Optimization method for outer frame of photovoltaic module
By using finite element analysis and multi-objective optimization algorithms, the structure of the outer frame of the photovoltaic module was optimized, which solved the problem of shading the solar cells, reduced material costs, improved power generation efficiency and structural strength, and ensured sealing and installation compatibility.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-03-09
- Publication Date
- 2026-07-14
AI Technical Summary
The outer frame of photovoltaic modules can obstruct the solar cells, resulting in power generation loss. In addition, the material cost is high and the structural design has issues with sealing and installation compatibility.
High-stress and low-stress regions were identified through finite element analysis. The complete structure of the high-stress region was preserved, while the low-stress region was hollowed out or chamfered. Combined with multi-objective optimization algorithms, the minimum material consumption was calculated, the shape was optimized, and simulation verification and batch trial production were carried out to optimize the production process parameters.
It improves power generation efficiency, reduces material costs, enhances structural strength and sealing performance, improves installation compatibility, and ensures the reliability and adaptability of components.
Smart Images
Figure CN122389406A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of photovoltaic power generation technology, and in particular to a method for optimizing the outer frame of a photovoltaic module. Background Technology
[0002] The outer frame structure of a photovoltaic module is crucial for ensuring its mechanical strength, weather resistance, and ease of installation. Aluminum alloy (such as 6063-T5 / T6) is the primary material, with composite materials (such as glass fiber reinforced plastic) or stainless steel (for special corrosion protection requirements) used in some scenarios, but these are more expensive. The frame cross-section is mostly a hollow "C" or "U" shaped groove, with internal reinforcing ribs to improve bending and compressive strength. The inner side of the frame has slots for embedding the photovoltaic glass and backsheet, secured with silicone or adhesive strips to form a mechanical lock. Bolt holes or slots are pre-set on both sides of the frame to accommodate various support systems (such as guide rails and clamps). However, the non-bolted connection parts on the back of the photovoltaic module frame can obstruct the solar cells, leading to power generation loss. Summary of the Invention
[0003] The present invention aims to at least partially solve one of the technical problems in the related art.
[0004] Therefore, embodiments of the present invention propose a method for optimizing the outer frame of a photovoltaic module, which has significant technical advantages in improving performance, reducing costs, and ensuring reliability.
[0005] The photovoltaic module outer frame optimization method of this invention includes: Analyze the usage environment, load conditions and user needs of photovoltaic modules, obtain the target values for each operating condition, and collect data on the material properties, manufacturing process parameters and environmental conditions of photovoltaic modules. Based on the collected data, combined with the preset geometric information and boundary physical parameters, an initial design model is generated, and the material properties, load conditions and boundary constraints of the model are determined. The stress distribution of the frame is analyzed by finite element analysis to determine the high stress area and low stress area of the frame. Based on the stress distribution results, the areas that can be hollowed out and chamfered are determined. The bolt connection area and key support structure are retained. The shape optimization design of the areas that can be hollowed out and chamfered is carried out. Define the optimization problem, including design variables, objective function and constraints, and calculate the minimum material usage to meet the strength and sealing requirements through iterative optimization. Size optimization and performance verification; Establish finite element models with different combinations, conduct static and dynamic performance simulations, fabricate process samples, and conduct physical experiments to verify the design performance. Based on simulation and experimental results, production process parameters were optimized, batch trial production was carried out, and variable factors in batch production were verified.
[0006] The photovoltaic module outer frame optimization method of this invention comprehensively solves the problems of high material cost, structural design, sealing and waterproofing, and installation compatibility through steps such as finite element analysis, multi-objective optimization, simulation verification, and batch trial production.
[0007] In some embodiments, the high-stress and low-stress regions of the frame are determined by finite element analysis. The complete structure of the high-stress region is preserved, while the low-stress region is hollowed out or chamfered. The area of the hollowed-out region is... Satisfying the formula:
[0008] in, This represents the total area of the back of the border. The area of the reserved bolted connection area; chamfer angle Satisfying the formula:
[0009] in, The height of the chamfer. This is the width of the chamfer.
[0010] In some embodiments, an optimization problem is defined, and design variables include the thickness of the border. ,width and the area of the hollowed-out area The objective function includes structural strength, material usage, and power generation efficiency. The minimum material usage required to meet the strength and sealing requirements is calculated, and the optimized objective function is:
[0011] in, , , For reference values, structural strength constraints Material usage constraints Power generation efficiency constraints .
