Lithium battery workshop rotating wheel dehumidification control system and method

Abstract

The application discloses a lithium battery workshop rotary wheel dehumidification control system and method, relates to the rotary wheel dehumidification control technical field, and solves the technical problem that the prior art lacks clear consideration of effective dehumidification time in each process interval, does not dynamically adjust the operation parameters of the rotary wheel dehumidifier according to the target humidity difference of different processes and real-time environmental temperature and humidity, and causes the dehumidification rate of the dehumidifier to be unmatched with actual dehumidification demand; the application obtains process data and environmental data of a lithium battery workshop; the effective dehumidification time between each process in the lithium battery workshop is obtained based on the process data; the dehumidification demand rate is calculated based on the effective dehumidification time and the environmental data; the best rotating speed of the rotary wheel dehumidifier is obtained based on the dehumidification demand rate; the corresponding best regeneration power is obtained based on the best rotating speed; the best rotating speed and the corresponding best regeneration power are sent to the control system of the rotary wheel dehumidifier for adjustment, and the above technical problem is solved.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of rotary dehumidification control, and particularly relates to a lithium battery workshop rotary dehumidification control system and method. BACKGROUND

[0002] In lithium battery production, materials such as pole pieces, electrolyte and diaphragm involved in each process are highly sensitive to moisture. For example, the injection process needs to control the humidity to be less than or equal to 1% RH to avoid the reaction of electrolyte and moisture, and the packaging process also needs a specific humidity range. If the humidity control is improper, it will directly affect the performance of the materials, cause unstable process quality, and ultimately damage the product performance and quality of the lithium battery. Therefore, humidity control is the key to ensuring smooth production and product qualification.

[0003] In the prior art, a rotary dehumidifier is usually used to regulate the humidity in the workshop. The main method is to monitor the environmental humidity in real time through a sensor, and when the humidity exceeds the preset threshold, the operating parameters (such as speed and regeneration power) of the rotary dehumidifier are adjusted according to a fixed speed or a simple PID algorithm to achieve humidity control. However, in the rotary dehumidification control of the lithium battery workshop, the prior art does not fully combine the characteristics of the production process with environmental data for precise regulation, lacks clear consideration of the effective dehumidification time in each process interval, and does not dynamically adjust the operating parameters (such as speed and regeneration power) of the rotary dehumidifier according to the differences in target humidity of different processes and real-time environmental temperature and humidity. This results in a mismatch between the dehumidification rate of the dehumidifier and the actual dehumidification demand, either failing to reduce the workshop environmental humidity to the target humidity required by the subsequent process within the effective dehumidification time, affecting the quality stability of the humidity-sensitive process in lithium battery production, or over-dehumidifying, causing waste of regeneration power and other energy consumption of the rotary dehumidifier, and possibly causing equipment wear and tear due to unreasonable parameter setting, ultimately affecting production efficiency and product performance.

[0004] Therefore, the present application proposes a lithium battery workshop rotary dehumidification control system and method to solve the above problems. SUMMARY

[0005] The present application aims to at least solve one of the technical problems existing in the prior art. To this end, the present application proposes a lithium battery workshop rotary dehumidification control system and method to solve the technical problem that the prior art does not fully combine the characteristics of the production process with environmental data for precise regulation, lacks clear consideration of the effective dehumidification time in each process interval, and does not dynamically adjust the operating parameters of the rotary dehumidifier according to the differences in target humidity of different processes and real-time environmental temperature and humidity, resulting in a mismatch between the dehumidification rate of the dehumidifier and the actual dehumidification demand, thereby affecting the production efficiency and quality of the lithium battery workshop.

[0006] To achieve the above object, the first aspect of the present application provides a lithium battery workshop rotary dehumidification control system, comprising: a data acquisition module, a data analysis module and a rotary dehumidification control module;

[0007] The data acquisition module is used to acquire process data and environmental data of the lithium battery workshop.

[0008] The data analysis module is used to acquire effective dehumidification time between each process in the lithium battery workshop based on the process data, calculate a dehumidification demand rate based on the effective dehumidification time and the environmental data, acquire an optimal rotation speed of the rotary dehumidifier based on the dehumidification demand rate, and acquire a corresponding optimal regeneration power based on the optimal rotation speed.

[0009] The rotary dehumidification control module is used to send the optimal rotation speed and the corresponding optimal regeneration power to the control system of the rotary dehumidifier for adjustment.

[0010] Based on the above technical solution, in the lithium battery workshop rotary dehumidification control system provided by the present application, the present application realizes the deep binding of dehumidification control and production process by acquiring process data such as start and end time and target humidity of each process from the MES system and by collecting environmental temperature and humidity, and breaks the limitation that dehumidification operation is disconnected from the process in the prior art; the present application accurately calculates the effective dehumidification time by deducting non-dehumidification time such as material handling and equipment debugging from the process interval time, clearly defines the core time window of dehumidification operation, and makes up for the deficiency that the effective dehumidification time is not clearly considered in the prior art; on this basis, the actual water vapor pressure and water vapor density are acquired by calculating the saturated water vapor pressure through the Magnus formula in combination with the environmental data, and finally the total water vapor amount to be removed and the dehumidification demand rate are obtained, so that dynamic calculation according to the differences in target humidity of different processes and real-time environmental parameters is realized; for the dehumidification demand rate, a nonlinear relationship model containing a conversion adjustment coefficient is constructed to dynamically match the optimal rotation speed of the rotary dehumidifier, and it is simultaneously judged whether the effective dehumidification time is sufficient; if yes, the optimal rotation speed is solved through the model, and if not, the time is prolonged and the highest rotation speed is enabled, so as to ensure that the dehumidification rate is accurately matched with the actual demand, and the problem that the dehumidification rate and the demand are not matched in the prior art, which leads to failure to meet the standard or excessive dehumidification, is avoided; the optimal rotation speed and the regeneration power are cooperatively regulated through a composite regulation equation, the dehumidification efficiency and the energy consumption are taken into account, and the energy waste and equipment loss caused by excessive dehumidification are reduced, so that the problems such as insufficient combination of process characteristics and environmental data, lack of dynamic parameter adjustment, and mismatch between dehumidification rate and demand in the prior art are comprehensively solved, and the efficiency and quality stability of lithium battery production are ensured.

