Digital production control system for processing lithium metal solid-state battery anode composite materials

Abstract

This invention discloses a digital production control system for processing lithium metal solid-state battery anode composite materials, belonging to the field of digital production technology. The system includes: a digital production control master node module, used to connect several production process sub-node modules and synchronize real-time data transmitted by the production process sub-node modules; production process sub-node modules, used to collect real-time data of the production processes during the processing of lithium metal solid-state battery anode composite materials and summarize it to the digital production control master node module; a synchronization monitoring module, used to determine whether the delay of the synchronization data between the digital production control master node module and the production process sub-node modules is abnormal; if an abnormal delay time exists, the synchronization control module is invoked; the synchronization control module is used to adjust the synchronization frequency when the delay time of the synchronization data is abnormal. This invention can enhance the level of digital production and improve product quality and yield.

Description

Technical Field

[0001] This invention relates to the field of digital production technology, specifically to a digital production control system for processing lithium metal solid-state battery anode composite materials. Background Technology

[0002] The rapid development of consumer electronics, electric vehicles, and smart grids has placed higher performance demands on current electrochemical energy storage systems. Limited by electrode matching, liquid electrolyte composition, and battery structure, using lithium metal as the anode composite material for solid-state batteries, thus balancing high energy density and high safety, has become a hot research direction for novel electrochemical energy storage devices.

[0003] With the continuous development of mobile communication technology, in the process of integrating intelligent lithium battery production lines with 5G network data transmission, due to the complicated and delicate processing technology of lithium metal solid battery anode composite materials, data synchronization abnormalities are prone to occur at the main and auxiliary process nodes in multiple processes such as controlling DC current, sputtering distance, substrate temperature, processing oxide electrolyte sheets, and preparing polymer electrolyte slurry, which can lead to problems such as decreased conductivity during the preparation process. Summary of the Invention

[0004] The purpose of this invention is to provide a digital production control system for processing lithium metal solid-state battery anode composite materials, in order to solve the problems raised in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a digital production control system for processing lithium metal solid-state battery anode composite materials, the system comprising:

[0006] The digital production control master node module is used to connect several production process sub-node modules and synchronize the real-time data transmitted by the production process sub-node modules.

[0007] The production process sub-node module is used to collect real-time data of the production process during the processing of lithium metal solid-state battery anode composite materials, and summarize it to the digital production control main node module.

[0008] The synchronization monitoring module is used to determine whether the delay of the synchronization data between the main node module of digital production control and the secondary node module of production process is abnormal. If there is an abnormal delay time, the synchronization control module is invoked.

[0009] The synchronization control module is used to adjust the synchronization frequency when the delay time of the synchronization data is abnormal.

[0010] According to the above technical solution, any one of the several production process sub-node modules is connected to a production process sub-node, and the same production process is connected to only one production process sub-node. The real-time data of the production process is transmitted to the digital production control master node module through the production process sub-node module.

[0011] According to the above technical solution, the production process includes:

[0012] The Li+ migration process includes Li+ being extracted from the cathode material and migrating through the electrolyte to the interface;

[0013] The electrolyte reaction process includes gaining electrons at the interface and setting up an electrolyte reaction to generate a stable SEI film, wherein the SEI film ensures that Li+ can work stably in a non-protic electrolyte.

[0014] The free diffusion process includes the nucleation and growth of Li metal under the SEI film and the free phase diffusion;

[0015] The negative electrode side modification process is used to solve the problem of lithium dendrites piercing the SEI film due to Li+ deposition.

[0016] According to the above technical solution, the determination of the delay in synchronization data between the digital production control master node module and the production process sub-node module includes:

[0017] Obtain the request data time value from the main node module of digital production control. ;

[0018] Obtain the synchronization transmission data time value of the sub-node module of the production process. ;

[0019] In the actual request process, the digital production control master node module prioritizes requesting data transmission, and then the production process slave node modules transmit data synchronously after receiving the request. Due to network latency limitations of equipment data, Less than ,like equal Then synchronous transmission has zero latency;

[0020] Based on synchronous transmission data time value With the requested data time value The difference forms the delay time value Construct a delay time processing model to determine the delay time value. Is the delay situation abnormal?

