An online estimation method and device for evaporation amount of lithium battery pole piece coating and drying

Abstract

The application discloses an online estimation method and device for evaporation quantity of lithium battery pole piece coating and drying, which comprises the following steps: obtaining the solvent mass ratio of the pole piece at the entrance of the oven, the total solvent residual mass ratio at the outlet of the oven and the outlet area density, and calculating the total evaporation solvent mass of the pole piece area per unit length; collecting humidity through the temperature and humidity sensors arranged at the air inlet and air outlet of each oven to obtain the absolute humidity of the air inlet and the absolute humidity of the air outlet corresponding to each oven; based on the mass conservation equation, the optimization problem is constructed according to the absolute humidity of the air inlet, the absolute humidity of the air outlet and the change rate of the absolute humidity of the air outlet with time, and the particle swarm optimization algorithm is used to solve the optimization problem to obtain the evaporation quantity per unit time of each oven; the evaporation quantity per unit time and the residence time of the pole piece in the single oven are calculated to obtain the solvent evaporation component of the pole piece in each oven, and the sum of the solvent evaporation components of each oven is equal to the total evaporation solvent mass.

Description

Technical Field

[0001] This invention relates to the field of lithium battery electrode drying technology, and in particular to an online estimation method, apparatus and equipment for the evaporation amount of lithium battery electrode coating drying. Background Technology

[0002] In the manufacturing process of lithium battery electrodes, drying after electrode coating is a crucial step to ensure battery performance and safety. This process first involves coating a slurry containing active materials onto a current collector, followed by rapid passage of the electrode through a drying system consisting of multiple ovens connected in series. Within the system, the electrode is suspended by hot air, and the solvent in the slurry needs to evaporate sufficiently during the brief residence time of the electrode as it passes through the oven. This ensures that the residual solvent at the electrode outlet is controlled within a reasonable range, meeting the requirements for electrode adhesion and mechanical integrity, thereby guaranteeing electrode quality and the smooth progress of subsequent processes. The electrode drying process involves complex heat and mass transfer mechanisms. The heat exchange mechanisms differ significantly between different drying stages (preheating, constant-rate drying, and deceleration drying), and the evaporation capacity of each oven also varies accordingly. In actual production, the setting of oven process parameters (such as heating temperature, fan frequency, and valve opening) usually relies on the accumulated experience of process engineers and is repeatedly revised based on the test data of the outlet electrode after trial production. For new grades or new materials, multiple experimental comparisons are often required to determine a relatively suitable process formulation.

[0003] However, due to the high speed of the coating process and the complex internal environment of the drying oven, it is difficult to directly measure the solvent evaporation rate of each section of the oven, resulting in a lack of data support for the quantitative analysis of the drying process. In existing technologies, the measurement of solvent residue is usually only performed at the main outlet of the oven, which cannot reflect the drying process inside each section of the oven. This "single-point measurement, multi-point control" mode allows for excessive freedom in adjusting process parameters, making it difficult to achieve precise and efficient process optimization, thus restricting the accuracy and intelligence level of process control. Summary of the Invention

[0004] In view of this, the purpose of this invention is to propose an online estimation method, device and equipment for the evaporation amount of lithium battery electrode coating drying, which aims to solve the problems in the prior art that the lack of quantitative monitoring means for the evaporation process inside multi-section drying ovens leads to the reliance on experience for setting drying process parameters and the difficulty in achieving precise control.

[0005] To achieve the above objectives, the present invention provides an online estimation method for the evaporation amount of lithium battery electrode coating drying, the method comprising:

[0006] Obtain the solvent mass percentage at the oven inlet, the total residual solvent mass percentage at the oven outlet, and the outlet surface density of the electrode, and calculate the total evaporated solvent mass per unit length of the electrode region based on the solvent mass percentage, the total residual solvent mass percentage, and the outlet surface density;

[0007] Humidity is collected by temperature and humidity sensors installed at the air inlet and air outlet of each oven section, and the absolute humidity of the air inlet and air outlet of each oven section is obtained.

[0008] Based on the mass conservation equation, an optimization problem is constructed according to the absolute humidity of the inlet air, the absolute humidity of the outlet air, and the rate of change of the absolute humidity of the outlet air over time. The particle swarm optimization algorithm is used to solve the optimization problem to obtain the evaporation rate per unit time of each oven section.

[0009] The solvent evaporation amount of the electrode in each oven section is calculated based on the evaporation rate per unit time and the residence time of the electrode in a single oven section. The sum of the solvent evaporation amounts in each oven section is equal to the total mass of the evaporated solvent.

[0010] Preferably, the calculation of the total mass of evaporated solvent per unit length of electrode region based on the solvent mass percentage, the total mass percentage of residual solvent, and the outlet areal density includes:

[0011] The coating surface area of ​​the electrode area per unit length is determined based on the current collector width, the coating blank size, and the preset unit cut length.

[0012] The coating quality per unit length of electrode area at the oven outlet is calculated based on the outlet surface density and the coating surface area.

[0013] The solvent mass percentage, the total residual solvent mass percentage, and the coating quality are expressed by the formula. Calculations were performed to obtain the total mass of the evaporated solvent, where, Indicates coating quality, Indicates the percentage of solvent by mass. This indicates the percentage of total residual solvent mass.

[0014] Preferably, the optimization problem based on the mass conservation equation, according to the absolute humidity of the inlet air, the absolute humidity of the outlet air, and the rate of change of the absolute humidity of the outlet air over time, includes:

[0015] Using the mass conservation equation A mass conservation relationship is established, and the filtered value of the absolute humidity of the outlet air is used as an approximation of the absolute humidity inside the oven. Where, This represents the absolute humidity inside the i-th section of the oven. This represents the rate of change calculated based on the filtered value of the absolute humidity of the outlet air. Indicates the internal volume of the oven. This represents the evaporation rate per unit time. Indicates air density, Indicates the length of a single section of the drying oven. This represents the length of the electrode region per unit length. Indicates the absolute humidity of the air outlet. and These represent the inlet air volumetric flow rate and the outlet air volumetric flow rate of the oven, respectively.

[0016] The optimization objective is to minimize the L2 norm of the difference between the derivatives of the measured absolute humidity values ​​of the multi-section oven and the estimated absolute humidity values ​​calculated based on the mass conservation equation. A fitness function is constructed to solve the optimization problem. The measured absolute humidity values ​​are filtered values ​​based on the absolute humidity of the outlet air, and the estimated absolute humidity values ​​are calculated by inputting the evaporation rate per unit time, the inlet air volume flow rate, and the outlet air volume flow rate into the mass conservation equation.