[0011] In combination with the above first aspect, in a possible implementation manner, the process data of the lithium battery workshop is acquired by:

[0012] extracting process data of the lithium battery workshop through an MES system; wherein the process data comprises: a starting time and an ending time of each process and a target humidity required by each process;

[0013] acquiring environmental data of the lithium battery workshop in real time through a data sensor; wherein the environmental data comprises: an environmental temperature and an environmental humidity.

[0014] It should be noted that the process refers to a phased production step in the lithium battery production process in a specific order, covering the key links of the whole process from raw material processing to cell forming, such as electrode coating, rolling, slitting, laminating / winding, packaging, liquid injection, formation, and separation; each process has a clear starting time and ending time, which can be tracked in real time through a production execution (MES) system, and is the core unit of the production rhythm and process connection of the lithium battery workshop;

[0015] The target humidity required by each process refers to the air humidity threshold that must be maintained in the workshop area of the process, which is pre-specified by the production standard according to the process characteristics and quality requirements of different processes in lithium battery production; its setting basis is the sensitivity of materials involved in each process (such as electrode, electrolyte, and separator) to moisture, for example, the liquid injection process requires very low humidity (usually ≤1% RH) to avoid the reaction of electrolyte with moisture, while the target humidity of the packaging process can be appropriately relaxed (such as ≤5% RH), and the ultimate goal is to ensure process quality stability and product performance.

[0016] In combination with the above first aspect, in a possible implementation manner, the effective dehumidification time between the processes in the lithium battery workshop is obtained based on the process data, comprising:

[0017] Based on the production sequence of the lithium battery workshop, the total interval time of each process interval is obtained by calculating the difference between the starting time of the next process and the ending time of the previous process;

[0018] Based on the historical production log of the lithium battery workshop, the non-dehumidification time of each process interval is obtained;

[0019] The effective dehumidification time of the corresponding process interval is obtained by calculating the difference between the total interval time and the non-dehumidification time of the corresponding process interval.

[0020] It should be noted that the process interval refers to the time span between two adjacent continuous processes in the lithium battery workshop, specifically the difference between the starting time of the next process and the ending time of the previous process, which is the time gap naturally formed by the connection of the previous and next processes in the production process, reflecting the time blank of process conversion in the production rhythm of the workshop;

[0021] The non-dehumidification time refers to a time during which the process interval cannot be used for the rotary dehumidifier to adjust humidity, mainly due to necessary production auxiliary operations in the process conversion process, such as material handling, transfer, equipment mold debugging, quality sampling, etc. after the previous process is completed, which will occupy part of the process interval time, resulting in that the time period does not have the conditions for dehumidification operation;

[0022] The effective dehumidification time refers to a time during which the process interval can be actually used for the rotary dehumidifier to adjust humidity, which is obtained by subtracting the non-dehumidification time from the total time length of the process interval, is a core time window for ensuring that the workshop environment humidity is reduced from the current value to the target humidity required by the subsequent process before the process starts, and directly determines the dehumidification efficiency of the dehumidifier and the setting basis of parameters such as rotation speed and regeneration power.

[0023] In combination with the above first aspect, in a possible implementation manner, the dehumidification demand rate is calculated based on the effective dehumidification time and the environment data, including:

[0024] Extracting the target humidity required by the process to be started and the current environment humidity of the area where the process is located, and marking the environment humidity as HS and the target humidity as MS;

[0025] Extracting the current environment temperature and marking it as HW;

[0026] Calculating the saturated water vapor pressure E at the current environment temperature by using the Magnus formula;

[0027] The Magnus formula is specifically: E=6.112×exp[(17.67×HW) / (HW+243.5)];

[0028] The actual water vapor pressure corresponding to the environment humidity is calculated by the formula e1=(HS×E) / 100; wherein e1 is the actual water vapor pressure corresponding to the environment humidity;

[0029] The actual water vapor pressure corresponding to the target humidity is calculated by the formula e2=(MS×E) / 100; wherein e2 is the actual water vapor pressure corresponding to the target humidity;

[0030] The water vapor density corresponding to the environment humidity is calculated by the formula ρ1=(e1×Mw) / (Rw×HW+273.15); wherein ρ1 is the water vapor density corresponding to the environment humidity, Mw is the molar mass of water, and Rw is the gas constant of water;

[0031] The water vapor density corresponding to the target humidity is calculated by the formula ρ2=(e2×Mw) / (Rw×HW+273.15); wherein ρ2 is the water vapor density corresponding to the target humidity;

[0032] The total water vapor amount to be removed from the current environment humidity to the target humidity is calculated by the formula Q=Vx(r1-r2), wherein Q is the total water vapor amount to be removed, and V is the area volume;

[0033] The dehumidification demand rate is calculated by the formula D=Q / AT, wherein D is the dehumidification demand rate, and AT is the effective dehumidification time corresponding to the interval between the process to be started and the previous process.

