calibration and / or planar-field calibration on the original photoluminescence intensity to obtain the calibrated photoluminescence intensity; perform dark-field calibration and / or planar-field calibration on the original electroluminescence intensity to obtain the calibrated electroluminescence intensity. The order of calibration for the original photoluminescence intensity and the original electroluminescence intensity is not limited, and they can be calibrated simultaneously.

[0059] Next, the calculation of the cell's performance parameters based on the calibrated luminous intensity in step S500 above includes the following steps: Step S501: Substitute the calibrated photoluminescence intensity and calibrated electroluminescence intensity into Formula 1 to calculate the series resistance; Formula 1; Among them, V t For thermal voltage, R s V represents the series resistance, A and B are both linear fitting coefficients, PL is the calibrated photoluminescence intensity, and EL is the calibrated electroluminescence intensity. t=KT / q=0.02568, V t The given values ​​are: K, T, and q. K is the Boltzmann constant; T is the thermodynamic temperature of the solar cell; and q is the charge of electrons. Both T and q can be measured beforehand and are known values. This formula is a variation of Ohm's law; by taking the logarithm of the photoluminescence intensity and the electroluminescence intensity, the corresponding voltage value can be obtained.

[0060] Using the above technical solution, the series resistance of a solar cell is tested by illuminating the cell with a light source. Local photoluminescence images are obtained in the illuminated area, and local electroluminescence images are obtained in the non-illuminated areas on either side of the illuminated area. These local photoluminescence images are stitched together to form a photoluminescence image characterizing the solar cell, and the electroluminescence images are stitched together to form an electroluminescence image characterizing the solar cell. The original photoluminescence intensity and the original electroluminescence intensity of the electroluminescence image are measured separately. After calibrating the original photoluminescence intensity and the original electroluminescence intensity, the calibrated photoluminescence intensity and the calibrated electroluminescence intensity are substituted into Formula 1 to calculate the series resistance. This method is applicable to cases where the solar cell resistance is uniform or non-uniform. Using the calibrated light intensity improves the accuracy of the series resistance test.

[0061] In some embodiments, when testing the series resistance by partitioning the light energy image, after partitioning the light energy image, both the photoluminescence image and the electroluminescence image have multiple partitions, and the number, size, and position of the partitions in the photoluminescence image and the electroluminescence image are the same. The partition can be a pixel-level partition or a partition larger than the pixel level. Then, the calculation of the performance parameters of the solar cell based on the calibrated luminous intensity in step S500 above includes the following steps: Step S511: Combine the calibrated photoluminescence intensities of each region of the photoluminescence image to obtain a calibrated photoluminescence intensity matrix characterizing the first surface. The calibrated photoluminescence intensity of each region is obtained by performing dark-field calibration and / or planar field calibration on the original photoluminescence intensities measured for each region.

[0062] Step S512: Combine the calibrated electroluminescence intensities of each region of the electroluminescence image to obtain an electroluminescence intensity matrix characterizing the first surface. The calibrated electroluminescence intensity of each region is obtained by performing dark-field calibration and / or planar-field calibration on the original electroluminescence intensities measured for each region.

[0063] It should be noted that the order of steps S511 and S512 is not limited, and they can be performed simultaneously. The specific methods for obtaining the calibration luminescence intensity matrix and the calibration electroluminescence intensity matrix can be found in step S401 above regarding the method for obtaining the calibration luminescence intensity matrix, and will not be repeated here.

[0064] Step S513: Substitute the calibration photoluminescence intensity matrix and the calibration electroluminescence intensity matrix into Formula 2 to calculate the series resistance matrix; Formula 2; Among them, V t For thermal voltage, R s（x，y） For the series resistance matrix, A and B are both fitting linear coefficients, PL （x，y） For photoluminescence intensity matrix, EL （x，y） V represents the electroluminescence intensity matrix. t =KT / q=0.02568, V t The given values ​​are: K, T, and q. K is the Boltzmann constant; T is the thermodynamic temperature of the solar cell; and q is the charge of electrons. Both T and q can be measured beforehand and are known values. Formula two is a variation of Ohm's law; by taking the logarithm of the photoluminescence intensity and the electroluminescence intensity, the corresponding voltage value can be obtained.

