Packaging method and system of power electronic component for automobile circuit board processing

Abstract

The invention discloses a packaging method and system of a power electronic component for automobile circuit board processing, and relates to the technical field of power electronic packaging, and the method comprises the steps: carrying out the preprocessing of an automobile circuit board, and generating the to-be-processed information of the automobile circuit board; the power electronic component is fixed to a preset position of the automobile circuit board to be electrically connected, and welding assembly parameters are obtained; encapsulating the power electronic component to generate an encapsulation component parameter; and performing a multi-dimensional packaging performance test based on the packaging component parameters, performing process backtracking according to a multi-dimensional test result, positioning target packaging process parameters for dynamic adjustment, and obtaining a packaging quality report of the power electronic component. The technical problems that a traditional packaging method does not adapt to the characteristics of an automobile circuit board carrier and the requirements of related components, control over all links is not accurate, and data acquisition is not comprehensive are solved, and the technical effects that packaging quality data are comprehensively acquired and accurately evaluated, and packaging reliability and quality control efficiency are improved are achieved.

Description

Technical Field

[0001] This invention relates to the field of power electronics packaging technology, and in particular to a packaging method and system for power electronic components used in automotive circuit board processing. Background Technology

[0002] The packaging quality of power electronic components on automotive circuit boards directly affects the reliability of automotive electronic systems and driving safety, making its precise control crucial. Existing technologies mostly employ conventional pre-processing, soldering, and encapsulation processes, playing a role in general electronic packaging. However, automotive circuit boards have unique surface conditions and demanding operating environments. Traditional processes lack precise control over each stage and comprehensive data collection, revealing limitations in application. Traditional methods cannot accurately adapt to the characteristics of automotive circuit boards and struggle to obtain critical data throughout the entire process, leading to unstable packaging quality and failing to meet the requirements for accurate assessment and effective control of power electronic component packaging quality in automotive scenarios. Summary of the Invention

[0003] This application provides a packaging method and system for power electronic components used in automotive circuit board processing, which solves the technical problems of traditional packaging methods not being adapted to the characteristics of automotive circuit board carriers and the requirements of related components, as well as inaccurate control of each link and incomplete data acquisition.

[0004] The first aspect of this application provides a packaging method for power electronic components used in automotive circuit board processing. The method includes: preprocessing the automotive circuit board to generate processing information for the automotive circuit board; fixing the power electronic components to predetermined positions on the automotive circuit board and electrically connecting them based on the processing information to obtain welding component parameters; encapsulating the power electronic components based on the welding component parameters to generate packaging component parameters; performing multi-dimensional packaging performance testing based on the packaging component parameters; performing process backtracking based on the multi-dimensional test results; dynamically adjusting the target packaging process parameters; and obtaining a packaging quality report for the power electronic components.

[0005] A second aspect of this application provides a packaging system for power electronic components used in automotive circuit board processing. The system includes: a processing information acquisition module for preprocessing the automotive circuit board to generate processing information; a welding component parameter acquisition module for fixing the power electronic components to predetermined positions on the automotive circuit board and electrically connecting them based on the processing information to obtain welding component parameters; a packaging component parameter acquisition module for encapsulating the power electronic components based on the welding component parameters to generate packaging component parameters; and a packaging quality report acquisition module for performing multi-dimensional packaging performance testing based on the packaging component parameters, performing process backtracking based on the multi-dimensional test results, dynamically adjusting the target packaging process parameters, and obtaining a packaging quality report for the power electronic components.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages: This application preprocesses automotive circuit boards, fixes and solders power electronic components, encapsulates the components and tests their packaging status, then conducts multi-dimensional performance testing and uses the test results to backtrack and adjust the process. By obtaining relevant data such as circuit board status, soldering quality, and packaging effect, it can accurately control the entire component packaging process, improve packaging reliability and consistency, meet the precise evaluation and control requirements of automotive circuit boards for the packaging quality of power electronic components, and achieve the technical effect of comprehensive acquisition and accurate evaluation of packaging quality data, thereby improving packaging reliability and quality control efficiency. Attached Figure Description

[0007] 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.

[0008] Figure 1 This is a schematic flowchart of the packaging method for power electronic components used in automotive circuit board processing provided in the embodiments of this application.

[0009] Figure 2 This is a schematic diagram of the packaging system for power electronic components used in automotive circuit board processing provided in this application embodiment.

[0010] Figure labeling: Module 1 for obtaining information to be processed, Module 2 for obtaining parameters of welding components, Module 3 for obtaining parameters of packaging components, and Module 4 for obtaining packaging quality report. Detailed Implementation

[0011] This application provides a packaging method and system for power electronic components used in automotive circuit board processing, which solves the technical problems of traditional packaging methods not being adapted to the characteristics of automotive circuit board carriers and the requirements of related components, as well as inaccurate control of each link and incomplete data acquisition.

[0012] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0013] It should be noted that the terms "first," "second," etc., in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to such processes, methods, products, or devices.

[0014] Example 1, as Figure 1 As shown, a packaging method for power electronic components used in automotive circuit board processing is provided, wherein the method includes: Preprocess the automotive circuit board to generate the information to be processed.

[0015] In this embodiment, the automotive circuit board is the core carrier of the automotive electronic system. It is mostly based on PCB (printed circuit board) and is used to carry and fix various electronic components. It also realizes the circuit connection between components through preset circuits, adapting to harsh operating conditions such as high temperature and vibration in automobiles.

[0016] Specifically, the process begins with surface cleaning of the automotive circuit board to obtain the cleaning results. Next, surface roughening is performed based on these results to obtain the roughened surface condition. Then, the surface state of the circuit board is scanned based on the roughened results to acquire multi-dimensional physical surface feature data. This data is then fused and analyzed to generate a processing identifier. Finally, this identifier is mapped and bound to the automotive circuit board to obtain the processing information for the automotive circuit board.

[0017] Based on the information to be processed, power electronic components are fixed to predetermined positions on the automotive circuit board and electrically connected to obtain welding component parameters.

[0018] In this embodiment, power electronic components are electronic devices used for power conversion and control. Common examples in automobiles include IGBTs, power MOSFETs, and rectifier bridges. These components perform functions such as power rectification, inversion, and voltage regulation, supporting the operation of key modules such as electric drive systems and vehicle power supplies. Electrical connections, achieved through methods such as soldering, plugging, and bonding, allow power electronic components to form a conductive path with the automotive circuit board or other components, ensuring stable current transmission. This is the fundamental connection method for realizing the electrical functions of components.

[0019] Optionally, the surface condition of the automotive circuit board is first analyzed based on the information to be processed, generating a surface condition map. Then, optical capture and positioning are performed by traversing the map to determine the coordinates of multiple reference points. Using these reference point coordinates as predetermined positions, the power electronic components are fixed in a simulation to generate a mounting path. Subsequently, the pick-and-place machine is controlled to pick up the components according to the mounting path, and the fixing process is monitored to obtain the mounting impact force. Finally, a safety judgment is made based on the mounting impact force, and the electrical connection between the components and the circuit board is established according to the judgment result, thereby constructing the soldering assembly parameters.

[0020] The power electronic components are encapsulated based on the welding component parameters to generate encapsulation component parameters.

[0021] In one embodiment of this application, three-dimensional analysis is first performed based on the welding component parameters to obtain three-dimensional topographic data. Then, the solder joints are identified using the three-dimensional topographic data to generate solder joint density data. Based on the solder joint density data, a dense analysis is performed on the automotive circuit board to delineate high-risk interference areas. Simultaneously, surface temperature data is combined to identify the welding heat distribution to generate residual stress concentration areas. Process simulation calculations are performed based on these two areas to construct the encapsulation material flow path. The encapsulation material is filled and distributed according to this path to construct the encapsulation protective layer parameters. Finally, non-destructive testing of the encapsulation quality is carried out based on the encapsulation protective layer parameters to construct the encapsulation component parameters.

