A perovskite battery production line control method and system

Abstract

The present application provides a perovskite battery production line control method and system, which belongs to the field of automatic control technology and is used to avoid congestion in the production of perovskite batteries. The method includes: an electronic device obtains the number of perovskite photovoltaic cells waiting for production scheduling in each production node of the i-th perovskite battery production line among M perovskite battery production lines; the electronic device determines the production status pattern of each production node of the i-th perovskite battery production line according to the number of perovskite photovoltaic cells waiting for production scheduling in each production node of the i-th perovskite battery production line, and uses a neural network model to analyze the production pattern of each production node of the i-th perovskite battery production line to determine whether there is a perovskite battery production line in the M perovskite battery production lines that is about to experience production congestion; if there is a target perovskite battery production line that is about to experience production congestion, the electronic device adjusts the number of perovskite photovoltaic cells waiting for production scheduling in the target perovskite battery production line.

Description

Technical Field

[0001] The present application relates to the field of automation control technology, and in particular to a method and system for controlling a perovskite battery production line. Background Art

[0002] Perovskite solar cells are a type of solar cell based on perovskite materials. The main principle is to use the photoelectric conversion characteristics of perovskite materials to convert solar energy into electrical energy. The structure of a perovskite cell usually includes conductive glass, a perovskite absorption layer, an electron transport layer, and a charge collection layer. The production process of a perovskite cell includes multiple steps, such as raw material preparation, perovskite precursor synthesis, crystal growth, surface treatment, etc. At present, with the popularization and application of automated production line control technology, the production line of perovskite cells also realizes automated control of perovskite cell production lines by applying automated production line control technology. For example, corresponding automated production equipment can be applied to each production node / link of perovskite cells to achieve automated production control accurate to the production node / link.

[0003] However, since the automated production equipment is applicable to their respective corresponding production nodes / links, the production coupling degree of the automated production equipment between different production nodes / links is insufficient, and different production nodes / links are prone to production congestion. Summary of the invention

[0004] The embodiments of the present application provide a perovskite battery production line control method and system to avoid congestion in the production of perovskite batteries.

[0005] In order to achieve the above objectives, this application adopts the following technical solutions:

[0006] In a first aspect, an embodiment of the present application provides a perovskite battery production line control method, the method is applied to an electronic device for controlling a perovskite battery production line, the perovskite battery production line comprising M perovskite battery production lines, the method comprising: the electronic device obtains the number of perovskite photovoltaic cells waiting for scheduling in each production node of the i-th perovskite battery production line among the M perovskite battery production lines, M is an integer greater than 1, and i is an integer traversing from 1 to M; the electronic device determines the production status pattern of each production node of the i-th perovskite battery production line according to the number of perovskite photovoltaic cells waiting for scheduling in each production node of the i-th perovskite battery production line, and the electronic device analyzes the production pattern of each production node of the i-th perovskite battery production line through a neural network model to determine whether there is a perovskite battery production line among the M perovskite battery production lines that is about to experience production congestion; if a target perovskite battery production line among the M perovskite battery production lines is about to experience production congestion, the electronic device regulates the number of perovskite photovoltaic cells waiting for scheduling in the target perovskite battery production line.

[0007] Optionally, the i-th perovskite battery production line includes N production nodes, N is an integer greater than or equal to 3, and the electronic device determines the production status pattern of each production node of the i-th perovskite battery production line according to the number of perovskite photovoltaic cells waiting to be scheduled in each production node of the i-th perovskite battery production line, including: the electronic device converts the number of perovskite photovoltaic cells waiting to be scheduled in each adjacent two production nodes of the N production nodes into a production status pattern of each adjacent two production nodes of the N production nodes, and obtains a total of N-1 production status patterns; accordingly, the electronic device analyzes the production patterns of each production node of the i-th perovskite battery production line through a neural network model to determine whether there is a perovskite battery production line with production congestion among the M perovskite battery production lines, including: the electronic device processes N-1 production status patterns through a neural network model to determine whether the i-th perovskite battery production line is a target perovskite battery production line that will experience production congestion, and when i traverses 1 to M, the electronic device determines whether there is a perovskite battery production line among the M perovskite battery production lines that will experience production congestion.

[0008] Optionally, the electronic device converts the number of perovskite photovoltaic cells waiting for production scheduling in every two adjacent production nodes among N production nodes into a production status pattern of every two adjacent production nodes among N production nodes, and a total of N-1 production status patterns are obtained, including: the electronic device determines the R value of each pixel point in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting for production scheduling in the j-th production node among the N production nodes, the electronic device determines the G value of each pixel point in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting for production scheduling in the j+1-th production node among the N production nodes, and the electronic device determines the G value of each pixel point in the j-th production status pattern to be the same preset value to obtain the j-th production status pattern, and when j is a traversal from 1 to N-1, a total of N-1 production status patterns are obtained.

[0009] Optionally, the number of battery production equipment in the jth production node is K j , K j The battery production equipment is the battery production equipment for the production link of the j-th production node, K j is an integer greater than 1, and the electronic device determines the R values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j-th production node of the N production nodes, including: the electronic device determines the R values ​​of the pixels in different areas of the j-th production status pattern according to K j The number of battery production equipment, the j-th production status pattern is gridded into K j grid, and according to K j Battery production equipment jThe number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j The Xth grid j The R value of each pixel in the grid; where X j To traverse 1 to K j The number of battery production equipment in the j+1th production node is K j+1 , K j+1 The battery production equipment is the battery production equipment for the production link applicable to the j+1th production node, K j+1 is an integer greater than 1; the electronic device determines the G values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j+1-th production node of the N production nodes, including: the electronic device determines the G values ​​of the pixels in different areas of the j-th production status pattern according to K j+1 The number of battery production equipment, the j-th production status pattern is gridded into K j+1 grid, and according to K j+1 Battery production equipment j+1 The number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j The Xth grid j+1 The G value of each pixel in the grid; where X j+1 To traverse 1 to K j+1 An integer.

[0010] Optionally, the i-th perovskite battery production line includes N production nodes, N is an integer greater than or equal to 3, and the electronic device determines the production status pattern of each production node of the i-th perovskite battery production line according to the number of perovskite photovoltaic cells waiting to be scheduled in each production node of the i-th perovskite battery production line, including: the electronic device converts the number of perovskite photovoltaic cells waiting to be scheduled in every three adjacent production nodes of the N production nodes into a production status pattern of every three adjacent production nodes of the N production nodes, and a total of N-2 production status patterns are obtained; accordingly, the electronic device analyzes the production patterns of each production node of the i-th perovskite battery production line through a neural network model to determine whether there is a perovskite battery production line with production congestion among the M perovskite battery production lines, including: the electronic device processes N-2 production status patterns through a neural network model to determine whether the i-th perovskite battery production line is a target perovskite battery production line that will experience production congestion, and when i traverses 1 to M, the electronic device determines whether there is a perovskite battery production line among the M perovskite battery production lines that will experience production congestion.

