IBC module potential-induced degradation suppression optimization method and system

Abstract

The invention relates to the technical field of potential optimization, and discloses an IBC module potential-induced degradation suppression optimization method and system, and the method comprises the steps: obtaining the electric field distribution data between back electrodes of an IBC module under a preset bias voltage; calculating charge non-uniformity distribution of each local area in the IBC module according to the electric field distribution data; based on the charge non-uniformity distribution and a preset charge aggregation threshold, identifying a high-risk sub-region of potential-induced attenuation in the IBC module; according to the charge non-uniformity corresponding to the high-risk sub-region, determining a repair voltage parameter applied to the corresponding back finger electrode of the high-risk sub-region; generating a repair instruction sequence of the IBC module according to the repair voltage parameter; performing selective and sequential local repair processing on the high-risk sub-region according to the repair instruction sequence; according to the invention, the efficiency of IBC module potential-induced attenuation suppression optimization can be improved.

Description

Technical Field

[0001] This invention relates to the field of potential optimization technology, and in particular to a method and system for optimizing the suppression of potential-induced decay in IBC modules. Background Technology

[0002] During long-term operation, uneven electric field distribution between the back electrodes of an IBC module can easily lead to charge accumulation, resulting in potential-induced decay and severely impacting the module's photoelectric conversion efficiency and long-term reliability. Existing suppression and optimization technologies for this problem mostly adopt a holistic repair strategy, failing to accurately distinguish the differences in charge distribution across different regions within the module. They lack the ability to specifically identify high-risk areas for potential-induced decay, leading to unreasonable resource allocation during the repair process. This not only makes it difficult to address the charge accumulation problem specifically but may also unnecessarily affect the performance of normal areas, resulting in unsatisfactory overall repair efficiency and effectiveness.

[0003] Existing technologies, when assessing charge distribution, often focus only on the single-dimensional characteristics of charge dispersion, failing to comprehensively consider the degree of dispersion of charge distribution within a region and the differences in charge distribution between regions. This results in an inaccurate assessment of charge non-uniformity, failing to provide a reliable basis for determining repair voltage parameters. Consequently, the setting of parameters such as the amplitude, polarity, and duration of the repair voltage lacks specificity. Insufficient parameters either lead to the inability to completely eliminate charge accumulation in high-risk areas, or excessive parameters cause damage to the internal structure of the module, further exacerbating the potential-induced decay problem, making it difficult to achieve effective recovery and long-term stability of module performance. Summary of the Invention

[0004] This invention provides an optimization method and system for suppressing potential-induced decay in IBC modules, in order to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides an optimization method for suppressing potential-induced decay in IBC modules, comprising: S1. Obtain the electric field distribution data between the back electrodes of the IBC module under a preset bias voltage; S2. Calculate the charge non-uniformity distribution in each local region within the IBC module based on the electric field distribution data; S3. Based on the charge non-uniformity distribution and the preset charge accumulation threshold, identify high-risk sub-regions of potential-induced decay in the IBC module; S4. Determine the repair voltage parameters applied to the back finger electrode corresponding to the high-risk sub-region based on the charge non-uniformity of the high-risk sub-region. S5. Generate a repair instruction sequence for the IBC module based on the repair voltage parameters; S6. Based on the repair instruction sequence, perform selective and time-sequential local repair processing on the high-risk sub-region.

[0006] In a preferred embodiment, acquiring the electric field distribution data between the back electrodes of the IBC module under a preset bias voltage includes: The surface of the finger electrodes on the back of the IBC module under a preset bias voltage is scanned to obtain the relative potential difference of each measurement point in the IBC module. By correlating the relative potential difference with the spatial coordinates of the back finger electrode surface, preliminary potential distribution data between the back electrodes are obtained; Based on the known dielectric constant of the IBC module, environmental interference compensation is performed on the preliminary potential distribution data to obtain corrected potential distribution data; The corrected potential distribution data is spatially interpolated on the surface of the back finger electrodes to obtain the electric field distribution data between the back electrodes.

[0007] In a preferred embodiment, calculating the charge non-uniformity distribution in each local region within the IBC module based on the electric field distribution data includes: Based on the physical layout of the finger electrodes on the back, the measurement area corresponding to the electric field distribution data is divided into grid sub-regions; The statistical variance of the electric field intensity at each point within the grid sub-region is used as the first non-uniformity index of the grid sub-region. The absolute value of the difference in average electric field intensity between the grid sub-region and all its adjacent grid sub-regions is used as the second non-uniformity index of the grid sub-region. The first non-uniformity index and the second non-uniformity index corresponding to the grid sub-region are weighted and fused to generate the comprehensive charge non-uniformity of the grid sub-region; By aggregating all the aforementioned combined charge nonuniformity, the charge nonuniformity distribution of each local region within the IBC module is obtained.

[0008] In a preferred embodiment, using the statistical variance of the electric field intensity at each point within the grid sub-region as the first non-uniformity index of the grid sub-region includes: Extract all electric field intensity data points belonging to the current grid sub-region; Calculate the arithmetic mean of all the electric field intensity data points; Calculate the squared difference between each electric field intensity data point and the arithmetic mean; The ratio of the sum of the squared differences to the total number of electric field strength data points is used as the statistical variance of the electric field strength at each point within the grid sub-region.

[0009] In a preferred embodiment, the formula for calculating the overall charge non-uniformity is as follows: ; In the formula, The overall charge non-uniformity, The contribution of the dispersion of the internal charge distribution to the non-uniformity. This is the first non-uniformity index. The contribution of neighborhood variance when both internal variance and neighborhood variance are large. This is the second non-uniformity index.

[0010] In a preferred embodiment, identifying high-risk sub-regions of potential-induced decay in the IBC module based on the charge non-uniformity distribution and a preset charge accumulation threshold includes: Traverse the charge non-uniformity distribution to obtain the comprehensive charge non-uniformity corresponding to each grid sub-region; Each comprehensive charge non-uniformity is compared with a preset charge accumulation threshold one by one; The grid sub-regions whose overall charge non-uniformity is greater than the preset charge accumulation threshold are marked as preliminary high-risk areas; Spatial clustering is performed on the initial high-risk areas to obtain continuous high-risk areas; The continuous high-risk areas with an area greater than the preset minimum area threshold are ultimately determined as high-risk sub-regions of potential-induced decay in the IBC module.

[0011] In a preferred embodiment, determining the repair voltage parameters applied to the back finger electrode corresponding to the high-risk sub-region based on the charge non-uniformity corresponding to the high-risk sub-region includes: Obtain the maximum value of the comprehensive charge nonuniformity in all grid sub-regions within the high-risk sub-region; Based on the maximum value and the predefined voltage amplitude mapping relationship, the initial voltage amplitude applied to the back finger electrode corresponding to the high-risk sub-region is determined; Obtain the mean value of the local average electric field intensity in all grid sub-regions within the high-risk sub-region; The polarity of the repair voltage is determined based on the mean value of the local average electric field intensity. Based on the area and shape characteristics of the high-risk sub-region, the application period of the repair voltage is determined; The output is a repair voltage parameter composed of the initial voltage amplitude, the polarity, and the operating period.

[0012] In a preferred embodiment, the predefined voltage amplitude mapping relationship includes: Identify the maximum value of charge non-uniformity distribution in the calibration sample IBC module; Under controlled laboratory conditions, repair voltages of different amplitudes were applied to the calibration sample IBC module, and the optimal repair voltage amplitude that enables the performance recovery to reach the preset target was determined by monitoring the degree of photoelectric performance recovery of the calibration sample IBC module. A dataset is established to establish the correspondence between the maximum value of the comprehensive charge nonuniformity and the optimal repair voltage amplitude, thereby obtaining the voltage amplitude mapping relationship.

