Double-closed-loop control method for drying temperature and humidity of cylindrical battery pole plate

Abstract

The invention relates to the technical field of battery manufacturing, and discloses a cylindrical battery pole plate drying temperature and humidity double-closed-loop control method which is used for solving the problem of double-closed-loop control response lag caused by temperature and humidity nonlinear coupling in a traditional method. The method comprises the following steps: firstly, acquiring real-time temperature and humidity data in a drying process, and transmitting and storing the real-time temperature and humidity data; establishing a nonlinear model based on the data, and analyzing the influence of the temperature on the evaporation rate and the reaction of the humidity on the temperature; performing parameter identification, and iteratively adjusting an influence coefficient and a reaction coefficient; designing a decoupling compensator, introducing a humidity compensation item into a temperature closed loop, introducing a temperature compensation item into a humidity closed loop, and integrating the items into a double-closed-loop frame; a compensator is used for adjusting heating power and a dehumidification air speed valve; monitoring the system state, and adjusting the compensation parameter in real time according to the difference between actual and set values. According to the method, the control precision is improved through model modeling and decoupling optimization.

Description

Technical Field

[0001] This invention relates to the field of battery manufacturing technology, specifically to a method for dual closed-loop control of temperature and humidity during the drying of cylindrical battery plates. Background Technology

[0002] The drying process of cylindrical battery plates is a critical step in lithium battery manufacturing, directly affecting plate quality and battery performance. Current technologies often employ a dual-loop temperature and humidity control method. This involves adjusting the heating element via a temperature loop and controlling the dehumidification system via a humidity loop to achieve uniform moisture evaporation and prevent capacity decay caused by plate cracks or residual moisture. However, due to the strong nonlinear coupling between temperature and humidity—for example, increased temperature accelerates moisture evaporation but may simultaneously cause uneven local humidity gradients, leading to feedback signal interference—existing dual-loop control methods struggle to accurately model this nonlinear dynamic and achieve real-time decoupling. This results in control response lag or system oscillation, hindering production efficiency and product quality. For example, CN114678585A discloses a cylindrical lithium battery electrode drying device and its control method. This method is based on a dual closed-loop system with temperature and humidity sensor feedback, and uses a PID algorithm to adjust heating and dehumidification parameters in real time to reduce the risk of electrode deformation. In experiments, it achieved a moisture residue rate of less than 1%. However, this patent uses a linear approximation in its modeling, ignoring the dynamic characteristics of the nonlinear coupling between temperature and humidity. As a result, in practical applications, when the ambient humidity fluctuates or the electrode thickness varies, the rapid response of the temperature closed loop will interfere with the humidity feedback, causing a control lag of several seconds or more, and even leading to over-drying. This increases the scrap rate and affects battery consistency. CN113809425A proposes a battery electrode drying control method based on multi-sensor fusion, which adopts a temperature and humidity dual closed-loop framework. Through threshold judgment and fuzzy logic optimization process, it is suitable for cylindrical battery electrodes. Experiments show that the control accuracy error is less than ±2%. However, its shortcomings are that it lacks accurate dynamic modeling and real-time decoupling algorithms for nonlinear coupling. For example, it does not establish a coupling equation that considers heat conduction and moisture diffusion. As a result, under high humidity conditions, the humidity closed loop is easily affected by temperature interference, and the response lag is significant. In actual production, this may prolong the drying cycle and increase energy consumption. While the aforementioned existing technologies have improved drying accuracy, none of them have effectively solved the problem of lag in dual-closed-loop control response caused by nonlinear coupling of temperature and humidity. Specifically, this nonlinearity manifests as the exponential effect of temperature on humidity evaporation rate and the reaction effect of humidity gradient on temperature distribution, making it difficult for traditional methods to achieve stable convergence. In large-scale cylindrical battery production, this problem will be amplified into system instability and quality fluctuations. Therefore, there is an urgent need for a control method that accurately models nonlinear dynamics and decouples them in real time to improve reliability and efficiency. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a dual closed-loop control method for temperature and humidity control of cylindrical battery plates during drying, which solves the problem of delayed response in dual closed-loop control caused by nonlinear coupling of temperature and humidity in traditional methods.

[0004] To achieve the goal of improving the response of dual closed-loop control mentioned in the background section, the present invention provides the following technical solution: A closed-loop temperature and humidity control method for drying cylindrical battery plates includes: S1: Collect real-time temperature and humidity data during the drying process of cylindrical battery plates, and transmit the collected temperature and humidity data to the control system for initial storage; S2: Based on the collected multi-point temperature and humidity data, a nonlinear model of temperature-humidity coupling, including temperature driving terms and humidity feedback terms, is established. S3: Perform parameter identification on the established nonlinear model, determine the influence coefficient of temperature on humidity and the reaction coefficient of humidity on temperature in the model, adjust these coefficients iteratively to make the model reflect the dynamic characteristics of the actual drying process, and update the identified parameters to the control system. S4: Design a temperature and humidity decoupling compensator. Based on the identified parameters, introduce a humidity compensation term in the temperature closed loop to offset humidity interference, and introduce a temperature compensation term in the humidity closed loop to offset temperature interference. Integrate the compensator into the dual closed-loop control framework. S5: Apply the decoupling compensator to the dual closed-loop control system. In the temperature closed loop, adjust the power output of the heating element according to the compensation term. In the humidity closed loop, adjust the wind speed and humidity valve opening of the dehumidification system according to the compensation term. S6: Monitors the operating status of the control system, provides real-time feedback and adjustment to the output of the decoupling compensator, and updates the parameters of the compensation item by comparing the actual temperature and humidity values ​​with the set values.

[0005] In a preferred embodiment, real-time temperature and humidity data are collected during the drying process of the cylindrical battery plates, and the collected temperature and humidity data are transmitted to the control system for initial storage, including: The drying oven cavity is divided into multiple zones along the vertical direction to match the electrode conveying path; Distributed temperature sensor arrays are deployed in various areas to monitor the temperature distribution gradient between the upper and lower parts; An array of capacitive humidity sensors is arranged on the side wall to monitor overall and lateral humidity flow; Data is sampled synchronously using a multi-channel data acquisition unit to ensure time alignment; After analog-to-digital conversion and shielding, the data is transmitted to the control system. After noise filtering and standardization preprocessing, it is stored in the embedded module in a time-series structure. Sensor calibration is performed before the process starts, and redundant wireless channels are designed.

[0006] In a preferred embodiment, based on the collected multi-point temperature and humidity data, a temperature-humidity coupled nonlinear model is established, including a temperature-driven term and a humidity feedback term, comprising: Retrieve time-series temperature and humidity data from structured spatiotemporal datasets, and divide the furnace body into upper, middle, and lower sub-regions to match the electrode paths; The mechanism by which temperature rise accelerates the rate of moisture evaporation on the electrode and the feedback constraint of humidity gradient on temperature uniformity are analyzed. Integrating the modulation and interaction process of electrode geometry and physical properties; The model is modularly imported into the embedded processor of the control system, and a parameter recognition interface is reserved.

[0007] In a preferred embodiment, parameter identification is performed on the established nonlinear model to determine the influence coefficient of temperature on humidity and the reaction coefficient of humidity on temperature in the model. These coefficients are then iteratively adjusted to ensure the model reflects the dynamic characteristics of the actual drying process. The identified parameters are then updated to the control system, including: Retrieve the spatiotemporal temperature and humidity dataset from the storage module by time series; The parameters that directly affect the humidity evaporation coefficient and the parameters that react with the humidity gradient on temperature diffusion are extracted from the model. These parameters are adjusted iteratively through data comparison, covering the entire drying cycle in multiple rounds, and emphasizing parameter linkage; A cross-comparison strategy is adopted, using partial data to adjust parameters and the remaining data to verify generalization ability; The optimized parameters are stored in the control system database as key-value pairs, and the available status is verified by playback.