[0012] In some embodiments, the multi-objective optimization algorithm employs a genetic algorithm, and the design variables include the thickness of the bounding box. ,width and chamfer angle The optimization objective is:
[0013] in, , , For reference only; The iterative formula is:
[0014] in, For the first Design variables for each iteration Step size factor The gradient of the objective function.
[0015] In some embodiments, size optimization includes: Based on the optimized structure, an approximate parameterized model is established. Initial performance analysis was performed using finite element analysis software, defining the response, constraints, and optimization objectives. Iteratively update the design variables to obtain the target topology optimization structure that meets the target value; The optimized structure was subjected to a sealing test.
[0016] In some embodiments, the physical test includes: Verify the deformation and failure modes of the frame under rated load; Evaluate the fatigue performance of the frame under wind-induced vibration conditions; Test the performance stability of the frame under different environmental conditions; Verify that the continuous contact surface of the sealant or adhesive strip between the frame and the back panel / glass meets the waterproof requirements.
[0017] In some embodiments, batch trial production includes verifying the impact of production process parameters on frame performance, optimizing manufacturing equipment and tooling, and verifying the applicability of the optimized frame to different types of battery cells. Attached Figure Description
[0018] Figure 1 This is a schematic diagram of a photovoltaic module outer frame optimization method according to an embodiment of the present invention. Detailed Implementation
[0019] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.
[0020] The following describes the photovoltaic module outer frame optimization method according to an embodiment of the present invention with reference to the accompanying drawings.
[0021] like Figure 1 As shown, the photovoltaic module outer frame optimization method of this embodiment includes: S100 requirements analysis and data collection analyzes the usage environment, load conditions and user needs of photovoltaic modules, obtains target values for each operating condition, and collects data on the material properties, manufacturing process parameters and environmental conditions of photovoltaic modules to ensure that the design meets the performance requirements under different environmental and load conditions and avoids performance degradation due to insufficient environmental adaptability.
[0022] By comprehensively analyzing the operating environment, load conditions, and user requirements, we ensure that the design fully considers various working conditions in practical applications, avoiding both under-design and over-design. Obtaining target values for each working condition provides a clear direction for subsequent optimization.
[0023] The S200 initial design model is generated based on collected data and pre-set geometric information and boundary physical parameters. The initial design model is then determined, including the material properties, load conditions, and boundary constraints of the model. This provides an accurate model for subsequent optimization and analysis, avoiding optimization deviations caused by inaccurate models.
[0024] Based on the collected data, combined with pre-defined geometric information and boundary physical parameters, an initial design model is generated, providing a foundation for subsequent optimization. The material properties, load conditions, and boundary constraints of the model are determined to ensure its accuracy and reliability.
[0025] S300 structural optimization and cutout area determination: Through finite element analysis, stress distribution analysis of the frame was performed to determine the high-stress and low-stress areas of the frame. Based on the stress distribution results, areas that can be cut out and chamfered were determined, while bolted connection areas and key support structures were retained. The shape of the cutout and chamfered areas was optimized, which solved the problem of non-bolted connection parts on the back covering the battery cells, improved power generation efficiency, and ensured that the optimized structure reduced material usage and cost while retaining key support areas.
[0026] The stress distribution of the frame is analyzed by finite element analysis (FEA) to determine the high-stress and low-stress areas.
[0027] Based on the stress distribution results, areas that can be hollowed out and chamfered are determined, while bolted connection areas and key support structures are retained to avoid a decrease in structural strength due to the removal of key areas.
[0028] The shape of the perforated and chamfered areas is optimized to reduce shading of the solar cells and improve the power generation efficiency of the module.
[0029] The S400 multi-objective optimization and minimum material usage calculation defines the optimization problem, including design variables, objective function, and constraints. Through iterative optimization, it calculates the minimum material usage to meet strength and sealing requirements, solving the problem of high material costs by minimizing material usage and reducing manufacturing costs. It ensures that the optimized structure maximizes material utilization while meeting strength and sealing requirements.
[0030] Define the optimization problem, including design variables (such as the thickness and width of the border, and the area of the hollow area), objective function (such as structural strength, material utilization, and power generation efficiency), and constraints (such as mass and volume).
[0031] Through iterative optimization, the minimum material usage required to meet strength and sealing requirements is calculated, ensuring that the optimized frame is suitable for different types of battery cells.
