Production process optimization method and system for photovoltaic module

Abstract

The invention discloses a production process optimization method and system for a photovoltaic module, and relates to the technical field of photovoltaic production. The method comprises the steps that front welding is conducted on a target photovoltaic module, heat distribution of a welding head and a welding seam area is monitored through an infrared thermal image, and welding seam peak temperature distribution is obtained through analysis; carrying out weldability identification on the plurality of welding tail ends after front welding according to a preset index to obtain tail end weldability distribution; on the basis of weld peak temperature distribution and tail end weldability distribution, positioning compensation and secondary backflow heat curve linkage matching are conducted on back face tandem connection, and a back face tandem connection process optimization scheme is formed; according to the scheme, back tandem connection is completed. The technical problems of unstable back tandem connection quality and electrical property loss caused by mismatching of front welding and back tandem connection process parameters are solved, and the technical effects that accurate positioning and thermal process matching of back tandem connection are achieved through data linkage of welding heat distribution and tail end weldability, and the tandem connection quality and the assembly yield are improved are achieved.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic production technology, and more specifically to a method and system for optimizing the production process of photovoltaic modules. Background Technology

[0002] With the rapid development of the photovoltaic power generation industry, the production efficiency and welding quality of photovoltaic modules have become key factors affecting module performance and lifespan. The traditional photovoltaic module production process typically includes front-side welding of cells, inspection, back-side stringing, and final inspection. The front-side welding process is responsible for establishing a conductive connection between the solder strips and the main busbars of the cells, while the back-side stringing process connects several cells in series using solder strips to form a module. There is a significant process correlation between the two processes, particularly in terms of welding temperature, solderability, alignment accuracy, and mechanical stress transfer.

[0003] In existing technologies, front-side welding process parameters, such as welding head temperature, moving speed, and pressure, are typically set empirically, lacking real-time monitoring and data feedback on welding heat distribution. This leads to uneven weld temperature and significant differences in weld strength. This not only affects the solderability of the solar cells and the positioning accuracy during back-side serialization but also easily causes defects such as incomplete welds, broken strips, and microcracks, reducing the electrical performance and reliability of the modules. Furthermore, the front-side welding and back-side serialization processes are often operated independently in existing production lines, lacking effective data linkage and process compensation mechanisms. This prevents dynamic optimization of the back-side serialization parameters based on the front-side welding status, making it difficult to guarantee serialization quality. Summary of the Invention

[0004] This application provides a method and system for optimizing the production process of photovoltaic modules, which solves the technical problem of unstable back-end connection quality and electrical performance loss caused by the mismatch between the front welding and back-end connection process parameters.

[0005] A first aspect of this application provides a method for optimizing the manufacturing process of photovoltaic modules, the method comprising: The target photovoltaic module is front-side welded, and the heat distribution of the weld head and weld seam area is monitored using infrared thermography. After analysis, the peak temperature distribution of the weld seam is obtained. The weldability of multiple weld tail ends after front-side welding is identified according to preset tail end indicators, and the weldability distribution of the weld tail ends is obtained. Based on the peak temperature distribution of the weld seam and the weldability distribution of the weld tail ends, the back-side series connection of the target photovoltaic module is positioned and compensated, and the secondary reflow thermal curve is linked and matched to obtain a back-side series connection process optimization scheme. The target photovoltaic module is then back-side series-connected according to the back-side series connection process optimization scheme.

[0006] A second aspect of this application provides a manufacturing process optimization system for photovoltaic modules, the system comprising: Temperature monitoring module: Performs front-side welding on the target photovoltaic module and uses infrared thermography to monitor the heat distribution of the welding head and weld seam in the welding area, and obtains the peak temperature distribution of the weld seam after analysis; Solderability identification module: Identifies the solderability of multiple weld tail ends after front-side welding according to preset tail end indicators, and obtains the solderability distribution of the weld tail ends; Process scheme acquisition module: Based on the peak temperature distribution of the weld seam and the solderability distribution of the weld tail ends, performs positioning compensation and secondary reflow thermal curve linkage matching for the back-side serial connection of the target photovoltaic module, and obtains the back-side serial connection process optimization scheme; Back-side serial connection module: Performs back-side serial connection of the target photovoltaic module according to the back-side serial connection process optimization scheme.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: First, the target photovoltaic module is welded on the front side, and the temperature distribution of the welding area is monitored in real time using infrared thermography to obtain the peak temperature distribution characteristics of the weld. Then, multiple weld ends after the front welding are completed are inspected, and their solderability is identified and evaluated based on preset end shapes and geometric parameters to obtain the solderability distribution. Next, the weld temperature distribution and solderability distribution are comprehensively analyzed, and positioning compensation and secondary reflow thermal profile matching are implemented for the back-side serial connection process to generate an optimized back-side serial connection process scheme. Finally, the back-side serial connection operation is performed according to the optimized scheme, achieving parameter linkage between the front and back processes and an overall improvement in welding quality. Attached Figure Description

[0008] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0009] Figure 1 This is a schematic diagram of a method for optimizing the production process of photovoltaic modules provided in an embodiment of this application.

[0010] Figure 2 This is a schematic diagram of the system structure for optimizing the production process of photovoltaic modules provided in an embodiment of this application.