[0008] In a preferred embodiment, a temperature and humidity decoupling compensator is designed. Based on the identified parameters, a humidity compensation term is introduced into the temperature closed loop to counteract humidity interference, and a temperature compensation term is introduced into the humidity closed loop to counteract temperature interference. The compensator is integrated into a dual-closed-loop control framework, including: Load identification parameters from the control system database, including temperature drive coefficient and humidity feedback coefficient; A humidity-based compensation module is added to the temperature closed-loop path to generate a compensation increment correction control signal based on the humidity deviation and feedback coefficient. A temperature-based compensation module is added to the humidity closed-loop path to generate a compensation increment correction control signal by inverting the temperature deviation and the driving coefficient. Two compensation modules are embedded in the dual closed-loop control framework to form a cross-complementary structure. The temperature loop input is connected to the humidity compensation module, and the humidity loop input is connected to the temperature compensation module. The compensator is constructed using modular logic units.

[0009] In a preferred embodiment, a decoupling compensator is applied to a dual-loop control system. In the temperature loop, the power output of the heating element is adjusted according to the compensation term. In the humidity loop, the fan speed and humidity valve opening of the dehumidification system are adjusted according to the compensation term. This includes: Load the identification parameters into the compensation module; In the temperature closed-loop path, the voltage offset increment generated by the output of the humidity compensation module is used to correct the original control signal and drive the power adjustment of the heating element. In the humidity closed-loop path, the original control signal is corrected based on the speed and angle offset increments generated by the temperature compensation module, which drives the fan speed and the opening and closing of the dehumidification valve to adjust. The actuator interface maps compensation increments to heating voltage, fan motor pulses, and valve servo positions.

[0010] In a preferred embodiment, it includes: A parallel frame structure is adopted to package the temperature closed-loop voltage regulation command and the humidity closed-loop wind speed angle regulation command into a composite execution package, which is synchronously sent to the central execution unit every cycle. The clock drives the multi-channel output, triggering the heating element and dehumidification system in parallel. The smoothness of the framework response was verified by simulating interference playback, thus forming parameter-driven synchronous execution logic.

[0011] In a preferred embodiment, the operating status of the monitoring and control system is monitored, and the output of the decoupling compensator is adjusted in real time. The parameters of the compensation item are updated by comparing the actual temperature and humidity values ​​with the set values, including: Temperature and humidity sensor values ​​are continuously collected from the actuator feedback signal, including the temperature distribution at the top and bottom and the humidity flow at the side wall end; The feedback sequence is compared with the preset target value to generate temperature difference vector and humidity difference vector, and the difference is allocated according to the closed loop. The compensator parameters are dynamically modified based on the differences, including adjusting the feedback coefficient of the humidity compensation module and the driving coefficient of the temperature compensation module, mapping the increment according to the difference magnitude and limiting the adjustment range.

[0012] In a preferred embodiment, it includes: Execute closed-loop coordination logic, using the stable state of the temperature loop as the reference input for the humidity loop, and otherwise locking the parameters; To handle abnormal feedback values, noise is identified and replaced with neighboring values. The system uses a tiered comparison logic, with fine-tuning for small differences and alerting and increasing the frequency of adjustments for large differences. The built-in version management module generates a record for each parameter modification, including the coefficient name, the values ​​before and after the modification, the reason, and the timestamp, supporting traceability and database storage.

[0013] Compared with the prior art, the present invention provides a dual closed-loop control method for temperature and humidity during the drying of cylindrical battery plates, which has the following beneficial effects: 1. This invention constructs a multi-point sensor network within the drying oven to acquire real-time temperature and humidity data. Using this data as input, a nonlinear temperature-humidity coupling model is built. Subsequently, a parameter identification method is used to determine the coupling coefficient between temperature-driven evaporation and humidity feedback suppression. A temperature-humidity decoupling compensator is then designed and embedded into a dual-loop control system. This allows for the addition of humidity compensation terms to the temperature control loop and temperature compensation terms to the humidity control loop, ensuring that temperature and humidity errors compensate for each other rather than interfere with each other. This effectively suppresses lower-level condensation caused by humidity gradients, overheating caused by upper-level temperature accumulation, and residual moisture retention caused by accelerated evaporation due to temperature increases. Simultaneously, the compensator output is directly mapped to the heating element power, dehumidifier fan speed, and humidity valve opening, forming synchronous parallel regulation of the temperature and humidity loops. During operation, the system monitors the actuator feedback on temperature and humidity status, compares actual values ​​with set values, and dynamically updates compensation parameters. This further enhances the system's robustness to different electrode batches, coating thickness differences, and changes in thermal and humidity disturbances, thus solving the problem of lag in dual-loop control response caused by nonlinear temperature-humidity coupling in traditional methods.

[0014] 2. This invention constructs a multi-point, synchronously sampled temperature and humidity monitoring system, forms a nonlinear coupling model of temperature and humidity, and identifies parameters. Then, a temperature-driven compensation module and a humidity feedback compensation module are designed and embedded in a dual-closed-loop control framework. Finally, at the actuator level, the heating power and dehumidifying fan / valve are corrected. This significantly improves the real-time response speed and dynamic adjustment accuracy of temperature and humidity control. Furthermore, because the compensation module can anticipate and offset the negative impact of humidity on the thermal field and the accelerating effect of temperature on the humid field, it significantly reduces energy consumption fluctuations, shortens drying time, reduces local overheating or residual moisture, improves the overall drying consistency of the electrode plates and the stability of product quality, and achieves efficient, stable, and energy-saving control of the drying system even under changes in electrode plate batches, coating thickness, and hot air circulation conditions. Attached Figure Description

[0015] Figure 1 This is a flowchart of the temperature and humidity dual closed-loop control method for drying cylindrical battery plates according to the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Example: Figure 1 The present invention provides a dual closed-loop control method for temperature and humidity control during the drying of cylindrical battery plates, comprising: S1: Collect real-time temperature and humidity data during the drying process of cylindrical battery plates, and transmit the collected temperature and humidity data to the control system for initial storage; S2: Based on the collected multi-point temperature and humidity data, a nonlinear model of temperature-humidity coupling, including temperature driving terms and humidity feedback terms, is established. S3: Perform parameter identification on the established nonlinear model, determine the influence coefficient of temperature on humidity and the reaction coefficient of humidity on temperature in the model, adjust these coefficients iteratively to make the model reflect the dynamic characteristics of the actual drying process, and update the identified parameters to the control system. S4: Design a temperature and humidity decoupling compensator. Based on the identified parameters, introduce a humidity compensation term in the temperature closed loop to offset humidity interference, and introduce a temperature compensation term in the humidity closed loop to offset temperature interference. Integrate the compensator into the dual closed-loop control framework. S5: Apply the decoupling compensator to the dual closed-loop control system. In the temperature closed loop, adjust the power output of the heating element according to the compensation term. In the humidity closed loop, adjust the wind speed and humidity valve opening of the dehumidification system according to the compensation term. S6: Monitors the operating status of the control system, provides real-time feedback and adjustment to the output of the decoupling compensator, and updates the parameters of the compensation item by comparing the actual temperature and humidity values ​​with the set values.