[0013] In a preferred embodiment, generating the repair instruction sequence for the IBC module based on the repair voltage parameters includes: The repair voltage parameter is decomposed into three independent control fields, corresponding to the voltage amplitude field, polarity field, and action period field, respectively. Obtain the spatial coordinate encoding of the geometric center of the high-risk sub-region in the rear finger electrode layout; The spatial coordinate encoding and the three independent control fields are formatted and encapsulated to obtain a single repair instruction block corresponding to the high-risk sub-region; The execution order of the individual repair instruction blocks is determined based on the spatial distance between the multiple high-risk sub-regions and the corresponding comprehensive charge non-uniformity values. According to the execution order, multiple individual repair instruction units are sequentially connected in series, and device status query instructions are inserted between adjacent instruction units to obtain the repair instruction sequence of the IBC module.

[0014] To address the above problems, the present invention also provides an IBC module potential-induced decay suppression optimization system, the system comprising: The electric field distribution acquisition module is used to acquire the electric field distribution data between the back electrodes of the IBC module under a preset bias voltage. The charge non-uniformity distribution acquisition module is used to calculate the charge non-uniformity distribution of each local region within the IBC module based on the electric field distribution data. The risk identification module is used to identify high-risk sub-regions of potential-induced decay in the IBC module based on the charge non-uniformity distribution and a preset charge accumulation threshold. The repair voltage calibration module is used to determine the repair voltage parameters applied to the back finger electrode corresponding to the high-risk sub-region based on the charge non-uniformity corresponding to the high-risk sub-region. A repair instruction generation module is used to generate a repair instruction sequence for the IBC module based on the repair voltage parameters. The repair module is used to perform selective and time-sequential local repair processing on the high-risk sub-regions according to the repair instruction sequence.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention accurately collects electric field distribution data between the back electrodes of the IBC module under a preset bias voltage, and combines the internal charge dispersion characteristics and charge differences between adjacent regions to construct a comprehensive charge non-uniformity evaluation index. This index can comprehensively and accurately reflect the charge distribution status of each local area of ​​the module, thereby accurately identifying high-risk sub-regions of potential-induced decay, providing a clear target for subsequent repair, significantly improving the pertinence and effectiveness of potential-induced decay suppression, and helping the charge distribution of the module to become more balanced.

[0016] 2. Based on the specific charge non-uniformity, electric field strength, and morphological characteristics of high-risk sub-regions, this invention customizes the amplitude, polarity, and duration of the repair voltage. Simultaneously, it generates a time-sequential repair instruction sequence and integrates it into the equipment status query mechanism. This achieves refined and orderly local repair of high-risk sub-regions, ensuring precise energy delivery and guaranteeing the safety of the repair process. It effectively restores the module's photoelectric conversion efficiency, extends the module's lifespan, and enhances the practicality and reliability of the overall optimization scheme. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating an optimization method for suppressing potential-induced decay in an IBC module according to an embodiment of the present invention. Figure 2 This is a functional block diagram of an IBC module potential-induced decay suppression optimization system provided in an embodiment of the present invention; The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0018] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0019] This application provides an optimization method for suppressing potential-induced decay in IBC modules. The execution subject of this optimization method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the optimization method for suppressing potential-induced decay in IBC modules can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0020] Reference Figure 1 The diagram shown is a flowchart illustrating an optimization method for suppressing potential-induced decay in an IBC module according to an embodiment of the present invention. In this embodiment, the optimization method for suppressing potential-induced decay in an IBC module includes: S1. Obtain the electric field distribution data between the back electrodes of the IBC module under a preset bias voltage; In this embodiment of the invention, obtaining the electric field distribution data between the back electrodes of the IBC module under a preset bias voltage includes: The surface of the finger electrodes on the back of the IBC module under a preset bias voltage is scanned to obtain the relative potential difference of each measurement point in the IBC module. By correlating the relative potential difference with the spatial coordinates of the back finger electrode surface, preliminary potential distribution data between the back electrodes are obtained; Based on the known dielectric constant of the IBC module, environmental interference compensation is performed on the preliminary potential distribution data to obtain corrected potential distribution data; The corrected potential distribution data is spatially interpolated on the surface of the back finger electrodes to obtain the electric field distribution data between the back electrodes.

[0021] The IBC module is fixed on a test platform free from electrostatic interference. The surface of the finger electrodes on the back of the module is kept horizontal and perpendicular to the probe end of the potential scanning probe. The movement step of the scanning probe is set to a fixed value that matches the linewidth of the finger electrodes on the back. The scanning probe is moved sequentially along the length of the finger electrodes and the transverse direction of the electrode spacing. With a preset bias voltage continuously and stably applied to both ends of the IBC module electrodes, the scanning probe collects the potential value at each position where the movement stops. The difference between all the collected potential values ​​and the potential value of the preset potential reference point is calculated. The difference result corresponding to each position is the relative potential difference of the measurement point. After completing the potential acquisition and difference calculation for all scanning positions, the system obtains the relative potential difference of all measurement points in the IBC module.

[0022] Before scanning the surface of the finger electrodes on the back of the IBC module, a two-dimensional rectangular coordinate system is established with one corner of the area where the finger electrodes are located as the origin of the spatial coordinates. The X-axis extends along the length of the finger electrodes, and the Y-axis extends laterally along the distance between the finger electrodes. When the scanning probe moves to a measurement point and completes potential acquisition, the corresponding X-axis coordinate value and Y-axis coordinate value are recorded simultaneously. The X-axis coordinate value and Y-axis coordinate value of each measurement point are bound one-to-one with the relative potential difference calculated for that measurement point to form a basic dataset containing coordinate information and corresponding relative potential difference. The basic dataset is then arranged in order according to the X-axis and Y-axis coordinate sequence. The complete basic dataset after arrangement is the preliminary potential distribution data between the electrodes on the back of the IBC module.

[0023] The known dielectric constants of the substrate and electrode materials used in the fabrication of the IBC module are retrieved. These dielectric constants are fixed values ​​measured by standard dielectric performance testing equipment according to national standard dielectric testing specifications. Based on the correlation between the dielectric constant and the influence of the environmental medium on the potential signal, the relative potential difference of each measurement point in the preliminary potential distribution data is compensated and corrected. Specifically, the influence of the environmental medium on the potential signal due to its dielectric properties is removed from the relative potential difference of each measurement point. The removal operation is carried out step by step according to the degree of attenuation of the potential signal by the environmental medium as reflected by the known dielectric constant, so that the relative potential difference of each measurement point is restored to the true potential difference value under the condition of no environmental medium interference. The coordinate information of all the corrected measurement points is re-bound to the corresponding true potential difference value and arranged in an orderly manner. The resulting new dataset is the corrected potential distribution data.

[0024] Within the two-dimensional coordinate range of the IBC module's back-side finger electrode surface covered by the corrected potential distribution data, an interpolation interval consistent with the movement step size during the scanning operation is selected. Interpolation points are added at the blank positions between the coordinates of existing measurement points according to this interpolation interval. Based on the coordinate information of multiple adjacent measurement points and the corresponding true potential difference, the potential value corresponding to each interpolation point is calculated step by step. The coordinate information of all interpolation points is bound one-to-one with the calculated potential value. Then, the measurement point information in the original corrected potential distribution data and the newly added interpolation point information are fully integrated. The orderly arrangement of the entire range of the back-side finger electrode surface is completed according to the coordinate order of the two-dimensional rectangular coordinate system. The spatial gradient of the potential values ​​of all points after integration and arrangement is calculated to obtain the potential change rate between each point. The complete dataset containing the coordinate information of all points, the corresponding potential values, and the potential change rate is the electric field distribution data between the back-side electrodes of the IBC module.

[0025] The beneficial effects are as follows: by accurately setting scanning conditions, the relative potential difference of each measurement point is collected and calculated. Combined with spatial coordinate correlation, a standardized and orderly preliminary potential distribution data is formed. Based on the known dielectric constant, the interference of the environmental medium is eliminated to complete the potential data correction. Then, by setting a uniform interpolation interval, interpolation points are supplemented and the corresponding potential values ​​are calculated. After integration, the spatial gradient calculation is completed. Finally, electric field distribution data covering the entire range of the finger electrode surface on the back of the IBC module and conforming to reality can be obtained, which ensures the accuracy and completeness of the electric field distribution data and realizes the accurate characterization of the electric field distribution between the back electrodes of the IBC module.