[0011] Explanation of reference numerals in the attached diagram: Temperature monitoring module 11, Solderability identification module 12, Process scheme acquisition module 13, Backside serial connection module 14. Detailed Implementation

[0012] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0013] Example 1, as Figure 1 As shown, this application provides a method for optimizing the manufacturing process of photovoltaic modules, the method including: The target photovoltaic module is welded on the front side, and the heat distribution of the weld head and weld seam area in the welding area is monitored by infrared thermography. The peak temperature distribution of the weld seam is obtained after analysis.

[0014] In this embodiment, the target photovoltaic module to be welded is first placed on a positioning adsorption platform to ensure the cells remain flat and stable during welding. Then, an infrared thermal imaging system is activated to calibrate the background thermal field of the welding area to eliminate ambient temperature interference. Next, process parameters such as the welding head's operating temperature, welding pressure, and moving speed are set, and the welding head is controlled to move along the main busbar direction of the cell, welding the solder strip to the main busbar under constant pressure. Afterward, the infrared thermal imaging system controls an infrared thermal camera installed above the welding area to collect real-time thermal radiation information of the welding head and weld area, marking the welding head position code information in each frame to generate a temperature-calibrated thermal image frame sequence. Finally, thermal distribution analysis is performed on this thermal image frame sequence to obtain the weld peak temperature distribution, reflecting the uniformity of heat input and local overheating at different locations during welding, providing a basis for subsequent judgment of the weld formation quality and the thermal matching of the back-side connection.

[0015] Furthermore, the target photovoltaic module is front-side welded, and infrared thermography is used to monitor the heat distribution of the weld head and weld seam in the welding area. After analysis, the peak temperature distribution of the weld seam is obtained, including: The target photovoltaic module's solar cell to be welded is placed on a positioning and adsorption platform, and the infrared thermal imaging system is activated for background stabilization calibration. A welding start command is obtained, and the welding head moves along the main grid line of the solar cell to be welded while applying constant pressure. Frontal welding is performed according to a preset welding head temperature and preset moving speed. During frontal welding, the infrared thermal imaging system synchronously acquires thermal images of the welding head and weld seam areas, obtaining a thermal image frame sequence. Each thermal image frame includes welding head position encoding information. Thermal distribution analysis is performed on the thermal image frame sequence to obtain the weld seam peak temperature distribution.

[0016] Preferably, the target photovoltaic module's cells to be welded are first accurately placed on a positioning adsorption platform. Vacuum adsorption ensures the cells remain stable, flat, and warp-free during welding. Then, the infrared thermal imaging system is activated to calibrate the background thermal field of the welding environment. Specifically, the infrared thermal camera is fixed approximately 200mm directly above the welding area, ensuring the lens is vertically aligned with the welding head and the center of the weld seam. The infrared thermal camera and acquisition system are then activated and run continuously for 2-3 minutes in a static state to allow the detector temperature to reach thermal equilibrium, effectively reducing initial thermal drift and improving the stability of subsequent temperature measurements. After calibration and receiving the welding start command, the welding head begins to move along the main grid lines of the cell, applying constant pressure while simultaneously performing front-side welding according to the preset temperature and moving speed, ensuring a thorough thermal fusion bond between the weld strip and the main grid lines. Because of the difference in heat conduction loss and material heat reflection between the set temperature of the welding head and the actual temperature of the welding contact area, infrared thermography is needed to obtain the true temperature distribution of the weld during the welding process. This involves using an infrared thermal imaging system to control an infrared thermal imaging camera at a fixed frame rate, such as 50 frames per second, to simultaneously acquire thermal image frames of the welding head and weld area. Each frame records the current position encoding information of the welding head for subsequent temperature and position correspondence analysis. Typically, the infrared thermal imaging band is set to 8–14 μm, and the emissivity parameter is set according to the material surface characteristics, such as 0.92 for silver paste and 0.80 for solder strip, to ensure temperature measurement accuracy. Then, a preset temperature calibration coefficient table is used to convert the acquired thermal image frame sequence to obtain a calibrated thermal image frame sequence. The effective pixel range of the weld area is then identified, and the highest temperature point in each frame is extracted. Combined with the welding head position encoding, this forms the weld peak temperature distribution. This weld peak temperature distribution not only reflects the actual heat input during the welding process but also provides a crucial basis for heat matching in subsequent back-side tandem processes. By understanding the heat distribution characteristics during front welding, the secondary reflow thermal profile can be optimized during back-side tandem welding, thereby avoiding thermal stress accumulation and improving welding reliability and electrical performance consistency.

[0017] Furthermore, thermal distribution analysis is performed on the thermal image frame sequence to obtain the peak temperature distribution of the weld, including: According to the preset temperature calibration coefficient table, the thermal image frame sequence is converted into temperature values ​​to obtain a calibrated thermal image frame sequence; the weld position is detected by traversing the calibrated thermal image frame sequence to obtain a weld position set sequence; the weld peak temperature is analyzed based on the weld position set sequence and the calibrated thermal image frame sequence to obtain the weld peak temperature distribution.