[0018] S1: Collect real-time temperature and humidity data during the drying process of the cylindrical battery plates, and transmit the collected temperature and humidity data to the control system for initial storage. Specifically, the implementation is as follows: The drying oven is designed as a closed rectangular cavity, with the internal space divided vertically into upper, middle, and lower regions to match the hierarchical arrangement of the electrode conveyor belt. The electrodes pass through the oven body horizontally, exposed to the hot air circulation system. To obtain high-resolution, time-domain continuous data of the thermal and humidity field for subsequent nonlinear coupling model establishment, multiple sensor points are arranged in each region. Temperature data acquisition uses a high-precision platinum resistance temperature sensor (PT100 type) with a measurement range of 0–200℃, an accuracy of ±0.1℃, and a response time of less than 1 second to meet the requirements of rapid changes in the thermal field during the drying process. The PT100 sensor is based on the principle that platinum resistance changes with temperature; its resistance is approximately 100Ω at 0℃, and the resistance increases with increasing temperature, exhibiting good linearity and stability. A temperature sensor array with at least three points is installed on the upper part of the furnace body, located at the center of the furnace top and the two side edges, to monitor the temperature distribution in the upper region. The mounting bracket is fixed about 10-20 cm away from the upper surface of the electrode plate, and the structure is ensured by threaded fixing. The sensor probes are wrapped with heat-insulating material to avoid external thermal and cold disturbances. At the same time, another temperature sensor array with at least three points is installed on the lower part of the furnace body, located at the center of the furnace bottom and the two sides, with an installation height of about 5-10 cm from the furnace bottom. A waterproof coating is applied to the probes to prevent measurement deviations caused by humid environments. The symmetrical arrangement of the upper and lower parts can cover the vertical temperature gradient changes and capture the stratification phenomenon caused by thermal convection, such as the upper temperature being 5-10°C higher than the lower temperature. In this way, the non-uniformity of the temperature field in the furnace cavity can be reflected in real time, and a reliable input can be provided for the subsequent model to determine the boundary conditions. In parallel with temperature acquisition, humidity data is collected by a capacitive humidity sensor (e.g., HMP110 type), with a measurement range of 0–100%RH, typical accuracy of ±1.5%RH, and a response time of less than 10 seconds, suitable for stable monitoring in high humidity environments. The humidity sensor is installed on the side wall at a height of about half the furnace height, with at least two points on each of the left and right walls to monitor the lateral humidity flow distribution, such as the humidity gradient change during the process of hot air entering from one side and exiting from the other. The sensor is embedded and fixed to the inner lining of the side wall, with the probe extending about 5cm into the furnace without interfering with the electrode plate conveying path. In addition, an auxiliary humidity sensor is installed at both the furnace inlet and outlet to monitor the humidity changes of the incoming and outgoing airflow, thereby supplementing the overall humidity distribution dataset. The combination of lateral and vertical sensor arrangement ensures spatial coverage of the humidity field within the furnace cavity. All sensor nodes sample at least 10 times per second (10Hz) to achieve high temporal resolution, thereby capturing transient changes such as the sudden increase in humidity caused by the moment the electrode enters the furnace. All sensors are connected through a multi-channel data acquisition unit that supports synchronous acquisition, ensuring precise alignment of the timestamps of temperature and humidity data, thus avoiding model input errors caused by asynchronous sampling. The acquired raw data includes: temperature value (°C), humidity value (%RH), timestamp, and sensor ID. Subsequently, the data is converted into digital signals by an analog-to-digital converter and transmitted to the control system via a shielded data cable according to the RS-485 protocol. This is suitable for long-distance transmission (up to approximately 50m) from the furnace to the control cabinet, and the data cable is equipped with an electromagnetic shielding layer to resist electromagnetic interference in the industrial environment, ensuring data transmission integrity and reducing transmission latency to less than 50ms. After receiving the data, the control system transmits it to the initial storage module, which can be implemented based on an embedded database or a real-time memory buffer. The storage capacity supports caching at least 1 hour of data (approximately 36,000 data points). The data storage process includes the following preprocessing steps: First, noise filtering is applied to the temperature and humidity data. Taking the median filtering algorithm as an example, when the temperature data shows a jump (e.g., a deviation exceeding ±5℃), the outlier is marked and replaced with the average of its nearest neighboring data. If the humidity data changes at a rate exceeding approximately 20%RH / second, it is similarly marked and replaced with the nearest neighboring average. Second, the temperature and humidity data are standardized. For example, the temperature data is normalized to the 0–1 range using a preset drying target temperature range (e.g., 80–120℃), and the humidity data is also converted to the 0–1 range according to a preset maximum humidity value, so that the subsequent model can input data in a unified format. Finally, the processed data is organized into a structured array according to the time series, including... as well as This structured data is indexed by time and corresponds to each sensor location; it is easy to query and retrieve by time indexing. To ensure data acquisition accuracy, the system implements a sensor calibration mechanism before the drying process begins: a standard temperature and humidity source (e.g., a wet-bulb / dry-bulb thermometer calibration device) is used to verify the accuracy of each temperature and humidity sensor; if a single sensor's deviation exceeds ±0.5℃ or ±0.5%RH, the system automatically alarms and suspends data acquisition until the sensor is replaced or recalibrated; considering the movement of the cylindrical battery plates on the conveyor belt, the sensor's installation height and angle are optimized to ensure that the sensor bracket or probe does not obstruct the hot air path or affect the plate transport; data transmission also features a redundant channel: if the primary RS-485 wired data line experiences a continuous failure (e.g., packet loss rate exceeding 10% continuously or communication delay exceeding 200ms), the system automatically switches to the backup wireless module (based on the ZigBee protocol) to continue transmission, maintaining the continuity and stability of the acquisition channel.