[0034] It should be noted that the area where the process is located refers to the workshop space range actually performed by a specific process in the production of lithium batteries. The area usually has a relatively independent environment control boundary (such as a sealed operation room where the liquid injection process is located, a production line area corresponding to the cutting process, etc.). The environment humidity, temperature and other parameters thereof need to be individually regulated according to the process requirements of the process, and it is a spatial object for which the dehumidification system implements precise humidity control;

[0035] The dehumidification demand rate refers to the water vapor mass to be removed from the air in the area per unit time in order to reduce the humidity in the area where the process is located from the current environment humidity to the target humidity within the effective dehumidification time. It is calculated by dividing the total water vapor amount to be removed by the effective dehumidification time, and is a core index for measuring the working strength of the dehumidifier, which directly determines the optimal rotation speed and regeneration power of the rotary dehumidifier required;

[0036] The area volume refers to the effective air space volume of the area where the process is located, that is, the three-dimensional space size actually containing air after deducting the solid occupied space of equipment, materials, tooling fixtures and the like in the area. The value thereof needs to be obtained in combination with the workshop layout drawing or on-site measurement;

[0037] 273.15 is used when calculating the water vapor density corresponding to the environment humidity and the target humidity, because the temperature unit corresponding to the water gas constant Rw used in the formula is Kelvin (absolute temperature), and the unit of the actual collected environment temperature HW is Celsius. 273.15 is the conversion constant of Celsius and Kelvin (i.e. Kelvin temperature = Celsius + 273.15), which can convert Celsius to Kelvin by adding 273.15 to the environment temperature HW, so as to match the temperature unit in the formula with the unit of the gas constant Rw, thereby accurately calculating the water vapor density reflecting the actual mass concentration of water vapor in the air, and providing a reliable basis for the subsequent calculation of the total water vapor amount and the dehumidification demand rate.

[0038] In combination with the above first aspect, in a possible implementation manner, the optimal rotation speed of the rotary dehumidifier is obtained based on the dehumidification demand rate, comprising:

[0039] A relationship model of the rotation speed of the rotary dehumidifier and the dehumidification rate is constructed.

[0040] The relationship model is specifically: D(N) = a x ln[(N+1)^(β x tanh(N))]+θ; wherein, D(N) is a dehumidification rate at a speed of N, a, β, and θ are conversion adjustment coefficients;

[0041] determining whether the rotary dehumidifier can complete the dehumidification task within the effective dehumidification time; if yes, inputting the dehumidification demand rate into the relationship model to obtain the optimal speed of the rotary dehumidifier; if no, extending the effective dehumidification time to the shortest completion time of the rotary dehumidifier, and taking the highest speed of the rotary dehumidifier as the optimal speed.

[0042] It should be noted that the conversion adjustment coefficient refers to a parameter in the relationship model of the speed of the rotary dehumidifier and the dehumidification rate, which is used to calibrate the matching degree of the model and the actual equipment characteristics; a mainly affects the overall scaling proportion of the dehumidification rate, β is used to adjust the nonlinear trend of the function with the speed, and θ corrects the baseline offset of the model, and the three work together to make the model accurately reflect the actual dehumidification rate characteristics of a specific rotary dehumidifier at different speeds;

[0043] The shortest completion time refers to, when the existing effective dehumidification time is insufficient for the rotary dehumidifier to complete the dehumidification task from the current humidity to the target humidity, the shortest dehumidification time that can be achieved by the rotary dehumidifier under its maximum dehumidification capacity (such as the highest speed, the optimal regeneration power); the time is determined by the physical performance of the equipment (such as the maximum dehumidification rate) and the dehumidification demand, and is the minimum time threshold to ensure that the dehumidification task is completed, and the original effective dehumidification time needs to be extended to the value to ensure that the process humidity meets the standard;

[0044] The highest speed refers to the maximum running speed of the rotary dehumidifier within the design safety range, which is jointly limited by the mechanical structure strength of the equipment, the performance limit of the adsorbent, and the energy consumption constraint; exceeding the speed may cause the rotary machine to wear out, the adsorbent to have too short contact time with air and the dehumidification efficiency to drop sharply, or cause equipment failure; when the effective dehumidification time is insufficient, taking it as the optimal speed can make the dehumidifier run at the maximum capacity and shorten the dehumidification time as much as possible.

[0045] In combination with the first aspect, in a possible implementation manner, the method for obtaining the conversion adjustment coefficient comprises:

[0046] obtaining the speeds of the rotary dehumidifiers and corresponding dehumidification rates from historical dehumidification records;

[0047] setting the sum of squares of errors as:

[0048] ;

[0049] Wherein, S is the error sum of squares, Ni refers to the rotating speed of the i th group of rotary dehumidifiers, Di refers to the dehumidification rate corresponding to the rotating speed of the i th group of rotary dehumidifiers, i={1, 2, 3, …, m}, and m is the total number of groups of the rotating speed and the corresponding dehumidification rate of the rotary dehumidifiers obtained from the historical dehumidification records;

[0050] The partial derivatives of a, β and θ in the error sum of squares formula are calculated, and the partial derivative values are set to zero to obtain a corresponding equation group.

