Method for predicting reliability of photovoltaic module

Abstract

The invention discloses a method for predicting the reliability of a photovoltaic module. The prediction method comprises the following steps: constructing a three-dimensional simulation structure of the photovoltaic module, configuring base material parameters for the three-dimensional simulation structure, and performing grid division on the three-dimensional simulation structure to obtain a plurality of nodes; circularly executing the following steps: when any cycle period meets a cycle stop condition, ending the cycle: performing thermal cycle test simulation by using the configured thermal cycle parameters and the three-dimensional simulation structure; calculating a broken gate factor of each node in the three-dimensional simulation structure; and according to the grid breaking factor of the node, analyzing whether the current thermal cycle period meets a cycle stop condition, and if so, outputting at least one of stress related data, a grid breaking factor cloud picture and thermal cycle times corresponding to each base material of the photovoltaic module. According to the scheme, the thermal stress resistance action process of the photovoltaic module and influence factors for thermal stress resistance can be provided, and the period and development cost of the structural design of the photovoltaic module are effectively reduced.

Description

Technical Field

[0001] The invention relates to a method for predicting the reliability of a photovoltaic component. Background Art

[0002] Thermal Cycling Test (TC) is a reliability accelerated aging test for photovoltaic modules. The test results can be used to evaluate the thermal stress resistance of photovoltaic modules to guide the selection of materials for making photovoltaic modules. Therefore, for photovoltaic modules using new materials or photovoltaic modules with new structures using existing materials, the results of thermal cycling tests are one of the important indicators for evaluating the new materials and new structures used in photovoltaic modules.

[0003] At present, in order to select new materials to prepare photovoltaic modules or use existing materials to prepare photovoltaic modules with new structures, it is necessary to first produce test photovoltaic modules and then conduct thermal cycle tests on the test photovoltaic modules. In the case where the selected materials are inappropriate or the structure is inappropriate, it is necessary to further adjust the materials or structures and re-produce the test photovoltaic modules with the adjusted materials or structures, and further test the re-produced test photovoltaic modules until the new structure is determined or the new material is selected or it is determined that all new structures or selected new materials are inappropriate.

[0004] Regarding the existing thermal cycle test, on the one hand, the results can only reflect the thermal stress resistance of photovoltaic modules, but cannot reveal the thermal stress resistance process and the factors affecting thermal stress resistance; on the other hand, the thermal cycle test cycle is relatively long, and the new material selection and structural design of photovoltaic modules lead to a relatively long cycle and high cost. Summary of the invention

[0005] In view of this, the present invention provides a method for predicting the reliability of photovoltaic modules, which can provide the thermal stress resistance process and influencing factors of thermal stress resistance for photovoltaic modules, and can effectively reduce the material selection or new structure design cycle of photovoltaic modules, thereby reducing the development cost of photovoltaic modules.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] A method for predicting the reliability of a photovoltaic module, comprising:

[0008] Step 1: construct a three-dimensional simulation structure for the photovoltaic module to be analyzed, configure substrate parameters for the three-dimensional simulation structure, and perform grid division on the three-dimensional simulation structure to obtain a plurality of nodes;

[0009] The following steps 2 to 4 are executed cyclically. The loop ends when the loop stop condition is met in any loop cycle:

[0010] Step 2: using the configured thermal cycle parameters to perform thermal cycle test simulation on the three-dimensional simulation structure;

[0011] Step 3, combining the simulation results, the thermal cycle parameters and the substrate parameters, calculating the gate breaking factor of each node in the three-dimensional simulation structure;

[0012] Step 4: Analyze whether the current thermal cycle meets the cycle stop condition according to the gate breaking factor of the node. If the cycle stop condition is met, execute step 5; if the cycle stop condition is not met, execute step 2 based on the three-dimensional simulation structure of the current thermal cycle simulation process;

[0013] Step 5: output at least one of the stress-related data, the grid-breaking factor cloud diagram, and the number of thermal cycles corresponding to each substrate of the photovoltaic module to be analyzed.

[0014] Optionally, the above-mentioned method for predicting the reliability of a photovoltaic module further comprises: determining a critical peeling force between a soldering ribbon and a solar cell included in the photovoltaic module to be analyzed;

[0015] Step 3 also includes: further combining the critical peeling force to calculate the breaking factor of each node in the three-dimensional simulation structure.

[0016] Optionally, step 3 includes: performing the following operations for each of the nodes:

[0017] Step 31, calculating the peeling shear force of the node;

[0018] Step 32: Calculate the breaking factor of the node using the peeling shear force of the node and the critical peeling force.

[0019] Optionally, determining the critical peeling force between the soldering ribbon and the solar cell of the photovoltaic module comprises:

[0020] The IEC standard is used to test the critical peeling force used for peeling between the solder ribbon used in the photovoltaic module to be analyzed and the grid line of the solar cell.

[0021] Optionally, for the case where the breaking factor of the node is obtained by dividing the peeling shear force of the node by the critical peeling force,

[0022] The cycle stopping condition of step 4 is: the gate breaking factor of any of the nodes in the current thermal cycle is greater than or equal to 1.

[0023] Optionally, step 31 includes:

[0024] The peeling shear force of the node is calculated using the elastic modulus, substrate thickness, substrate thermal expansion coefficient, neutral axis curvature, temperature variation of each substrate included in the substrate parameters and the normal strain of the node included in the simulation results.