[0019] S2: Based on the collected multi-point temperature and humidity data, a temperature-humidity coupled nonlinear model is established, including a temperature driving term and a humidity feedback term. The specific implementation is as follows: Based on the structured spatiotemporal temperature and humidity dataset collected and stored in S1, the dataset was first retrieved from the storage module according to time series. This dataset includes multiple temperature and humidity points, with temperature points covering different areas of the upper, middle, and lower parts of the furnace body, and humidity points including locations such as the side walls, inlet, and outlet. The data has been synchronized by timestamp and preprocessed and normalized, providing a reliable foundation for subsequent model input. Next, model building begins with independent analysis of the temperature series. The temperature rise phase is manifested as the hot air circulation in the furnace body causing the temperature in the area where the electrode plates are located to rise. This temperature change directly increases the kinetic energy of water molecules inside the electrode plates, decreases surface tension, and accelerates the rate of water migration to the gas phase, thereby triggering a change in the evaporation rate from linear... The process evolves from a phased to an exponential phase. Assuming that the evaporation rate can be driven by variables such as temperature, temperature gradient, and humidity gradient, then: "The evaporation rate equals the baseline evaporation constant multiplied by the temperature increase exponential term, then by the temperature gradient enhancement term, and finally by the humidity gradient suppression term." Among these, the temperature increase exponential term reflects that the evaporation rate increases exponentially with each increase in temperature; the temperature gradient enhancement term reflects that evaporation accelerates when the local temperature distribution changes drastically; and the humidity gradient suppression term reflects that the greater the humidity gradient, the more evaporation is hindered. In the temperature sequence, it can be observed that when the temperature at the top of the furnace increases from the initial room temperature to the target temperature range (e.g., 80-120℃), the corresponding humidity point first shows a brief peak and then rapidly decreases, confirming that evaporation dominates the change in the humidity field. Then, the independent analysis of the humidity sequence was carried out. The inlet end carries more moisture, and the humidity is high when the fresh electrode plate first enters the furnace body, while the humidity is lower at the outlet end, resulting in the formation of a humidity gradient in the furnace cavity. This humidity gradient affects the temperature distribution in reverse through water vapor diffusion, condensation, or hot air convection mechanisms. For example, when water vapor condenses or a water film forms in a high-humidity area, it needs to absorb heat to cause a phase change, resulting in a decrease in the temperature of that area. This can be expressed as: "The rate of temperature change is equal to the baseline thermal conductivity difference multiplied by the ambient temperature minus the sub-region temperature, and then minus the heat loss term caused by the humidity gradient." Among them, the heat loss term caused by the humidity gradient emphasizes that the larger the humidity gradient, the more obvious the suppression of local temperature. The data analysis results show that when the humidity gradient on the sidewall exceeds the preset threshold, the lower temperature sensor records a gradual decreasing trend, indicating the actual role of the humidity gradient as a heat sink. Next, temperature-driven analysis and humidity feedback analysis are integrated into a coupled model. The core logic of the model is: temperature is the dominant variable, and its change drives the humidity response, while humidity and its gradient, as feedback variables, affect the temperature field distribution. The model is expressed as: "The rate of temperature change equals the heat conduction term plus the humidity feedback correction term, and the rate of humidity change equals the temperature-driven term minus the humidity self-diffusion term." The interaction term clearly shows that the temperature gradient accelerates evaporation, while the humidity gradient inhibits temperature rise or causes temperature to fall. To adapt to the furnace's spatial structure, the furnace is divided into several sub-regions, each of which independently maps temperature and humidity data and constructs local coupled equations. The upper sub-region mainly reflects the temperature-driven... The dynamic evaporation mechanism is as follows: the lower sub-region mainly reflects the humidity deposition or condensation mechanism, while the side wall sub-region mainly reflects the lateral humidity and temperature interaction. Taking sub-region i as an example, its temperature change rate is: "the temperature change rate of the sub-region is equal to the heat conduction difference of the sub-region multiplied by the external ambient temperature minus the sub-region temperature, and then minus the humidity gradient of the sub-region multiplied by the feedback coefficient". The humidity change rate is: "the humidity change rate of the sub-region is equal to the temperature driving term of the sub-region multiplied by the temperature sensitivity coefficient, and then minus the humidity diffusion term of the sub-region multiplied by the humidity gradient coefficient". This domain division logic ensures that the model can track how the temperature and humidity state of the electrode plate propagates along the furnace direction on the conveyor belt path and is affected by the humidity gradient to generate temperature deviation in the downstream region. Furthermore, the influence of the geometry and physical properties of the cylindrical battery plates on the coupling mechanism was considered; the plates are typically of type 18650 or 21700, with a diameter of approximately 18–21 mm and a length of approximately 65–70 mm, and their cylindrical surface curvature, coating thickness distribution, and heat capacity were also taken into account. and initial moisture content These characteristics all affect the evaporation / temperature coupling process. The evaporation rate modulation in the model is set as: "baseline evaporation constant multiplied by temperature rise exponent, then multiplied by moisture content attenuation function". The moisture content attenuation function reflects that as the moisture content inside the electrode decreases, the humidity feedback intensity decreases, forming a self-limiting coupling cycle. When the moisture content of the electrode decreases, the feedback effect of the humidity gradient on temperature weakens, and the temperature continues to rise until thermal equilibrium is reached. This consideration enhances the applicability of the model to the special form of battery electrode. After the model is built, it will be imported into the control system in a modular form. The various sub-modules of the model (temperature drive module, humidity feedback module, sub-region mapping module, and plate characteristic modulation module) will be packaged into a recognizable structure (e.g., model definition file) and transmitted to the embedded processor core via the internal bus of the control system. The processor is part of the control system and has a dedicated memory area allocated inside it to store interaction item data, sub-region coefficients, and model calculation cache. The model is in an inactive state and can only run after the parameter identification is completed in the next step. The parameter identification module extracts the initial coefficients (such as the reference evaporation constant, temperature sensitivity coefficient, humidity feedback coefficient, thermal conductivity coefficient, diffusion coefficient, and moisture content attenuation index) from the data collected by S1 and mapped by S2, and writes them into the model running unit after identification. The model import logic ensures seamless data and model integration and provides an interface for downstream compensator design. The application of the model in the control system is to bridge the gap between data input and control output, thereby completing the logical closed loop of the overall control process.

[0020] S3: Perform parameter identification on the established nonlinear model, determine the influence coefficient of temperature on humidity and the reaction coefficient of humidity on temperature in the model, adjust these coefficients iteratively to make the model reflect the dynamic characteristics of the actual drying process, and update the identified parameters to the control system: Within the processing unit of the control system, a nonlinear model of temperature-humidity coupling, including temperature driving terms and humidity feedback terms, imported from S2, is used. Key coefficients in this model are then parameterized to ensure that the model accurately reflects the dynamic characteristics of the cylindrical battery plate drying process and provides a precise parameter basis for subsequent decoupling compensator design. First, the "temperature driving coefficient" is extracted from the model equations to address the driving effect of temperature on humidity evaporation. This coefficient represents the direct influence of the temperature change rate on the humidity evaporation rate per unit time. Specifically, the temperature change rate is defined as the temperature increase per unit time. The model assumes that the evaporation rate is driven by an exponentially amplified temperature increase, defined as: "Evaporation rate equals the baseline evaporation constant multiplied by the temperature increase exponential term multiplied by the temperature gradient enhancement term multiplied by the humidity gradient suppression term." During parameter identification, a structured array containing... The analysis focuses on the time series data of fields such as [field name], specifically the range where the initial drying temperature rapidly increases from approximately 60℃ to approximately 100℃; by comparing this temperature change range with the corresponding [field name]... By observing humidity changes at constant humidity points, it was found that the greater the rate of temperature change, the faster the humidity decreases. This establishes a power-law relationship between the temperature driving coefficient and the rate of temperature change, meaning that the doubling trend of the evaporation rate is stronger than the linear state when the temperature increases by 1°C. During identification, the initial temperature driving coefficient can be determined based on experience or preliminary experimental data. For example, the baseline value can be set to 1.0 unit, and the adjustment step size can be selected as increasing or decreasing by 5% each time. When the maximum deviation between the model prediction curve and the actual humidity curve is less than the preset 3% and the number of adjustment rounds does not exceed five rounds, it is considered that the coefficient has converged. Secondly, the "humidity feedback coefficient" is extracted from the humidity feedback part of the model equation. This coefficient represents the strength of the reaction of the humidity gradient on temperature diffusion and distribution. The humidity gradient is defined as the difference in humidity values ​​at different locations within the furnace cavity; for example, the humidity at the inlet side is approximately 70%RH, and at the outlet side is approximately 20%RH, thus forming a gradient of approximately 50%RH. During the parameter identification process, the following parameters are retrieved... Time series data such as fields, and By comparing temperature change data across fields, the influence of humidity gradient changes on temperature decreases or fluctuations is analyzed. For example, during periods of significant increase in humidity gradient, the lower temperature point shows a decreasing trend of approximately 3°C, indicating that humidity in this area acts as a heat sink, affecting temperature. The humidity feedback term in the model is expressed as: "The rate of temperature change equals the difference in heat conduction multiplied by the ambient temperature minus the regional temperature, then minus the humidity gradient multiplied by the feedback coefficient." During identification, the humidity feedback coefficient can be initially set to a neutral value of 0.5 units, and adjusted round by round based on the deviation between the model's predicted temperature curve and the actual temperature curve, with a recommended adjustment step size of 5% per adjustment. The error judgment criteria are also: the maximum deviation is less than 3% and the number of rounds does not exceed five. Subsequently, an iterative comparison and adjustment process was carried out; firstly, the data was input into the storage module and identified as... Using isothermal sequences, a coupled model is run to generate corresponding humidity prediction curves, which are then compared with measured values. The data is compared; if the model predicts a slower evaporation rate, the temperature driving coefficient is adjusted upwards; if the prediction is faster, it is adjusted downwards; the second stage inputs the humidity sequence. ...and generate a temperature diffusion prediction curve, and compare it with the measured... The process involves several steps: if the diffusion rate is higher than the actual rate, the humidity feedback coefficient is increased to strengthen suppression; if it is lower than the actual rate, the feedback coefficient is decreased. The entire iterative process is divided into three to five rounds to cover different stages, including initial rapid heating, stable drying, and final cooling, so that the model parameters can adapt to the dynamic behavior of the entire drying cycle. In addition, the linkage between coefficients must be considered during the adjustment process. That is, if the temperature driving coefficient increases, it may lead to excessively rapid predicted evaporation, resulting in an imbalance in the temperature field. In this case, the humidity feedback coefficient must be fine-tuned simultaneously to maintain model stability, thereby reflecting the closed-loop characteristics of temperature and humidity coupling. To enhance generalization ability, a data cross-comparison strategy is also adopted: data from a portion of the time period (such as the first half of the drying cycle) is used for parameter adjustment, and the remaining data (such as the second half of the cycle) is used for parameter verification to ensure that the parameters are applicable to different electrode batches or coating thickness variations. After parameter identification is completed, the optimized temperature driving coefficient and humidity feedback coefficient are stored in the control system database in key-value pair format; the database structure is as follows: [Table name missing] The fields include model ID, coefficient name (temperature-driven coefficient / humidity feedback coefficient), version number (e.g., v1.0, v1.1), iteration round, maximum deviation statistics, and save timestamp; a new version is generated and archived for each round of parameter adjustment; the saving process includes verification steps: reloading the identified coefficients into the coupled model, replaying the model prediction using complete drying cycle data, and confirming that the maximum deviation between the model output and the measured data is less than a preset threshold (e.g., 3%), then marking the current coefficient version as "available"; the database supports fast retrieval and version backtracking to ensure that the control system can call the latest and verified parameter set; Through the above extraction, comparison, iteration, and storage process, the core coefficients in the model are refined, enabling a quantitative description of both the driving force of temperature on humidity evaporation and the feedback force of humidity on temperature diffusion. A hierarchical extraction method using temperature change rate and humidity gradient is employed, and a linked iterative approach is used to achieve synergistic optimization of the driving and feedback coefficients. This adapts to the nonlinear coupling behavior caused by the geometric and physical characteristics of cylindrical battery plates (e.g., plates with diameters of 18–21 mm and lengths of 65–70 mm may have different coating thicknesses and initial moisture contents). This surpasses traditional static parameter setting methods, improving the model's responsiveness and accuracy in real-world scenarios. The identified temperature driving and humidity feedback coefficients will be directly used in the decoupling compensator design in S4, thus achieving a complete workflow connection between data acquisition, model building, parameter identification, and control compensation.

