Stress test method, device and equipment of solar cell and storage medium

Abstract

This application proposes a method, apparatus, device, and storage medium for stress testing of solar cells. The method obtains the target characteristic peak shift of the solar cell through spectrometer scanning. The target stress of the solar cell is determined based on the target characteristic peak shift and its corresponding relationship. The corresponding relationship characterizes the relationship between the stress and the characteristic peak shift of the solar cell, and is derived from multiple characteristic peak shifts and multiple maximum stresses. The maximum stress characterizes the maximum stress that the surface of the solar cell can withstand under bending deformation. This technical solution, by obtaining the target characteristic peak shift of the solar cell through spectrometer scanning and combining it with a pre-calibrated correspondence between the characteristic peak shift and stress, yields the target stress, realizing a non-destructive and rapid stress testing scheme.

Description

Technical Field

[0001] This application relates to the field of stress testing technology, and in particular to a stress testing method, apparatus, device, and storage medium for solar cells. Background Technology

[0002] The reliability of cells and modules has always significantly impacted module lifespan and efficiency. After soldering and lamination, different parts of the cells experience strain and stress. Quantifying these influencing factors provides a solid and reliable basis for subsequent process improvements and material replacements. Currently, effective methods for measuring stress distribution are lacking in battery laboratories. However, to optimize the soldering process, it is urgent to characterize the stress effects of different soldering temperatures and solder strips on the cells after stringing. This is because accumulated stress is released during subsequent lamination, leading to microcracks in the silicon wafer and delamination of the grid lines. Theoretically, X-ray diffraction (XRD) is a commonly used method for measuring residual stress, but its application to solar cells faces two key obstacles: First, XRD requires the test surface to be as smooth as possible, while the surface of solar cells is fabricated with a pyramidal textured structure to enhance light trapping, and the rough surface does not meet the testing requirements; second, X-rays have a shallow penetration depth into silicon, only able to measure the stress on the outermost layer, and cannot reflect the overall or critical interface stress distribution. Therefore, how to effectively test the stress of solar cells has become an urgent problem to be solved. Summary of the Invention

[0003] This application provides a method, apparatus, electronic device, and storage medium for stress testing of solar cells, which can effectively test the stress of solar cells.

[0004] The first aspect of this application provides a method for stress testing of solar cells, the method comprising: Obtain the target characteristic peak shift of the solar cell obtained by scanning with a spectrometer; The target stress of the solar cell is determined based on the target characteristic peak offset and the corresponding relationship. The corresponding relationship is used to characterize the relationship between the stress of the solar cell and the characteristic peak offset. The corresponding relationship is obtained based on multiple characteristic peak offsets and multiple maximum stresses. The maximum stress is used to characterize the maximum stress that the surface of the solar cell bears under bending deformation.

[0005] In some embodiments, the correspondence is represented by a fitting algorithm, the coefficients of which are obtained by linear fitting based on the multiple characteristic peak offsets and the multiple maximum stresses.

[0006] In some embodiments, the method further includes: Multiple sets of data are obtained, each set of data including a maximum stress of the solar cell and the characteristic peak offset corresponding to the maximum stress; Based on the multiple sets of data, a linear fit is performed to determine the coefficients of the fitting algorithm.

[0007] In some embodiments, obtaining multiple sets of data includes: For any set of data, determine the Young's modulus of the solar cell and the bending radius of the solar cell, the bending radius being generated when an external force is applied to the target area of ​​the solar cell; The maximum stress of the solar cell is determined based on the Young's modulus, the bending radius, and the thickness of the solar cell. The target region is scanned by the spectrometer to obtain the characteristic peak shift corresponding to the maximum stress; wherein... Different sets of data correspond to different external forces.

[0008] In some embodiments, determining the Young's modulus of the solar cell includes: The Young's modulus of the solar cell is determined based on the external force, the physical dimensions of the solar cell, and the deflection of the solar cell. The physical dimensions include the width, thickness, and span of the solar cell.

[0009] In some embodiments, determining the bending radius of the solar cell includes: Obtain a bending cross-sectional image of the solar cell under the action of the external force; Identify the curved contour lines of the curved cross-section image; Based on the curved contour line, fit the arc parameters corresponding to the solar cell; The bending radius of the solar cell is determined based on the arc parameters.

[0010] In some embodiments, the correspondence is represented by a correspondence table, which includes the relationship between the plurality of characteristic peak offsets and the plurality of maximum stresses; Determining the target stress of the solar cell based on the target characteristic peak offset and its correspondence includes: Find the target stress corresponding to the target characteristic peak offset from the correspondence table.

[0011] A second aspect of this application provides a stress testing device for solar cells, the device comprising: The acquisition module is used to acquire the target characteristic peak shift of the solar cell obtained by scanning with a spectrometer; The determination module is used to determine the target stress of the solar cell based on the target characteristic peak offset and the corresponding relationship. The corresponding relationship is used to characterize the relationship between the stress of the solar cell and the characteristic peak offset. The corresponding relationship is obtained based on multiple characteristic peak offsets and multiple maximum stresses. The maximum stress is used to characterize the maximum stress that the surface of the solar cell bears under bending deformation.

[0012] A third aspect of this application provides an electronic device including a processor and a memory, the memory storing a computer program, wherein the processor executes the computer program to implement the steps of any of the methods described in the first aspect of this application.

[0013] A fourth aspect of this application provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the steps of any of the methods described in the first aspect of this application.