[0017] Preferably, the fitness function for solving the optimization problem is constructed with minimizing the L2 norm of the difference between the derivatives of the measured absolute humidity values ​​of the multi-section oven and the estimated absolute humidity values ​​calculated based on the mass conservation equation as the optimization objective, including:

[0018] Constructing the fitness function In the formula, This indicates the total number of sections in the oven. Let represent the derivative of the measured absolute humidity value of the oven in section i. Let represent the derivative of the absolute humidity estimate of the oven in section i.

[0019] Preferably, the step of using particle swarm optimization algorithm to solve the optimization problem to obtain the evaporation rate per unit time of each oven section includes:

[0020] During the period when the oven reaches a steady state, multiple sets of time series measurement data of inlet and outlet absolute humidity were collected.

[0021] With the fitness function as the objective, the particle swarm optimization algorithm is used to iteratively search for the optimal estimates of the evaporation rate per unit time, the inlet air volume flow rate, and the outlet air volume flow rate based on multiple sets of the measurement data, and the evaporation rate per unit time of each oven section is extracted from the optimal estimates.

[0022] Preferably, the method further includes:

[0023] The solvent residue mass percentage at the outlet of each oven section is calculated based on the solvent evaporation fraction, the solvent mass percentage, and the total solvent residue mass percentage.

[0024] Preferably, the step of recursively calculating the solvent residual mass percentage at the outlet of each oven section based on the solvent evaporation fraction, the solvent mass percentage, and the total solvent residual mass percentage includes:

[0025] according to Perform recursive calculations, where, Indicates the amount of solvent evaporated. The coating quality per unit length of electrode area at the oven outlet is calculated from the outlet areal density C and the area of ​​the electrode area per unit length. This indicates the percentage of solvent residue at the outlet of the (i-1)th oven section. This represents the percentage of solvent residue at the outlet of the i-th oven. Equal to the solvent mass ratio at the oven inlet , Equal to the total mass percentage of solvent residue at the oven outlet .

[0026] Preferably, the method further includes:

[0027] The oven is judged to have reached a steady state based on the variation of the optimal estimated values ​​of the inlet volume flow rate and the outlet volume flow rate over a continuous time series. Specifically, the oven is judged to have reached a steady state when the variation is less than a preset threshold.

[0028] When the oven reaches a steady state, record the solvent evaporation component of each oven section under the current steady-state operating conditions and the corresponding oven process parameters, and generate a historical data mapping table. The oven process parameters include at least one of the following: oven heating temperature, hot air circulation fan frequency, exhaust fan frequency, fresh air valve opening degree, and exhaust valve opening degree.

[0029] Based on the target solvent residue percentage or target evaporation fraction, the adjustment amount of the oven process parameters is determined according to the historical data mapping table.

[0030] To achieve the above objectives, the present invention also provides an online estimation device for the evaporation amount of lithium battery electrode coating drying, the device comprising:

[0031] The acquisition unit is used to acquire the solvent mass ratio at the oven inlet, the total residual solvent mass ratio at the oven outlet, and the outlet surface density of the electrode, and to calculate the total mass of evaporated solvent per unit length of electrode region based on the solvent mass ratio, the total residual solvent mass ratio, and the outlet surface density.

[0032] The data acquisition unit is used to collect humidity data by using temperature and humidity sensors installed at the air inlet and air outlet of each oven section, so as to obtain the absolute humidity of the air inlet and the absolute humidity of the air outlet of each oven section.

[0033] The construction unit is used to construct an optimization problem based on the mass conservation equation, according to the absolute humidity of the inlet air, the absolute humidity of the outlet air, and the rate of change of the absolute humidity of the outlet air over time, and to solve the optimization problem using the particle swarm optimization algorithm to obtain the evaporation rate per unit time of each oven section.

[0034] The calculation unit is used to calculate the solvent evaporation amount of the electrode in each oven section based on the evaporation amount per unit time and the residence time of the electrode in a single oven section, wherein the sum of the solvent evaporation amounts in each oven section is equal to the total mass of the evaporated solvent.

[0035] To achieve the above objectives, the present invention also proposes an online estimation device for the evaporation amount of lithium battery electrode coating drying, comprising a processor, a memory, and a computer program stored in the memory, wherein the computer program is executed by the processor to implement the steps of the online estimation method for the evaporation amount of lithium battery electrode coating drying as described in the above embodiments.

[0036] To achieve the above objectives, the present invention also proposes a computer-readable storage medium storing a computer program that is executed by a processor to implement the steps of an online estimation method for the evaporation amount of lithium battery electrode coating drying as described in the above embodiments.

[0037] Beneficial effects:

[0038] The above scheme establishes a macroscopic quality benchmark by acquiring the solvent ratio at the oven inlet, the residual solvent ratio at the outlet, and the outlet surface density. Then, combining this with temperature and humidity sensor data from the inlet and outlet of each oven section, an optimization problem is constructed based on the mass conservation equation and solved using a particle swarm optimization algorithm. This enables online prediction and estimation of the evaporation rate per unit time for each oven section. This method transforms the evaporation process, which cannot be directly measured, into a quantifiable and solvable mathematical problem. Specifically, by using easily implemented online temperature and humidity measurements, combined with mass conservation and optimization algorithms, the real-time evaporation rate of each oven section can be indirectly and accurately derived. This fundamentally changes the traditional passive mode of relying on outlet results for back-calculation and trial and error. It provides a direct data foundation for real-time monitoring, precise analysis, and proactive control of the drying process, and is key to improving process controllability and intelligence, overcoming the limitations of traditional methods that rely on experience-based adjustments.

[0039] Based on the evaporation amount obtained from each oven section, the residual solvent ratio at the outlet of each oven section is further calculated. This transforms the predicted evaporation data into a direct insight into the "intermediate state" of the drying process, enabling a "penetrating view" of the internal state of the drying process. This allows operators to intuitively understand the drying progress of the electrodes in each oven section, providing a clear quantitative basis for targeted adjustments to process parameters. Consequently, it enables refined segmented monitoring of the entire multi-section drying process, providing precise quantitative basis for targeted adjustments to the process parameters of each oven section to achieve more balanced and efficient drying. This effectively solves the problem that traditional "single-point measurement" cannot reflect the internal state.

[0040] By specifically defining the calculation process for the total mass of the evaporated solvent, it clarifies the complete calculation process from electrode geometry and areal density to coating quality and final total evaporation, ensuring the accuracy and consistency of the quality benchmark for all subsequent online estimation steps. This enhances the robustness and reliability of the entire prediction method, ensures that the prediction results conform to the basic law of conservation of mass, and avoids deviations from physical reality due to data errors.