[0021] S4: Design a temperature and humidity decoupling compensator. Based on the identified parameters, introduce a humidity compensation term into the temperature closed loop to counteract humidity interference, and introduce a temperature compensation term into the humidity closed loop to counteract temperature interference. Integrate the compensator into the dual closed-loop control framework. Specific implementation is as follows: Based on the temperature driving coefficient and humidity feedback coefficient identified in S3 above, a temperature and humidity decoupling compensator is designed and integrated into the control system to counteract the interference of humidity on temperature and the driving force of temperature on humidity during the temperature-humidity coupling process, thereby achieving the independence and stability of the temperature and humidity loops in the dual closed-loop control framework. First, identified parameters are loaded from the control system database. These parameters include the driving strength of the temperature change rate on humidity evaporation (i.e., the temperature driving coefficient) and the suppressing strength of the humidity gradient on temperature diffusion (i.e., the humidity feedback coefficient). In the compensator design, these two types of coefficients are used in their respective compensation modules, logically constructing two compensation paths to specifically correct coupling interference. A humidity-based compensation module is set in the loop path. Its logic is as follows: The temperature control loop originally maintains the target temperature by adjusting the power of the heating element, but due to high humidity, heat absorption or condensation of moisture causing lag in the thermal field response, compensation is required. The compensation module generates a compensation increment by comparing the current humidity with the target humidity. This increment is multiplied by the humidity feedback coefficient. For example, when the humidity gradient is significant, the compensation increment is increased, thereby increasing the heating signal strength and pre-compensating for the heat absorption and cooling effect. This compensation module is placed at the front end of the temperature feedback loop. The logic is to first correct the heating signal before entering the temperature controller to ensure that the temperature closed loop can anticipate humidity interference and avoid temperature overshoot or lag, thereby ensuring that the thermal field in the furnace advances uniformly. Meanwhile, a temperature-based compensation module is added to the humidity closed-loop path. The logic is as follows: The humidity control loop originally controls the moisture evaporation rate by adjusting the dehumidification fan speed or valve opening. However, when the temperature change rate is high, evaporation is accelerated by temperature, which may lead to excessively rapid humidity drop, humidity control oscillation, or excessively low humidity. The compensation module generates a correction increment for the humidity control signal by comparing the current temperature with the target temperature. This increment is inversely proportional to the temperature drive coefficient. For example, when the temperature change rate is large, the compensation increment decreases, thereby weakening the dehumidification signal and avoiding excessive drying. This module is also placed at the front end of the humidity feedback loop to ensure that the humidity closed-loop signal has considered the temperature drive effect before entering the controller, thus avoiding the humidity control being disturbed by temperature changes. Based on this, the two compensation modules mentioned above are embedded in the logic framework of a dual-closed-loop control. This dual-closed-loop control framework includes an inner temperature closed loop and an outer humidity closed loop, with the compensator acting as a bridging element at the interface between the two loops. The temperature compensation module is inserted into the input of the temperature loop, and the humidity compensation module is inserted into the input of the humidity loop. The actual signal path is as follows: the signal received by the temperature loop is the original temperature feedback signal plus the humidity compensation increment; while the signal received by the humidity loop is the original humidity feedback signal plus the temperature compensation increment. Through this cross-compensation structure, the coupling effect of the two loops is isolated, the temperature loop can ignore humidity disturbances to a certain extent, and the humidity loop can operate independently of temperature disturbances. After the framework design is completed, it is verified by playing back simulation data from the control system, such as simulating scenarios of temperature rise, humidity drop, and humidity disturbances during the drying process, and observing the changes in loop response before and after the compensator intervention. The simulation results confirm that after the compensator is embedded, the temperature response is smoother, the humidity oscillation amplitude is reduced, and the coupling-induced oscillations generated by the two loops disappear, thus verifying the effectiveness of the compensation design. The compensator design emphasizes a modular structure: each compensation module is an independent logic unit, with inputs being identification parameters and real-time measurement signals, and outputs being control signal correction increments. Taking the temperature compensation module as an example, its logic chain is: humidity deviation (i.e., the difference between current humidity and target humidity) multiplied by the humidity feedback coefficient generates the increment, which is directly superimposed on the temperature control signal. Similarly, taking the humidity compensation module as an example, its logic chain is: temperature deviation (i.e., the difference between current temperature and target temperature) multiplied by the reciprocal of the temperature driving coefficient generates the increment, which is directly superimposed on the humidity control signal. This modular structure simplifies maintenance and expansion. When identification parameters are updated or electrode batches change, the internal coefficients of the module can be quickly replaced without reconstructing the entire control framework. The design further divides the embedding layers: the first layer is path addition, connecting the compensation modules in series to the feedback link; the second layer is parameter binding, fixing the temperature driving coefficient and humidity feedback coefficient within each module; the third layer is framework testing, monitoring response delay, gain, and oscillation conditions through the control system, adjusting module positions and signal weighting to minimize system delay and coupling effects. Through parameter-driven compensation construction, a complementary decoupling framework is achieved: the humidity compensation module in the temperature path is used to correct the thermal response affected by humidity disturbances, and the temperature compensation module in the humidity path is used to correct the evaporation rate affected by temperature disturbances, thereby achieving logical isolation of coupled variables; on the one hand, the compensator design is directly based on the identified parameters, reflecting the three-level logical integration of parameters-modules-framework; on the other hand, the compensator does not act unidirectionally, but forms a complementary structure between the two closed loops, so that the coupling of temperature to humidity and humidity to temperature can be systematically controlled. The document describes every step from parameter loading, module design, signal superposition, framework embedding to verification testing. It describes how to construct a compensation module by identifying coefficients, form a complementary structure by cross-inserting two closed-loop input terminals, and verify the compensation effect by replaying simulated data. After identification, the temperature driving coefficient and humidity feedback coefficient are directly input into the compensator module and configured into the control system. This allows the temperature compensation module to correct the heating power execution signal and the humidity compensation module to correct the dehumidification fan speed or valve opening execution signal simultaneously, thus forming a complete logical link between data acquisition, model building, parameter identification, compensation design and control execution.

