Method for non-contact testing of solar cell IV characteristics

Abstract

The application discloses a kind of non-contact test solar cell IV characteristic method, it is related to optical imaging technology, for improving the problem of inaccurate test and mechanical damage to solar cell caused by poor contact due to contact type test, including setting excitation light source and light energy capture device;Utilize light energy capture device to capture transition light energy and generate light energy image, obtain the pixel point brightness value fluctuation of light energy image and judge light energy capture effect, and select whether to reset for secondary capture;After light energy capture is completed, first, the transition light energy in the local area of solar cell is photoelectric conversion characterization, and the local IV space uniformity difference is obtained;Then, the whole IV of solar cell is characterized, and the comprehensive IV characteristic curve of the whole to-be-tested cell is obtained.

Description

Technical Field

[0001] This invention relates to the field of optical imaging technology, and more specifically, to a method for non-contact testing of the IV characteristics of solar cells. Background Technology

[0002] Existing IV (voltage characteristic) technologies are mostly contact-based testing techniques. They use a solar simulator as a light source and employ probes or special fixtures to contact the positive and negative electrodes of the solar cell to measure voltage (V) and current (I). During the test, the resistance of the electronic load is continuously changed, and the current (I) and voltage (V) of the cell are detected in real time using the contact method, thereby obtaining a complete IV characteristic curve of the cell.

[0003] The existing technology has the following shortcomings:

[0004] As solar cells develop, electrodes become smaller and smaller, making it impossible for traditional contact-type fixtures to make good contact with solar cells. This results in an inability to effectively draw current, ultimately leading to inaccurate testing, poor repeatability, and mechanical damage to the solar cells during testing, which can cause defects such as microcracks in the finished cells. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a method for non-contact testing of the IV characteristics of a solar cell. This method involves exciting a light source to release light energy with a stepped intensity variation onto the solar cell under test, causing it to produce photoluminescence or fluorescence. A light-harvesting device captures the fluorescence information of the solar cell under different illuminations. The brightness of the fluorescence image under different light intensities can be directly correlated with the voltage (V). Simultaneously, since the current of a solar cell is linearly related to the light intensity, different light intensities also imply different currents (I) in the cell. Thus, the voltage V of the solar cell under test at different currents I is indirectly obtained. Using these different I and V values, an integrated IV characteristic curve of the solar cell under test can be plotted, thereby solving the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for non-contact testing of the IV characteristics of a solar cell, comprising step S1: setting excitation light source parameters, including excitation frequency, excitation light intensity gradient and wavelength range;

[0007] Step S2: Set the parameters of the light energy harvesting device, including the detection start wavelength, the termination wavelength, the cutoff depth, and the signal gain;

[0008] Step S3: Drive the excitation light source to irradiate the solar cell under test under different excitation light intensities, and simultaneously capture the light energy images under different excitation light intensities through the light energy capture device;

[0009] Step S4: Obtain the pixel brightness value of the light energy image, determine the light energy capture effect, and select whether to reset the excitation light source parameters or the light energy capture device parameters based on the effect, and perform secondary capture.

[0010] Step S5: Establish the relationship between image brightness and electrical performance based on the captured light energy image, perform local analysis on the light energy image to obtain the local uniformity difference distribution of the solar cell under test, and integrate and analyze the overall light energy image to plot the overall IV characteristic curve of the solar cell under test.

[0011] In a preferred embodiment, in step S1, the selection of the excitation frequency needs to take into account the relationship between photon energy and penetration depth, the excitation intensity gradient needs to cover all test points from low light intensity to high light intensity, and the wavelength range needs to be set according to the photoluminescence characteristics of the solar cell material under test.

[0012] In a preferred embodiment, in step S2, the setting of the detection start wavelength and the stop wavelength needs to be based on the photoluminescence characteristics of the solar cell material under test, the setting of the cutoff depth needs to be combined with the thickness of the solar cell under test and the photon penetration characteristics, and the setting of the signal gain needs to be dynamically adjusted according to the change of light intensity.

