Intelligent optimization control system and device for lithium deposition production process of battery-grade lithium carbonate

Abstract

The invention relates to the technical field of battery production. The intelligent optimization control system comprises a data acquisition and monitoring module, a model construction module, a process optimization module, an intelligent analysis and decision module, an automatic control module, a feedback correction module, a visualization and remote monitoring module, a multi-stage interlocking safety protection mechanism and an online monitoring system. And a system management module. By integrating the data acquisition and monitoring module, the model construction module and the process optimization module, automatic adjustment and optimization of parameters are realized, the data acquisition and monitoring module is utilized to acquire key parameters such as temperature, concentration and pH value in real time, the model construction module constructs a dynamic mathematical model based on the data, and the process optimization is realized. And a process optimization module is used for calculating an optimal process parameter combination according to the model, so that the manual intervention is reduced, the adjustment process is shortened, and the energy consumption is reduced and the recovery rate is improved by optimizing parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of battery production, and in particular to an intelligent optimization control system and device for a battery-grade lithium carbonate precipitation production process. Background Art

[0002] Battery-grade lithium carbonate is the core raw material of lithium-ion batteries, and its lithium precipitation process directly affects product quality and production costs. In the existing technology, the traditional lithium precipitation process relies on manual experience to adjust parameters, and has problems such as lengthy process, high energy consumption, and low recovery rate (for example, the recovery rate of lithium extraction from lithium mica is less than 90%). In addition, the insufficient accuracy of the sensor leads to large control deviations of key parameters (such as temperature and pH value), and the lack of encryption mechanism for data collection and transmission poses a safety hazard. In addition, the improvement schemes recorded in the public literature (such as composite extractant lithium extraction and adsorption method optimization) still face technical bottlenecks such as high extractant cost, difficult adsorbent regeneration, and low mass transfer efficiency. The existing control system also lacks multi-level interlocking protection and adaptive adjustment capabilities, and it is difficult to cope with raw material fluctuations or sudden abnormalities. Therefore, it is urgent to design an intelligent optimization control system and device for the battery-grade lithium carbonate precipitation production process to solve the above problems. Summary of the Invention

[0003] The purpose of the present invention is to provide an intelligent optimization control system and device for the production process of battery-grade lithium carbonate precipitation, so as to solve the problems in the prior art proposed in the above background technology, in which the traditional lithium precipitation process relies on manual experience to adjust parameters, has the characteristics of lengthy process, high energy consumption, low recovery rate, lack of encryption mechanism for data collection and transmission, and potential safety hazards.

[0004] To achieve the above-mentioned objectives, the present invention provides the following technical solutions: an intelligent optimization and control system for the production process of battery-grade lithium carbonate precipitation, comprising a data acquisition and monitoring module, a model building module, a process optimization module, an intelligent analysis and decision-making module, an automation control module, a feedback correction module, a visualization and remote monitoring module, a multi-level interlocking safety protection mechanism, an online monitoring system, and a system management module. The data acquisition and monitoring module is used to collect key parameters in the lithium precipitation process in real time, including temperature, concentration, pH value, and flow rate; the model building module constructs a dynamic mathematical model of the process based on the collected historical data; the process optimization module calculates the optimal process parameter combination according to the dynamic mathematical model; the intelligent analysis and decision-making module optimizes the process parameters through big data analysis and machine learning algorithms; the automation control module sends the optimized process parameters to the actuator to realize automatic adjustment of the process parameters; the feedback correction module corrects the model deviation in real time; the visualization and remote monitoring module is used to realize real-time monitoring and remote operation of the production process; the multi-level interlocking safety protection mechanism is used to automatically cut off or adjust the process parameters under abnormal circumstances; the online monitoring system is used to monitor the process parameters and product quality in real time; and the system management module is used to store historical data, analyze production trends, and optimize production plans.

[0005] Preferably, the data acquisition and monitoring module includes multiple sensor nodes and a data encryption transmission unit. The sensor nodes have an anti-interference design, can work stably in high temperature and high humidity environments, and ensure data accuracy through a self-calibration function; the data encryption transmission unit is used to encrypt the collected data and transmit it to the central control system through a secure communication protocol.

[0006] Preferably, the intelligent analysis and decision-making module includes a data preprocessing unit, a machine learning model and an adaptive adjustment unit. The data preprocessing unit is used to clean and normalize the collected data; the machine learning model is used to optimize process parameters based on historical data and real-time data; and the adaptive adjustment unit is used to dynamically adjust the optimization strategy based on raw material characteristics and production environment.

[0007] Preferably, the automation control module includes an actuator and a feedback control unit, wherein the actuator is used to adjust the temperature, stirring speed and feeding speed of the lithium precipitation reactor; and the feedback control unit is used to dynamically adjust the working state of the actuator according to real-time data.

[0008] Preferably, the visualization and remote monitoring module includes an intelligent central control screen and a mobile terminal. The intelligent central control screen is used to display production data and equipment status in real time; the mobile terminal is used for remote monitoring and operation, and ensures system security through identity authentication and authority management.