[0011] Optionally, the electronic device converts the number of perovskite photovoltaic cells waiting for production scheduling in every two adjacent production nodes among N production nodes into production status patterns of every two adjacent production nodes among N production nodes, and obtains a total of N-1 production status patterns, including: the electronic device determines the R value of each pixel point in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting for production scheduling in the j-th production node among the N production nodes, the electronic device determines the G value of each pixel point in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting for production scheduling in the j+1-th production node among the N production nodes, and the electronic device determines the B value of each pixel point in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting for production scheduling in the j+2-th production node among the N production nodes; when j is a traversal from 1 to N-2, a total of N-2 production status patterns are obtained.

[0012] Optionally, the number of battery production equipment in the jth production node is K j , K j The battery production equipment is the battery production equipment for the production link of the j-th production node, K j is an integer greater than 1, and the electronic device determines the R values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j-th production node of the N production nodes, including: the electronic device determines the R values ​​of the pixels in different areas of the j-th production status pattern according to K j The number of battery production equipment, the j-th production status pattern is gridded into K j grid, and according to K j Battery production equipment j The number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j The Xth grid j The R value of each pixel in the grid; where X j To traverse 1 to K j The number of battery production equipment in the j+1th production node is K j+1 , K j+1 The battery production equipment is the battery production equipment for the production link applicable to the j+1th production node, K j+1 is an integer greater than 1; the electronic device determines the G values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j+1-th production node of the N production nodes, including: the electronic device determines the G values ​​of the pixels in different areas of the j-th production status pattern according to K j+1 The number of battery production equipment, the j-th production status pattern is gridded into K j+1 grid, and according to K j+1 Battery production equipment j+1The number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j The Xth grid j+1 The G value of each pixel in the grid; where X j+1 To traverse 1 to K j+1 The number of battery production equipment in the j+2th production node is K j+2 , K j+2 The battery production equipment is the battery production equipment for the production link applicable to the j+2 production node, K j+2 is an integer greater than 1; the electronic device determines the B values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j+2-th production node of the N production nodes, including: the electronic device determines the B values ​​of the pixels in different areas of the j-th production status pattern according to K j+2 The number of battery production equipment, the j-th production status pattern is gridded into K j+2 grid, and according to K j+2 Battery production equipment j+2 The number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j+2 The Xth grid j+2 The B value of each pixel in the grid; where X j+2 To traverse 1 to K j+2 An integer.

[0013] Optionally, the number of perovskite photovoltaic cells waiting to be scheduled for production of each battery production equipment in each production node is positively correlated / negatively correlated with a pixel value of each pixel point in a grid corresponding to the battery production equipment.

[0014] Optionally, the electronic device regulates the number of perovskite photovoltaic cells waiting to be scheduled in the target perovskite cell production line, including: the electronic device adjusts the perovskite photovoltaic cells waiting to be scheduled in the target perovskite cell production line to other perovskite cell production lines among the M perovskite cell production lines that are not about to experience production congestion.

[0015] In a second aspect, an embodiment of the present application provides a perovskite battery production line control system, the system includes an electronic device for controlling the perovskite battery production line, the perovskite battery production line includes M perovskite battery production lines, and the system is configured as follows: the electronic device obtains the number of perovskite photovoltaic cells waiting for scheduling in each production node of the i-th perovskite battery production line among the M perovskite battery production lines, M is an integer greater than 1, and i is an integer traversing from 1 to M; the electronic device determines the production status pattern of each production node of the i-th perovskite battery production line according to the number of perovskite photovoltaic cells waiting for scheduling in each production node of the i-th perovskite battery production line, and the electronic device analyzes the production pattern of each production node of the i-th perovskite battery production line through a neural network model to determine whether there is a perovskite battery production line among the M perovskite battery production lines that is about to experience production congestion; if a target perovskite battery production line among the M perovskite battery production lines is about to experience production congestion, the electronic device regulates the number of perovskite photovoltaic cells waiting for scheduling in the target perovskite battery production line.

[0016] Optionally, the i-th perovskite battery production line includes N production nodes, N is an integer greater than or equal to 3, and the electronic device determines the production status pattern of each production node of the i-th perovskite battery production line according to the number of perovskite photovoltaic cells waiting to be scheduled in each production node of the i-th perovskite battery production line, including: the electronic device converts the number of perovskite photovoltaic cells waiting to be scheduled in each adjacent two production nodes of the N production nodes into a production status pattern of each adjacent two production nodes of the N production nodes, and obtains a total of N-1 production status patterns; accordingly, the electronic device analyzes the production patterns of each production node of the i-th perovskite battery production line through a neural network model to determine whether there is a perovskite battery production line with production congestion among the M perovskite battery production lines, including: the electronic device processes N-1 production status patterns through a neural network model to determine whether the i-th perovskite battery production line is a target perovskite battery production line that will experience production congestion, and when i traverses 1 to M, the electronic device determines whether there is a perovskite battery production line among the M perovskite battery production lines that will experience production congestion.

[0017] Optionally, the electronic device converts the number of perovskite photovoltaic cells waiting for production scheduling in every two adjacent production nodes among N production nodes into a production status pattern of every two adjacent production nodes among N production nodes, and a total of N-1 production status patterns are obtained, including: the electronic device determines the R value of each pixel point in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting for production scheduling in the j-th production node among the N production nodes, the electronic device determines the G value of each pixel point in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting for production scheduling in the j+1-th production node among the N production nodes, and the electronic device determines the G value of each pixel point in the j-th production status pattern to be the same preset value to obtain the j-th production status pattern, and when j is a traversal from 1 to N-1, a total of N-1 production status patterns are obtained.

[0018] Optionally, the number of battery production equipment in the jth production node is K j , K j The battery production equipment is the battery production equipment for the production link of the j-th production node, K j is an integer greater than 1, and the electronic device determines the R values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j-th production node of the N production nodes, including: the electronic device determines the R values ​​of the pixels in different areas of the j-th production status pattern according to K j The number of battery production equipment, the j-th production status pattern is gridded into K j grid, and according to K j Battery production equipment j The number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j The Xth grid j The R value of each pixel in the grid; where X j To traverse 1 to K j The number of battery production equipment in the j+1th production node is K j+1 , K j+1 The battery production equipment is the battery production equipment for the production link applicable to the j+1th production node, K j+1 is an integer greater than 1; the electronic device determines the G values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j+1-th production node of the N production nodes, including: the electronic device determines the G values ​​of the pixels in different areas of the j-th production status pattern according to K j+1 The number of battery production equipment, the j-th production status pattern is gridded into K j+1 grid, and according to K j+1 Battery production equipment j+1 The number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines Kj The Xth grid j+1 The G value of each pixel in the grid; where X j+1 To traverse 1 to K j+1 An integer.