[0051] The equation group is solved by a solving algorithm to obtain the optimal values of the conversion adjustment coefficients a, β and θ; wherein the solving algorithm includes matrix operation or Gaussian elimination.

[0052] It should be noted that the several groups of rotary dehumidifier rotating speeds (Ni) and corresponding dehumidification rates (Di) obtained from the historical dehumidification records provide actual observation basis for solving the model parameters, and these data directly reflect the real running characteristics of the equipment under different working conditions; the error sum of squares S is set, and its expression quantifies the total deviation between the model prediction value (the dehumidification rate calculated based on a, β and θ) and the actual observation value (Di); the smaller the deviation, the more accurate the simulation of the model to the actual situation; since the error sum of squares is a function of a, β and θ, to make the model optimal (i.e. the total deviation is minimum), the function needs to satisfy the condition of taking the minimum value, i.e. the partial derivatives of a, β and θ are calculated and the partial derivative values are set to zero, and the equation group obtained at this time corresponds to the parameter value condition of the minimum total deviation; the equation group can be solved by a solving algorithm such as matrix operation or Gaussian elimination, and the optimal values of a, β and θ that minimize the error sum of squares can be directly obtained, thereby ensuring that the rotary dehumidifier rotating speed and dehumidification rate relationship model constructed can accurately match the actual running characteristics of the equipment.

[0053] In combination with the first aspect, in a possible implementation manner, the judging whether the rotary dehumidifier can complete the dehumidification task within the effective dehumidification time includes:

[0054] The maximum rotating speed of the rotary dehumidifier is input into the relationship model to obtain the dehumidification rate corresponding to the maximum rotating speed.

[0055] It is judged whether the dehumidification demand rate is less than or equal to the dehumidification rate corresponding to the maximum rotating speed; if yes, the rotary dehumidifier can complete the dehumidification task within the effective dehumidification time; and if no, the rotary dehumidifier cannot complete the dehumidification task within the effective dehumidification time.

[0056] In combination with the first aspect, in a possible implementation manner, the inputting the dehumidification demand rate into the relationship model includes:

[0057] The dehumidification demand rate D is extracted.

[0058] Let D(N) = D input relation model, and solve, get the best speed of the rotary dehumidifier.

[0059] In combination with the first aspect, in a possible implementation manner, the obtaining of the corresponding optimal regeneration power based on the optimal speed comprises:

[0060] Mark the optimal speed of the rotary dehumidifier as ZN;

[0061] Extract the current time environmental humidity HS and the target humidity MS required by the process to be started;

[0062] Establish a compound control equation of the rotary speed and the regeneration power;

[0063] The compound control equation is specifically: P = A * ZN + B * |Delta d| ^ 2; wherein, P is the optimal regeneration power, A is a regeneration efficiency coefficient, B is a deviation penalty factor, and Delta d = HS-MS;

[0064] The optimal speed of the rotary dehumidifier is input into the compound control equation to obtain the optimal regeneration power corresponding to the optimal speed.

[0065] The second aspect of the application provides a lithium battery workshop rotary dehumidification control method, comprising:

[0066] Obtain the process data and environmental data of the lithium battery workshop;

[0067] Based on the process data, obtain the effective dehumidification time between each process in the lithium battery workshop;

[0068] Based on the effective dehumidification time and the environmental data, the dehumidification demand rate is calculated;

[0069] Based on the dehumidification demand rate, the optimal speed of the rotary dehumidifier is obtained;

[0070] Based on the optimal speed, the corresponding optimal regeneration power is obtained;

[0071] The optimal speed and the corresponding optimal regeneration power are sent to the control system of the rotary dehumidifier for adjustment.

[0072] Compared with the prior art, the beneficial effects of the application are:

[0073] The application integrates the process data of the MES system and the environmental data obtained by the sensor in real time through the data acquisition module, the data analysis module can accurately calculate the effective dehumidification time of each process interval, and based on the environmental temperature and humidity, the dehumidification demand rate meeting the actual demand is obtained through calculation, and then the optimal speed of the rotary dehumidifier and the corresponding regeneration power are determined; this dynamic adjustment based on the actual process demand and the environmental state can ensure that the workshop environmental humidity is accurately reduced to the target humidity required by the process before the subsequent process starts, effectively avoiding the quality problems caused by the influence of moisture on materials such as pole pieces and electrolyte due to insufficient dehumidification, and ensuring the quality stability of each key process.

[0074] The application determines the optimal speed by constructing the relationship model of the speed of the rotary dehumidifier and the dehumidification rate, combining the dehumidification demand rate, and obtaining the optimal regeneration power through the composite control equation based on the optimal speed and the humidity deviation, so that the operation parameters of the dehumidifier are highly matched with the actual dehumidification demand, and the energy waste caused by excessive dehumidification is avoided; in addition, by judging whether the effective dehumidification time is sufficient to complete the dehumidification task, the time is adjusted or the highest speed is adopted when necessary, which not only ensures the completion of the dehumidification task, but also reduces the mechanical wear of the equipment caused by unreasonable parameters, prolongs the service life of the equipment, and reduces the production cost while improving the production efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0075] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only some embodiments of the application, and for those skilled in the art, other drawings can be obtained without creative labor on the basis of these drawings.

[0076] Figure 1 The system module schematic diagram of the embodiment of the application is shown in the figure.