[0013] In a preferred embodiment, in step S3, the light energy image and its corresponding pixel brightness value are recorded for each excitation light intensity. If the light energy capture effect is not good, the parameters of the excitation light source or the light energy capture device need to be readjusted and a second capture is performed.

[0014] In a preferred embodiment, during step S3, the light intensity gradient and detection wavelength range need to be optimized during the secondary capture to improve the quality of the light energy image.

[0015] In a preferred embodiment, in step S4, the average brightness of each pixel in the light energy image is calculated and used as the main indicator for evaluating the light energy capture effect. If the average value is lower than a preset threshold, the light energy capture effect is determined to be poor, and the parameters of the excitation light source or the light energy capture device need to be reset.

[0016] In a preferred embodiment, in step S4, when resetting the parameters of the excitation source or the light energy capture device, the intensity gradient of the excitation source and the detection wavelength range of the light energy capture device are adjusted first.

[0017] In a preferred embodiment, in step S5, the voltage value of the cell under test is derived from the brightness of the light energy image, and the voltage value of the cell under test under different currents is indirectly obtained by changing the light intensity of the excitation light source. The IV characteristic curve of the solar cell under test is plotted using these data.

[0018] In a preferred embodiment, in step S5, the solar cell under test is divided into several small regions, and light energy images of each region are captured under different excitation light intensities. The average brightness of each region is calculated, and regions with excellent or poor performance are identified by comparing the average brightness of each region.

[0019] In a preferred embodiment, in step S5, the entire solar cell under test is treated as an analysis area. The overall IV characteristics of the solar cell under test are analyzed based on the captured overall light energy image, and the overall IV characteristic curve of the solar cell under test is further plotted by integrating the data from each area.

[0020] The technical effects and advantages of this invention are as follows:

[0021] 1. This invention first establishes an excitation source and a light energy capture device, enabling the system to possess the initial hardware capability for testing IV characteristics. The excitation source emits light energy with varying intensity across a preset wavelength band to irradiate the cell under test; the cell under test is excited, producing photoluminescence or fluorescence corresponding to the excitation intensity in a specific wavelength band; the light energy capture device captures the fluorescence and generates a corresponding light energy image; based on the pixel brightness and fluctuations of the light energy image, the light energy capture effect is judged, and a choice is made whether to accept the light energy image or reset the excitation source and light energy capture device to perform a secondary capture of the transition light energy. After obtaining a satisfactory light energy image, the cell under test is first analyzed in sections to obtain an IV characteristic non-uniformity distribution map; then, the entire cell under test is analyzed to obtain the overall IV characteristic curve of the solar cell. This method can efficiently and accurately test the cell under test and avoids the mechanical damage caused by contact measurement. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of a non-contact testing method for the IV characteristics of solar cells according to the present invention.

[0023] Figure 2 This invention relates to a capture device for a non-contact testing method for the IV characteristics of solar cells. Figure 1 .

[0024] Figure 3 This invention relates to a capture device for a non-contact testing method for the IV characteristics of solar cells. Figure 2 .

[0025] Figure 4 This invention relates to a capture device for a non-contact testing method for the IV characteristics of solar cells. Figure 3 .

[0026] Figure 5 This invention relates to a capture device for a non-contact testing method for the IV characteristics of solar cells. Figure 4.

[0027] Figure 6 This is an IV characteristic curve diagram of a non-contact testing method for the IV characteristics of solar cells according to the present invention. Detailed Implementation

[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] An excitation source emits light energy with varying intensity across a preset wavelength band to irradiate the cell under test. The cell is excited, producing photoluminescence or fluorescence corresponding to the excitation intensity in a specific wavelength band. A light capture device captures the fluorescence and generates a corresponding light energy image. Based on the pixel brightness and fluctuations of the light energy image, the light capture effect is assessed, and a choice is made between accepting the image or resetting the excitation source and light capture device to re-capture the transition light energy. After obtaining a satisfactory light energy image, the cell under test is first analyzed in sections to obtain an IV characteristic non-uniformity distribution map. Then, the entire cell under test is analyzed to obtain the overall IV characteristic curve of the solar cell.