[0014] The technical solutions provided in this application have at least the following beneficial effects: This application proposes a method, apparatus, device, and storage medium for stress testing of solar cells. The method obtains the target characteristic peak offset of the solar cell through spectrometer scanning and combines it with a pre-calibrated correspondence between the characteristic peak offset and stress to obtain the target stress. This provides a non-destructive and rapid stress testing scheme, effectively solving the technical problem in existing technologies where accurate stress testing is difficult due to the rough surface of the solar cell and the limited penetration depth of X-rays. Specifically, this scheme first obtains the target characteristic peak offset of the solar cell through spectrometer scanning, and then determines the target stress based on the offset and the correspondence. Since the spectrometer scanning process does not change the physical morphology and electrical properties of the solar cell, the tested solar cell can still be used for subsequent processes or reliability verification, thus achieving true non-destructive testing. Furthermore, after obtaining the pre-calibrated correspondence between the characteristic peak offset and stress, in actual testing, only the measured target characteristic peak offset needs to be substituted into this correspondence to directly obtain the stress value, eliminating the need for repeated complex mechanical modeling or finite element analysis for each test. By establishing a pre-established correspondence and using the target feature peak offset obtained from scanning, the accuracy of the test results is ensured, and the computational burden in the testing phase is significantly reduced, making the entire stress testing process more efficient and convenient. Attached Figure Description

[0015] Figure 1 This is a schematic flowchart of a stress testing method for a solar cell according to an embodiment of this application; Figure 2This is a schematic diagram of the process for determining the fitting algorithm coefficients in a stress testing method for a solar cell proposed in an embodiment of this application; Figure 3 This is a schematic diagram of the fitting algorithm proposed in the embodiments of this application after fitting; Figure 4 A schematic diagram of the stress testing platform for the solar cell proposed in this application embodiment; Figure 5 This is a schematic diagram of the forces acting on the solar cell according to an embodiment of this application; Figure 6 This is a flowchart illustrating the process of determining multiple data points in a stress testing method for a solar cell according to an embodiment of this application. Figure 7 This is a schematic flowchart illustrating the process of determining the bending radius in a stress testing method for a solar cell according to an embodiment of this application. Figure 8 This is a schematic diagram illustrating the determination of the bending radius in a stress testing method for a solar cell according to an embodiment of this application. Figure 9 This is a schematic diagram of the structure of a stress testing device for a solar cell according to an embodiment of this application; Figure 10 This is a schematic diagram of the structure of the electronic device proposed in the embodiments of this application. Detailed Implementation

[0016] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0017] To facilitate a clear description of the technical solutions in the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with essentially the same function and effect. For example, "first instruction" and "second instruction" are used to distinguish different user instructions and do not limit their order. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and the terms "first" and "second" are not necessarily different.

[0018] It should be noted that in the embodiments of this application, the words "exemplarily" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplarily" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplarily" or "for example" is intended to present the relevant concepts in a specific manner.

[0019] Furthermore, "at least one" refers to one or more, while "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, and c can mean: a, or b, or c, or a and b, or a and c, or b and c, or a, b, and c, where a, b, and c can be single or multiple.

[0020] It should be noted that, in the embodiments of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0021] The reliability of cells and modules has always significantly impacted module lifespan and efficiency. After soldering and lamination, different parts of the cells experience strain and stress. Quantifying these influencing factors provides a solid and reliable basis for subsequent process improvements and material replacements. Currently, effective methods for measuring stress distribution are lacking in battery laboratories. However, to optimize the soldering process, it is urgent to characterize the stress effects of different soldering temperatures and solder strips on the cells after stringing. This is because accumulated stress is released during subsequent lamination, leading to microcracks in the silicon wafer and delamination of the grid lines. Theoretically, X-ray diffraction (XRD) is a commonly used method for measuring residual stress, but its application to solar cells faces two key obstacles: First, XRD requires the test surface to be as smooth as possible, while the surface of solar cells is fabricated with a pyramidal textured structure to enhance light trapping, and the rough surface does not meet the testing requirements; second, X-rays have a shallow penetration depth into silicon materials, only able to measure the stress on the outermost layer, and cannot reflect the overall or critical interface stress distribution.

[0022] In addition, existing methods for testing stress include software simulation, such as finite element method (FEM), which uses computer software to numerically simulate the geometric model and stress conditions of an object. However, this method is a mathematical approximation rather than a result of actual measurements, heavily relies on accurate material parameters and boundary conditions, and involves huge and complex mesh generation and computation.

[0023] Therefore, how to effectively test the stress of solar cells has become an urgent problem to be solved.

[0024] In view of this, this application proposes a stress testing method, apparatus, device, and storage medium for solar cells. The method obtains the target characteristic peak offset of the solar cell through spectrometer scanning; the target stress of the solar cell is determined based on the target characteristic peak offset and its corresponding relationship. The corresponding relationship characterizes the relationship between the stress and the characteristic peak offset of the solar cell, and is obtained based on multiple characteristic peak offsets and multiple maximum stresses. The maximum stress characterizes the maximum stress that the surface of the solar cell can withstand under bending deformation. This technical solution, by obtaining the target characteristic peak offset of the solar cell through spectrometer scanning and combining it with a pre-calibrated correspondence between the characteristic peak offset and stress, provides a non-destructive and rapid stress testing scheme, effectively solving the technical problem in the prior art where accurate stress testing is difficult due to the rough surface of the solar cell and the limited penetration depth of X-rays. Specifically, this scheme first obtains the target characteristic peak offset of the solar cell through spectrometer scanning, and then determines the target stress based on the offset and its corresponding relationship. Since the spectrometer scanning process does not change the physical morphology and electrical properties of the solar cell, the tested solar cell can still be used for subsequent processes or reliability verification, thus achieving true non-destructive testing. Furthermore, after establishing a pre-calibrated correspondence between characteristic peak offset and stress, the stress value can be directly obtained by substituting the measured target characteristic peak offset into this correspondence during actual testing, eliminating the need for repeated complex mechanical modeling or finite element analysis for each test. The pre-established correspondence and the target characteristic peak offset obtained through scanning ensure the accuracy of the test results while significantly reducing the computational burden during the stress testing phase, making the entire stress testing process more efficient and convenient.