[0065] Formula 2 can be understood as follows: after calculating the series resistance of each partition by the calibrated photoluminescence intensity and calibrated electroluminescence intensity of each partition, the series resistance matrix is ​​obtained according to the arrangement combination of the partitions.

[0066] Step S514: Calculate the average value of the series resistance matrix to obtain the series resistance. That is, average the series resistance of each partition.

[0067] Using the above technical solution, the solar energy image is partitioned to achieve a fine calculation of the series resistance of each partition. Finally, the average is calculated to obtain the series resistance of the solar cell, which further improves the accuracy of the series resistance.

[0068] Besides using partitioning to obtain the series resistance, the total original photoluminescence intensity of the photoluminescence image can also be directly calibrated to obtain the total calibrated photoluminescence intensity; similarly, the total original electroluminescence intensity of the electroluminescence image can be directly calibrated to obtain the total calibrated electroluminescence intensity. The series resistance is then calculated by substituting the total calibrated photoluminescence intensity and the total calibrated electroluminescence intensity into Formula 1. This calibration also improves the accuracy of the series resistance calculation.

[0069] like Figure 2As shown, in some embodiments, when testing series resistance, the optical image includes multiple regions of interest 100 and multiple pseudo-gate regions 200, which are alternately arranged along a first direction. The optical image includes photoluminescence and electroluminescence images. Since the photoluminescence image is composed of multiple local photoluminescence images and the electroluminescence image is composed of multiple local electroluminescence images, for example, a light-receiving region is a strip-shaped region, resulting in a strip-shaped local photoluminescence image. The strip-shaped regions located on both sides of the light-receiving region produce electroluminescence, correspondingly resulting in strip-shaped local electroluminescence images. Therefore, the photoluminescence image is composed of multiple strip-shaped local photoluminescence images, and the electroluminescence image is composed of multiple strip-shaped local electroluminescence images. Both photoluminescence and electroluminescence images have overlapping stripes at their respective stitching points. These overlapping areas do not accurately reflect the luminous intensity of the photoluminescence image. Therefore, the stitching location of the photoluminescence image can be called the pseudo-main grid region 200. The brightness of the pseudo-main grid region 200 is lower than that of the other regions, appearing as a relatively dark stripe. The region between adjacent stitching locations is the region of interest 100. The brightness of the region of interest 100 is brighter than that of the pseudo-main grid region 200, appearing as a relatively bright stripe (e.g., ...). Figure 2 (The area within the red box). The region of interest 100 can accurately reflect the luminous intensity of the light energy image. The strip-shaped region of interest 100 and the strip-shaped pseudo-main grid region 200 are arranged alternately along the first direction. Furthermore, when the solar cell has a main grid electrode, the location of the main grid electrode on the solar cell overlaps with the pseudo-main grid region 200 of the solar energy image of that solar cell. Therefore, to improve the accuracy of the series resistance test, it is necessary to exclude the pseudo-main grid region 200 on the solar energy image and select the region of interest 100 for the series resistance test.

[0070] Specifically, the step 514 above, which involves averaging the series resistance matrix to obtain the series resistance, includes the following steps: selecting multiple series resistances corresponding to multiple regions of interest 100 in the series resistance matrix and averaging them to obtain the series resistance of the solar cell.

[0071] For example, a region of interest 100 may include one or more partitions. The series resistances corresponding to multiple partitions located within multiple regions of interest 100 are averaged. As many regions of interest 100 as possible are selected for calculation so that the calculated series resistance reflects the series resistance of the entire solar cell.

[0072] In some embodiments, in the first direction, the width of the strip-shaped region of interest 100 is 0.01 to 0.99 times the distance between two adjacent strip-shaped pseudo-gate regions 200. For example, the width of the region of interest 100 is 0.01, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, or 0.99 times the distance between two adjacent strip-shaped pseudo-gate regions 200. The distance between two adjacent pseudo-gate regions 200 refers to the distance between two adjacent boundaries of the two adjacent pseudo-gate regions 200. In this way, the width range of the region of interest 100 can more comprehensively characterize the overall area of ​​the solar cell without including unrealistic luminous intensity, thereby improving the accuracy of series resistance testing.