[0018] Preferably, to accurately obtain the actual temperature distribution of the welding area, the acquired thermal image frame sequence is first converted to temperature values ​​according to a preset temperature calibration coefficient table. This temperature calibration coefficient table is obtained by calibration using a standard blackbody radiation source, and the linear mapping relationship between pixel grayscale values ​​and actual temperatures is determined through the grayscale response relationship at different temperature points. For each pixel (c,y) in the thermal image frame, according to the formula: T(c,y)=a×G(c,y)+b, the original grayscale thermal image data can be converted into a calibrated thermal image frame sequence reflecting the true heat distribution, where T(c,y) is the actual temperature value corresponding to the pixel; G(c,y) is the grayscale value of the corresponding pixel in the infrared image; and a and b are linear calibration coefficients obtained through blackbody calibration experiments. Subsequently, the calibrated thermal image frame sequence is traversed and analyzed. For each traversed thermal image frame, the frame is bound to the corresponding weld head position code, forming a time-location synchronization data pair. Then, the weld head position codes belonging to the same thermal image frame are stored in a set, forming a weld position set sequence. This weld position set sequence reflects the spatial movement trajectory and morphological changes of the weld in different time frames. Next, based on the weld position set sequence and the calibrated thermal image frame sequence, the weld peak temperature is analyzed. That is, the local highest temperature point is searched within each weld position region, and then the highest temperature points of the weld in all frames are summarized and spatially mapped to form a complete weld peak temperature distribution. This provides accurate data support for thermal profile matching and welding stress compensation in the subsequent back-side serial connection process, thereby achieving closed-loop optimization and traceable control of the photovoltaic module welding process.

[0019] Furthermore, based on the weld location set sequence and the calibrated thermal image frame sequence, the weld peak temperature is analyzed to obtain the weld peak temperature distribution, including: Based on the weld location set sequence, the effective peak temperature extraction region is identified in the calibration thermal image frame sequence to obtain an effective peak temperature extraction region set sequence; the effective peak temperature extraction region set sequence and the calibration thermal image frame sequence are combined to search for the highest temperature value in the region to determine the highest temperature value set sequence in the region; the highest temperature value set sequence in the region is classified with the same weld head based on the weld head position encoding information, and the maximum temperature value in the classification result is extracted to obtain the weld peak temperature distribution.

[0020] Optionally, based on the obtained weld location sequence, the effective temperature extraction region of the weld is first identified in each frame of the calibrated thermal image. During this process, by analyzing the temperature gradient change around the weld centerline, pixel areas with temperatures exceeding a set threshold, such as 70% of the average weld head temperature, are identified as effective peak temperature extraction regions. Frame-by-frame scanning then generates continuous region identification results, resulting in a sequence of effective peak temperature extraction regions. This sequence effectively eliminates non-welding areas and background thermal interference, ensuring the accuracy of subsequent temperature extraction. Subsequently, the effective peak temperature extraction region sequence is spatially mapped to the calibrated thermal image frame sequence. Within each identified effective region, the highest temperature point is searched using pixel traversal, and its pixel coordinates, frame number, and corresponding temperature value are recorded. By sequentially arranging the highest temperature points across all frames, a sequence of regional highest temperature values ​​is formed. This sequence fully reflects the temperature change trend and hotspot distribution characteristics of the weld along both temporal and spatial directions. Subsequently, combining the weld head position coding information recorded during the welding process, the sequence of highest temperature values ​​in the region is categorized by weld head. That is, based on the real-time position coding of the weld head, each highest temperature point is grouped according to its corresponding welding position, ensuring a one-to-one correspondence between the peak temperature data of each weld segment and the specific welding path. For each categorization result, the maximum temperature value is extracted, representing the true thermal peak response at that location when the weld formed. Finally, the maximum temperature values ​​corresponding to all weld heads are spatially sorted to obtain the weld peak temperature distribution. This provides a precise thermal data foundation for subsequent back-side cascade thermal curve linkage matching and process compensation, enabling intelligent optimization of the welding process and traceable quality control.

[0021] Weldability of multiple welded ends after front welding is identified according to preset end indicators to obtain the weldability distribution of welded ends.

[0022] In one embodiment, the target photovoltaic module with completed front-side welding is first transferred to an automated optical inspection station. An automated optical inspection system acquires images of each weld tail area. This system uses a linear or area array camera structure, coupled with a ring light source or side-lit light source to eliminate reflection interference and ensure clear visibility of the weld strip edge, tail shape, and weld point outline. After acquiring the weld tail images, feature recognition and solderability assessment are performed based on preset tail indicators. The solderability coefficient of each weld tail is calculated, and combined with the spatial coordinate information of each weld tail on the solar cell, a two-dimensional mapping of all tail solderability coefficients is performed to form a weld tail solderability distribution. This distribution visually displays the quality status of each weld tail and its distribution pattern within the module, improving the automation and accuracy of weld tail inspection and providing effective support for quality control and process optimization in the photovoltaic module welding process.

[0023] Furthermore, the weldability of multiple weld ends after front-side welding is identified according to preset end-end indicators to obtain the weldability distribution of the weld ends, including: An automatic optical inspection system is used to traverse the multiple welding tail ends to acquire high-definition images, thereby obtaining multiple welding tail end images. The weldability of the multiple welding tail end images is identified according to the preset tail end index, thereby obtaining multiple welding tail end weldability coefficients. Combined with the position of the multiple welding tail ends, the distribution of the multiple welding tail end weldability coefficients is identified to obtain the welding tail end weldability distribution.