[0025] Raman spectroscopy has long been an effective and non-destructive method for stress analysis, but establishing the relationship between Raman frequency shift wavenumber and stress has remained a challenge. Raman spectroscopy uses phonons to study and analyze the molecular properties of materials. Phonons, as quanta quantizing lattice vibration energy, cause changes in the lattice constant and thus the lattice vibration frequency when a material is subjected to stress. This change can be used to analyze and quantify the stress on the material. The characteristic peak of single-crystal silicon is located at 520 cm⁻¹ in the Raman spectrum. -1When single-crystal silicon is subjected to compressive stress, its lattice constant decreases, causing the characteristic peaks of silicon to shift towards higher wavenumbers. Conversely, when the material is subjected to tensile stress, its lattice constant increases, causing the characteristic peaks of silicon to shift towards lower wavenumbers. This wavenumber variation is used to characterize stress changes in specific regions of a sample. Calculating the stress of a three-dimensional object requires complex and extensive computation because, unlike two-dimensional graphics which only involve stress along the x and y axes, calculating the stress of a three-dimensional object involves the x, y, and z axes, as well as xy-axis, xz-axis, and yz-axis, etc. This exponentially increases the computational load and makes the process time-consuming and laborious.

[0026] Combining the advantages of Raman spectroscopy, such as fast result output, non-destructive testing, and high tolerance to sample preparation conditions, Raman spectroscopy can be used to rapidly test stress and stress distribution.

[0027] Formulas in published literature suggest that, under certain circumstances, even in three-dimensional situations, stress can sometimes be represented in two dimensions, namely the xx-axis, yy-axis, and xy-axis. This is because, in reality, there are currently no effective means to measure stress distribution in battery laboratories. However, characterization is urgently needed to test the stress effects of different welding temperatures and the solder strips after stringing on the cell. The stress accumulated after lamination will be released, causing microcracks in the silicon wafer and delamination of the grid lines. Online research has revealed that when a sample is subjected to tensile or compressive stress, it will be reflected in the Raman spectrum shift. This shift can quantify the stress experienced by the object.

[0028] The following examples detail how the mechanical properties from the microscopic to the macroscopic levels were used to establish the relationships between phonon energy and strain, Raman frequency shift and eigenvalues, Raman frequency shift and strain, strain and stress, and finally, the relationship between Raman frequency shift and stress.

[0029] 1. Physical Principle (Eigenvalue equations describing how optical phonon energy in silicon crystals is affected by strain): Phonon Energy and Strain The phonon eigenvalue equation for Raman shift (primarily describing the phonon frequency change in a silicon lattice under stress): (1) (2) in where is the strain tensor component; p, q, r are the phonon deformation potentials, which are material constants of silicon; The eigenvalues ​​are directly related to the Raman frequency shift. Equation (1) is used to solve for the change in the frequency of Raman-active phonons in silicon crystal under stress (i.e., the Raman frequency shift), which includes all possible strain stresses and components. Its physical significance lies in its description of how lattice vibrations respond under the most general stress state. To solve it accurately, all six independent strain components need to be known, which is very difficult experimentally. Equation (1) is simplified to equation (2) based on the analysis of the research object and process; solar cells are very thin (typically ~135μm), while their dimensions in the planar direction are large. Under in-plane thermal stress, it is difficult for thin sheet structures to accumulate significant stress in the thickness direction. The cells are wrapped in soft EVA encapsulant rather than rigidly clamped, so they can deform slightly and freely in the thickness direction, thereby releasing the stress. Equal stress.

[0030] 2. Expression for eigenvalues: It is known that the front side of a solar cell has a pyramid structure, which includes (111) and (100) crystal planes. Existing literature derives formulas for an ideal (100) crystal plane. Furthermore, when performing backscattered Raman measurements on a (100) silicon surface, only one Raman mode (the third mode) is active. Therefore, when observing the front side of a cell dominated by the (100) crystal plane, it is unnecessary to... and And only need to obtain eigenvalues, therefore The eigenvalues ​​are: (3) 3. Relationship between frequency shift and eigenvalues: After obtaining the eigenvalues, a relationship can be established with the translation of the Raman spectrum to obtain: (4) The above formula can prove the Raman frequency shift. With eigenvalues They are directly proportional.

[0031] 4. Substituting formula (3) into formula (4) yields formula (5): (5) in For the Raman frequency shift that occurs after stress is applied This represents the Raman frequency shift exhibited without applied stress. It is a Raman shift. These are the three normal strain components of the strain tensor. For phonon shape transformation potential (material constant) This is the reference frequency under stress-free conditions.

[0032] Formula (5) is the relationship between stress and Raman frequency shift. Now we need to use Hooke's law to confirm the relationship between stress and strain.

[0033] 5. Conversion between strain and stress: Hooke's generalized law:

[0034] , , The strain forces representing the x, y, and z directions can be either contraction or tension. This represents the angular change, or shear strain, in the xy plane. The 6x6 matrix in the formula is the structural matrix of silicon or diamond materials. , , The compliance constant of silicon can be obtained experimentally. This relates to the effect of stress in the x-direction on strain in the x-direction; This relates to the effect of stress in the y or z direction on strain in the x direction; It is related to shear strain and shear stress. and These represent the stresses in the x and y directions, respectively. This represents the in-plane shear stress. Wherein , , All are 0. Among them The value of 0 is based on the assumption that the battery is very thin, about 130 micrometers, so the stress on the Z-axis is negligible; , The value of 0 also represents the neglect of shear stress on the thickness because the battery thickness is too thin.

[0035] 6. Relationship between frequency shift and stress: Therefore, formula (5) can be written as: It can also be simplified to a formula: (6) in .

[0036] Where p and q are the phonon deformation potentials of silicon, and are material constants. These are the components of the elastic compliance matrix of silicon. It is the in-plane stress component.

[0037] So far, the relationship between Raman frequency shift, stress, and strain has been successfully established. Through this relationship, we can successfully set up experiments to calculate and characterize stress distribution.

[0038] Having successfully established the relationship between stress, strain, and Raman shift, the following details a stress testing method for solar cells proposed in this application based on this theory.

[0039] In some embodiments, such as Figure 1 As shown, it includes: Step 101: Obtain the target characteristic peak offset of the solar cell obtained by scanning with a spectrometer.