[0009] An intelligent optimization control device for the production process of battery-grade lithium carbonate and lithium precipitation includes an extraction device, a lithium precipitation reactor, a filtering device, a drying device, a central controller, an intelligent inspection robot, and an exhaust gas treatment device. The extraction device is used for extracting and separating lithium salts; the lithium precipitation reactor is used to precipitate lithium carbonate under optimized process conditions; the filtering device is used to separate the precipitate from the mother liquor; the drying device is used to dry the filter cake to a finished product; the central controller receives the optimization parameters and controls the operation of each device; the intelligent inspection robot is used to replace manual inspections; and the exhaust gas treatment device is used to treat harmful gases generated during the production process.

[0010] Preferably, the lithium precipitation reactor is equipped with a high-precision temperature control system and a stirring device. The high-precision temperature control system adopts an advanced control algorithm and can accurately control the temperature of the reactor; the stirring device can automatically adjust the stirring speed according to the optimized process parameters to improve the reaction efficiency.

[0011] Preferably, the intelligent control unit can dynamically adjust the operating parameters during the evaporation and crystallization process according to real-time data.

[0012] Preferably, the multi-sensor fusion system includes a temperature sensor, a humidity sensor, and a gas concentration sensor; the wireless communication module supports high-speed data transmission, ensuring that the device status data collected in real time can be transmitted to the central control system in a timely manner.

[0013] Preferably, the central controller adopts a multi-level control strategy and supports manual, semi-automatic and fully automatic mode switching. The multi-level control strategy can automatically adjust the control strategy according to production needs.

[0014] Compared with the prior art, the present invention has the following beneficial effects:

[0015] 1. By integrating the data acquisition and monitoring module, the model building module and the process optimization module, automatic adjustment and optimization of parameters are achieved. The data acquisition and monitoring module is used to collect key parameters such as temperature, concentration, pH value in real time. The model building module builds a dynamic mathematical model based on this data. The process optimization module then calculates the optimal process parameter combination according to the model, thereby reducing manual intervention, shortening the adjustment process, and achieving reduced energy consumption and improved recovery rate by optimizing parameters.

[0016] 2. A data encryption transmission unit is integrated into the data acquisition and monitoring module. This unit uses a highly efficient data encryption algorithm to encrypt the collected data and transmit it through a strict secure communication protocol, ensuring data security during transmission. This encryption mechanism prevents data leakage and tampering in complex network environments, ensuring the security of production data.

[0017] 3. The central controller adopts a multi-level control strategy and integrates a feedback correction module and an adaptive adjustment unit. It can monitor the real-time data of the production line in real time and automatically adjust the control strategy to adapt to different production needs and environmental changes. The multi-level interlocking safety protection mechanism can automatically cut off or adjust process parameters under abnormal circumstances to ensure the continuity and stability of the production process. This adaptive control strategy improves the flexibility and robustness of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a planar schematic diagram of the overall production process of the structure of the present invention;

[0019] Figure 2 This is a platform block diagram of the main material processing process of the present invention;

[0020] Figure 3 A platform block diagram of the central controller and sensor network of the present invention;

[0021] Figure 4 This is a platform block diagram of the intelligent control and feedback logic of the present invention;

[0022] Figure 5 This is a platform block diagram of the safety and inspection process of the present invention.

[0023] In the figure: 1. Central controller; 11. Intelligent inspection robot; 2. Extraction device; 21. Lithium precipitation reactor; 22. Filtration device; 23. Drying device; 3. Exhaust gas treatment device. DETAILED DESCRIPTION

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0025] See also Figure 1-5 , an embodiment provided by the present invention:

[0026] Intelligent optimization control system for battery-grade lithium carbonate precipitation production process: includes data acquisition and monitoring module, model building module, process optimization module, intelligent analysis and decision-making module, automation control module, feedback correction module, visualization and remote monitoring module, multi-level interlocking safety protection mechanism, online monitoring system, and system management module. The data acquisition and monitoring module is used to collect key parameters in the lithium precipitation process in real time, including temperature, concentration, pH value, and flow rate; the model building module constructs a dynamic mathematical model of the process based on the collected historical data; the process optimization module calculates the optimal process parameter combination according to the dynamic mathematical model; the intelligent analysis and decision-making module optimizes the process parameters through big data analysis and machine learning algorithms; the automation control module sends the optimized process parameters to the actuator to realize automatic adjustment of the process parameters; the feedback correction module corrects the model deviation in real time; the visualization and remote monitoring module is used to realize real-time monitoring and remote operation of the production process; the multi-level interlocking safety protection mechanism is used to automatically cut off or adjust the process parameters under abnormal circumstances; the online monitoring system is used to monitor the process parameters and product quality in real time; the system management module is used to store historical data, analyze production trends, and optimize production plans.

[0027] Furthermore, the data acquisition and monitoring module consists of multiple sensor nodes with anti-interference designs and a data encryption transmission unit. These sensor nodes are not only able to maintain stable operation in extreme high temperature and high humidity environments, but are also equipped with advanced self-calibration functions, which can monitor and adjust sensor performance in real time to ensure the accuracy of collected data. At the same time, the data encryption transmission unit uses a highly efficient data encryption algorithm to encrypt the data collected by the sensor nodes to ensure the security of the data during transmission. In addition, the unit also adheres to strict security communication protocols to ensure the secure transmission of data in complex network environments. Ultimately, this encrypted data is stably and reliably transmitted to the central control system for processing and analysis, thereby expanding the data processing capabilities and application scope of the entire monitoring system.