[0019] Optionally, the i-th perovskite battery production line includes N production nodes, N is an integer greater than or equal to 3, and the electronic device determines the production status pattern of each production node of the i-th perovskite battery production line according to the number of perovskite photovoltaic cells waiting to be scheduled in each production node of the i-th perovskite battery production line, including: the electronic device converts the number of perovskite photovoltaic cells waiting to be scheduled in every three adjacent production nodes of the N production nodes into a production status pattern of every three adjacent production nodes of the N production nodes, and a total of N-2 production status patterns are obtained; accordingly, the electronic device analyzes the production patterns of each production node of the i-th perovskite battery production line through a neural network model to determine whether there is a perovskite battery production line with production congestion among the M perovskite battery production lines, including: the electronic device processes N-2 production status patterns through a neural network model to determine whether the i-th perovskite battery production line is a target perovskite battery production line that will experience production congestion, and when i traverses 1 to M, the electronic device determines whether there is a perovskite battery production line among the M perovskite battery production lines that will experience production congestion.

[0020] Optionally, the electronic device converts the number of perovskite photovoltaic cells waiting for production scheduling in every two adjacent production nodes among N production nodes into production status patterns of every two adjacent production nodes among N production nodes, and obtains a total of N-1 production status patterns, including: the electronic device determines the R value of each pixel point in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting for production scheduling in the j-th production node among the N production nodes, the electronic device determines the G value of each pixel point in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting for production scheduling in the j+1-th production node among the N production nodes, and the electronic device determines the B value of each pixel point in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting for production scheduling in the j+2-th production node among the N production nodes; when j is a traversal from 1 to N-2, a total of N-2 production status patterns are obtained.

[0021] Optionally, the number of battery production equipment in the jth production node is K j , K j The battery production equipment is the battery production equipment for the production link of the j-th production node, K jis an integer greater than 1, and the electronic device determines the R values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j-th production node of the N production nodes, including: the electronic device determines the R values ​​of the pixels in different areas of the j-th production status pattern according to K j The number of battery production equipment, the j-th production status pattern is gridded into K j grid, and according to K j Battery production equipment j The number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j The Xth grid j The R value of each pixel in the grid; where X j To traverse 1 to K j The number of battery production equipment in the j+1th production node is K j+1 , K j+1 The battery production equipment is the battery production equipment for the production link applicable to the j+1th production node, K j+1 is an integer greater than 1; the electronic device determines the G values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j+1-th production node of the N production nodes, including: the electronic device determines the G values ​​of the pixels in different areas of the j-th production status pattern according to K j+1 The number of battery production equipment, the j-th production status pattern is gridded into K j+1 grid, and according to K j+1 Battery production equipment j+1 The number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j The Xth grid j+1 The G value of each pixel in the grid; where X j+1 To traverse 1 to K j+1 The number of battery production equipment in the j+2th production node is K j+2 , K j+2 The battery production equipment is the battery production equipment for the production link applicable to the j+2 production node, K j+2 is an integer greater than 1; the electronic device determines the B values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j+2-th production node of the N production nodes, including: the electronic device determines the B values ​​of the pixels in different areas of the j-th production status pattern according to K j+2 The number of battery production equipment, the j-th production status pattern is gridded into K j+2 grid, and according to K j+2 Battery production equipment j+2 The number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j+2 The Xth gridj+2 The B value of each pixel in the grid; where X j+2 To traverse 1 to K j+2 An integer.

[0022] Optionally, the number of perovskite photovoltaic cells waiting to be scheduled for production of each battery production equipment in each production node is positively correlated / negatively correlated with a pixel value of each pixel point in a grid corresponding to the battery production equipment.

[0023] Optionally, the electronic device regulates the number of perovskite photovoltaic cells waiting to be scheduled in the target perovskite cell production line, including: the electronic device adjusts the perovskite photovoltaic cells waiting to be scheduled in the target perovskite cell production line to other perovskite cell production lines among the M perovskite cell production lines that are not about to experience production congestion.

[0024] In a third aspect, an embodiment of the present application provides a computer-readable storage medium having program code stored thereon. When the program code is executed by the computer, the method described in the first aspect is executed.

[0025] In summary, the above method and device have the following technical effects:

[0026] For M perovskite battery production lines, i traverses from 1 to M, and the electronic device can obtain the number of perovskite photovoltaic cells waiting to be scheduled in each production node of the i-th perovskite battery production line. The electronic device can determine the production status pattern of each production node of the i-th perovskite battery production line based on this, and analyze these production patterns through a neural network model to determine whether there is a perovskite battery production line among the M perovskite battery production lines that will experience production congestion. In this way, if a target perovskite battery production line is about to experience production congestion, the electronic device will adjust the number of perovskite photovoltaic cells waiting to be scheduled in the target perovskite battery production line in advance to avoid congestion in the subsequent production of perovskite batteries, thereby improving production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A schematic diagram of the architecture of a production system provided in an embodiment of the present application;

[0028] Figure 2 A flowchart of a perovskite battery production line control method provided in an embodiment of the present application;

[0029] Figure 3 A schematic diagram of a scenario of a perovskite battery production line control method provided in an embodiment of the present application;

[0030] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0031] 1. Deep neural network (DNN):

[0032] DNN is a specific implementation of machine learning. According to the universal approximation theorem, neural networks can theoretically approximate any continuous function, thus enabling neural networks to learn any mapping. According to the way the network is constructed, DNN can be divided into feed forward neural networks (FNN), convolutional neural networks (CNN) and recurrent neural networks (RNN).

[0033] The characteristic of FNN network is that neurons in adjacent layers are fully connected to each other, which usually requires a large amount of storage space and leads to high computational complexity.

[0034] CNN is a neural network that is specifically designed to process data with a grid-like structure. For example, time series data (discrete sampling on the time axis) and image data (discrete sampling on two dimensions) can be considered to be data with a grid-like structure. CNN does not use all the input information for calculations at once, but uses a fixed-size window to intercept part of the information for convolution operations, which greatly reduces the amount of calculation of model parameters. In addition, depending on the type of information intercepted by the window (for example, people and objects in a picture are different types of information), each window can use different convolution kernel operations, which enables CNN to better extract the features of the input data.

[0035] RNN is a type of DNN network that uses feedback time series information. Its input includes the new input value at the current moment and its own output value at the previous moment. RNN is suitable for obtaining sequence features that are correlated in time, and is particularly suitable for applications such as speech recognition and channel coding.

[0036] In the embodiment of the present invention, "indication" may include direct indication and indirect indication, and may also include explicit indication and implicit indication. The information indicated by a certain information is called information to be indicated. In the specific implementation process, there are many ways to indicate the information to be indicated, such as but not limited to, the information to be indicated can be directly indicated, such as the information to be indicated itself or the index of the information to be indicated. The information to be indicated can also be indirectly indicated by indicating other information, wherein there is an association relationship between the other information and the information to be indicated. It is also possible to indicate only a part of the information to be indicated, while the other parts of the information to be indicated are known or agreed in advance. For example, the indication of specific information can also be achieved by means of the arrangement order of each information agreed in advance (for example, specified by the protocol), thereby reducing the indication overhead to a certain extent. At the same time, the common parts of each information can also be identified and indicated uniformly to reduce the indication overhead caused by indicating the same information separately.

[0037] In addition, the specific indication method may also be various existing indication methods, such as but not limited to the above-mentioned indication methods and various combinations thereof. The specific details of the various indication methods can refer to the prior art and will not be repeated herein. As can be seen from the above, for example, when it is necessary to indicate multiple information of the same type, different indication methods may be used for different information. In the specific implementation process, the desired indication method can be selected according to specific needs. The embodiment of the present invention does not limit the selected indication method. In this way, the indication method involved in the embodiment of the present invention should be understood to cover various methods that can enable the party to be indicated to obtain the information to be indicated.