[0021] According to the above technical solution, the processing model for the delay time includes:

[0022] Based on historical big data retrieval, several historical delay times for corresponding production process sub-nodes are generated;

[0023] Sequence matching is performed based on several historical delay times, from smallest to largest, to form a sequence. ,in, These represent the delay times from smallest to largest;

[0024] If it exists Then determine the delay time value. If it is not considered an abnormal delay, then the delay time value is determined. This is an abnormal delay situation.

[0025] According to the above technical solution, the synchronization frequency adjustment includes:

[0026] The system has several preset synchronization frequencies. Several synchronization data points are randomly selected from the historical database. Each synchronization data point must include at least two data characteristics: whether the delay time is normal and the synchronization frequency used. The system then performs calculations and processing on these synchronization data points.

[0027] Among the several preset synchronization frequencies in the system, select any one synchronization frequency, denoted as K;

[0028] In a randomly selected set of synchronization data, the probability of a normal delay time when using synchronization frequency K is calculated and denoted as follows: Without using the synchronization frequency K, the probability of the delay time under normal conditions is denoted as: The probability that the delay time is normal among several synchronized data is denoted as . ;

[0029] The effect of the synchronization frequency K on the probability P of normal delay time:

[0030] Calculate all synchronization frequencies other than the currently used synchronization frequencies, and select the synchronization frequency corresponding to the maximum probability influence P as the new synchronization frequency.

[0031] According to the above technical solution, it also includes:

[0032] The synchronization data detection module is used to detect data loss at each sub-node of the production process after adjusting the synchronization frequency when the delay time of the synchronization data is abnormal.

[0033] According to the above technical solution, the data loss detection includes:

[0034] The amount of data generated by the secondary node module of the production process and the amount of data received by the main node module of digital production control are obtained separately. If there is a difference, it is determined that there is data loss.

[0035] According to the above technical solution, it also includes:

[0036] If only one production process sub-node has data loss, a data alert is issued for that sub-node; if several production process sub-nodes have data loss at the same time, a data node alert priority is established.

[0037] According to the above technical solution, the priority of forming data node early warning includes:

[0038] The system sets a warning score feature, which takes a value within a preset data range. The value is selected based on the difference between the data loss amount and the synchronization frequency adjustment of the sub-node of the production process. The warning score feature increases as the difference between the data loss amount and the synchronization frequency adjustment of the sub-node of the production process increases. When the difference between the data loss amount and the synchronization frequency adjustment of the sub-node of the production process is in a situation where one increases and the other decreases, the data loss amount of the sub-node of the production process is taken as the main feature.

[0039] Several data sets are formed, each including early warning score features, data loss amount of production process sub-nodes, and synchronization frequency adjustment difference. Linear regression is performed on the values ​​of the early warning score features, data loss amount of production process sub-nodes, and synchronization frequency adjustment difference to form a regression equation between the early warning score features and the values ​​of data loss amount of production process sub-nodes and synchronization frequency adjustment difference:

[0040] Where Y represents the early warning score characteristic; , These represent the linear regression parameters; , , represent the data loss amount and synchronization frequency adjustment difference of the secondary nodes in the production process, respectively; u represents the constant term;

[0041] The early warning score characteristics of each sub-node in the production process are calculated based on the regression equation, and the early warning priority of data nodes is formed according to the early warning branch characteristics from large to small.

[0042] Compared with the prior art, the beneficial effects of the present invention are: In the digital process of using lithium metal as the anode composite material for solid-state batteries, the present invention calculates the data synchronization relationship between the production process and the main control node, and forms a digital production control system for the processing of lithium metal solid-state battery anode composite materials based on the adjustment of data synchronization frequency and the calculation of data loss, which can enhance the level of digital process and improve product quality yield. Attached Figure Description

[0043] Figure 1This is a schematic diagram of the digital production control system for processing lithium metal solid-state battery anode composite materials according to the present invention. Detailed Implementation

[0044] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0045] Example: Figure 1 As shown, this invention provides a digital production control system for processing lithium metal solid-state battery anode composite materials, the system comprising:

[0046] The digital production control master node module is used to connect several production process sub-node modules and synchronize the real-time data transmitted by the production process sub-node modules.

