CN117391404A - Control method and device for coating transverse surface density of lithium battery and electronic equipment - Google Patents
Control method and device for coating transverse surface density of lithium battery and electronic equipment Download PDFInfo
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Abstract
The invention provides a control method and a device for the density of a lithium battery coating transverse surface, and electronic equipment, and relates to the technical field of density control, comprising the following steps: acquiring coating transverse surface density data in the lithium battery generation process; determining an areal density model based on the coated transverse areal density data; acquiring learning surface density data; determining whether to set parameters to be set of a preset closed-loop algorithm or not based on a preset surface density data threshold value and self-learning surface density data; if the parameters to be set of the closed-loop algorithm are set, setting the parameters to be set of the closed-loop algorithm based on the self-learning surface density data and the surface density model; and controlling the transverse surface density of the lithium battery coating based on the surface density model through a closed-loop algorithm after parameter setting. In the mode, the closed-loop algorithm is optimized through self-learning surface density data, so that the anti-interference capability of the coating transverse surface density is improved, and the consistency of the coating transverse surface density is ensured.
Description
Technical Field
The invention relates to the technical field of density control, in particular to a control method and device for the density of a lithium battery coating transverse surface and electronic equipment.
Background
The slit coating equipment for lithium batteries is one of key equipment for producing lithium batteries of various types, and the consistency of the transverse surface density of coating is a crucial technological index in the process of using the slit coating equipment for lithium batteries. At present, most of lithium battery slit coating equipment uses the displacement of an adjusting block to adjust the size of the transverse surface density of coating, and the opening degree of a slit is changed by adjusting the displacement of the adjusting block so as to control the transverse surface density.
In the related art, each adjusting block is generally regarded as a linear controlled object, a fixed control gain is generally adopted when a control algorithm is designed for the adjusting block, the displacement of the adjusting block required by different errors is different in fact, the displacement of the adjusting block is not a linear relationship, and when the adjusting block is positioned at different positions, the input-output relationship between the coating transverse area density and the displacement of the adjusting block can be inevitably changed, so that the consistency of the coating transverse area density is difficult to ensure.
Disclosure of Invention
In view of the above, the present invention aims to provide a method, a device and an electronic device for controlling the coating transverse surface density of a lithium battery, so as to ensure the consistency of the coating transverse surface density.
In a first aspect, an embodiment of the present invention provides a method for controlling a coated lateral surface density of a lithium battery, to obtain coated lateral surface density data in a lithium battery generating process; determining an areal density model based on the coated transverse areal density data; acquiring learning surface density data; determining whether to set parameters to be set of a preset closed-loop algorithm or not based on a preset surface density data threshold value and self-learning surface density data; if the parameters to be set of the closed-loop algorithm are set, setting the parameters to be set of the closed-loop algorithm based on the self-learning surface density data and the surface density model; and controlling the transverse surface density of the lithium battery coating based on the surface density model through a closed-loop algorithm after parameter setting.
In a preferred embodiment of the present invention, the determining an areal density model based on the coated transverse areal density data includes: determining a conditioning block displacement and a coating transverse areal density based on the coating transverse areal density data; the areal density model was established by a step test method based on the adjustment block displacement and the coated transverse areal density.
In a preferred embodiment of the present invention, after the above-mentioned obtaining of the coated transverse area density data of the lithium battery generating process, the method further includes: if the first historical coating transverse surface density data does not exist before the coating transverse surface density data is acquired, establishing a cloud database based on the coating transverse surface density data; if the first historical coating cross-directional areal density data exists before the coating cross-directional areal density data is obtained, the coating cross-directional areal density data is added to the cloud database.
In a preferred embodiment of the present invention, the acquiring self-learning surface density data includes: selecting second historical coating transverse areal density data in a preset time interval in a cloud database; determining an areal density standard deviation based on the second historical coating transverse areal density data; and if the surface density standard deviation is smaller than or equal to a preset surface density standard deviation threshold value, taking the second historical coating transverse surface density data as self-learning surface density data.
In a preferred embodiment of the present invention, the determining whether to set the preset parameters to be set of the closed-loop algorithm based on the preset surface density data threshold and the self-learning surface density data includes: determining a control gain based on the self-learning areal density data; and if the control gain is larger than the surface density data threshold value, setting the parameters to be set of the closed-loop algorithm.