[0038] It should be understood that the information to be indicated can be sent as a whole or divided into multiple sub-information and sent separately, and the sending period and / or sending time of these sub-information can be the same or different. The specific sending method is not limited in the embodiment of the present invention. Among them, the sending period and / or sending time of these sub-information can be pre-defined, for example, pre-defined according to a protocol, or can be configured by the sending end device by sending configuration information to the receiving end device.

[0039] "Pre-definition" or "pre-configuration" can be implemented by pre-saving corresponding codes, tables or other methods that can be used to indicate relevant information in the device, and the embodiments of the present invention do not limit the specific implementation method. Among them, "saving" can mean saving in one or more memories. The one or more memories can be set separately or integrated in an encoder or decoder, a processor, or an electronic device. The one or more memories can also be partially set separately and partially integrated in a decoder, a processor, or an electronic device. The type of memory can be any form of storage medium, which is not limited by the embodiments of the present invention.

[0040] The "protocol" involved in the embodiments of the present invention may refer to a protocol family in the communication field, a standard protocol with a similar protocol family frame structure, or a related protocol in a reliable access method system for future Internet of Things devices, and the embodiments of the present invention do not specifically limit this.

[0041] In the embodiments of the present invention, descriptions such as "when...", "in the case of...", "if" and "if" all mean that the device will perform corresponding processing under certain objective circumstances, but do not limit the time, nor do they require the device to perform judgment actions when implementing, nor do they mean the existence of other limitations.

[0042] In the description of the embodiments of the present invention, unless otherwise specified, " / " indicates that the objects associated before and after are in an "or" relationship, for example, A / B can represent A or B; "and / or" in the embodiments of the present invention is only a kind of association relationship describing the associated objects, indicating that there can be three relationships, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. In addition, in the description of the embodiments of the present invention, unless otherwise specified, "multiple" refers to two or more than two. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple. In addition, in order to facilitate the clear description of the technical solution of the embodiments of the present invention, in the embodiments of the present invention, the words "first" and "second" are used to distinguish the same or similar items with basically the same functions and effects. Those skilled in the art will appreciate that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit the difference. At the same time, in the embodiments of the present invention, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way for easy understanding.

[0043] The network architecture and business scenarios described in the embodiments of the present invention are intended to more clearly illustrate the technical solutions of the embodiments of the present invention, and do not constitute a limitation on the technical solutions provided by the embodiments of the present invention. A person of ordinary skill in the art can appreciate that with the evolution of the network architecture and the emergence of new business scenarios, the technical solutions provided by the embodiments of the present invention are equally applicable to similar technical problems.

[0044] The technical solution in this application will be described below in conjunction with the accompanying drawings.

[0045] See also Figure 1 , an embodiment of the present application provides a production system, which may include: an electronic device for controlling a perovskite battery production line and a perovskite battery production line.

[0046] Among them, the perovskite battery production line and the electronic device can be understood as a terminal, and the terminal can be a terminal with a communication function, or can be a chip or chip system set in the terminal. The terminal device can also be called a user equipment (UE), an access terminal, a user unit, a user station, a mobile station, a mobile station, a remote station, a remote terminal, a mobile device, a user terminal, a terminal, a wireless communication device, a user agent or a user device. The terminal device in the embodiment of the present application can be a mobile phone, a tablet computer (Pad), a computer with a wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal in industrial control, a wireless terminal in self driving, a wireless terminal in remote medical, a wireless terminal in smart grid, a wireless terminal in transportation safety, a wireless terminal in smart city, a wireless terminal in smart home, a vehicle-mounted terminal, an RSU with terminal function, etc.

[0047] The following will explain the method.

[0048] See also Figure 2 , the embodiment of the present application provides a method for controlling a perovskite battery production line. The process of the method includes:

[0049] S201, the electronic device obtains the number of perovskite photovoltaic cells waiting to be scheduled in each production node of the i-th perovskite cell production line among M perovskite cell production lines.

[0050] The perovskite battery production line may include M perovskite battery production lines, where M is an integer greater than 1, and i is an integer ranging from 1 to M. Each of the M perovskite battery production lines is a complete production process. For example, for the i-th perovskite battery production line, each production node of the i-th perovskite battery production line is a complete production process, that is, by sequentially executing each production node on the production raw materials, a perovskite battery can be finally obtained.

[0051] For example, Figure 3 As shown, the production process includes the following: providing a substrate, forming a bottom electrode on the substrate, forming an electron transport layer on the bottom electrode, forming a perovskite layer on the electron transport layer, forming a hole transport layer on the perovskite layer, forming a top electric layer on the hole transport layer, and forming a metal grid layer on the top electric layer according to preset data. Then the first production node can be providing a substrate, the second production node can be forming a bottom electrode on the substrate, and so on, the last production node can be forming a metal grid layer on the top electric layer according to preset data, and finally a perovskite battery is obtained. The perovskite photovoltaic cell waiting for production scheduling in each production node can be a perovskite photovoltaic cell in production, which is not a finished product. For example, the perovskite photovoltaic cell waiting for production scheduling in the first production node can be a substrate to be provided, the perovskite photovoltaic cell waiting for production scheduling in the second production node can be a substrate on which a bottom electrode is to be formed, and so on, the perovskite photovoltaic cell waiting for production scheduling in the last production node can be a structure in which a top electric layer has been formed on the hole transport layer.

[0052] The electronic device can establish a communication (such as wireless communication) connection with M perovskite battery production lines to periodically obtain the number of perovskite photovoltaic cells waiting to be scheduled in each production node of each perovskite battery production line in the current cycle through the communication connection.

[0053] S202, the electronic device determines the production status pattern of each production node of the ith perovskite battery production line according to the number of perovskite photovoltaic cells waiting to be scheduled in each production node of the ith perovskite battery production line, and the electronic device analyzes the production pattern of each production node of the ith perovskite battery production line through a neural network model to determine whether there is any perovskite battery production line among the M perovskite battery production lines that will experience production congestion.

[0054] In the case where each production node is completed independently by the corresponding battery production equipment, the contradiction lies in the dependence between adjacent production nodes in the production process. Therefore, this is also the cause of congestion, that is, the previous production node outputs more results, resulting in the next production node not having time to process them in time, causing and aggravating congestion, and affecting the production efficiency of subsequent nodes. In this regard, the core of the present application is to analyze adjacent production nodes. Specifically, since the number of perovskite photovoltaic cells waiting for production scheduling at each production node cannot reflect the situation of adjacent production nodes, it is necessary to associate the number of perovskite photovoltaic cells waiting for production scheduling at adjacent production nodes for analysis. One idea proposed in the present application is to convert them into related patterns and analyze the patterns through neural networks to determine whether there will be congestion, as follows.