[0030] Example 1

[0031] Please see Figures 1 to 6 A non-contact method for testing the IV characteristics of solar cells, the specific operation process is as follows:

[0032] Step S1: Set the excitation source parameters, including excitation frequency, excitation light intensity gradient, and wavelength range;

[0033] Step S2: Set the parameters of the light energy harvesting device, including the detection start wavelength, the termination wavelength, the cutoff depth, and the signal gain;

[0034] Step S3: Drive the excitation light source to irradiate the solar cell under test under different excitation light intensities, and simultaneously capture the light energy images under different excitation light intensities through the light energy capture device;

[0035] Step S4: Obtain the pixel brightness value of the light energy image, determine the light energy capture effect, and select whether to reset the excitation light source parameters or the light energy capture device parameters based on the effect, and perform secondary capture.

[0036] Step S5: Establish the relationship between image brightness and electrical performance based on the captured light energy image, perform local analysis on the light energy image to obtain the local uniformity difference distribution of the solar cell under test, and integrate and analyze the overall light energy image to plot the overall IV characteristic curve of the solar cell under test.

[0037] First, in step S1, the parameters of the excitation source need to be set, including the excitation frequency, excitation light intensity gradient, and wavelength range.

[0038] The selection of the excitation source frequency needs to take into account the relationship between photon energy and penetration depth. Higher frequencies result in higher photon energy, which makes it easier to excite electrons in the solar cell under test to a high energy state, thereby generating a fluorescence effect. However, if the frequency is too high, the photon penetration depth will be shallower, and it will not be able to fully reflect the overall characteristics of the cell from top to bottom. Therefore, the selection of the excitation source frequency needs to comprehensively weigh multiple factors.

[0039] The intensity gradient of the excitation light source needs to cover the intensity of all test points from low to high light intensity. The more gradients there are, the denser the test points are, and the more complete the IV curve will be.

[0040] In the high-light test area, the light intensity of the excitation source needs to be consistent with the light intensity value of the traditional contact test. In the low-light test area, the light intensity of the excitation source needs to be able to generate sufficient fluorescence signal and be effectively distinguished from background noise.

[0041] The wavelength range of the excitation light source needs to be set according to the material characteristics of the solar cell under test to ensure that the photon energy of the excitation light source can be absorbed by the cell and produce photoluminescence.

[0042] Adjusting the excitation frequency can adapt to the response characteristics of different materials or tissues to different frequency light signals, improve the signal modulation depth and recognition sensitivity, and set the excitation intensity gradient to help construct a nonlinear response curve, enhance the system's adaptability in high and low reflectivity regions, expand the dynamic response range, and set the wavelength range to cover the possible absorption or fluorescence excitation range of the target, thereby improving spectral compatibility and analytical resolution.

[0043] In step S2, the parameters of the light energy harvesting device need to be set, including the detection start wavelength, the termination wavelength, the cutoff depth, and the signal gain.

[0044] These parameters need to be considered comprehensively to eliminate interference from the excitation source itself and capture only the fluorescence signal emitted by the solar cell under test.

[0045] The setting of the detection start and stop wavelengths must be based on the photoluminescence characteristics of the solar cell material under test to ensure that the captured photon signals cover all key wavelength bands.

[0046] The cutoff depth setting needs to be combined with the thickness of the solar cell under test and the photon transmission characteristics to ensure that the captured signal can reflect the photon transitions inside the cell.

[0047] The signal gain setting needs to be dynamically adjusted according to changes in light intensity in order to obtain a clear light energy image under different light intensities.

[0048] like Figure 2 As shown, the light energy harvesting device is located between the excitation source and the solar cell under test. The positional relationship must ensure that the light energy harvesting device can effectively receive the photon signal emitted by the solar cell under test, while avoiding direct interference from the excitation source.