[0026] S2. Calculate the charge non-uniformity distribution in each local region within the IBC module based on the electric field distribution data; In this embodiment of the invention, calculating the charge non-uniformity distribution in each local region within the IBC module based on the electric field distribution data includes: Based on the physical layout of the finger electrodes on the back, the measurement area corresponding to the electric field distribution data is divided into grid sub-regions; The statistical variance of the electric field intensity at each point within the grid sub-region is used as the first non-uniformity index of the grid sub-region. The absolute value of the difference in average electric field intensity between the grid sub-region and all its adjacent grid sub-regions is used as the second non-uniformity index of the grid sub-region. The first non-uniformity index and the second non-uniformity index corresponding to the grid sub-region are weighted and fused to generate the comprehensive charge non-uniformity of the grid sub-region; By aggregating all the aforementioned combined charge nonuniformity, the charge nonuniformity distribution of each local region within the IBC module is obtained.

[0027] The step of using the statistical variance of the electric field intensity at each point within the grid sub-region as the first non-uniformity index of the grid sub-region includes: Extract all electric field intensity data points belonging to the current grid sub-region; Calculate the arithmetic mean of all the electric field intensity data points; Calculate the squared difference between each electric field intensity data point and the arithmetic mean; The ratio of the sum of the squared differences to the total number of electric field strength data points is used as the statistical variance of the electric field strength at each point within the grid sub-region.

[0028] The formula for calculating the overall charge non-uniformity is as follows: ; In the formula, The overall charge non-uniformity, The contribution of the dispersion of the internal charge distribution to the non-uniformity. This is the first non-uniformity index. The contribution of neighborhood variance when both internal variance and neighborhood variance are large. This is the second non-uniformity index.

[0029] The comprehensive charge nonuniformity is a comprehensive quantitative value obtained by weighted fusion of electric field distribution data between the back electrodes of the IBC module, after grid sub-region division and calculation of two types of nonuniformity indices. The value is determined by the contribution of the dispersion of the internal charge distribution to the nonuniformity, the first nonuniformity index, the contribution of the neighborhood difference when the internal variance and the neighborhood difference are both large, and the second nonuniformity index.

[0030] The contribution of the dispersion of internal charge distribution to non-uniformity is based on the physical layout characteristics of the finger electrodes on the back of the IBC module, combined with the inherent correlation between electric field intensity distribution and charge distribution. It is a fixed weight value determined after data fitting and multiple validity verifications based on a large amount of measured data of charge distribution of IBC module and electric field simulation analysis results. The core basis for setting this value is the proportion of the influence of the dispersion of internal charge distribution on the non-uniformity of charge in local areas.

[0031] The first non-uniformity index is the statistical variance of the electric field intensity at each point within the grid sub-region. It is obtained by extracting all electric field intensity data points belonging to the grid sub-region based on the spatial coordinate range of the grid sub-region, calculating the arithmetic mean of all data points, then calculating the squared difference between each data point and the arithmetic mean, and finally dividing the sum of all squared differences by the total number of electric field intensity data points. It is a quantitative index that directly reflects the discreteness of the electric field distribution within the grid sub-region, and thus characterizes the degree of discreteness of the internal charge distribution.

[0032] When both internal variance and neighborhood variance are large, the contribution of neighborhood variance is determined based on the influence of neighborhood variance on the local charge distribution of the IBC module. It combines the interaction characteristics when internal charge distribution dispersion and neighborhood charge distribution variance coexist. The fixed weight value was determined after fitting and validity verification of a large number of measured and simulated data of IBC modules. The core basis for setting this value is the proportion of the additional influence of neighborhood variance on the non-uniformity of local charge when internal dispersion is large.

[0033] The second non-uniformity index is the absolute value of the difference between the average electric field intensity of a grid sub-region and all its adjacent grid sub-regions. It is obtained by determining the adjacent grid sub-regions of the grid sub-region, calculating the average electric field intensity of the grid sub-region and all its adjacent grid sub-regions respectively, calculating the difference between the average electric field intensity of the grid sub-region and each of its adjacent grid sub-regions and taking the absolute value, and then dividing the sum of all the absolute values ​​by the total number of adjacent grid sub-regions. It is a quantitative index that directly reflects the difference in electric field distribution between the grid sub-region and its neighboring regions, and thus characterizes the degree of difference in charge distribution in the neighborhood.

[0034] This formula is a quantitative calculation method for weighted fusion of two types of charge non-uniformity indices in the IBC module grid sub-region. It combines the first non-uniformity index, which reflects the discreteness of charge distribution within the grid sub-region, and the second non-uniformity index, which reflects the difference in charge distribution between the grid sub-region and its neighbors, thus overcoming the limitations of single-index representation. The contribution of the discreteness of the internal charge distribution to the non-uniformity is assigned an appropriate weight to the first non-uniformity index, highlighting the core influence of the discreteness of the internal charge distribution on the comprehensive charge non-uniformity of the grid sub-region, which conforms to the inherent law of charge distribution in the IBC module.

[0035] When both internal variance and neighborhood variance are large, the contribution of neighborhood variance is assigned an appropriate weight to the second non-uniformity index. This takes into account the additional impact of neighborhood charge distribution differences on the comprehensive charge non-uniformity of the grid sub-region when the internal charge distribution dispersion is large, making the quantization results more consistent with the actual charge distribution state of the IBC module.

[0036] The comprehensive charge nonuniformity calculated by this formula can comprehensively and accurately quantify the degree of charge nonuniformity in each grid sub-region of the IBC module. It provides a unified and effective quantitative basis for the subsequent collection of comprehensive charge nonuniformity in all grid sub-regions and the acquisition of charge nonuniformity distribution in each local region within the IBC module. It is a key quantitative calculation link connecting electric field distribution data and charge nonuniformity distribution.

[0037] First, determine the actual length of the back-side finger electrodes, the width of a single electrode, and the center-to-center distance between two adjacent finger electrodes. Use half the center-to-center distance between adjacent back-side finger electrodes as the side length of the rectangular grid sub-region. According to the arrangement direction of the back-side finger electrodes, uniformly divide the entire measurement area corresponding to the electric field distribution data into multiple rectangular grid sub-regions. During the division process, ensure that each grid sub-region falls completely within the measurement area and does not cross the boundary of any back-side finger electrode. At the same time, ensure that all grid sub-regions are connected to each other, with no overlapping parts and no gaps. After the division is completed, each grid sub-region corresponds to a unique spatial location range, thus obtaining all the divided grid sub-regions.

[0038] For each predefined grid sub-region, the electric field intensity values ​​corresponding to all measurement points within that sub-region are extracted one by one. First, all extracted electric field intensity values ​​within the sub-region are summed. Then, the summation result is divided by the total number of measurement points within the sub-region to obtain the average electric field intensity at each point within the sub-region. Next, the difference between the electric field intensity value at each measurement point within the sub-region and the above average value is calculated one by one. Each calculated difference is squared. Then, all squared differences are summed. Finally, the summation result is divided by the total number of measurement points within the sub-region. The result is the statistical variance of the electric field intensity at each point within the sub-region. This statistical variance is the first non-uniformity index of the sub-region.

[0039] For each grid sub-region, its adjacent grid sub-regions are first determined. Adjacent grid sub-regions refer only to those grid sub-regions that are in direct contact with the current grid sub-region in the horizontal or vertical direction, with completely overlapping boundaries and no gaps, excluding grid sub-regions that are in contact diagonally. Then, following the method for extracting the average electric field intensity of a single grid sub-region, the average electric field intensity of the current grid sub-region and the average electric field intensity of each of its adjacent grid sub-regions are calculated. Then, the difference between the average electric field intensity of the current grid sub-region and the average electric field intensity of each of its adjacent grid sub-regions is calculated one by one. The absolute value of each difference is taken, and then all the differences after taking the absolute value are summed. Finally, the summation result is divided by the total number of adjacent grid sub-regions of the current grid sub-region. The result is the absolute value of the difference between the average electric field intensity of the current grid sub-region and all its adjacent grid sub-regions. This value is the second non-uniformity index of the current grid sub-region.