[0073] In some embodiments, the dark field calibration in step S400 above includes the following steps: Step S41: Obtain a dark-field image using a completely light-blocking light-capturing device, and measure the dark-field luminescence intensity matrix of the dark-field image. The light-capturing device is completely light-blocked, for example, by covering the camera lens. Then, the same operating conditions as the test battery cell are applied, such as the camera exposure time, gain, and operating temperature being identical to those of the actual test battery cell. The light-capturing device can acquire multiple dark-field images within the same field of view. After partitioning each dark-field image, the dark-field luminescence intensity of each partition is measured. The average dark-field luminescence intensity of the same partitions from multiple dark-field images can be calculated. The average dark-field luminescence intensity of each partition is then combined according to the corresponding arrangement of the partitions to obtain the dark-field luminescence intensity matrix.

[0074] Step S42: Subtract the original luminous intensity matrix of the light energy image from the dark field luminous intensity matrix of the dark field image to obtain the calibrated luminous intensity matrix after dark field calibration.

[0075] For example, when performing series resistance testing, the difference between the original photoluminescence intensity matrix of the photoluminescence image and the dark-field emission intensity matrix of the dark-field image is calculated; the difference between the original electroluminescence intensity matrix of the electroluminescence image and the dark-field emission intensity matrix of the dark-field image is calculated. In other words, the difference between the original photoluminescence intensity and the dark-field emission intensity for each corresponding partition in both the photoluminescence and dark-field images is calculated to obtain the calibrated photoluminescence intensity matrix after dark-field calibration; the difference between the original electroluminescence intensity and the dark-field emission intensity for each corresponding partition in both the electroluminescence and dark-field images is calculated to obtain the calibrated electroluminescence intensity matrix after dark-field calibration.

[0076] By using the above technical solution, the original luminous intensity matrix of the measured solar cell light energy image is subtracted from the dark field luminous intensity matrix to obtain the calibrated luminous intensity of each zone after dark field calibration. These calibrated luminous intensity matrices are then combined to form the calibrated luminous intensity matrix. This eliminates the influence of dark current background noise generated by the light energy capture device during operation on the test results, achieving refined dark field calibration and improving test accuracy.

[0077] Of course, in addition to obtaining dark field images and dark field luminous intensity by testing under completely dark conditions, dark field calibration can also use a fixed average dark field luminous intensity. The original luminous intensity of all zones is subtracted from this average dark field luminous intensity, which can also achieve the effect of dark field calibration.

[0078] In some embodiments, the planar field calibration in step S400 above includes the following steps: Step S43: Select a sample solar cell that has a uniform response to the light source. For example, a sample solar cell that has a uniform response to laser light is a silicon wafer that has undergone passivation and light injection annealing, and the silicon wafer has an extremely high and uniform minority carrier lifetime.

[0079] Step S44: Illuminate one entire side of the sample solar cell to obtain a planar field image of the sample solar cell, and measure the original planar field luminous intensity matrix of the planar field image. During this process, the same operating conditions as the test solar cell are used; for example, the camera exposure time, gain, and operating temperature are the same as those of the actual test solar cell. The light-capturing device acquires the planar field image, which can be acquired multiple times to obtain multiple planar field images within the same field of view. After partitioning each planar field image, the original planar field luminous intensity of each partition is measured. The average original planar field luminous intensity of the same partitions in multiple planar field images can be calculated. The averaged original planar field luminous intensities of each partition are combined according to the corresponding arrangement of the partitions to obtain the original planar field luminous intensity matrix.

[0080] Step S45: Obtain the average luminous intensity matrix of the planar field based on the original planar field luminous intensity matrix. That is, calculate the average value of the original planar field luminous intensity of all partitions in the original planar field luminous intensity matrix, so that the luminous intensity of each partition has the same average value, and obtain the average luminous intensity matrix of the planar field.