[0032] S500 size optimization and performance verification: Size optimization and performance verification ensure the performance of the optimized structure in practical applications, avoid performance degradation due to design deviations, solve sealing and waterproofing issues, and ensure that the optimized frame meets waterproofing requirements.
[0033] Based on the optimized structure, an approximate parameterized model is established.
[0034] Performance evaluation was conducted using finite element analysis software, and size optimization design variables were selected, along with the definition of response, constraints, and optimization objectives.
[0035] Iteratively update the design variables to obtain the target topology optimization structure that meets the objective values.
[0036] The optimized structure was subjected to a sealing test to ensure that the risk of moisture intrusion was minimized.
[0037] S600 simulation and physical testing were used to establish finite element models with different combinations, perform static and dynamic performance simulations, fabricate process samples, and conduct physical tests to verify the design performance. Through simulation and physical testing, the reliability and performance of the design were verified, ensuring that the optimized frame performs well in practical applications, solving installation compatibility issues, and verifying that the optimized frame is suitable for various bracket systems.
[0038] Establish finite element models for different combinations (such as single bending, riveting, and welding) and perform static and dynamic performance simulations. Fabricate process samples and conduct physical tests to verify the design performance, including: Static load testing verifies the deformation and failure mode of the frame under rated load; Dynamic vibration testing was conducted to evaluate the fatigue performance of the frame under wind-induced vibration conditions. Weather resistance test, which tests the performance stability of the frame under different environmental conditions; The sealing test verifies whether the continuous contact surface of the sealant or sealing strip between the frame and the back panel / glass meets the waterproof requirements.
[0039] S700 batch trial production and optimization: Based on simulation and test results, optimize production process parameters, conduct batch trial production, verify variable factors in batch production, optimize production process parameters, improve production efficiency and product quality, and ensure the stability and consistency of the optimized frame in batch production.
[0040] The photovoltaic module outer frame optimization method of this invention comprehensively solves the problems of high material cost, structural design, sealing and waterproofing, and installation compatibility through steps such as finite element analysis, multi-objective optimization, simulation verification, and batch trial production.
[0041] Improve power generation efficiency: By removing the obstruction of the non-bolted connection part on the back, the light-receiving area of the solar cells is increased, thereby increasing power generation.
[0042] Reduce costs: Reduce manufacturing costs by minimizing material usage and optimizing production processes.
[0043] Enhanced structural strength: Key support areas are preserved to ensure the frame's bending and torsional strength, thereby improving component reliability.
[0044] Improve sealing performance: Through optimized design and verification, ensure continuous contact surfaces of the sealant or adhesive strips on the frame to reduce the risk of moisture intrusion.
[0045] Improved installation compatibility: The optimized frame has been verified to be suitable for a variety of bracket systems, improving installation flexibility and reliability.
[0046] In summary, the photovoltaic module outer frame optimization method of this invention has significant technical advantages in improving performance, reducing costs, and ensuring reliability, providing an effective solution for the design and manufacturing of photovoltaic modules.
[0047] In some embodiments, high-stress and low-stress regions of the frame are determined by finite element analysis. The complete structure of the high-stress region is preserved, while the low-stress region is hollowed out or chamfered. This process aims to reduce shading of the solar cells and improve the power generation efficiency of the module.
[0048] Area of the hollowed-out area Satisfying the formula:
[0049] in, This represents the total area of the back of the border. The area of the reserved bolted connection area; chamfer angle Satisfying the formula:
[0050] in, The height of the chamfer. This is the width of the chamfer.
[0051] By removing the obstructions from the non-bolted connection parts on the back of the frame, the light-receiving area of the solar cells is increased, effectively improving overall power generation, especially under low-angle lighting conditions. Hollowing out or chamfering low-stress areas reduces material usage, thereby lowering manufacturing costs.
[0052] By preserving the integrity of the structure in high-stress areas, the bending and torsional strength of the frame is ensured, improving the mechanical reliability and service life of the components. Scientific structural optimization ensures continuous contact between the frame and the sealant or adhesive strips of the back panel or glass, reducing the risk of moisture intrusion and mitigating PID degradation.
[0053] The optimized structure is suitable for a variety of support systems, improving installation flexibility and stability, and ensuring the adaptability of components in different application scenarios.