[0040] For each grid sub-region, the weight of the first non-uniformity index is pre-set to 0.6 and the weight of the second non-uniformity index is set to 0.4. The basis for this weight setting is that the first non-uniformity index reflects the uniformity of the electric field distribution inside the grid sub-region and has a greater impact on charge non-uniformity, while the second non-uniformity index reflects the difference in electric field between the grid sub-region and the surrounding region and has a relatively smaller impact. The sum of the weights of the two is 1. First, the first non-uniformity index corresponding to the grid sub-region is multiplied by 0.6 to obtain the first weighted result. Then, the second non-uniformity index corresponding to the grid sub-region is multiplied by 0.4 to obtain the second weighted result. The first weighted result and the second weighted result are summed. The summed value is the comprehensive charge non-uniformity of the grid sub-region.

[0041] The comprehensive charge non-uniformity corresponding to all grid sub-regions is extracted one by one. Each comprehensive charge non-uniformity is bound to the spatial coordinate range of its corresponding grid sub-region to ensure that each grid sub-region has a unique comprehensive charge non-uniformity. Then, according to the spatial arrangement order of the grid sub-regions in the measurement area on the back of the IBC module, all comprehensive charge non-uniformities bound to spatial coordinate ranges are sorted in an orderly manner. The sorted complete data set is the charge non-uniformity distribution of each local region in the IBC module.

[0042] Based on the spatial coordinate range of the current grid sub-region, which is a fixed rectangular coordinate interval set when dividing the grid sub-region, the spatial coordinates of all electric field intensity data points in the electric field distribution data are checked one by one to determine whether their coordinates fall completely within the rectangular coordinate interval. All electric field intensity data points whose coordinates meet the judgment condition are filtered out. After the filtering is completed, all the filtered data points are uniformly collected. All the collected data points are the electric field intensity data points belonging to the current grid sub-region.

[0043] For all electric field intensity data points belonging to the current grid sub-region after aggregation, the electric field intensity values ​​are extracted one by one. All extracted electric field intensity values ​​are accumulated sequentially until all electric field intensity values ​​are accumulated, and the sum of all electric field intensity values ​​is obtained. At the same time, the number of aggregated electric field intensity data points is accurately counted to obtain the total number of electric field intensity data points. The sum of the accumulated values ​​is divided by the total number of electric field intensity data points, and the result is the arithmetic mean of all electric field intensity data points.

[0044] Each electric field intensity data point belonging to the current grid sub-region is selected one by one. The electric field intensity value corresponding to the data point is extracted. The electric field intensity value is subtracted from the calculated arithmetic mean to obtain the difference between the individual electric field intensity data point and the arithmetic mean. The difference of each calculated difference is squared to make the processed values ​​non-negative. After the difference calculation and squaring of all electric field intensity data points in the current grid sub-region are completed, each data point corresponds to a unique squared difference result. Finally, the squared difference corresponding to each of the electric field intensity data points is obtained.

[0045] The squared differences of all electric field intensity data points within the current grid sub-region are sequentially summed. After summing all the squared differences, the sum of the squared differences is obtained. This sum of squared differences is then divided by the total number of electric field intensity data points. The result is the statistical variance of the electric field intensity at each point within the grid sub-region. This statistical variance is directly used as the first non-uniformity index of the grid sub-region.

[0046] The beneficial effects are as follows: by accurately defining the relevant physical characteristics of the back-side finger electrodes and rationally dividing the grid sub-regions, the grid sub-regions are ensured to be reasonably laid out and fit the measurement area and electrode boundary. Then, by standardizing the extraction of electric field intensity data points belonging to each grid sub-region, the arithmetic mean, squared difference, and statistical variance of the electric field intensity data points are accurately calculated to obtain the first non-uniformity index that accurately reflects the dispersion of the electric field distribution within the grid sub-region. At the same time, adjacent grid sub-regions are standardized and the second non-uniformity index that reflects the difference between the electric field of the grid sub-region and the neighboring area is accurately calculated. By reasonably setting weights, the two types of non-uniformity indices are weighted and fused to obtain the comprehensive charge non-uniformity that can comprehensively quantify the degree of charge non-uniformity in the grid sub-regions. The comprehensive charge non-uniformity is bound to the spatial coordinate range of the corresponding grid sub-region and organized in an orderly manner. Finally, the charge non-uniformity distribution that can accurately characterize the charge non-uniformity state of each local area within the IBC module is obtained. This effectively ensures the accuracy, standardization, and reproducibility of charge non-uniformity distribution measurement and calculation, and fully makes up for the limitations of single index characterization, providing a reliable quantitative basis for subsequent analysis of IBC module related characteristics.

[0047] S3. Based on the charge non-uniformity distribution and the preset charge accumulation threshold, identify high-risk sub-regions of potential-induced decay in the IBC module; In this embodiment of the invention, identifying high-risk sub-regions of potential-induced decay in the IBC module based on the charge non-uniformity distribution and a preset charge accumulation threshold includes: Traverse the charge non-uniformity distribution to obtain the comprehensive charge non-uniformity corresponding to each grid sub-region; Each comprehensive charge non-uniformity is compared with a preset charge accumulation threshold one by one; The grid sub-regions whose overall charge non-uniformity is greater than the preset charge accumulation threshold are marked as preliminary high-risk areas; Spatial clustering is performed on the initial high-risk areas to obtain continuous high-risk areas; The continuous high-risk areas with an area greater than the preset minimum area threshold are ultimately determined as high-risk sub-regions of potential-induced decay in the IBC module.

[0048] According to the spatial arrangement order of the grid sub-regions in the charge non-uniformity distribution of each local area within the IBC module, the charge non-uniformity distribution is enumerated and traversed one by one. The spatial coordinate range of each grid sub-region and its associated comprehensive charge non-uniformity value are extracted one by one. This ensures that the traversal process covers all grid sub-regions in the charge non-uniformity distribution without repeated extraction, and finally, the comprehensive charge non-uniformity corresponding to each grid sub-region is obtained completely.

[0049] The preset charge accumulation threshold is based on a large amount of measured data on potential-induced decay of IBC modules. It combines the inherent correlation between charge non-uniformity and the risk of potential-induced decay, and uses a fixed judgment value determined by the physical layout characteristics of the finger electrodes on the back of the IBC module. The comprehensive charge non-uniformity value corresponding to each grid sub-region is compared with this preset charge accumulation threshold one by one. The comparison results for each grid sub-region are recorded to ensure no omissions or duplications. Based on the recorded comparison results, grid sub-regions with comprehensive charge non-uniformity values ​​greater than the preset charge accumulation threshold are marked as high-risk by labeling their unique spatial coordinate range. All grid sub-regions marked as high-risk are then uniformly aggregated, and the resulting set of all aggregated grid sub-regions constitutes the initial high-risk area.

[0050] Using the spatial adjacency of grid sub-regions as the sole clustering criterion, spatial clustering operations are performed on the initial high-risk areas. Only marked grid sub-regions that are directly in contact in the horizontal or vertical direction and whose boundaries completely overlap are spatially merged. Individual marked grid sub-regions without any adjacent marked grid sub-regions remain independent. All merged grid sub-region groups and the individual marked grid sub-regions that remain independent each form an independent region, and each of these independent regions is a continuous high-risk area.