[0022] Based on the parameters of the packaging components, multi-dimensional packaging performance testing is performed. Based on the multi-dimensional test results, process backtracking is performed to locate the target packaging process parameters for dynamic adjustment, and a packaging quality report of power electronic components is obtained.

[0023] Specifically, based on the parameters of the packaged components, electrical performance, thermal performance, mechanical performance, and environmental performance tests are performed on the power electronic component package to obtain the corresponding test results. These results are then integrated in multiple dimensions to obtain multi-dimensional test results.

[0024] Next, based on digital twin technology, process mapping analysis was performed on the four types of test results—electrical, thermal, mechanical, and environmental—to obtain the corresponding process mapping relationships. Then, process fluctuations were simulated based on these mapping relationships to generate process fluctuation simulation data. Based on this data, a retrospective impact analysis was performed on the multi-dimensional test results to derive the process influence coefficient. Subsequently, a power electronic component packaging process set was introduced, and the contribution degree was calculated by traversing the packaging process parameter set according to the process influence coefficient, resulting in multiple process contribution degrees. Finally, the packaging process parameter set was sorted in descending order of process contribution degree, and the first parameter was extracted as the target packaging process parameter.

[0025] Finally, based on the target packaging process parameters, three stages were defined: pretreatment, soldering, and encapsulation. Subsequently, for each stage, surface analysis was performed on the power electronic components in conjunction with the target packaging process parameters, generating data on surface roughness, peak soldering temperature, and material injection pressure. Then, based on these three types of data, the target packaging process was adjusted and analyzed, generating dynamic adjustment instructions. After executing the instructions to optimize the target packaging process parameters, the optimized parameters were used to verify the packaging quality. Finally, a packaging quality report for the power electronic components was constructed based on the verification results.

[0026] Furthermore, the method provided in this application embodiment includes: A surface cleaning process is performed on the automotive circuit board to obtain a cleaning result; a surface roughening process is performed on the automotive circuit board based on the cleaning result to obtain a roughening result; a surface state scan is performed on the automotive circuit board based on the roughening result to obtain multi-dimensional physical surface feature data; the multi-dimensional physical surface feature data is fused and analyzed to generate a processing identifier; the processing identifier is mapped to the automotive circuit board for identifier binding to obtain the processing information of the automotive circuit board.

[0027] Specifically, ultrasonic cleaning is first used to clean the surface of the automotive circuit board. An ultrasonic cleaner with a frequency of 40kHz is selected, and a 5% (w / w) cleaning solution is prepared by adding a neutral cleaning agent. The circuit board is immersed in the cleaning solution, and the cleaning temperature is controlled at 50℃ for 10 minutes. After cleaning, the circuit board is removed, rinsed with deionized water for 2 minutes to remove residual cleaning agent, and then placed in an 80℃ hot air dryer for 5 minutes to dry. Visual inspection confirms that there are no oil stains, dust or other contaminants on the surface of the circuit board, thus obtaining the cleaning result.

[0028] Next, based on the cleaning results, a chemical etching method was used to roughen the surface of the automotive circuit board. A 10% sulfuric acid etching solution was prepared, and the circuit board was completely immersed in the etching solution. The etching temperature was controlled at 45°C and the etching time was 3 minutes. During the etching process, the solution was stirred at a constant speed to ensure uniform etching. After etching, the circuit board was removed and rinsed with deionized water for 3 minutes to terminate the etching reaction. The surface roughness of the circuit board was measured using a surface roughness meter to ensure that the Ra value was within the range of 1.2-1.8 μm, thus obtaining the roughening treatment result.

[0029] Then, based on the roughening results, a laser scanning microscope was used to scan the surface condition of the automotive circuit board. The resolution of the laser scanning microscope was set to 500 nm and the scanning speed to 10 mm / s. The scanning range covered the entire effective area of ​​the circuit board. During the scanning process, multi-dimensional physical surface feature data such as surface roughness distribution, flatness deviation, micro scratches and dents were collected in real time. The collected data was stored in a computer database.

[0030] The collected data are then standardized to eliminate dimensional differences. Principal components are extracted by calculating the covariance matrix, and the top three principal components with a cumulative contribution rate of over 90% are selected as analysis indicators. The principal component indicators are compared with the preset circuit board processing qualification threshold. If all principal component indicators meet the threshold requirements, a processing identifier is generated to indicate that the circuit board can proceed to the next processing stage.

[0031] Finally, laser marking is used to map the markings to be processed onto the automotive circuit board for marking binding. A fiber laser marking machine is used to etch the markings to be processed into QR codes in the blank area without circuit wiring on the edge of the automotive circuit board according to the preset encoding rules. After marking is completed, a QR code scanner is used to read the QR code information on the circuit board and compare it with the markings to be processed stored in the computer. After confirming that the information is consistent, the binding is completed, and the automotive circuit board processing information containing circuit board processing adaptation parameters and marking information is obtained.

[0032] Furthermore, the method provided in this application embodiment includes: Based on the information to be processed, the surface state of the automotive circuit board is analyzed to obtain a surface state map; the surface state map is traversed for optical capture and positioning to determine the coordinates of multiple reference points; the coordinates of the multiple reference points are used as predetermined positions to perform fixed simulation of power electronic components and generate a mounting path; the placement machine is controlled to pick up power electronic components according to the mounting path to perform fixed monitoring of the automotive circuit board and obtain the mounting impact force; a safety judgment is made based on the mounting impact force, and electrical connections are made according to the safety judgment result to construct the welding component parameters.

[0033] Optionally, the circuit board size, surface roughness, and other data in the information to be processed are first imported into the control unit. The industrial camera is then controlled to take pictures of the circuit board surface from all angles to obtain multiple surface images. Next, the surface images are processed into grayscale, Gaussian filtering is used to eliminate noise, and threshold segmentation is used to distinguish between circuit areas and blank areas. Finally, the multiple processed images are stitched together to form a surface state map that reflects the circuit distribution and flatness of the circuit board surface.

[0034] Next, during optical capture and localization by traversing the surface state map, the Canny edge detection and feature point extraction method is employed. The surface state map is traversed line by line, with the Canny edge detection algorithm activated during the process: First, Gaussian filtering is applied to the surface state map, smoothing the pixel grayscale values ​​using a 5×5 Gaussian kernel to eliminate minor noise interference. Then, the gradient magnitude and direction of each pixel are calculated to determine the direction of potential edges. Subsequently, non-maximum suppression is performed, eliminating pixels with non-local maxima in the gradient direction to refine the edge contours. Finally, dual threshold detection is used, setting a high threshold and a low threshold to retain strong edges above the high threshold and weak edges connected to strong edges above the low threshold, thereby accurately identifying contour features such as circuit board edges and pad edges in the surface state map.

[0035] Subsequently, the center of the solder pad and the diagonal vertex of the circuit board were selected as candidate reference points from the aforementioned contour features. A sub-pixel positioning algorithm was used to calculate the coordinates of these candidate points: a quadratic polynomial interpolation method was employed to fit the grayscale values ​​of a 3×3 pixel region surrounding each candidate reference point, constructing a quadratic polynomial curve representing the grayscale value variation. By solving for the coordinates corresponding to the extreme points of the curve, sub-pixel coordinate values ​​with pixel-level precision were obtained, correcting the errors of traditional pixel positioning. Finally, the coordinates of four evenly distributed reference points were determined, with coordinate accuracy controlled within 0.01 mm.