[0054] In some embodiments, multi-objective optimization plays a crucial role in the photovoltaic module outer frame optimization method. Its main functions are as follows: Balancing multiple design goals: The design of photovoltaic module frames needs to simultaneously satisfy several conflicting objectives, such as improving structural strength, reducing material usage, and increasing power generation efficiency. Multi-objective optimization can find a compromise solution among these objectives, ensuring the comprehensiveness and practicality of the design.
[0055] Improving design efficiency: Traditional design methods often require repeated trials and adjustments, which is time-consuming. In contrast, multi-objective optimization, through systematic algorithms, can find the optimal solution in a shorter time, significantly improving design efficiency.
[0056] Ensuring design feasibility: Multi-objective optimization not only pursues performance improvement but also must ensure the feasibility of the design in actual manufacturing and application. By setting reasonable constraints, the optimization process can generate design solutions that conform to production processes and usage environments.
[0057] In multi-objective optimization, the selection of design variables and objective functions directly affects the validity and rationality of the optimization results. Design variables include the thickness of the bounding box. The thickness adjustment directly affects the structural strength and material usage; the width Changes in width will affect the bending and torsional resistance of the frame; the area of the hollowed-out region The size of the hollowed-out area directly affects material savings and the obstruction of the battery cells.
[0058] The objective function includes structural strength, material usage, and power generation efficiency. The minimum material usage required to meet the strength and sealing requirements is calculated, and the optimized objective function is:
[0059] in, , , For reference only.
[0060] Structural strength constraints , The optimized maximum stress, This represents the allowable stress of the material.
[0061] Material usage constraints , To optimize material usage, This represents the maximum limit on the amount of material used.
[0062] Power generation efficiency constraints , To optimize power generation efficiency, This is the minimum requirement for power generation efficiency.
[0063] Iterative optimization is the core process of multi-objective optimization. It involves progressively adjusting design variables to optimize the objective function while simultaneously satisfying all constraints. The specific steps are as follows: Initialization: Set initial design variables, define objective functions and constraints.
[0064] Evaluation: Calculate whether the objective function values and constraints of the current design variables are satisfied.
[0065] Optimization: Based on the evaluation results, adjust the design variables and generate new design schemes.
[0066] Termination condition: The optimization process terminates when the objective function value reaches the predetermined optimization target or when the maximum number of iterations is reached.
[0067] By combining multi-objective optimization with minimum material usage calculation, the photovoltaic module outer frame optimization method of this invention significantly reduces manufacturing costs by minimizing material usage. According to the optimization results, material utilization is improved. 15%, manufacturing costs reduced 10%. The optimized frame, while retaining key support areas, improves bending and torsional strength, thereby enhancing structural strength. 20%. By removing the obstruction from the non-bolted connection parts on the back, the light-receiving area of the solar cells was increased, thus improving power generation efficiency. 0.5%.
[0068] In some embodiments, the multi-objective optimization algorithm employs a genetic algorithm, and the design variables include the thickness of the bounding box. ,width and chamfer angle The optimization objective is:
[0069] in, , , For reference only; The iterative formula is:
[0070] in, For the first Design variables for each iteration Step size factor The gradient of the objective function.
[0071] The design of the outer frame of photovoltaic modules needs to simultaneously meet multiple objectives, such as structural strength, material utilization, and power generation efficiency, which may conflict with each other. Genetic algorithms can effectively find a compromise solution among these objectives, ensuring the comprehensiveness and practicality of the design.
[0072] Traditional optimization methods may require repeated trials and adjustments, which is time-consuming. In contrast, genetic algorithms, through a systematic search strategy, can find the optimal solution in a shorter time, significantly improving optimization efficiency.
[0073] In some embodiments, batch trial production includes verifying the impact of production process parameters on frame performance, optimizing manufacturing equipment and tooling, and verifying the applicability of the optimized frame to different types of battery cells.
[0074] By verifying the impact of different manufacturing process parameters (such as temperature, pressure, and cooling time) on frame performance, optimal process conditions can be found to ensure stable performance of frames produced in each batch. Optimizing manufacturing process parameters can reduce waste and rework during production, improving production efficiency. Through systematic testing and analysis, process parameters that may lead to quality problems can be identified, thereby avoiding fluctuations in these parameters during production.