[0025] Optionally, for each cycle as the current thermal cycle, if step 4 analyzes that the current thermal cycle does not meet the cycle stop condition, the method further includes:

[0026] Step 5': using the gate breaking factor of each node, calculate the simulated cumulative damage of the photovoltaic assembly to be analyzed, and introduce the simulated cumulative damage into the three-dimensional simulation structure of the current thermal cycle simulation process.

[0027] Optionally, the substrate parameters include multiple of the following parameters:

[0028] Density, specific heat capacity, coefficient of thermal expansion, Young's modulus, thermal conductivity, material type, PV module dimensions, and substrate dimensions.

[0029] Optionally, the thermal cycle parameters include: initial temperature, temperature change time and temperature change rate.

[0030] Optionally, the stress-related data of each substrate output in step 5 includes: a stress cloud diagram of each substrate, a stress magnitude of each substrate corresponding to the node, and a stress direction corresponding to the node.

[0031] Optionally, the above photovoltaic module reliability prediction method further includes:

[0032] Comparing at least one of the stress-related data, the grid-breaking factor cloud diagram, and the number of thermal cycles of each substrate of photovoltaic modules with different structures;

[0033] Based on the comparison results, the material and size combination of the substrate of the photovoltaic module whose performance meets the set conditions are determined.

[0034] Optionally, the above-mentioned photovoltaic module reliability prediction method also includes: based on at least one of the stress-related data of each substrate, the grid breaking factor cloud map and the number of thermal cycles, analyzing the cause of the thermal cycle failure of the photovoltaic module and the factors leading to the thermal cycle failure.

[0035] Optionally, the above photovoltaic module reliability prediction method is implemented based on ANSYS-APDL language.

[0036] Optionally, the above photovoltaic module reliability prediction method further includes:

[0037] Use substrates whose performance meets the set conditions to assemble test photovoltaic modules;

[0038] Performing a thermal cycle test on the test photovoltaic module according to the thermal cycle parameters and the predicted number of thermal cycles;

[0039] The photovoltaic modules after thermal cycle test are verified by electroluminescence EL test.

[0040] The technical solution of the first aspect of the above invention has the following advantages or beneficial effects:

[0041] In the technical solution provided by the embodiment of the present invention, a three-dimensional simulation structure is constructed for the photovoltaic assembly to be analyzed, and substrate parameters are configured for the three-dimensional simulation structure, so that the three-dimensional simulation structure can simulate the relationship between the photovoltaic assembly to be analyzed or the core substrate of the photovoltaic assembly to be analyzed. Subsequently, the three-dimensional simulation structure is subjected to a plurality of cycles of thermal cycle tests, and the stress-related data of each substrate under each node can be simulated in each cycle. In each cycle, the gate-breaking factor of each node divided by the three-dimensional simulation structure is calculated, which can not only control the cycle to stop and avoid entering a dead loop, but also simulate the gate-breaking factor cloud map of the photovoltaic assembly to be analyzed and the number of thermal cycles of the photovoltaic assembly to be analyzed. By outputting at least one of the stress-related data, the gate-breaking factor cloud map and the number of thermal cycles corresponding to each substrate of the photovoltaic assembly to be analyzed, these data can reflect the thermal stress resistance of the photovoltaic assembly to be analyzed, the thermal stress resistance process, and the influencing factors for thermal stress resistance. In addition, these data are obtained by simulation, and the user does not need to specially make a test photovoltaic assembly, which can greatly shorten the cycle of new material selection or new structure design for photovoltaic assemblies, and reduce the development cost of photovoltaic assemblies. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 is a schematic diagram of the main process of a method for predicting the reliability of a photovoltaic module according to an embodiment of the present invention;

[0043] Figure 2 is a schematic diagram of a time-temperature relationship curve of a thermal cycle provided in an embodiment of the present invention;

[0044] Figure 3 It is a curve diagram of the thermal expansion coefficient of a carrier film in a photovoltaic module to be analyzed at different temperatures according to an embodiment of the present invention. DETAILED DESCRIPTION

[0045] At present, the main method is to experimentally produce test photovoltaic modules, and then obtain the thermal stress resistance of the test photovoltaic modules by conducting thermal cycle tests on the test photovoltaic modules. With this current processing method, only the results of the thermal stress resistance of the test photovoltaic modules can be obtained, and it cannot reflect the process of the thermal stress resistance of each film layer or functional structure (such as encapsulation film, battery cell) of the test photovoltaic modules, nor can it reflect the main factors and failure mechanisms that affect the thermal stress resistance of the test photovoltaic modules. The existing test cycle of this method is relatively long and requires relatively high production costs.

[0046] Although there are literatures on the simulation of thermal stress cycles, the simulation is mainly for the thermal stress simulation of materials and structural parts used in aviation, automobile manufacturing, nuclear energy facilities, etc., and the current thermal stress cycle simulation is generally an independent simulation of materials or structures formed by materials, or through a pre-established environmental influencing factor model for the failure of crystalline silicon photovoltaic modules, the reliability and durability test of crystalline silicon photovoltaic modules is improved by using the finite element analysis method. Among them, for the pre-established environmental influencing factor model for the failure of crystalline silicon photovoltaic modules, it is necessary to first know the failure mechanisms of various structures of crystalline silicon photovoltaic modules, such as the failure mechanism of glass breakage, the failure mechanism of EVA film aging, the failure mechanism of hot spot bands, the hidden cracks of battery cells, lightning patterns, PID effects, and the cracking and powdering of backplanes. In addition, the use of finite element analysis still requires a large amount of statistical data to establish a photovoltaic module mechanical stress and thermal stress analysis model to simulate thermal stress. Therefore, the existing simulation process requires the construction of a complex analysis model, resulting in low analysis efficiency and high consumption of computing resources.