[0036] Then, 2D CAD software is used for path planning. The coordinates of the aforementioned reference points are input into the CAD software, along with the package dimensions and pin spacing data of the power electronic components. A 3D model of the power electronic components is created in the CAD software, and the pin centers of the model are aligned with the reference point coordinates to simulate the fixed position of the power electronic components. Subsequently, those skilled in the art set parameters such as the placement machine's moving speed and turning radius in the software according to actual needs. The CAD software automatically calculates the moving trajectory based on the arrangement order of the power electronic components using a built-in path optimization algorithm, generating a placement path that includes the direction of movement and dwell time.

[0037] The placement path is then imported into the pick-and-place machine's control system. The control system controls the nozzle to pick up components from the tray using a 0.05MPa vacuum. Following the placement path, the nozzle moves the power electronic components above the reference point on the automotive circuit board, slowly descending until the pins contact the pads. At this point, the pick-and-place machine's built-in strain gauge force sensor detects the reaction force on the nozzle in real time, converting the force signal into an electrical signal and recording it to obtain the placement impact force when each power electronic component is fixed.

[0038] Finally, the adhesion coefficient of the automotive circuit board is calculated based on the surface condition map. Then, an impact force safety range is set based on this coefficient, and it is determined whether the mounting impact force falls within this range. If the mounting impact force is within the safety range, a soldering target value is set, and the surface temperature data is obtained by measuring the mounting path according to the target value. Next, the surface temperature data is integrated with the mounting time to construct a time-temperature matrix. Subsequently, the matrix is ​​traversed to extract thermal history parameters, and a three-dimensional morphology evaluation is performed based on these parameters to obtain a solder joint morphology consistency score. Finally, the thermal history parameters and the solder joint morphology consistency score are fused to ultimately construct the soldering component parameters. This step will be explained in detail later.

[0039] By employing methods such as industrial camera shooting and image processing, edge detection and sub-pixel positioning, CAD software path planning, and force sensing monitoring of the placement machine, the surface state analysis of the circuit board, reference point positioning, placement path generation, and placement impact force acquisition were achieved. This enabled the precise determination of component fixing positions, stable control of the placement process, and acquisition of key parameters of the soldering assembly.

[0040] Furthermore, the method provided in this application embodiment includes: The adhesion of the automotive circuit board is calculated based on the surface state map to obtain the adhesion coefficient. An impact force safety range is set based on the adhesion coefficient, and it is determined whether the mounting impact force exceeds this range. When the mounting impact force is within the safety range, a welding target value is set, and the mounting path is temperature-measured according to the welding target value to obtain surface temperature data. The surface temperature data is integrated with the mounting time to construct a time-temperature matrix. Feature extraction is performed by traversing the time-temperature matrix to obtain thermal history parameters. A three-dimensional morphology evaluation is performed based on the thermal history parameters to construct a solder joint morphology consistency score. The thermal history parameters and the solder joint morphology consistency score are fused to construct the welding component parameters.

[0041] Specifically, firstly, six evenly distributed 2mm×2mm test areas were selected from the surface condition map. Using a scratch tester equipped with a diamond indenter, a 5mm long scratch was made in each area at a loading speed of 5N / min. Simultaneously, an industrial camera was used to capture images of the entire scratch process. The images of the entire scratch process were compared with the original surface condition map. Image analysis software was used to statistically calculate the proportion of the peeling area at the scratch edge. Combined with the real-time loading force of the indenter, the adhesion coefficient was calculated for each area according to the formula: adhesion coefficient = loading force / proportion of peeling area. The average of the six results was taken as the final adhesion coefficient.

[0042] Then, 50 sets of historical data from the same model of automotive circuit boards were collected to establish a linear regression model of adhesion coefficient and mounting impact force. The model was constructed with adhesion coefficient as the independent variable (x) and mounting impact force as the dependent variable (y). The model was fitted using the historical data from the 50 sets of the same model of automotive circuit boards, resulting in the form y = ax + b, where a is the regression coefficient, representing the change in mounting impact force for each unit change in adhesion coefficient; b is the intercept term, representing the baseline impact force value under basic operating conditions. The calculated adhesion coefficient was substituted into the model to obtain the theoretically safe mounting impact force value. Then, considering the buffering characteristics of the silicone material of the pick-and-place machine nozzle, a safety redundancy factor of 0.8 was multiplied to determine the lower limit, and a tolerance factor of 1.2 was multiplied to determine the upper limit, forming a safe impact force range. The measured mounting impact force was compared with this range to complete the safety assessment.

[0043] When the placement impact force is within a safe range, based on the Sn-Ag-Cu solder melting point of the power electronic component pins, set the target peak soldering temperature to 230℃ and the target holding temperature to 210℃. Fix an infrared thermometer with a resolution of 0.1℃ next to the placement machine, align it with the pad area on the placement path, and collect temperature data at a frequency of 10 times / second. Discard abnormal values ​​caused by reflection, and retain 3 consecutive stable temperature data as surface temperature data.

[0044] Next, taking the instant the pick-and-place nozzle contacts the pad as the zero point, a timestamp accurate to milliseconds is added to each set of surface temperature data. The data is arranged in ascending order of time, with horizontal time nodes such as 0ms, 50ms, and 100ms, and vertical time nodes corresponding to the temperature values ​​of each node, automatically generating a time-temperature matrix with corresponding rows and columns.

[0045] Subsequently, when extracting parameters and evaluating the morphology by traversing the time-temperature matrix, a method combining peak extraction and 3D scanning was adopted. Data processing software was used to traverse the matrix and extract the temperature peak, heating rate, and cooling rate as thermal history parameters. Then, a laser scanning microscope was used to scan the solder joint to obtain 3D point cloud data, which was compared with a preset standard solder joint morphology model. The root mean square deviation of the two contours was calculated. According to the rule that a deviation ≤0.02mm is 100 points and 20 points are deducted for every 0.01mm increase, it is converted into a solder joint morphology consistency score.

[0046] Finally, the weights of thermal history parameters and morphology scores were set according to the importance of the process. The thermal history parameters were standardized to a score of 0-100 using the formula (measured value - standard value) / standard value × 100. Then, the scores were multiplied by their corresponding weights and summed to obtain a comprehensive quantitative value. This comprehensive quantitative value was integrated with data such as mounting impact force and adhesion coefficient to form welding component parameters that include core indicators of electrical connection quality.

[0047] Furthermore, the method provided in this application embodiment includes: Three-dimensional analysis is performed based on the welding component parameters to obtain three-dimensional morphology data. Solder joints are identified based on the morphology data to generate solder joint density data. A dense analysis of the automotive circuit board is performed based on the solder joint density data to delineate high-risk interference regions. Welding heat distribution is identified based on the surface temperature data to generate residual stress concentration regions. Process simulation calculations are performed based on the high-risk interference regions and the residual stress concentration regions to construct the encapsulation material flow path. Filling and distribution are performed according to the encapsulation material flow path to construct encapsulation protection layer parameters. Non-destructive testing of encapsulation quality is performed based on the encapsulation protection layer parameters to construct the encapsulation component parameters.

[0048] Specifically, during the 3D analysis based on the welding component parameters, data such as solder joint positions and circuit board dimensions are imported into a laser 3D scanner. The scanning accuracy is set to 0.02mm, and the scanning range covers the entire circuit board and component area. After starting the scanner, the laser beam scans point by point along a preset path, collecting 3D coordinate data of the circuit board surface and solder joints. The data is then imported into processing software for stitching and noise reduction, removing redundant point clouds to generate complete 3D topographic data of the circuit board. Subsequently, the solder joint recognition function is activated in the software. By comparing the grayscale differences and 3D protrusion features between the solder joints and the circuit board substrate, all solder joint positions are marked, and the number of solder joints per unit area is counted to generate solder joint density data.

[0049] Then, the average solder joint density of the entire circuit board is calculated, and 1.5 times the average density is set as the density threshold. The circuit board is divided into several 10mm × 10mm sub-regions, and the solder joint density of each sub-region is calculated and compared with the density threshold. If the density of a sub-region exceeds the density threshold, and the spacing between adjacent solder joints within the region is less than 0.5mm, the region is determined to be a high-risk interference region. The region is marked with a specific color on the circuit board layout to avoid spatial interference during subsequent packaging material filling.

