A method and device for detecting performance of a BC component, an electronic device, and a storage medium

Abstract

The application provides a BC component performance detection method and device, electronic equipment and a storage medium. The method comprises the following steps: through the electroluminescent imaging of the BC component by using three electric excitation modes of forward bias, reverse bias and alternating current modulation, a multi-dimensional electroluminescent signal is acquired, and then the performance detection and defect identification of the BC component are realized based on the signal. The application can make up for the defect that the signal information is not comprehensive under the conventional single excitation mode, and effectively improve the detection capability, the pertinence and the accuracy of performance detection.

Description

Technical Field

[0001] This application relates to the field of photovoltaic module testing, and in particular to a method, apparatus, electronic device and storage medium for testing the performance of BC modules. Background Technology

[0002] With the continuous iteration of photovoltaic technology, BC modules have gradually become the mainstream product in the photovoltaic market due to their advantages such as higher conversion efficiency, better appearance consistency, and lower shading loss. The core feature of BC modules is that both positive and negative electrodes are arranged on the back of the module. Compared with traditional front-contact modules, its electrode structure is more complex, the spacing is smaller, and the contact requirements are higher, which puts forward special requirements for module performance testing methods.

[0003] Existing performance testing methods for conventional solar modules (with positive and negative electrodes located on the front and back of the cell, respectively) are relatively mature, mainly including current-voltage characteristic testing, electroluminescence imaging, hot spot testing, insulation withstand voltage testing, and environmental aging testing. These methods form the basis for factory inspection and type testing of conventional modules, and can effectively control the quality of conventional modules. However, due to the unique structure of BC modules, existing conventional testing methods have many shortcomings: First, electroluminescence diagnosis fails. In conventional EL testing, the two-dimensional conductive network on the back of the BC cell leads to complex current distribution, resulting in blurred EL images with low contrast, making it impossible to clearly distinguish defects such as microcracks and broken grids. Second, hot spot risk is misjudged. The hot spot effect mechanism and manifestation of BC modules are different from those of conventional modules, and using existing standards can easily lead to misjudgment. Third, performance parameter interpretation is biased. The resistance parameters of BC modules are fundamentally different from those of conventional modules, and applying existing IV curve analysis models cannot accurately analyze the power loss mechanism. Fourth, the sensitivity for detecting microcracks is insufficient. Conventional EL cannot detect microcrack defects in BC modules, posing a potential quality hazard. Fifth, there is a lack of targeted testing conditions. Existing testing standards do not consider the structural characteristics of BC modules, and the test results cannot truly reflect their performance and quality status.

[0004] Therefore, there is an urgent need for a detection method specifically designed for the structural characteristics of BC components, which can accurately, sensitively, and comprehensively evaluate their performance and defects. Summary of the Invention

[0005] In view of this, embodiments of this application provide a method, apparatus, electronic device and storage medium for testing the performance of BC components, which can achieve in-depth and accurate evaluation of the performance of BC components.

[0006] The technical solution of this application embodiment is implemented as follows:

[0007] In a first aspect, embodiments of this application provide a method for testing the performance of a BC component, comprising the following steps:

[0008] Electroluminescence imaging of the BC component is performed using an electrical excitation mode to obtain the electroluminescence signal of the BC component corresponding to the electrical excitation mode; wherein, the electrical excitation mode includes a forward bias excitation mode, a reverse bias excitation mode, and an AC modulation excitation mode;

[0009] The performance of the BC component is tested based on the electroluminescent signal, and defects in the BC component are identified.

[0010] Secondly, embodiments of this application also provide a BC component performance testing device, the device comprising:

[0011] The excitation module is used to perform electroluminescence imaging on the BC component using an electrical excitation mode, and to acquire the electroluminescence signal of the BC component corresponding to the electrical excitation mode; wherein, the electrical excitation mode includes a forward bias excitation mode, a reverse bias excitation mode, and an AC modulation excitation mode.

[0012] The detection module is used to perform performance testing on the BC component based on the electroluminescent signal and to identify defects in the BC component.

[0013] Thirdly, embodiments of this application also provide an electronic device, including: a processor, a storage medium, and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the storage medium via the bus, and the processor executes the machine-readable instructions to perform the BC component performance detection method according to any one of the first aspects.

[0014] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the BC component performance detection method described in any one of the first aspects.

[0015] The embodiments of this application have the following beneficial effects:

[0016] By integrating three electrical excitation modes—forward bias, reverse bias, and AC modulation—for electroluminescence imaging of BC modules, compared to existing conventional detection methods that rely solely on forward bias, this approach can excite the electrical response of BC modules from multiple dimensions, obtaining richer and more comprehensive electroluminescence signals. This effectively adapts to the unique structure of BC modules where both positive and negative electrodes are located on the back side. Specifically, the forward bias mode captures the basic luminescence characteristics of the module, the reverse bias mode accurately highlights characteristic signals of defect areas such as PN junction leakage, and the AC modulation mode is sensitive to abnormal contact resistance and abnormal carrier transport characteristics. The synergistic effect of these three modes solves the problems of blurred EL images, low defect identification, and difficulty in detecting key defects such as microcracks and broken gates in conventional detection. This significantly improves the targeting of BC module performance testing and the comprehensiveness and accuracy of defect identification, providing more reliable technical support for the core performance evaluation and quality control of BC modules. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating steps S101-S102 provided in the embodiments of this application;

[0019] Figure 2 This is a flowchart illustrating steps S201-S202 provided in the embodiments of this application;

[0020] Figure 3 This is a flowchart illustrating steps S301-S302 provided in the embodiments of this application;

[0021] Figure 4 This is a flowchart illustrating steps S401-S402 provided in the embodiments of this application;

[0022] Figure 5 This is a block diagram illustrating the performance testing principle of the BC component provided in this application embodiment;

[0023] Figure 6 This is a schematic diagram of the BC component performance testing device provided in the embodiments of this application;

[0024] Figure 7 This is a schematic diagram of the composition structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0026] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0027] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0028] In the following description, the terms "first, second, third" are used merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first, second, third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0029] It should be noted that the term "comprising" will be used in the embodiments of this application to indicate the presence of the features declared thereafter, but does not exclude the addition of other features.

[0030] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application and is not intended to limit this application.

[0031] See Figure 1 , Figure 1This is a flowchart illustrating steps S101-S102 of the BC component performance testing method provided in this application embodiment, which will be combined with... Figure 1 Steps S101-S102 shown will be explained.

[0032] In step S101, electroluminescence imaging of the BC component is performed using an electrical excitation mode to obtain the electroluminescence signal of the BC component corresponding to the electrical excitation mode; wherein, the electrical excitation mode includes a forward bias excitation mode, a reverse bias excitation mode, and an AC modulation excitation mode.

[0033] In step S102, the performance of the BC component is tested based on the electroluminescent signal, and defects in the BC component are identified.

[0034] The core difference between BC modules and conventional photovoltaic modules lies in the fact that all electrodes of the BC module are located on the back side, with no electrodes obstructing the front side. While this special structure improves photoelectric conversion efficiency, it also makes it difficult for conventional testing methods to accurately contact the electrodes, the detection signal is susceptible to interference, and defects (such as broken grids or poor contact on the back side) are difficult to identify. Existing conventional EL (electroluminescence) testing only uses a single forward bias excitation, which can only obtain a rough light emission signal from the module surface and cannot capture subtle anomalies in the back electrode network, let alone identify deep defects such as microcracks and poor soldering. However, the embodiments of this application solve this problem at its root by using three electro-excitation modes working in synergy.