[0041] By introducing a filtered value of the absolute humidity of the outlet air as an approximation of the internal humidity, the dynamic rate of change is quantified. A fitness function is constructed with the objective of minimizing the L2 norm of the difference between the derivatives of the measured and estimated humidity, making the optimization problem solvable. A particle swarm optimization algorithm is employed for iterative search based on steady-state multi-set data, ensuring the accuracy and robustness of the solution. This technical solution organically combines physical mechanisms with intelligent optimization algorithms, possessing a solid theoretical basis and good engineering feasibility, significantly improving the accuracy and reliability of evaporation estimation.

[0042] Steady-state determination is performed based on the estimated changes in inlet and outlet air volumetric flow rates. During steady-state operation, the evaporation component and corresponding process parameters are recorded, generating a historical data mapping table. This allows for a traceable correlation between process parameters and evaporation effects under each stable operating condition, providing data-driven decision-making for subsequent process adjustments. The function of querying adjustment amounts based on target residual or target evaporation amounts transforms the process from "experience-based trial and error" to "data-driven guidance," significantly improving the efficiency and accuracy of process optimization. By converting predicted data into executable process instructions, reliance on operator experience is greatly reduced, providing a powerful support tool for the rapid introduction of new grades, rapid correction of process anomalies, and intelligent, adaptive optimization of the production process. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a flowchart illustrating an online estimation method for the evaporation amount of lithium battery electrode coating drying, as provided in an embodiment of the present invention.

[0045] Figure 2 This is a schematic diagram of an online estimation device for the evaporation amount of lithium battery electrode coating drying, provided in an embodiment of the present invention.

[0046] The realization of the invention's objective, its functional characteristics, and advantages will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to represent selected embodiments of the invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] The present invention will be described in detail below with reference to the embodiments.

[0049] Reference Figure 1 The diagram shows a flowchart illustrating an online estimation method for the evaporation amount during coating and drying of lithium battery electrodes, according to an embodiment of the present invention. In this embodiment, the method includes:

[0050] S11, Obtain the solvent mass percentage of the electrode at the oven inlet. The percentage of total solvent residue at the oven outlet The outlet surface density C is calculated, and the total mass of evaporated solvent per unit length of electrode region is calculated based on the solvent mass percentage, the total mass percentage of residual solvent, and the outlet surface density.

[0051] Furthermore, in step S11, calculating the total mass of evaporated solvent per unit length of electrode region based on the solvent mass ratio, the total mass ratio of residual solvent, and the outlet areal density includes:

[0052] S11-1, Determine the coating surface area of ​​the electrode area per unit length based on the current collector width, coating blank size and preset unit cut length;

[0053] S11-2, Calculate the coating quality per unit length of electrode area at the oven outlet based on the outlet surface density C and the coating surface area. ;

[0054] S11-3, the solvent mass ratio The total mass percentage of the solvent residue and the mass of the coating Through formula Calculations were performed to obtain the total mass of the evaporated solvent. In the formula, Indicates coating quality, Indicates the percentage of solvent by mass. This indicates the percentage of total residual solvent mass.

[0055] In this embodiment, taking negative electrode coating as an example, the solvent is water. The solvent mass percentage A% at the oven inlet of the electrode is obtained from the production slurry label. For example, if the solid content of a certain batch of negative electrode slurry is 50%, then A% = 50%. At the same time, the total solvent residual mass percentage B% at the oven outlet of the electrode is obtained by an online moisture meter set at the oven outlet. For example, if the process requires the outlet residual amount to be controlled at about 1%, then B% = 1%. In addition, the outlet areal density (net weight) C of the electrode is obtained by an online areal density meter set at the oven outlet, with the unit being g / m² or mg / m².

[0056] Taking continuous coating in a single film area as an example, if the width of the current collector foil is Width (in mm) and the margins on both sides are Margin (in mm), then the effective coating width is (Width - 2). Margin); a preset unit cut-out length L (in mm) is cut out in the machine travel direction in the coating direction, and the coating surface area S of the electrode area of ​​this unit length is... A That is, (Width - 2×Margin) × L (unit: mm²). This unit length region serves as the spatial reference for all subsequent quality calculations, used to discretize the continuous coating and drying process into analyzable micro-units.

[0057] The coating surface area S obtained above A Substituting the outlet surface density C into the formula Calculations were performed to obtain the coating quality per unit length of electrode area at the oven outlet. (Unit: g). This represents the total mass of the micro-region when it leaves the entire oven, including solid matter and residual solvent, and serves as the baseline data for subsequent calculations of the total evaporation.

[0058] According to the principle of conservation of mass, the mass of the solid substances (active material, binder, and conductive agent) remains constant during the drying process of the electrode. Based on this, the quality of the outlet coating is the first consideration. and the proportion of solvent residue in exports Calculate the mass of the solid substance The mass of this solid substance also exists at the inlet, therefore the total mass of the wet coating at the inlet can be deduced from the mass of the solid substance. The difference between the total mass of the inlet wet coating and the mass of the outlet coating is the total mass of solvent evaporated per unit length of electrode area throughout the entire oven. The above calculations yielded the total mass of evaporated solvent per unit length of electrode region during its passage through the entire multi-section drying oven. ,Should This will serve as a macro-level constraint for the online estimation in subsequent steps; that is, the sum of the evaporation components of each oven section calculated subsequently must equal this. This value establishes an accurate quality benchmark for the entire online evaporation prediction method.

[0059] S12, humidity is collected by temperature and humidity sensors installed at the air inlet and outlet of each drying oven section to obtain the absolute humidity of the air entering each drying oven section. and absolute humidity of the air outlet .

[0060] In this embodiment, continuing the above example of negative electrode coating, the oven consists of 12 sub-ovens connected in series. To achieve dynamic monitoring of the evaporation process inside each oven section, high-precision temperature and humidity sensors are installed at the air inlet and outlet ducts of each oven section to measure the absolute humidity of the incoming air in real time. and absolute humidity of the air outlet (AH) out Among them, the absolute humidity of the incoming air The absolute humidity of the outlet air (AH) reflects the water vapor content carried by the hot air entering the oven section. out This represents the concentration of water vapor in the air leaving the oven section.

[0061] S13, based on the mass conservation equation, according to the absolute humidity of the incoming air. The absolute humidity of the air outlet (AH) outThe optimization problem is constructed by considering the rate of change of the absolute humidity of the outlet air over time, and the optimization problem is solved using the particle swarm optimization algorithm to obtain the evaporation rate per unit time of each oven section. .