[0049] Setting the detection start wavelength and end wavelength can effectively limit the detection window, receiving only signals within the target response band range, suppressing background stray light interference, and improving spectral selectivity. The cutoff depth setting is based on the optical bandpass / cutoff filtering characteristics of the selected sensor, further shielding non-target spectral components and reducing the system false detection rate. The signal gain adjustment enables fine amplification of weak light signals, improving signal recognition capabilities in low light intensity scenarios, while avoiding saturation distortion in strong signal ranges.

[0050] In step S3, the excitation light source is driven to irradiate the solar cell under test under different excitation light intensities, and the light energy images under different excitation light intensities are captured synchronously by the light energy capture device.

[0051] During this process, it is necessary to record the light energy image and its corresponding pixel brightness value under each light intensity.

[0052] Changes in pixel brightness values ​​can be used to evaluate the light capture effect. If the light capture effect is poor, the parameters of the excitation light source or the light capture device need to be readjusted and a second capture should be performed.

[0053] During secondary capture, it is necessary to focus on optimizing the light intensity gradient and the detection wavelength range to improve image quality.

[0054] The distance between the excitation light source and the solar cell under test needs to be adjusted according to the actual testing requirements to ensure that the light intensity of the excitation light source can uniformly cover the surface of the solar cell under test while avoiding excessive light intensity that could damage the surface of the cell.

[0055] The distance between the light-harvesting device and the solar cell under test also needs to be set appropriately to ensure that the light-harvesting device can receive a sufficiently strong photon signal while avoiding signal saturation.

[0056] Achieving Light Intensity-Response Curve Construction: Light energy images acquired under multi-level excitation light intensities can be used to construct the light intensity-electric response mapping relationship of solar cells, evaluate the linearity, saturation characteristics, and dynamic response range of their photoelectric conversion capability, and enhance the ability to identify defect areas: Some latent defects (such as microcracks, material inhomogeneities, or surface contamination) may only exhibit local abnormal responses under specific light intensity conditions. By comparing images under different light intensities, such latent defects can be effectively revealed, improving the sensitivity and accuracy of defect detection, and enhancing the dimensionality and robustness of image data: Image data acquired under multi-intensity excitation has stronger feature diversity, which helps to conduct multi-dimensional modeling and analysis based on image processing or machine learning algorithms, improving the generalization ability and discrimination stability of the model.

[0057] After obtaining the pixel brightness values ​​of the light energy image in step S4, they need to be analyzed in detail.

[0058] First, the average pixel brightness of each light energy image is calculated and used as the main indicator for evaluating the light energy capture effect.

[0059] If the average value is lower than the preset threshold, the light energy capture effect is determined to be poor, and the parameters of the excitation source or the light energy capture device need to be reset.

[0060] When resetting, prioritize adjusting the intensity gradient of the excitation source and the detection wavelength range of the light capture device. After secondary capture is completed, the light capture effect needs to be re-evaluated until the requirements are met.

[0061] In practice, the light energy capture effect can be optimized by adjusting the frequency and intensity of the excitation light source, as well as the cutoff depth and signal gain of the light energy capture device.

[0062] For example, when the brightness of the light energy image is low, the light intensity of the excitation source can be appropriately increased or the signal gain of the light energy capturing device can be increased. When the brightness of the light energy image is high, the light intensity of the excitation source can be appropriately reduced or the signal gain of the light energy capturing device can be reduced to avoid signal saturation.

[0063] Achieving closed-loop control of image quality: By statistically analyzing brightness values ​​(such as average brightness, maximum / minimum grayscale values, brightness distribution uniformity, etc.), it is possible to determine whether the image is too dark, overexposed, or has insufficient local contrast, and adjust parameters in a timely manner to avoid invalid data acquisition, thereby enhancing system adaptability: Different solar cells have differences in spectral reflectivity, surface texture, and defect distribution. This step can dynamically adjust parameters such as the light intensity, wavelength, or detector gain of the excitation light source based on real-time image feedback, enhancing the system's adaptability to different test objects and improving data validity and analysis accuracy: By judging whether the acquired image meets the set quality threshold and performing necessary secondary capture, low-quality images can be effectively filtered out, avoiding the impact of input data deviation on subsequent feature extraction and diagnostic judgment, improving the stability and accuracy of the overall system output, and supporting parameter self-learning and algorithm fusion: The brightness value evaluation mechanism can be combined with machine learning models as the basis for image quality annotation, training light energy capture parameter optimization strategies, and forming an intelligent, self-learning system adjustment model;

[0064] In step S5, the relationship between image brightness and electrical performance is established based on the captured light energy image.