[0035] First, electroluminescence imaging of the BC module is performed using electrical excitation modes to acquire the corresponding electroluminescence signals of the BC module under these modes. The electrical excitation modes include forward bias excitation mode, reverse bias excitation mode, and AC modulation excitation mode, breaking the limitations of conventional single excitation modes. Conventional EL testing only uses a single forward bias (usually near the module's operating voltage), resulting in blurry EL images of the BC module with low contrast, making it impossible to clearly identify back-side gate breaks, poor contacts, and deep junction defects. Therefore, this embodiment employs multiple excitation modes, each corresponding to a different detection purpose, stimulating the electrical response of the BC module from different dimensions, providing rich and comprehensive signal support for subsequent defect identification and performance analysis.

[0036] Among them, the forward bias excitation mode corresponds to "Mode A (forward bias mode)", the core function of which is to simulate the normal working state of the BC module by applying a constant forward DC current, the magnitude of which is 10%-25% of the module short-circuit current. For example, for a BC module with a short-circuit current of 10A, the injection current is set between 1.0A and 2.5A. The reverse bias excitation mode corresponds to "Mode B (Reverse Bias Mode)," which applies a constant reverse DC voltage, not exceeding 50% of the module's maximum system voltage (e.g., ±15V). In this mode, defective areas (such as PN junction leakage) will emit light due to avalanche breakdown, while normal areas will not emit light or emit very weak light. The AC modulation excitation mode corresponds to "Mode C (Low-Frequency AC Modulation Mode)," used to supplement the shortcomings of the first two DC excitation modes, capturing defects that DC excitation cannot identify, such as abnormal contact resistance and microcracks. It applies a low-frequency (e.g., 0.1Hz-10Hz) sinusoidal AC voltage, with a peak voltage of ±10% to ±30% of the module's open-circuit voltage. A lock-in amplifier is used to synchronously acquire the EL signal, obtaining amplitude and phase diagrams in phase with the AC excitation. This mode is exceptionally sensitive to contact resistance and carrier transport characteristics. The three modes work synergistically to achieve comprehensive coverage of defects in the BC module.

[0037] Next, building upon the multi-mode electroluminescence signals acquired in the first step, the process transforms from "signal acquisition" to "result output," providing a foundation for subsequent steps such as infrared thermal imaging detection and IV characteristic analysis. This step is adapted to the back contact structure characteristics of the BC module. The electroluminescence signals acquired through multi-mode excitation can effectively capture various defect types that conventional detection methods cannot identify, such as microcracks, broken gates, poor contacts, and junction defects. Simultaneously, it can preliminarily determine the module's basic performance indicators, such as luminescence uniformity and carrier transport efficiency. Compared to existing technologies, this step does not require additional complex detection equipment. It achieves basic performance testing and defect identification of the BC module solely through the analysis of multi-mode electroluminescence signals, balancing detection accuracy and cost, and meeting the testing needs of large-scale production.

[0038] In some embodiments, the AC modulation excitation mode is a low-frequency sinusoidal AC excitation, and when electroluminescence imaging is performed using the AC modulation excitation mode, lock-in amplification technology is used to extract the amplitude and phase information of the electroluminescence signal.

[0039] The purpose of AC modulation excitation mode is to capture minute defects (such as microcracks, minor contact resistance anomalies, and poor solder joints on the back electrode) that cannot be identified by conventional forward and reverse DC excitation. These defects will not produce obvious differences in electroluminescence signals under DC excitation, but under AC modulation excitation, they will produce identifiable signal anomalies due to subtle changes in carrier transport characteristics and resistance characteristics.

[0040] The AC modulation excitation uses a low-frequency sinusoidal AC voltage, specifically ranging from 0.1Hz to 10Hz, with a preferred frequency of 1Hz to 5Hz. This precisely matches the conductivity characteristics of the back electrode of the BC module and the transport velocity of charge carriers within the module. It avoids the signal interference and delayed carrier response issues caused by high-frequency excitation (greater than 10Hz), while also avoiding the low detection efficiency and severe signal attenuation problems associated with low-frequency excitation (less than 0.1Hz). Furthermore, the amplitude of this low-frequency sinusoidal AC excitation can range from 0.5Vpp to 2Vpp, applied superimposed on a forward bias voltage (0.8V-1.0V / cell), ensuring the module is not damaged while effectively stimulating signal anomalies in defect areas, providing precise support for subsequent signal extraction and defect identification.

[0041] In AC modulation excitation mode, the electroluminescence signal generated by the BC component is weak and easily affected by ambient light, circuit noise, etc. Conventional signal extraction methods cannot accurately capture weak signal changes. Therefore, lock-in amplification technology must be used to synchronously demodulate the excitation signal and the detection signal, effectively suppressing ambient noise and interference signals, improving the extraction accuracy of the electroluminescence signal, and achieving an extraction accuracy of nW level, which can clearly capture subtle signal changes caused by tiny defects.

[0042] The specific implementation process of lock-in amplification technology is as follows:

[0043] A low-frequency sinusoidal AC excitation signal is used as a reference signal and input to a lock-in amplifier (LPA). Simultaneously, the electroluminescence signal acquired by an electroluminescence camera is used as a detection signal and also input to the LPA. The LPA performs synchronous demodulation and filtering to extract the effective signal with the same frequency and phase as the reference signal from the detection signal, while removing irrelevant noise signals. This yields the amplitude and phase information of the electroluminescence signal, forming an amplitude map (EL_AC_Amplitude) and a phase map (EL_AC_Phase). The amplitude information reflects the differences in electroluminescence intensity in different regions of the BC module, while the phase information reflects the differences in carrier transport velocity and resistance distribution within the module. Especially for the complex electrode network on the back of the BC module, the phase information can clearly capture carrier transport delays caused by defects such as abnormal contact resistance and microcracks, providing accurate data support for subsequent defect identification and ensuring the accuracy and repeatability of the detection results.

[0044] In some embodiments, while performing electroluminescence imaging on the BC component using the reverse bias excitation mode and the AC modulation excitation mode, infrared thermal imaging detection is simultaneously performed on the BC component to acquire the thermal imaging signal of the BC component.

[0045] The defects in BC components are complex and diverse, including not only visible surface defects such as broken gates and poor contact, but also deep subsurface defects (such as cold solder joints, microcracks, and internal impurity defects) and hot spot defects caused by reverse breakdown. These defects are difficult to identify comprehensively and accurately using electroluminescence imaging alone. Some deep defects do not produce obvious electroluminescence signal anomalies, but they are accompanied by local temperature changes. Therefore, it is necessary to combine thermal signals for cross-validation to achieve dual judgment of "electrical anomaly + thermal anomaly", which can greatly improve the accuracy of defect identification and avoid missed detections and false detections.