[0040] The shift of characteristic peaks of a material under stress is obtained using a spectrometer. For example, the shift of a target characteristic peak in a solar cell can be obtained by scanning with a Raman spectrometer. This is because Raman scattering is extremely sensitive to changes in interatomic spacing in crystalline materials and can effectively capture changes in lattice vibration frequencies caused by stress. Specifically, when a laser irradiates the surface of a solar cell, the lattice vibrations of silicon produce specific Raman scattering peaks. Under stress-free conditions, this characteristic peak is located at a known standard wavenumber position; for example, the typical Raman peak for single-crystal silicon is approximately 520 cm⁻¹. -1 However, when the solar cell is subjected to external force and bends or deforms, the lattice is compressed or stretched, causing the Raman peak to shift towards higher or lower wavenumbers. This shift is the target characteristic peak shift.

[0041] For example, to obtain a reliable target characteristic peak shift, the process can be divided into two stages: benchmark calibration and actual measurement. First, a scan is performed on an unstressed area of ​​the solar cell to determine the standard peak position under stress-free conditions. Then, a certain load is applied to the test area of ​​the solar cell, or a region with pre-existing stress from the manufacturing process, such as near the solder ribbon or below the grid lines, is directly measured, and Raman spectra under stress are acquired. By comparing the changes in peak position before and after stress, the target characteristic peak shift can be calculated. This value is typically expressed as a wavenumber difference (cm²). - ¹) indicates that the positive and negative signs correspond to compressive stress and tensile stress, respectively.

[0042] It is important to note that the measurement accuracy of the Raman spectrometer directly affects the reliability of the results; therefore, a high resolution (e.g., better than 1 cm⁻¹) should be selected in practical operation. - ¹) The equipment should be designed to maintain the consistency of laser focusing depth and incident angle as much as possible to reduce system errors.

[0043] Step 102: Determine the target stress of the solar cell based on the target characteristic peak offset and the corresponding relationship. The corresponding relationship is used to characterize the relationship between the stress of the solar cell and the characteristic peak offset. The corresponding relationship is obtained based on multiple characteristic peak offsets and multiple maximum stresses. The maximum stress is used to characterize the maximum stress that the surface of the solar cell bears under bending deformation.

[0044] After obtaining the target characteristic peak shift, it is converted into the actual stress value borne by the solar cell using a pre-established correspondence. This correspondence describes the quantitative relationship between stress and characteristic peak shift, and is usually obtained through a series of calibration experiments.

[0045] For example, since there is an approximately linear relationship between the Raman frequency shift of silicon and stress, the proportionality constant, i.e., the coefficient, can be determined through calibration experiments.

[0046] For example, a direct correspondence between multiple characteristic peak offsets and maximum stress can also be established for solar cells.

[0047] For example, the correspondence is derived based on multiple characteristic peak offsets and multiple maximum stresses. The reason for establishing the correspondence based on the maximum stress is that, in calibration experiments, the maximum stress is the only characteristic stress value that can be directly and accurately calculated using mechanical formulas, and it is also the core indicator that determines whether a solar cell will develop microcracks or delamination. In detail, when a known bending load is applied to a solar cell, the physical dimensions of the material and the applied external force are both known quantities. The theoretical maximum stress on the surface can be accurately calculated using beam bending theory, while the stress distribution at other arbitrary locations cannot be uniquely determined solely by these macroscopic parameters.

[0048] Meanwhile, when measuring the characteristic peak shift, the Raman spectrometer is specifically aligned with the region where the theoretical maximum stress occurs, thus establishing a one-to-one correspondence between the maximum stress and the characteristic peak shift. Therefore, choosing the maximum stress as the core variable for this correspondence ensures both the calculability and repeatability of the calibration process and the effectiveness of assessing the failure risk of solar cells in subsequent tests.

[0049] The above technical solution obtains the target characteristic peak shift of the solar cell by scanning with a spectrometer, and combines this with a pre-calibrated correspondence between the characteristic peak shift and stress to obtain the target stress. This provides a non-destructive and rapid stress testing method, effectively solving the technical problem in existing technologies where accurate stress testing is difficult due to the rough surface of the solar cell and the limited penetration depth of X-rays. Specifically, this solution first obtains the target characteristic peak shift of the solar cell through spectrometer scanning, and then determines the target stress based on this shift and the corresponding relationship. Since the spectrometer scanning process does not change the physical morphology and electrical properties of the solar cell, the tested solar cell can still be used for subsequent processes or reliability verification, thus achieving true non-destructive testing. Furthermore, after obtaining the pre-calibrated correspondence between the characteristic peak shift and stress, in actual testing, only the measured target characteristic peak shift needs to be substituted into this correspondence to directly obtain the stress value, eliminating the need for repeated complex mechanical modeling or finite element analysis for each test. The pre-established correspondence and the target characteristic peak shift obtained through scanning ensure the accuracy of the test results and significantly reduce the computational burden in the stress testing stage, making the entire stress testing process more efficient and convenient.

[0050] In some embodiments, the correspondence is represented by a fitting algorithm, the coefficients of which are obtained by linear fitting based on multiple characteristic peak offsets and multiple maximum stresses.

[0051] For example, the formula for this fitting algorithm can be: (7) in, For the target stress, K represents the target feature peak offset, and K represents the coefficients of the fitting algorithm, which are obtained by linear fitting based on multiple feature peak offsets and multiple maximum stresses.

[0052] The above technical solution uses a fitting algorithm to represent the corresponding relationship. Once the target characteristic peak offset is obtained, the corresponding target stress can be quickly calculated using this fitting algorithm.

[0053] The following examples illustrate the detailed steps for determining the coefficients of the fitting algorithm.

[0054] In some embodiments, such as Figure 2 As shown, the method also includes: Step 201: Obtain multiple sets of data, each set including a maximum stress of the solar cell and the characteristic peak offset corresponding to the maximum stress.

[0055] For example, a progressively increasing force can be applied using a universal testing machine, while simultaneously measuring the peak shift in the central region of the solar cell using a Raman spectrometer. Each force level corresponds to a theoretical maximum stress and a measured shift, forming a set of data.