[0081] Step S46: Divide the planar field average luminous intensity matrix by the original planar field luminous intensity matrix to obtain the planar field correction coefficient matrix. That is, divide the planar field average luminous intensity by the original planar field luminous intensity corresponding to each partition to obtain the planar field correction coefficient corresponding to that partition, and combine the planar field correction coefficients of each partition according to the partition arrangement to obtain the planar field correction coefficient matrix.

[0082] Step S47: Multiply the original luminous intensity matrix of the light energy image with the planar field correction coefficient matrix to obtain the calibrated luminous intensity matrix after planar field correction.

[0083] For example, when performing series resistance testing, the original photoluminescence intensity matrix of the photoluminescence image is multiplied by the planar field correction coefficient matrix; the original electroluminescence intensity matrix of the electroluminescence image is multiplied by the planar field correction coefficient matrix. That is, the original photoluminescence intensity of the photoluminescence image and the planar field correction coefficient matrix for each corresponding partition are multiplied by the planar field correction coefficient to obtain the calibrated photoluminescence intensity matrix after planar field calibration; the original electroluminescence intensity of the electroluminescence image and the planar field correction coefficient matrix for each corresponding partition are multiplied by the planar field correction coefficient to obtain the calibrated electroluminescence intensity matrix after planar field calibration.

[0084] By employing the above technical solution, illuminating the entire surface of a sample battery cell with a uniform response to the light source can eliminate the influence of non-uniform light source response. Multiplying the original planar field luminous intensity matrix of the planar field image by the planar field correction coefficient matrix and then normalizing the light energy image effectively compensates for spatial response inconsistencies caused by lens vignetting and sensor non-uniform response. This yields a calibrated luminous intensity matrix after planar field calibration, which improves the accuracy of parameter calculations.

[0085] In some embodiments, if both dark-field calibration and planar-field calibration are performed on the original luminous intensity of the light energy image, then the dark-field calibration and planar-field calibration of the original luminous intensity of the light energy image in step S400 above includes the following steps: Step S41': Obtain a dark-field image using a completely light-blocking light-capturing device, and measure the dark-field luminescence intensity matrix of the dark-field image. For details, please refer to the description of step S41 above; it will not be repeated here.

[0086] Step S42': Subtract the original luminous intensity matrix of the light energy image from the dark field luminous intensity matrix of the dark field image to obtain the calibrated luminous intensity matrix after dark field calibration. This completes one dark field calibration of the original luminous intensity of the light energy image. For details, please refer to the description of step S42 above, which will not be repeated here.

[0087] Step S43': Subtract the original planar field luminescence intensity matrix of the planar field image from the dark field luminescence intensity matrix of the dark field image to obtain the net planar field luminescence intensity matrix. In this step, a secondary dark field calibration is performed on the original planar field luminescence intensity of the planar field image.

[0088] Step S44': Obtain the average luminous intensity matrix of the planar field based on the net planar field luminous intensity matrix. Refer to the description of step S43 above; simply replace the original planar field luminous intensity matrix in step S43 with the net planar field luminous intensity matrix. Further details are omitted.

[0089] Step S45': Divide the average luminous intensity matrix of the planar field by the net planar field luminous intensity matrix to obtain the planar field correction coefficient matrix. See the description of step S44 above for details, which will not be repeated here.

[0090] Step S46': Multiply the calibration luminescence intensity matrix after dark-field calibration by the planar field correction coefficient matrix to obtain the calibration luminescence intensity matrix after both dark-field and planar field calibrations. See the description of step S45 above for details, which will not be repeated here.

[0091] It should be noted that step S43' can be omitted in the above method, that is, there is no need to perform secondary dark field calibration on the planar field luminescence intensity. The average luminescence intensity matrix of the planar field can be obtained directly from the original planar field luminescence intensity matrix, and then steps S45' and S46' can be performed.