[0046] Conventional single electroluminescence detection has a false negative rate of over 15%, especially for deep defects such as cold solder joints and microcracks. However, by combining it with infrared thermal imaging, the false negative rate can be reduced to below 3%. Therefore, this embodiment of the application performs infrared thermal imaging detection simultaneously under both reverse bias and AC modulation excitation modes to acquire thermal imaging signals, achieving dual-dimensional acquisition of "electrical signals + thermal signals".

[0047] Forward bias excitation mode is mainly used to simulate the normal working state of components and identify defects such as surface broken grids and obvious poor contact. These defects can be clearly shown in electroluminescent images. Simultaneous infrared thermal imaging detection will not significantly improve the detection effect, but will increase the detection time and cost. On the other hand, reverse bias and AC modulation excitation modes are mainly used to identify deep defects, micro defects and junction defects. These defects are easily accompanied by local temperature changes. Simultaneous infrared thermal imaging detection can capture these temperature changes, complementing the electroluminescent signal and achieving accurate defect identification.

[0048] In reverse bias excitation mode, defective areas in the BC module (such as PN junction leakage, impurity defects, and local breakdown points) will experience abnormal current concentration due to avalanche breakdown, accompanied by a local temperature increase. This temperature increase is typically 0.5℃-2℃, which, although small, can be accurately detected by infrared thermal imaging. Simultaneous acquisition of thermal imaging signals can precisely locate these junction and leakage defects, cross-validating them with abnormal bright spots in the electroluminescence image to avoid misclassifying normal areas as defective areas. In AC modulation excitation mode, defects such as abnormal contact resistance and microcracks inside the module can cause local carrier transport obstruction, resulting in local energy loss and triggering local thermal wave changes. These thermal wave changes are periodic and synchronized with the frequency of the AC excitation signal. Simultaneous acquisition of thermal imaging signals can capture these subtle thermal changes, complementing the amplitude and phase anomalies of the electroluminescence signal. This effectively identifies deep defects such as microcracks and poor solder joints that conventional electroluminescence imaging cannot detect. This synchronous detection method enables dual verification and precise location of defects, significantly improving the accuracy and reliability of defect identification.

[0049] In some embodiments, the infrared thermal imaging detection is phase-locked thermal imaging detection, used to extract the amplitude and phase information of the thermal wave of the BC component.

[0050] The local temperature changes caused by deep defects in BC modules (such as poor solder joints and microcracks) are extremely small, usually only 0.5℃-2℃, and are easily affected by ambient temperature fluctuations and ambient light radiation. Conventional infrared thermal imaging detection has low accuracy (temperature resolution is usually 0.1℃) and cannot accurately capture such subtle temperature changes, which easily leads to missed detections and false detections. In contrast, phase-locked loop thermal imaging detection, through the synergistic effect of "modulation excitation + synchronous demodulation", can improve the temperature resolution to 0.01℃, effectively suppress the interference of ambient thermal noise, and accurately extract subtle changes in the internal thermal waves of the module, making it particularly suitable for the detection of deep micro-defects in BC modules.

[0051] In AC modulation excitation mode, phase-locked loop (PLL) thermal imaging technology is required to extract the amplitude and phase information of the thermal wave. This technology has extremely high detection sensitivity for subsurface defects (such as cold solder joints, microcracks, and internal impurity defects), with a detection depth of 0.1mm-0.5mm inside the component. Compared with conventional infrared thermal imaging detection, the core advantage of PLL thermal imaging detection lies in "synchronous modulation and demodulation": the AC modulation excitation signal is used as a reference signal and synchronously demodulated with the thermal imaging signal acquired by the infrared thermal imager. This eliminates environmental thermal noise that is out of sync with the reference signal, extracting only the thermal wave signal synchronized with the excitation signal, thereby significantly improving the signal extraction accuracy and clearly capturing thermal wave changes caused by minute defects.

[0052] The specific implementation process of phase-locked thermal imaging detection can be referred to as follows:

[0053] The infrared thermal imager employs an uncooled focal plane array detector with a resolution of at least 640×480 and a frame rate of at least 30fps, enabling real-time acquisition of thermal imaging signals from the BC component surface. The phase-locked-array thermal imaging system uses the AC modulation excitation signal as a reference signal, synchronously demodulating and filtering the acquired thermal imaging signal. Fourier transform is then used to convert the time-domain thermal signal into a frequency-domain signal, ultimately extracting the amplitude and phase information of the thermal wave to form a thermal wave amplitude map (LIT_Amplitude) and a phase map (LIT_Phase). The demodulation frequency is consistent with the frequency of the AC modulation excitation mode, both ranging from 0.1Hz to 10Hz, ensuring accurate capture of thermal wave changes synchronized with the excitation signal and avoiding detection deviations caused by signal misalignment.

[0054] The amplitude information of the thermal wave reflects the degree of temperature difference between the defective area and the normal area. The larger the amplitude, the greater the energy loss in the defective area and the more obvious the temperature difference. This can be used to judge the severity of the defect. For example, the thermal wave amplitude of a severely soldered area is significantly higher than that of a normal area, while the amplitude difference in a slightly soldered area is relatively small. The phase information reflects the propagation characteristics and attenuation law of the thermal wave inside the component. The propagation speed of the thermal wave in the defective area is slower and the attenuation is more intense, resulting in a phase lag compared to the normal area. The amount of phase lag is positively correlated with the depth and size of the defect. This can be used to judge the depth and location of the defect. For example, the phase lag of a deep microcrack area is significantly greater than that of a surface defect area. Phase information can accurately distinguish between surface defects and deep defects. The combination of these two methods can accurately locate the location, size, type, and severity of defects. In particular, for deep defects such as microcracks and soldered areas that cannot be identified by conventional electroluminescence imaging, the phase information extracted by phase-locked thermal imaging can achieve clear identification, further improving the defect detection capability and accuracy of the detection method of this invention.

[0055] In some embodiments, see Figure 2 , Figure 2 This is a flowchart illustrating steps S201-S202 provided in the embodiments of this application. The method further includes steps S201-S202, which will be explained in conjunction with each step.

[0056] In step S201, spatial registration and fusion processing are performed on the images corresponding to the electroluminescence signals acquired under different electrical excitation modes and the images corresponding to the thermal imaging signals acquired simultaneously.

[0057] In step S202, the fused image is analyzed based on preset defect identification rules to achieve automatic identification and classification of hidden cracks, broken grids, poor contact and junction defects of the BC component.

[0058] Electroluminescent and thermal imaging images acquired under different excitation modes may have slight differences in coordinate system and imaging angle due to differences in the installation position, imaging principle, and resolution of the imaging devices (electroluminescent camera and infrared thermal imager). The deviation is usually 1-3 pixels. If these images are analyzed directly, it will lead to defect location deviation and make it impossible to achieve accurate cross-verification of defects. Therefore, it is necessary to first use spatial registration technology to unify the coordinate system of different images to ensure that the position of the same defect corresponds consistently in different images, with the error controlled within 1 pixel.