[0062] Furthermore, in step S13, the optimization problem constructed based on the mass conservation equation, according to the absolute humidity of the inlet air, the absolute humidity of the outlet air, and the rate of change of the absolute humidity of the outlet air over time, includes:

[0063] S13-1, using the mass conservation equation Construct a mass conservation relationship, and use the absolute humidity of the outlet air as the basis. The filtered value is used as the absolute humidity inside the oven. The approximate value of, in the formula, d(AH) represents the absolute humidity inside the i-th oven. i ) / dt represents the rate of change calculated based on the filtered value of the absolute humidity of the outlet air. Indicates the internal volume of the oven. This represents the evaporation rate per unit time. Indicates air density, Indicates the length of a single section of the drying oven. This represents the length of the electrode region per unit length. and These represent the inlet air volumetric flow rate and the outlet air volumetric flow rate of the oven, respectively.

[0064] S13-2, with the optimization objective of minimizing the L2 norm of the difference between the derivatives of the measured absolute humidity values ​​of the multi-section drying oven and the estimated absolute humidity values ​​calculated based on the mass conservation equation, a fitness function is constructed to solve the optimization problem, wherein the measured absolute humidity values ​​are based on the absolute humidity of the outlet air. The filtered value, wherein the absolute humidity estimate is the evaporation per unit time to be solved. Inlet air volume flow rate and outlet air volume flow rate The result was obtained by inputting the mass conservation equation.

[0065] Furthermore, in step S13-2, the optimization objective is to minimize the L2 norm of the difference between the derivatives of the measured absolute humidity values ​​of the multi-section oven and the estimated absolute humidity values ​​calculated based on the mass conservation equation. A fitness function is then constructed to solve the optimization problem, including:

[0066] Constructing the fitness function In the formula, This indicates the total number of sections in the oven. Let represent the derivative of the measured absolute humidity value of the oven in section i. Let represent the derivative of the absolute humidity estimate of the oven in section i.

[0067] Furthermore, in step S13, the particle swarm optimization algorithm is used to solve the optimization problem to obtain the evaporation rate per unit time for each oven section, including:

[0068] S13-3, During the period when the oven reaches steady state, collect multiple sets of time series of absolute humidity data for the incoming air. and absolute humidity of the air outlet Measurement data;

[0069] S13-4, with the goal of minimizing the fitness function, a particle swarm optimization algorithm is used to iteratively search for the evaporation rate per unit time based on multiple sets of the measurement data. Inlet air volume flow rate and outlet air volume flow rate The optimal estimate is obtained, and the evaporation rate per unit time for each oven section is extracted from the optimal estimate. .

[0070] In step S13-3, the following is included:

[0071] Set the time window length T h and sampling step size T s Multiple sets of absolute humidity (AH) data for incoming air were collected within the time window. in and absolute humidity of the air outlet (AH) out The measurement data, where N = T h / T s And N≥ 60.

[0072] Step S13-4 includes:

[0073] Initialize a particle swarm containing M particles, each particle representing a set of parameters to be solved (W). qi V in V out Candidate solutions to )

[0074] Set the maximum number of iterations, individual learning factor c1, swarm learning factor c2, and convergence weight w, and use the fitness function as the fitness evaluation function of the particle swarm.

[0075] In each iteration, the fitness function value corresponding to each particle is calculated based on the current position of each particle, and the individual optimal position of each particle and the global optimal position of the entire particle swarm are updated.

[0076] The velocity and position of each particle are updated based on the individual optimal position, the global optimal position, and the convergence weight, so that the particle swarm searches for regions with smaller fitness function values.

[0077] When the iteration reaches the maximum number of iterations or the convergence condition is met, the parameter combination corresponding to the final global optimal position is taken as the evaporation rate W per unit time. qi Inlet air volumetric flow rate V in and outlet air volume flow rate V out The optimal estimate.

[0078] In this embodiment, continuing the above example of negative electrode coating, the oven consists of 12 sub-ovens connected in series. The internal volume V of each oven is a known fixed design parameter (e.g., obtainable through geometric measurement). To achieve online estimation of the evaporation rate of each oven section, it is first necessary to establish a differential equation describing the mass conservation relationship of the gaseous solvent in each oven section, serving as the physical basis for subsequent optimization solutions. For the i-th oven section, the following mass conservation equation is established:

[0079] In the formula, AH i d(AH) represents the absolute humidity inside the i-th oven. i ) / dt represents the rate of change of absolute humidity inside the oven with respect to time; V represents the effective internal volume of the oven in this section (unit: m³). ρ represents the evaporation rate per unit time (g / s) of the i-th section of the oven to be solved, i.e., the mass of solvent evaporated from the electrode coating inside this section of the oven per second; ρ represents the air density (g / m³), which can be given as a constant value based on the physical properties of air since the temperature inside the oven is relatively stable; L o L represents the length of a single oven section (in meters); L represents the length of the unit length electrode area set in step S11 (in meters), which is used to scale up the evaporation rate based on the unit length to the scale of the entire oven section. and These represent the inlet and outlet volumetric flow rates of the oven (unit: m³ / s); AH in and AH out These are the absolute humidity of the incoming air and the absolute humidity of the outgoing air (unit: g / m³) collected in step S12.

[0080] Since there is usually good airflow mixing inside the oven, we can assume that the internal absolute humidity AH is... i Approximately equal to the absolute humidity of the outlet air (AH) out Therefore, in practical applications, the collected absolute humidity of the outlet air (AH) will be used. out The original signal is filtered (e.g., using moving average or low-pass filtering) to eliminate measurement noise and short-term fluctuations, resulting in the filtered value. out And use it as the absolute humidity AH inside the oven. iAn approximation of the value. Simultaneously, based on the filtered outlet absolute humidity data, its rate of change with time, d(…), is calculated using a numerical differentiation method. out ) / dt, used to approximate d(AH) on the left side of the equation i ) / dt, which is an approximation of the dynamic rate of change of absolute humidity inside the oven.

[0081] To solve the three unknown parameters in the mass conservation equation: evaporation rate W per unit time qi Inlet air volumetric flow rate V in and outlet air volume flow rate V out Therefore, a quantifiable optimization objective needs to be constructed. The optimization objective is to minimize the L2 norm of the difference between the derivatives of the measured absolute humidity values ​​and the estimated absolute humidity values ​​of each oven section. The fitness function is then constructed as follows: In the formula, N=12 represents the total number of sections in the oven. This represents the derivative of the measured absolute humidity value of the i-th oven section, i.e., the filtered value based on the absolute humidity of the outlet air. out The calculated d( out ) / dt; The derivative of the estimated absolute humidity value of the oven in section i is the parameter to be solved (W). qi V in V out The theoretical absolute humidity value obtained after substituting into the mass conservation equation i The estimated value of the derivative. The smaller the value of this fitness function, the smaller the deviation between the theoretical value calculated based on the mass conservation equation and the sensor's measured value, and the better the corresponding parameter combination (W). qi V in V out The closer it is to real working conditions.