[0051] The preset minimum area threshold is an area determination value based on the actual occurrence law of potential-induced decay in the IBC module. This threshold is set on the premise that small areas of charge accumulation will not cause actual potential-induced decay risk, and it is adapted to the linewidth of the finger electrodes on the back of the IBC module and the fixed side length of the grid sub-regions. First, the specific number of grid sub-regions contained in each continuous high-risk region is counted. This number is multiplied by the fixed area of ​​a single grid sub-region to obtain the actual occupied area of ​​each continuous high-risk region. Then, the actual occupied area of ​​each continuous high-risk region is compared with the preset minimum area threshold. Continuous high-risk regions that are determined to have an actual occupied area greater than the preset minimum area threshold are finally identified as high-risk sub-regions of potential-induced decay in the IBC module.

[0052] The beneficial effects are as follows: by traversing the charge non-uniformity distribution in spatial order, the comprehensive charge non-uniformity corresponding to each grid sub-region is fully obtained. Combined with the characteristics of the IBC module and based on sufficient preset charge aggregation thresholds, each region is compared one by one to accurately mark and collect the initial high-risk regions. Then, based on spatial adjacency, the initial high-risk regions are scientifically clustered to obtain continuous high-risk regions. At the same time, based on the actual occurrence law of potential-induced decay, a preset minimum area threshold is set. By calculating the actual area of ​​continuous high-risk regions and comparing and filtering, the high-risk sub-regions of potential-induced decay in the IBC module are finally accurately determined. This effectively avoids misjudgment and omission, ensuring that the identified high-risk sub-regions are consistent with the actual risk status. This provides accurate and reliable regional positioning basis for the subsequent prevention and optimization of potential-induced decay in the IBC module, and ensures the standardization and reproducibility of the identification process.

[0053] S4. Determine the repair voltage parameters applied to the back finger electrode corresponding to the high-risk sub-region based on the charge non-uniformity of the high-risk sub-region. In this embodiment of the invention, determining the repair voltage parameters applied to the back finger electrode corresponding to the high-risk sub-region based on the charge non-uniformity corresponding to the high-risk sub-region includes: Obtain the maximum value of the comprehensive charge nonuniformity in all grid sub-regions within the high-risk sub-region; Based on the maximum value and the predefined voltage amplitude mapping relationship, the initial voltage amplitude applied to the back finger electrode corresponding to the high-risk sub-region is determined; Obtain the mean value of the local average electric field intensity in all grid sub-regions within the high-risk sub-region; The polarity of the repair voltage is determined based on the mean value of the local average electric field intensity. Based on the area and shape characteristics of the high-risk sub-region, the application period of the repair voltage is determined; The output is a repair voltage parameter composed of the initial voltage amplitude, the polarity, and the operating period.

[0054] The predefined voltage amplitude mapping relationship includes: Identify the maximum value of charge non-uniformity distribution in the calibration sample IBC module; Under controlled laboratory conditions, repair voltages of different amplitudes were applied to the calibration sample IBC module, and the optimal repair voltage amplitude that enables the performance recovery to reach the preset target was determined by monitoring the degree of photoelectric performance recovery of the calibration sample IBC module. A dataset is established to establish the correspondence between the maximum value of the comprehensive charge nonuniformity and the optimal repair voltage amplitude, thereby obtaining the voltage amplitude mapping relationship.

[0055] Extract the comprehensive charge non-uniformity values ​​of each of the grid sub-regions contained within the high-risk sub-region, place all extracted values ​​in the same set for comparison, and select the comprehensive charge non-uniformity value with the largest value in the set. This value is the maximum comprehensive charge non-uniformity value among all grid sub-regions in the high-risk sub-region. The extraction and comparison process ensures that all grid sub-regions in the high-risk sub-region are covered without omission.

[0056] The predefined voltage amplitude mapping relationship is based on a large amount of measured data matching the charge nonuniformity of IBC modules with the repair voltage amplitude. Combined with the inherent correlation between the degree of charge accumulation and the required repair electric field strength, the unique correspondence between the comprehensive charge nonuniformity value and the repair voltage amplitude is established after multiple validity verifications. The maximum value of the obtained comprehensive charge nonuniformity is substituted into this mapping relationship to obtain the unique corresponding voltage amplitude value, which is the initial voltage amplitude applied to the back finger electrode corresponding to the high-risk sub-region.

[0057] The local average electric field intensity value corresponding to each grid sub-region within the high-risk sub-region is extracted one by one. All extracted local average electric field intensity values ​​are summed to obtain a total sum. At the same time, the total number of grid sub-regions contained in the high-risk sub-region is counted. The sum is divided by the total number of grid sub-regions. The result is the mean of the local average electric field intensity of all grid sub-regions within the high-risk sub-region.

[0058] Based on the inherent correlation between the polarity of the electric field intensity and the polarity of charge accumulation at the finger electrodes on the back of the IBC module, the polarity of the mean of the local average electric field intensity is used as the criterion. If the mean of the local average electric field intensity is positive, the polarity of the repair voltage is set to positive; if the mean of the local average electric field intensity is negative, the polarity of the repair voltage is set to negative. This ensures that the polarity of the repair voltage matches the electric field polarity in the high-risk sub-region, thereby achieving the directional dissipation of accumulated charges. First, the number of grid sub-regions contained within a high-risk sub-region is counted. This number is then multiplied by the fixed area of ​​a single grid sub-region to obtain the actual area of ​​the high-risk sub-region. Next, the shape characteristics of the high-risk sub-regions are identified. The shape characteristics are divided into two categories: regular rectangles and irregular shapes. Regular rectangles are regions whose boundaries are completely parallel to the grid sub-region arrangement direction, while irregular shapes are regions that are not regular rectangles. Based on the correlation between the charge dissipation rate and the area and shape of the charge accumulation region, the high-risk sub-regions with regular rectangles are matched with the corresponding basic action cycle according to their actual area. The high-risk sub-regions with irregular shapes are adjusted by a fixed duration on top of the basic action cycle corresponding to the regular rectangles of the same area. The adjusted duration is the application cycle of the repair voltage.

[0059] The determined initial voltage amplitude, the polarity of the repair voltage, and the application period of the repair voltage are integrated to form a complete set of interrelated parameters. This set of parameters is directly used as the repair voltage parameter applied to the corresponding back finger electrode of the high-risk sub-region. The complete output of this set of parameters ensures that all three determined parameters are included without any omissions.

[0060] A calibration sample IBC module with specifications completely identical to the IBC module under test was selected. The length of the back finger electrodes, the width of a single electrode, the center-to-center distance between adjacent electrodes, and the dielectric constant of the calibration sample IBC module were all consistent with those of the IBC module under test. Following the same procedure as obtaining the charge non-uniformity distribution of the IBC module under test, the charge non-uniformity distribution of the calibration sample IBC module was obtained. The comprehensive charge non-uniformity values ​​corresponding to all grid sub-regions in the charge non-uniformity distribution were extracted one by one. All values ​​were compared one by one, and the comprehensive charge non-uniformity with the largest value was selected. This value is the maximum value of the charge non-uniformity distribution in the calibration sample IBC module.

[0061] The calibration sample IBC module was fixed on a dedicated laboratory testing platform. The laboratory environment was controlled to maintain a stable temperature of 25 degrees Celsius, a stable humidity of 50%, and free from electrostatic interference and external electric field interference, thus creating controllable laboratory conditions. A voltage range of 0.5 volts to 10 volts was selected, and multiple different repair voltage amplitudes were set at fixed intervals of 0.1 volts. Each repair voltage amplitude was applied individually to the finger electrodes on the back of the calibration sample IBC module. The repair voltage of each amplitude maintained the same application period. During the application process, the two core photoelectric performance parameters of the calibration sample IBC module, namely open-circuit voltage and short-circuit current, were monitored in real time. The specific values ​​of the two parameters after each repair voltage amplitude were recorded. The preset target was to restore the photoelectric performance to 95% of the initial photoelectric performance of the calibration sample IBC module before potential-induced decay. The photoelectric performance parameters after each repair voltage amplitude were compared with the initial parameters to identify all repair voltage amplitudes that could restore the photoelectric performance to the preset target. The repair voltage amplitude with the smallest value was selected as the optimal repair voltage amplitude to restore the performance to the preset target.