[0055] Method 1:

[0056] The i-th perovskite cell production line includes N production nodes, where N is an integer greater than or equal to 3. The electronic device can convert the number of perovskite photovoltaic cells waiting to be scheduled in every two adjacent production nodes among the N production nodes into a production status pattern of every two adjacent production nodes among the N production nodes, and obtain a total of N-1 production status patterns.

[0057] For example, the electronic device can determine the R values ​​of pixels in different areas of the j-th production status pattern based on the number of perovskite photovoltaic cells waiting to be scheduled in the j-th production node of N production nodes. Among them, the three RGB values ​​of a pixel represent the intensity of red, green and blue, respectively. In image processing, each pixel is composed of three components, and the value range of each component is 0 to 255. For example, if the RGB value of a pixel is (255, 0, 0), it means that it is red, because the red component reaches the maximum value of 255, while the green and blue components are both 0, and the other values ​​are similar. The R value, B value and G value mentioned below are all understood in this way. Specifically, the number of battery production equipment in the j-th production node is K j , K j The battery production equipment is the battery production equipment for the production link of the j-th production node, K j is an integer greater than 1, and the electronic device can j The number of battery production equipment, the j-th production status pattern is gridded into K j grid, and according to K j Battery production equipment j The number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j The Xth grid j The R value of each pixel in the grid; where X j To traverse 1 to K j An integer.

[0058] For example, K j =6, the jth production status pattern can be divided into 3×2 or 2×3 grids, that is, 2 rows, 3 grids per row, or 3 rows, 2 grids per row. Or, K j =5, the jth production status pattern can be divided into 3+2 or 2+3 grids, that is, 2 rows, 3 grids in the first row, 2 grids in the second row, or 2 rows, 2 grids in the first row, 3 grids in the second row. Or, K j =9, the jth production status pattern can be divided into 3×3, i.e. 3 rows, 3 grids in each row. Or, K j=8, the jth production state pattern can be divided into 3+3+2, that is, 3 rows, 3 grids in the first row, 3 grids in the second row, and 2 grids in the third row. In other words, the core idea of ​​division is to ensure that the number of rows and columns of the grids is as uniform as possible. The size of the grids in each row / column is the same.

[0059] The electronic device can determine the G value of each pixel point in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j+1-th production node of N production nodes. For example, the number of battery production equipment in the j+1-th production node is K j+1 , K j+1 The battery production equipment is the battery production equipment for the production link applicable to the j+1th production node, K j+1 is an integer greater than 1; similar to the above, the electronic device can be based on K j+1 The number of battery production equipment, the j-th production status pattern is gridded into K j+1 grid, and according to K j+1 Battery production equipment j+1 The number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j The Xth grid j+1 The G value of each pixel in the grid; where X j+1 To traverse 1 to K j+1 An integer.

[0060] Furthermore, the electronic device may also determine the G values ​​of all pixels in the j-th production status pattern to be the same preset value.

[0061] In this way, the electronic device determines the RGB value of each pixel in the j-th production state, that is, the j-th production state pattern can be obtained. When j is traversed from 1 to N-1, a total of N-1 production state patterns are obtained.

[0062] It can be understood that by mapping the number of perovskite photovoltaic cells waiting to be scheduled to pixel values, the number of perovskite photovoltaic cells waiting to be scheduled at adjacent production nodes is associated at one pixel point through the combination of RG / RB / GB. In this way, the electronic device processes N-1 production status patterns through the neural network model to determine whether the i-th perovskite battery production line is the target perovskite battery production line that will experience production congestion. When i traverses from 1 to M, the electronic device determines whether there is a perovskite battery production line among the M perovskite battery production lines that will experience production congestion. For example, the neural network model performs joint analysis and processing through the N-1 production status patterns of a perovskite battery production line, or the N-1 production status patterns are input into the neural network model for processing together, and the probability of congestion of the perovskite battery production line output by the neural network model is obtained. If the probability is greater than the threshold, it means that production congestion will occur, otherwise, production congestion will not occur.

[0063] Method 2:

[0064] The i-th perovskite cell production line includes N production nodes, where N is an integer greater than or equal to 3. The electronic device can convert the number of perovskite photovoltaic cells waiting to be scheduled in every three adjacent production nodes among the N production nodes into a production status pattern of every three adjacent production nodes among the N production nodes, and obtain a total of N-2 production status patterns.

[0065] For example, the electronic device determines the R values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j-th production node of N production nodes. Specifically, similar to the above, the number of battery production equipment in the j-th production node is K j , K j The battery production equipment is the battery production equipment for the production link of the j-th production node, K j is an integer greater than 1, and the electronic device is based on K j The number of battery production equipment, the j-th production status pattern is gridded into K j grid, and according to K j Battery production equipment j The number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j The Xth grid j The R value of each pixel in the grid; where X j To traverse 1 to K j integer;

[0066] The electronic device can also determine the G values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j+1-th production node of the N production nodes. Specifically, similar to the above, the number of battery production equipment in the j+1-th production node is K j+1 , K j+1 The battery production equipment is the battery production equipment for the production link applicable to the j+1th production node, K j+1 is an integer greater than 1; electronic equipment is based on K j+1 The number of battery production equipment, the j-th production status pattern is gridded into K j+1 grid, and according to K j+1 Battery production equipment j+1 The number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j The Xth grid j+1 The G value of each pixel in the grid; where X j+1 To traverse 1 to K j+1 integer;

[0067] Furthermore, the electronic device can also determine the B values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j+2-th production node of the N production nodes. Specifically, similar to the above, the number of battery production equipment in the j+2-th production node is K j+2 , K j+2 The battery production equipment is the battery production equipment for the production link applicable to the j+2 production node, K j+2 is an integer greater than 1; electronic equipment is based on K j+2 The number of battery production equipment, the j-th production status pattern is gridded into K j+2 grid, and according to K j+2 Battery production equipment j+2 The number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j+2 The Xth grid j+2 The B value of each pixel in the grid; where X j+2 To traverse 1 to K j+2 An integer.

[0068] When j is traversed from 1 to N-2, the electronic device obtains N-2 production status patterns. In this way, by mapping the number of perovskite photovoltaic cells waiting to be scheduled to the pixel value, the number of perovskite photovoltaic cells waiting to be scheduled at adjacent production nodes is associated at one pixel point through the RGB combination. In this way, the electronic device processes N-2 production status patterns through the neural network model to determine whether the i-th perovskite battery production line is the target perovskite battery production line that will experience production congestion. When i traverses from 1 to M, the electronic device determines whether there is a perovskite battery production line among the M perovskite battery production lines that will experience production congestion. For example, the neural network model performs joint analysis and processing through the N-2 production status patterns of a perovskite battery production line, or the N-2 production status patterns are input into the neural network model for processing together, and the probability of congestion of the perovskite battery production line output by the neural network model is obtained. If the probability is greater than the threshold, it means that production congestion will occur, otherwise, production congestion will not occur.

[0069] The number of perovskite photovoltaic cells waiting to be scheduled for production in each battery production equipment in each of the above-mentioned production nodes is positively correlated / negatively correlated with a pixel value of each pixel point in a grid corresponding to the battery production equipment. This positive / negative correlation correspondence can be pre-configured, such as the number 0-10 corresponds to a pixel value R of 20, the number 11-20 corresponds to a pixel value R of 30, and so on.