[0024] Preferably, an automated optical inspection system is first used to acquire images of multiple weld tail ends in a traversal manner. This system employs deployed high-resolution cameras to capture high-definition images of the weld tail ends, including their overall shape, length, and position, forming multiple weld tail end images to provide basic data for subsequent weldability analysis. Subsequently, each weld tail end image is identified and analyzed according to preset tail end indicators. During this process, the Canny edge detection algorithm is used to detect the edges of the weld strip in the image, extracting the start and end points of the weld strip and calculating the length of the weld tail end. Morphological analysis methods, such as expansion and corrosion operations, are used to identify the actual position of the weld tail end and calculate the deviation between the weld tail end and the designed position. A straight-line fitting algorithm is used to detect the angle between the weld tail end and the main busbar of the solar cell. A plane fitting algorithm is used to measure the warpage of the weld tail end. Next, these extracted features are divided by their corresponding solderability standard values, and then all the calculated quotients are weighted and summed to obtain the solderability coefficient for each weld end. Each solderability coefficient is between 0 and 1, where 0 indicates that the weld end is not solderable, and 1 indicates that the weld end fully meets the predetermined standard. After obtaining the solderability coefficients for all weld ends, the solderability coefficient of each weld end is combined with its position on the solar cell, and the solderability coefficients are displayed using a two-dimensional coordinate system to form a weld end solderability distribution map. This weld end solderability distribution map can intuitively show the quality status of each weld end, thereby revealing potential welding quality problems in the entire photovoltaic module, such as excessive tail end deviation or excessive warpage, so that precise process compensation or optimization can be performed in the back-side series connection process.

[0025] Furthermore, the preset tail end indicators include tail length, position, included angle, and warp.

[0026] Optional, preset end-of-weld parameters are key parameters used to evaluate whether the weld end meets welding requirements. These include end-of-weld length, position, angle, and warpage. End-of-weld length refers to the length of the solder strip extending from the starting point of the main busbar to the end of the weld. An appropriate end-of-weld length ensures sufficient heat input margin during welding, preventing the solder joint from failing to completely cover the cell's busbars, thus affecting the reliability of the electrical connection. The position of the weld end reflects the deviation of the solder strip's end from the cell's designed position. Positional deviation may lead to misalignment during welding, thus affecting the welding effect and cell performance. The angle refers to the angle between the weld end and the main busbar. An appropriate angle helps the solder to be evenly distributed in the welding area, ensuring the stability of the weld contact point. Warpage refers to the degree of warping or bending of the weld end due to temperature gradients or other external forces. During welding, excessive warpage at the end can affect welding alignment accuracy and may even lead to poor contact between the solder strip and the cell.

[0027] Based on the peak temperature distribution of the weld and the weldability distribution at the weld tail, the back-side serial connection of the target photovoltaic module is positioned and compensated, and the secondary reflow thermal curve is matched to obtain an optimized back-side serial connection process.

[0028] In one embodiment, after obtaining the weld peak temperature distribution and the weld end weldability distribution, a dual-item superimposed process connection certification is performed based on these two distribution information. If the certification is successful, a secondary reflow thermal profile is matched based on the weld peak temperature distribution, and adaptive compensation is applied to the weld end weldability at different locations to ensure precise alignment between the solder strip and the preceding welding area. By combining positioning compensation with secondary reflow thermal profile matching, the system can optimize the back-side serial connection process, ensuring the stability of the welding area, the consistency of solder joints, and the reliability of electrical performance. Finally, the back-side serial connection process optimization scheme obtained based on the linkage optimization automatically adjusts the back-side serial connection process to its optimal state, achieving efficient production and high-quality output of photovoltaic modules.

[0029] Furthermore, based on the peak temperature distribution of the weld and the weldability distribution at the weld tail, positioning compensation and secondary reflow thermal curve linkage matching are performed on the back-side series connection of the target photovoltaic module to obtain an optimized back-side series connection process, including: The peak temperature distribution of the weld and the weldability distribution at the weld tail are subjected to dual-item superposition process connection certification. If the certification is successful, a secondary reflow thermal curve linkage matching is performed based on the peak temperature distribution of the weld to obtain a set of matched secondary reflow thermal curves. Position compensation is then performed based on the weldability distribution at the weld tail to obtain a position compensation distribution. The preset back-side serial connection process is optimized by combining the set of matched secondary reflow thermal curves and the position compensation distribution to obtain the optimized back-side serial connection process scheme. If the certification fails, an early warning information is obtained.