[0056] For example, one end of the solar cell can be fixed, and an external force can be applied to the other end to generate maximum stress near the fixed end. A Raman beam can then be used to measure this area. By changing the load, multiple sets of data can be obtained.

[0057] For example, a controllable micro-displacement can also be applied to the solar cell using a precision micrometer screw or piezoelectric ceramic, and the displacement can be converted into maximum stress using beam bending theory, while the offset is measured using Raman spectroscopy.

[0058] Step 202: Perform linear fitting based on multiple sets of data to determine the coefficients of the fitting algorithm.

[0059] Given n sets of data points, each containing a characteristic peak offset x_i and a corresponding maximum stress y_i (unit: MPa), i.e. (x1, y1), (x2, y2), ..., (xn, yn), the goal of linear fitting is to find a straight line (e.g., y = k·x+b) that best describes the relationship between x and y, where k is the slope (i.e., coefficient).

[0060] The linear model was chosen because numerous experiments have shown a strong linear relationship between the Raman peak shift and the applied stress within the elastic deformation range of silicon materials. This relationship is determined by the physical mechanism between lattice vibration and strain, and is derived theoretically. (in and (representing stresses in the x and y directions respectively) directly supports the conclusion that σ and Δω have a linear relationship.

[0061] For example, linear fitting can be performed using the least squares method, which is a method for determining the linear relationship between two variables. Its core principle is to find an optimal fitting line through optimization criteria, such that the line can approximate the overall distribution trend of the observed data points to the greatest extent.

[0062] In detail, after obtaining multiple sets of calibration data points containing characteristic peak shifts and corresponding maximum stresses, each data point represents a measured stress value and its corresponding spectral shift. Plotting these data points on a coordinate system with Δω as the abscissa and σ as the ordinate typically shows an approximately linear distribution trend. Therefore, it can be assumed that the two satisfy a linear relationship of σ = k·Δω + b, where k is the proportionality coefficient (i.e., the stress-frequency shift coefficient), and b is the intercept term (theoretically, it should be close to zero under ideal stress-free conditions, but it can be retained in actual fitting to compensate for system bias). The core objective of linear fitting is to find a straight line using the least squares method that minimizes the sum of the squares of the vertical distances from all data points to this line, i.e., solving for the optimal k and b to minimize the error function Σ(σ_i - (k·Δω_i + b))². This optimization problem can be solved by solving the normal equation system or using numerical calculation methods (such as gradient descent or matrix inversion) to obtain uniquely determined coefficients k and b. The resulting fitted straight line constitutes a quantitative mapping relationship from the characteristic peak offset to the maximum stress. In subsequent tests, the actual measured Δω can be substituted into this linear equation to quickly calculate the corresponding target stress value. This linear fitting method not only simplifies the calculation process but also evaluates the linear correlation of the calibration data through the goodness-of-fit (R²), thereby verifying the rationality of the linear assumption between stress and Raman offset.

[0063] For example, the fitted curve is as follows Figure 3 As shown, frequency shift refers to the shift of characteristic peaks, Δω is the horizontal axis, σ is the vertical axis, and σMax is the maximum stress.

[0064] The above technical solution, based on linear fitting of multiple characteristic peak offsets and multiple maximum stresses, can make full use of all calibration data rather than relying on single-point correspondence, thereby effectively offsetting the influence of measurement errors of individual data points on the overall correspondence and improving the robustness and reliability of the stress-characteristic peak offset mapping relationship.

[0065] The following embodiments describe an exemplary method for acquiring multiple sets of data. Before acquiring multiple sets of data, a simple platform can be built to make the solar cell exhibit warping deformation.

[0066] For example, such as Figure 4 As shown and Figure 5 As shown, Figure 4 This is a schematic diagram of a solar cell; the target area is the region scanned by the spectrometer. Figure 5 This is a schematic diagram of the bending deformation of a solar cell when an external force is applied to the target area.

[0067] As shown in the figure, four fixing posts are set up to secure the battery. Another fixing post, 8mm in diameter and longer than the battery width, is attached to both ends with ropes. This fixing post is placed below the battery cell, with ropes attached to both ends, and an electronic scale is connected to the other end. Lifting the electronic scale upwards will move the fixing post below the battery. Because the battery cell is fixed, the upward movement of the fixing post will cause deformation of the solar cell. After lifting, the electronic scale will record the weight of the fixing post and the force required for the battery to return to its initial state after deformation. When an object is subjected to compressive stress, the Raman peak will show a blue shift; conversely, under tensile stress, it will show a red shift. When the electronic scale is lifted, because the two ends of the battery are fixed, the middle bulge deforms, thus exhibiting tensile stress at the highest point of the bulge. When Raman scans this region, the peak position is red-shifted due to tensile stress compared to the unstressed state. Here, S represents the deflection, which is the height difference between the solar cell under stress and the solar cell under tension. l For span, span l It is half of the straight-line distance L between fixed column 1 and fixed column 2.

[0068] Based on this, in some embodiments, multiple sets of data are obtained, such as Figure 6 As shown, it includes: Step 601: For any set of data, determine the Young's modulus of the solar cell and the bending radius of the solar cell, which is generated when an external force is applied to the target area of ​​the solar cell.

[0069] For example, such as Figure 5 As shown, after lifting, the electronic scale will record the weight of the fixed column and the force exerted by the battery as it attempts to return to its initial state after deformation. After subtracting the weight of the fixed column, this external force can be calculated using the formula... get.

[0070] The relationship between stress, strain, and Raman frequency shift was obtained in the previous derivation; now we need to establish the connection between macroscopic mechanical properties and Raman frequency shift.

[0071] When a tensile force is applied, the solar cell will deform. The relationship between deflection and tensile force can be obtained through the bending theory of beams, thereby determining Young's modulus. Young's modulus is a physical quantity used to characterize the ability of a solar cell to resist elastic deformation.

[0072] When a tensile force is applied, the solar cell will deform, and the deformed solar cell will bend, thus obtaining the bending radius.