[0070] It can be understood that the neural network model can be a trained CNN model.

[0071] S203, if a target perovskite cell production line among the M perovskite cell production lines is about to experience production congestion, the electronic device controls the number of perovskite photovoltaic cells waiting to be scheduled in the target perovskite cell production line.

[0072] The electronic device adjusts the perovskite photovoltaic cells waiting for production scheduling in the target perovskite battery production line to other perovskite battery production lines among the M perovskite battery production lines where production congestion will not occur. For example, the perovskite photovoltaic cells waiting for production scheduling at the production nodes located at the front of the production process in the target perovskite battery production line are adjusted to the corresponding production nodes in other perovskite battery production lines as much as possible.

[0073] In summary, for M perovskite battery production lines, i traverses from 1 to M, and the electronic device can obtain the number of perovskite photovoltaic cells waiting to be scheduled in each production node of the i-th perovskite battery production line. The electronic device can determine the production status pattern of each production node of the i-th perovskite battery production line based on this, and analyze these production patterns through the neural network model to determine whether there is a perovskite battery production line among the M perovskite battery production lines that will experience production congestion. In this way, if a target perovskite battery production line is about to experience production congestion, the electronic device will adjust the number of perovskite photovoltaic cells waiting to be scheduled in the target perovskite battery production line in advance to avoid congestion in the subsequent production of perovskite batteries, thereby improving production efficiency.

[0074] Combination of the above Figure 3 The method provided by the embodiment of the present application is described in detail. The following introduces a perovskite battery production line control system for executing the method provided by the embodiment of the present application.

[0075] The system includes an electronic device for controlling a perovskite battery production line, wherein the perovskite battery production line includes M perovskite battery production lines. The system is configured as follows: the electronic device obtains the number of perovskite photovoltaic cells waiting to be scheduled in each production node of the i-th perovskite battery production line among the M perovskite battery production lines, where M is an integer greater than 1, and i is an integer traversing from 1 to M; the electronic device determines the production status pattern of each production node of the i-th perovskite battery production line according to the number of perovskite photovoltaic cells waiting to be scheduled in each production node of the i-th perovskite battery production line, and the electronic device analyzes the production pattern of each production node of the i-th perovskite battery production line through a neural network model to determine whether there is a perovskite battery production line among the M perovskite battery production lines that is about to experience production congestion; if a target perovskite battery production line among the M perovskite battery production lines is about to experience production congestion, the electronic device controls the number of perovskite photovoltaic cells waiting to be scheduled in the target perovskite battery production line.

[0076] Optionally, the i-th perovskite battery production line includes N production nodes, N is an integer greater than or equal to 3, and the electronic device determines the production status pattern of each production node of the i-th perovskite battery production line according to the number of perovskite photovoltaic cells waiting to be scheduled in each production node of the i-th perovskite battery production line, including: the electronic device converts the number of perovskite photovoltaic cells waiting to be scheduled in each adjacent two production nodes of the N production nodes into a production status pattern of each adjacent two production nodes of the N production nodes, and obtains a total of N-1 production status patterns; accordingly, the electronic device analyzes the production patterns of each production node of the i-th perovskite battery production line through a neural network model to determine whether there is a perovskite battery production line with production congestion among the M perovskite battery production lines, including: the electronic device processes N-1 production status patterns through a neural network model to determine whether the i-th perovskite battery production line is a target perovskite battery production line that will experience production congestion, and when i traverses 1 to M, the electronic device determines whether there is a perovskite battery production line among the M perovskite battery production lines that will experience production congestion.

[0077] Optionally, the electronic device converts the number of perovskite photovoltaic cells waiting for production scheduling in every two adjacent production nodes among N production nodes into a production status pattern of every two adjacent production nodes among N production nodes, and a total of N-1 production status patterns are obtained, including: the electronic device determines the R value of each pixel point in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting for production scheduling in the j-th production node among the N production nodes, the electronic device determines the G value of each pixel point in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting for production scheduling in the j+1-th production node among the N production nodes, and the electronic device determines the G value of each pixel point in the j-th production status pattern to be the same preset value to obtain the j-th production status pattern, and when j is a traversal from 1 to N-1, a total of N-1 production status patterns are obtained.

[0078] Optionally, the number of battery production equipment in the jth production node is K j , K j The battery production equipment is the battery production equipment for the production link of the j-th production node, K j is an integer greater than 1, and the electronic device determines the R values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j-th production node of the N production nodes, including: the electronic device determines the R values ​​of the pixels in different areas of the j-th production status pattern according to K j The number of battery production equipment, the j-th production status pattern is gridded into K j grid, and according to K j Battery production equipment jThe number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j The Xth grid j The R value of each pixel in the grid; where X j To traverse 1 to K j The number of battery production equipment in the j+1th production node is K j+1 , K j+1 The battery production equipment is the battery production equipment for the production link applicable to the j+1th production node, K j+1 is an integer greater than 1; the electronic device determines the G values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j+1-th production node of the N production nodes, including: the electronic device determines the G values ​​of the pixels in different areas of the j-th production status pattern according to K j+1 The number of battery production equipment, the j-th production status pattern is gridded into K j+1 grid, and according to K j+1 Battery production equipment j+1 The number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j The Xth grid j+1 The G value of each pixel in the grid; where X j+1 To traverse 1 to K j+1 An integer.

[0079] Optionally, the i-th perovskite battery production line includes N production nodes, N is an integer greater than or equal to 3, and the electronic device determines the production status pattern of each production node of the i-th perovskite battery production line according to the number of perovskite photovoltaic cells waiting to be scheduled in each production node of the i-th perovskite battery production line, including: the electronic device converts the number of perovskite photovoltaic cells waiting to be scheduled in every three adjacent production nodes of the N production nodes into the production status pattern of every three adjacent production nodes of the N production nodes, and obtains N-2 production status patterns in total;

[0080] Optionally, the electronic device converts the number of perovskite photovoltaic cells waiting for production scheduling in every two adjacent production nodes among N production nodes into production status patterns of every two adjacent production nodes among N production nodes, and obtains a total of N-1 production status patterns, including: the electronic device determines the R value of each pixel point in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting for production scheduling in the j-th production node among the N production nodes, the electronic device determines the G value of each pixel point in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting for production scheduling in the j+1-th production node among the N production nodes, and the electronic device determines the B value of each pixel point in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting for production scheduling in the j+2-th production node among the N production nodes; when j is a traversal from 1 to N-2, a total of N-2 production status patterns are obtained.