[0062] Fifty calibration sample IBC modules with specifications consistent with the IBC module under test were selected. The above two steps were repeated for each calibration sample IBC module to obtain the maximum value of charge non-uniformity distribution and the optimal repair voltage amplitude for each calibration sample IBC module, forming 50 sets of one-to-one numerical pairs. All numerical pairs were arranged in ascending order of the maximum value of charge non-uniformity distribution. Abnormal numerical pairs found during the arrangement process were removed. The criterion for judging abnormal numerical pairs was that the optimal repair voltage amplitude exceeded the preset range of 0.5 V to 10 V. Valid numerical pairs were retained and organized into a complete correspondence dataset. This correspondence dataset is the correspondence dataset between the maximum value of comprehensive charge non-uniformity and the optimal repair voltage amplitude. This dataset is directly used as a predefined voltage amplitude mapping relationship for subsequent matching of the initial voltage amplitude based on the maximum value of comprehensive charge non-uniformity in the high-risk sub-region of the IBC module under test.

[0063] The beneficial effects are as follows: By accurately extracting the comprehensive charge non-uniformity values ​​of all grid sub-regions within the high-risk sub-region and selecting the maximum value, combined with a reliable voltage amplitude mapping relationship established after testing and determining the optimal repair voltage amplitude under strict laboratory control conditions using a large number of calibrated IBC modules with consistent specifications, the initial voltage amplitude suitable for the high-risk sub-region is accurately matched. Then, the mean value of the local average electric field intensity within the high-risk sub-region is obtained through reasonable calculation, thereby determining the polarity of the repair voltage that can achieve the directional dissipation of accumulated charges. At the same time, combined with the actual area and shape characteristics of the high-risk sub-region, the repair voltage application period suitable for the charge dissipation rate is determined, and the three... The system integrates and outputs complete repair voltage parameters, ensuring that the repair voltage parameters are accurately matched with the actual charge accumulation in high-risk sub-regions. The establishment of the voltage amplitude mapping relationship is ensured through standardized calibration sample testing, abnormal data removal, and orderly sorting, guaranteeing the reliability and uniqueness of the mapping relationship. This, in turn, ensures the accuracy and rationality of the repair voltage parameters. The entire process of determining the repair voltage parameters is standardized and reproducible, providing reliable voltage parameter support for the accurate repair of high-risk sub-regions of potential-induced decay in IBC modules. This effectively guarantees the repair effect, achieves directional and efficient dissipation of accumulated charge in high-risk sub-regions, and further improves the photoelectric performance stability of IBC modules.

[0064] S5. Generate a repair instruction sequence for the IBC module based on the repair voltage parameters; In this embodiment of the invention, generating the repair instruction sequence for the IBC module based on the repair voltage parameters includes: The repair voltage parameter is decomposed into three independent control fields, corresponding to the voltage amplitude field, polarity field, and action period field, respectively. Obtain the spatial coordinate encoding of the geometric center of the high-risk sub-region in the rear finger electrode layout; The spatial coordinate encoding and the three independent control fields are formatted and encapsulated to obtain a single repair instruction block corresponding to the high-risk sub-region; The execution order of the individual repair instruction blocks is determined based on the spatial distance between the multiple high-risk sub-regions and the corresponding comprehensive charge non-uniformity values. According to the execution order, multiple individual repair instruction units are sequentially connected in series, and device status query instructions are inserted between adjacent instruction units to obtain the repair instruction sequence of the IBC module.

[0065] The three core pieces of information contained in the repair voltage parameters are extracted: initial voltage amplitude, polarity of the repair voltage, and application period of the repair voltage. Each piece of information is assigned a unique field identifier that is compatible with the instruction recognition specifications of the repair execution device. At the same time, a fixed data format is set for each piece of information, which matches the information reading rules of the repair execution device. The initial voltage amplitude is combined with the corresponding field identifier and data format to form an independent voltage amplitude field. The polarity of the repair voltage is combined with the corresponding field identifier and data format to form an independent polarity field. The application period of the repair voltage is combined with the corresponding field identifier and data format to form an independent application period field. This ensures that the information in each of the three control fields is complete and can be individually identified by the repair execution device. The spatial coordinate boundaries of all grid sub-regions constituting the high-risk sub-region are determined. The overall spatial coordinate range of the high-risk sub-region is formed by these coordinate boundaries. Based on the two-dimensional rectangular coordinate system established when dividing the grid sub-regions, the two-dimensional rectangular coordinate values ​​corresponding to the geometric center of the overall spatial coordinate range are calculated. A fixed coordinate encoding rule is formulated according to the layout rules of the back finger electrodes. This encoding rule is a code form that can be recognized by the repair execution device. The two-dimensional rectangular coordinate values ​​of the geometric center are substituted into this encoding rule for conversion. The converted code contains the position information of the geometric center and the corresponding back finger electrode area information. This code is the spatial coordinate code of the geometric center of the high-risk sub-region in the layout of the back finger electrodes. A fixed encapsulation format is set to adapt to the instruction recognition requirements of the repair execution device. This encapsulation format includes a pre-identifier bit, a spatial coordinate encoding bit, a voltage amplitude field bit, a polarity field bit, an action period field bit, and a post-verification bit. The pre-identifier bit is used to identify the starting position of a single repair instruction block by the repair execution device. The post-verification bit is used to verify the integrity of the instruction block information after encapsulation. The spatial coordinate encoding corresponding to the high-risk sub-region is completely filled into the spatial coordinate encoding bit. The voltage amplitude field, polarity field, and action period field are filled into the corresponding field bits in a preset fixed order. After all information bits are filled, the integrity and matching of all information in the encapsulation format are verified. The complete data block after verification is the single repair instruction block corresponding to the high-risk sub-region.The maximum value of the comprehensive charge non-uniformity is extracted for each high-risk sub-region. All high-risk sub-regions are initially sorted in descending order of this maximum value. The individual repair instruction blocks of the high-risk sub-regions at the top of the sort are executed first. For high-risk sub-regions with the same maximum value of comprehensive charge non-uniformity in the initial sort, the spatial straight-line distance between the geometric centers of such high-risk sub-regions is calculated. The sorting of such high-risk sub-regions is adjusted in ascending order of spatial straight-line distance, so that the individual repair instruction blocks corresponding to high-risk sub-regions with close spatial distances are arranged consecutively. During the sorting process, it is ensured that the individual repair instruction block corresponding to each high-risk sub-region has a unique arrangement position. The final complete sorting result is the execution order of the multiple individual repair instruction blocks. According to the predetermined execution order, all individual repair instruction blocks corresponding to high-risk sub-regions are sequentially linked end to end to form a continuous instruction string without gaps. The device status query instruction is a preset fixed format instruction. This instruction is used to check the core operating parameters of the device, such as voltage output accuracy, electrode contact status, and power supply stability, after the device completes the execution of the previous individual repair instruction block. In the continuous instruction string, the fixed format device status query instruction is inserted at the connection position of every two adjacent individual repair instruction blocks. After insertion, the entire instruction content is checked to ensure that all individual repair instruction blocks are arranged in the execution order and that there is a device status query instruction between adjacent instruction blocks. The complete instruction content after the check passes is the repair instruction sequence of the IBC module.