[0047] In order to solve the above problems existing in the reliability analysis of photovoltaic modules, the embodiment of the present invention provides a novel method for predicting the reliability of photovoltaic modules, which can not only provide stress-related data, grid-breaking factor cloud diagram and thermal cycle times of each substrate during thermal cycle simulation, but also effectively reduce the consumption of computing resources.

[0048] in, Figure 1 A schematic diagram showing the main flow of a method for predicting the reliability of a photovoltaic module provided by an embodiment of the present invention.

[0049] like Figure 1 As shown, the photovoltaic module reliability prediction method provided by the embodiment of the present invention may include the following steps:

[0050] Step S101: construct a three-dimensional simulation structure for the photovoltaic module to be analyzed, configure substrate parameters for the three-dimensional simulation structure, and perform grid division on the three-dimensional simulation structure to obtain a plurality of nodes.

[0051] The photovoltaic module to be analyzed generally refers to a photovoltaic module whose performance or reliability (especially thermal cycle performance) is still unclear and needs further study. Specifically, the photovoltaic module to be analyzed can be a photovoltaic module with a new structure designed by the user, or a new photovoltaic module composed of a new material selected by the user to replace one or more materials in an existing photovoltaic module.

[0052] In the embodiment of the present invention, the three-dimensional simulation structure may be a three-dimensional presentation of the complete structure of a photovoltaic module, or may be a three-dimensional presentation of the relative position relationship of the core substrate in the photovoltaic module.

[0053] In the embodiments of the present invention, the substrate generally refers to the material or structure used to form a photovoltaic module. For example, the photovoltaic module to be analyzed includes a glass cover plate, an upper packaging film, a battery cell, a welding strip, a lower packaging film and a glass back plate. The glass cover plate, the upper packaging film, the battery cell, the welding strip, the lower packaging film and the glass back plate are the substrates of the photovoltaic module.

[0054] For the three-dimensional simulation structure, it can include the structures of all substrates of the photovoltaic assembly to be analyzed (i.e., the structure corresponding to the glass cover plate, the structure corresponding to the upper encapsulation film, the structure corresponding to the battery cell, the structure corresponding to the welding strip, the structure corresponding to the lower encapsulation film, and the structure corresponding to the glass back plate), and present the relative position relationship and interaction between the structures of these substrates. In addition, the three-dimensional simulation structure can also be composed of only the structure of part of the substrate of the photovoltaic assembly to be analyzed, and present the relative position relationship and interaction between the structures of this part of the substrate. For example, the three-dimensional simulation structure is composed of the structure corresponding to the upper encapsulation film, the structure corresponding to the battery cell, the structure corresponding to the welding strip, and the structure corresponding to the lower encapsulation film, and presents the relative position relationship and interaction between the structure corresponding to the upper encapsulation film, the structure corresponding to the battery cell, the structure corresponding to the welding strip, and the structure corresponding to the lower encapsulation film. For another example, the three-dimensional simulation structure is composed of only the structure corresponding to the upper encapsulation film, the structure corresponding to the battery cell, and the structure corresponding to the welding strip, and presents the relative position relationship and interaction between the structure corresponding to the upper encapsulation film, the structure corresponding to the battery cell, and the structure corresponding to the welding strip. For another example, the three-dimensional simulation structure is only composed of the structure corresponding to the battery cell and the structure corresponding to the welding strip, which presents the relative position relationship and interaction between the structure corresponding to the battery cell and the structure corresponding to the welding strip.

[0055] That is to say, the three-dimensional simulation structure constructed by the embodiment of the present invention is not necessarily a combination of structures corresponding to all substrates of the photovoltaic module, but can also be a combination of structures corresponding to some substrates of the photovoltaic module. The user can select which substrates the three-dimensional simulation structure is composed of according to actual needs.

[0056] Among them, the substrate parameters refer to the structural configuration corresponding to the substrate contained in the three-dimensional simulation structure, so that the structure can simulate the substrate more realistically, such as the parameters of the glass cover plate, the parameters of the back plate, the parameters of the battery cell, the parameters of the upper encapsulation film, the parameters of the welding strip, the parameters of the lower encapsulation film, etc. The substrate parameters may include multiple of the following parameters: elastic modulus, density, specific heat capacity, thermal expansion coefficient, Young's modulus, thermal conductivity, material type, photovoltaic module size and substrate size, etc. Such as the density, specific heat capacity, thermal expansion coefficient, Young's modulus, etc. of the battery cell, preferably, the substrate parameters at least include thermal expansion coefficient, Young's modulus and material type. In addition, the substrate parameters also include: photovoltaic module width, length, battery cell thickness, fine grid height, encapsulation film thickness, carrier film thickness, welding strip radius, glass cover thickness, etc. Among them, the elastic modulus refers to the stress of the material under unidirectional stress state divided by the strain in the direction of material deformation. The thermal expansion coefficient is a physical quantity that describes the expansion of a material under temperature change, which is generally the expansion per unit length or unit volume of the material under unit temperature change. Thermal expansion coefficient can be expressed by linear expansion coefficient (linear expansion rate) and volume expansion coefficient (volume expansion rate). Linear expansion coefficient is the ratio of the expansion of a material unit length when the temperature changes to the original length. Volume expansion coefficient is the ratio of the expansion of a material unit volume when the temperature changes to the original volume. In addition, Young's modulus of a material is a physical quantity of the material's ability to resist deformation, which is the ratio between uniaxial stress and uniaxial deformation within the range where Hooke's law applies.