[0073] For example, the bending radius can be determined by measuring the maximum deflection at the center point of the solar cell (i.e., the vertical displacement of the center point relative to the line connecting the two fixed points) after the solar cell has been bent and deformed, while the span between the two fixed points is also known. Based on this, the bent solar cell is approximated as a circular arc, and the bending radius is calculated using a formula based on the geometric relationship between the chord length and the arch height. Specifically, the bending radius can be approximately determined by dividing the sum of the square of the span and eight times the deflection by twice the deflection.

[0074] For example, the bending radius can also be determined based on the direct measurement method using a curvature sensor. A flexible curvature sensor or strain gauge is tightly attached to the area to be measured along the tangent direction of the curved surface of the solar cell. When the solar cell bends, the sensor deforms along with the surface of the cell, and its internal resistance value or the reflected wavelength of the fiber optic grating undergoes a regular change related to the curvature change. Using a pre-calibrated curve showing the relationship between curvature and electrical signal (or wavelength), the signal output by the sensor is converted into a local curvature value at that measurement point; the reciprocal of the curvature is the bending radius at that point.

[0075] For example, the bending radius can also be determined by taking a picture from the side of the stressed battery cell, uploading the picture to a computer, plotting points to obtain a circle that matches the curve, and using the radius of the circle as the bending radius. The method will be described in detail in the following embodiments.

[0076] Step 602: Determine the maximum stress of the solar cell based on Young's modulus, bending radius, and thickness of the solar cell.

[0077] For example, the maximum stress at the surface of a bent beam can be calculated using a basic formula from beam bending theory: (8) in, The maximum stress experienced by the test point in the target area is E, where E is Young's modulus, d is the thickness of the solar cell, and r is the bending radius.

[0078] Step 603: Scan the target area with a spectrometer to obtain the characteristic peak shift corresponding to the maximum stress; different sets of data correspond to different external forces.

[0079] The target region on the solar cell is scanned using a spectrometer (such as a Raman spectrometer) to obtain the characteristic peak shift corresponding to the maximum stress under the currently applied external force. Different sets of data correspond to different external forces; that is, each set of calibration data is obtained under an external force of a specific magnitude.

[0080] Under different external forces, the Young's modulus and bending radius of the solar cell are also different, and the maximum stress obtained is also different. When the maximum stress is different, the characteristic peak shift obtained by scanning is also different. Therefore, by changing the magnitude of the external force, multiple maximum stresses and multiple characteristic peak shifts can be obtained, that is, multiple sets of data can be obtained.

[0081] For example, in the experiment, a series of known external forces that increase in level can be applied to the solar cell. Under each external force, on the one hand, the theoretical maximum stress σ_max on the surface of the solar cell under that state is calculated using the beam bending theory formula, and on the other hand, the characteristic peak shift Δω is measured by aligning a Raman spectrometer with the position where the maximum stress occurs, thereby forming multiple sets of (Δω, σ) data.

[0082] The above technical solution calculates the maximum stress based on three pre-determined parameters: Young's modulus, bending radius, and thickness. This avoids the error accumulation caused by directly relying on external forces for stress calculation, as external force measurement is greatly affected by factors such as the accuracy of the loading device and friction. Young's modulus and bending radius can be obtained more accurately through independent experiments, thereby improving the calibration accuracy of the maximum stress. The calculated maximum stress is then matched one-to-one with the characteristic peak shift measured by the spectrometer, forming multiple sets of data points. By repeating the above process under different external force levels, calibration data covering multiple stresses within the elastic deformation range is obtained, making the subsequently established correspondence have a wider range of applicability and higher predictive reliability.

[0083] In some embodiments, determining the Young's modulus of a solar cell includes: The Young's modulus of the solar cell is determined based on the external force, the physical dimensions of the solar cell, and the deflection of the solar cell.

[0084] For example, the physical dimensions of the solar cell include the width b, the thickness d, and the span. l .

[0085] Young's modulus is known to be a material's "resistance to deformation," and is an intrinsic property of the material. (9) in Representative stress (force per unit area, measured in Pa or MPa) and The relative deformation of a material, representing strain, is a dimensionless parameter. Because the solar cell is fixed at two points at both ends, a force F is applied to the center point, causing the cell to bend. Therefore, the bending theory of beams can be applied: (10) This formula shows the relationship between deflection S and applied force, where 48 is a constant, E is Young's modulus, and I is the moment of inertia of the cross section. For a rectangular cross section: (11) Substituting formula (10) into formula (9) yields: (12) The Young's modulus of a solar cell is derived as follows: (13) Where E is Young's modulus and F is the upward pulling force. l d is the span, representing half the straight-line distance between the two fixed pillars; b is the sample thickness; and S is the deflection of the center point, which is the distance between the center point of the battery and its original state after an upward force F is applied.

[0086] The aforementioned technical solution calculates Young's modulus by using three directly measurable or known parameters—external force, physical dimensions, and deflection—as input variables. Based on the deflection formula in beam bending theory, a functional relationship is established between Young's modulus and measurable parameters. This eliminates the need for complex and expensive dynamic mechanical analysis equipment; testing can be completed using only conventional mechanical loading devices and displacement measurement tools, significantly reducing testing costs and equipment barriers. The solution employs a static bending loading method, ensuring a stable and controllable testing process and enabling the acquisition of batch-standardized Young's modulus data. Furthermore, this solution is applicable to solar cells of different sizes and thicknesses, requiring no special surface treatment of the cells, maintaining sample integrity and traceability, and possessing good versatility and engineering practical value.

[0087] In some embodiments, such as Figure 7 As shown, determining the bending radius of a solar cell includes: Step 701: Obtain a bending cross-sectional image of the solar cell under external force.

[0088] Applying a predetermined external force to the solar cell causes it to undergo a stable bending deformation. For example, an image acquisition device, such as an industrial camera, microscope, or optical profilometer, can be positioned on the side of the solar cell perpendicular to its length direction to capture a cross-sectional image of the bent side of the cell. This cross-sectional image should clearly show the contour curve of the solar cell along its length, i.e., the continuous arc-shaped edge formed by bending from one fixed point to the other.