In a preferred embodiment of the present invention, the setting parameters to be set based on the self-learning surface density data and the surface density model setting closed-loop algorithm include: determining a proportional control gain and a speed control gain based on the self-learning areal density data; adjusting the control gain of the comparative example based on the action intensity of the surface density model; adjusting the speed control gain based on the response speed of the surface density model; and taking the adjusted proportional control gain and the adjusted speed control gain as the adjusted parameters to be adjusted.
In a preferred embodiment of the present invention, after setting the parameters to be set based on the self-learning surface density data and the surface density model setting closed-loop algorithm, the method further includes: discretizing the closed-loop algorithm to obtain discrete sentences; a closed-loop algorithm is performed in the computer based on the discrete statement.
In a second aspect, an embodiment of the present invention further provides a control device for a coated lateral area density of a lithium battery, including: the coating transverse surface density data acquisition module is used for acquiring coating transverse surface density data in the lithium battery generation process; an areal density model determination module for determining an areal density model based on the coated transverse areal density data; the self-learning surface density data acquisition module is used for acquiring self-learning surface density data; the setting judging module is used for determining whether to set the preset parameters to be set of the closed-loop algorithm or not based on the preset surface density data threshold value and the self-learning surface density data; the to-be-set parameter setting module is used for setting the to-be-set parameters of the closed-loop algorithm based on the self-learning surface density data and the surface density model if the to-be-set parameters of the closed-loop algorithm are set; and the transverse areal density control module is used for controlling the coating transverse areal density of the lithium battery based on the areal density model through a closed-loop algorithm after parameter setting.
In a third aspect, an embodiment of the present invention further provides an electronic device, including a processor and a memory, where the memory stores computer executable instructions executable by the processor, where the processor executes the computer executable instructions to implement the method for controlling the lateral areal density of lithium battery coating according to the first aspect.
In a fourth aspect, an embodiment of the present invention further provides a computer readable storage medium, where computer executable instructions are stored, where the computer executable instructions, when invoked and executed by a processor, cause the processor to implement the method for controlling the transverse areal density of lithium battery coating according to the first aspect.
The embodiment of the invention has the following beneficial effects:
the embodiment of the invention provides a control method, a device and electronic equipment for coating transverse surface density of a lithium battery, which are characterized in that through acquiring coating transverse surface density data in a lithium battery generation process, determining a surface density model based on the coating transverse surface density data, acquiring self-learning surface density data, determining whether to-be-set parameters of a preset closed-loop algorithm are set based on a preset surface density data threshold value and the self-learning surface density data, if the to-be-set parameters of the closed-loop algorithm are set, setting the to-be-set parameters of the closed-loop algorithm based on the self-learning surface density data and the surface density model, and then controlling the coating transverse surface density of the lithium battery based on the surface density model through the closed-loop algorithm after parameter setting. In the mode, the closed-loop algorithm is optimized through self-learning surface density data, so that the anti-interference capability of the coating transverse surface density is improved, and the consistency of the coating transverse surface density is ensured.
Additional features and advantages of the disclosure will be set forth in the description which follows, or in part will be obvious from the description, or may be learned by practice of the techniques of the disclosure.
The foregoing objects, features and advantages of the disclosure will be more readily apparent from the following detailed description of the preferred embodiments taken in conjunction with the accompanying drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a method for controlling a coating transverse area density of a lithium battery according to an embodiment of the present invention;
fig. 2 is a flowchart of another method for controlling the coating transverse areal density of a lithium battery according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a control device for coating transverse area density of a lithium battery according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of an areal density model according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The slit coating equipment for lithium batteries is one of key equipment for producing lithium batteries of various types, and the consistency of the transverse surface density of coating is a crucial technological index in the process of using the slit coating equipment for lithium batteries. At present, most of lithium battery slit coating equipment uses the displacement of an adjusting block to adjust the size of the transverse surface density of coating, and the opening degree of a slit is changed by adjusting the displacement of the adjusting block so as to control the transverse surface density.
In the related art, each adjusting block is generally regarded as a linear controlled object, a fixed control gain is generally adopted when a control algorithm is designed for the adjusting block, the displacement of the adjusting block required by different errors is different in fact, the displacement of the adjusting block is not a linear relationship, and when the adjusting block is positioned at different positions, the input-output relationship between the coating transverse area density and the displacement of the adjusting block can be inevitably changed, so that the consistency of the coating transverse area density is difficult to ensure.