[0075] Optimizing the performance parameters of manufacturing equipment (such as processing speed and precision) can improve production efficiency and meet the needs of large-scale production. Optimizing tooling design can improve the manufacturing precision of the frame, ensuring a good fit between the frame and other components of the photovoltaic module (such as the backsheet and glass). Optimized manufacturing equipment and tooling design can reduce equipment wear and failure rates, and lower maintenance costs.
[0076] By validating the applicability of the optimized frame to different types of solar cells, the versatility and flexibility of the frame design can be ensured, meeting diverse market demands. The optimized frame can adapt to different types of solar cells (such as monocrystalline silicon, polycrystalline silicon, and thin-film cells), improving the product's market adaptability. Validating the frame's applicability to different solar cells ensures module performance and reliability, enhancing user satisfaction.
[0077] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.
[0078] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.
[0079] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection, an electrical connection, or a connection that allows communication between them; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.
[0080] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "over," and "on top" of the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.
[0081] In this invention, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.
[0082] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.
Claims
1. A method for optimizing the outer frame of a photovoltaic module, characterized in that, include: Analyze the usage environment, load conditions and user needs of photovoltaic modules, obtain the target values for each operating condition, and collect data on the material properties, manufacturing process parameters and environmental conditions of photovoltaic modules. Based on the collected data, combined with the preset geometric information and boundary physical parameters, an initial design model is generated, and the material properties, load conditions and boundary constraints of the model are determined. The stress distribution of the frame is analyzed by finite element analysis to determine the high stress area and low stress area of the frame. Based on the stress distribution results, the areas that can be hollowed out and chamfered are determined. The bolt connection area and key support structure are retained. The shape optimization design of the areas that can be hollowed out and chamfered is carried out. Define the optimization problem, including design variables, objective function and constraints, and calculate the minimum material usage to meet the strength and sealing requirements through iterative optimization. Size optimization and performance verification; Establish finite element models with different combinations, conduct static and dynamic performance simulations, fabricate process samples, and conduct physical experiments to verify the design performance. Based on simulation and experimental results, production process parameters were optimized, batch trial production was carried out, and variable factors in batch production were verified.
2. The method for optimizing the outer frame of a photovoltaic module according to claim 1, characterized in that, The high-stress and low-stress regions of the frame were determined using finite element analysis. The complete structure of the high-stress regions was preserved, while the low-stress regions were either hollowed out or chamfered. The area of the hollowed-out regions was determined. Satisfying the formula: in, This represents the total area of the back of the border. The area of the reserved bolted connection area; chamfer angle Satisfying the formula: in, The height of the chamfer. This is the width of the chamfer.
3. The method for optimizing the outer frame of a photovoltaic module according to claim 1, characterized in that, Define the optimization problem, and design variables include the thickness of the border. ,width and the area of the hollowed-out area The objective function includes structural strength, material usage, and power generation efficiency. The minimum material usage required to meet the strength and sealing requirements is calculated, and the optimized objective function is: in, , , For reference values, structural strength constraints Material usage constraints Power generation efficiency constraints .
4. The method for optimizing the outer frame of a photovoltaic module according to claim 1, characterized in that, The multi-objective optimization algorithm uses a genetic algorithm, and the design variables include the thickness of the border. ,width and chamfer angle The optimization objective is: in, , , For reference only; The iterative formula is: in, For the first Design variables for each iteration Step size factor The gradient of the objective function.
5. The method for optimizing the outer frame of a photovoltaic module according to claim 1, characterized in that, Size optimization includes: Based on the optimized structure, an approximate parameterized model is established. Initial performance analysis was performed using finite element analysis software, defining the response, constraints, and optimization objectives. Iteratively update the design variables to obtain the target topology optimization structure that meets the target value; The optimized structure was subjected to a sealing test.
6. The method for optimizing the outer frame of a photovoltaic module according to claim 5, characterized in that, The physical experiments include: Verify the deformation and failure modes of the frame under rated load; Evaluate the fatigue performance of the frame under wind-induced vibration conditions; Test the performance stability of the frame under different environmental conditions; Verify that the continuous contact surface of the sealant or adhesive strip between the frame and the back panel / glass meets the waterproof requirements.
7. The method for optimizing the outer frame of a photovoltaic module according to claim 1, characterized in that, Batch trial production includes verifying the impact of production process parameters on frame performance, optimizing manufacturing equipment and tooling, and verifying the applicability of the optimized frame on different types of solar cells.