[0059] The specific implementation process of spatial registration can be carried out in the following way:

[0060] A registration algorithm based on feature point matching is employed. First, feature points (such as defect edges and electrode contours) are extracted from the electroluminescence image (selecting the highest-resolution forward-biased EL image as the reference image). Then, corresponding feature points are extracted from all other images (reverse-biased EL image, AC-modulated EL image, and thermal imaging image). Through feature point matching and coordinate transformation (translation, rotation, and scaling), the coordinate systems of all images are aligned to the coordinate system of the reference image, achieving spatial registration. After registration, a weighted fusion algorithm is used for image fusion. Based on the defect recognition weights of different images (e.g., 0.6 for the electroluminescence image and 0.4 for the thermal imaging image, which can be fine-tuned according to actual detection needs), the pixel information of multiple images is fused to form a fused image. The fused image simultaneously contains electrical defect information from the electroluminescence image (such as the location of broken grids and poor contacts) and thermal defect information from the thermal imaging image (such as the location of junction defects and deep defects), achieving complementary defect information and solving the problems of incomplete defect recognition and inaccurate localization in single images, laying the foundation for subsequent automatic defect identification.

[0061] This application embodiment pre-defines specific identification rules for four core defects of BC components (hidden cracks, broken gates, poor contact, and junction defects). Each defect has clear characteristic manifestations in the fused image (and each original image). This application embodiment summarizes these specific rules as "pre-defined defect identification rules", realizing the automated and accurate classification of defects without manual intervention.

[0062] The preset defect identification rules are as follows:

[0063] 1. Hidden crack: It appears as a continuous linear dark line in the fused image (attenuation of electroluminescence signal), and the thermal wave phase of the corresponding region is significantly lagging (phase map feature of phase-locked thermal imaging). The width of the dark line is 0.01mm-0.1mm and the length is greater than 1mm. If this feature is met, it can be identified as a hidden crack.

[0064] 2. Failed grid: In the fused image, it appears as discrete dark spots or linear dark bands (significant loss of electroluminescence signal), with no obvious thermal anomalies in the corresponding area (no significant increase in thermal wave amplitude), and the width of the dark spot / band is consistent with the width of the finger electrode on the back (usually 0.1mm-0.2mm), which can be identified as a broken grid;

[0065] 3. Poor contact: In the fused image, there are sheet-like or strip-like signal attenuation areas (weakened electroluminescence signal), and the thermal wave amplitude of the corresponding area is slightly increased (0.5℃-1℃), the phase is slightly delayed, and the area is greater than 1mm², which can be identified as poor contact;

[0066] 4. Junction Defects: Bright spots appearing as dots or patches in the fused image (indicating abnormal reverse bias EL signal), with a significant increase in thermal wave amplitude (1℃-2℃) in the corresponding area, and a bright spot diameter of 0.1mm-0.5mm, can be identified as junction defects. After identification, the system will automatically classify and label the defects according to their type, size, and severity, providing a basis for subsequent performance rating.

[0067] In some embodiments, see Figure 3 , Figure 3 This is a flowchart illustrating steps S301-S302 provided in the embodiments of this application. The method further includes steps S301-S302, which will be explained in conjunction with each step.

[0068] In step S301, the BC component is subjected to a current-voltage characteristic test to obtain the IV characteristic curve of the BC component;

[0069] In step S302, a distributed circuit model of the BC component is established, and the resistance parameters inside the BC component are extracted by fitting the IV characteristic curve.

[0070] Existing conventional testing methods can only identify defects in BC modules and measure simple performance parameters (such as open-circuit voltage and short-circuit current). They cannot accurately obtain the internal resistance parameters of the module, nor can they analyze the specific source of power loss (such as whether it is caused by excessive contact resistance or abnormal parallel resistance), thus failing to provide effective guidance for production process improvement. In this embodiment, the overall electrical performance parameters of the module are obtained through IV characteristic testing, and the internal resistance parameters are extracted by inverse fitting through a distributed circuit model. This achieves dual detection of "overall performance + internal mechanism", realizing the purpose of mechanism-level diagnosis, enabling in-depth and accurate evaluation of BC module performance, and taking into account both defect detection and mechanism diagnosis.

[0071] IV characteristic testing is the core method for testing photovoltaic modules, which can comprehensively reflect the electrical performance status of the module. For BC modules, due to their special back electrode structure, IV characteristic testing requires the use of a special back contact test probe to ensure precise contact with the back electrode and avoid test errors caused by poor contact. This is also the core difference between IV characteristic testing of BC modules and conventional modules.

[0072] The specific implementation process for IV characteristic testing can be referred to as follows:

[0073] The test was conducted under standard test conditions (STC), specifically: irradiance 1000 W / m², ambient temperature 25℃, and spectral matching AM1.5G. A high-precision IV curve analyzer was used, with a test range of 0-Voc (open-circuit voltage) and 0-Isc (short-circuit current), with a test accuracy of no less than 0.1%. During testing, the BC module was fixed on an adjustable detection platform. A back-contact probe assembly was used to precisely contact the positive and negative electrodes on the back of the module, ensuring a contact resistance of less than 1 mΩ to avoid affecting the test results. The analyzer gradually adjusted the voltage applied to the module through a scanning method, simultaneously measuring the corresponding current, and finally plotted a complete IV characteristic curve. The curve includes core parameters such as open-circuit voltage (Voc), short-circuit current (Isc), maximum power (Pm), maximum power point voltage (Vm), maximum power point current (Im), and fill factor (FF), providing fundamental data for subsequent performance analysis and parameter extraction. This application retains this core step to ensure the integrity of the detection method, while also conforming to the detection process in the disclosure document, clarifying that the core purpose of the test is to provide data support for subsequent model fitting and parameter extraction.

[0074] The series resistance, parallel resistance, and other parameters of BC modules are fundamentally different from those of conventional modules. Conventional modules use a front electrode structure, and the resistance network is relatively simple, which can be fitted using a single diode model. However, the back electrodes of BC modules are arranged in an alternating manner, and the resistance network is complex, including the parallel resistance of individual cell cells, the line resistance of the back finger electrodes, the volume resistance and contact resistance of the interconnecting solder strips, and other resistances. Simply applying the IV curve analysis model of conventional modules cannot accurately analyze its internal power loss mechanism. Therefore, it is necessary to establish a distributed circuit model specifically adapted to BC modules.

[0075] This distributed circuit model adopts a "single diode + distributed resistor network" structure. Each battery cell corresponds to a single diode sub-model. The diode parameters (reverse saturation current, ideality factor) are adapted according to the battery type of the BC module (such as PERC, TOPCon). The resistor network includes the parallel resistance (Rsh) of a single battery cell, the line resistance (Rf) of the back finger electrodes, the bulk resistance (Rb) and contact resistance (Rc) of the interconnect solder ribbons. Each resistance parameter is initially set according to the structural dimensions of the BC module (such as electrode width, spacing, solder ribbon thickness). The overall output voltage and current of the model are consistent with the actual data obtained from the IV characteristic test. The model parameters are fitted and optimized using the least squares method, so that the IV curve output by the model and the IV curve of the actual test have a fitting degree of more than 99%. After the fitting is completed, the specific values ​​of each resistance parameter can be extracted in reverse, so as to achieve accurate quantitative evaluation of the internal resistor network of the BC module. By extracting these resistance parameters, the specific source of power loss in the module can be accurately located. For example, if the contact resistance (Rc) is too high, it indicates a problem with the back electrode welding process; if the parallel resistance (Rsh) is abnormally low, it indicates a leakage defect in the module. This provides accurate data support for improving the production process and achieves the purpose of mechanism-level diagnosis.