Based on the above, the method, the device and the electronic equipment for controlling the coating transverse surface density of the lithium battery provided by the embodiment of the invention are used for determining the surface density model based on the coating transverse surface density data in the lithium battery generation process by acquiring the coating transverse surface density data, acquiring the self-learning surface density data, determining whether to-be-set parameters of a preset closed-loop algorithm are set based on a preset surface density data threshold value and the self-learning surface density data, if the to-be-set parameters of the closed-loop algorithm are set, setting the to-be-set parameters of the closed-loop algorithm based on the self-learning surface density data and the surface density model, and controlling the coating transverse surface density of the lithium battery based on the surface density model by the closed-loop algorithm after parameter setting. In the mode, the closed-loop algorithm is optimized through self-learning surface density data, so that the anti-interference capability of the coating transverse surface density is improved, and the consistency of the coating transverse surface density is ensured.
For the convenience of understanding the present embodiment, a method for controlling the coating transverse area density of a lithium battery according to the embodiment of the present invention will be described in detail.
Example 1
The embodiment of the invention provides a control method for the coating transverse surface density of a lithium battery, and fig. 1 is a flow chart of the control method for the coating transverse surface density of the lithium battery. As shown in fig. 1, the control method of the coating transverse area density of the lithium battery can comprise the following steps:
step S101, obtaining coated transverse area density data in the lithium battery generating process.
The coating transverse area density data may include a plurality of partitioned adjustment block displacements and coating transverse area densities corresponding to the plurality of partitioned adjustment block displacements. The displacement of the adjusting block is understood to be the up and down movement of each zoned steel adjusting block in the die head of the apparatus.
Step S102, determining an area density model based on the coating transverse area density data.
The surface density model is a mathematical model between the displacement of the regulating block and the transverse surface density of the coating.
Specifically, determining the areal density model based on the coated transverse areal density data may include: determining a conditioning block displacement and a coating transverse areal density based on the coating transverse areal density data; the areal density model was established by a step test method based on the adjustment block displacement and the coated transverse areal density.
The displacement of the regulating block represents the displacement of the regulating blocks of a plurality of subareas, and the opening degree of the slit can be changed by adjusting the displacement of the regulating blocks of each subarea, so that the coating transverse surface density is controlled.
Step S103, obtaining self-learning surface density data.
The self-learning areal density data is obtained from historical coating transverse areal density data.
The change rule of the coating transverse area density for a period of time can be learned through self-learning area density data, and can be used for predicting the coating transverse area density value.
Step S104, determining whether to set the preset parameters to be set of the closed-loop algorithm or not based on the preset surface density data threshold and the self-learning surface density data.
Wherein the areal density data threshold is set in accordance with an acceptable transverse areal density standard deviation.
Specifically, determining whether to set the preset parameters to be set of the closed-loop algorithm based on the preset surface density data threshold and the self-learning surface density data may include: determining a control gain based on the self-learning areal density data; and if the control gain is larger than the surface density data threshold value, setting the parameters to be set of the closed-loop algorithm.
The control gain may include a proportional control gain and a speed control gain, the control gain may be changed by self-learning the surface density data, and when the control gain is greater than the surface density data threshold, the magnitude of the control gain change may be considered to satisfy the requirement, that is, the control gain change is necessary, so that the control gain of the surface density model is adjusted by applying the control gain changed from the learning the surface density data when necessary, that is, the parameter to be set of the closed-loop algorithm is set, so as to change the action strength and the response speed of the surface density model.
Step S105, if the parameters to be set of the closed-loop algorithm are adjusted, the parameters to be set of the closed-loop algorithm are set based on the self-learning surface density data and the surface density model.
Wherein the areal density model varies the control gain by a closed loop algorithm.
Specifically, the parameters to be set based on the self-learning surface density data and the surface density model setting closed-loop algorithm may include: determining a proportional control gain and a speed control gain based on the self-learning areal density data; adjusting the control gain of the comparative example based on the action intensity of the surface density model; adjusting the speed control gain based on the response speed of the surface density model; and taking the adjusted proportional control gain and the adjusted speed control gain as the adjusted parameters to be adjusted.