[0057] Furthermore, the substrate parameters may also include: defining the contact between structures corresponding to each substrate in the simulation structure, such as the contact between glass and adhesive film, adhesive film and carrier film, carrier film and welding strip, fine grid and battery cell, etc.

[0058] Among them, this step is to divide the mesh of the three-dimensional simulation structure, and the size of the mesh can be designed according to actual needs. The node is the intersection of each mesh line. For example, each small polyhedron (such as a tetrahedron, a hexahedron, etc.) is divided by the mesh, and the vertices of each small polyhedron are nodes. The size of the polyhedron can be set according to needs.

[0059] The following steps S102 to S104 are executed cyclically, and the loop ends when the loop stop condition is met in any loop period:

[0060] Step S102: using the configured thermal cycle parameters to perform thermal cycle test simulation on the three-dimensional simulation structure.

[0061] The thermal cycle parameters may include: initial temperature, temperature change time and temperature change rate. In addition, they may also include maximum temperature, various temperature change time periods, etc. The initial temperature, maximum temperature, temperature change time and temperature change rate are variable values, and users can set them according to their needs. For example, Figure 2 The cycle shown in FIG. 1 includes five temperature change time periods, namely: temperature change time period 1 corresponds to the first hour (h) from the beginning, the temperature is uniformly reduced from 25°C to -40°C, and the temperature change rate is -65°C / h (or -1.08°C / min); temperature change time period 2 is after temperature change time period 1, which corresponds to (i.e. 10 minutes), the temperature in the temperature change time period 2 is kept at -40°C, and the temperature change rate is 0; the temperature change time period 3 is after the temperature change time period 2, which corresponds to (i.e. 170 minutes), the temperature in the temperature change time period 3 rises uniformly from -40°C to 80°C, and the temperature change rate is 42.4°C / h (or 0.71°C / min); the temperature change time period 4 is after the temperature change time period 3, which corresponds to (i.e. 10 minutes), the temperature is maintained at 80°C during the temperature change period 4, and the temperature change rate is 0; the temperature change period 5 is after the temperature change period 4, which corresponds to (ie 110 min), the temperature evenly dropped from 80°C to 25°C during the temperature change time period 5, and the temperature change rate was 30.1°C / h (or 0.5°C / min).

[0062] The thermal cycle test simulation of the three-dimensional simulation structure can be completed by existing simulation software. The simulation software can simulate the stress-related data (such as normal stress, stress direction, etc.) of each node of the corresponding structure of each substrate according to the above-mentioned substrate parameters and can simulate and simulate the changes of stress-related data with each time point in the cycle period. Although the existing simulation software can simulate the stress-related data of each node of each substrate, it cannot associate the stress change-related data with the thermal cycle. Therefore, the current use of simulation software to simulate the thermal cycle process requires the establishment of a new thermal cycle-related calculation model to perform thermal cycle testing based on the new thermal cycle-related calculation model, and the new thermal cycle-related calculation model construction process is complex and requires more computing resources. The thermal cycle simulation process provided by the embodiment of the present invention uses the existing simulation software to simulate the stress-related data of each node of each substrate.

[0063] Step S103: Calculate the gate breaking factor of each node in the three-dimensional simulation structure by combining the simulation results, thermal cycle parameters and substrate parameters.

[0064] The broken gate factor provided in the embodiment of the present invention is used to evaluate the risk of broken gate in a three-dimensional simulation structure or to evaluate whether broken gate occurs in a three-dimensional simulation structure. The calculation process of the broken gate factor does not involve the construction of a complex calculation model and complex calculations, and consumes relatively little computing resources.

[0065] The gate-breaking factor of each node calculated in this step can be calculated in real time within a cycle, or can be the gate-breaking factor corresponding to the time point at the end of a cycle, or can be calculated at multiple time points within a cycle (such as 3h, 4h or The gate breaking factor of

[0066] Step S104: Analyze whether the current thermal cycle meets the cycle stop condition based on the node's gate breaking factor. If the cycle stop condition is met, execute step S105; if the cycle stop condition is not met, execute step S102 based on the three-dimensional simulation structure of the current thermal cycle simulation processing.

[0067] Step S105: outputting at least one of the stress-related data, the grid-breaking factor cloud diagram, and the number of thermal cycles corresponding to each substrate of the photovoltaic module.

[0068] Specifically, the stress-related data of each substrate outputted in step S105 includes: a stress cloud diagram of each substrate, a stress magnitude of each substrate corresponding to a node, and a stress direction corresponding to a node.

[0069] against Figure 1 In the provided embodiment, a three-dimensional simulation structure is constructed for the photovoltaic assembly to be analyzed, and substrate parameters are configured for the three-dimensional simulation structure, so that the three-dimensional simulation structure can simulate the relationship between the photovoltaic assembly to be analyzed or the core substrate of the photovoltaic assembly to be analyzed. Subsequently, the three-dimensional simulation structure is subjected to a plurality of cycles of thermal cycle tests, and the stress-related data of each substrate under each node can be simulated in each cycle. In each cycle, the gate-breaking factor of each node divided by the three-dimensional simulation structure is calculated, which can not only control the cycle to stop and avoid entering a dead loop, but also simulate the gate-breaking factor cloud map of the photovoltaic assembly to be analyzed and the number of thermal cycles of the photovoltaic assembly to be analyzed. By outputting at least one of the stress-related data, the gate-breaking factor cloud map and the number of thermal cycles corresponding to each substrate of the photovoltaic assembly to be analyzed, these data can reflect the thermal stress resistance of the photovoltaic assembly to be analyzed, the process of thermal stress resistance, and the factors affecting thermal stress resistance. In addition, these data are obtained by simulation, and the user does not need to specially make a photovoltaic assembly for testing, which can greatly shorten the cycle of new material selection or new structure design for photovoltaic assemblies, and reduce the development cost of photovoltaic assemblies.