[0030] Preferably, the peak temperature distribution of the weld seam is first superimposed with the weldability distribution at the weld tail end. This is then verified through a connection certification process to ensure a reasonable spatial and temporal alignment between the weld temperature and the weldability at the weld tail end. During the certification process, the average temperature and temperature standard deviation are calculated based on the peak temperature distribution of the weld seam. When the average temperature is within the standard temperature range and the temperature standard deviation is less than the standard deviation threshold, it indicates that the temperature is uniformly distributed within the standard range, and the first layer of certification is passed. Next, the number of weld ends with weldability coefficients below the threshold is counted based on the weldability distribution at the weld tail end. When the number of weld ends is less than the threshold number, it indicates that the defective weld points have not exceeded the allowable deviation, and the dual-item superimposed process connection certification is passed. Conversely, if any standard is not met, such as excessively low overall temperature, extremely poor uniformity, or too many defective weld points, the dual-item superimposed process connection certification fails. The system will trigger an early warning message, directly generating a warning message containing the specific non-compliance item, and notifying the operator to intervene or redirect the process to the maintenance station. For certified welds, a secondary reflow thermal profile is used for matching based on the weld peak temperature distribution, the material's allowable heat input threshold, and the standard reflow thermal profile. This determines a suitable set of secondary reflow thermal profiles, ensuring more uniform and stable heat input in the welding area during back-side tandem welding. Then, based on the weldability distribution at the weld tail, compensation rules are matched for each location. For weldability coefficients within the excellent range (e.g., [0.9, 1.0]), no compensation adjustment is needed. For weldability coefficients within the good range (e.g., [0.7, 0.9]), XY fine-tuning is performed. This involves subtracting the weldability coefficient from 1, and then multiplying this difference by the X fine-tuning standard value (e.g., 0.1 mm) and the Y fine-tuning standard value (e.g., 0.05 mm) to obtain the compensation amounts for X and Y. For weldability coefficients within the middle range (e.g., [0.5, 0.7)), Z-θ three-dimensional compensation is performed. This involves subtracting the weldability coefficient from 0.7, and then multiplying this difference by the standard angle adjustment value (e.g., 3°) and the standard Z adjustment value (e.g., 0.1 mm) to obtain the compensation amounts for θ and Z. For weldability coefficients within the poor range (e.g., [0, 0.5)), there are usually irreparable defects that cannot be repaired through compensation. Forced welding will inevitably result in a weak weld and must be skipped and handled by subsequent processes. After positioning compensation, a positioning compensation distribution is obtained. This distribution shows the weldability status and location of the compensated weld tail, helping to understand which areas have been improved and which areas still have potential problems. Then, based on the obtained set of matching secondary reflow thermal curves and positioning compensation distribution, the preset back-side tandem process is optimized and analyzed by the process optimization analyzer to obtain the final back-side tandem process optimization scheme. This back-side tandem process optimization scheme can achieve precise welding position adjustment and heat input control, ensure the precise connection between the welding head and the welding tail during back-side tandem, and improve the electrical performance and mechanical strength of the welding point.

[0031] Furthermore, based on the weld peak temperature distribution, a secondary reflow thermal profile is matched to obtain a set of matched secondary reflow thermal profiles, including: Based on the material information of the solar cells to be welded, the allowable heat input threshold of the material is determined; a standard reflow thermal profile for the back-side connection is obtained, wherein the standard reflow thermal profile includes the predicted zone temperature and time, the peak temperature and time of the heating zone, and the cooling zone temperature; a heat input margin analysis is performed based on the weld peak temperature distribution and the allowable heat input threshold of the material to obtain a heat input margin distribution; the standard reflow thermal profile is mapped based on the heat input margin distribution to obtain a set of matching secondary reflow thermal profiles.

[0032] Optionally, based on the material information of the cells to be welded, such as material type and thermal conductivity, the allowable heat input threshold for the material is matched from the cell information database. This allowable heat input threshold is typically the total energy of the front welding heat input and the back series connection heat input. Then, the standard reflow thermal profile for the back series connection station is called. This standard reflow thermal profile is set according to actual process experience and standard requirements, including the preheating zone temperature, the peak temperature of the heating zone, and the cooling zone temperature. The preheating zone temperature range is 150-180°C, and the time is 3-6 seconds. The purpose of the preheating zone is to preheat the welding area to avoid cold welding and to facilitate uniform solder flow. The peak temperature of the heating zone is between 260-300°C, and the time is 1-3 seconds. The heating zone is used to bring the welding to the optimal temperature, ensuring full fusion of the welded parts. The cooling zone temperature is below 100°C. The purpose of the cooling zone is to ensure rapid cooling of the welding area, forming a stable weld joint, while avoiding excessive thermal stress. Next, by integrating the temperature at each location in the weld peak temperature distribution, the actual heat input value absorbed at each location during the front welding process is calculated, forming an actual front heat input distribution. Then, the material's allowable heat input threshold is used to subtract the actual heat input value at each location from the actual front heat input distribution to obtain the heat input margin at each location, thus forming a heat input margin distribution. When the heat input margin is greater than 0, it indicates that there is still heat input margin at that location, which can be used for back-side welding. Conversely, it indicates that the front heat input has reached or exceeded the total budget, and back-side welding requires extra caution, necessitating a reduction in heat input. Then, based on the obtained heat input margin distribution, the standard reflow thermal profile is matched and adjusted. Specifically, the temperature matching adjustment coefficient and time matching adjustment coefficient, set based on empirical values, are obtained. Then, the product of the temperature matching adjustment coefficient and the heat input margin is subtracted from the peak temperature in the heating zone to map the heat input margin back to the temperature dimension. Finally, the product of the time corresponding to the peak temperature in the heating zone and the time matching adjustment coefficient mapped back to the temperature dimension is added to map the heat input margin back to the time dimension. Next, the solder joints on the photovoltaic modules are divided into strings. Since the solder joints within the same string have similar manufacturing processes, the peak temperature and heating time of the heating zone after adjusting the position of all solder joints within the same string are averaged to obtain the peak temperature and matching heating time of the matching heating zone for that string. Then, using the peak temperature and matching heating time of the matching heating zone for each string, combined with parameters such as the unadjusted preheating zone temperature, preheating time, and cooling zone temperature, a new secondary reflow thermal profile data package is formed. This data package records in detail the temperature-time parameters of each stage in the back-side string connection process for each string. Finally, the secondary reflow thermal profile data packages corresponding to all strings are integrated to form a matching secondary reflow thermal profile set. Each curve in this set has been optimized and adjusted according to the actual situation of different strings of photovoltaic modules, which can better adapt to the heat input requirements in actual production and improve the quality and reliability of back-side string connection.

