Battery manufacturing process optimization methods, devices, equipment and storage media

Abstract

This invention belongs to the field of battery manufacturing technology and discloses a method, apparatus, equipment, and storage medium for optimizing battery manufacturing processes. The method includes: determining a first and a second production process route based on cell-level traceability of battery production; comparing the differences in processes and parameters between the first and second production process routes; adjusting the second production process route based on the differences in processes and parameters, using the first production process route as a benchmark; detecting the proportion of high-efficiency battery cells corresponding to the adjusted second production process route; and optimizing the battery manufacturing process by using the first production process route as the target production process route when the proportion of high-efficiency battery cells corresponding to the adjusted second production process route meets preset conditions. This method can more accurately locate the relatively optimal equipment and process parameter range for each process, improving the optimization effect by utilizing precise process parameters.

Description

Technical Field

[0001] This invention relates to the field of battery manufacturing technology, and in particular to a method, apparatus, equipment, and storage medium for optimizing battery manufacturing processes. Background Technology

[0002] In the current photovoltaic solar cell industry, photoelectric conversion efficiency (hereinafter referred to as efficiency) is a very important indicator of cell quality. Cell efficiency can only be obtained in the final process of finished product IV testing (electrical performance testing). Traditional cell manufacturing plants lack cell-level data traceability capabilities, which leads to delays in process adjustments, affecting cell efficiency. It is difficult to accurately locate abnormal parameters in problematic processes, and it is difficult to quickly find an effective way to analyze the optimal range of parameter configurations for each piece of equipment through the test results. Current methods can only adjust to a relatively reasonable parameter range through experiments, and then select some parameters within this range to optimize the cell production process. However, these parameters are not optimal, resulting in the final optimization effect not meeting expectations.

[0003] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0004] The main objective of this invention is to provide a method, apparatus, equipment, and storage medium for optimizing battery manufacturing processes. The aim is to address the technical problem that previous methods could only adjust to a relatively reasonable parameter range through experiments, and then select some parameters within this range to optimize the battery manufacturing process. However, these parameters were not optimal, resulting in the final optimization effect not meeting expectations.

[0005] To achieve the above objectives, the present invention provides a method for optimizing a battery manufacturing process, the method comprising the following steps: The first and second production process routes are determined based on cell-level traceability of battery production, wherein the proportion of high-efficiency battery cells corresponding to the first production process route is greater than the proportion of high-efficiency battery cells corresponding to the second production process route. Compare the different processes and process parameters between the first production process route and the second production process route; Based on the first production process route, the second production process route is adjusted according to the different processes and the different process parameters; The proportion of high-efficiency solar cells corresponding to the adjusted second production process route is detected. If the proportion of high-efficiency solar cells corresponding to the adjusted second production process route meets the preset conditions, the first production process route is taken as the target production process route. Optimize the battery manufacturing process based on the steps and process parameters of the target production process route.

[0006] In some embodiments, the determination of the first and second production process routes based on cell-level traceability of battery production includes: Query the percentage of high-efficiency solar cells in the test and sorting process within a preset time period, and select the test and sorting line equipment with the highest percentage as the first line equipment; The high-efficiency solar cell is traced in reverse to determine the production path of all processes before testing and sorting. The distribution of high-efficiency cell production line equipment in each process is analyzed sequentially from front to back along the production path. The production line equipment with the highest proportion of high-efficiency cells in each process is selected and connected in series to form the first production process route. Query the percentage of low-efficiency solar cells in the test sorting process within a preset time period, and select the test sorting line equipment with the highest percentage as the second line equipment for that process; The inefficient cells are traced in reverse to determine the production path of all processes before testing and sorting. The production line equipment with the highest efficiency of inefficient cells in each process is selected and connected in series to form a second production process route.

[0007] In some embodiments, the first production line includes an optimal printing production line, an optimal backsheet production line, and an optimal furnace tube production line. The step of querying the percentage of high-efficiency solar cells in the test sorting process within a preset time period and selecting the test sorting line with the highest percentage as the first production line includes: Determine the distribution of high-efficiency solar cells from the test sorting line equipment in the printing process, and identify the line equipment with the highest proportion as the optimal printing line equipment; Determine the distribution of high-efficiency solar cells in each backsheet line for testing and sorting, and identify the line with the highest percentage as the optimal backsheet line. The distribution of high-efficiency solar cells in each furnace tube was determined by the test and sorting process, and the line equipment with the highest proportion was selected as the optimal furnace tube line equipment.