[0070] Furthermore, the above-mentioned photovoltaic module reliability prediction method may further include: determining the critical peeling force between the soldering ribbon and the solar cell included in the photovoltaic module. The above-mentioned step S103 may further include: further combining the critical peeling force to calculate the breaking factor of each node in the three-dimensional simulation structure.

[0071] Specifically, there are two ways to determine the critical peeling force between the welding ribbon and the solar cell included in the photovoltaic module.

[0072] The first implementation method: Use the IEC standard to test the critical peeling force used for peeling between the soldering ribbon used in the photovoltaic module to be analyzed and the grid line of the cell. Specifically, establish a connection relationship between the soldering ribbon and the grid line of the cell, and then use the IEC standard to test the critical peeling force used for peeling between the soldering ribbon and the grid line of the cell. That is, it is only necessary to establish a connection relationship between the soldering ribbon and the cell, and the critical peeling force can be obtained without making the entire photovoltaic module to be analyzed. Among them, the IEC standard refers to the method and requirements for testing the peeling test of the soldering ribbon of photovoltaic cells formulated by the International Electrotechnical Commission (IEC). Specifically, the IEC standard uses standard test equipment to test the critical peeling force between the soldering ribbon and the surface of the cell at a temperature of 23°C±5°C.

[0073] The second implementation method: using the critical peeling force between the soldering ribbon and the cell in the existing photovoltaic module and the parameters of the soldering ribbon and the cell, the model is trained to obtain a calculation model of the critical peeling force. The critical peeling force between the soldering ribbon and the cell is calculated using the calculation model.

[0074] Specifically, for the technical solution combining the critical peeling force, the specific implementation of the above step S103 may include: performing the following steps S1031 and S1032 for each node:

[0075] Step S1031: Calculate the peeling shear force of the node.

[0076] Specifically, the peeling shear force of the node is calculated using the elastic modulus, substrate thickness, substrate thermal expansion coefficient, and curvature of the neutral axis of each substrate included in the substrate parameters, the temperature change included in the thermal cycle parameters, and the normal strain of the node included in the simulation results.

[0077] The peeling shear force at any node can be calculated using the following calculation formula (1).

[0078]

[0079] Among them, Q pst represents the peeling shear force of node s at time point t in the current thermal cycle; i represents the i-th layer structure in the three-dimensional simulation structure; n represents the total number of layers of the structure included in the three-dimensional simulation structure; E it represents the elastic modulus of the i-th layer structure at time point t in the current thermal cycle; h i represents the thickness of the i-th layer structure at time point t within a cycle; ki Represents the curvature of the neutral axis of the i-th layer structure in the three-dimensional simulation structure input by the user; ε st represents the positive strain of node s at time point t in the current thermal cycle; α it represents the thermal expansion coefficient of the i-th layer structure at time point t in the current thermal cycle; ΔT represents the temperature change from the previous time point t-1 to time point t in the current thermal cycle.

[0080] Among them, the neutral axis refers to the intersection of the cross section and the stress plane of the three-dimensional simulation structure in the case of plane bending and oblique bending. This intersection is the neutral axis, and the positive stress value of each point on the neutral axis is zero. Correspondingly, the curvature of the neutral axis refers to the curvature of the axis where the node with zero positive stress is located in the three-dimensional simulation structure. Since the thickness of each layer structure is relatively thin and the weight is relatively light, in the embodiment of the present invention, the three-dimensional simulation structure is taken as a whole, and the curvature of the neutral axis of each layer structure in the three-dimensional simulation structure is generally set to the same value. Therefore, the curvature of the neutral axis of the i-th layer structure in the three-dimensional simulation structure is generally set to a constant.

[0081] In addition, as mentioned above, the thermal expansion coefficient is a physical quantity that describes the expansion of a material under temperature changes, which is generally the expansion per unit length or per unit volume of the material under unit temperature changes. The thermal expansion coefficient can be represented by a linear expansion coefficient (linear expansion rate) and a volume expansion coefficient (volume expansion rate). In this embodiment, the thermal expansion coefficient can be selected from the linear expansion coefficient of the material, and can also be selected from the volume expansion coefficient of the material.

[0082] Among them, E it , ε st , α it and ΔT are temperature-related parameters, such as Figure 3 As shown in Figure 2, since the temperature changes with the time point t during the current thermal cycle, E it , ε st , α it and ΔT will also change with temperature. It is worth noting that ε st In addition to being affected by temperature, it is also affected by the number of thermal cycle cycles and the location of the node s. st It is the simulation result obtained by superimposing the simulation results generated by each thermal cycle before the current thermal cycle test cycle in the above step S102 during the thermal cycle test simulation process of the three-dimensional simulation structure. st It is the value output by the above step S102 according to the simulation result.

[0083] For example, α it Can be as Figure 3 As shown, the αit The temperature varies with the temperature. Based on this curve or the calculation equation corresponding to the curve, α can be determined according to the temperature value at time point t in the current thermal cycle. it .