[0077] Figure 2 The method step schematic diagram of the embodiment of the application is shown in the figure. DETAILED DESCRIPTION

[0078] The technical solutions of the application will be described clearly and completely in combination with the embodiments. Obviously, the described embodiments are only some of the embodiments of the application, not all. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the application.

[0079] Please refer to Figure 1 The first aspect embodiment of the application provides a rotary dehumidification control system for lithium battery workshop, comprising: a data acquisition module, a data analysis module and a rotary dehumidification control module.

[0080] The data acquisition module is configured to acquire process data and environment data of the lithium battery workshop.

[0081] The process data of the lithium battery workshop is acquired, including:

[0082] The process data of the lithium battery workshop is extracted through the MES system; wherein, the process data includes: the start time and end time of each process and the target humidity required by each process;

[0083] The environment data of the lithium battery workshop is acquired in real time through the data sensor; wherein, the environment data includes: the environment temperature and the environment humidity.

[0084] The data analysis module is configured to acquire the effective dehumidification time between each process in the lithium battery workshop based on the process data; calculate the dehumidification demand rate based on the effective dehumidification time and the environment data; acquire the optimal rotation speed of the rotary dehumidifier based on the dehumidification demand rate; and acquire the corresponding optimal regeneration power based on the optimal rotation speed.

[0085] The effective dehumidification time between each process in the lithium battery workshop is acquired based on the process data, including:

[0086] The total interval time of each process interval is obtained by calculating the difference between the start time of the next process and the end time of the previous process between adjacent processes based on the production sequence of the lithium battery workshop.

[0087] The non-dehumidification time of each process interval is acquired based on the historical production log of the lithium battery workshop.

[0088] The effective dehumidification time of the corresponding process interval is obtained by calculating the difference between the total interval time and the non-dehumidification time of the corresponding process interval.

[0089] The dehumidification demand rate is calculated based on the effective dehumidification time and the environment data, including:

[0090] The target humidity required by the process to be started and the current environment humidity of the area where the process is located are extracted, and the environment humidity is marked as HS and the target humidity is marked as MS;

[0091] The environment temperature at the current time is extracted and marked as HW;

[0092] The saturated water vapor pressure E at the current environment temperature is calculated by using the Magnus formula;

[0093] The Magnus formula is specifically: E = 6.112 x exp[(17.67 x HW) / (HW + 243.5)];

[0094] An actual water vapor pressure corresponding to the environmental humidity is calculated by a formula e1=(HS×E) / 100; wherein, e1 is the actual water vapor pressure corresponding to the environmental humidity;

[0095] An actual water vapor pressure corresponding to the target humidity is calculated by a formula e2=(MS×E) / 100; wherein, e2 is the actual water vapor pressure corresponding to the target humidity;

[0096] A water vapor density corresponding to the environmental humidity is calculated by a formula ρ1=(e1×Mw) / (Rw×HW+273.15); wherein, ρ1 is the water vapor density corresponding to the environmental humidity, Mw is a molar mass of water, and Rw is a gas constant of water;

[0097] A water vapor density corresponding to the target humidity is calculated by a formula ρ2=(e2×Mw) / (Rw×HW+273.15); wherein, ρ2 is the water vapor density corresponding to the target humidity;

[0098] A total water vapor amount to be removed from the current environmental humidity to the target humidity is calculated by a formula Q=V×(ρ1-ρ2); wherein, Q is the total water vapor amount to be removed, and V is a volume of the area;

[0099] A dehumidification demand rate is calculated by a formula D=Q / ΔT; wherein, D is the dehumidification demand rate, and ΔT is an effective dehumidification time corresponding to a process interval between a process to be started and a previous process.

[0100] An optimal rotating speed of a rotary dehumidifier is obtained based on the dehumidification demand rate, comprising:

[0101] A relationship model of the rotating speed of the rotary dehumidifier and the dehumidification rate is constructed;

[0102] The relationship model is specifically: D(N)=α×ln[(N+1)^(β×tanh(N))]+θ; wherein, D(N) is the dehumidification rate at the rotating speed of N, and α, β, and θ are conversion adjustment coefficients;

[0103] It is judged whether the rotary dehumidifier can complete the dehumidification task within the effective dehumidification time; if yes, the dehumidification demand rate is input into the relationship model to obtain the optimal rotating speed of the rotary dehumidifier; if no, the effective dehumidification time is extended to the shortest completion time of the rotary dehumidifier, and the highest rotating speed of the rotary dehumidifier is taken as the optimal rotating speed.

[0104] A method for obtaining the conversion adjustment coefficients, comprising:

[0105] A plurality of sets of the rotating speed of the rotary dehumidifier and the corresponding dehumidification rate are obtained from historical dehumidification records;

[0106] An error sum of squares is set as:

[0107] ;

[0108] wherein, S is error sum of squares, Ni refers to the rotating speed of the i th group of rotary dehumidifiers, Di refers to the dehumidification rate corresponding to the rotating speed of the i th group of rotary dehumidifiers, i={1, 2, 3, …, m}, m is the total number of groups of the rotating speed and the corresponding dehumidification rate of the rotary dehumidifiers obtained from the historical dehumidification records;

[0109] The partial derivatives of a, β and θ in the error sum of squares formula are calculated, and the partial derivatives are set to zero to obtain the corresponding equation group;

[0110] The equation group is solved by a solving algorithm to obtain the optimal values of the conversion adjustment coefficients a, β and θ; wherein, the solving algorithm includes: matrix operation or Gaussian elimination method.