[0022] S5: Apply a decoupling compensator to the dual closed-loop control system. In the temperature closed loop, adjust the power output of the heating element according to the compensation term. In the humidity closed loop, adjust the fan speed and humidity valve opening of the dehumidification system according to the compensation term. The specific implementation is as follows: Based on the temperature and humidity decoupling compensator designed and configured in the control system in S4, the temperature driving coefficient and humidity feedback coefficient identified in S3 are used to apply the output increment of the compensator to the dual closed-loop control system to achieve independent adjustment of the temperature closed-loop and humidity closed-loop paths, thereby ensuring that the control commands for the thermal and humidity environment of the plates in the drying oven can be executed synchronously and accurately. First, in the temperature closed-loop path, the power output of the heating element is adjusted according to the humidity correction increment output by the compensation module. The original temperature closed-loop control path uses the target temperature as a reference, and the control signal is generated after sensor feedback to drive the heating element. However, humidity disturbances in the furnace, especially when the humidity gradient is significant, cause the moisture to absorb heat or condense, resulting in a lag in the heating response. After the compensation module loads the humidity feedback coefficient, it compares the current humidity value with the target humidity value and generates a compensation increment, which is proportionally related to the humidity feedback coefficient. When the humidity is too high or the humidity gradient is large, the compensation increment is larger, thereby increasing the heating voltage offset to enhance the pre-compensation heat absorption and cooling effect of the heating power. Furthermore, this module is positioned at the front end of the temperature feedback closed loop. Logically, the original temperature control signal is first superimposed with a compensation increment before being input to the temperature controller. This ensures that the temperature closed loop operates independently under humidity disturbance conditions, avoiding temperature overshoot or lag. The voltage offset value output by the compensation module directly points to the heating element driver. If a resistance wire heater is used, its voltage input range can be set to 0–220V, corresponding to an adjustable power output range of 0–10kW. Assuming that the power increases by approximately 1kW for every 10V increase in voltage, in the upper high-temperature plate area, when the humidity is high, the compensation module increases the voltage to maintain uniform heat penetration and avoid local overheating. The adjustment logic steps include: first, reading the incremental value output by the compensation module; second, integrating this increment with the original temperature closed loop control signal; and third, modulating the voltage waveform in real time through the power controller, with a response time controlled to within 1 second. This ensures the independent response of the temperature closed loop under humidity disturbances and can accurately match the heat demand of the plate. For example, during the peak humidity stage in the middle of drying, the heating voltage is automatically increased to compensate for heat loss. Meanwhile, in the humidity closed-loop path, the fan speed and humidity valve opening of the dehumidification system are adjusted according to the temperature correction increment output by the compensation module. This humidity closed-loop control path uses the target humidity as a reference, receives feedback from the humidity sensor, and generates the original humidity control command to adjust the dehumidification fan speed and valve opening / closing. However, when the temperature change rate is large, the humidity may drop too quickly due to accelerated evaporation caused by temperature drive, potentially leading to control oscillation or excessively low humidity. After loading the temperature drive coefficient, the compensation module compares the current temperature value with the target temperature value to generate a compensation increment, which is inversely proportional to the temperature drive coefficient. When the temperature change rate is high, the compensation increment is smaller to reduce the dehumidification fan speed or decrease the valve opening, thereby mitigating the evaporation rate and preventing excessively rapid humidity drop. This module is placed at the front end of the humidity feedback closed loop; logically, the humidity control signal is first superimposed with the temperature compensation increment before being processed by the humidity controller. The fan speed and humidity valve opening of the compensation module are adjusted accordingly. Speed ​​offset and valve angle offset are achieved through the actuator interface; for example, the fan uses a variable frequency motor with a speed range of 0–3000 r / min, and the valve uses an electric butterfly valve with an opening angle range of 0–90 degrees; assuming that the dehumidification efficiency decreases by about 20% for every 500 r / min reduction in fan speed, and the airflow resistance increases by about 10% for every 10 degree reduction in valve angle, then under the condition of humidity retention on the lower wet zone plate, the airflow intensity is controlled by reducing the fan speed and narrowing the valve angle, thereby ensuring that moisture evaporates quickly but not excessively; the adjustment process includes: reading the compensation increment value; integrating it into the humidity control signal; and adjusting the fan speed and valve angle in real time, with a response time controlled to less than 2 seconds; ensuring that the humidity closed loop can maintain independent operation under temperature disturbances, and that the fan and valve work together to meet the moisture evaporation requirements of the plate, for example, in the initial stage of temperature rise during drying, the fan speed is automatically reduced to compensate for excessive evaporation; To ensure the simultaneous execution of the two closed-loop control commands in the drying oven, a synchronous execution mechanism is also set up to coordinate the parallel output of correction signals for the temperature and humidity paths. The control system adopts a parallel structure, packaging the voltage regulation command of the temperature closed loop and the wind speed / valve angle adjustment command of the humidity closed loop into a single package, and sending it to the furnace actuator system every cycle (e.g., 100ms). The synchronization logic starts from signal fusion, packaging the temperature control command and humidity control command into a composite execution command, which is output through multiple channels of the central execution unit (e.g., PLC controller) to trigger the actions of the heating element and dehumidification system in parallel. The logic implementation is as follows: first trigger the heating voltage command, and simultaneously start the fan and adjust the valve to ensure that the hot air circulation and dehumidification actions are coordinated, avoiding local humidity accumulation or thermal imbalance. During the simulation verification, the system response after the intervention of the compensator showed that the temperature and humidity deviations converged simultaneously, without coupling-induced oscillation. This synchronization mechanism ensures that the command has no time delay interference, which plays a key role in ensuring the overall drying process of the cylindrical plates. For example, in the initial stage when a large number of wet plates enter the furnace at the inlet, the heating voltage and valve opening are adjusted synchronously to prevent condensation on the plate surface and ensure uniform evaporation. Regarding actuator mapping, the control logic is clearly hierarchically structured: in the temperature closed loop, the heating element voltage regulation chain is "compensation increment - signal superposition - power conversion," aiming to capture the heat absorption effect of humidity on the thermal field; in the humidity closed loop, the fan speed regulation chain is "compensation increment - signal superposition - motor pulse," aiming to capture the driving effect of temperature on evaporation, and the valve angle regulation chain is "compensation increment - signal superposition - servo position," used to assist in airflow optimization; after integration, the control framework logic has a three-level structure of "compensation guidance - actuator response - synchronous feedback"; the system also sets up simulated interference tests, such as injecting virtual humidity peaks, and observing the temperature closed loop power increase and humidity closed loop speed adjustment through the compensator. The system was designed to ensure no oscillations occurred. Parameter mapping was used to drive compensation execution, achieving synchronous dual-loop control: humidity correction in the temperature path adjusted the heating power, while temperature correction in the humidity path adjusted the dehumidification speed and valve opening. This ensured logical isolation of temperature and humidity disturbances during the drying process and guaranteed accurate system response. Furthermore, the compensation actuator logic was integrated in parallel, surpassing traditional series control methods. Actuator adjustment logic was specifically designed for the temperature and humidity coupling characteristics during the cylindrical plate drying process (such as temperature-driven evaporation acceleration and humidity gradient-induced heat sink effect). The system was described in detail from compensation output, actuator mapping, synchronization mechanism, control logic, and simulation verification, completing the design, integration, and operation of the entire control system. The identified temperature driving coefficient and humidity feedback coefficient will be directly used as the calling parameters of the compensator module in the control system. The correction signal output by the compensator is mapped to the control commands of the heating power adjustment and dehumidification system fan / valve, thereby realizing a complete closed loop process from data acquisition, model building, parameter identification, compensation design to control execution.