[0084] In addition, E it and h i are also input by the user, and represent the elastic modulus and thickness of the material used for the i-th layer structure respectively. ΔT can be determined based on the time difference between the last time point t-1 and the time point t defined by the user and the thermal cycle parameters. For example, if Q pst If it is a real-time calculation, then the time difference between the previous time point t-1 and time point t is the time difference between the two adjacent calculation time points. For example, if the time point t-1 and time point t are both in Figure 2 In the temperature change time period 2 shown in FIG. 1 , ΔT = 0. If the time point t-1 and the time point t are both Figure 2 In the temperature change time period 3 shown, ΔT=v×(t t -t t-1 ), where v represents the temperature change rate in the temperature change time period 3 between time point t-1 and time point t; t t Indicates the time corresponding to time point t; t t-1 Indicates the time corresponding to time point t-1.

[0085] It is worth noting that n is determined by the three-dimensional simulation structure. For example, if the three-dimensional simulation structure only includes a battery cell, a soldering tape and an upper packaging film, then n = 3, where the battery cell is a layer, the soldering tape is a layer, and the upper packaging film is a layer. For a three-dimensional simulation structure including a glass cover, an upper packaging film, a soldering tape, a battery cell, a lower packaging film and a backplane, n = 6 for the three-dimensional simulation structure.

[0086] Step S1032: Calculate the node breaking factor using the node peeling shear force and critical peeling force.

[0087] Specifically, this step can be calculated using the following calculation formula (2).

[0088]

[0089] Among them, r st represents the gate-breaking factor of node s at time point t in the current thermal cycle; Q pst represents the peeling shear force of node s at time point t in the current thermal cycle; Q p Indicates the critical peeling force.

[0090] Among them, for the case where the node's breaking factor is obtained by dividing the node's peeling shear force by the critical peeling force, that is, for the case where the node's breaking factor is calculated using calculation formula (2), the cycle stop condition of step S104 is: the breaking factor of any node in the current thermal cycle is greater than or equal to 1.

[0091] In addition, the gate breaking factor can also be expressed based on a modified formula of the calculation formula (2). For example, it is calculated using the following calculation formula (3).

[0092]

[0093] Wherein, in the case where the gate-off factor of a node is calculated using calculation formula (3), the loop stop condition of step S104 is: the gate-off factor of any node in the current thermal cycle is less than or equal to 1.

[0094] Regardless of whether the broken grid factor is calculated based on the above calculation formula (2) or the calculation formula (3), it means that if the peeling shear force of any node is greater than or equal to the critical peeling force, it is determined that the photovoltaic module has a risk of broken grid or grid line detachment, that is, the three-dimensional simulation structure of the simulated photovoltaic module is damaged, and the stop condition of the thermal cycle detection is reached.

[0095] Furthermore, for each cycle as the current thermal cycle, when the current thermal cycle is analyzed in step S104 and it is found that the cycle stop condition is not satisfied, the above-mentioned photovoltaic module reliability prediction method further includes:

[0096] The simulated cumulative damage of the photovoltaic module is calculated using the gate breaking factor of each node, and the simulated cumulative damage is introduced into the three-dimensional simulation structure of the current thermal cycle simulation processing.

[0097] Specifically, the following calculation formula (4) is used to calculate the simulated cumulative damage of the photovoltaic module to be analyzed.

[0098]

[0099] Among them, r j represents the simulated cumulative damage calculated for the jth thermal cycle; C represents the correction coefficient; s represents the sth node; m represents the total number of nodes included in the three-dimensional simulation structure of the photovoltaic module to be analyzed; r stj It represents the gate breaking factor of the sth node at time point t in the jth thermal cycle.

[0100] The calculation formula (4) is mainly used to calculate the simulated cumulative damage under the thermal cycle by using the gate breaking factor of each node corresponding to the end time point of the thermal cycle.

[0101] Furthermore, the simulated cumulative damage of the photovoltaic module can also be calculated using the following calculation formula (5).

[0102]

[0103] Among them, r j represents the simulated cumulative damage calculated for the jth thermal cycle; C represents the correction coefficient; s represents the sth node; m represents the total number of nodes contained in the three-dimensional simulation structure of the photovoltaic module to be analyzed; t represents the time point t; L represents the duration of a thermal cycle; r stj It represents the gate breaking factor of the sth node at time point t in the jth thermal cycle.

[0104] The calculation formula (5) is obtained by superimposing the gate breaking factors of each node at various time points in a thermal cycle.

[0105] Although the calculation results obtained by calculation formula (5) and calculation formula (4) are different, it is found through experiments that the final output results are not much different. The result given by calculation formula (5) is more sensitive. According to the computing resource requirements, calculation formula (4) or calculation formula (5) can be selected to improve the calculation flexibility.

[0106] Furthermore, the above-mentioned prediction method of the reliability of photovoltaic modules may also include: comparing at least one of the stress-related data, the grid-breaking factor cloud map and the number of thermal cycles of each substrate of photovoltaic modules with different structures; according to the comparison results, determining the material and size combination selected for the substrate of the photovoltaic module whose performance meets the set conditions. The set conditions may be a threshold value of the number of thermal cycles, a stress threshold, or may be to select a photovoltaic module with the largest number of thermal cycles or to select a photovoltaic module with the smallest stress, etc. Among them, the threshold value of the number of thermal cycles or the stress threshold may be set according to the user's requirements for photovoltaic modules. That is, by constructing a three-dimensional simulation structure for substrates with different parameters, and performing a thermal cycle test simulation on the three-dimensional simulation structure through the above process, and calculating the grid-breaking factor, according to the output results corresponding to each three-dimensional simulation structure: the stress-related data of each substrate included in each three-dimensional simulation structure, the grid-breaking factor cloud map and the number of thermal cycles of each three-dimensional simulation structure, the three-dimensional simulation structure with the best performance or the performance that meets the user's requirements is selected, so as to determine that the material parameters corresponding to the three-dimensional simulation structure are substrates with excellent performance.