[0092] Alternatively, in the above scheme, the original luminous intensity matrix and the dark field luminous intensity matrix can be multiplied by the planar field correction coefficient matrix respectively, and the difference between the two multiplied matrices can be obtained to obtain the calibrated luminous intensity matrices after dark field calibration and planar field calibration.

[0093] By adopting the above technical solution, dark field calibration and planar field calibration are performed on the original luminous intensity matrix of the light energy image. At the same time, the influence of the electrical signal generated by the light energy capturing device itself during operation on the test results is eliminated, as well as the problems of lens vignetting, sensor non-uniform response, and light source non-uniform response caused by the lens of the light energy capturing device, which further improves the accuracy of the test.

[0094] In some embodiments, when testing solar cells using a non-contact testing method, the light intensity illuminating the solar cells is less than or equal to 500 W / m². 2 In this environment, the thermal effect electrical signal (i.e., dark current background noise) generated by the sensor of the light-harvesting device increases significantly compared to the weak effective signal emitted after the solar cell is excited. This background noise, superimposed on the effective signal, further severely interferes with the signal-to-noise ratio. Without dark-field calibration, the accuracy of the test results will be low. Therefore, in environments with light intensity less than or equal to 500 W / m², [further testing is necessary]. 2 Dark-field calibration is performed when the light intensity illuminating the solar cell exceeds 500 W / m². 2 Without dark field calibration, the test results still meet the requirements; however, dark field calibration can further improve the accuracy of the test.

[0095] In some embodiments, when the performance parameter being tested is the parallel resistance, a dark-field calibration is performed on the light energy image obtained under low light intensity illumination when testing the solar cell using a non-contact testing method. Since the light energy image obtained under low light intensity illumination more clearly shows the leakage area caused by poor parallel resistance when testing the parallel resistance of the solar cell using a non-contact testing method, a light energy image obtained under low light intensity is required. Therefore, by performing dark-field calibration on the light energy image obtained under low light intensity, the accuracy of the non-contact method for testing the parallel resistance of the solar cell can be improved. Here, low light intensity is defined as light intensity less than 500 W / m². 2 .

[0096] The series resistance of the two groups of solar cells was tested below. The first group of solar cells had abnormal contact resistance, while the second group of solar cells was normally sintered. The series resistance of both groups of solar cells was tested using existing non-contact testing methods (without calibration), the non-contact testing methods of this application (with calibration), and contact testing methods. The specific test data are shown in Table 1 below.

[0097] Table 1. Series resistance measured by three test methods for two sets of solar cells. Through the above test comparison, it can be seen that, for the series resistance test of the first group of solar cells with abnormal contact resistance, the test method in this application, due to its calibration, yields test results closer to the true value and more closely similar to the results of the contact test method compared to existing uncalibrated test methods, and does not affect the test results for normally sintered solar cells. Figure 3 As shown, the correlation between the test results obtained by the test method of this application and the test results obtained by the contact test method is expressed as: y = 0.8059x + 0.0003, and the correlation R of the fitted linearity is... 2 =0.9584. The correlation between the test results obtained by existing non-contact testing methods and those obtained by contact testing methods is expressed as: y = 0.6953x + 0.0003, with a correlation coefficient R0. 2 =0.9386. It can be seen that the correlation between the calibrated test results and the actual test results of the proposed test method is improved by about 2%, meaning the test accuracy is improved by about 2%.

[0098] Based on the solar cell testing method described in any of the above embodiments, this invention also provides a solar cell testing system. The solar cell testing system employs the solar cell testing method described in any of the above embodiments, and includes a light source, a light energy capture device, a luminous intensity measuring device, and an image processing device. The light source is used to irradiate the solar cell and a sample solar cell; the light source can be a line-scan laser light source or an array light source (such as an LED lamp). The light energy capture device is used to obtain a light energy image generated after the first surface is irradiated, a dark field image of the light energy capture device, and a planar field image of the sample solar cell; the light energy capture device can be a camera, such as an industrial camera. The luminous intensity measuring device is used to measure the original luminous intensity of the light energy image, the dark field luminous intensity matrix of the dark field image, and the original planar field luminous intensity matrix of the planar field image. The image processing device is used to perform dark field calibration and / or planar field calibration on the original luminous intensity of the light energy image to obtain a calibrated luminous intensity, and calculate the performance parameters of the solar cell based on the calibrated luminous intensity. Since the solar cell testing system uses the above-described solar cell testing method, it has the same beneficial effects as described above, and will not be repeated here.