[0008] In some embodiments, adjusting the second production process route based on the first production process route and the different processes and parameters includes: Based on the first production process route, adjust the processes in the second production process route that differ from each other; Based on the difference in process parameters, determine the parameters to be adjusted in the second production process route, use the parameters of the first production process route as the reference parameters, and adjust the parameters to be adjusted according to the reference parameters.

[0009] In some embodiments, the method further includes: The percentage of high-efficiency solar cells corresponding to the adjusted second production process route was measured. If the proportion of high-efficiency solar cells corresponding to the adjusted second production process route reaches a preset proportion, or if the difference between the proportion of high-efficiency solar cells corresponding to the adjusted second production process route and the proportion of high-efficiency solar cells corresponding to the original second production process route is greater than a preset difference, then it is determined that the proportion of high-efficiency solar cells corresponding to the adjusted second production process route meets the preset condition.

[0010] Furthermore, to achieve the above objectives, the present invention also proposes a battery manufacturing process optimization device, the battery manufacturing process optimization device comprising: The screening module is used to determine the first production process route and the second production process route based on the cell-level traceability of battery production, wherein the proportion of high-efficiency battery cells corresponding to the first production process route is greater than the proportion of high-efficiency battery cells corresponding to the second production process route. The comparison module is used to compare the differences in processes and process parameters between the first production process route and the second production process route. The adjustment module is used to adjust the second production process route based on the first production process route and the different processes and the different process parameters. The detection module is used to detect the proportion of high-efficiency solar cells corresponding to the adjusted second production process route. If the proportion of high-efficiency solar cells corresponding to the adjusted second production process route meets the preset conditions, the first production process route is taken as the target production process route. The optimization module is used to optimize the battery production process based on the steps and process parameters of the target production process route.

[0011] In some embodiments, the filtering module is used to query the proportion of high-efficiency battery cells in the test sorting process within a preset time period, and select the test sorting line equipment with the highest proportion as the first line equipment; The high-efficiency solar cell is traced in reverse to determine the production path of all processes before testing and sorting. The distribution of high-efficiency cell production line equipment in each process is analyzed sequentially from front to back along the production path. The production line equipment with the highest proportion of high-efficiency cells in each process is selected and connected in series to form the first production process route. Query the percentage of low-efficiency solar cells in the test sorting process within a preset time period, and select the test sorting line equipment with the highest percentage as the second line equipment for that process; The inefficient cells are traced in reverse to determine the production path of all processes before testing and sorting. The production line equipment with the highest efficiency of inefficient cells in each process is selected and connected in series to form a second production process route.

[0012] In some embodiments, the first line equipment includes a printing optimal line equipment, a back film optimal line equipment, and a furnace tube optimal line equipment. The screening module is used to determine the distribution of high-efficiency solar cells in the printing line equipment during the test and sorting process, and to select the line equipment with the highest proportion as the printing optimal line equipment. Determine the distribution of high-efficiency solar cells in each backsheet line for testing and sorting, and identify the line with the highest percentage as the optimal backsheet line. The distribution of high-efficiency solar cells in each furnace tube was determined by the test and sorting process, and the line equipment with the highest proportion was selected as the optimal furnace tube line equipment.

[0013] Furthermore, to achieve the above objectives, the present invention also proposes a battery manufacturing process optimization device, which includes: a memory, a processor, and a battery manufacturing process optimization program stored in the memory and executable on the processor. The battery manufacturing process optimization program is configured to implement the steps of the battery manufacturing process optimization method described above.

[0014] Furthermore, to achieve the above objectives, the present invention also proposes a storage medium storing a battery manufacturing process optimization program, wherein when the battery manufacturing process optimization program is executed by a processor, it implements the steps of the battery manufacturing process optimization method described above.