[0065] Since the photoluminescence brightness of a solar cell is related to the degree of separation of its quasi-Fermi level, and the degree of separation of the quasi-Fermi level is directly related to the voltage, the voltage value of the cell under test can be derived from the brightness of the photoluminescence image.

[0066] Meanwhile, the current of a solar cell is linearly related to the light intensity. By changing the light intensity of the excitation source, the voltage value of the cell under test at different currents can be indirectly obtained.

[0067] These data can be used to plot the IV characteristic curve of the solar cell under test.

[0068] Furthermore, by performing zonal analysis on the light energy image, the local uniformity difference distribution in different regions of the tested solar cell can be obtained.

[0069] For example, by calculating the average brightness of each area and comparing it with the overall average brightness, areas with excellent or poor performance can be identified.

[0070] Enhancing Local Defect Identification: Through image segmentation or region analysis, the brightness differences and electrical performance fluctuations of each sub-region can be quantified, identifying local performance degradation caused by microcracks, uneven doping, passivation layer defects, etc., thereby obtaining a spatial distribution map of local uniformity differences in the solar cell. Supporting Overall Performance Characteristic Mapping: Based on the integration of full-image brightness-electrical performance data, the overall IV characteristic curve is plotted through integral fitting or modeling methods to express the current-voltage relationship under illumination intensity, thus reflecting the overall energy conversion capability of the solar cell and improving detection efficiency and automation: This image modeling method is a non-destructive, fast, area array analysis method, which has advantages such as strong parallelism, comprehensive coverage, and stable output compared to traditional point measurement methods. It can support online detection and intelligent sorting, and build a visual analysis platform: Combining image processing results and IV curve analysis results, a visual analysis interface can be formed to display the overall performance trend and local abnormal areas in a linked manner, assisting maintenance personnel in making rapid judgments and decisions.

[0071] By integrating data from various regions, the overall IV characteristic curve of the cell under test can be further plotted.

[0072] like Figure 5 The figure shows the IV characteristic curve plotted based on the brightness analysis of the light energy image. The schematic diagram illustrates the voltage and current correspondence obtained through a non-contact method.

[0073] In practical applications, the solar cell under test can be divided into several small regions, and the light energy images of each region under different light intensities can be captured and the average brightness of each region can be calculated.

[0074] By comparing the average brightness of each area, areas with excellent or poor performance can be identified.

[0075] For example, if the average brightness of a certain area is significantly higher than that of other areas, it can be judged that the electrical performance of that area is better; conversely, it can be judged that the electrical performance of that area is worse.

[0076] Furthermore, the entire solar cell under test is treated as an analysis area, and the overall IV characteristics of the cell under test are analyzed based on the captured overall light energy image.

[0077] This method not only allows us to obtain the overall IV characteristic curve of the solar cell under test, but also identifies regions with excellent or poor performance, providing an important basis for subsequent process improvements.

[0078] In the specific implementation of this invention, the positional relationship between the excitation light source and the light energy harvesting device needs to be precisely adjusted to ensure that the light energy harvesting device can receive the photon signal emitted by the solar cell under test while avoiding direct interference from the excitation light source.

[0079] The frequency, intensity, and wavelength range of the excitation light source need to be optimized according to the material characteristics of the solar cell under test and the testing requirements to ensure that the photon energy of the excitation light source can be absorbed by the cell and produce photoluminescence.

[0080] The detection start wavelength, stop wavelength, cutoff depth, and signal gain of the light energy harvesting device need to be optimized according to the photoluminescence characteristics of the solar cell under test and the test environment to ensure that the light energy harvesting device can accurately capture the photon signal emitted by the solar cell under test, while eliminating interference from the excitation source.