Wherein, the proportional control gain can influence the action intensity of the surface density model, and the speed control gain can influence the response speed of the surface density model.
The greater the proportional control gain, the weaker the applied strength of the areal density model, which is generally applicable to cases where the coating transverse areal density is very small, and the smaller the proportional control gain, the stronger the applied strength of the areal density model, which is generally applicable to cases where the coating transverse areal density is very large.
The larger the speed control gain is, the faster the response speed of the surface density model is, but the weaker the model mismatch resistance is, the smaller the speed control gain is, the slower the response speed of the surface density model is, but the stronger the model mismatch resistance is.
In summary of the above control relationships, the control gains of the comparative examples and the speed control gains are adjusted to ensure consistency of the coated transverse surface density, and the adjusted proportional control gains and the adjusted speed control gains are used as the parameters to be adjusted after adjustment to control the coated transverse surface density of the lithium battery.
Because the closed-loop algorithm needs to be realized in a computer, and the computer can only recognize discrete sentences, but the formula of the closed-loop algorithm has continuity, the closed-loop algorithm needs to be subjected to discretization to obtain the discrete sentences; a closed-loop algorithm is performed in the computer based on the discrete statement.
Specifically, a closed-loop algorithm is performed in ohm's software based on discrete statements. Wherein the discrete statement may be a formula of discretization.
And S106, controlling the transverse surface density of the lithium battery coating based on the surface density model through a closed-loop algorithm after parameter setting.
The action intensity and the response speed of the surface density model can be consistent with the consistency of the transverse surface density of the coating through a closed-loop algorithm after parameter setting.
According to the control method for the coating transverse surface density of the lithium battery, the coating transverse surface density data in the lithium battery generating process can be obtained, the surface density model is determined based on the coating transverse surface density data, the self-learning surface density data is obtained, whether the parameters to be set of a preset closed-loop algorithm are set or not is determined based on the preset surface density data threshold value and the self-learning surface density data, if the parameters to be set of the closed-loop algorithm are set, the parameters to be set of the closed-loop algorithm are set based on the self-learning surface density data and the surface density model, and then the transverse surface density of the lithium battery is controlled based on the surface density model through the closed-loop algorithm after parameter setting. In the mode, the closed-loop algorithm is optimized through self-learning surface density data, so that the anti-interference capability of the coating transverse surface density is improved, and the consistency of the coating transverse surface density is ensured.
Example 2
The embodiment of the invention also provides another control method for the coating transverse surface density of the lithium battery; the method is realized on the basis of the method of the embodiment; the method focuses on the steps after acquisition of the coated transverse areal density data of the lithium battery generation process.
Fig. 2 is a flowchart of another method for controlling the coating transverse areal density of a lithium battery according to an embodiment of the present invention, as shown in fig. 2, after the step of obtaining the coating transverse areal density data in the lithium battery generating process, the method may further include the following steps:
step S201 determines whether there is first historical coating cross-directional areal density data before the coating cross-directional areal density data is acquired.
The first historical coating transverse area density data is coating transverse area density data generated in the lithium battery generating process before the coating transverse area density data are acquired.
Specifically, determining whether the first historical coating cross-machine direction areal density data exists prior to acquiring the coating cross-machine direction areal density data may include: determining a time point at which the coating cross-directional areal density data is acquired, determining whether the coating cross-directional areal density data exists before the time point, if the coating cross-directional areal density data exists before the time point, determining that the first historical coating cross-directional areal density data exists before the acquisition of the coating cross-directional areal density data, and if the coating cross-directional areal density data does not exist before the time point, determining that the first historical coating cross-directional areal density data does not exist before the acquisition of the coating cross-directional areal density data.
Illustratively, if the determination result of step S201 is no, that is, there is no first historical coating transverse areal density data before the coating transverse areal density data is acquired, step S202 is executed, and if the determination result of step S201 is yes, that is, there is first historical coating transverse areal density data before the coating transverse areal density data is acquired, step S203 is executed.
Step S202, a cloud database is established based on the coating transverse surface density data.
Under the condition that the first historical coating transverse surface density data does not exist before the coating transverse surface density data is acquired, the cloud database is considered to be absent for storing the coating transverse surface density data generated in the lithium battery generating process, so that the cloud database can be established, and only the coating transverse surface density data is contained in the cloud database at the moment.
In step S203, the coating transverse area density data is added to the cloud database.