[0089] For example, to ensure image quality, backlighting or laser-assisted focusing can be used to enhance contour contrast, while ensuring that the time axis remains perpendicular to the side of the battery cell during shooting to avoid distortion introducing errors into subsequent measurements.

[0090] Step 702: Identify the curved profile of the curved section image.

[0091] After obtaining the bending cross-section image acquired in step 701, it can be input into the image processing module.

[0092] The image processing module preprocesses the curved cross-section image, including grayscale conversion, filtering and noise reduction, and thresholding, to remove background interference and highlight the edge contour of the battery cell.

[0093] For example, edge detection algorithms, such as the Canny operator or the Sobel operator, can be used to extract continuous boundary pixels on the tensile or compressive side of the battery cell in the image. These boundary pixels constitute a discrete set of points reflecting the curved shape of the battery cell, i.e., the desired curved contour line.

[0094] Step 703: Fit the arc parameters corresponding to the solar cell based on the curved profile.

[0095] After obtaining the feature points of the curved profile, assuming the curved shape of the solar cell is approximately an arc, an arc fitting method can be used to determine the arc parameters describing the arc. For example, the arc parameters may include the center and radius.

[0096] For example, a circle matching the contour of the curved surface can be generated based on the plurality of feature points; the radius of the circle is calculated and output as the bending radius. Figure 8 As shown, Figure 8 This is a schematic diagram for obtaining the bending radius. (a) is a cross-sectional image of the bending section, (b) is multiple points on the bending profile, and (c) is the fitted circle with the radius of the bending radius.

[0097] For example, the arc fitting method can be either the least squares arc fitting method or the algebraic distance fitting method. The basic principle of least squares arc fitting is to find a center coordinate and radius that minimizes the sum of the squares of the radial distances from all points on the contour line to the arc. During calculation, the coordinate data of each point on the curved contour line are used as input. By solving a nonlinear optimization problem or using a system of linear equations transformed by geometric algebra, the center position, radius, and starting and ending angles of the fitted arc are obtained. This fitted radius is the bending radius of the solar cell in this curved state.

[0098] Step 704: Determine the bending radius of the solar cell based on the arc parameters.

[0099] The radius value of the arc is directly extracted from the fitting results and used as the bending radius of the solar cell under the current external force.

[0100] The above technical solution achieves non-contact measurement of bending radius based on image acquisition and contour recognition technology, avoiding interference from the original bending state of the battery cell by the traditional mechanical contact method, while eliminating human reading errors and improving the objectivity and repeatability of the measurement. Based on the arc fitting algorithm, discrete contour pixels are transformed into continuous arc parameters, which can effectively suppress the disturbance of local noise and image noise on the measurement results, quickly obtain the bending radius, and improve the robustness and accuracy of the measurement.

[0101] In some embodiments, the correspondence is represented by a correspondence table, which includes the relationship between multiple characteristic peak offsets and multiple maximum stresses.

[0102] The target stress of the solar cell is determined based on the target characteristic peak shift and corresponding relationship, including: Find the target stress corresponding to the target characteristic peak offset from the correspondence table.

[0103] In practice, after scanning the target area of ​​the solar cell under test with a Raman spectrometer and obtaining the target characteristic peak offset, this offset is used as a lookup key in a pre-established correspondence table. If a record exists in the table whose characteristic peak offset is equal to or consistent with the currently measured target characteristic peak offset within the allowable error range, the corresponding maximum stress value in that record is directly read as the target stress at the current test point.

[0104] The aforementioned lookup-based determination method based on a correspondence table offers fast response times and is particularly suitable for scenarios where calibration has been fully completed, data points are dense, and the entire stress range is covered. Furthermore, when there are a sufficient number of calibration data points and sufficiently small offset intervals, the lookup method itself can provide high accuracy, and its hardware implementation cost is low, making it easy to integrate.

[0105] In other embodiments, if no target stress corresponding to the target characteristic peak offset is found from the correspondence, the target stress is considered.

[0106] For example, if no target stress with an exact offset from the target characteristic peak is found in the correspondence table, the target stress value cannot be obtained directly by looking up the table. In this case, interpolation or interval correspondence methods can be used to determine the target stress.

[0107] The correspondence table records a finite set of characteristic peak offsets and corresponding data with maximum stress. In actual testing, the measured target characteristic peak offset is likely to fall between two adjacent recorded points in the table, and will not be exactly equal to any existing offset value in the table.

[0108] At this point, we can find the two offset values ​​adjacent to the target characteristic peak offset in the correspondence table, i.e., one value less than the target characteristic peak offset and the other greater than the target characteristic peak offset, and obtain the stress values ​​corresponding to these two offsets. Then, assuming that the characteristic peak offset and stress have a linear relationship between two adjacent data points, we use linear interpolation to calculate the corresponding target stress value proportionally based on the relative position of the target offset between the two adjacent points.

[0109] For example, if the offset of the target feature peak exceeds the offset range covered by the corresponding relationship table, that is, less than the minimum offset in the table or greater than the maximum offset in the table.

[0110] One exemplary approach is to issue a prompt message informing the user that the current measured offset has exceeded the calibration range and suggesting that the calibration experiment be repeated to expand the coverage of the correspondence table; otherwise, the extrapolated stress value may have a large error.

[0111] Another exemplary method is that if it is known in advance that the stress and the characteristic peak offset still maintain a linear relationship outside the range, the nearest neighbor method can be used, that is, the stress value corresponding to the offset that is closest to the target offset in the corresponding relationship table can be directly used as the estimation result.

[0112] It should be understood that although the steps in the flowchart above are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart above may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0113] In some embodiments, such as Figure 9 As shown, a stress testing device for solar cells is provided, comprising: an acquisition module 901 and a determination module 902, wherein: The acquisition module 901 is used to acquire the target characteristic peak offset of the solar cell obtained by scanning with a spectrometer.