[0023] S6: Monitor the operating status of the control system, provide real-time feedback adjustment to the output of the decoupling compensator, and update the parameters of the compensation item by comparing the actual temperature and humidity values ​​with the set values. Specifically, this is implemented as follows: Based on the temperature and humidity decoupling compensator and dual closed-loop control system used in S5, a monitoring submodule is set up within the control system to provide real-time feedback and adjustment of the execution status, ensuring the stable coordinated operation of the temperature and humidity closed loops. First, the system starts with actuator feedback signals, including the temperature response after heating power adjustment and the humidity response after fan / valve adjustment. The monitoring submodule continuously collects these feedback signals, compares them with the incremental effect of the compensator output, and determines whether the control action is implemented as expected. Specifically, the temperature feedback signal comes from the upper and lower points of the temperature sensing network, reflecting changes in the thermal field distribution; the humidity feedback signal comes from the humidity sensing points on the side walls and at the ends, reflecting the flow state of the humid field. The acquisition frequency is set to ten times per second, consistent with the data acquisition frequency in step S1, to ensure data synchronization. The acquired data is immediately entered into a buffer for subsequent comparison. Secondly, the monitoring module compares the feedback values ​​with preset target values. The target values ​​are preset by the process standards, for example, the temperature target is in the range of 80 to 120°C, and the humidity target is in the range of 20% to 50%RH. The comparison process first extracts the current upper and lower temperatures from the temperature feedback sequence and compares them with the target range to generate a temperature difference vector. If the upper temperature is higher than the target range, it indicates that the heating may be excessive or the humidity suppression may be insufficient. If the lower temperature is lower than the target, it indicates that the heat conduction is insufficient. Similarly, for the humidity, the current values ​​are extracted from the sidewall humidity and end humidity and compared with the target range to generate a humidity difference vector. High sidewall humidity indicates the risk of residual moisture, and low end humidity indicates that it may be too dry. The difference index is used to identify nonlinear coupling residues. For example, if the humidity is still high after humidity compensation, it means that the temperature drive has not been sufficiently suppressed. Based on the difference vector, the monitoring module dynamically modifies the internal parameters of the compensator. The humidity compensation module parameters (i.e., the humidity feedback coefficient) in the temperature closed loop are driven by the temperature difference: if the temperature difference is positive (actual temperature is higher than the target), the system logic appropriately reduces the humidity feedback coefficient to weaken the humidity compensation increment and prevent overheating; if the temperature difference is negative, the coefficient is increased to strengthen compensation. The temperature compensation module parameters (i.e., the temperature driving coefficient) in the humidity closed loop are driven by the humidity difference: if the humidity difference is positive (actual humidity is higher than the target), the logic increases the reciprocal of the temperature driving coefficient to strengthen the humidity compensation effect and avoid residual moisture; if the humidity difference is negative, the coefficient is decreased to slow down the evaporation tendency. The parameter adjustment range is usually limited to ±20% of the identification benchmark, and is modified at most once per cycle (each acquisition cycle or each adjustment cycle). The modification process includes: first, allocating the differences according to the closed loop (temperature difference corresponds to the humidity module, humidity difference corresponds to the temperature module); then, mapping the parameter increment according to the difference magnitude (large difference, large adjustment magnitude; small difference, fine adjustment); finally, immediately applying the modification results to the compensation output and observing the deviation change in the next cycle. The monitoring module simultaneously executes closed-loop coordination logic to ensure that the two closed-loop systems do not interfere with each other and operate stably as a whole. After the temperature loop stabilizes, its output state will serve as the reference input for the humidity loop. Conversely, after the humidity loop stabilizes, its state can lock the temperature loop parameters, thereby achieving priority sorting. For example, when the temperature loop deviation is cleared to zero, the system automatically maintains the humidity loop parameters at the current value to avoid readjustment. The entire monitoring-feedback-modification-coordination loop runs continuously, and the acquisition-comparison-modification logic is repeatedly executed. The monitoring module records the deviation trend: when the average deviation is lower than the set threshold and remains stable for several consecutive cycles, the system is marked as operating in a stable state; when the deviation exceeds the preset upper limit, the system triggers an alarm and continues parameter correction. To enhance implementation feasibility, mechanisms for anomaly handling and historical data analysis are also included. For jumps or anomalies in collected values ​​(such as sudden temperature drops or humidity increases), the monitoring module will mark the anomaly and replace it with the nearest average value or the previous period's value to prevent noise-induced erroneous corrections. The comparison logic is tiered: a fine-tuning mode is used when differences are small, while a warning mode is entered when differences suddenly increase or the trend continues, with increased parameter adjustment amplitude and frequency. Upper and lower limits for parameters are set in the coordination logic to prevent excessive adjustment of compensator parameters from causing system oscillations or control instability. The system has a built-in version management module that generates a version record for each parameter modification, including the parameter name, previous value, new value, reason for modification, and timestamp, facilitating traceability and maintenance. Furthermore, the closed-loop feedback logic of difference-parameter-coordination can continuously adjust the controller parameters to address the nonlinear coupling characteristics during the drying process of cylindrical battery plates (such as temperature-driven evaporation acceleration and humidity gradient-induced condensation suppression), thereby improving the robustness and response performance of the system. Furthermore, the entire process, from feedback acquisition, difference comparison, parameter modification, and closed-loop coordination, is based on the design of the monitoring module, the real-time adjustment of the control system, and the updating of the compensator parameters. The execution status data collected by the monitoring system (including heating voltage, fan speed, valve angle, temperature deviation, and humidity deviation) will be used for the next round of compensator parameter updates, forming a closed-loop control process of monitoring-feedback-adjustment.

[0024] In this embodiment, the scheme first collects real-time temperature and humidity data through a distributed sensor network. This includes arranging platinum resistance temperature sensors and capacitive humidity sensors on the upper, lower, and side walls of the drying oven to obtain the heat and humidity distribution inside the oven through multi-channel synchronous sampling. After noise filtering and standardization preprocessing, the data is structured and stored in the control system, providing a foundation for subsequent modeling. Next, based on the collected data, a temperature-humidity coupled nonlinear model is established, including temperature driving terms and humidity feedback terms. This model analyzes the accelerating effect of temperature increase on the evaporation rate of moisture on the electrode plates and the inverse effect of humidity gradient on temperature uniformity, forming a quantitative equation containing interaction terms, which is then imported into the processing unit. Finally, the model is parameter identified, and parameters directly affecting the humidity evaporation coefficient and the effect of humidity gradient on temperature are extracted. The reaction parameters for temperature diffusion are iteratively adjusted through multiple data comparisons to match the actual dynamics and saved to a database. Subsequently, a temperature and humidity decoupling compensator is designed. Based on the identified parameters, a humidity compensation module is added to the temperature closed loop to correct the control signal, and a temperature compensation module is added to the humidity closed loop to correct the control signal. This is embedded in a dual-closed-loop framework to achieve interference cancellation. Then, the compensator is applied to the control system. During the temperature closed loop execution, the voltage input control power of the heating element is adjusted based on the compensation output. During the humidity closed loop execution, the fan speed and the opening angle of the dehumidification valve are adjusted to ensure that the commands act synchronously on the drying oven. Finally, the system's operating status is monitored, and sensor feedback values ​​are continuously collected and compared with preset targets. The compensator parameters are dynamically modified based on the differences to maintain the coordination and stability of the temperature and humidity closed loops. This method, through layer-by-layer logic construction and parameter optimization, effectively solves the response lag problem caused by the nonlinear coupling of temperature and humidity, improving drying accuracy and efficiency.

[0025] It should be noted that this invention can be deployed on the device itself to realize embedded applications, or it can run on a PC or other terminal with a user interface, thereby meeting various hardware environments and usage requirements.