Under the condition that the first historical coating transverse surface density data exists before the coating transverse surface density data is acquired, the cloud database can be considered to be established, so that the coating transverse surface density data can be added into the cloud database to update the cloud database.
Further, the coating transverse area density data may be stored in time intervals, and the number of the coating transverse area density data in each time interval is the same, and the longer the corresponding time period of the time interval is, the larger the data amount of the coating transverse area density is.
Based on this, the above step S103 may include: selecting second historical coating transverse areal density data in a preset time interval in a cloud database; determining an areal density standard deviation based on the second historical coating transverse areal density data; and if the surface density standard deviation is smaller than or equal to a preset surface density standard deviation threshold value, taking the second historical coating transverse surface density data as self-learning surface density data.
The selection of the preset time interval is determined according to the capability of the executing mechanism and the actual control requirement. The capacity of the actuator is the number of zones of the die head of the device, the speed of the tape, and the length of the oven. The actual control demand may refer to an acceptable error range size, and the larger the acceptable error range, the shorter the selected time interval may be.
The second historical coating transverse surface density data are a plurality of coating transverse surface density data stored in a preset time interval, and standard deviation operation is carried out on the plurality of coating transverse surface density data to obtain the surface density standard deviation.
Wherein the smaller the standard deviation due to areal density. The better the consistency of the coating cross-directional areal density, the second historical coating cross-directional areal density data can be regarded as self-learning areal density data if the areal density standard deviation is less than or equal to a preset areal density standard deviation threshold.
According to the control method for the coating transverse surface density of the lithium battery, the cloud database is established, the coating transverse surface density data is recorded, the self-learning surface density data is determined according to the historical coating transverse surface density data, and the parameters to be set of a closed-loop algorithm are set according to the self-learning surface density data, so that the consistency of the coating transverse surface density is ensured.
Example 3
Corresponding to the above method embodiment, the embodiment of the present invention provides a device for controlling the density of a coated lateral surface of a lithium battery, and fig. 3 is a schematic structural diagram of the device for controlling the density of a coated lateral surface of a lithium battery, as shown in fig. 3, where the device for controlling the density of a coated lateral surface of a lithium battery may include:
the coated transverse area density data acquisition module 301 is configured to acquire coated transverse area density data in a lithium battery generating process.
An areal density model determination module 302 for determining an areal density model based on the coated transverse areal density data.
The self-learning surface density data acquisition module 303 is configured to acquire self-learning surface density data.
The setting determining module 304 is configured to determine whether to set a preset parameter to be set of the closed-loop algorithm based on a preset surface density data threshold and self-learning surface density data.
And the to-be-set parameter setting module 305 is configured to set to-be-set parameters of the closed-loop algorithm based on the self-learning surface density data and the surface density model if the to-be-set parameters of the closed-loop algorithm are set.
The transverse areal density control module 306 is used for controlling the transverse areal density of the lithium battery coating based on the areal density model through a closed-loop algorithm after parameter setting.
According to the control device for the coating transverse surface density of the lithium battery, provided by the embodiment of the invention, the coating transverse surface density data in the lithium battery generation process can be obtained, the surface density model is determined based on the coating transverse surface density data, the self-learning surface density data is obtained, whether the parameters to be set of a preset closed-loop algorithm are set or not is determined based on the preset surface density data threshold value and the self-learning surface density data, if the parameters to be set of the closed-loop algorithm are set, the parameters to be set of the closed-loop algorithm are set based on the self-learning surface density data and the surface density model, and then the transverse surface density of the lithium battery is controlled based on the surface density model by the closed-loop algorithm after parameter setting. In the mode, the closed-loop algorithm is optimized through self-learning surface density data, so that the anti-interference capability of the coating transverse surface density is improved, and the consistency of the coating transverse surface density is ensured.
In some embodiments, the areal density model determination module is further to determine the conditioning block displacement and the coating lateral areal density based on the coating lateral areal density data; the areal density model was established by a step test method based on the adjustment block displacement and the coated transverse areal density.
In some embodiments, the coating transverse areal density data acquisition module is further configured to establish a cloud database based on the coating transverse areal density data if the first historical coating transverse areal density data does not exist prior to acquiring the coating transverse areal density data; if the first historical coating cross-directional areal density data exists before the coating cross-directional areal density data is obtained, the coating cross-directional areal density data is added to the cloud database.