[0050] The surface temperature data obtained in the preceding steps were then imported into infrared thermal imaging processing software in a time series format to generate a dynamic heat distribution map of the welding process, identifying high-temperature regions with temperatures exceeding 200℃ and regions with temperature change rates greater than 5℃ / s. The heat distribution data was then imported into finite element analysis software, and parameters such as the coefficient of thermal expansion and elastic modulus of the automotive circuit board substrate and power electronic components were set to simulate the internal stress generated by the temperature gradient during welding cooling. The stress values ​​in each region were calculated, and regions with stress values ​​exceeding 80% of the material's yield strength were marked as residual stress concentration areas.

[0051] Next, a 3D model of the circuit board and components was constructed in the simulation software. The coordinate data of the high-risk interference region and the residual stress concentration region were imported, and these two regions were set as the constraint regions for the flow of the encapsulation material. The encapsulation material was set as epoxy resin, and its viscosity, density before curing, and other parameters were input. The flow process of the encapsulation material after flowing out of the dispensing port was simulated. The position and flow rate of the dispensing port were adjusted to make the material flow path avoid the high-risk interference region and maintain a smooth flow in the residual stress concentration region to reduce additional stress. Finally, the optimal flow path of the encapsulation material was determined.

[0052] Next, the total volume of the area covered by the flow path is calculated. Based on the requirement that the encapsulation material needs to fill 1mm above the surface of the automotive circuit board, the total material usage is determined. The flow path is divided into three stages. The first stage corresponds to the area far from the constraint region, and the dispensing flow rate is set to 5. The second stage corresponds to the region close to the residual stress concentration area, where the flow rate is reduced to 3. The third phase corresponds to the areas surrounding high-risk intervention zones, with the flow rate adjusted to 2. Record the dispensing time, flow rate, and material filling thickness at each stage, and integrate this data to construct encapsulation and protective layer parameters that include material usage, filling rate, and protective layer thickness.

[0053] Finally, the encapsulation protective layer parameters are scanned to obtain an encapsulation scan dataset containing encapsulation thickness distribution data and internal defect data. Next, the encapsulation thickness distribution data is compared with the predicted thickness distribution data to calculate a thickness uniformity coefficient. This coefficient is then used to determine if it meets the expected thickness threshold, thus obtaining the thickness uniformity compliance. Simultaneously, it is determined whether the internal defect data is within the expected range, obtaining the critical value for internal defect size. Based on the thickness uniformity compliance and the critical value for internal defect size, non-destructive testing of the encapsulation quality is completed, generating non-destructive testing results. Finally, these non-destructive testing results are added to the encapsulation component parameters to form complete encapsulation component parameters. This step will be explained in detail later.

[0054] Furthermore, the method provided in this application embodiment includes: The encapsulation protective layer parameters are scanned to obtain an encapsulation scan dataset, which includes encapsulation thickness distribution data and encapsulation internal defect data. A thickness uniformity coefficient is calculated by comparing the encapsulation thickness distribution data with the predicted thickness distribution data. It is then determined whether the thickness uniformity coefficient meets the expected thickness threshold to obtain a thickness uniformity compliance rate. Finally, it is determined whether the encapsulation internal defect data falls within the expected defect data range to obtain an internal defect size critical value. Based on the thickness uniformity compliance rate and the internal defect size critical value, non-destructive testing of the encapsulation quality is performed to generate non-destructive testing results. These results are then added to the encapsulation component parameters.

[0055] Specifically, firstly, an ultrasonic flaw detector with a frequency of 10MHz is used. The probe is vertically aligned with the surface of the encapsulation protective layer, and the scanning step size is set to 0.1mm. The probe is moved point by point along the length and width of the circuit board. After the ultrasonic signal penetrates the encapsulation protective layer, the thickness at each point is calculated based on the time difference of the reflected signal, generating encapsulation thickness distribution data. At the same time, internal defects such as bubbles and cracks are identified by the amplitude changes of the reflected signal. The location and size of the defects are recorded to generate internal defect data of the encapsulation, thus forming an encapsulation scan dataset containing both types of data.

[0056] Next, 100 uniformly distributed sample points are selected from the encapsulation thickness distribution data, and the actual thickness value of each sample point is recorded. Simultaneously, the predicted thickness value of the corresponding sample point is extracted from the predicted thickness distribution data. The deviation between the actual thickness and the predicted thickness at each sample point is calculated. All deviations are squared, summed, and then divided by the number of sample points to obtain the average squared deviation value. The thickness uniformity coefficient is obtained by subtracting the ratio of the average squared deviation value to the squared predicted thickness from 1.

[0057] Furthermore, the predicted thickness value is generated by combining encapsulation process design parameters with fluid dynamics simulation. First, key data such as the preset target encapsulation thickness, injection port location, encapsulation material viscosity, and circuit board 3D morphology are extracted from the encapsulation protective layer parameters and imported into fluid dynamics simulation software. A simulation environment consistent with actual production is constructed in the software, setting process parameters such as injection flow rate and pressure to simulate the entire process of encapsulation material flowing from the injection port and filling the circuit board surface. Based on the material flow characteristics and circuit board structure, the simulation software automatically calculates the theoretical filling thickness of each region of the circuit board, forming initial predicted thickness distribution data. Then, actual thickness distribution data from the past 10 sets of packaged products of the same model of automotive circuit board are retrieved, and the average deviation between each set of data and the initial predicted data is calculated. This average deviation is used as a correction factor to adjust the initial predicted data, ultimately obtaining predicted thickness distribution data that matches the actual production scenario. The predicted thickness value when selecting sample points is derived from this data.

[0058] When determining whether the thickness uniformity coefficient meets the expected thickness threshold, the expected thickness threshold is set to 0.85 according to the industry standard for automotive circuit board packaging. The calculated thickness uniformity coefficient is compared with 0.85. If the coefficient is greater than or equal to 0.85, the thickness uniformity is deemed acceptable; if the coefficient is less than 0.85, the thickness uniformity is deemed unacceptable. The difference between the coefficient and the threshold is recorded.

[0059] When determining whether the internal defect data of the package falls within the expected defect data range, based on the packaging process requirements, the expected defect data is defined as a maximum size of no more than 0.2 mm for a single defect and no more than one defect per square centimeter. The maximum size and distribution density of each defect are extracted from the internal defect data. If all defects meet the expected requirements, the critical value for the internal defect size is determined to be 0.2 mm. If defects exceed the expected value, the maximum defect size is used as the critical value for the internal defect size, and the location of the out-of-tolerance defects is recorded.

[0060] Then, when performing non-destructive testing on packaging quality based on thickness uniformity compliance and internal defect size critical value, if the thickness uniformity compliance is qualified and the internal defect size critical value does not exceed 0.2mm, the packaging quality is judged to be qualified, and a qualified non-destructive testing result is generated. At the same time, the thickness uniformity coefficient and the internal defect distribution are recorded. If either of them does not meet the requirements, the packaging quality is judged to be unqualified, and a unqualified non-destructive testing result is generated, clearly marking the unqualified items and specific out-of-tolerance data.

[0061] Finally, retrieve the basic packaging component parameters containing the encapsulation and protective layer parameters constructed in the aforementioned steps, and add the pass / fail judgment conclusions, thickness uniformity coefficients, internal defect size critical values, and out-of-tolerance records from the non-destructive testing results to the basic packaging component parameters according to the parameter categories. This forms a complete packaging component parameter containing quality inspection information, ensuring that the parameter covers the packaging process, protective layer characteristics, and quality judgment results.