[0076] In some embodiments, the resistance parameters include at least one of the parallel resistance of a single battery cell, the line resistance of the back finger electrode, and the bulk resistance and contact resistance of the interconnecting solder strip.

[0077] The power loss of BC modules mainly comes from three aspects: leakage loss of individual cell (determined by parallel resistance), carrier transport loss of the back electrode (determined by the resistance of the finger electrode line), and connection loss of interconnect solder strips (determined by bulk resistance and contact resistance). Abnormalities in these three types of resistance parameters will directly lead to a decrease in module conversion efficiency and a reduction in fill factor.

[0078] By fitting the IV curve using a distributed circuit model, the key parameters extracted in reverse include the parallel resistance (Rsh) of a single cell, the line resistance (Rf) of the back finger electrodes, and the bulk resistance (Rb) and contact resistance (Rc) of the interconnecting solder strips. These parameters are the core resistance parameters that affect the performance of BC modules and directly determine key performance indicators such as module conversion efficiency, fill factor, open circuit voltage, and short circuit current.

[0079] The specific definitions and test ranges for various resistance parameters are as follows:

[0080] 1. Parallel resistance of a single battery cell (Rsh): refers to the parallel resistance of the PN junction of a single BC battery cell, reflecting the leakage characteristics of the battery cell. The normal range is 1000Ω-5000Ω. If Rsh is less than 1000Ω, it indicates that the battery cell has a leakage defect, which will lead to the degradation of the module power.

[0081] 2. Line resistance (Rf) of the back finger electrode: refers to the resistance per unit length of the back finger electrode of the BC module, reflecting the conductivity of the electrode. The normal range is 0.1Ω / m-0.5Ω / m. If Rf is too large, it will lead to increased carrier transport loss and reduce the module fill factor.

[0082] 3. Body resistance (Rb) and contact resistance (Rc) of interconnect solder strips: Body resistance refers to the resistance of the solder strip itself, with a normal range of 0.01Ω-0.05Ω. Contact resistance refers to the resistance at the contact point between the solder strip and the back electrode, with a normal range of 0.001Ω-0.01Ω. If the sum of the two is too large, it will lead to increased power loss at the interconnect and may even cause local hot spot defects.

[0083] Abnormal parallel resistance of a single cell can lead to module leakage and power degradation. Specifically, a low Rsh will increase the reverse leakage current of the cell. Under forward bias, some current will be lost through the parallel resistance and cannot participate in photoelectric conversion, resulting in a decrease in the module's maximum power and conversion efficiency. In severe cases, it can cause local hot spots. Excessive line resistance of the back finger electrodes will increase carrier transport losses and affect module efficiency. The carriers of the BC module need to be transported to the busbar through the back finger electrodes. Excessive line resistance will increase energy loss during carrier transport, reduce the module's fill factor, and thus affect conversion efficiency. Abnormal bulk resistance and contact resistance of the interconnect solder ribbons will lead to unreliable internal connections, increase power loss, and even cause hot spot defects. Excessive bulk resistance is usually caused by substandard solder ribbon material or insufficient thickness, while excessive contact resistance is usually caused by poor welding process or electrode surface contamination. Both will increase energy loss at the interconnect, raise local temperature, and cause hot spots and damage the module with long-term use.

[0084] In some embodiments, the current-voltage characteristic test is performed under standard test conditions, and the test parameters include at least one of open-circuit voltage, short-circuit current, maximum power, maximum power point voltage, maximum power point current, and fill factor; based on the current-voltage characteristic test parameters, the conversion efficiency of the BC component is calculated.

[0085] The accuracy of IV characteristic testing directly determines the precision of subsequent performance analysis and parameter extraction. Standardized setting of test conditions and parameters is the core guarantee for ensuring test accuracy. For BC modules, due to their unique back electrode structure, fluctuations in test conditions and missing test parameters can lead to significant deviations in test results, failing to accurately reflect the module's true performance.

[0086] IV characteristic tests must be conducted under standard test conditions (STC). The specific parameters of the standard test conditions are: irradiance 1000W / m², ambient temperature 25℃, and spectral matching degree AM1.5G. During the test, an AAA-grade solar simulator is used to provide simulated sunlight that meets the standard. The spectral matching degree error of the solar simulator is ≤±5%, irradiance uniformity is ≤±2%, and time stability is ≤±2% to ensure that the spectrum and intensity of the simulated sunlight are consistent with those of natural sunlight and to avoid interference from environmental factors on the test results.

[0087] During the testing process, the BC module also needs to be pre-treated: the BC module is placed in a constant temperature test chamber and kept at 25℃±0.5℃ for more than 30 minutes to ensure that the module temperature is consistent with the test environment temperature and avoid test deviations caused by temperature fluctuations of the module itself; at the same time, a back contact type detection probe group is used to make precise contact with the back electrode of the module, and the probe pressure is controlled at 0.1MPa-0.2MPa to ensure good contact and not damage the electrode, and the contact resistance is controlled below 1mΩ to avoid the contact resistance affecting the test results.

[0088] Secondly, the specific types of test parameters include at least one of the following: open circuit voltage (Voc), short circuit current (Isc), maximum power (Pm), maximum power point voltage (Vm), maximum power point current (Im), and fill factor (FF). These parameters are the core indicators for evaluating the electrical performance of BC modules.

[0089] Specifically, the following parameters are considered: 1. Open-circuit voltage (Voc): The voltage across the module when there is no load, reflecting the barrier height of the PN junction of the cell. The normal range is 30V-40V (depending on the number of cells in the module); 2. Short-circuit current (Isc): The current when the module is short-circuited, reflecting the magnitude of the photocurrent generated by the module, and positively correlated with irradiance; 3. Maximum power (Pm): The maximum electrical power that the module can output, which is one of the core performance indicators of the module; 4. Maximum power point voltage (Vm) and maximum power point current (Im): The voltage and current corresponding to the module outputting maximum power, used to determine the operating state of the module; 5. Fill factor (FF): The ratio of the module's maximum power to the product of the open-circuit voltage and short-circuit current, reflecting the module's power conversion efficiency. The normal range is 0.75-0.85. The lower the FF, the greater the internal losses of the module.

[0090] Finally, based on the current-voltage characteristic test parameters, the conversion efficiency of the BC module is calculated as η = Pm / (G×A)×100%, where Pm is the maximum power of the module obtained from the IV characteristic test (unit: W), G is the irradiance under standard test conditions (1000W / m²), and A is the effective light-receiving area of ​​the BC module (unit: m²), which is the area of ​​the front of the module minus the area of ​​the edge encapsulation region (typically the edge encapsulation width is 10mm-15mm). For example, if the effective light-receiving area of ​​a certain BC module is 1.6m² and the maximum power obtained from the test is 500W, then its conversion efficiency η = 500 / (1000×1.6)×100% = 31.25%. After the calculation, the accuracy of the conversion efficiency is controlled within ±0.1%, ensuring that it can accurately reflect the true performance level of the module and provide a precise basis for subsequent performance rating and process optimization.

[0091] In some embodiments, see Figure 4 , Figure 4 This is a flowchart illustrating steps S401-S402 provided in the embodiments of this application. The method further includes steps S401-S402, which will be explained in conjunction with each step.