[0047] The production process sub-node module is used to collect real-time data of the production process during the processing of lithium metal solid-state battery anode composite materials, and summarize it to the digital production control main node module.

[0048] Any one of the several production process sub-node modules is connected to a production process sub-node. The same production process is connected to only one production process sub-node. The real-time data of the production process is transmitted to the digital production control master node module through the production process sub-node module.

[0049] The production process includes:

[0050] The Li+ migration process includes Li+ being extracted from the cathode material and migrating through the electrolyte to the interface;

[0051] The electrolyte reaction process includes gaining electrons at the interface and setting up an electrolyte reaction to generate a stable SEI film, wherein the SEI film ensures that Li+ can work stably in a non-protic electrolyte.

[0052] The free diffusion process includes the nucleation and growth of Li metal under the SEI film and the free phase diffusion;

[0053] The negative electrode side modification process is used to solve the problem of lithium dendrites piercing the SEI film due to Li+ deposition.

[0054] In the above production process, each production process also includes a large number of branch processes. Taking the negative electrode side modification process as an example, the three branch processes of the negative electrode side modification process are explained, including the use of physical / chemical deposition modification layer, the use of polymer coating, and the co-sintering of substrate-surface modification layer.

[0055] For example, a lithium-stable LiPON layer is obtained by sputtering a Li3PO4 target onto a LAGP oxide electrolyte under nitrogen atmosphere to form a physical / chemical deposition modification layer. By controlling parameters such as DC current, sputtering distance, and substrate temperature, amorphous LiPONs with different thicknesses, morphologies, and growth directions can be obtained. Polymer coatings include pretreatment nodes, configuration nodes, and polymerization nodes. The pretreatment node refers to pretreating the oxide electrolyte sheet; the configuration node refers to preparing the polymer electrolyte slurry and transferring it to the oxide electrolyte surface via methods such as scraping, dripping, or spin coating, controlling the process to regulate its thickness; the polymerization node refers to using a solution of polymer monomers and lithium salts, transferring it to the electrolyte sheet surface, and then initiating polymerization through light or heat to obtain a surface polymer layer. Substrate-surface modification layer co-sintering involves mixing the modification layer material, binder, and solvent, transferring it to the electrolyte sheet surface via screen printing, spin coating, or scraping, and then performing a co-sintering operation.

[0056] The synchronization monitoring module is used to determine whether the delay of the synchronization data between the main node module of digital production control and the secondary node module of production process is abnormal. If there is an abnormal delay time, the synchronization control module is invoked.

[0057] The determination of the latency of synchronization data between the main node module of digital production control and the secondary node module of production process includes:

[0058] Obtain the request data time value from the main node module of digital production control. ;

[0059] Obtain the synchronization transmission data time value of the sub-node module of the production process. ;

[0060] Based on synchronous transmission data time value With the requested data time value The difference forms the delay time value Construct a delay time processing model to determine the delay time value. Is the delay situation abnormal?

[0061] The delay time processing model includes:

[0062] Based on historical big data retrieval, several historical delay times for corresponding production process sub-nodes are generated;

[0063] Sequence matching is performed based on several historical delay times, from smallest to largest, to form a sequence. ,in, These represent the delay times from smallest to largest;

[0064] If it exists Then determine the delay time value. If it is not considered an abnormal delay, then the delay time value is determined. This is an abnormal delay situation.

[0065] The synchronization control module is used to adjust the synchronization frequency when the delay time of the synchronization data is abnormal.

[0066] The synchronization frequency adjustment includes:

[0067] The system has several preset synchronization frequencies. Several synchronization data points are randomly selected from the historical database. Each synchronization data point must include at least two data characteristics: whether the delay time is normal and the synchronization frequency used. The system then performs calculations and processing on these synchronization data points.