[0111] Judging whether the rotary dehumidifier can complete the dehumidification task within the effective dehumidification time, comprising:

[0112] The maximum rotating speed of the rotary dehumidifier is input into the relationship model to obtain the dehumidification rate corresponding to the maximum rotating speed;

[0113] Judging whether the dehumidification demand rate is less than or equal to the dehumidification rate corresponding to the maximum rotating speed; if yes, the rotary dehumidifier can complete the dehumidification task within the effective dehumidification time; if no, the rotary dehumidifier cannot complete the dehumidification task within the effective dehumidification time.

[0114] Inputting the dehumidification demand rate into the relationship model, comprising:

[0115] Extracting the dehumidification demand rate D;

[0116] Let D(N)=D input the relationship model and solve to obtain the optimal rotating speed of the rotary dehumidifier.

[0117] Based on the optimal rotating speed, the corresponding optimal regeneration power is obtained, comprising:

[0118] Marking the optimal rotating speed of the rotary dehumidifier as ZN;

[0119] Extracting the current environmental humidity HS and the target humidity MS required for the process to be started;

[0120] Establishing a compound control equation of the rotary speed and the regeneration power;

[0121] The compound control equation is specifically: P=A×ZN+B×∣Δd∣^2; wherein, P is the optimal regeneration power, A is a regeneration efficiency coefficient, B is a deviation penalty factor, and Δd=HS-MS;

[0122] The optimal rotating speed of the rotary dehumidifier is input into the compound control equation to obtain the optimal regeneration power corresponding to the optimal rotating speed.

[0123] Rotary dehumidification control module: used to send the optimal rotating speed and the corresponding optimal regeneration power to the control system of the rotary dehumidifier for adjustment.

[0124] For example, the specific application of the present application is described in detail in combination with the actual conversion scene of the lithium battery workshop "pole piece slitting process → liquid injection process":

[0125] A production line in a lithium battery workshop needs to complete the process conversion of "pole piece slitting → liquid injection", and the liquid injection process has very high humidity requirements (target humidity ≤1%RH), and the specific parameters are as follows:

[0126] 1. The basic data obtained by the data acquisition module;

[0127] Process data (from MES system):

[0128] End time of pole piece slitting process: 10:30;

[0129] Start time of liquid injection process: 10:50;

[0130] Target humidity (MS) of liquid injection process: 1%RH;

[0131] Environmental data (real-time acquisition from sensor):

[0132] Current environmental humidity (HS) of the area where the liquid injection process is located: 6%RH;

[0133] Current environmental temperature (HW): 25℃;

[0134] Volume of liquid injection area (V): 800m³ (effective air volume excluding equipment);

[0135] 2. The data analysis module calculates the effective dehumidification time;

[0136] Total interval time: start time of liquid injection process - end time of slitting process = 20 minutes;

[0137] Non-dehumidification time: according to historical production log, 3 minutes are needed for pole piece transportation after slitting to the liquid injection area, and 5 minutes are needed for mold adjustment of liquid injection machine, totaling 8 minutes;

[0138] Effective dehumidification time (ΔT): total interval time - non-dehumidification time = 12 minutes (i.e. 0.2 hours);

[0139] 3. Calculate the dehumidification demand rate;

[0140] Step 1: Calculate the saturated water vapor pressure (E);

[0141] Magnus formula is adopted: E=6.112×exp[(17.67×HW) / (HW+243.5)];

[0142] Substitute the data, E≈33.43 hPa;

[0143] Step 2: Calculate the actual water vapor pressure;

[0144] The actual water vapor pressure (e1) corresponding to the ambient humidity:

[0145] e1=(HS×E) / 100=(6×33.43) / 100≈2.01 hPa;

[0146] The actual water vapor pressure (e2) corresponding to the target humidity:

[0147] e2=(MS×E) / 100=(1×33.43) / 100≈0.33 hPa;

[0148] Step 3: Calculate the water vapor density;

[0149] The molar mass of water (Mw) = 18 g / mol, the gas constant of water (Rw) = 461.5 J / (kg·K), and the temperature is converted to Kelvin: 25 + 273.15 = 298.15 K;

[0150] Calculate the water vapor density (ρ1) corresponding to the ambient humidity by the formula ρ1=(e1×Mw) / [Rw×(HW+273.15)];

[0151] Substitute the data, ρ1≈0.0263 kg / m 3 ;

[0152] Calculate the water vapor density (ρ2) corresponding to the target humidity by the formula ρ2=(e2×Mw) / [Rw×(HW+273.15)];

[0153] Substitute the data, ρ2≈0.0043 kg / m 3 ;

[0154] Step 4: Calculate the total water vapor quantity (Q) and the dehumidification demand rate (D);

[0155] Total water vapor quantity to be removed:

[0156] Q=V×(ρ1-ρ2)=800×(0.0263-0.0043)=17.6 kg;

[0157] Dehumidification demand rate (water vapor quantity to be removed per unit time):

[0158] D=Q / ΔT=17.6 / 0.2=88 kg / h;

[0159] 4. Determine the optimal rotation speed of the rotary dehumidifier;

[0160] The relationship model parameters: fitted by experiment, the relationship model between the rotation speed and the dehumidification rate of the workshop rotary dehumidifier is D(n)=a x ln[(N+1)^(b x tanh(N))]+0; where a=12, b=0.8, 0=0.5, N is the rotation speed, unit r / h;

[0161] Judging the feasibility of the dehumidification task:

[0162] The maximum rotation speed of the dehumidifier is 30 r / h, and the maximum dehumidification rate is obtained by substituting the model:

[0163] D(30)=12 x ln[(30+1)^(0.8 x tanh(30))]+0.5≈33.4 kg / h;

[0164] At this time, the dehumidification demand rate (88 kg / h) is greater than the maximum dehumidification rate (33.4 kg / h), and it is determined that the existing effective dehumidification time (12 minutes) is insufficient.