In some embodiments, the self-learning areal density data acquisition module is further configured to select, in the cloud database, second historical coating lateral areal density data within a preset time interval; determining an areal density standard deviation based on the second historical coating transverse areal density data; and if the surface density standard deviation is smaller than or equal to a preset surface density standard deviation threshold value, taking the second historical coating transverse surface density data as self-learning surface density data.
In some embodiments, the tuning decision module is further configured to determine a control gain based on the self-learning areal density data; and if the control gain is larger than the surface density data threshold value, setting the parameters to be set of the closed-loop algorithm.
In some embodiments, the parameter to be set setting module is further configured to determine a proportional control gain and a speed control gain based on the self-learned areal density data; adjusting the control gain of the comparative example based on the action intensity of the surface density model; adjusting the speed control gain based on the response speed of the surface density model; and taking the adjusted proportional control gain and the adjusted speed control gain as the adjusted parameters to be adjusted.
In some embodiments, the transverse areal density control module is further configured to discretize a closed-loop algorithm to obtain a discrete sentence; a closed-loop algorithm is performed in the computer based on the discrete statement.
The device provided by the embodiment of the present invention has the same implementation principle and technical effects as those of the foregoing method embodiment, and for the sake of brevity, reference may be made to the corresponding content in the foregoing method embodiment where the device embodiment is not mentioned.
Example 4
Corresponding to the above method embodiment, the embodiment of the present invention provides an areal density model, which may be applied to the method of any of the above embodiments, and fig. 4 is a schematic structural diagram of an areal density model provided by the embodiment of the present invention, and as shown in fig. 4, the areal density model may include: a first controller 401 and a second controller 402.
Wherein the first controller 401 is used for controlling the transverse area density according to the coating transverse area density data, and the second controller 402 is used for predicting the transverse area density. In practical applications, if the transverse areal density value predicted by the second controller 402 cannot guarantee the consistency of the coating transverse areal density, self-learning areal density data is obtained to set the parameters to be set of the closed-loop algorithm, so as to reduce the mismatch capability of the areal density model and improve the anti-interference capability of the areal density model.
Example 5
The embodiment of the invention also provides electronic equipment, which is used for running the control method of the lithium battery coating transverse surface density; referring to fig. 5, an electronic device includes a memory 500 and a processor 501, where the memory 500 is configured to store one or more computer instructions, and the one or more computer instructions are executed by the processor 501 to implement the method for controlling the lateral areal density of a lithium battery coating.
Further, the electronic device shown in fig. 5 further includes a bus 502 and a communication interface 503, and the processor 501, the communication interface 503, and the memory 500 are connected by the bus 502.
The memory 500 may include a high-speed random access memory (RAM, random Access Memory), and may further include a non-volatile memory (non-volatile memory), such as at least one magnetic disk memory. The communication connection between the system network element and at least one other network element is implemented via at least one communication interface 503 (which may be wired or wireless), which may use the internet, a wide area network, a local network, a metropolitan area network, etc. Bus 502 may be an ISA bus, a PCI bus, an EISA bus, or the like. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, only one bi-directional arrow is shown in FIG. 5, but not only one bus or type of bus.
The processor 501 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuitry in hardware or instructions in software in the processor 501. The processor 501 may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU for short), a network processor (Network Processor, NP for short), etc.; but also digital signal processors (Digital Signal Processor, DSP for short), application specific integrated circuits (Application Specific Integrated Circuit, ASIC for short), field-programmable gate arrays (Field-Programmable Gate Array, FPGA for short) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be embodied directly in the execution of a hardware decoding processor, or in the execution of a combination of hardware and software modules in a decoding processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in the memory 500, and the processor 501 reads the information in the memory 500, and in combination with its hardware, performs the steps of the method of the previous embodiment.
The embodiment of the invention also provides a computer readable storage medium, which stores computer executable instructions that, when being called and executed by a processor, cause the processor to implement the method for controlling the transverse area density of the coating of the lithium battery, and the specific implementation can be seen in the method embodiment and will not be described herein.