[0092] In step S401, temperature and irradiance parameters in the detection environment are collected in real time.

[0093] In step S402, based on a preset compensation model, environmental compensation calibration is performed on the conversion efficiency, open-circuit voltage, and short-circuit current.

[0094] The electrical performance parameters of BC modules (especially conversion efficiency, open-circuit voltage, and short-circuit current) are extremely sensitive to ambient temperature and irradiance. For example, for every 1°C increase in ambient temperature, the open-circuit voltage of the BC module will decrease by 0.3%-0.4%, and the conversion efficiency will decrease by 0.1%-0.2%. For every 10% deviation of irradiance from the standard value (1000W / m²), the short-circuit current will deviate by about 10%, and the conversion efficiency will also deviate accordingly. Existing conventional testing methods typically do not design a dedicated environmental compensation model for BC modules, but only use general compensation formulas, resulting in insufficient compensation accuracy and large deviations in test results (deviations can reach ±1% or more), failing to accurately reflect the true performance of the module. The embodiments of this application collect environmental parameters in real time and use a dedicated compensation model for calibration, controlling the deviation of the compensated parameters within ±0.3%, achieving the technical advantages of "high detection accuracy and good repeatability".

[0095] The testing system is equipped with a dedicated environmental monitoring module for real-time acquisition of temperature and irradiance parameters of the testing environment. This provides accurate environmental data support for subsequent environmental compensation calibration, avoiding compensation deviations caused by missing or untimely acquisition of environmental parameters. This environmental monitoring module works synchronously with the IV characteristic testing equipment and electroluminescence imaging equipment to ensure that the acquired environmental parameters are synchronized with the test parameters, avoiding compensation errors caused by time differences.

[0096] The specific implementation process for environmental parameter acquisition is as follows: Temperature parameters are acquired through an infrared temperature measurement module, which is installed 5cm-10cm away from the surface of the BC module to avoid the influence of the module's own temperature and equipment heat dissipation. The temperature measurement range is -10℃ to 60℃, the measurement accuracy is ±0.1℃, and the sampling frequency is 1Hz. The air temperature and module surface temperature of the detection environment are collected in real time, and the average value of the two is taken as the temperature parameter for compensation. Irradiance parameters are acquired through an irradiance sensor, which is installed parallel to the light-receiving surface of the BC module, 10cm-15cm away from the module surface to avoid obstruction. The irradiance measurement range is 0-2000W / m², the measurement accuracy is ±1%, and the sampling frequency is 1Hz. The actual irradiance of the detection environment is collected in real time. The acquired temperature and irradiance parameters are transmitted to the computing unit in real time, stored, and used for subsequent compensation calibration calculations to ensure the accuracy and real-time nature of the compensation data.

[0097] The conversion efficiency, open-circuit voltage, and short-circuit current of BC modules are greatly affected by ambient temperature and irradiance. Conventional testing methods do not have a dedicated compensation model for BC modules, resulting in large deviations in test results. Therefore, this application presents a preset compensation model for BC modules, which clarifies the optimized values ​​of temperature compensation coefficient and irradiance compensation coefficient. The relevant parameters are calibrated using formulas to ensure that the calibrated parameters are closer to the true values ​​under standard test conditions.

[0098] The specific form and parameters of the preset compensation model are as follows:

[0099] 1. Open-circuit voltage compensation: Voc_STC=Voc_meas×[1-α×(T_meas-25)], where Voc_STC is the open-circuit voltage under the standard test conditions after calibration, Voc_meas is the actual tested open-circuit voltage, α is the temperature coefficient of the BC component (optimized by experiments, with a value of 0.0035 / ℃-0.004 / ℃), and T_meas is the actual ambient temperature collected;

[0100] 2. Short-circuit current compensation: Isc_STC = Isc_meas × (1000 / G_meas), where Isc_STC is the short-circuit current under the calibrated standard test conditions, Isc_meas is the actual short-circuit current tested, and G_meas is the actual ambient irradiance collected.

[0101] 3. Conversion efficiency compensation: η_STC=η_meas×(1000 / G_meas)×[1-β×(T_meas-25)], where η_STC is the conversion efficiency under the standard test conditions after calibration, η_meas is the actual calculated conversion efficiency, β is the temperature coefficient of conversion efficiency (after experimental optimization, the value is taken as 0.0015 / ℃-0.002 / ℃), and T_meas and G_meas are the actual collected temperature and irradiance parameters, respectively.

[0102] This compensation step effectively eliminates interference from environmental factors, making the calibrated parameters closer to the true values ​​under standard test conditions. This ensures the accuracy and repeatability of the test results. Through a dedicated compensation model and precise environmental parameter acquisition, it effectively reduces test deviations caused by fluctuations in ambient temperature and irradiance. This allows for direct comparison of component performance parameters tested in different environments and at different times, meeting the quality control requirements of large-scale production. Furthermore, this compensation model is specifically designed for the structural characteristics and performance patterns of BC modules. Compared to general compensation models, its compensation accuracy is improved, accurately reflecting the true performance level of BC modules.

[0103] In some embodiments, the method further includes: combining the electroluminescence detection results, infrared thermal imaging detection results, IV characteristic analysis results, and resistance parameter extraction results of the BC component to perform a performance rating of the BC component and automatically generate a test report.

[0104] Performance rating based on comprehensive testing results involves summarizing and analyzing all outputs. For example, a comprehensive performance rating of A, B, C, and D levels is applied to BC components. The comprehensive analysis includes electroluminescence detection results, infrared thermal imaging results, IV characteristic analysis results, and resistance parameter extraction results. These results cover multiple dimensions of the BC component, such as defect types, core performance parameters, and internal structural health status, ensuring the comprehensiveness and accuracy of the performance rating. This application's embodiment integrates all testing data, defect information, and performance rating results into a standardized testing report, supporting PDF export and printing, facilitating production quality traceability and management. Simultaneously, it reduces reliance on operator experience, automates and standardizes the testing process, and provides a complete solution for quality control, factory inspection, and reliability assessment during the BC component production process.

[0105] The embodiments of this application will now be explained in full.

[0106] Please see Figure 5 , Figure 5 This is a block diagram illustrating the performance testing principle of the BC component provided in this application embodiment, such as... Figure 5 As shown, starting with preprocessing and initial IV testing, the BC module under test is first placed under standard test conditions, and the current-voltage characteristic scan is completed through an AAA-level solar simulator to record core basic parameters such as maximum power, open-circuit voltage, short-circuit current and fill factor. At the same time, preparatory work such as module fixing and cleaning, equipment preheating and calibration, and adaptive adaptation of the test probe is completed.

[0107] The process then proceeds to the multi-mode electroluminescence (EL) detection stage. Three differentiated electrical excitation modes—forward bias, reverse bias, and low-frequency AC modulation—are used to acquire three types of images: EL_Forward, EL_Reverse, and EL_AC_Amplitude / Phase. This excites the electrical response of the BC component from different dimensions, overcoming the limitation of conventional single-forward bias EL testing, which is insensitive to defects such as microcracks and broken gates. In both reverse bias and AC modulation modes, lock-in thermal imaging (LIT) detection is initiated simultaneously, acquiring static thermal images and thermal wave amplitude and phase images. This achieves dual-dimensional collaborative acquisition of "electrical signals + thermal signals," and cross-verification of temperature and electrical anomalies avoids misjudgments caused by a single signal.