[0015] In this invention, a first and a second production process route are determined by cell-level traceability based on battery production; the differences in processes and parameters between the first and second production process routes are compared; the second production process route is adjusted based on the differences in processes and parameters, using the first production process route as a benchmark; the proportion of high-efficiency battery cells corresponding to the adjusted second production process route is detected; when the proportion of high-efficiency battery cells corresponding to the adjusted second production process route meets preset conditions, the first production process route is used as the target production process route to optimize the battery production process. The above method can more accurately locate the relatively optimal equipment and process parameter range for each process, and improve the optimization effect by using precise process parameters. Attached Figure Description

[0016] Figure 1 This is a schematic flowchart of the first embodiment of the battery manufacturing process optimization method of the present invention; Figure 2 This is a structural block diagram of the first embodiment of the battery manufacturing process optimization device of the present invention.

[0017] 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 for illustrative purposes only and are not intended to limit the scope of the invention.

[0019] This invention provides a method for optimizing battery manufacturing processes, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of a battery manufacturing process optimization method according to the present invention.

[0020] In this embodiment, the battery manufacturing process optimization method includes the following steps: Step S10: Determine the first and second production process routes based on cell-level traceability of battery production.

[0021] In this embodiment, the execution subject is a battery production process optimization device, which has functions such as data processing, data communication, and program execution. The battery production process optimization device can be a computer terminal device or other network device, or other devices with similar functions. This embodiment does not limit the scope of the implementation.

[0022] It should be noted that in the current photovoltaic solar cell industry, photoelectric conversion efficiency (hereinafter referred to as efficiency) is a very important indicator of cell quality. Cell efficiency can only be obtained in the final process, finished product IV testing (electrical performance testing). Traditional cell manufacturing plants lack cell-level data traceability capabilities, which leads to delays in process adjustments, affecting cell efficiency. Quality problems are difficult to pinpoint abnormal parameters in problematic processes, and it is difficult to quickly find an effective way to analyze the optimal range of parameter configurations for each piece of equipment through testing results. Current methods can only adjust to a relatively reasonable parameter range through experiments, and then select some parameters within this range to optimize the cell production process. However, these parameters are not optimal, resulting in the final optimization effect not meeting expectations.

[0023] To address the aforementioned technical issues, this embodiment determines a first and second production process route based on cell-level traceability in battery production; compares the differences in processes and parameters between the first and second production process routes; adjusts the second production process route based on the differences in processes and parameters, using the first production process route as a benchmark; detects the proportion of high-efficiency battery cells corresponding to the adjusted second production process route; and optimizes the battery production process by using the first production process route as the target production process route when the proportion of high-efficiency battery cells corresponding to the adjusted second production process route meets preset conditions. This method can more accurately locate the relatively optimal equipment and process parameter range for each process, improving the optimization effect by using precise process parameters. Specifically, it can be implemented as follows.

[0024] It should be noted that in this embodiment, when the single-cell traceability function connects the production history of the battery cell in the process, the final finished product inspection results are traced and associated with the key process parameters PV (actual value) and SV (set value) involved in the process. The analysis is conducted on the battery cells with relatively high production efficiency within a certain period of time, and the distribution of these high-efficiency battery cells in different lines of each process equipment is analyzed.

[0025] In the specific implementation, this embodiment uses wafer-level traceability to select the first and second production process routes for any time period. Specifically, it queries the proportion of high-efficiency battery cells in the test and sorting process within a preset time period and selects the test and sorting line equipment with the highest proportion as the first line equipment. The high-efficiency solar cells are traced backwards to determine the production path of all processes before testing and sorting. The distribution of production line equipment for high-efficiency solar cells in each process is analyzed sequentially from front to back along the production path. The production line equipment with the highest proportion of high-efficiency cells in each process is selected and connected in series to form the first production process route. The proportion of low-efficiency solar cells in the testing and sorting process within a preset time period is queried, and the testing and sorting line equipment with the highest proportion is selected as the second production line equipment for that process. The low-efficiency solar cells are traced backwards to determine the production path of all processes before testing and sorting. The production line equipment with the highest proportion of low-efficiency solar cells in each process is selected and connected in series to form the second production process route.

[0026] It should be noted that the first and second production process routes mentioned above represent the production process routes with the largest proportion of high-efficiency cells and the largest proportion of low-efficiency cells (i.e., the lowest proportion of high-efficiency cells), respectively. Multiple production process routes exist within the same time period, and the above method can be used to select two routes. The definition of high-efficiency cells can be determined based on actual conditions or customized according to the different shipment requirements of each manufacturer. A production process route contains a large number of cells; the aforementioned proportions can be calculated by combining the number of high-efficiency cells with the total number of cells in the production process route, which will not be elaborated upon here.