[0068] Among the several preset synchronization frequencies in the system, select any one synchronization frequency, denoted as K;

[0069] In a randomly selected set of synchronization data, the probability of a normal delay time when using synchronization frequency K is calculated and denoted as follows: Without using the synchronization frequency K, the probability of the delay time under normal conditions is denoted as: The probability that the delay time is normal among several synchronized data is denoted as . ;

[0070] The effect of the synchronization frequency K on the probability P of normal delay time:

[0071] Calculate all synchronization frequencies other than the currently used synchronization frequencies, and select the synchronization frequency corresponding to the maximum probability influence P as the new synchronization frequency.

[0072] Also includes:

[0073] The synchronization data detection module is used to detect data loss at each sub-node of the production process after adjusting the synchronization frequency when the delay time of the synchronization data is abnormal.

[0074] The data loss detection includes:

[0075] The amount of data generated by the secondary node module of the production process and the amount of data received by the main node module of digital production control are obtained separately. If there is a difference, it is determined that there is data loss.

[0076] Also includes:

[0077] If only one production process sub-node has data loss, a data alert is issued for that sub-node; if several production process sub-nodes have data loss at the same time, a data node alert priority is established.

[0078] The priority for forming data node early warnings includes:

[0079] The system sets a warning score feature, which takes a value within a preset data range. The value is selected based on the difference between the data loss amount and the synchronization frequency adjustment of the sub-node of the production process. The warning score feature increases as the difference between the data loss amount and the synchronization frequency adjustment of the sub-node of the production process increases. When the difference between the data loss amount and the synchronization frequency adjustment of the sub-node of the production process is in a situation where one increases and the other decreases, the data loss amount of the sub-node of the production process is taken as the main feature.

[0080] Several data sets are formed, each including early warning score features, data loss amount of production process sub-nodes, and synchronization frequency adjustment difference. Linear regression is performed on the values ​​of the early warning score features, data loss amount of production process sub-nodes, and synchronization frequency adjustment difference to form a regression equation between the early warning score features and the values ​​of data loss amount of production process sub-nodes and synchronization frequency adjustment difference:

[0081] Where Y represents the early warning score characteristic; These represent the linear regression parameters; These represent the data loss amount and synchronization frequency adjustment difference of the secondary nodes in the production process, respectively; u represents a constant term.

[0082] The early warning score characteristics of each sub-node in the production process are calculated based on the regression equation, and the early warning priority of data nodes is formed according to the early warning branch characteristics from large to small.

[0083] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A digital production control system for processing of a metal lithium solid-state battery negative electrode composite material, characterized in that: The system comprises: a digital production control master node module, used for connecting a plurality of production process slave node modules and synchronizing real-time data transmitted by the production process slave node modules; a production process slave node module, used for collecting real-time data of a production process in a metal lithium solid-state battery negative electrode composite material processing process and aggregating the real-time data to the digital production control master node module; a synchronization monitoring module, used for judging whether a delay of synchronization data between the digital production control master node module and the production process slave node module is abnormal, and calling a synchronization control module if the delay is abnormal; a synchronization control module, used for realizing synchronization frequency adjustment when the delay of the synchronization data is abnormal; the synchronization frequency adjustment comprises: a plurality of synchronization frequencies are preset in the system, a plurality of synchronization data are randomly extracted from a historical database, each of the synchronization data includes at least two data characteristics of whether the delay time is normal and a used synchronization frequency, and the plurality of synchronization data are calculated and processed: in the plurality of preset synchronization frequencies in the system, any synchronization frequency is selected and recorded as K; In a number of randomly selected synchronization data, the probability of the delay time being normal when the synchronization frequency K is used is denoted as , the probability of the delay time being normal when the synchronization frequency K is not used is denoted as , and the probability of the delay time being normal in a number of synchronization data is denoted as ; a probability influence P of the synchronization frequency K on the normal delay time is formed: all the synchronization frequencies except the currently used synchronization frequency are calculated, and a synchronization frequency corresponding to a maximum probability influence P is selected as a new synchronization frequency.