[0107] Furthermore, the above-mentioned prediction method of the reliability of photovoltaic modules may also include: based on at least one of the stress-related data of each substrate, the grid-breaking factor cloud map and the number of thermal cycles, analyzing the cause of thermal cycle failure of the photovoltaic module and the factors leading to thermal cycle failure. Specifically, the cause of thermal cycle failure and the factors leading to thermal cycle failure can be determined based on the mapping relationship between the pre-constructed mapping relationship between the cause of thermal cycle failure and the factors leading to thermal cycle failure and the stress-related data of each substrate, the grid-breaking factor cloud map and the number of thermal cycles, so as to provide a reference for further analysis by the user.

[0108] Furthermore, the above-mentioned method for predicting the reliability of photovoltaic modules may also include: using a substrate whose performance meets the set conditions to form a test photovoltaic module; performing a thermal cycle test on the test photovoltaic module according to the thermal cycle parameters and the predicted number of thermal cycles; and verifying the photovoltaic module after the thermal cycle test by an electroluminescent (EL) test. Among them, the thermal cycle test is to perform an actual thermal cycle test on the test photovoltaic module according to the above-mentioned thermal cycle test simulation process for the three-dimensional simulation structure, and then perform an electroluminescent test on the photovoltaic module after the thermal cycle test by an EL tester to verify the simulation results and ensure that the substrate finally selected can prepare a photovoltaic module with excellent performance. As described above, the set conditions can be a thermal cycle number threshold, a stress threshold, or a photovoltaic module with the largest number of thermal cycles or a photovoltaic module with the smallest stress. Among them, the thermal cycle number threshold or the stress threshold can be set according to the user's demand for photovoltaic modules.

[0109] Furthermore, the above-mentioned embodiments can be implemented based on ANSYS-APDL language.

[0110] In the process of implementation based on ANSYS-APDL language, the above simulation process establishes boundary conditions for the three-dimensional simulation structure, and the simulated cumulative damage obtained in each thermal cycle is used as the boundary condition of the next thermal cycle. For example, for the ANSYS-APDL language, for the above substrate parameter configuration, the EDCGEN command can be used to define the contact between the layers of materials, the LESIZE command in ANSYS-APDL can be used to define the mesh size for each edge of the cross section, and then the AMESH command can be used to mesh the component. Use the EDLOAD command to configure the thermal cycle parameters.

[0111] The following describes the photovoltaic module reliability prediction method implemented by the technical solution provided in the embodiment of the present invention for two scenarios: selecting excellent materials for photovoltaic modules and evaluating photovoltaic modules with newly designed structures.

[0112] Scenario 1: Selecting excellent materials for photovoltaic modules

[0113] Step A1: receiving substrate parameters input by a user, wherein the substrate parameters correspond to parameters of multiple materials corresponding to each substrate and combination relationships between multiple materials of the multiple substrates.

[0114] Step B1: construct a corresponding three-dimensional simulation structure for each combination relationship according to the parameters of the various materials corresponding to each substrate and the combination relationship between the various materials of the various substrates.

[0115] Step C1, performing thermal cycle test simulation for each three-dimensional simulation structure cycle, and in each cycle, calculating the gate breaking factor of the three-dimensional simulation structure using the above-mentioned gate breaking factor calculation formula, and executing step D1 when the cycle stop condition is met; if the cycle stop condition is not met, performing the next thermal cycle based on the three-dimensional simulation structure simulated in the current thermal cycle cycle;

[0116] Step D1, outputting stress-related data, gate breaking factor cloud diagram and thermal cycle times of each substrate of each three-dimensional simulation structure.

[0117] Step E1, selecting the three-dimensional simulation structure with the best performance from the stress-related data, the breaking factor cloud map and the number of thermal cycles of each substrate of each three-dimensional simulation structure, and determining the material corresponding to the three-dimensional simulation structure with the best performance.

[0118] Scenario 2: Evaluating a newly designed photovoltaic module structure

[0119] Step A2: receiving substrate parameters of a photovoltaic module of a newly designed structure input by a user, wherein the substrate parameters include parameters of materials corresponding to each substrate and structural relationships between the substrates.

[0120] Step B2: construct a corresponding three-dimensional simulation structure for the designed photovoltaic module with a new structure according to the parameters of the material corresponding to each substrate in the substrate parameters and the structural relationship between the substrates.

[0121] Step C2, performing a thermal cycle test simulation on the three-dimensional simulation structure cycle, and in each cycle, calculating the gate breaking factor of the three-dimensional simulation structure using the above-mentioned gate breaking factor calculation formula, and executing step D2 when the cycle stop condition is met; if the cycle stop condition is not met, performing the next thermal cycle based on the three-dimensional simulation structure processed by the current thermal cycle cycle simulation;

[0122] Step D2: outputting stress-related data, gate breaking factor cloud diagram and thermal cycle times of each substrate of the three-dimensional simulation structure.

[0123] Step E2: Determine the thermal cycle performance of the photovoltaic module with the newly designed structure according to the stress-related data of each substrate, the grid breaking factor cloud diagram and the number of thermal cycles.

[0124] Furthermore, an embodiment of the present invention provides an electronic device, which may include:

[0125] one or more processors;

[0126] a storage device for storing one or more programs,

[0127] When one or more programs are executed by one or more processors, the one or more processors implement the photovoltaic component reliability prediction method provided in any of the above embodiments.