[0062] Furthermore, the method provided in this application embodiment includes: Electrical performance tests are performed on the power electronic component package based on the package component parameters to obtain electrical test results; thermal performance tests are performed on the power electronic component package based on the package component parameters to obtain thermal test results; mechanical performance tests are performed on the power electronic component package based on the package component parameters to obtain mechanical test results; environmental performance tests are performed on the power electronic component package based on the package component parameters to obtain environmental test results; the electrical test results, thermal test results, mechanical test results, and environmental test results are then integrated in multiple dimensions to obtain the multidimensional test results.

[0063] In one embodiment, firstly, when performing electrical performance tests based on the packaged component parameters, the power electronic component package is placed in a high-temperature chamber, a low-temperature chamber, and a room-temperature test area. The high-temperature chamber is set to 55°C and held for 30 minutes, the low-temperature chamber is set to -40°C and held for 30 minutes, and the room-temperature test area is maintained at a constant temperature of 25°C. After the package temperature stabilizes, a precision DC power supply with an accuracy of 0.01V is used to provide the component with its rated operating voltage. An oscilloscope probe with a bandwidth of 1GHz is connected to the component pins, and the sampling rate is set to 100MS / s. The switching rate (the time interval from turn-on to turn-off) and the on-state voltage drop (the voltage difference across the pins in the on-state) are measured. After completion, an insulation withstand voltage tester is used to apply a 500V DC voltage between the component pins and the circuit board substrate for 1 minute. The leakage current is monitored using a microammeter connected in series to determine the insulation withstand voltage strength. The measurement data under different environments are compiled into electrical test results.

[0064] Next, during the thermal performance testing based on the packaged component parameters, the package was fixed on a temperature-controlled thermal testing platform with an initial platform temperature set at 25°C. Rated operating current was applied to the components via copper busbars. Simultaneously, an infrared thermal imager with a resolution of 0.1°C was aimed at the package surface, and a frame rate of 10 frames per second was set for continuous recording for 30 minutes, recording the temperature changes at various points on the package surface in real time and generating a temperature distribution thermal map. After the test, the highest temperature at the center of the package was selected as the junction temperature reference value. Combined with the platform ambient temperature, the thermal resistance from the junction to the environment was calculated using the thermal resistance calculation formula: Thermal resistance = Difference between junction temperature and ambient temperature / Component power loss. The temperature distribution data and the thermal resistance value were then integrated into the thermal test results.

[0065] Then, during the mechanical performance testing based on the packaged component parameters, in accordance with the automotive industry standard GB / T 28046.3, the package was fixed to a mechanical vibration table using a fixture. The vibration direction was set to bidirectional (vertical and horizontal), with a frequency sweep range of 10-2000Hz, an acceleration of 20g, and each frequency step held for 2 minutes. An acoustic emission sensor was attached to the surface of the package and connected to a signal acquisition instrument. The sampling frequency was set to 1MHz, and the signal threshold to 0.5V. Abnormal signals such as crack propagation and solder joint detachment caused by vibration inside the package were monitored in real time. After the vibration test was completed, the sensor signal waveforms before and after the test were compared. If no sudden signals exceeding the threshold appeared, the mechanical performance was deemed qualified. The vibration parameters and signal monitoring data were then used to form the mechanical test results.

[0066] Subsequently, during environmental performance testing based on the packaged component parameters, the package was placed in a constant temperature and humidity chamber, with the temperature set at 85℃ and the relative humidity at 85%. Simultaneously, a 100V reverse bias voltage was applied across the components via a DC power supply for 1000 hours of accelerated aging testing. The test was interrupted every 200 hours, the package was removed, and allowed to recover at room temperature for 1 hour. The on-resistance and insulation resistance were measured using a multimeter, and the on-state voltage drop was remeasured using an oscilloscope. The deviations of each parameter from the initial values ​​were recorded. After the aging test, the maximum parameter drift was statistically analyzed, and the aging conditions, monitoring period, and parameter change data were compiled into environmental test results.

[0067] Finally, the electrical test results, thermal test results, mechanical test results, and environmental test results are integrated in multiple dimensions. The test items are classified as the first level, and the subcategories are as follows: electrical performance includes three-temperature environmental parameters and corresponding measured values; thermal performance includes temperature distribution and thermal resistance; mechanical performance includes vibration parameters and signal monitoring results; and environmental performance includes aging conditions and parameter drift data. All data are entered into the computer database according to the categories to form multi-dimensional test results containing four types of performance indicators.

[0068] Through the above-mentioned sequential testing steps, the multi-dimensional performance testing and data integration of the package were systematically completed, achieving a comprehensive evaluation of the reliability of power electronic component packages under different operating conditions, and providing complete data support for subsequent process optimization.

[0069] Furthermore, the method provided in this application embodiment includes: Based on digital twin technology, process mapping analysis is performed on the electrical test results, thermal test results, mechanical test results, and environmental test results to obtain a first process mapping relationship, a second process mapping relationship, a third process mapping relationship, and a fourth process mapping relationship. Process fluctuations are simulated according to these relationships to generate process fluctuation simulation data. Based on this simulation data, a retrospective impact analysis is performed on the multi-dimensional test results to generate process influence coefficients. A packaging process set for power electronic components is introduced, and the contribution of the packaging process parameter set is calculated by traversing the set according to the process influence coefficients, generating multiple process contribution degrees. The packaging process parameter set is then sorted in descending order according to these multiple process contribution degrees, and the first-order packaging process parameter is extracted as the target packaging process parameter.

[0070] Optionally, firstly, geometric data of the power electronic component package is acquired through 3D scanning. Combined with material properties and structural dimensions from the package component parameters, a virtual package model consistent with the physical component is constructed in a digital twin platform. Switching speed and on-state voltage drop from electrical test results, temperature distribution and thermal resistance from thermal test results, vibration signals from mechanical test results, and parameter drift data from environmental test results are imported into the virtual package model. A corresponding physical field simulation module is established for each type of test result. The electrical performance module correlates welding parameters with conduction characteristics; the thermal performance module correlates the thermal conductivity and thermal resistance of the encapsulation material; the mechanical performance module correlates solder joint density with vibration resistance; and the environmental performance module correlates the protective layer thickness with aging resistance. The simulation module calculates the correlation strength between various test results and corresponding packaging process parameters, generating first to fourth process mapping relationships, corresponding to the relationships between electrical, thermal, mechanical, and environmental performance and process parameters, respectively.

[0071] Next, in the process simulation module of the digital twin platform, the process parameter with the highest correlation in the mapping relationship is selected as the fluctuation variable. For example, the welding peak temperature is selected from the first process mapping relationship, and the encapsulation material injection pressure is selected from the second process mapping relationship. The fluctuation range of each variable is set to ±10% of the normal process value, and the variable value is gradually adjusted in a 5% gradient. Each time a variable is adjusted, the corresponding physical field simulation is run, and the change data of the test results are recorded. For example, the change value of the conduction voltage drop when the welding temperature increases by 5°C, and the change value of the thermal resistance when the injection pressure decreases by 5%. All fluctuation variables and corresponding test result change data are compiled into process fluctuation simulation data.

[0072] The process parameter fluctuations in the simulated process fluctuation data were then used as independent variables, and the changes in test results as dependent variables, and imported into data analysis software. The Pearson correlation coefficient was calculated to quantify the impact of each process parameter fluctuation on the test results; the closer the absolute value of the correlation coefficient is to 1, the greater the impact of that parameter on the test results. The correlation coefficients were statistically categorized by process parameter. Combining the comprehensive impact of parameter fluctuations on multiple test results, a weighted calculation was performed to obtain the comprehensive impact score for each process parameter. This score is the process influence coefficient, where the weights for electrical, thermal, mechanical, and environmental performance were all set to 0.25.