[0081] The above steps enable non-contact IV characteristic testing of the solar cell under test, generating high-quality light energy images, and ultimately plotting accurate and reliable IV characteristic curves.

[0082] To enable those skilled in the art to fully understand and implement this invention, the specific implementation principles of this invention are further supplemented below with a specific application scenario.

[0083] In actual testing, the solar cell under test must first be placed in a fixed position between the excitation source and the light energy capture device.

[0084] like Figure 2 As shown, the excitation light source is located on both sides above the solar cell under test, while the light energy harvesting device is arranged directly above the cell. Their relative positions are precisely adjusted to ensure that the light energy harvesting device can effectively receive the fluorescence signal emitted by the solar cell under test, while avoiding direct interference from the excitation light source.

[0085] In this step, the distance between the excitation light source and the solar cell under test needs to be adjusted so that the light intensity of the excitation light source uniformly covers the surface of the solar cell under test. A suitable wavelength range and light intensity step are set according to the material characteristics of the cell, so as to ensure that the photon energy can be absorbed by the cell and produce photoluminescence.

[0086] Next, the excitation light source is driven to release light energy of different intensities according to preset parameters.

[0087] At this time, the light energy capture device synchronously records the light energy image under each illumination.

[0088] like Figure 1 As shown, in step S3, the light energy capturing device captures a series of light energy images, each image corresponding to a specific excitation light intensity.

[0089] To ensure the accuracy of the captured information, the signal gain of the light energy capture device needs to be dynamically adjusted to adapt to signal changes under different light intensity conditions.

[0090] For example, when the excitation light intensity is low, the signal gain can be appropriately increased to enhance the capture capability of weak signals; while under high light intensity conditions, the signal gain can be reduced to avoid signal saturation.

[0091] In addition, the settings for the detection start and stop wavelengths need to be optimized based on the photoluminescence characteristics of the solar cell under test to ensure that the captured photon signals cover all key wavelength bands.

[0092] After acquiring the light energy images, the data analysis phase begins.

[0093] like Figure 1 As shown, the brightness distribution of each test point can be obtained by calculating the pixel brightness values ​​of the light energy image.

[0094] The core of this process lies in establishing the relationship between brightness and electrical performance.

[0095] Since the brightness of photoluminescence is related to the degree of separation of the quasi-Fermi level, and the degree of separation of the quasi-Fermi level is directly related to the voltage, the voltage value of the cell under test can be derived from the brightness.

[0096] Meanwhile, by changing the light intensity of the excitation source, different current conditions are indirectly simulated, thereby plotting the IV characteristic curve.

[0097] During this process, if the average brightness of a certain area deviates significantly from the overall average brightness, it can be determined that there may be performance differences in that area, thereby identifying local uniformity issues in the solar cells.

[0098] To further improve testing accuracy, the solar cell under test can be divided into several small regions, and the light energy images of each region under different light intensities can be captured separately.

[0099] For example, suppose the cell under test is divided into four regions, and a corresponding light energy image is captured for each region and the average brightness is calculated.

[0100] By comparing the brightness distribution of each area, areas with excellent or poor performance can be quickly located.

[0101] This zonal analysis method can not only reveal the overall IV characteristics of the solar cell, but also provide an important basis for subsequent process improvements.

[0102] Throughout the testing process, parameters such as the frequency of the excitation light source, the light intensity gradient, and the cutoff depth of the light energy capture device all need to be optimized and adjusted according to actual requirements.

[0103] For example, when testing silicon-based solar cells, the wavelength range of the excitation light source is usually set in the near-infrared region to match the light absorption characteristics of silicon materials.

[0104] Meanwhile, the cutoff depth of the light energy harvesting device needs to be set in conjunction with the thickness of the solar cell to ensure that the captured signal can fully reflect the photon transitions inside the solar cell.

[0105] Through the above steps, not only can non-contact IV characteristic testing of the solar cell under test be achieved, but also high-quality light energy images can be generated and accurate and reliable IV characteristic curves can be plotted.