2. The metal lithium solid-state battery negative composite material processing digital production control system according to claim 1, characterized in that: any production process slave node module of the plurality of production process slave node modules is connected to one production process slave node, one production process slave node is connected to one production process only, and real-time data of a production process are transmitted from the production process slave node module to the digital production control master node module.

3. The metal lithium solid-state battery negative composite material processing digital production control system according to claim 2, characterized in that: the production process comprises: a Li+ migration process, including Li+ being separated from a positive electrode material and migrating to an interface through an electrolyte; an electrolyte reaction process, including obtaining an electron at the interface and generating a stable SEI film by electrolyte reaction, the SEI film ensuring that Li+ can work stably in an aprotic electrolyte; a free diffusion process, including nucleation and growth of Li metal under the SEI film and free phase diffusion; a negative electrode side modification process, used for solving a problem that lithium dendrites formed due to deposition of Li+ pierce the SEI film.

4. The metal lithium solid-state battery negative composite material processing digital production control system according to claim 1, characterized in that: the judgment of the delay of the synchronization data between the digital production control master node module and the production process slave node module comprises: Acquiring a request data time value of a digital production control master node module ; Acquiring a synchronization transmission data time value of a production process sub-node module ; Based on synchronous transmission data time value With the requested data time value The difference forms the delay time value Construct a delay time processing model to determine the delay time value. Is the delay situation abnormal? 5. The metal lithium solid-state battery negative composite material processing digital production control system according to claim 4, characterized in that: the processing model of the delay time comprises: a plurality of historical delay times of corresponding production process slave nodes are formed based on historical big data retrieval; Based on several historical delay times, from small to large sequence matching, form a sequence wherein, respectively represent the delay time from small to large, n represents the number sequence; If there is then it is determined that the delay time value does not belong to the delay abnormal case, otherwise it is determined that the delay time value belongs to the delay abnormal case.

6. The metal lithium solid-state battery negative composite material processing digital production control system according to claim 1, characterized in that: further comprising: a synchronization data detection module, used for detecting data loss of each production process slave node after the synchronization frequency adjustment when the delay time of the synchronization data is abnormal.

7. The metal lithium solid-state battery negative composite material processing digital production control system according to claim 6, characterized in that: the data loss detection comprises: amounts of data formed by the production process slave node modules and amounts of data received by the digital production control master node module are respectively acquired, and if there is a difference, it is judged that there is data loss.

8. The metal lithium solid-state battery negative composite material processing digital production control system according to claim 7, characterized in that: further comprising: if only one production process slave node has data loss, data warning is performed on the production process slave node with data loss; when a plurality of production process slave nodes have data loss simultaneously, a data node warning priority is constructed.

9. The metal lithium solid-state battery negative composite material processing digital production control system according to claim 8, characterized in that: the construction of the data node warning priority comprises: The system sets a pre-warning score feature, the pre-warning score feature is valued within a preset data range, the value is selected based on the data loss amount of the production process sub-node and the synchronization frequency adjustment difference, and increases with the increase of the data loss amount of the production process sub-node and the synchronization frequency adjustment difference. When the data loss amount of the production process sub-node and the synchronization frequency adjustment difference are in a situation of one increasing and one decreasing, the data loss amount of the production process sub-node is taken as the main feature for value; A plurality of data groups are formed, any one of which includes a pre-warning score feature, a data loss amount of a production process sub-node and a synchronization frequency adjustment difference, and the values of the pre-warning score feature, the data loss amount of the production process sub-node and the synchronization frequency adjustment difference are linearly regressed to form a regression equation between the pre-warning score feature and the values of the data loss amount of the production process sub-node and the synchronization frequency adjustment difference: wherein, represents a warning score feature; , respectively represent linear regression parameters; , respectively represent a data loss amount of a production process sub-node, and a numerical value of a synchronization frequency adjustment difference; represents a constant term; The pre-warning score feature of each production process sub-node is calculated based on the regression equation, and the data node pre-warning priority is formed according to the pre-warning branch feature from large to small.

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