[0027] Furthermore, in this embodiment, the first production line equipment includes an optimal printing production line, an optimal backsheet production line, and an optimal furnace tube production line. The distribution of high-efficiency solar cells in the printing production line is determined, and the production line with the highest percentage is designated as the optimal printing production line. Similarly, the distribution of high-efficiency solar cells in the backsheet production line is determined, and the production line with the highest percentage is designated as the optimal backsheet production line. Finally, the distribution of high-efficiency solar cells in the furnace tubes is determined, and the production line with the highest percentage is designated as the optimal furnace tube production line. For example, query the percentage of high-efficiency sheets (high-efficiency sheets are not defined for this product and need to be customized according to the different shipping requirements of each manufacturer) of all test sorting lines within the same time period; select the line equipment with the highest percentage of high-efficiency sheets in the test sorting process; this line equipment is the optimal process line equipment for this process. Then, trace back to the line equipment of all processes before the test sorting of this batch of high-efficiency sheets, i.e., the complete production path from printing to texturing. Note that high-temperature processes and (including boron diffusion, annealing, ALD) coating processes (including Poly, positive film, and back film) using tubular equipment need to be specified down to the actual process sub-equipment - furnace tube; then, select the optimal line equipment for each test sorting process. The high-efficiency sheets from the printing equipment are analyzed to determine their distribution across printing lines. The line with the highest percentage is identified as the optimal line for that process (printing and testing / sorting are generally hard-connected, so the optimal testing / sorting line is the optimal printing line). Similarly, the high-efficiency sheets from the printing equipment are analyzed to determine their distribution across backing film lines. The line with the highest percentage is identified as the optimal backing film line. Then, the distribution of the sheets within that line across different furnace tubes is analyzed, and the line with the highest percentage is identified as the optimal line. This process is repeated to trace back to the optimal line for each process. The production chain formed by these lines is the optimal process route.

[0028] Step S20: Compare the differences in processes and process parameters between the first production process route and the second production process route.

[0029] In this embodiment, the earliest and latest times when the batch of cells passes through each device in the optimal and worst process routes are found, and the PV and SV of each process parameter of each device are found. By comparison, it can be analyzed which parameters or processes may affect the final proportion of high-efficiency cells.

[0030] Step S30: Based on the first production process route, adjust the second production process route according to the difference process and the difference process parameters.

[0031] In this specific implementation, the first production process route is used as a benchmark, and the differences in the second production process route are adjusted accordingly. The adjustment process involves adjusting the processes in the second production process route that differ from the first production process route; determining the parameters to be adjusted in the second production process route based on the differing process parameters; using the parameters of the first production process route as benchmark parameters; and adjusting the parameters to be adjusted based on the benchmark parameters.

[0032] It should be noted that the general production path of TOPCon photovoltaic cells is as follows: texturing -> boron diffusion -> BSG removal + alkaline polishing -> poly -> annealing -> PSG removal + RCA -> ALD -> front film -> back film -> printing -> testing and sorting. Adjustments to the process can be made according to the above steps. Parameter adjustments can be made based on the parameters of the first production process route, increasing or decreasing the parameters by the amount corresponding to the parameter difference between the two production processes.

[0033] Step S40: Detect the proportion of high-efficiency solar cells corresponding to the adjusted second production process route. If the proportion of high-efficiency solar cells corresponding to the adjusted second production process route meets the preset conditions, then the first production process route is taken as the target production process route.

[0034] It should be noted that in this embodiment, if the proportion of high-efficiency solar cells corresponding to the adjusted second production process route reaches a preset proportion, or if the difference between the proportion of high-efficiency solar cells corresponding to the adjusted second production process route and the proportion of high-efficiency solar cells corresponding to the original second production process route is greater than a preset difference, then it is determined that the proportion of high-efficiency solar cells corresponding to the adjusted second production process route meets the preset conditions. The preset proportion and preset difference can be set according to actual needs, and this embodiment does not impose any restrictions on them.

[0035] It should be understood that if the above conditions are not met, it means that the first production process route is not the optimal production process route, but merely the production process route with the highest proportion of high-efficiency battery cells in any of the above-mentioned arbitrarily selected time periods. There are multiple time periods in the entire process. If the first production process route in that time period is not the optimal production process route, that is, not the target production process route, then the above process is repeated to determine a new target production process route.