[0165] Adjusting the effective dehumidification time and determining the optimal rotation speed:

[0166] The shortest completion time: total water vapor amount / maximum dehumidification rate=17.6 kg / 33.4 kg / h≈0.527 h (about 32 minutes);

[0167] The effective dehumidification time is extended to 32 minutes (the MES system needs to be coordinated to delay the start time of the liquid injection process to 11:10), and the highest rotation speed 30 r / h is used as the optimal rotation speed to ensure that the dehumidification is completed within 32 minutes.

[0168] 5. Calculate the optimal regeneration power;

[0169] The composite control equation: the regeneration power control equation of the workshop is P=A x ZN+B x |Ad|2; where A=0.8, B=1.2, Ad=HS-MS=6-1=5;

[0170] The optimal regeneration power:

[0171] P=0.8 x 30+1.2 x |5|2=54 kW.

[0172] 6. Control execution and results;

[0173] The optimal rotation speed 30 r / h and the regeneration power 54 kW are sent to the dehumidifier by the rotary dehumidification control module, and the humidity in the liquid injection area is reduced from 6% RH to 1% RH within 32 minutes. The liquid injection process starts on time at 11:10, and the humidity fully meets the process requirements.

[0174] The application binds process data and environmental parameters, accurately calculates effective dehumidification window and dehumidification demand, and dynamically matches device parameters using a nonlinear model. The application not only solves the problem of unqualified humidity caused by the disconnection between traditional control and process, but also avoids energy waste caused by blindly increasing power by coordinating the speed and regeneration power, thereby significantly improving production stability and energy efficiency.

[0175] Referring to Figure 2 The second aspect of the application provides a lithium battery workshop rotary dehumidification control method, comprising:

[0176] Obtain process data and environmental data of the lithium battery workshop;

[0177] Based on the process data, obtain the effective dehumidification time between each process in the lithium battery workshop;

[0178] Based on the effective dehumidification time and the environmental data, calculate the dehumidification demand rate;

[0179] Based on the dehumidification demand rate, obtain the optimal speed of the rotary dehumidifier;

[0180] Based on the optimal speed, obtain the corresponding optimal regeneration power;

[0181] Send the optimal speed and the corresponding optimal regeneration power to the control system of the rotary dehumidifier for adjustment.

[0182] Some data in the above formula is calculated by removing the dimension and taking the numerical value. The formula is obtained by software simulation of a large amount of collected data to obtain a formula closest to the real situation. The preset parameters and the preset threshold in the formula are set by a person skilled in the art according to the actual situation or obtained by a large amount of data simulation.

[0183] The above embodiments are only used to illustrate the technical method of the application and are not limiting. Although the application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the application can be modified or replaced equivalently without departing from the spirit and scope of the technical method of the application.

Claims

1. A lithium battery plant trolley wheel dehumidification control system, characterized in that, The application relates to a lithium battery workshop rotary dehumidification control method, which comprises the following steps: A data acquisition module, a data analysis module and a rotary dehumidification control module are provided. The data acquisition module is used for acquiring process data and environment data of the lithium battery workshop. The data analysis module is used for acquiring effective dehumidification time between processes in the lithium battery workshop based on the process data, calculating a dehumidification demand rate based on the effective dehumidification time and the environment data, acquiring an optimal rotary speed of a rotary dehumidifier based on the dehumidification demand rate, and acquiring corresponding optimal regeneration power based on the optimal rotary speed. The rotary dehumidification control module is used for sending the optimal rotary speed and the corresponding optimal regeneration power to a control system of the rotary dehumidifier for adjustment. The optimal rotary speed of the rotary dehumidifier based on the dehumidification demand rate comprises the following steps: A relationship model of the rotary speed and the dehumidification rate of the rotary dehumidifier is constructed. The relationship model is specifically D(N)=alpha*ln[(N+1)^(beta*tanh(N))]+theta, wherein D(N) is the dehumidification rate under the rotary speed N, alpha, beta and theta are conversion adjustment coefficients. It is judged whether the rotary dehumidifier can complete the dehumidification task within the effective dehumidification time; if yes, the dehumidification demand rate is input into the relationship model to obtain the optimal rotary speed of the rotary dehumidifier; if not, the effective dehumidification time is prolonged to the shortest completion time of the rotary dehumidifier, and the highest rotary speed of the rotary dehumidifier is taken as the optimal rotary speed.

2. A lithium battery plant transfer wheel dehumidification control system according to claim 1, characterized in that, The process data of the lithium battery workshop comprises the following steps: Process data of the lithium battery workshop is extracted through an MES system, wherein the process data comprises starting time and ending time of each process and target humidity required by each process. Environment data of the lithium battery workshop is acquired in real time through a data sensor, wherein the environment data comprises environment temperature and environment humidity.