[0033] Furthermore, by combining the set of matching secondary reflux thermal profiles and the positioning compensation distribution to optimize the preset back-side serial connection process, an optimized back-side serial connection process scheme is obtained, including: A process optimization analyzer is obtained, wherein the process optimization analyzer is obtained after training a framework based on a feedforward neural network; the process optimization analyzer is used to analyze the preset back-side serial connection process using the matching secondary reflux thermal curve set and the positioning compensation distribution to obtain the optimization scheme for the back-side serial connection process.

[0034] Optionally, when optimizing the back-side tandem bonding process, a process optimization analyzer is first constructed. This analyzer is trained based on a feedforward neural network architecture. The training data used includes historical matching secondary reflow thermal profiles, historical positioning distributions, preset back-side tandem bonding processes, and historical back-side tandem bonding process schemes. The training steps involved include forward propagation, loss calculation, backpropagation, and parameter optimization. Subsequently, the obtained set of matching secondary reflow thermal profiles and positioning compensation distributions are input into this process optimization analyzer. This analyzer combines the received matching secondary reflow thermal profiles and positioning information with the internally preset back-side tandem bonding process. Based on the rules learned during training, it identifies the optimal matching relationship between each welding area and the welding tail, evaluates the impact of different welding parameters, and automatically generates the optimal back-side tandem bonding process optimization scheme. This optimization scheme includes parameters such as welding head position, heat input, cooling rate, welding sequence, and solder strip tension to ensure the quality and reliability of each weld point and improve overall production efficiency.

[0035] The target photovoltaic module is connected in series on the back side according to the optimized back-side connection process scheme.

[0036] In one embodiment, after obtaining the optimized back-side serial connection process plan, the welding equipment is automatically adjusted according to this plan, including parameters such as the position of the welding head, welding temperature, pressure, and moving speed, to ensure that the welding process can respond to process requirements in real time. During the back-side serial connection process, the system ensures uniform heat input in the welding area by controlling the temperature during the heating, holding, and cooling stages in real time, ensuring that the quality of each weld point meets the requirements, and adjusting and optimizing process parameters in real time when any abnormalities occur. The back-side serial connection process ends when all weld points are completed. Through this efficient and precise welding process, the photovoltaic modules ensure stable connections between cells, exhibiting high electrical performance and mechanical strength.

[0037] In summary, the embodiments of this application have at least the following technical effects: First, the target photovoltaic module is front-side welded, and the heat distribution of the weld head and weld seam area is monitored using infrared thermography. The peak temperature distribution of the weld seam is then obtained after analysis. Next, the solderability of multiple weld ends after front-side welding is identified according to preset end-end indicators, obtaining the solderability distribution of the weld ends. Then, based on the weld seam peak temperature distribution and the weld end solderability distribution, positioning compensation and secondary reflow thermal curve linkage matching are performed on the back-side series connection of the target photovoltaic module to obtain an optimized back-side series connection process scheme. Finally, the target photovoltaic module is back-side series-connected according to the optimized back-side series connection process scheme. This solves the technical problem of unstable back-side series connection quality and electrical performance loss caused by the mismatch between front-side welding and back-side series connection process parameters. It achieves the technical effect of precise positioning and thermal process matching of back-side series connection through data linkage between welding heat distribution and end-end solderability, thereby improving series connection quality and module yield.

[0038] Example 2, based on the same inventive concept as the photovoltaic module manufacturing process optimization method in the foregoing examples, such as... Figure 2 As shown, this application provides a manufacturing process optimization system for photovoltaic modules, the system comprising: Temperature monitoring module 11: Performs front-side welding on the target photovoltaic module and uses infrared thermography to monitor the heat distribution of the welding head and weld seam in the welding area, and obtains the peak temperature distribution of the weld seam after analysis; Solderability identification module 12: Identifies the solderability of multiple welding tail ends after front-side welding according to preset tail end indicators, and obtains the solderability distribution of the welding tail ends; Process scheme acquisition module 13: Based on the peak temperature distribution of the weld seam and the solderability distribution of the welding tail ends, performs positioning compensation and secondary reflow thermal curve linkage matching for the back-side serial connection of the target photovoltaic module, and obtains the back-side serial connection process optimization scheme; Back-side serial connection module 14: Performs back-side serial connection on the target photovoltaic module according to the back-side serial connection process optimization scheme.

[0039] Furthermore, the temperature monitoring module 11 is used to perform the following methods: The target photovoltaic module's solar cell to be welded is placed on a positioning and adsorption platform, and the infrared thermal imaging system is activated for background stabilization calibration. A welding start command is obtained, and the welding head moves along the main grid line of the solar cell to be welded while applying constant pressure. Frontal welding is performed according to a preset welding head temperature and preset moving speed. During frontal welding, the infrared thermal imaging system synchronously acquires thermal images of the welding head and weld seam areas, obtaining a thermal image frame sequence. Each thermal image frame includes welding head position encoding information. Thermal distribution analysis is performed on the thermal image frame sequence to obtain the weld seam peak temperature distribution.