[0073] Subsequently, when calculating the process contribution of the packaging process set, the packaging process set is first organized into a list, clearly specifying all process parameters involved in packaging, including cleaning time and roughening degree in the pretreatment stage, temperature and time in the soldering stage, and material viscosity and injection rate in the encapsulation stage. The specific details of the four types of process mapping relationships are also listed. Next, a statistical table is created, with the table header showing the process parameter name, the type of associated mapping relationship, the number of associations, the process influence coefficient, and the process contribution. Each process parameter in the process set is extracted, and compared with the four types of process mapping relationships. The mapping category in which the process parameter is associated is marked. For example, if the soldering temperature parameter is associated with on-state voltage drop in the electrical performance mapping relationship and with thermal resistance in the thermal performance mapping relationship, then the associated mapping relationship category column is filled with "electrical performance" and the associated number column is filled with "2".

[0074] Then, from the retrospective impact analysis results of the above steps, extract the process impact coefficient corresponding to the parameter and fill it into the table. Perform the calculation according to the formula: Process Contribution = Process Impact Coefficient × Number of Associations, and fill the result into the Process Contribution column. Repeat this process for all process parameters in the packaging process set, performing association counts, process impact coefficient extraction, and process contribution calculation for each parameter, ultimately generating a complete data list containing the process contribution corresponding to each process parameter, resulting in multiple process contribution values.

[0075] Finally, the contribution of all process parameters is sorted in descending order in the data analysis software. The process parameter with the highest contribution is extracted from the sorting results. Since it has the highest contribution among all process parameters, it is determined as the target packaging process parameter.

[0076] By employing methods such as digital twin modeling, parameter fluctuation simulation, correlation analysis, contribution calculation, and ranking extraction, the backtracking and positioning of multi-dimensional test results to target packaging process parameters was completed. This achieved the goal of accurately identifying the key process parameters that have the greatest impact on packaging quality, providing a clear direction for subsequent process optimization.

[0077] Furthermore, the method provided in this application embodiment includes: Based on the target packaging process parameters, the process is divided into stages: pretreatment, soldering, and encapsulation. Surface analysis of the power electronic components is performed based on the pretreatment stage and the target packaging process parameters to generate surface roughness data. Surface analysis of the power electronic components is also performed based on the soldering stage and the target packaging process parameters to generate soldering peak temperature data. Surface analysis of the power electronic components is also performed based on the encapsulation stage and the target packaging process parameters to generate material injection pressure data. The target packaging process is adjusted and analyzed according to the surface roughness, soldering peak temperature data, and material injection pressure data to generate dynamic adjustment instructions. The dynamic adjustment instructions are executed to optimize the target packaging process parameters, generating optimized target packaging process parameters to verify the packaging quality. Based on the verification results, a packaging quality report for the power electronic components is constructed.

[0078] In one embodiment, the complete process of packaging power electronic components for automotive circuit boards is first outlined, clarifying the core functions of the pretreatment stage (responsible for cleaning and roughening the circuit board surface), the soldering stage (responsible for fixing and electrically connecting components), and the encapsulation stage (responsible for filling the protective layer). Then, the target packaging process parameters are classified according to their functions. If the target packaging process parameter is the degree of surface roughening, it is classified into the pretreatment stage; if it is the soldering temperature, it is classified into the soldering stage; and if it is the material injection pressure, it is classified into the encapsulation stage. This determines the division of the pretreatment stage, soldering stage, and encapsulation stage.

[0079] Next, three evenly distributed areas to be processed on the automotive circuit board were selected, each with an area of ​​1mm × 1mm. The stylus of the surface roughness tester was gently brought into contact with the surface of the area. The measurement length was set to 2.5mm and the sampling frequency to 500Hz. Measurements were taken once in the transverse and once in the longitudinal direction of the area, and the Ra value, i.e., the arithmetic mean deviation of the profile, was recorded for each measurement. The maximum and minimum values ​​of the six measurements in the three areas were removed, and the average value of the remaining four data was taken as the final surface roughness.

[0080] Then, fix the infrared thermometer 5cm directly below the soldering head of the pick-and-place machine, aiming it at the solder joint area on the automotive circuit board. Set the temperature measurement range to 0-300℃ and the sampling frequency to 10 times / second. Start the soldering process, and the infrared thermometer collects the solder joint temperature data in real time. After the soldering process is completed, extract the highest value from the collected temperature data. This value is the peak soldering temperature data, and the time point when the peak temperature occurs is also recorded.

[0081] Next, a pressure sensor with a range of 0-10 MPa is installed at the injection port of the encapsulation equipment. The sensor is connected to a data logger, and the data acquisition frequency is set to 1 time / second. The encapsulation process is started, and the pressure sensor monitors the material pressure at the injection port in real time, while the data logger simultaneously stores the pressure data. After encapsulation is completed, the average value of the pressure stabilization phase is extracted from the stored data; this average value is the material injection pressure data.

[0082] Next, a threshold comparison method is used to generate dynamic adjustment instructions: First, the acceptable threshold ranges for each parameter are set. For example, assume the acceptable range for surface roughness is 1.2-1.8 μm, the acceptable range for welding peak temperature is 220-240℃, and the acceptable range for material injection pressure is 3-5 MPa. Then, the surface roughness measured in the above steps is compared with the acceptable ranges. If it is less than 1.2 μm, an adjustment instruction to "extend the roughening treatment time by 1 minute" is generated; if it is greater than 1.8 μm, an adjustment instruction to "shorten the roughening treatment time by 30 seconds" is generated. Similarly, when the welding peak temperature is below 220℃, an instruction to "increase the welding temperature by 5℃" is generated; when it is above 240℃, an instruction to "decrease the welding temperature by 5℃" is generated. When the material injection pressure is below 3 MPa, an instruction to "increase the injection pressure by 0.2 MPa" is generated; when it is above 5 MPa, an instruction to "decrease the injection pressure by 0.2 MPa" is generated. These instructions are integrated to form dynamic adjustment instructions.

[0083] Finally, the packaging equipment parameters are adjusted according to the aforementioned dynamic adjustment instructions. For example, the processing time of chemical etching is modified according to the roughening time adjustment instruction, the solder head temperature setting is modified according to the soldering temperature instruction, and the pressure parameters of the encapsulation equipment are modified according to the injection pressure instruction. The above process of adjusting the packaging equipment parameters is the optimization of the target packaging process parameters. The target packaging process parameters include core indicators such as pretreatment roughening time, soldering peak temperature, and encapsulation injection pressure. Modifying packaging equipment parameters such as chemical etching time, solder head temperature, and encapsulation pressure transforms the target packaging process parameters from theoretical values ​​to optimized values ​​suitable for production. After the adjustment is completed, 10 sets of packaging samples are reproduced, and the surface roughness, soldering peak temperature, and material injection pressure of each set of samples are measured to confirm that all parameters are within the acceptable range. At the same time, non-destructive testing is performed on the samples to check the uniformity of the encapsulation thickness and internal defects. The parameter measurement results, non-destructive testing results, and parameter comparison data before and after adjustment are compiled into a document, clearly marking the qualified and unqualified items in the document. This document is the packaging quality report of the power electronic components.

[0084] By dividing the process into stages, measuring with conventional instruments, adjusting thresholds, and verifying samples, the dynamic optimization and quality verification of the target packaging process parameters were completed. This achieved the effect of accurately adjusting key packaging parameters, ensuring that the packaging quality meets the standards, and forming a complete quality record.

[0085] In summary, the packaging method for power electronic components used in automotive circuit board processing provided in this application has the following technical effects: This application obtains processing information through preprocessing of automotive circuit boards, fixes and welds power electronic components, encapsulates them, and then performs non-destructive testing. Following this, it conducts multi-dimensional performance tests on electrical, thermal, mechanical, and environmental parameters. Combined with digital twin backtracking to locate target process parameters and dynamically adjusting them, the entire packaging process is precisely controlled. This results in more reliable packaging quality and more stable performance for automotive circuit board components, achieving comprehensive acquisition and accurate evaluation of packaging quality data, and improving packaging reliability and quality control efficiency.