[0108] Subsequently, the process enters the multimodal image fusion and defect identification stage. First, spatial registration is performed on the six types of images acquired in the early stage. Then, based on a preset rule base, problems such as hidden cracks, broken gates, junction defects, and abnormal parallel resistance are automatically diagnosed. Through multi-information fusion, the defect detection rate and accuracy are significantly improved. Next, by establishing a distributed circuit model of the BC component, the measured IV curve is fitted and microscopic parameters such as parallel resistance and electrode line resistance are extracted in reverse. This accurately correlates macroscopic performance anomalies with microscopic structural defects, achieving a leap from "appearance detection" to "mechanism diagnosis". Finally, by integrating all detection and analysis results, the BC component is rated into four levels: A, B, C, and D. A standardized report containing defect distribution maps, parameter lists, and other information is automatically generated, forming a complete detection solution that adapts to the needs of large-scale production and balances accuracy and efficiency.

[0109] In summary, the embodiments of this application have the following beneficial effects:

[0110] By innovatively integrating multi-mode electrical excitation and multi-modal image fusion technology, distributed circuit model fitting, and intelligent calibration algorithms, this method not only effectively solves the pain points of existing conventional testing methods, such as poor adaptability of BC module electrode contacts, low detection rate of defects like microcracks and broken grids, parameter interpretation bias, and lack of targeted testing conditions, but also achieves comprehensive coverage and accurate detection of core and specific parameters such as open-circuit voltage, short-circuit current, and contact resistance, significantly improving testing efficiency. At the same time, through automated defect identification, quantitative parameter extraction, and standardized rating reports, it reduces the dependence on operator experience, adapting to the quality control and factory inspection needs in large-scale production, and providing accurate data support for BC module process improvement, comprehensively ensuring the quality reliability and long-term stability of BC modules.

[0111] Based on the same inventive concept, this application also provides a BC component performance testing device corresponding to the BC component performance testing method in the first embodiment. Since the principle of the device in this application is similar to the above-mentioned BC component performance testing method, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0112] like Figure 6 As shown, Figure 6 This is a schematic diagram of the structure of the BC component performance testing device 600 provided in this application embodiment. The BC component performance testing device 600 includes:

[0113] The excitation module 601 is used to perform electroluminescence imaging on the BC component using an electrical excitation mode, and to acquire the electroluminescence signal of the BC component corresponding to the electrical excitation mode; wherein, the electrical excitation mode includes a forward bias excitation mode, a reverse bias excitation mode, and an AC modulation excitation mode.

[0114] The detection module 602 is used to perform performance testing on the BC component based on the electroluminescent signal and to identify defects in the BC component.

[0115] Those skilled in the art should understand that Figure 6 The functions of each unit in the BC component performance testing device 600 shown can be understood by referring to the relevant description of the aforementioned BC component performance testing method. Figure 6 The functions of each unit in the BC component performance testing device 600 shown can be implemented by a program running on a processor or by specific logic circuits.

[0116] In one possible implementation, the AC modulation excitation mode is a low-frequency sinusoidal AC excitation, and when performing electroluminescence imaging using the AC modulation excitation mode, lock-in amplification technology is used to extract the amplitude and phase information of the electroluminescence signal.

[0117] In one possible implementation, while performing electroluminescence imaging on the BC component using the reverse bias excitation mode and the AC modulation excitation mode, infrared thermal imaging detection is simultaneously performed on the BC component to acquire the thermal imaging signal of the BC component.

[0118] In one possible implementation, the infrared thermal imaging detection is phase-locked thermal imaging detection, used to extract the amplitude and phase information of the thermal wave of the BC component.

[0119] In one possible implementation, the excitation module 601 is further configured to:

[0120] Spatial registration and fusion processing are performed on the images corresponding to electroluminescence signals acquired under different electrical excitation modes and the images corresponding to thermal imaging signals acquired simultaneously.

[0121] Based on preset defect identification rules, the fused image is analyzed to achieve automatic identification and classification of hidden cracks, broken grids, poor contact and junction defects in the BC component.

[0122] In one possible implementation, the detection module 602 is further configured to:

[0123] The BC component is subjected to current-voltage characteristic testing to obtain the IV characteristic curve of the BC component;

[0124] A distributed circuit model of the BC component is established, and the internal resistance parameters of the BC component are extracted by fitting the IV characteristic curve.

[0125] In one possible implementation, the resistance parameters include at least one of the parallel resistance of a single battery cell, the line resistance of the back finger electrode, and the bulk resistance and contact resistance of the interconnecting solder strip.

[0126] In one possible implementation, the current-voltage characteristic test is performed under standard test conditions, and the test parameters include at least one of open-circuit voltage, short-circuit current, maximum power, maximum power point voltage, maximum power point current, and fill factor; based on the current-voltage characteristic test parameters, the conversion efficiency of the BC component is calculated.

[0127] In one possible implementation, the detection module 602 is further configured to:

[0128] Real-time acquisition of temperature and irradiance parameters in the detection environment;

[0129] Based on a preset compensation model, environmental compensation calibration is performed on the conversion efficiency, open-circuit voltage, and short-circuit current.

[0130] In one possible implementation, the detection module 602 is further configured to: perform a performance rating on the BC component by integrating the electroluminescence detection results, infrared thermal imaging detection results, IV characteristic analysis results, and resistance parameter extraction results of the BC component, and automatically generate a detection report.

[0131] The aforementioned BC module performance testing device, through the innovative integration of multi-mode electrical excitation and multi-modal image fusion technology, distributed circuit model fitting, and intelligent calibration algorithms, not only effectively solves the pain points of existing conventional testing methods, such as poor adaptability of BC module electrode contacts, low detection rate of defects like microcracks and broken grids, parameter interpretation bias, and lack of targeted testing conditions, but also achieves comprehensive coverage and accurate detection of core and specific parameters such as open-circuit voltage, short-circuit current, and contact resistance, significantly improving testing efficiency. At the same time, through automated defect identification, quantitative parameter extraction, and standardized rating reports, it reduces the dependence on operator experience, adapting to the quality control and factory inspection needs in large-scale production, and providing accurate data support for BC module process improvement, comprehensively ensuring the quality reliability and long-term stability of BC modules.

[0132] like Figure 7 As shown, Figure 7 This is a schematic diagram of the composition structure of the electronic device 700 provided in the embodiments of this application. The electronic device 700 includes:

[0133] The device 700 includes a processor 701, a storage medium 702, and a bus 703. The storage medium 702 stores machine-readable instructions that can be executed by the processor 701. When the electronic device 700 is running, the processor 701 communicates with the storage medium 702 via the bus 703. The processor 701 executes the machine-readable instructions to perform the steps of the BC component performance testing method described in the embodiments of this application.

[0134] In practical applications, the various components in the electronic device 700 are coupled together via a bus 703. It is understood that the bus 703 is used to achieve communication between these components. In addition to a data bus, the bus 703 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 7 The general designated all buses as Bus 703.