[0040] Furthermore, the temperature monitoring module 11 is used to perform the following methods: The target photovoltaic module's solar cell to be welded is placed on a positioning and adsorption platform, and the infrared thermal imaging system is activated for background stabilization calibration. A welding start command is obtained, and the welding head moves along the main grid line of the solar cell to be welded while applying constant pressure. Frontal welding is performed according to a preset welding head temperature and preset moving speed. During frontal welding, the infrared thermal imaging system synchronously acquires thermal images of the welding head and weld seam areas, obtaining a thermal image frame sequence. Each thermal image frame includes welding head position encoding information. Thermal distribution analysis is performed on the thermal image frame sequence to obtain the weld seam peak temperature distribution.

[0041] Furthermore, the temperature monitoring module 11 is used to perform the following methods: Based on the weld location set sequence, the effective peak temperature extraction region is identified in the calibration thermal image frame sequence to obtain an effective peak temperature extraction region set sequence; the effective peak temperature extraction region set sequence and the calibration thermal image frame sequence are combined to search for the highest temperature value in the region to determine the highest temperature value set sequence in the region; the highest temperature value set sequence in the region is classified with the same weld head based on the weld head position encoding information, and the maximum temperature value in the classification result is extracted to obtain the weld peak temperature distribution.

[0042] Furthermore, the solderability identification module 12 is used to perform the following method: An automatic optical inspection system is used to traverse the multiple welding tail ends to acquire high-definition images, thereby obtaining multiple welding tail end images. The weldability of the multiple welding tail end images is identified according to the preset tail end index, thereby obtaining multiple welding tail end weldability coefficients. Combined with the position of the multiple welding tail ends, the distribution of the multiple welding tail end weldability coefficients is identified to obtain the welding tail end weldability distribution.

[0043] Furthermore, the solderability identification module 12 is used to perform the following method: The preset tail end parameters include tail length, position, included angle, and warp.

[0044] Furthermore, the process scheme acquisition module 13 is used to perform the following method: The peak temperature distribution of the weld and the weldability distribution at the weld tail are subjected to dual-item superposition process connection certification. If the certification is successful, a secondary reflow thermal curve linkage matching is performed based on the peak temperature distribution of the weld to obtain a set of matched secondary reflow thermal curves. Position compensation is then performed based on the weldability distribution at the weld tail to obtain a position compensation distribution. The preset back-side serial connection process is optimized by combining the set of matched secondary reflow thermal curves and the position compensation distribution to obtain the optimized back-side serial connection process scheme. If the certification fails, an early warning information is obtained.

[0045] Furthermore, the process scheme acquisition module 13 is used to perform the following method: Based on the material information of the solar cells to be welded, the allowable heat input threshold of the material is determined; a standard reflow thermal profile for the back-side connection is obtained, wherein the standard reflow thermal profile includes the predicted zone temperature and time, the peak temperature and time of the heating zone, and the cooling zone temperature; a heat input margin analysis is performed based on the weld peak temperature distribution and the allowable heat input threshold of the material to obtain a heat input margin distribution; the standard reflow thermal profile is mapped based on the heat input margin distribution to obtain a set of matching secondary reflow thermal profiles.

[0046] Furthermore, the process scheme acquisition module 13 is used to perform the following method: A process optimization analyzer is obtained, wherein the process optimization analyzer is obtained after training a framework based on a feedforward neural network; the process optimization analyzer is used to analyze the preset back-side serial connection process using the matching secondary reflux thermal curve set and the positioning compensation distribution to obtain the optimization scheme for the back-side serial connection process.

[0047] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for optimizing the manufacturing process of photovoltaic modules, characterized in that, The method includes: The target photovoltaic module is welded on the front side, and the heat distribution of the welding head and weld seam area in the welding area is monitored by infrared thermography. The peak temperature distribution of the weld seam is obtained after analysis. Weldability of multiple welded tail ends after front welding is identified according to preset tail end indicators to obtain the weldability distribution of welded tail ends. Based on the peak temperature distribution of the weld and the weldability distribution of the weld tail, the back-side serial connection of the target photovoltaic module is positioned and compensated and the secondary reflow thermal curve is matched to obtain an optimized back-side serial connection process. The target photovoltaic module is connected in series on the back side according to the optimized back-side connection process scheme.

2. The method for optimizing the production process of photovoltaic modules as described in claim 1, characterized in that, The target photovoltaic module is front-side welded, and the heat distribution of the weld head and weld seam area is monitored using infrared thermography. After analysis, the peak temperature distribution of the weld seam is obtained, including: Place the cells to be welded in the target photovoltaic module on the positioning and adsorption platform, and start the infrared thermal imaging acquisition system for background stabilization calibration. Upon receiving the welding start command, the welding head moves along the main grid line of the cell to be welded and applies constant pressure, performing front welding according to the preset welding head temperature and preset moving speed; During the front welding process, the infrared thermal imaging system synchronously acquires thermal images of the welding head and weld seam areas in the welding area to obtain a thermal image frame sequence, wherein each thermal image frame includes welding head position encoding information. Thermal distribution analysis is performed on the thermal image frame sequence to obtain the peak temperature distribution of the weld.