[0036] Step S50: Optimize the battery production process based on the steps and process parameters of the target production process route.

[0037] In practical implementation, the process steps and process parameters of the target production process route are also the optimal process steps and process parameters. By following the process steps and process parameters of the target production process route, the battery production process can be optimized to achieve the expected optimization effect.

[0038] In this embodiment, a first production process route and a second production process route are determined by cell-level traceability based on battery production; the differences in processes and process parameters between the first and second production process routes are compared; the second production process route is adjusted based on the differences in processes and process parameters, using the first production process route as a benchmark; the proportion of high-efficiency battery cells corresponding to the adjusted second production process route is detected; when the proportion of high-efficiency battery cells corresponding to the adjusted second production process route meets preset conditions, the first production process route is used as the target production process route to optimize the battery production process. The above method can more accurately locate the relatively optimal equipment and process parameter range for each process, and improve the optimization effect by using precise process parameters.

[0039] Furthermore, this embodiment of the invention also proposes a storage medium storing a battery manufacturing process optimization program, which, when executed by a processor, implements the steps of the battery manufacturing process optimization method described above.

[0040] Reference Figure 2 , Figure 2 This is a structural block diagram of the first embodiment of the battery manufacturing process optimization device of the present invention.

[0041] like Figure 2 As shown, the battery manufacturing process optimization device proposed in this embodiment of the invention includes: The screening module 10 is used to determine the first production process route and the second production process route based on the cell-level traceability of battery production, wherein the proportion of high-efficiency battery cells corresponding to the first production process route is greater than the proportion of high-efficiency battery cells corresponding to the second production process route. Comparison module 20 is used to compare the differences in processes and process parameters between the first production process route and the second production process route; The adjustment module 30 is used to adjust the second production process route based on the first production process route and the difference process and the difference process parameters. The detection module 40 is used to detect the proportion of high-efficiency solar cells corresponding to the adjusted second production process route. If the proportion of high-efficiency solar cells corresponding to the adjusted second production process route meets the preset conditions, the first production process route is taken as the target production process route. The optimization module 50 is used to optimize the battery production process based on the steps and process parameters of the target production process route.

[0042] In this embodiment, a first production process route and a second production process route are determined by cell-level traceability based on battery production; the differences in processes and process parameters between the first and second production process routes are compared; the second production process route is adjusted based on the differences in processes and process parameters, using the first production process route as a benchmark; the proportion of high-efficiency battery cells corresponding to the adjusted second production process route is detected; when the proportion of high-efficiency battery cells corresponding to the adjusted second production process route meets preset conditions, the first production process route is used as the target production process route to optimize the battery production process. The above method can more accurately locate the relatively optimal equipment and process parameter range for each process, and improve the optimization effect by using precise process parameters.

[0043] In some embodiments, the filtering module 10 is used to query the proportion of high-efficiency battery cells in the test sorting process within a preset time period, and select the test sorting line equipment with the highest proportion as the first line equipment. The high-efficiency solar cell is traced in reverse to determine the production path of all processes before testing and sorting. The distribution of high-efficiency cell production line equipment in each process is analyzed sequentially from front to back along the production path. The production line equipment with the highest proportion of high-efficiency cells in each process is selected and connected in series to form the first production process route. Query the percentage of low-efficiency solar cells in the test sorting process within a preset time period, and select the test sorting line equipment with the highest percentage as the second line equipment for that process; The inefficient cells are traced in reverse to determine the production path of all processes before testing and sorting. The production line equipment with the highest efficiency of inefficient cells in each process is selected and connected in series to form a second production process route.

[0044] In some embodiments, the first line equipment includes a printing optimal line equipment, a back film optimal line equipment, and a furnace tube optimal line equipment. The screening module 10 is used to determine the distribution of high-efficiency solar cells in the printing line equipment during the test and sorting, and to take the line equipment with the highest proportion as the printing optimal line equipment. Determine the distribution of high-efficiency solar cells in each backsheet line for testing and sorting, and identify the line with the highest percentage as the optimal backsheet line. The distribution of high-efficiency solar cells in each furnace tube was determined by the test and sorting process, and the line equipment with the highest proportion was selected as the optimal furnace tube line equipment.