[0082] In actual production, after the actuators such as the valves, internal circulation fan, and exhaust fan frequency of the oven are adjusted, the pressure fluctuations and airflow state inside the oven will reach dynamic equilibrium after a period of time (e.g., 3-5 minutes). At this time, the inlet air volumetric flow rate V in and outlet air volume flow rate V out It tends to stabilize, satisfying the assumption of constant parameters in the mass conservation equation.

[0083] To obtain sufficient data for parameter estimation, a time window length T is set. h (e.g., 5 minutes) and sampling step size T s (e.g., 10 seconds), within each steady-state time window, continuously collect multiple sets of time series of absolute humidity (AH) data. inand absolute humidity of the air outlet (AH) out The measurement data ensures that the number of samples N=T within each time window. h / T s And N≥60, to meet the data volume requirements of subsequent optimization algorithms. Multiple sets of collected data (AH...) in ,AH out ,d( out The mass conservation equation and fitness function for each section of the oven (dt) will be used to construct the mass conservation equation and fitness function for each section, and then the key parameters such as the evaporation rate per unit time for each section will be solved using an optimization algorithm. The particle swarm optimization algorithm is used to solve the above optimization problem, and the specific process is as follows:

[0084] First, initialize a particle swarm containing M particles (e.g., M=40), where each particle represents a set of parameters to be solved (W). qi V in V out The candidate solutions are: the initial position of each particle is randomly generated within the possible range of parameter values, and the initial velocity is also randomly set.

[0085] Next, set the algorithm's running parameters: maximum number of iterations (e.g., 500), individual learning factor c1, swarm learning factor c2 (usually c1=c2=2), and convergence weight w (e.g., w=0.8). Use the fitness function constructed above as the fitness evaluation function for the particle swarm.

[0086] In each iteration, perform the following operations: based on the current position (W) of each particle... qi V in V out Calculate the corresponding fitness function value; for each particle, compare its current fitness value with its historical best position (individual best position p). best The fitness values ​​of each particle are compared, and if the fitness value is better, the individual's optimal position is updated. The optimal positions of all particles are then compared, and the position with the smallest fitness value is taken as the current global optimal position g for the entire particle swarm. best The velocity and position of each particle are updated based on its individual optimal position, global optimal position, and convergence weights. Iteration stops when the preset maximum number of iterations is reached, or when the fitness value of the global optimal position changes less than a preset threshold (i.e., convergence is satisfied) in multiple consecutive iterations. At this point, the final global optimal position g is determined. best The corresponding parameter combination is used as the evaporation rate W per unit time. qi Inlet air volumetric flow rate V in and outlet air volume flow rate V out The optimal estimate.

[0087] Finally, the evaporation rate W per unit time for each oven section is extracted from the optimal estimate obtained from the solution. qi This parameter will be used in subsequent steps to calculate the solvent evaporation fraction of each oven section. Simultaneously, the calculated inlet air volumetric flow rate V... in and outlet air volume flow rate V out It can also be used for steady-state determination of oven operation and establishment of process parameter mapping tables.

[0088] S14, based on the evaporation rate W per unit time qi And the residence time T of the electrode in a single oven section. o Calculations were performed to obtain the solvent evaporation fraction W of the electrode in each oven section. S (i), where the solvent evaporation component W of each oven section S (i) The sum of these equals the total mass W of the evaporated solvent. s .

[0089] In this embodiment, the length of each oven section is assumed to be L. o (Unit: m). The operating speed of the coating machine is v. coating (Unit: m / s) The residence time T of the electrode in a single oven section o Calculate using the following formula: T o =L o / v coating For example, if the length of a single oven section is L... o =5m, coating speed v coating =1m / s (i.e., 60m / min), then the residence time T of the electrode in each oven section. o =5 seconds. This dwell time represents the time required for the unit length of electrode region captured in step S11 to pass through each section of the oven.

[0090] The evaporation rate per unit time for each oven section has been calculated using the mass conservation equation and particle swarm optimization algorithm. (Unit: g / s) This parameter reflects the mass of solvent evaporated from a unit length of electrode region in the i-th section of the oven per unit time. Based on this, the total amount of solvent evaporated from the unit length of electrode region in the i-th section of the oven during the entire residence time can be calculated, i.e., the solvent evaporation component W. S (i): W S (i)=W qi ×T o In the formula, W S (i) is in g, representing the mass of solvent evaporated in the i-th section of the oven for a unit length of the cut electrode region.

[0091] According to the principle of mass conservation, the total mass W of solvent evaporated per unit length of electrode region in the entire oven (all 12 oven sections) is...S It should equal the sum of the evaporation components of each section of the oven. Therefore, the following total constraint relationship exists: This constraint relationship relates to the total mass W of evaporated solvent calculated in step S11 based on the inlet solvent percentage A%, the outlet solvent residue percentage B%, and the outlet surface density C. s This forms a closure verification. In practical applications, this can be achieved by comparing ∑W. S (i) and W s The deviation between the two is used to verify the accuracy of the parameter estimation. If the deviation exceeds the preset range, it indicates that there may be errors in the optimization solution process, and it is necessary to re-examine the assumptions of the mass conservation equation (such as the uniformity of mixing inside the oven, constant air density, etc.) or the parameter settings of the particle swarm optimization algorithm (such as particle swarm size, learning factor, convergence weight, etc.) to ensure the reliability of the parameter estimation. Through the above calculations, the accuracy of the parameter estimation is achieved from the macroscopic total W. s To each section of micro-component W s The decomposition of (i) provides crucial input data for subsequent steps.

[0092] In another embodiment, the method further includes:

[0093] S15, according to the solvent evaporation fraction W S (i) The solvent mass percentage and the total residual solvent mass percentage are used to calculate the residual solvent mass percentage B at the outlet of each oven section. i .

[0094] Furthermore, in step S15, the step of determining the solvent evaporation fraction W... S (i) The solvent mass percentage and the total residual solvent mass percentage are recursively calculated to obtain the residual solvent mass percentage B at the outlet of each oven section. i ,include:

[0095] according to Perform recursive calculations, where, The coating quality per unit length of electrode area at the oven outlet is calculated from the outlet areal density C and the area of ​​the electrode area per unit length. This indicates the percentage of solvent residue at the outlet of the (i-1)th oven section. This represents the percentage of solvent residue at the outlet of the i-th oven. The solvent mass percentage at the oven inlet is equal to A%. This is equal to B, which is the total percentage of solvent residue at the oven outlet.