3. The method for optimizing the production process of photovoltaic modules as described in claim 2, characterized in that, Perform thermal distribution analysis on the thermal image frame sequence to obtain the peak temperature distribution of the weld, including: According to the preset temperature calibration coefficient table, the thermal image frame sequence is converted into temperature values ​​to obtain the calibrated thermal image frame sequence. The weld position is detected by traversing the calibrated thermal image frame sequence to obtain a set sequence of weld positions. Based on the weld location set sequence and the calibration thermal image frame sequence, the weld peak temperature is analyzed to obtain the weld peak temperature distribution.

4. The method for optimizing the production process of photovoltaic modules as described in claim 3, characterized in that, Based on the weld location set sequence and the calibrated thermal image frame sequence, the weld peak temperature is analyzed to obtain the weld peak temperature distribution, including: Based on the weld location set sequence, the effective peak temperature extraction region is identified in the calibrated thermal image frame sequence to obtain the effective peak temperature extraction region set sequence. By combining the effective peak temperature extraction region set sequence and the calibrated thermal image frame sequence, the highest temperature value is searched to determine the region's highest temperature value set sequence. The highest temperature value set sequence in the region is categorized by weld head based on the weld head position coding information, and the maximum temperature value in the categorization result is extracted to obtain the weld peak temperature distribution.

5. The method for optimizing the production process of photovoltaic modules as described in claim 1, characterized in that, Weldability identification of multiple weld ends after front welding is performed according to preset end indicators to obtain the weldability distribution of weld ends, including: An automated optical inspection system was used to traverse the multiple welding tail ends and acquire high-definition images, resulting in multiple images of the welding tail ends. Weldability identification is performed on the multiple welding tail images according to the preset tail index to obtain multiple welding tail weldability coefficients. By combining the positions of the multiple welding tail ends, the weldability coefficients of the multiple welding tail ends are distributed and identified to obtain the weldability distribution of the welding tail ends.

6. The method for optimizing the production process of photovoltaic modules as described in claim 5, characterized in that, The preset tail end parameters include tail length, position, included angle, and warp.

7. The method for optimizing the production process of photovoltaic modules as described in claim 1, characterized in that, Based on the peak temperature distribution of the weld and the weldability distribution at the weld tail, positioning compensation and secondary reflow thermal curve linkage matching are performed on the back-side series connection of the target photovoltaic module to obtain an optimized back-side series connection process, including: The peak temperature distribution of the weld and the weldability distribution at the weld tail are subjected to dual-item superposition process connection certification. If the certification is successful, a secondary reflow thermal curve linkage matching is performed based on the peak temperature distribution of the weld to obtain a set of matched secondary reflow thermal curves. Position compensation is performed based on the weldability distribution at the weld tail to obtain a position compensation distribution. The preset back-side serial connection process is optimized by combining the set of matched secondary reflow thermal curves and the position compensation distribution to obtain the optimized back-side serial connection process scheme. If authentication fails, a warning message will be generated.

8. The method for optimizing the production process of photovoltaic modules as described in claim 7, characterized in that, Based on the peak temperature distribution of the weld, a set of matched secondary reflow thermal profiles is obtained through linkage matching, including: Based on the material information of the battery cell to be welded, determine the allowable thermal input threshold of the material; Obtain the standard reflux thermal profile of the back-side connection, wherein the standard reflux thermal profile includes the predicted zone temperature and time, the peak temperature and time of the heating zone, and the cooling zone temperature; Based on the weld peak temperature distribution and the material's allowable heat input threshold, a heat input margin analysis is performed to obtain the heat input margin distribution; The standard reflux heat curve is mapped based on the heat input margin distribution to obtain a set of matching secondary reflux heat curves.

9. The method for optimizing the production process of photovoltaic modules as described in claim 7, characterized in that, The preset back-side serial connection process is optimized by combining the set of matching secondary reflux thermal profiles and the positioning compensation distribution to obtain the optimized back-side serial connection process scheme, including: A process optimization analyzer is obtained, wherein the process optimization analyzer is obtained by training a framework based on a feedforward neural network; The process optimization analyzer is used to analyze the set of matching secondary reflux thermal curves and the positioning compensation distribution to obtain the optimized scheme for the back-side serial connection process.

10. A system for optimizing the production process of photovoltaic modules, characterized in that, The system is used to implement the photovoltaic module manufacturing process optimization method according to any one of claims 1-9, the system comprising: Temperature monitoring module: Performs front welding on the target photovoltaic module and uses infrared thermography to monitor the heat distribution of the welding head and weld seam in the welding area, and obtains the peak temperature distribution of the weld seam after analysis; Solderability identification module: After welding the front side, the solderability of multiple weld ends is identified according to preset end indicators to obtain the solderability distribution of the weld ends; Process scheme acquisition module: Based on the peak temperature distribution of the weld and the weldability distribution of the weld tail, the back-side serial connection of the target photovoltaic module is positioned and compensated and the secondary reflow thermal curve is matched to obtain the optimized back-side serial connection process scheme. Back-side series connection module: The target photovoltaic module is connected in series on the back side according to the optimized back-side series connection process scheme.

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