[0026] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wireless or wired transmission; wired transmission methods include optical fiber, twisted pair, coaxial cable, etc.; wireless transmission includes infrared, microwave, etc. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center containing one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0027] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0028] In the embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0029] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0030] In addition, the functional modules in the embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0031] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0032] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0033] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for dual closed-loop control of temperature and humidity during drying of cylindrical battery plates, characterized in that, include: S1: Collect real-time temperature and humidity data during the drying process of cylindrical battery plates, and transmit the collected temperature and humidity data to the control system for initial storage; S2: Based on the collected multi-point temperature and humidity data, a nonlinear model of temperature-humidity coupling, including temperature driving terms and humidity feedback terms, is established. S3: Perform parameter identification on the established nonlinear model, determine the influence coefficient of temperature on humidity and the reaction coefficient of humidity on temperature in the model, adjust these coefficients iteratively to make the model reflect the dynamic characteristics of the actual drying process, and update the identified parameters to the control system. S4: Design a temperature and humidity decoupling compensator. Based on the identified parameters, introduce a humidity compensation term in the temperature closed loop to offset humidity interference, and introduce a temperature compensation term in the humidity closed loop to offset temperature interference. Integrate the compensator into the dual closed-loop control framework. S5: Apply the decoupling compensator to the dual closed-loop control system. In the temperature closed loop, adjust the power output of the heating element according to the compensation term. In the humidity closed loop, adjust the wind speed and humidity valve opening of the dehumidification system according to the compensation term. S6: Monitors the operating status of the control system, provides real-time feedback and adjustment to the output of the decoupling compensator, and updates the parameters of the compensation item by comparing the actual temperature and humidity values ​​with the set values.

2. The method for dual closed-loop temperature and humidity control of cylindrical battery plates according to claim 1, characterized in that, Real-time temperature and humidity data are collected during the drying process of cylindrical battery plates. The collected temperature and humidity data are then transmitted to the control system for initial storage, including: The drying oven cavity is divided into multiple zones along the vertical direction to match the electrode conveying path; Distributed temperature sensor arrays are deployed in various areas to monitor the temperature distribution gradient between the upper and lower parts; An array of capacitive humidity sensors is arranged on the side wall to monitor overall and lateral humidity flow; Data is sampled synchronously using a multi-channel data acquisition unit to ensure time alignment; After analog-to-digital conversion and shielding, the data is transmitted to the control system. After noise filtering and standardization preprocessing, it is stored in the embedded module in a time-series structure. Sensor calibration is performed before the process starts, and redundant wireless channels are designed.

3. The method for dual closed-loop temperature and humidity control for drying cylindrical battery plates according to claim 1, characterized in that, Based on the collected multi-point temperature and humidity data, a temperature-humidity coupled nonlinear model is established, including a temperature-driven term and a humidity feedback term, comprising: Retrieve time-series temperature and humidity data from structured spatiotemporal datasets, and divide the furnace body into upper, middle, and lower sub-regions to match the electrode paths; The mechanism by which temperature rise accelerates the rate of moisture evaporation on the electrode and the feedback constraint of humidity gradient on temperature uniformity are analyzed. Integrating the modulation and interaction process of electrode geometry and physical properties; The model is modularly imported into the embedded processor of the control system, and a parameter recognition interface is reserved.

4. The method for dual closed-loop temperature and humidity control of cylindrical battery plates for drying according to claim 1, characterized in that, The established nonlinear model is parameter identified to determine the influence coefficient of temperature on humidity and the reaction coefficient of humidity on temperature. These coefficients are then iteratively adjusted to ensure the model reflects the dynamic characteristics of the actual drying process. The identified parameters are then updated to the control system, including: Retrieve the spatiotemporal temperature and humidity dataset from the storage module by time series; The parameters that directly affect the humidity evaporation coefficient and the parameters that react with the humidity gradient on temperature diffusion are extracted from the model. These parameters are adjusted iteratively through data comparison, covering the entire drying cycle in multiple rounds, and emphasizing parameter linkage; A cross-comparison strategy is adopted, using partial data to adjust parameters and the remaining data to verify generalization ability; The optimized parameters are stored in the control system database as key-value pairs, and the available status is verified by playback.

5. The method for dual closed-loop temperature and humidity control for drying cylindrical battery plates according to claim 1, characterized in that, Design a temperature and humidity decoupling compensator. Based on the identified parameters, introduce a humidity compensation term into the temperature closed loop to counteract humidity interference, and introduce a temperature compensation term into the humidity closed loop to counteract temperature interference. Integrate the compensator into a dual closed-loop control framework, including: Load identification parameters from the control system database, including temperature drive coefficient and humidity feedback coefficient; A humidity-based compensation module is added to the temperature closed-loop path to generate a compensation increment correction control signal based on the humidity deviation and feedback coefficient. A temperature-based compensation module is added to the humidity closed-loop path to generate a compensation increment correction control signal by inverting the temperature deviation and the driving coefficient. Two compensation modules are embedded in the dual closed-loop control framework to form a cross-complementary structure. The temperature loop input is connected to the humidity compensation module, and the humidity loop input is connected to the temperature compensation module. The compensator is constructed using modular logic units.

6. The method for dual closed-loop temperature and humidity control for drying cylindrical battery plates according to claim 1, characterized in that, The decoupling compensator is applied to a dual-loop control system. In the temperature closed loop, the power output of the heating element is adjusted according to the compensation term. In the humidity closed loop, the fan speed and humidity valve opening of the dehumidification system are adjusted according to the compensation term. This includes: Load the identification parameters into the compensation module; In the temperature closed-loop path, the voltage offset increment generated by the output of the humidity compensation module is used to correct the original control signal and drive the power adjustment of the heating element. In the humidity closed-loop path, the original control signal is corrected based on the speed and angle offset increments generated by the temperature compensation module, which drives the fan speed and the opening and closing of the dehumidification valve to adjust. The actuator interface maps compensation increments to heating voltage, fan motor pulses, and valve servo positions.

7. The method for dual closed-loop temperature and humidity control of cylindrical battery plates for drying according to claim 6, characterized in that, include: A parallel frame structure is adopted to package the temperature closed-loop voltage regulation command and the humidity closed-loop wind speed angle regulation command into a composite execution package, which is synchronously sent to the central execution unit every cycle. The clock drives the multi-channel output, triggering the heating element and dehumidification system in parallel. The smoothness of the framework response was verified by simulating interference playback, thus forming parameter-driven synchronous execution logic.

8. The method for dual closed-loop temperature and humidity control for drying cylindrical battery plates according to claim 1, characterized in that, The system monitors and controls the operating status, provides real-time feedback adjustments to the output of the decoupling compensator, and updates the parameters of the compensation items by comparing actual temperature and humidity values ​​with set values, including: Temperature and humidity sensor values ​​are continuously collected from the actuator feedback signal, including the temperature distribution at the top and bottom and the humidity flow at the side wall end; The feedback sequence is compared with the preset target value to generate temperature difference vector and humidity difference vector, and the difference is allocated according to the closed loop. The compensator parameters are dynamically modified based on the differences, including adjusting the feedback coefficient of the humidity compensation module and the driving coefficient of the temperature compensation module, mapping the increment according to the difference magnitude and limiting the adjustment range.

9. The method for dual closed-loop temperature and humidity control for drying cylindrical battery plates according to claim 8, characterized in that, include: Execute closed-loop coordination logic, using the stable state of the temperature loop as the reference input for the humidity loop, and otherwise locking the parameters; To handle abnormal feedback values, noise is identified and replaced with neighboring values. The system uses a tiered comparison logic, with fine-tuning for small differences and alerting and increasing the frequency of adjustments for large differences. The built-in version management module generates a record for each parameter modification, including the coefficient name, the values ​​before and after the modification, the reason, and the timestamp, supporting traceability and database storage.

Images