[0096] In this embodiment, the solvent evaporation fraction W per unit length of electrode region in each oven section has been obtained through step S14. S(i) (where i=1,2,…,12), and based on the solvent mass percentage A% at the oven inlet and the total solvent residual mass percentage B% at the oven outlet obtained above, the solvent residual mass percentage Bi% at the outlet of each section of the oven can be further calculated, thereby achieving "penetration" of the drying process of the electrode inside the oven.

[0097] Based on the W obtained above out And the known boundary conditions B0%=A%, B N %=B% Apply the above formula to the first section of the oven (i=1): = Among them, W S (1) The solvent evaporation fractions of the first oven section, A%, B%, and W, obtained in step S14. out Since this is a known quantity, the solvent residue percentage B1% at the oven outlet in Section 1 can be calculated, i.e. After obtaining B1%, continue applying the formula to the second oven section (i=2): Substitute the known W S (2) B%, B1% and W out B2% can be calculated from this. This process is repeated section by section until the residual solvent percentage at the outlet of each intermediate oven section is calculated: B1%, B2%, ..., B. 11 %.

[0098] Through the above recursive calculations, the percentage of solvent residue at the outlet of each oven section was obtained. These data directly reflect the drying process of the electrode within each oven section: for example, the solvent content is higher during the preheating and heating stages; during the constant-rate drying stage, the solvent evaporates at a relatively stable rate; and during the falling-rate drying stage, the solvent content gradually decreases to the outlet target value of B%. Operators can use these calculations to determine the completion status of the drying task in each oven section and compare it with the process design targets (such as the expected solvent residue range for each stage).

[0099] When the solvent residue ratio at the outlet of a certain oven section deviates from the expected value, the inlet air volumetric flow rate V obtained in step S13 can be used as a reference. in and outlet air volume flow rate V out In addition, a pre-established historical data mapping table is used to adjust the process parameters of the oven section (such as heating temperature, fan frequency, etc.) in a targeted manner, so that the actual drying curve approaches the ideal drying curve, thereby achieving refined control of the drying process.

[0100] In another embodiment, the method further includes:

[0101] S16, based on inlet air volumetric flow rate V in and outlet air volume flow rate V outThe oven is judged to have reached a steady state by measuring the change of the optimal estimated value over a continuous time series. Specifically, the oven is judged to have reached a steady state when the change is less than a preset threshold.

[0102] S17, when the oven reaches steady state, record the solvent evaporation component W of each section of the oven under the current steady-state conditions. S (i) and the corresponding oven process parameters, generate a historical data mapping table, wherein the oven process parameters include at least one of the following: oven heating temperature, hot air circulation fan frequency, exhaust fan frequency, fresh air valve opening degree and exhaust valve opening degree;

[0103] S18. Based on the target solvent residual ratio or target evaporation fraction, determine the adjustment amount of the oven process parameters according to the historical data mapping table, and guide the adjustment and optimization of the drying process according to the adjustment amount.

[0104] In actual production, after adjustments are made to the oven's heating temperature, fan frequency, valve opening, and other actuators, it takes a period of time (e.g., 3-5 minutes) for the airflow and heat / humidity exchange inside the oven to reach dynamic equilibrium. To accurately determine whether the oven has reached a stable operating state, V can be analyzed based on a continuous time series. in and V out The estimated values ​​are monitored.

[0105] Specifically, a time window length is set (e.g., 5 minutes), and V values ​​are continuously acquired at multiple points within this time window. in and V out Estimate the value and calculate its magnitude of change (e.g., standard deviation or range). When V spans multiple consecutive time windows... in and V out When the changes in all values ​​are less than a preset threshold (e.g., relative change less than 5%), the oven is considered to have reached a steady state. This preset threshold can be pre-set based on historical data or process requirements to balance the sensitivity and stability of steady-state determination.

[0106] In addition, to further verify the reliability of the steady-state determination, the measurement data from the negative pressure sensor installed inside the oven or the anemometer in the air duct can be used for auxiliary verification. When the values ​​of the negative pressure sensor or the anemometer measurements also tend to be stable, it can be further confirmed that the oven has reached a steady state.

[0107] Once the oven reaches a steady state, the system automatically records key data under the current steady-state operating conditions; the recorded data includes: the solvent evaporation fraction W for each oven section. S (i) The oven process parameters corresponding to each oven section, such as oven heating temperature, hot air circulation fan frequency, exhaust fan frequency, fresh air valve opening, exhaust valve opening, etc.

[0108] As the production process continues, the system repeats the above recording process whenever the oven adjusts its process parameters and reaches a new steady-state condition. Multiple sets of steady-state data accumulated over long-term operation form a historical data mapping table covering different combinations of process parameters and their corresponding evaporation effects. This mapping table records the actual solvent evaporation amount achieved by each section of the oven under different process parameter settings, providing a data-driven decision-making basis for subsequent process optimization.

[0109] In actual production, process engineers can set target values ​​based on product quality requirements. These target values ​​include the target solvent residue percentage or the target evaporation percentage. For example, the target solvent residue percentage might be adjusted from the current B% to a new target value B% based on product specifications. target Based on this target residual percentage, and combined with the recursive formula in step S15, the target evaporation amount W to be achieved in each section of the oven can be calculated in reverse. S target (i). Target evaporation component: Directly set the target evaporation component W to be achieved in each section of the oven. S target (i) For example, to increase or decrease the drying intensity of a certain section of an oven. After obtaining the target evaporation component, based on the historical data mapping table generated above, the following operations can be performed, such as:

[0110] Query matching: Find the historical steady-state operating condition that is closest to the target evaporation component in the mapping relationship table, and read the oven process parameter combination corresponding to the operating condition;

[0111] Interpolation calculation: If the target evaporation component is between multiple historical data points, interpolation methods (such as linear interpolation and spline interpolation) can be used to calculate the corresponding process parameter adjustment amount;

[0112] Trend analysis: Analyze the changing trend of evaporation component in the same oven section under different process parameter settings, establish the sensitivity relationship of evaporation component to parameters such as temperature and fan frequency, and thus more accurately determine the adjustment amount.

[0113] For example, if the target evaporation component of the fifth oven needs to be increased by 10% based on the target solvent residue ratio, the adjustment range of temperature or fan frequency corresponding to the evaporation component increase of 10% can be found in the mapping table of the historical data of the oven section. Based on this, specific adjustment instructions can be generated, such as "increase the heating temperature of the fifth oven by 5℃" or "increase the exhaust fan frequency by 3Hz".