[0081] Optionally, the number of battery production equipment in the jth production node is K j , K j The battery production equipment is the battery production equipment for the production link of the j-th production node, K j is an integer greater than 1, and the electronic device determines the R values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j-th production node of the N production nodes, including: the electronic device determines the R values ​​of the pixels in different areas of the j-th production status pattern according to K j The number of battery production equipment, the j-th production status pattern is gridded into K j grid, and according to K j Battery production equipment j The number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j The Xth grid j The R value of each pixel in the grid; where X j To traverse 1 to K j The number of battery production equipment in the j+1th production node is K j+1 , K j+1 The battery production equipment is the battery production equipment for the production link applicable to the j+1th production node, K j+1 is an integer greater than 1; the electronic device determines the G values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j+1-th production node of the N production nodes, including: the electronic device determines the G values ​​of the pixels in different areas of the j-th production status pattern according to K j+1 The number of battery production equipment, the j-th production status pattern is gridded into K j+1 grid, and according to K j+1 Battery production equipment j+1The number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j The Xth grid j+1 The G value of each pixel in the grid; where X j+1 To traverse 1 to K j+1 The number of battery production equipment in the j+2th production node is K j+2 , K j+2 The battery production equipment is the battery production equipment for the production link applicable to the j+2 production node, K j+2 is an integer greater than 1; the electronic device determines the B values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j+2-th production node of the N production nodes, including: the electronic device determines the B values ​​of the pixels in different areas of the j-th production status pattern according to K j+2 The number of battery production equipment, the j-th production status pattern is gridded into K j+2 grid, and according to K j+2 Battery production equipment j+2 The number of perovskite photovoltaic cells waiting to be scheduled for production in a cell production facility determines K j+2 The Xth grid j+2 The B value of each pixel in the grid; where X j+2 To traverse 1 to K j+2 An integer.

[0082] Optionally, the number of perovskite photovoltaic cells waiting to be scheduled for production of each battery production equipment in each production node is positively correlated / negatively correlated with a pixel value of each pixel point in a grid corresponding to the battery production equipment.

[0083] Optionally, the electronic device regulates the number of perovskite photovoltaic cells waiting to be scheduled in the target perovskite cell production line, including: the electronic device adjusts the perovskite photovoltaic cells waiting to be scheduled in the target perovskite cell production line to other perovskite cell production lines among the M perovskite cell production lines that are not about to experience production congestion.

[0084] Combine the following Figure 4 The components of the electronic device 500 are described in detail:

[0085] The processor 501 is the control center of the electronic device 500, and may be a processor or a general term for multiple processing elements. For example, the processor 501 is one or more central processing units (CPUs), or may be application specific integrated circuits (ASICs), or may be one or more integrated circuits configured to implement the embodiments of the present application, such as one or more microprocessors (digital signal processors, DSPs), or one or more field programmable gate arrays (FPGAs).

[0086] Optionally, the processor 501 can execute various functions of the electronic device 500 by running or executing the software program stored in the memory 502 and calling the data stored in the memory 502, as described above. Figure 2 Functionality in the method shown.

[0087] In a specific implementation, as an embodiment, the processor 501 may include one or more CPUs, such as Figure 4 CPU0 and CPU1 are shown in FIG.

[0088] In a specific implementation, as an embodiment, the electronic device 500 may also include multiple processors. Each of these processors may be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). The processor here may refer to one or more devices, circuits, and / or processing cores for processing data (such as computer program instructions).

[0089] Among them, the memory 502 is used to store the software program for executing the solution of the present application, and the execution is controlled by the processor 501. The specific implementation method can refer to the above method embodiment and will not be repeated here.

[0090] Optionally, the memory 502 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or

[0091] Other types of dynamic storage devices that can store information and instructions may also be electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to these. The memory 502 may be integrated with the processor 501, or it may exist independently and be stored in the electronic device 500.

[0092] The interface circuit ( Figure 4 (not shown) is coupled to the processor 501, which is not specifically limited in this embodiment of the present application.

[0093] The transceiver 503 is used for communication with other devices. For example, if the multi-beam based positioning device is a terminal, the transceiver 503 can be used for communication with a network device or another terminal.

[0094] Optionally, the transceiver 503 may include a receiver and a transmitter ( Figure 4 The receiver is used to implement a receiving function, and the transmitter is used to implement a sending function.

[0095] Optionally, the transceiver 503 may be integrated with the processor 501, or may exist independently and communicate with the processor 501 through the interface circuit ( Figure 4 (not shown) is coupled to the processor 501, which is not specifically limited in this embodiment of the present application.

[0096] It should be noted that Figure 4 The structure of the electronic device 500 shown in the figure does not constitute a limitation on the device, and the actual electronic device 500 may include more or less components than those shown in the figure, or combine certain components, or arrange the components differently.

[0097] In addition, the technical effects based on the electronic device 500 can refer to the technical effects of the method in the above method embodiment, which will not be repeated here.

[0098] It should be understood that the processor in the embodiments of the present application may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0099] It should also be understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0100] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0101] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0102] In this application, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0103] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0104] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0105] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0106] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some feature fields can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0107] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0108] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0109] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0110] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A perovskite battery production line control method, characterized in that: The method is applied to an electronic device controlling a perovskite battery production line, wherein the perovskite battery production line comprises M perovskite battery production lines, and the method comprises: The electronic device obtains the number of perovskite photovoltaic cells waiting to be scheduled in each production node of the i-th perovskite cell production line among the M perovskite cell production lines, where M is an integer greater than 1, and i is an integer ranging from 1 to M; The electronic device determines the production status pattern of each production node of the i-th perovskite battery production line according to the number of perovskite photovoltaic cells waiting to be scheduled in each production node of the i-th perovskite battery production line, and the electronic device analyzes the production pattern of each production node of the i-th perovskite battery production line through a neural network model to determine whether there is a perovskite battery production line among the M perovskite battery production lines that is about to experience production congestion; If a target perovskite cell production line among the M perovskite cell production lines is about to experience production congestion, the electronic device controls the number of perovskite photovoltaic cells waiting to be scheduled in the target perovskite cell production line; The i-th perovskite battery production line includes N production nodes, where N is an integer greater than or equal to 3, and the electronic device determines the production status pattern of each production node of the i-th perovskite battery production line according to the number of perovskite photovoltaic cells waiting to be scheduled in each production node of the i-th perovskite battery production line, including: The electronic device converts the number of perovskite photovoltaic cells waiting to be scheduled in every two adjacent production nodes in the N production nodes into a production status pattern of every two adjacent production nodes in the N production nodes, and obtains a total of N-1 production status patterns; Accordingly, the electronic device analyzes the production pattern of each production node of the i-th perovskite battery production line through a neural network model to determine whether there is a perovskite battery production line with production congestion among the M perovskite battery production lines, including: The electronic device processes the N-1 production status patterns through the neural network model to determine whether the i-th perovskite battery production line is a target perovskite battery production line that will experience production congestion, and when i traverses from 1 to M, the electronic device determines whether there is a perovskite battery production line among the M perovskite battery production lines that will experience production congestion; The electronic device converts the number of perovskite photovoltaic cells waiting to be scheduled in every two adjacent production nodes in the N production nodes into a production status pattern of every two adjacent production nodes in the N production nodes, and obtains a total of N-1 production status patterns, including: The electronic device determines the R values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j-th production node of the N production nodes, determines the G values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j+1-th production node of the N production nodes, and the electronic device determines the G values ​​of all pixels in the j-th production status pattern to be the same preset value to obtain the j-th production status pattern. When j is traversed from 1 to N-1, a total of N-1 production status patterns are obtained.