[0045] In some embodiments, the adjustment module 30 is used to adjust the processes in the second production process route that differ from the first production process route; Based on the difference in process parameters, determine the parameters to be adjusted in the second production process route, use the parameters of the first production process route as the reference parameters, and adjust the parameters to be adjusted according to the reference parameters.

[0046] In some embodiments, the method further includes: The percentage of high-efficiency solar cells corresponding to the adjusted second production process route was measured. If the proportion of high-efficiency solar cells corresponding to the adjusted second production process route reaches a preset proportion, or if the difference between the proportion of high-efficiency solar cells corresponding to the adjusted second production process route and the proportion of high-efficiency solar cells corresponding to the original second production process route is greater than a preset difference, then it is determined that the proportion of high-efficiency solar cells corresponding to the adjusted second production process route meets the preset condition.

[0047] This application embodiment also provides a battery manufacturing process optimization device, including a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other through the communication bus. The memory is used to store battery manufacturing process optimization programs. When the processor executes the programs stored in the memory, it implements the above-mentioned battery manufacturing process optimization method.

[0048] The communication bus mentioned in the aforementioned battery manufacturing process optimization equipment can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc.

[0049] The communication interface is used for communication between the aforementioned battery manufacturing process optimization equipment and other equipment.

[0050] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0051] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0052] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid state disk (SSD)).

[0053] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0054] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0055] 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 the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

[0056] It should be understood that the above are merely illustrative examples and do not constitute any limitation on the technical solutions of the present invention. In specific applications, those skilled in the art can make settings as needed, and the present invention does not impose any restrictions on this.

[0057] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of this invention. In practical applications, those skilled in the art can select some or all of the workflow to achieve the purpose of this embodiment according to actual needs, and no restrictions are imposed here.

[0058] In addition, for technical details not described in detail in this embodiment, please refer to the battery manufacturing process optimization method provided in any embodiment of the present invention, which will not be repeated here.

[0059] Furthermore, it should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0060] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0061] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory (ROM) / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0062] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

[0063] It is understood that the system provided in the embodiments of the present invention corresponds to the method provided in the embodiments of the present invention, and the explanation, examples and beneficial effects of the relevant content can be referred to the corresponding parts of the above methods.

Claims

1. A method for optimizing battery manufacturing process, characterized in that, The battery manufacturing process optimization method includes: The first and second production process routes are determined based on cell-level traceability of battery production, wherein the proportion of high-efficiency battery cells corresponding to the first production process route is greater than the proportion of high-efficiency battery cells corresponding to the second production process route. Compare the different processes and process parameters between the first production process route and the second production process route; Based on the first production process route, the second production process route is adjusted according to the different processes and the different process parameters; The proportion of high-efficiency solar cells corresponding to the adjusted second production process route is detected. If the proportion of high-efficiency solar cells corresponding to the adjusted second production process route meets the preset conditions, the first production process route is taken as the target production process route. Optimize the battery manufacturing process based on the steps and process parameters of the target production process route; The determination of the first and second production process routes based on cell-level traceability of battery production includes: Query the percentage of high-efficiency solar cells in the test and sorting process within a preset time period, and select the test and sorting line equipment with the highest percentage as the first line equipment; The high-efficiency solar cell is traced in reverse to determine the production path of all processes before testing and sorting. The distribution of high-efficiency cell production line equipment in each process is analyzed sequentially from front to back along the production path. The production line equipment with the highest proportion of high-efficiency cells in each process is selected and connected in series to form the first production process route. Query the percentage of low-efficiency solar cells in the test sorting process within a preset time period, and select the test sorting line equipment with the highest percentage as the second line equipment for that process; The low-efficiency solar cells are traced in reverse to determine the production path of all processes before testing and sorting. The production line equipment with the highest efficiency of low-efficiency solar cells in each process is selected and connected in series to form a second production process route.