The computer program product for performing the method for controlling the transverse areal density of lithium battery coating provided by the embodiment of the invention comprises a computer readable storage medium storing non-volatile program codes executable by a processor, wherein the instructions included in the program codes can be used for executing the method described in the method embodiment, and specific implementation can be seen in the method embodiment and will not be repeated here.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of 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.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer readable storage medium executable by a processor. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Finally, it should be noted that: the above examples are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention, but it should be understood by those skilled in the art that the present invention is not limited thereto, and that the present invention is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (10)
1. A method for controlling the coating transverse areal density of a lithium battery, the method comprising:
acquiring coating transverse surface density data in the lithium battery generation process;
determining an areal density model based on the coated transverse areal density data;
acquiring learning surface density data;
determining whether to set parameters to be set of a preset closed-loop algorithm or not based on a preset surface density data threshold value and the self-learning surface density data;
if the parameters to be set of the closed-loop algorithm are set, setting the parameters to be set of the closed-loop algorithm based on the self-learning surface density data and the surface density model;
and controlling the transverse surface density of the lithium battery coating based on the surface density model through the closed-loop algorithm after parameter setting.
2. The method of claim 1, wherein the determining an areal density model based on the coated transverse areal density data comprises:
determining a conditioning block displacement and a coating transverse areal density based on the coating transverse areal density data;
and establishing the surface density model by a step test method based on the displacement of the regulating block and the coating transverse surface density.
3. The method of claim 1, wherein after the acquiring the coated lateral areal density data of the lithium battery generation process, the method further comprises:
if the first historical coating transverse surface density data does not exist before the coating transverse surface density data is acquired, establishing a cloud database based on the coating transverse surface density data;
if the first historical coating transverse areal density data exists before the coating transverse areal density data is acquired, adding the coating transverse areal density data into the cloud database.
4. A method according to claim 3, wherein the obtaining of self-learning areal density data comprises:
selecting second historical coating transverse areal density data in a preset time interval from the cloud database;
determining an areal density standard deviation based on the second historical coating cross-directional areal density data;
and if the surface density standard deviation is smaller than or equal to a preset surface density standard deviation threshold, taking the second historical coating transverse surface density data as self-learning surface density data.
5. The method of claim 1, wherein the determining whether to set the preset closed-loop algorithm parameters to be set based on the preset surface density data threshold and the self-learning surface density data comprises:
determining a control gain based on the self-learning areal density data;
and if the control gain is larger than the surface density data threshold value, setting the parameter to be set of the closed-loop algorithm.
6. The method of claim 1, wherein the tuning the parameters to be tuned of the closed-loop algorithm based on the self-learning areal density data and the areal density model comprises:
determining a proportional control gain and a speed control gain based on the self-learning areal density data;
adjusting the proportional control gain based on the intensity of the action of the areal density model;
adjusting the speed control gain based on the response speed of the areal density model;
and taking the adjusted proportional control gain and the adjusted speed control gain as the adjusted parameters to be adjusted.
7. The method of claim 1, wherein after the tuning of the parameters to be tuned of the closed loop algorithm based on the self-learned areal density data and the areal density model, the method further comprises:
discretizing the closed-loop algorithm to obtain discrete sentences;
the closed loop algorithm is performed in a computer based on the discrete statement.
8. A control device for the coating transverse areal density of a lithium battery, the device comprising:
the coating transverse surface density data acquisition module is used for acquiring coating transverse surface density data in the lithium battery generation process;
an areal density model determination module for determining an areal density model based on the coated transverse areal density data;
the self-learning surface density data acquisition module is used for acquiring self-learning surface density data;
the setting judging module is used for determining whether to set the preset parameters to be set of the closed-loop algorithm or not based on a preset surface density data threshold value and the self-learning surface density data;
the to-be-set parameter setting module is used for setting the to-be-set parameter of the closed-loop algorithm based on the self-learning surface density data and the surface density model if the to-be-set parameter of the closed-loop algorithm is set;
and the transverse areal density control module is used for controlling the coating transverse areal density of the lithium battery based on the areal density model through the closed-loop algorithm after parameter setting.
9. An electronic device comprising a processor and a memory, the memory storing computer-executable instructions executable by the processor, the processor executing the computer-executable instructions to implement the method of controlling the lithium battery coated lateral areal density of any one of claims 1 to 7.
10. A computer readable storage medium storing computer executable instructions which, when invoked and executed by a processor, cause the processor to implement the method of controlling the coating transverse areal density of a lithium battery according to any one of claims 1 to 7.
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