[0106] This method effectively solves the problems of mechanical damage and testing errors in traditional contact testing, while significantly improving testing efficiency and accuracy, providing a more scientific technical means for the quality assessment of solar cells.

[0107] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0108] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and inventive constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0109] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0110] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0111] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for non-contact testing of the IV characteristics of solar cells, characterized in that: Includes the following steps: Step S1: Set the excitation source parameters, including excitation frequency, excitation light intensity gradient, and wavelength range; Step S2: Set the parameters of the light energy harvesting device, including the detection start wavelength, the termination wavelength, the cutoff depth, and the signal gain; Step S3: Drive the excitation light source to irradiate the solar cell under test under different excitation light intensities, and simultaneously capture the light energy images under different excitation light intensities through the light energy capture device; Step S4: Obtain the pixel brightness value of the light energy image, determine the light energy capture effect, and select whether to reset the excitation light source parameters or the light energy capture device parameters based on the effect, and perform secondary capture. Step S5: Establish the relationship between image brightness and electrical performance based on the captured light energy image, perform local analysis on the light energy image to obtain the local uniformity difference distribution of the solar cell under test, and integrate and analyze the overall light energy image to plot the overall IV characteristic curve of the solar cell under test.

2. The method for non-contact testing of IV characteristics of solar cells according to claim 1, characterized in that: In step S1, the selection of the excitation frequency needs to take into account the relationship between photon energy and penetration depth. The excitation intensity gradient needs to cover all test points from low to high intensity. The wavelength range needs to be set according to the photoluminescence characteristics of the solar cell material under test.

3. The method for non-contact testing of IV characteristics of solar cells according to claim 1, characterized in that: In step S2, the setting of the detection start wavelength and the stop wavelength must be based on the photoluminescence characteristics of the solar cell material under test, the setting of the cutoff depth must be combined with the thickness of the solar cell under test and the photon penetration characteristics, and the setting of the signal gain must be dynamically adjusted according to the change of light intensity.

4. The method for non-contact testing of IV characteristics of solar cells according to claim 1, characterized in that: In step S3, the light energy image and its corresponding pixel brightness value are recorded under each excitation light intensity. If the light energy capture effect is not good, the parameters of the excitation light source or the light energy capture device need to be readjusted and a second capture is performed.

5. The method for non-contact testing of IV characteristics of solar cells according to claim 4, characterized in that: In step S3, the light intensity gradient and detection wavelength range need to be optimized during the secondary capture to improve the quality of the light energy image.

6. The method for non-contact testing of IV characteristics of solar cells according to claim 1, characterized in that: In step S4, the average brightness of each pixel in the light energy image is calculated and used as the main indicator for evaluating the light energy capture effect. If the average value is lower than the preset threshold, the light energy capture effect is determined to be poor, and the excitation light source parameters or light energy capture device parameters need to be reset.

7. The method for non-contact testing of IV characteristics of solar cells according to claim 6, characterized in that: In step S4, when resetting the parameters of the excitation source or the light energy capture device, priority is given to adjusting the light intensity gradient of the excitation source and the detection wavelength range of the light energy capture device.

8. The method for non-contact testing of IV characteristics of solar cells according to claim 1, characterized in that: In step S5, the voltage value of the cell under test is derived from the brightness of the light energy image, and the voltage value of the cell under test under different currents is indirectly obtained by changing the light intensity of the excitation light source. The IV characteristic curve of the solar cell under test is plotted using these data.

9. A method for non-contact testing of IV characteristics of solar cells according to claim 8, characterized in that: In step S5, the solar cell under test is divided into several small regions, and light energy images of each region are captured under different excitation light intensities. The average brightness of each region is calculated, and regions with excellent or poor performance are identified by comparing the average brightness of each region.

10. A method for non-contact testing of IV characteristics of solar cells according to claim 9, characterized in that: In step S5, the entire solar cell under test is treated as an analysis area. The overall IV characteristics of the solar cell under test are analyzed based on the captured overall light energy image. The overall IV characteristic curve of the solar cell under test is further plotted by integrating the data from each area.

Images