[0086] Example 2, as Figure 2 As shown, based on the same inventive concept as in Embodiment 1 above, this application provides a packaging system for power electronic components used in automotive circuit board processing, the system comprising: The module 1 for acquiring information to be processed is used to preprocess the automotive circuit board and generate information to be processed for the automotive circuit board.

[0087] The welding component parameter acquisition module 2, based on the information to be processed, fixes the power electronic components to a predetermined position on the automotive circuit board and makes electrical connections to obtain the welding component parameters.

[0088] The packaging component parameter acquisition module 3 encapsulates the power electronic components based on the welding component parameters to generate packaging component parameters.

[0089] The packaging quality report acquisition module 4 performs multi-dimensional packaging performance testing based on the packaging component parameters, performs process backtracking based on the multi-dimensional test results, locates the target packaging process parameters for dynamic adjustment, and obtains the packaging quality report of the power electronic components.

[0090] Furthermore, the process information acquisition module 1 is used to perform the following steps: A surface cleaning process is performed on the automotive circuit board to obtain a cleaning result; a surface roughening process is performed on the automotive circuit board based on the cleaning result to obtain a roughening result; a surface state scan is performed on the automotive circuit board based on the roughening result to obtain multi-dimensional physical surface feature data; the multi-dimensional physical surface feature data is fused and analyzed to generate a processing identifier; the processing identifier is mapped to the automotive circuit board for identifier binding to obtain the processing information of the automotive circuit board.

[0091] Furthermore, the welding component parameter acquisition module 2 is used to perform the following steps: Based on the information to be processed, the surface state of the automotive circuit board is analyzed to obtain a surface state map; the surface state map is traversed for optical capture and positioning to determine the coordinates of multiple reference points; the coordinates of the multiple reference points are used as predetermined positions to perform fixed simulation of power electronic components and generate a mounting path; the placement machine is controlled to pick up power electronic components according to the mounting path to perform fixed monitoring of the automotive circuit board and obtain the mounting impact force; a safety judgment is made based on the mounting impact force, and electrical connections are made according to the safety judgment result to construct the welding component parameters.

[0092] Furthermore, the welding component parameter acquisition module 2 is used to perform the following steps: The adhesion of the automotive circuit board is calculated based on the surface state map to obtain the adhesion coefficient. An impact force safety range is set based on the adhesion coefficient, and it is determined whether the mounting impact force exceeds this range. When the mounting impact force is within the safety range, a welding target value is set, and the mounting path is temperature-measured according to the welding target value to obtain surface temperature data. The surface temperature data is integrated with the mounting time to construct a time-temperature matrix. Feature extraction is performed by traversing the time-temperature matrix to obtain thermal history parameters. A three-dimensional morphology evaluation is performed based on the thermal history parameters to construct a solder joint morphology consistency score. The thermal history parameters and the solder joint morphology consistency score are fused to construct the welding component parameters.

[0093] Furthermore, the encapsulation component parameter acquisition module 3 is used to perform the following steps: Three-dimensional analysis is performed based on the welding component parameters to obtain three-dimensional morphology data. Solder joints are identified based on the morphology data to generate solder joint density data. A dense analysis of the automotive circuit board is performed based on the solder joint density data to delineate high-risk interference regions. Welding heat distribution is identified based on the surface temperature data to generate residual stress concentration regions. Process simulation calculations are performed based on the high-risk interference regions and the residual stress concentration regions to construct the encapsulation material flow path. Filling and distribution are performed according to the encapsulation material flow path to construct encapsulation protection layer parameters. Non-destructive testing of encapsulation quality is performed based on the encapsulation protection layer parameters to construct the encapsulation component parameters.

[0094] Furthermore, the encapsulation component parameter acquisition module 3 is used to perform the following steps: The encapsulation protective layer parameters are scanned to obtain an encapsulation scan dataset, which includes encapsulation thickness distribution data and encapsulation internal defect data. A thickness uniformity coefficient is calculated by comparing the encapsulation thickness distribution data with the predicted thickness distribution data. It is then determined whether the thickness uniformity coefficient meets the expected thickness threshold to obtain a thickness uniformity compliance rate. Finally, it is determined whether the encapsulation internal defect data falls within the expected defect data range to obtain an internal defect size critical value. Based on the thickness uniformity compliance rate and the internal defect size critical value, non-destructive testing of the encapsulation quality is performed to generate non-destructive testing results. These results are then added to the encapsulation component parameters.

[0095] Furthermore, the packaging quality report acquisition module 4 is used to perform the following steps: Electrical performance tests are performed on the power electronic component package based on the package component parameters to obtain electrical test results; thermal performance tests are performed on the power electronic component package based on the package component parameters to obtain thermal test results; mechanical performance tests are performed on the power electronic component package based on the package component parameters to obtain mechanical test results; environmental performance tests are performed on the power electronic component package based on the package component parameters to obtain environmental test results; the electrical test results, thermal test results, mechanical test results, and environmental test results are then integrated in multiple dimensions to obtain the multidimensional test results.

[0096] Furthermore, the packaging quality report acquisition module 4 is used to perform the following steps: Based on digital twin technology, process mapping analysis is performed on the electrical test results, thermal test results, mechanical test results, and environmental test results to obtain a first process mapping relationship, a second process mapping relationship, a third process mapping relationship, and a fourth process mapping relationship. Process fluctuations are simulated according to these relationships to generate process fluctuation simulation data. Based on this simulation data, a retrospective impact analysis is performed on the multi-dimensional test results to generate process influence coefficients. A packaging process set for power electronic components is introduced, and the contribution of the packaging process parameter set is calculated by traversing the set according to the process influence coefficients, generating multiple process contribution degrees. The packaging process parameter set is then sorted in descending order according to these multiple process contribution degrees, and the first-order packaging process parameter is extracted as the target packaging process parameter.

[0097] Furthermore, the packaging quality report acquisition module 4 is used to perform the following steps: Based on the target packaging process parameters, the process is divided into stages: pretreatment, soldering, and encapsulation. Surface analysis of the power electronic components is performed based on the pretreatment stage and the target packaging process parameters to generate surface roughness data. Surface analysis of the power electronic components is also performed based on the soldering stage and the target packaging process parameters to generate soldering peak temperature data. Surface analysis of the power electronic components is also performed based on the encapsulation stage and the target packaging process parameters to generate material injection pressure data. The target packaging process is adjusted and analyzed according to the surface roughness, soldering peak temperature data, and material injection pressure data to generate dynamic adjustment instructions. The dynamic adjustment instructions are executed to optimize the target packaging process parameters, generating optimized target packaging process parameters to verify the packaging quality. Based on the verification results, a packaging quality report for the power electronic components is constructed.

[0098] The packaging system for power electronic components for automotive circuit board processing provided in this embodiment of the invention can execute the packaging method for power electronic components for automotive circuit board processing provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0099] Although this application makes various references to certain modules in the system according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of this invention.

[0100] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application. In some cases, the actions or steps described in this application can be performed in a different order than that shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A packaging method for power electronic components used in automotive circuit board processing, characterized in that, The method includes: Preprocess the automotive circuit board to generate the information to be processed. Based on the information to be processed, power electronic components are fixed to predetermined positions on the automotive circuit board for electrical connection to obtain welding component parameters; Based on the welding component parameters, the power electronic components are encapsulated to generate encapsulation component parameters; Based on the parameters of the packaging components, multi-dimensional packaging performance testing is performed. Based on the multi-dimensional test results, process backtracking is performed to locate the target packaging process parameters for dynamic adjustment, and a packaging quality report of power electronic components is obtained.