2. The method according to claim 1, characterized in that The number of battery production equipment in the j-th production node is K j , K j The battery production equipment is the battery production equipment for the production link of the j-th production node, K j is an integer greater than 1, and the electronic device determines the R values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j-th production node of the N production nodes, including: The electronic device is configured to j The number of battery production equipment is the number of battery production equipment, and the j-th production status pattern is gridded into K j grids, and according to the K j Battery production equipment j The number of perovskite photovoltaic cells waiting to be scheduled for production in a battery production device determines the K j The Xth grid j The R value of each pixel in the grid; Among them, X j To traverse 1 to K j integer; The number of battery production equipment in the j+1th production node is K j+1 , K j+1 The battery production equipment is the battery production equipment for the production link applicable to the j+1th production node, K j+1 is an integer greater than 1; the electronic device determines the G values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j+1-th production node of the N production nodes, including: The electronic device is configured to j+1 The number of battery production equipment is the number of battery production equipment, and the j-th production status pattern is gridded into K j+1 grids, and according to the K j+1 Battery production equipment j+1 The number of perovskite photovoltaic cells waiting to be scheduled for production in a battery production device determines the K j The Xth grid j+1 The G value of each pixel in the grid; Among them, X j+1 To traverse 1 to K j+1 An integer.

3. The method according to claim 1 or 2, characterized in that: The number of perovskite photovoltaic cells waiting to be scheduled for production in each battery production equipment in each of the production nodes is positively correlated / negatively correlated with a pixel value of each pixel point in a grid corresponding to the battery production equipment.

4. The method according to claim 1, characterized in that: The electronic device controls the number of perovskite photovoltaic cells waiting to be scheduled in the target perovskite cell production line, including: The electronic device adjusts the perovskite photovoltaic cells waiting to be scheduled in the target perovskite cell production line to other perovskite cell production lines among the M perovskite cell production lines that are not about to experience production congestion.

5. A perovskite battery production line control method, characterized in that: The method is applied to an electronic device controlling a perovskite battery production line, wherein the perovskite battery production line comprises M perovskite battery production lines, and the method comprises: The electronic device obtains the number of perovskite photovoltaic cells waiting to be scheduled in each production node of the i-th perovskite cell production line among the M perovskite cell production lines, where M is an integer greater than 1, and i is an integer ranging from 1 to M; The electronic device determines the production status pattern of each production node of the i-th perovskite battery production line according to the number of perovskite photovoltaic cells waiting to be scheduled in each production node of the i-th perovskite battery production line, and the electronic device analyzes the production pattern of each production node of the i-th perovskite battery production line through a neural network model to determine whether there is a perovskite battery production line among the M perovskite battery production lines that is about to experience production congestion; If a target perovskite cell production line among the M perovskite cell production lines is about to experience production congestion, the electronic device controls the number of perovskite photovoltaic cells waiting to be scheduled in the target perovskite cell production line; The i-th perovskite battery production line includes N production nodes, where N is an integer greater than or equal to 3, and the electronic device determines the production status pattern of each production node of the i-th perovskite battery production line according to the number of perovskite photovoltaic cells waiting to be scheduled in each production node of the i-th perovskite battery production line, including: The electronic device converts the number of perovskite photovoltaic cells waiting to be scheduled in every three adjacent production nodes among the N production nodes into a production status pattern of every three adjacent production nodes among the N production nodes, and obtains a total of N-2 production status patterns; Accordingly, the electronic device analyzes the production pattern of each production node of the i-th perovskite battery production line through a neural network model to determine whether there is a perovskite battery production line with production congestion among the M perovskite battery production lines, including: The electronic device processes the N-2 production status patterns through the neural network model to determine whether the i-th perovskite battery production line is a target perovskite battery production line that will experience production congestion, and when i traverses from 1 to M, the electronic device determines whether there is a perovskite battery production line among the M perovskite battery production lines that will experience production congestion; The electronic device converts the number of perovskite photovoltaic cells waiting to be scheduled in every two adjacent production nodes in the N production nodes into a production status pattern of every two adjacent production nodes in the N production nodes, and obtains a total of N-1 production status patterns, including: The electronic device determines the R values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting for production scheduling in the j-th production node of the N production nodes, the G values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting for production scheduling in the j+1-th production node of the N production nodes, and the B values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting for production scheduling in the j+2-th production node of the N production nodes; when j is traversed from 1 to N-2, a total of N-2 production status patterns are obtained.

6. The method according to claim 5, characterized in that The number of battery production equipment in the j-th production node is K j , K j The battery production equipment is the battery production equipment for the production link of the j-th production node, K j is an integer greater than 1, and the electronic device determines the R values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j-th production node of the N production nodes, including: The electronic device is configured to j The number of battery production equipment is the number of battery production equipment, and the j-th production status pattern is gridded into K j grids, and according to the K j Battery production equipment j The number of perovskite photovoltaic cells waiting to be scheduled for production in a battery production device determines the K j The Xth grid j The R value of each pixel in the grid; Among them, X j To traverse 1 to K j integer; The number of battery production equipment in the j+1th production node is K j+1 , K j+1 The battery production equipment is the battery production equipment for the production link applicable to the j+1th production node, K j+1 is an integer greater than 1; the electronic device determines the G values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j+1-th production node of the N production nodes, including: The electronic device is configured to j+1 The number of battery production equipment is the number of battery production equipment, and the j-th production status pattern is gridded into K j+1 grids, and according to the K j+1 Battery production equipment j+1 The number of perovskite photovoltaic cells waiting to be scheduled for production in a battery production device determines the K j The Xth grid j+1 The G value of each pixel in the grid; Among them, X j+1 To traverse 1 to K j+1 integer; The number of battery production equipment in the j+2th production node is K j+2 , K j+2 The battery production equipment is the battery production equipment for the production link of the j+2 production node, K j+2 is an integer greater than 1; the electronic device determines the B values ​​of the pixels in different areas of the j-th production status pattern according to the number of perovskite photovoltaic cells waiting to be scheduled in the j+2-th production node of the N production nodes, including: The electronic device is configured to j+2 The number of battery production equipment is the number of battery production equipment, and the j-th production status pattern is gridded into K j+2 grids, and according to the K j+2 Battery production equipment j+2 The number of perovskite photovoltaic cells waiting to be scheduled for production in a battery production device determines the K j+2 The Xth grid j+2 The B value of each pixel in the grid; Among them, X j+2 To traverse 1 to K j+2 An integer.

7. The method according to claim 5 or 6, characterized in that: The number of perovskite photovoltaic cells waiting to be scheduled for production in each battery production equipment in each of the production nodes is positively correlated / negatively correlated with a pixel value of each pixel point in a grid corresponding to the battery production equipment.

8. The method according to claim 5, characterized in that The electronic device controls the number of perovskite photovoltaic cells waiting to be scheduled in the target perovskite cell production line, including: The electronic device adjusts the perovskite photovoltaic cells waiting to be scheduled in the target perovskite cell production line to other perovskite cell production lines among the M perovskite cell production lines that are not about to experience production congestion.

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