[0066] The beneficial effects are as follows: By decomposing the repair voltage parameter into three independent control fields specific to and adapted to the identification specifications of the repair execution device, the system ensures accurate transmission of repair voltage-related information and allows for individual device identification. Furthermore, the system obtains the spatial coordinate encoding of the geometric center of the high-risk sub-region through specifications and completes format encapsulation. Combined with a verification mechanism, this ensures the integrity and accuracy of individual repair instruction blocks, giving each high-risk sub-region a dedicated and reliable individual repair instruction block. This achieves precise positioning of high-risk sub-regions and accurate matching of repair parameters. By combining the maximum value of comprehensive charge non-uniformity and spatial distance to determine the execution order of individual repair instruction blocks, the system prioritizes the repair of areas with high charge concentration while ensuring continuous repair of spatially proximate areas, effectively improving repair efficiency and avoiding poor repair results caused by an unreasonable repair order. Inserting device status query commands between adjacent individual repair command blocks enables real-time self-checking of the core operating parameters of the repair execution device, timely troubleshooting of device malfunctions, and ensuring the stability and accuracy of the repair process. Finally, through orderly serialization and full-process inspection, a complete repair command sequence is generated, ensuring that the command sequence is standardized, executable, and without missing information. This provides reliable command support for the accurate, orderly, and stable repair of high-risk sub-regions of the IBC module, further guaranteeing the repair effect, promoting the efficient recovery of the photoelectric performance of the IBC module, and improving the reliability and reproducibility of the repair process.

[0067] In this embodiment of the invention, S6, selective and time-sequential local repair processing is performed on the high-risk sub-region according to the repair instruction sequence.

[0068] The repair instruction sequence is imported into the instruction parsing module of the repair execution device. This module reads the instruction content segment by segment according to the order of the repair instruction sequence, accurately identifies and separates the device status query instruction from all individual repair instruction blocks, and parses the internal spatial coordinate code, voltage amplitude field, polarity field, and action period field of each individual repair instruction block according to a preset encapsulation format. At the same time, the integrity of all parsed field information is checked. The verification criteria are that the field information is not missing and the field format completely matches the identification specification of the repair execution device. After the verification is passed, the parsing results are stored in an orderly manner according to the execution order of the individual repair instruction blocks, ensuring that the parsed information of each individual repair instruction block corresponds one-to-one with the corresponding high-risk sub-region.

[0069] The repair execution device uses the spatial coordinate encoding of the first single repair instruction block stored in an orderly manner to convert it into the corresponding two-dimensional rectangular coordinate value according to the coordinate encoding rules of the back finger electrode layout. This value is the physical position coordinate of the geometric center of the high-risk sub-region on the test platform. The device drives the voltage output terminal to move along the guide rail of the test platform to this physical position coordinate, so that the voltage output terminal makes precise contact with the back finger electrode at the corresponding position. After the contact is completed, the contact status is verified by the contact detection module of the device. The verification standard is that the contact resistance value between the voltage output terminal and the electrode is within the preset normal contact resistance range. After the verification is passed, the physical positioning of the first high-risk sub-region is completed, realizing the selective positioning requirement of repair.

[0070] The repair execution device extracts the core parameters of voltage amplitude, polarity, and action period fields from the parsed information of the first single repair instruction block. It adjusts the device's voltage output module to the corresponding output amplitude according to the parameters of the voltage amplitude field, and sets the output polarity of the voltage output module according to the parameters of the polarity field. After the parameter setting is completed, the voltage output module is started, and the repair voltage is continuously applied to the back finger electrode corresponding to the high-risk sub-region that has been located. During the application process, the device's real-time monitoring module continuously collects the actual amplitude and polarity of the voltage output to ensure that the actual output parameters are completely consistent with the set parameters, and that the application duration is completely matched with the parameters of the action period field. The output of the repair voltage is stopped after the preset action period is reached, thus completing the local repair treatment of the first high-risk sub-region. After the local repair of the first high-risk sub-area is completed, the repair execution equipment executes subsequent equipment status query commands in the order of the repair command sequence. The equipment's self-test module is then activated to comprehensively test core operating parameters such as voltage output accuracy, electrode contact status, and power supply stability, and obtain the actual test values ​​of each parameter. All actual test values ​​are compared one by one with the normal operating threshold calibrated by the equipment at the factory. This threshold is the qualified range of equipment operating parameters to ensure the repair effect. If all actual test values ​​are within the normal operating threshold, the equipment is judged to be in normal condition. If any actual test value exceeds the normal operating threshold, the repair process is stopped immediately and an equipment abnormality warning signal is issued. The subsequent commands are executed again after the equipment fault is eliminated and the verification is qualified.

[0071] After the repair execution device determines that its own status is normal, it retrieves the parsing information of the next single repair instruction block stored in an ordered manner, and repeatedly executes operations such as reverse conversion of spatial coordinate encoding, physical positioning and contact status verification of voltage output terminal, parameter setting and application of repair voltage, and real-time monitoring of repair voltage output. According to the parameters of the single repair instruction block, it performs selective local repair processing on the corresponding next high-risk sub-region, and the repair processing of the high-risk sub-region strictly follows the order of execution of the repair instruction sequence to achieve the time-sequential requirements of repair. After each local repair processing of a high-risk sub-region is completed, the device status query instruction is executed once according to the setting of the repair instruction sequence to complete a comprehensive verification of the device status. The device to be repaired executes the local repair processing of all high-risk sub-regions corresponding to individual repair instruction blocks in the order of the repair instruction sequence. After the device status is determined to be normal throughout the process, the device drive voltage output terminal moves to the initial reset position of the test platform to complete the device reset operation. Then, using the same scanning parameters and scanning method as when acquiring the initial electric field distribution data of the IBC module, the electric field distribution data of all high-risk sub-regions that have been repaired are re-acquired. The acquisition process ensures that all grid sub-regions of the high-risk sub-regions are covered, providing corresponding electric field distribution data for subsequent verification of the repair effect, thus completing the entire selective and time-sequential local repair processing flow.

[0072] The beneficial effects include: by accurately parsing, verifying, and storing the repair instruction sequence in an orderly manner, ensuring the completeness of information in each individual repair instruction block and its precise correspondence with the corresponding high-risk sub-region, a solid foundation is laid for selective and sequential repair. Through standardized spatial coordinate encoding reverse conversion, physical positioning, and contact status verification, the repair execution equipment achieves precise selective positioning of high-risk sub-regions, ensuring that the repair voltage only acts on the target area and avoids unnecessary impact on non-high-risk areas. By strictly adjusting the voltage output according to the repair instruction parameters and monitoring the output status in real time, the accuracy of local repair processing is guaranteed, ensuring that the repair effect meets the expected requirements. By performing equipment status queries and comprehensive self-checks between adjacent repair steps, equipment malfunctions are promptly identified, ensuring the stability and continuity of the repair process and avoiding repair deviations caused by equipment failures. By sequentially executing the repair operations of all high-risk sub-regions according to the order of the repair instruction sequence, areas with high charge accumulation are prioritized, effectively improving repair efficiency. Simultaneously, after repair, equipment reset and re-collection of electric field distribution data in high-risk sub-regions provide a reliable basis for verifying the repair effect. The entire process is standardized and reproducible, effectively achieving precise and orderly repair of high-risk sub-regions of the IBC module, restoring the module's optoelectronic performance to normal levels, ensuring the long-term operational stability of the module, and avoiding ineffective operations and secondary damage during the repair process.

[0073] like Figure 2The diagram shown is a functional block diagram of an IBC module potential-induced decay suppression optimization system provided in an embodiment of the present invention.

[0074] The IBC module potential-induced decay suppression optimization system 100 described in this invention can be installed in an electronic device. Depending on the functions implemented, the IBC module potential-induced decay suppression optimization system 100 may include an electric field distribution acquisition module 101, a charge non-uniformity distribution acquisition module 102, a risk identification module 103, a repair voltage calibration module 104, a repair instruction generation module 105, and a repair module 106. The module described in this invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and are stored in the memory of the electronic device.

[0075] In this embodiment, the functions of each module / unit are as follows: The electric field distribution acquisition module 101 is used to acquire electric field distribution data between the back electrodes of the IBC module under a preset bias voltage. The charge non-uniformity distribution acquisition module 102 is used to calculate the charge non-uniformity distribution of each local region within the IBC module based on the electric field distribution data. The risk identification module 103 is used to identify high-risk sub-regions of potential-induced decay in the IBC module based on the charge non-uniformity distribution and a preset charge accumulation threshold. The repair voltage calibration module 104 is used to determine the repair voltage parameters applied to the back finger electrode corresponding to the high-risk sub-region based on the charge non-uniformity corresponding to the high-risk sub-region. The repair instruction generation module 105 is used to generate a repair instruction sequence for the IBC module based on the repair voltage parameters. The repair module 106 is used to perform selective and time-sequential local repair processing on the high-risk sub-region according to the repair instruction sequence.