2. The packaging method for power electronic components used in automotive circuit board processing as described in claim 1, characterized in that, Preprocessing automotive circuit boards to generate information on the circuit boards to be processed includes the following methods: Perform surface cleaning treatment on automotive circuit boards to obtain cleaning results; Based on the cleaning results, a surface roughening treatment is performed on the automotive circuit board to obtain the roughening treatment result; Based on the roughening process results, a surface state scan is performed on the automotive circuit board to obtain multi-dimensional physical surface feature data. The multidimensional physical surface feature data are fused and analyzed to generate a processing identifier; The identifier to be processed is mapped to the automotive circuit board for identifier binding, thereby obtaining the processing information of the automotive circuit board.

3. The packaging method for power electronic components used in automotive circuit board processing as described in claim 1, characterized in that, Based on the information to be processed, power electronic components are fixed to predetermined positions on the automotive circuit board for electrical connection to obtain welding assembly parameters. The method includes: Based on the information to be processed, the surface state of the automotive circuit board is analyzed to obtain a surface state map. The surface state map is traversed for optical capture and positioning to determine the coordinates of multiple reference points. The coordinates of the multiple reference points are used as predetermined positions to perform fixed simulation of power electronic components, and a mounting path is generated. According to the mounting path, the pick-and-place machine picks up power electronic components to monitor the fixation of the automotive circuit board and obtains the mounting impact force. Safety is assessed based on the mounting impact force, and electrical connections are made according to the safety assessment results to construct the welding component parameters.

4. The packaging method for power electronic components used in automotive circuit board processing as described in claim 3, characterized in that, The method includes: determining safety based on the mounting impact force, making electrical connections according to the safety determination results, and constructing the parameters of the welding assembly. The adhesion force of the automotive circuit board is calculated based on the surface state map to obtain the adhesion coefficient. Based on the adhesion coefficient, a safe range of impact force is set, and it is determined whether the mounting impact force exceeds the safe range of impact force. When the mounting impact force is within the safe range, a welding target value is set, and the mounting path is temperature measured according to the welding target value to obtain surface temperature data. Based on the surface temperature data and the mounting time, a time-temperature matrix is ​​constructed. Feature extraction is performed by traversing the time-temperature matrix to obtain thermal history parameters. Based on the thermal history parameters, a three-dimensional morphology evaluation is performed to construct a solder joint morphology consistency score. The thermal history parameters and the weld joint morphology consistency score are fused to construct the welding component parameters.

5. The packaging method for power electronic components used in automotive circuit board processing as described in claim 4, characterized in that, The method for encapsulating the power electronic components based on the welding component parameters to generate encapsulation component parameters includes: Three-dimensional analysis is performed based on the parameters of the welding components to obtain three-dimensional morphology data. Weld point identification is performed based on the three-dimensional morphology data to generate weld point density data. Based on the solder joint density data, a dense analysis of the automotive circuit board was performed to identify high-risk interference areas. Welding heat distribution is identified based on the surface temperature data, and residual stress concentration areas are generated. Based on the high-risk interference region and the residual stress concentration region, process simulation calculations are performed to construct the encapsulation material flow path; The encapsulation material is filled and distributed according to the flow path of the encapsulation material to construct the encapsulation protection layer parameters; Based on the encapsulation protection layer parameters, non-destructive testing of the encapsulation quality is performed to construct the encapsulation component parameters.

6. The packaging method for power electronic components used in automotive circuit board processing as described in claim 5, characterized in that, The method for constructing the packaging component parameters by performing non-destructive testing of packaging quality based on the encapsulation protection layer parameters includes: The parameters of the encapsulation protective layer are scanned to obtain an encapsulation scan dataset, which includes encapsulation thickness distribution data and encapsulation internal defect data. The thickness uniformity coefficient is calculated by comparing the encapsulation thickness distribution data with the predicted thickness distribution data. Determine whether the thickness uniformity coefficient meets the desired thickness threshold to obtain the thickness uniformity compliance. Determine whether the internal defect data of the encapsulation is within the expected defect data to obtain the critical value of the internal defect size; Based on the thickness uniformity and the critical value of the internal defect size, non-destructive testing of the packaging quality is performed to generate non-destructive testing results. The non-destructive testing results are added to the packaging component parameters.

7. The packaging method for power electronic components used in automotive circuit board processing as described in claim 1, characterized in that, The method for performing multi-dimensional packaging performance testing based on the aforementioned packaging component parameters includes: Based on the packaging component parameters, electrical performance tests are performed on the power electronic component package to obtain electrical test results. Thermal performance tests were performed on the power electronic component package based on the package component parameters to obtain thermal test results. Mechanical performance tests are performed on the power electronic component package based on the package component parameters to obtain mechanical test results; Environmental performance tests were performed on the power electronic component package based on the package component parameters to obtain the environmental test results. The electrical test results, thermal test results, mechanical test results, and environmental test results are integrated in multiple dimensions to obtain the multidimensional test results.

8. The packaging method for power electronic components used in automotive circuit board processing as described in claim 7, characterized in that, Based on the multidimensional test results, process backtracking is performed to locate the target packaging process parameters. The method includes: Based on digital twin technology, process mapping analysis is performed on the electrical test results, thermal test results, mechanical test results, and environmental test results to obtain a first process mapping relationship, a second process mapping relationship, a third process mapping relationship, and a fourth process mapping relationship; Simulate process fluctuations according to the first process mapping relationship, the second process mapping relationship, the third process mapping relationship, and the fourth process mapping relationship to generate process fluctuation simulation data; Based on the process fluctuation simulation data, a retrospective impact analysis of the multidimensional test results is performed to generate a process impact coefficient. A set of packaging processes for power electronic components is introduced, and the contribution is calculated by traversing the set of packaging process parameters according to the process influence coefficient, generating multiple process contribution degrees. The packaging process parameter set is sorted in descending order according to the contribution of the multiple processes, and the packaging process parameter with the first order is extracted as the target packaging process parameter.

9. The packaging method for power electronic components used in automotive circuit board processing as described in claim 8, characterized in that, The method involves dynamically adjusting the target packaging process parameters to obtain a packaging quality report for power electronic components. Based on the target packaging process parameters, the process is divided into stages, including the pretreatment stage, the soldering stage, and the encapsulation stage. Based on the preprocessing stage and the target packaging process parameters, surface analysis is performed on the power electronic components to generate surface roughness. Based on the welding stage and the target packaging process parameters, surface analysis of power electronic components is performed to generate welding peak temperature data. Based on the encapsulation stage and the target packaging process parameters, surface analysis of power electronic components is performed to generate material injection pressure data. The target packaging process is adjusted and analyzed based on the surface roughness, the welding peak temperature data, and the material injection pressure data to generate dynamic adjustment instructions. The dynamic adjustment instructions are executed to optimize the target packaging process parameters, and the optimized target packaging process parameters are generated to verify the packaging quality. Based on the verification results, the packaging quality report of the power electronic components is constructed.

10. A packaging system for power electronic components used in automotive circuit board processing, characterized in that, A packaging method for implementing the power electronic components for automotive circuit board processing according to any one of claims 1-9, the system comprising: The module for acquiring information to be processed is used to preprocess automotive circuit boards and generate information to be processed for automotive circuit boards. The welding component parameter acquisition module, based on the information to be processed, fixes the power electronic components to a predetermined position on the automotive circuit board and makes electrical connections to obtain the welding component parameters; The encapsulation component parameter acquisition module encapsulates the power electronic components based on the welding component parameters to generate encapsulation component parameters. The packaging quality report acquisition module performs multi-dimensional packaging performance testing based on the packaging component parameters, performs process backtracking based on the multi-dimensional test results, locates the target packaging process parameters for dynamic adjustment, and obtains the packaging quality report of the power electronic components.

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