[0114] Based on the above, the original process adjustment process, which relied on trial and error based on experience, is transformed into a scientific decision-making process based on historical data mapping relationships. Process engineers can fine-tune parameters according to the adjustment amount recommended by the system, and after adjustment, verify the new steady-state conditions again through steps S16-S17, forming a closed-loop control of "parameter adjustment → status monitoring → data accumulation → optimization decision-making", continuously improving the accuracy and production efficiency of the drying process.

[0115] Reference Figure 2 The diagram shown is a schematic representation of an online estimation device for the evaporation amount of lithium battery electrode coating drying according to an embodiment of the present invention.

[0116] In this embodiment, the device 20 includes:

[0117] The acquisition unit 21 is used to acquire the solvent mass ratio at the oven inlet, the total residual solvent mass ratio at the oven outlet, and the outlet surface density of the electrode, and to calculate the total mass of evaporated solvent per unit length of electrode region based on the solvent mass ratio, the total residual solvent mass ratio, and the outlet surface density.

[0118] The data acquisition unit 22 is used to collect humidity data by means of temperature and humidity sensors installed at the air inlet and air outlet of each oven section, so as to obtain the absolute humidity of the air inlet and the absolute humidity of the air outlet of each oven section.

[0119] Construction unit 23 is used to construct an optimization problem based on the mass conservation equation, according to the absolute humidity of the inlet air, the absolute humidity of the outlet air, and the rate of change of the absolute humidity of the outlet air over time, and to solve the optimization problem using the particle swarm optimization algorithm to obtain the evaporation rate per unit time of each oven section.

[0120] The calculation unit 24 is used to calculate the solvent evaporation amount of the electrode in each oven section based on the evaporation amount per unit time and the residence time of the electrode in a single oven section, wherein the sum of the solvent evaporation amounts in each oven section is equal to the total mass of the evaporated solvent.

[0121] In another embodiment, the device 20 further includes:

[0122] The calculation unit is used to calculate the solvent residual mass percentage at the outlet of each oven section based on the solvent evaporation fraction, the solvent mass percentage, and the total solvent residual mass percentage.

[0123] In another embodiment, the device 20 further includes:

[0124] The judgment unit is used to determine whether the oven has reached a steady state based on the variation range of the optimal estimated values ​​of the inlet volume flow rate and the outlet volume flow rate over a continuous time series. The oven is determined to have reached a steady state when the variation range is less than a preset threshold.

[0125] The generation unit is used to record the solvent evaporation component and corresponding oven process parameters of each oven section under the current steady-state operating conditions when the oven reaches a steady state, and generate a historical data mapping table. The oven process parameters include at least one of the following: oven heating temperature, hot air circulation fan frequency, exhaust fan frequency, fresh air valve opening degree, and exhaust valve opening degree.

[0126] The adjustment unit is used to determine the adjustment amount of the oven process parameters based on the historical data mapping table, according to the target solvent residual ratio or the target evaporation fraction.

[0127] Each unit module of the device 20 can execute the corresponding steps in the above method embodiment, so the details of each unit module will not be elaborated here. Please refer to the description of the corresponding steps above for details.

[0128] This invention also provides an online estimation device for the evaporation amount of lithium battery electrode coating drying, which includes the online estimation apparatus for the evaporation amount of lithium battery electrode coating drying as described above. The online estimation apparatus for the evaporation amount of lithium battery electrode coating drying can employ... Figure 2 The structure of the embodiment, correspondingly, can be executed Figure 1 The technical solutions of the method embodiments shown are similar in implementation principle and technical effect. For details, please refer to the relevant records in the above embodiments, which will not be repeated here.

[0129] The device includes: a mobile phone, digital camera, or tablet computer, or other device with a camera function; or a device with an image processing function; or a device with an image display function. The device may include components such as a memory, processor, input unit, display unit, and power supply.

[0130] The memory can be used to store software programs and modules. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory. The memory can mainly include a program storage area and a data storage area. The program storage area can store the operating system, applications required for at least one function, etc.; the data storage area can store data created according to the use of the device, etc. In addition, the memory can include high-speed random access memory, and can also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory can also include a memory controller to provide access to the memory for the processor and input units.

[0131] The input unit can be used to receive input numerical, character, or image information, and to generate keyboard, mouse, joystick, optical, or trackball signal inputs related to user settings and function control. Specifically, in addition to a camera, the input unit of this embodiment may also include a touch-sensitive surface (e.g., a touch screen) and other input devices.

[0132] The display unit can be used to display information input by the user or information provided to the user, as well as various graphical user interfaces of the device. These graphical user interfaces can be composed of graphics, text, icons, video, and any combination thereof. The display unit may include a display panel, optionally configured as an LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), or other similar display panel. Furthermore, a touch-sensitive surface may cover the display panel. When the touch-sensitive surface detects a touch operation on or near it, it transmits the information to the processor to determine the type of touch event. Subsequently, the processor provides corresponding visual output on the display panel based on the type of touch event.

[0133] This invention also provides a computer-readable storage medium, which may be a computer-readable storage medium included in the memory described in the above embodiments; or it may be a standalone computer-readable storage medium not assembled into a device. The computer-readable storage medium stores at least one instruction, which is loaded and executed by a processor to implement... Figure 1 The method shown is an online estimation method for the evaporation amount of lithium battery electrode coating during drying. The computer-readable storage medium can be a read-only memory, a disk, or an optical disk, etc.

[0134] This invention also provides a computer program product, including a computer program / instructions, which are loaded and executed by a processor to implement... Figure 1 This paper presents an online estimation method for the evaporation rate of lithium battery electrode coating drying.

[0135] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the device embodiments, equipment embodiments, and storage medium embodiments, since they are basically similar to the method embodiments, the descriptions are relatively simple, and relevant parts can be referred to the descriptions in the method embodiments.

[0136] Furthermore, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0137] The foregoing description illustrates and describes preferred embodiments of the present invention. It should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the inventive concept by means of the foregoing teachings or techniques or knowledge in related fields. Any modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