[0076] In the several embodiments provided by this invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0077] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0078] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0079] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0080] This application embodiment can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0081] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for optimizing the suppression of potential-induced decay in an IBC module, characterized in that, The method includes: S1. Obtain the electric field distribution data between the back electrodes of the IBC module under a preset bias voltage; S2. Calculate the charge non-uniformity distribution in each local region within the IBC module based on the electric field distribution data; S3. Based on the charge non-uniformity distribution and the preset charge accumulation threshold, identify high-risk sub-regions of potential-induced decay in the IBC module; S4. Determine the repair voltage parameters applied to the back finger electrode corresponding to the high-risk sub-region based on the charge non-uniformity of the high-risk sub-region. S5. Generate a repair instruction sequence for the IBC module based on the repair voltage parameters; S6. Based on the repair instruction sequence, perform selective and time-sequential local repair processing on the high-risk sub-region.

2. The method for optimizing the suppression of potential-induced decay in an IBC module as described in claim 1, characterized in that, The acquisition of electric field distribution data between the back electrodes of the IBC module under a preset bias voltage includes: The surface of the finger electrodes on the back of the IBC module under a preset bias voltage is scanned to obtain the relative potential difference of each measurement point in the IBC module. By correlating the relative potential difference with the spatial coordinates of the back finger electrode surface, preliminary potential distribution data between the back electrodes are obtained; Based on the known dielectric constant of the IBC module, environmental interference compensation is performed on the preliminary potential distribution data to obtain corrected potential distribution data; The corrected potential distribution data is spatially interpolated on the surface of the back finger electrodes to obtain the electric field distribution data between the back electrodes.

3. The method for optimizing the suppression of potential-induced decay in an IBC module as described in claim 1, characterized in that, The step of calculating the charge non-uniformity distribution in each local region within the IBC module based on the electric field distribution data includes: Based on the physical layout of the finger electrodes on the back, the measurement area corresponding to the electric field distribution data is divided into grid sub-regions; The statistical variance of the electric field intensity at each point within the grid sub-region is used as the first non-uniformity index of the grid sub-region. The absolute value of the difference in average electric field intensity between the grid sub-region and all its adjacent grid sub-regions is used as the second non-uniformity index of the grid sub-region. The first non-uniformity index and the second non-uniformity index corresponding to the grid sub-region are weighted and fused to generate the comprehensive charge non-uniformity of the grid sub-region; By aggregating all the aforementioned combined charge nonuniformity, the charge nonuniformity distribution of each local region within the IBC module is obtained.

4. The method for optimizing the suppression of potential-induced decay in an IBC module as described in claim 3, characterized in that, The step of using the statistical variance of the electric field intensity at each point within the grid sub-region as the first non-uniformity index of the grid sub-region includes: Extract all electric field intensity data points belonging to the current grid sub-region; Calculate the arithmetic mean of all the electric field intensity data points; Calculate the squared difference between each electric field intensity data point and the arithmetic mean; The ratio of the sum of the squared differences to the total number of electric field strength data points is used as the statistical variance of the electric field strength at each point within the grid sub-region.

5. The method for optimizing the suppression of potential-induced decay in an IBC module as described in claim 3, characterized in that, The formula for calculating the overall charge non-uniformity is as follows: ； In the formula, The overall charge non-uniformity, The contribution of the dispersion of the internal charge distribution to the non-uniformity. This is the first non-uniformity index. The contribution of neighborhood variance when both internal variance and neighborhood variance are large. This is the second non-uniformity index.

6. The method for optimizing the suppression of potential-induced decay in an IBC module as described in claim 1, characterized in that, The step of identifying high-risk sub-regions of potential-induced decay in the IBC module based on the charge non-uniformity distribution and a preset charge accumulation threshold includes: Traverse the charge non-uniformity distribution to obtain the comprehensive charge non-uniformity corresponding to each grid sub-region; Each comprehensive charge non-uniformity is compared with a preset charge accumulation threshold one by one; The grid sub-regions whose overall charge non-uniformity is greater than the preset charge accumulation threshold are marked as preliminary high-risk areas; Spatial clustering is performed on the initial high-risk areas to obtain continuous high-risk areas; The continuous high-risk areas with an area greater than the preset minimum area threshold are ultimately determined as high-risk sub-regions of potential-induced decay in the IBC module.

7. The method for optimizing the suppression of potential-induced decay in an IBC module as described in claim 1, characterized in that, The step of determining the repair voltage parameters applied to the back finger electrode corresponding to the high-risk sub-region based on the charge non-uniformity of the high-risk sub-region includes: Obtain the maximum value of the comprehensive charge nonuniformity in all grid sub-regions within the high-risk sub-region; Based on the maximum value and the predefined voltage amplitude mapping relationship, the initial voltage amplitude applied to the back finger electrode corresponding to the high-risk sub-region is determined; Obtain the mean value of the local average electric field intensity in all grid sub-regions within the high-risk sub-region; The polarity of the repair voltage is determined based on the mean value of the local average electric field intensity. Based on the area and shape characteristics of the high-risk sub-region, the application period of the repair voltage is determined; The output is a repair voltage parameter composed of the initial voltage amplitude, the polarity, and the operating period.

8. The method for optimizing the suppression of potential-induced decay in an IBC module as described in claim 7, characterized in that, The predefined voltage amplitude mapping relationship includes: Identify the maximum value of charge non-uniformity distribution in the calibration sample IBC module; Under controlled laboratory conditions, repair voltages of different amplitudes were applied to the calibration sample IBC module, and the optimal repair voltage amplitude that enables the performance recovery to reach the preset target was determined by monitoring the degree of photoelectric performance recovery of the calibration sample IBC module. A dataset is established to establish the correspondence between the maximum value of the comprehensive charge nonuniformity and the optimal repair voltage amplitude, thereby obtaining the voltage amplitude mapping relationship.

9. The method for optimizing the suppression of potential-induced decay in an IBC module as described in claim 1, characterized in that, The step of generating a repair instruction sequence for the IBC module based on the repair voltage parameters includes: The repair voltage parameter is decomposed into three independent control fields, corresponding to the voltage amplitude field, polarity field, and action period field, respectively. Obtain the spatial coordinate encoding of the geometric center of the high-risk sub-region in the rear finger electrode layout; The spatial coordinate encoding and the three independent control fields are formatted and encapsulated to obtain a single repair instruction block corresponding to the high-risk sub-region; The execution order of the individual repair instruction blocks is determined based on the spatial distance between the multiple high-risk sub-regions and the corresponding comprehensive charge non-uniformity values. According to the execution order, multiple individual repair instruction units are sequentially connected in series, and device status query instructions are inserted between adjacent instruction units to obtain the repair instruction sequence of the IBC module.

10. An IBC module potential-induced decay suppression optimization system, used to implement the IBC module potential-induced decay suppression optimization method according to claim 1, the system comprising: The electric field distribution acquisition module is used to acquire the electric field distribution data between the back electrodes of the IBC module under a preset bias voltage. The charge non-uniformity distribution acquisition module is used to calculate the charge non-uniformity distribution of each local region within the IBC module based on the electric field distribution data. The risk identification module is used to identify high-risk sub-regions of potential-induced decay in the IBC module based on the charge non-uniformity distribution and a preset charge accumulation threshold. The repair voltage calibration module is used to determine the repair voltage parameters applied to the back finger electrode corresponding to the high-risk sub-region based on the charge non-uniformity corresponding to the high-risk sub-region. A repair instruction generation module is used to generate a repair instruction sequence for the IBC module based on the repair voltage parameters. The repair module is used to perform selective and time-sequential local repair processing on the high-risk sub-regions according to the repair instruction sequence.

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