[0114] The determination module 902 is used to determine the target stress of the solar cell based on the target characteristic peak offset and the corresponding relationship. The corresponding relationship is used to characterize the relationship between the stress of the solar cell and the characteristic peak offset. The corresponding relationship is obtained based on multiple characteristic peak offsets and multiple maximum stresses.

[0115] Further limitations on the stress testing device for solar cells can be found in the limitations on the stress testing method for solar cells described above, and will not be repeated here. Each module in the aforementioned stress testing device for solar cells can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of the terminal device in hardware form or independently of it, or stored in the memory of the terminal device in software form, so that the processor can call and execute the corresponding operations of each module.

[0116] Another embodiment provides a computer-readable storage medium for storing a computer program. This computer program contains instructions for implementing the methods described in the embodiments of this application. By installing this computer program on a computer, the computer can execute the corresponding methods.

[0117] Another embodiment proposes a computer program product that includes computer program code. When this computer program code is run on a computer, it causes the computer to implement the methods proposed in the embodiments of this application. Thus, a user can implement these methods by using this computer program product.

[0118] In some embodiments, Figure 10 This is a schematic block diagram of the electronic device provided in the embodiments of this application.

[0119] Electronic device 1000 may include: a memory 1001 storing executable program code and a processor 1002 coupled to the memory 1001.

[0120] In this embodiment, the processor 1002 calls executable program code stored in memory to execute any of the methods disclosed in the embodiments of this application. Those skilled in the art will understand that... Figure 10 The electronic device structure shown does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0121] The processor 1002 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines, and performs various functions and processes data by running or executing software programs and / or modules stored in the memory, and by calling data stored in the memory, thereby providing overall monitoring of the electronic device. Optionally, the processor may include one or more processing units; preferably, the processor may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may also not be integrated into the processor.

[0122] The memory 1001 can be used to store software programs and modules. The processor executes various functional applications and data processing of the electronic device by running the software programs and modules stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function, etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0123] It should be understood that, in the embodiments of this application, the processor may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0124] In implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software. The steps of the method disclosed in the embodiments of this application can be directly manifested as execution by a hardware processor, or as a combination of hardware and software modules within the processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory, and the processor executes the instructions in the memory, combining them with its hardware to complete the steps of the above method. To avoid repetition, detailed descriptions are omitted here.

[0125] Those skilled in the art will recognize that the units 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 design 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 the embodiments of this application.

[0126] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0127] In the embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms.

[0128] The units described as separate components may or may not be physically separate. The components shown as units 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.

[0129] 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.

[0130] If the aforementioned function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application embodiment, essentially, or the part that contributes to the prior art, or a part 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, server, or 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, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0131] The above description is merely a specific implementation of the embodiments of this application, but the protection scope of the embodiments of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the embodiments of this application should be included within the protection scope of the embodiments of this application. Therefore, the protection scope of the embodiments of this application should be determined by the protection scope of the claims.

Claims

1. A method for stress testing of solar cells, characterized in that, The method includes: Obtain the target characteristic peak shift of the solar cell obtained by scanning with a spectrometer; The target stress of the solar cell is determined based on the target characteristic peak offset and the corresponding relationship. The corresponding relationship is used to characterize the relationship between the stress of the solar cell and the characteristic peak offset. The corresponding relationship is obtained based on multiple characteristic peak offsets and multiple maximum stresses. The maximum stress is used to characterize the maximum stress that the surface of the solar cell bears under bending deformation.

2. The method according to claim 1, characterized in that, The correspondence is represented by a fitting algorithm, and the coefficients of the fitting algorithm are obtained by linear fitting based on the multiple characteristic peak offsets and the multiple maximum stresses.

3. The method according to claim 2, characterized in that, The method further includes: Multiple sets of data are obtained, each set of data including a maximum stress of the solar cell and the characteristic peak offset corresponding to the maximum stress; Based on the multiple sets of data, a linear fit is performed to determine the coefficients of the fitting algorithm.

4. The method according to claim 3, characterized in that, The acquisition of multiple sets of data includes: For any set of data, determine the Young's modulus of the solar cell and the bending radius of the solar cell, the bending radius being generated when an external force is applied to the target area of ​​the solar cell; The maximum stress of the solar cell is determined based on the Young's modulus, the bending radius, and the thickness of the solar cell. The target region is scanned by the spectrometer to obtain the characteristic peak shift corresponding to the maximum stress; wherein... Different sets of data correspond to different external forces.

5. The method according to claim 4, characterized in that, Determining the Young's modulus of the solar cell includes: The Young's modulus of the solar cell is determined based on the external force, the physical dimensions of the solar cell, and the deflection of the solar cell. The physical dimensions include the width, thickness, and span of the solar cell.

6. The method according to claim 5, characterized in that, Determining the bending radius of the solar cell includes: Obtain a bending cross-sectional image of the solar cell under the action of the external force; Identify the curved contour lines of the curved cross-section image; Based on the curved contour line, fit the arc parameters corresponding to the solar cell; The bending radius of the solar cell is determined based on the arc parameters.

7. The method according to claim 1, characterized in that, The correspondence is represented by a correspondence table, which includes the relationship between the multiple characteristic peak offsets and the multiple maximum stresses; Determining the target stress of the solar cell based on the target characteristic peak offset and its correspondence includes: Find the target stress corresponding to the target characteristic peak offset from the correspondence table.

8. A stress testing device for solar cells, characterized in that, The device includes: The acquisition module is used to acquire the target characteristic peak shift of the solar cell obtained by scanning with a spectrometer; The determination module is used to determine the target stress of the solar cell based on the target characteristic peak offset and the corresponding relationship. The corresponding relationship is used to characterize the relationship between the stress of the solar cell and the characteristic peak offset. The corresponding relationship is obtained based on multiple characteristic peak offsets and multiple maximum stresses. The maximum stress is used to characterize the maximum stress that the surface of the solar cell bears under bending deformation.

9. An electronic device, characterized in that, It includes a processor and a memory, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The device stores computer instructions that, when executed by a processor, implement the steps of the method according to any one of claims 1-7.

Images