[0128] Furthermore, an embodiment of the present invention provides a computer-readable medium having a computer program stored thereon, and when the program is executed by a processor, the method for predicting the reliability of a photovoltaic module provided in any of the above embodiments is implemented.

[0129] In particular, according to the embodiments disclosed in the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication part, and / or installed from a removable medium. When the computer program is executed by a central processing unit (CPU), the above-mentioned functions defined in the system of the present invention are executed.

[0130] It should be noted that the computer-readable medium shown in the present invention may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0131] The introduction provided in the above steps is only used to help understand the structure, method and core idea of ​​the present invention. For ordinary technicians in this technical field, without departing from the principle of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications also belong to the scope of protection of the claims of the present invention.

Claims

1. A method for predicting the reliability of a photovoltaic module, characterized in that: include: Step 1: construct a three-dimensional simulation structure for the photovoltaic module to be analyzed, configure substrate parameters for the three-dimensional simulation structure, and perform grid division on the three-dimensional simulation structure to obtain a plurality of nodes; The following steps 2 to 4 are executed cyclically. The loop ends when the loop stop condition is met in any loop cycle: Step 2: using the configured thermal cycle parameters to perform thermal cycle test simulation on the three-dimensional simulation structure; Step 3, combining the simulation results, the thermal cycle parameters and the substrate parameters, calculating the gate breaking factor of each node in the three-dimensional simulation structure; Step 4: Analyze whether the current thermal cycle meets the cycle stop condition according to the gate breaking factor of the node. If the cycle stop condition is met, execute step 5; if the cycle stop condition is not met, execute step 2 based on the three-dimensional simulation structure of the current thermal cycle simulation process; Step 5: output at least one of the stress-related data, the grid-breaking factor cloud diagram, and the number of thermal cycles corresponding to each substrate of the photovoltaic module to be analyzed.

2. The method for predicting the reliability of a photovoltaic module according to claim 1, characterized in that: The prediction method further comprises: determining a critical peeling force between a soldering ribbon and a cell sheet included in the photovoltaic assembly to be analyzed; Step 3 also includes: further combining the critical peeling force to calculate the breaking factor of each node in the three-dimensional simulation structure.

3. The method for predicting the reliability of a photovoltaic module according to claim 2, characterized in that: Step 3 includes: For each of the nodes, perform the following operations: Step 31, calculating the peeling shear force of the node; Step 32: Calculate the breaking factor of the node using the peeling shear force of the node and the critical peeling force.

4. The method for predicting the reliability of a photovoltaic module according to claim 2, characterized in that: The step of determining a critical peeling force between a soldering ribbon and a solar cell included in the photovoltaic module comprises: The IEC standard is used to test the critical peeling force used for peeling between the solder ribbon used in the photovoltaic module to be analyzed and the grid line of the solar cell.

5. The method for predicting the reliability of a photovoltaic module according to claim 2, characterized in that: For the case where the breaking factor of the node is obtained by dividing the peeling shear force of the node by the critical peeling force, The cycle stopping condition of step 4 is: the gate breaking factor of any of the nodes in the current thermal cycle is greater than or equal to 1.

6. The method for predicting the reliability of a photovoltaic module according to claim 3, characterized in that: Step 31 includes: The peeling shear force of the node is calculated using the elastic modulus, substrate thickness, substrate thermal expansion coefficient, neutral axis curvature, temperature variation of each substrate included in the substrate parameters and the normal strain of the node included in the simulation results.

7. The method for predicting the reliability of a photovoltaic module according to any one of claims 1 to 6, characterized in that: For each cycle as the current thermal cycle, if step 4 analyzes that the current thermal cycle does not meet the cycle stop condition, it also includes: Step 5': using the gate breaking factor of each node, calculate the simulated cumulative damage of the photovoltaic assembly to be analyzed, and introduce the simulated cumulative damage into the three-dimensional simulation structure of the current thermal cycle simulation process.

8. The method for predicting the reliability of a photovoltaic module according to claim 1, characterized in that: The substrate parameters include multiple of the following parameters: Density, specific heat capacity, coefficient of thermal expansion, Young's modulus, thermal conductivity, material type, PV module dimensions, and substrate dimensions; and / or, The thermal cycle parameters include: initial temperature, temperature change time and temperature change rate; and / or, The stress-related data of each substrate outputted in step 5 include: a stress cloud diagram of each substrate, a stress magnitude of each substrate corresponding to the node, and a stress direction corresponding to the node.

9. The method for predicting the reliability of a photovoltaic module according to any one of claims 1 to 6 and 8, characterized in that: The method further comprises: Comparing at least one of the stress-related data, the grid-breaking factor cloud diagram, and the number of thermal cycles of each substrate of photovoltaic modules with different structures; According to the comparison results, determine the materials and size combinations for the substrate of photovoltaic modules that meet the set conditions; and / or, The method further includes: analyzing the cause of thermal cycle failure of the photovoltaic module and the factors leading to the thermal cycle failure based on at least one of stress-related data of each substrate, a grid-breaking factor cloud map, and the number of thermal cycles; and / or, The method is implemented based on ANSYS-APDL language.

10. The method for predicting the reliability of a photovoltaic module according to claim 9, characterized in that: Also includes: Use substrates whose performance meets the set conditions to assemble test photovoltaic modules; Performing a thermal cycle test on the test photovoltaic module according to the thermal cycle parameters and the predicted number of thermal cycles; The photovoltaic modules after thermal cycle test are verified by electroluminescence (EL) test.

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