2. The battery manufacturing process optimization method as described in claim 1, characterized in that, The first production line includes an optimal printing production line, an optimal back film production line, and an optimal furnace tube production line. The step of querying the percentage of high-efficiency solar cells in the testing and sorting process within a preset time period and selecting the testing and sorting line with the highest percentage as the first production line includes: Determine the distribution of high-efficiency solar cells from the test sorting line equipment in the printing process, and identify the line equipment with the highest proportion as the optimal printing line equipment; Determine the distribution of high-efficiency solar cells in each backsheet line for testing and sorting, and identify the line with the highest percentage as the optimal backsheet line. The distribution of high-efficiency solar cells in each furnace tube was determined by the test and sorting process, and the line equipment with the highest proportion was selected as the optimal furnace tube line equipment.

3. The battery manufacturing process optimization method as described in claim 1, characterized in that, The adjustment of the second production process route based on the first production process route and the different processes and parameters includes: Based on the first production process route, adjust the processes in the second production process route that differ from each other; Based on the difference in process parameters, determine the parameters to be adjusted in the second production process route, use the parameters of the first production process route as the reference parameters, and adjust the parameters to be adjusted according to the reference parameters.

4. The battery manufacturing process optimization method as described in claim 1, characterized in that, The method further includes: The percentage of high-efficiency solar cells corresponding to the adjusted second production process route was measured. If the proportion of high-efficiency solar cells corresponding to the adjusted second production process route reaches a preset proportion, or if the difference between the proportion of high-efficiency solar cells corresponding to the adjusted second production process route and the proportion of high-efficiency solar cells corresponding to the original second production process route is greater than a preset difference, then it is determined that the proportion of high-efficiency solar cells corresponding to the adjusted second production process route meets the preset condition.

5. A battery manufacturing process optimization device, characterized in that, The battery manufacturing process optimization device includes: The screening module is used to determine the first production process route and the second production process route based on the cell-level traceability of battery production, wherein the proportion of high-efficiency battery cells corresponding to the first production process route is greater than the proportion of high-efficiency battery cells corresponding to the second production process route. The comparison module is used to compare the differences in processes and process parameters between the first production process route and the second production process route. The adjustment module is used to adjust the second production process route based on the first production process route and the different processes and the different process parameters. The detection module is used to detect the proportion of high-efficiency solar cells corresponding to the adjusted second production process route. If the proportion of high-efficiency solar cells corresponding to the adjusted second production process route meets the preset conditions, the first production process route is taken as the target production process route. The optimization module is used to optimize the battery production process based on the steps and process parameters of the target production process route. The filtering module is used to query the proportion of high-efficiency battery cells in the test sorting process within a preset time period, and select the test sorting line equipment with the highest proportion as the first line equipment. The high-efficiency solar cell is traced in reverse to determine the production path of all processes before testing and sorting. The distribution of high-efficiency cell production line equipment in each process is analyzed sequentially from front to back along the production path. The production line equipment with the highest proportion of high-efficiency cells in each process is selected and connected in series to form the first production process route. Query the percentage of low-efficiency solar cells in the test sorting process within a preset time period, and select the test sorting line equipment with the highest percentage as the second line equipment for that process; The low-efficiency solar cells are traced in reverse to determine the production path of all processes before testing and sorting. The production line equipment with the highest efficiency of low-efficiency solar cells in each process is selected and connected in series to form a second production process route.

6. The battery manufacturing process optimization apparatus as described in claim 5, characterized in that, The first production line equipment includes an optimal printing production line equipment, an optimal back film production line equipment, and an optimal furnace tube production line equipment. The screening module is used to determine the distribution of high-efficiency solar cells in the printing production line equipment during the testing and sorting process, and to designate the production line equipment with the highest proportion as the optimal printing production line equipment. Determine the distribution of high-efficiency solar cells in each backsheet line for testing and sorting, and identify the line with the highest percentage as the optimal backsheet line. The distribution of high-efficiency solar cells in each furnace tube was determined by the test and sorting process, and the line equipment with the highest proportion was selected as the optimal furnace tube line equipment.

7. A battery manufacturing process optimization device, characterized in that, The battery manufacturing process optimization equipment includes: a memory, a processor, and a battery manufacturing process optimization program stored in the memory and executable on the processor, wherein the battery manufacturing process optimization program is configured to implement the steps of the battery manufacturing process optimization method as described in any one of claims 1 to 4.

8. A storage medium, characterized in that, The storage medium stores a battery manufacturing process optimization program, which, when executed by a processor, implements the steps of the battery manufacturing process optimization method as described in any one of claims 1 to 4.

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