3. The lithium battery plant transfer wheel dehumidification control system of claim 1, wherein, The effective dehumidification time between processes in the lithium battery workshop based on the process data comprises the following steps: Based on the production sequence of the lithium battery workshop, the total interval time of each process interval is obtained by calculating the difference between the starting time of the next process and the ending time of the previous process between adjacent processes. Based on the historical production log of the lithium battery workshop, the non-dehumidification time of each process interval is obtained. The effective dehumidification time of the corresponding process interval is obtained by calculating the difference between the total interval time and the non-dehumidification time of the corresponding process interval.

4. The lithium battery plant transfer wheel dehumidification control system of claim 1, wherein, The dehumidification demand rate calculated based on the effective dehumidification time and the environment data comprises the following steps: The target humidity required by the process to be started and the current environment humidity of the area where the process is located are extracted, and the environment humidity is marked as HS and the target humidity is marked as MS. The environment temperature at the current moment is extracted and marked as HW. The saturated water vapor pressure E under the environment temperature at the current moment is calculated by using a Magnus formula. The Magnus formula is specifically E=6.112*exp[(17.67*HW) / (HW+243.5)]. The actual water vapor pressure corresponding to the environment humidity is calculated by using a formula e1=(HS*E) / 100; wherein e1 is the actual water vapor pressure corresponding to the environment humidity. The actual water vapor pressure corresponding to the target humidity is calculated by using a formula e2=(MS*E) / 100; wherein e2 is the actual water vapor pressure corresponding to the target humidity. The water vapor density corresponding to the ambient humidity is calculated by the formula p1=(e1*Mw) / (Rw*HW+273.15); wherein, p1 is the water vapor density corresponding to the ambient humidity, Mw is the molar mass of water, and Rw is the gas constant of water; The water vapor density corresponding to the target humidity is calculated by the formula p2=(e2*Mw) / (Rw*HW+273.15); wherein, p2 is the water vapor density corresponding to the target humidity; The total water vapor amount to be removed from the current ambient humidity to the target humidity is calculated by the formula Q=V*(p1-p2); wherein, Q is the total water vapor amount to be removed, and V is the volume of the area; The dehumidification demand rate is calculated by the formula D=Q / AT; wherein, D is the dehumidification demand rate, and AT is the effective dehumidification time corresponding to the interval between the process to be started and the previous process.

5. The lithium battery plant transfer wheel dehumidification control system of claim 1, wherein, The method for obtaining the conversion adjustment coefficient comprises: Obtaining the rotation speed of the rotary dehumidifier and the corresponding dehumidification rate from historical dehumidification records; Setting the error sum of squares as follows: ； wherein, S is the error sum of squares, Ni is the rotation speed of the i-th rotary dehumidifier, Di is the dehumidification rate corresponding to the rotation speed of the i-th rotary dehumidifier, i={1, 2, 3, …, m}, and m is the total number of groups of the rotation speed of the rotary dehumidifier and the corresponding dehumidification rate obtained from the historical dehumidification records; Deriving the partial derivatives of a, b, and theta in the error sum of squares formula, and setting the partial derivatives to zero to obtain the corresponding equation group; Solving the equation group by a solving algorithm to obtain the optimal values of the conversion adjustment coefficients a, b, and theta; wherein, the solving algorithm comprises: matrix operation or Gaussian elimination.

6. The lithium battery plant transfer wheel dehumidification control system of claim 1, wherein, The method for judging whether the rotary dehumidifier can complete the dehumidification task within the effective dehumidification time comprises: Inputting the maximum rotation speed of the rotary dehumidifier into the relationship model to obtain the dehumidification rate corresponding to the maximum rotation speed; Judging whether the dehumidification demand rate is less than or equal to the dehumidification rate corresponding to the maximum rotation speed; if yes, the rotary dehumidifier can complete the dehumidification task within the effective dehumidification time; if no, the rotary dehumidifier cannot complete the dehumidification task within the effective dehumidification time.

7. The lithium battery plant transfer wheel dehumidification control system of claim 1, wherein, The method for inputting the dehumidification demand rate into the relationship model comprises: Extracting the dehumidification demand rate D; Inputting D(N)=D into the relationship model and solving to obtain the optimal rotation speed of the rotary dehumidifier.

8. The lithium battery plant transfer wheel dehumidification control system of claim 1, wherein, The method for obtaining the corresponding optimal regeneration power based on the optimal rotation speed comprises: Marking the optimal rotation speed of the rotary dehumidifier as ZN; Extracting the ambient humidity HS at the current time and the target humidity MS required by the process to be started; Establishing a composite control equation of the rotation speed of the rotary dehumidifier and the regeneration power; The composite control equation is specifically: P=A*ZN+B*(HS-MS)^2; wherein, P is the optimal regeneration power, A is a regeneration efficiency coefficient, B is a deviation penalty factor, and HS-MS is Δd; Inputting the optimal rotation speed of the rotary dehumidifier into the composite control equation to obtain the optimal regeneration power corresponding to the optimal rotation speed.

9. A lithium battery workshop rotary dehumidification control method applied to the lithium battery workshop rotary dehumidification control system of any one of claims 1-8, characterized in that, Comprise: Obtaining process data and environmental data of a lithium battery workshop; Obtaining the effective dehumidification time between each process in the lithium battery workshop based on the process data; Calculating the dehumidification demand rate based on the effective dehumidification time and the environmental data; Based on the dehumidification demand rate, an optimal rotating speed of the rotary dehumidifier is obtained; Based on the optimal rotating speed, a corresponding optimal regeneration power is obtained; The optimal rotating speed and the corresponding optimal regeneration power are sent to a control system of the rotary dehumidifier for adjustment.

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