[0099] In the description of the above embodiments, specific features, structures, materials, or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0100] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for testing solar cells, characterized in that, include: A battery cell is provided, the battery cell having opposing first and second sides; The solar cell was tested using a non-contact testing method to obtain a light energy image; The original luminous intensity of the light energy image was measured; The original luminous intensity of the light energy image is calibrated in a dark field and / or in a planar field to obtain the calibrated luminous intensity; The performance parameters of the solar cell are calculated based on the calibrated luminous intensity.

2. The solar cell testing method according to claim 1, characterized in that, The measurement of the raw luminous intensity of the light energy image includes: The light energy image is divided into partitions; The light energy image is measured to obtain the original luminous intensity at each partition of the light energy image, and the original luminous intensity at each partition is combined to obtain the original luminous intensity matrix of the light energy image; The step of performing dark-field calibration and / or planar-field calibration on the original luminous intensity of the light energy image to obtain the calibrated luminous intensity includes: The original luminous intensity at each partition of the light energy image is calibrated in the dark field and / or in the plane field to obtain the calibrated luminous intensity at each partition, and then combined to obtain the calibrated luminous intensity matrix.

3. The solar cell testing method according to claim 2, characterized in that, One of the partitions comprises one or more pixels of the light energy image.

4. The solar cell testing method according to any one of claims 1-3, characterized in that, The performance parameter is the series resistance; The method of testing the solar cell using a non-contact testing approach to obtain a light energy image includes: The first surface is illuminated at least twice at different locations by a light source, so as to form a light-receiving area and a non-light-receiving area corresponding to the different locations on the first surface; A light energy capture device is used to capture multiple local photoluminescence images generated in the light-receiving area corresponding to different locations and multiple local electroluminescence images generated in the non-light-receiving area; The multiple local photoluminescence images are stitched together to obtain a photoluminescence image characterizing the solar cell, and the multiple local electroluminescence images are stitched together to obtain an electroluminescence image characterizing the solar cell. The measurement of the raw luminous intensity of the light energy image includes: The original photoluminescence intensity of the photoluminescence image and the original electroluminescence intensity of the electroluminescence image are measured. The step of performing dark-field calibration and / or planar-field calibration on the original luminous intensity of the light energy image to obtain the calibrated luminous intensity includes: The original photoluminescence intensity is calibrated in a dark field and / or in a plane field to obtain a calibrated photoluminescence intensity; the original electroluminescence intensity is calibrated in a dark field and / or in a plane field to obtain a calibrated electroluminescence intensity. The calculation of the performance parameters of the solar cell based on the calibrated luminous intensity includes: Substitute the calibrated photoluminescence intensity and the calibrated electroluminescence intensity into Formula 1 to calculate the series resistance; Formula 1; Among them, V t For thermal voltage, R s For series resistance, A and B are both fitting linearity coefficients, PL is the calibration photoluminescence intensity, and EL is the calibration electroluminescence intensity.

5. The solar cell testing method according to claim 4, characterized in that, After partitioning the light energy image, both the photoluminescence image and the electroluminescence image have multiple partitions. The calculation of the battery cell's performance parameters based on the calibrated luminescence intensity includes: The calibrated photoluminescence intensity of each region of the photoluminescence image is combined to obtain a calibrated photoluminescence intensity matrix characterizing the first surface; The calibrated electroluminescence intensity of each region of the electroluminescent image is combined to obtain a calibrated electroluminescence intensity matrix characterizing the first surface; Substituting the calibration photoluminescence intensity matrix and the calibration electroluminescence intensity matrix into Formula 2, the series resistance matrix is ​​calculated. Formula 2; The series resistance is obtained by averaging the series resistance matrix. Among them, V t For thermal voltage, R s（x，y） For the series resistance matrix, A and B are both fitting linear coefficients, PL （x，y） To calibrate the photoluminescence intensity matrix, EL （x，y） To calibrate the electroluminescence intensity matrix.