Claims

1. An online estimation method for the evaporation amount during coating and drying of lithium battery electrode sheets, characterized in that, The method includes: Obtain the solvent mass percentage at the oven inlet, the total residual solvent mass percentage at the oven outlet, and the outlet surface density of the electrode, and calculate the total evaporated solvent mass per unit length of the electrode region based on the solvent mass percentage, the total residual solvent mass percentage, and the outlet surface density; Humidity is collected by temperature and humidity sensors installed at the air inlet and air outlet of each oven section, and the absolute humidity of the air inlet and air outlet of each oven section is obtained. Based on the mass conservation equation, an optimization problem is constructed according to the absolute humidity of the inlet air, the absolute humidity of the outlet air, and the rate of change of the absolute humidity of the outlet air over time. The particle swarm optimization algorithm is used to solve the optimization problem to obtain the evaporation rate per unit time of each oven section. The optimization problem based on the mass conservation equation, according to the absolute humidity of the inlet air, the absolute humidity of the outlet air, and the rate of change of the absolute humidity of the outlet air over time, includes: Using the mass conservation equation A mass conservation relationship is established, and the filtered value of the absolute humidity of the outlet air is used as an approximation of the absolute humidity inside the oven. Where, This represents the absolute humidity inside the i-th section of the oven. This represents the rate of change calculated based on the filtered value of the absolute humidity of the outlet air. Indicates the internal volume of the oven. The evaporation rate per unit time represents the mass of solvent evaporated from a unit length of electrode region in the i-th section of the oven per unit time. Indicates the length of a single section of the drying oven. This represents the length of the electrode region per unit length. Indicates the absolute humidity of the air outlet. Indicates the absolute humidity of the incoming air. and These represent the inlet air volumetric flow rate and the outlet air volumetric flow rate of the oven, respectively. The optimization objective is to minimize the L2 norm of the difference between the derivatives of the measured absolute humidity values ​​of the multi-section drying oven and the estimated absolute humidity values ​​calculated based on the mass conservation equation. A fitness function is constructed to solve this optimization problem. The measured absolute humidity values ​​are filtered values ​​based on the outlet absolute humidity. The estimated absolute humidity values ​​are calculated by inputting the unit-time evaporation rate, inlet volumetric flow rate, and outlet volumetric flow rate into the mass conservation equation, including: Constructing the fitness function In the formula, This indicates the total number of sections in the oven. Let represent the derivative of the measured absolute humidity value of the oven in section i. The derivative of the estimated absolute humidity value of the oven in section i; The optimization problem is solved using a particle swarm optimization algorithm to obtain the evaporation rate per unit time for each oven section, including: During the period when the oven reaches a steady state, multiple sets of time series measurement data of inlet and outlet absolute humidity were collected. With the fitness function as the objective, the particle swarm optimization algorithm is used to iteratively search for the optimal estimates of evaporation per unit time, inlet volumetric flow rate, and outlet volumetric flow rate based on multiple sets of the measurement data, and the evaporation per unit time is extracted from the optimal estimates. The solvent evaporation amount per unit time and the residence time of the electrode per unit length in a single oven section are calculated to obtain the solvent evaporation amount per unit length in each oven section, wherein the sum of the solvent evaporation amounts in each oven section is equal to the total mass of the evaporated solvent.

2. The online estimation method for the evaporation amount of lithium battery electrode coating drying according to claim 1, characterized in that, The calculation of the total mass of evaporated solvent per unit length of electrode region based on the solvent mass ratio, the total mass ratio of residual solvent, and the outlet areal density includes: The coating surface area of ​​the electrode area per unit length is determined based on the current collector width, the coating blank size, and the preset unit cut length. The coating quality per unit length of electrode area at the oven outlet is calculated based on the outlet surface density and the coating surface area. The solvent mass percentage, the total residual solvent mass percentage, and the coating quality are expressed by the formula. Calculations were performed to obtain the total mass of the evaporated solvent, where, The coating quality is indicated by the outlet areal density. The area of ​​the electrode region per unit length is calculated. Indicates the percentage of solvent by mass. This indicates the percentage of total residual solvent mass.

3. The online estimation method for the evaporation amount of lithium battery electrode coating drying according to claim 1, characterized in that, The method further includes: The solvent residue mass percentage at the outlet of each oven section is calculated based on the solvent evaporation fraction, the solvent mass percentage, and the total solvent residue mass percentage.

4. The online estimation method for the evaporation amount of lithium battery electrode coating drying according to claim 3, characterized in that, The step of recursively calculating the solvent residual mass percentage at the outlet of each oven section based on the solvent evaporation fraction, the solvent mass percentage, and the total solvent residual mass percentage includes: according to Perform recursive calculations, where, Indicates the amount of solvent evaporated. This indicates the coating quality per unit length of electrode area at the oven outlet. This indicates the percentage of solvent residue at the outlet of the (i-1)th oven section. This represents the percentage of solvent residue at the outlet of the i-th oven. Equal to the solvent mass ratio at the oven inlet , Equal to the total mass percentage of solvent residue at the oven outlet .

5. The online estimation method for the evaporation amount of lithium battery electrode coating drying according to claim 1, characterized in that, The method further includes: The oven is judged to have reached a steady state based on the variation of the optimal estimated values ​​of the inlet volume flow rate and the outlet volume flow rate over a continuous time series. Specifically, the oven is judged to have reached a steady state when the variation is less than a preset threshold. When the oven reaches a steady state, record the solvent evaporation component of each oven section under the current steady-state operating conditions and the corresponding oven process parameters, and generate a historical data mapping table. The oven process parameters include at least one of the following: oven heating temperature, hot air circulation fan frequency, exhaust fan frequency, fresh air valve opening degree, and exhaust valve opening degree. Based on the target solvent residue percentage or target evaporation fraction, the adjustment amount of the oven process parameters is determined according to the historical data mapping table.

6. An online estimation device for the evaporation amount of lithium battery electrode coating drying, characterized in that, Using the online estimation method for the evaporation amount of lithium battery electrode coating drying according to any one of claims 1-5, the apparatus comprises: The acquisition unit is used to acquire the solvent mass ratio at the oven inlet, the total residual solvent mass ratio at the oven outlet, and the outlet surface density of the electrode, and to calculate the total mass of evaporated solvent per unit length of electrode region based on the solvent mass ratio, the total residual solvent mass ratio, and the outlet surface density. The data acquisition unit is used to collect humidity data by using temperature and humidity sensors installed at the air inlet and air outlet of each oven section, so as to obtain the absolute humidity of the air inlet and the absolute humidity of the air outlet of each oven section. The construction unit is used to construct an optimization problem based on the mass conservation equation, according to the absolute humidity of the inlet air, the absolute humidity of the outlet air, and the rate of change of the absolute humidity of the outlet air over time, and to solve the optimization problem using the particle swarm optimization algorithm to obtain the evaporation rate per unit time. The calculation unit is used to calculate the solvent evaporation amount per unit length of electrode in each oven section based on the evaporation amount per unit time and the residence time of the electrode in a single oven section, wherein the sum of the solvent evaporation amounts in each oven section is equal to the total mass of the evaporated solvent.

7. An online estimation device for the evaporation amount of lithium battery electrode coating drying, characterized in that, The device includes a processor, a memory, and a computer program stored in the memory, wherein the computer program, when executed by the processor, implements the steps of an online estimation method for the evaporation amount of lithium battery electrode coating drying as described in any one of claims 1 to 5.

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