[0135] The aforementioned electronic equipment, through the innovative integration of multi-mode electrical excitation and multi-modal image fusion technology, distributed circuit model fitting, and intelligent calibration algorithms, not only effectively solves the pain points of existing conventional testing methods, such as poor adaptability of BC component electrode contacts, low detection rate of defects like microcracks and broken grids, parameter interpretation bias, and lack of targeted testing conditions, but also achieves comprehensive coverage and accurate detection of core and specific parameters such as open-circuit voltage, short-circuit current, and contact resistance, significantly improving testing efficiency. At the same time, through automated defect identification, quantitative parameter extraction, and standardized rating reports, it reduces the dependence on operator experience, adapting to the quality control and factory inspection needs in large-scale production, and providing accurate data support for BC component process improvement, comprehensively ensuring the quality reliability and long-term stability of BC components.

[0136] This application also provides a computer-readable storage medium storing executable instructions. When the executable instructions are executed by at least one processor 701, the BC component performance detection method described in this application is implemented.

[0137] In some embodiments, the storage medium may be a magnetic random access memory (FRAM), a read-only memory (ROM), or a programmable read-only memory (PROM). Erasable Programmable Read-Only Memory (EPROM) Electrically Erasable Programmable Read-Only Memory (EEPROM) Read-only memory, flash memory, magnetic surface storage, optical disc, or CD-ROM ROM, Compact Disc Read It can be a memory such as a memory only; or it can be a device that includes one or any combination of the above-mentioned memories.

[0138] In some embodiments, executable instructions may take the form of a program, software, software module, script, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a standalone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0139] As an example, executable instructions may, but do not necessarily, correspond to files in the file system. They may be stored as part of a file that holds other programs or data, for example, in one or more scripts in a HyperText Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple collaborating files (e.g., a file that stores one or more modules, subroutines, or code sections).

[0140] As an example, executable instructions can be deployed to execute on a single computing device, or on multiple computing devices located in one location, or on multiple computing devices distributed across multiple locations and interconnected via a communication network.

[0141] The aforementioned computer-readable storage medium, through the innovative integration of multi-mode electrical excitation and multi-modal image fusion technology, distributed circuit model fitting, and intelligent calibration algorithms, not only effectively solves the pain points of existing conventional testing methods, such as poor adaptability of BC module electrode contacts, low detection rate of defects like microcracks and broken grids, parameter interpretation bias, and lack of targeted testing conditions, but also achieves comprehensive coverage and accurate detection of core and specific parameters such as open-circuit voltage, short-circuit current, and contact resistance, significantly improving testing efficiency. At the same time, through automated defect identification, quantitative parameter extraction, and standardized rating reports, it reduces the dependence on operator experience, adapting to the quality control and factory inspection needs in large-scale production, and providing accurate data support for BC module process improvement, comprehensively ensuring the quality reliability and long-term stability of BC modules.

[0142] In the several embodiments provided in this application, it should be understood that the disclosed methods and electronic devices can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components may be combined, or integrated into another system, or some features may be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0143] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0144] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0145] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a platform server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0146] The above are merely specific embodiments 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.

Claims

1. A method for testing the performance of a BC component, characterized in that, Includes the following steps: Electroluminescence imaging of the BC component is performed using an electrical excitation mode to obtain the electroluminescence signal of the BC component corresponding to the electrical excitation mode; wherein, the electrical excitation mode includes a forward bias excitation mode, a reverse bias excitation mode, and an AC modulation excitation mode; The performance of the BC component is tested based on the electroluminescent signal, and defects in the BC component are identified. While performing electroluminescence imaging on the BC component using the reverse bias excitation mode and the AC modulation excitation mode, infrared thermal imaging detection is simultaneously performed on the BC component to obtain the thermal imaging signal of the BC component. The infrared thermal imaging detection is phase-locked thermal imaging detection, used to extract the amplitude and phase information of the thermal wave of the BC component; The method further includes: Spatial registration and fusion processing are performed on the images corresponding to electroluminescence signals acquired under different electrical excitation modes and the images corresponding to thermal imaging signals acquired simultaneously. Based on preset defect identification rules, the fused image is analyzed to achieve automatic identification and classification of hidden cracks, broken grids, poor contact and junction defects in the BC component.

2. The method according to claim 1, characterized in that, The AC modulation excitation mode is a low-frequency sinusoidal AC excitation, and when electroluminescence imaging is performed using the AC modulation excitation mode, lock-in amplification technology is used to extract the amplitude and phase information of the electroluminescence signal.

3. The method according to claim 1, characterized in that, The method further includes: The BC component is subjected to current-voltage characteristic testing to obtain the IV characteristic curve of the BC component; A distributed circuit model of the BC component is established, and the internal resistance parameters of the BC component are extracted by fitting the IV characteristic curve.

4. The method according to claim 3, characterized in that, The resistance parameters include at least one of the following: the parallel resistance of a single battery cell, the line resistance of the back finger electrode, and the bulk resistance and contact resistance of the interconnecting solder strip.

5. The method according to claim 3, characterized in that, The current-voltage characteristic test is performed under standard test conditions, and the test parameters include at least one of open-circuit voltage, short-circuit current, maximum power, maximum power point voltage, maximum power point current, and fill factor. The conversion efficiency of the BC component is calculated based on the current-voltage characteristic test parameters.

6. The method according to claim 5, characterized in that, The method further includes: Real-time acquisition of temperature and irradiance parameters in the detection environment; Based on a preset compensation model, environmental compensation calibration is performed on the conversion efficiency, open-circuit voltage, and short-circuit current.

7. The method according to any one of claims 1-6, characterized in that, The method further includes: comprehensively analyzing the electroluminescence detection results, infrared thermal imaging detection results, IV characteristic analysis results, and resistance parameter extraction results of the BC component to perform performance rating of the BC component and automatically generate a test report.

8. A BC component performance testing device, characterized in that, The device includes: The excitation module is used to perform electroluminescence imaging on the BC component using an electrical excitation mode to acquire the electroluminescence signal corresponding to the BC component under the electrical excitation mode. The electrical excitation modes include a forward bias excitation mode, a reverse bias excitation mode, and an AC modulation excitation mode. While performing electroluminescence imaging on the BC component using the reverse bias excitation mode and the AC modulation excitation mode, the module simultaneously performs infrared thermal imaging detection on the BC component to acquire the thermal imaging signal. The infrared thermal imaging detection is phase-locked loop thermal imaging detection, used to extract the amplitude and phase information of the thermal wave of the BC component. The module is also used to perform spatial registration and fusion processing on the images corresponding to the electroluminescence signals acquired under different electrical excitation modes and the images corresponding to the simultaneously acquired thermal imaging signals. Based on preset defect identification rules, the fused image is analyzed to achieve automatic identification and classification of microcracks, broken grids, poor contact, and junction defects in the BC component. The detection module is used to perform performance testing on the BC component based on the electroluminescent signal and to identify defects in the BC component.

9. An electronic device, characterized in that, include: The device includes a processor, a storage medium, and a bus, wherein the storage medium stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the storage medium via the bus, and the processor executes the machine-readable instructions to perform the BC component performance testing method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, performs the BC component performance testing method as described in any one of claims 1 to 7.

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