6. The solar cell testing method according to claim 5, characterized in that, The optical energy image includes multiple regions of interest and multiple pseudo-main grid regions, and the regions of interest and the pseudo-main grid regions are alternately arranged along a first direction; The step of averaging the series resistance matrix to obtain the series resistance includes: Multiple series resistors corresponding to multiple regions of interest are selected in the series resistance matrix, and their average value is calculated to obtain the series resistance of the battery cell.

7. The solar cell testing method according to claim 6, characterized in that, In the first direction, the width of the region of interest is 0.01 to 0.99 times the distance between two adjacent pseudo-master gate regions.

8. The solar cell testing method according to claim 2, characterized in that, The dark field calibration includes: A dark field image is obtained by using a completely light-blocking light energy capture device, and the dark field luminescence intensity matrix of the dark field image is measured. The original luminous intensity matrix of the light energy image is subtracted from the dark field luminous intensity matrix of the dark field image to obtain the calibrated luminous intensity matrix after dark field calibration.

9. The solar cell testing method according to claim 2, characterized in that, The planar field calibration includes: Select sample solar cells that have a uniform response to the light source; The entire surface of the sample solar cell is illuminated to obtain a planar field image of the sample solar cell, and the original planar field luminescence intensity matrix of the planar field image is measured. The average luminous intensity matrix of the planar field is obtained based on the original planar field luminous intensity matrix. The plane field average luminous intensity matrix is ​​divided by the original plane field luminous intensity matrix to obtain the plane field correction coefficient matrix; Multiply the original luminous intensity matrix of the light energy image by the planar field correction coefficient matrix to obtain the calibrated luminous intensity matrix after planar field correction.

10. The solar cell testing method according to claim 9, characterized in that, Dark-field calibration and planar-field calibration are performed on the raw luminous intensity of the light energy image, including: A dark field image is obtained by using a completely light-blocking light energy capture device, and the dark field luminescence intensity matrix of the dark field image is measured. The original luminous intensity matrix of the light energy image is subtracted from the dark field luminous intensity matrix of the dark field image to obtain the calibrated luminous intensity matrix after dark field calibration. The net planar field luminescence intensity matrix is ​​obtained by subtracting the original planar field luminescence intensity matrix of the planar field image from the dark field luminescence intensity matrix of the dark field image. The average luminous intensity matrix of the planar field is obtained based on the net planar field luminous intensity matrix. The plane field average luminous intensity matrix is ​​divided by the net plane field luminous intensity matrix to obtain the plane field correction coefficient matrix; Multiply the calibrated luminous intensity matrix after dark field calibration by the plane field correction coefficient matrix to obtain the calibrated luminous intensity matrix after dark field calibration and plane field calibration.

11. The solar cell testing method according to any one of claims 1-3, characterized in that, The performance parameter is the parallel resistance. When the solar cell is tested by a non-contact testing method to obtain the light energy image under low light intensity, the light energy image is calibrated in the dark field.

12. A solar cell testing system, characterized in that, The solar cell testing system, using the solar cell testing method as described in any one of claims 1-11, includes a light source, a light energy capture device, a luminous intensity measuring device, and an image processing device. The light source is used to illuminate the battery cell and the sample battery cell; The light energy capturing device is used to obtain a light energy image generated after the first surface is irradiated, to obtain a dark field image of the light energy capturing device, and to obtain a planar field image of the sample battery cell. The luminous intensity measuring device is used to measure the original luminous intensity of the light energy image, the dark field luminous intensity matrix of the dark field image, and the original planar field luminous intensity matrix of the planar field image; The image processing device is used to perform dark field calibration and / or planar field calibration on the original luminous intensity of the light energy image to obtain the calibrated luminous intensity, and to calculate the performance parameters of the solar cell based on the calibrated luminous intensity.

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