[0028] Furthermore, the intelligent analysis and decision-making module is the brain of the entire system, its efficient operation ensuring the intelligent and automated production process. This module integrates a data preprocessing unit, an advanced machine learning model, and a flexible adaptive adjustment unit. The data preprocessing unit plays a crucial role, initially processing the large amount of data transmitted from the data acquisition and monitoring module. This includes, but is not limited to, data cleaning, removing outliers and noise, and normalizing the data to ensure that the data quality input to subsequent processing meets the requirements for accurate analysis and decision-making. The machine learning model is the core of the module, applying advanced algorithms based on a large amount of historical and real-time data to optimize process parameters. This model is able to continuously improve its prediction and decision-making algorithms through self-learning and adaptation, thereby achieving refined management of the production process and improving production efficiency and product quality. The adaptive adjustment unit is the intelligent regulator of the intelligent analysis and decision-making module, dynamically adjusting optimization strategies based on raw material characteristics, real-time changes in the production environment, and other relevant factors. This adaptive capability enables the system to respond quickly to changing operating conditions, ensuring the continuity and stability of the production process while maximizing the optimization potential of the machine learning model to achieve optimal configuration of process parameters.

[0029] Furthermore, the automated control module is a key component for achieving precise control of the entire system. It consists of two main components: the actuator and the feedback control unit. The actuator possesses high-precision control capabilities, enabling precise adjustment of key process parameters of the lithium precipitation reactor 21, including temperature, stirring speed, and feeding rate, according to instructions from the central control system. Precise control of these parameters is crucial for ensuring the uniformity of the lithium precipitation reaction and the stability of product quality. The actuator, through its high-response drive system, ensures timely and accurate adjustment. The feedback control unit, working in conjunction with the actuator, serves as the intelligent adjustment hub of the automated control module. It collects real-time sensor data from various internal and external sensors of the reactor, including key parameters such as temperature, pressure, and liquid level, analyzes this data in real time, and compares it with preset process parameters. If a deviation between the actual operating state and the preset parameters is detected, the feedback control unit immediately adjusts the operating state, sending a correction signal to the actuator to dynamically adjust its operating state to eliminate the deviation and ensure that the lithium precipitation reaction process always operates under optimal operating conditions. This closed-loop control mechanism greatly improves system control efficiency and product quality consistency.

[0030] Furthermore, the visualization and remote monitoring module, serving as the system's human-machine interface, greatly improves the user's monitoring and management efficiency of the production process. This module consists of two key components: an intelligent central control screen and a mobile terminal, which together provide users with a comprehensive and intuitive production monitoring platform. The intelligent central control screen has high resolution and excellent display effects. Operators can intuitively grasp the real-time dynamics of the entire production line in front of the central control screen and make decisions quickly. The mobile terminal provides flexible remote monitoring and operation functions. Users can log in to the system anytime, anywhere through a smartphone or tablet to view production data and equipment status. The mobile terminal application is designed with ease of use and security in mind. Through identity authentication and permission management systems, it ensures that only authorized users can access the system and perform remote operations.

[0031] An intelligent optimization control device for the production process of battery-grade lithium carbonate precipitation includes an extraction device 2, a lithium precipitation reactor 21, a filtering device 22, a drying device 23, a central controller 1, an intelligent inspection robot 11, and an exhaust gas treatment device 3. The extraction device 2 is used for extracting and separating lithium salts; the lithium precipitation reactor 21 is used for realizing the precipitation of lithium carbonate under optimized process conditions; the filtering device 22 is used for separating the precipitate from the mother liquor; the drying device 23 is used for drying the filter cake to a finished product; the central controller 1 receives the optimization parameters and controls the operation of each device; the intelligent inspection robot 11 is used to replace manual inspection; and the exhaust gas treatment device 3 is used to treat harmful gases generated during the production process.

[0032] Furthermore, the lithium precipitation reactor 21 is equipped with a high-precision temperature control system and a stirring device. The high-precision temperature control system adopts advanced control algorithms and can accurately control the temperature of the reactor; the stirring device can automatically adjust the stirring speed according to the optimized process parameters to improve the reaction efficiency. This process can achieve the best stirring effect in different production stages and conditions, which not only avoids energy waste caused by excessive stirring, but also ensures the maximization of reaction efficiency.

[0033] Furthermore, the intelligent control unit can dynamically adjust the operating parameters during the evaporation and crystallization process based on real-time data. The intelligent control unit adopts model predictive control MPC and fuzzy-PID composite control to achieve full closed-loop optimization of the evaporation and crystallization processes, significantly improving the product consistency and production efficiency of battery-grade lithium carbonate.

[0034] Furthermore, the multi-sensor fusion system includes temperature sensors, humidity sensors, and gas concentration sensors. The wireless communication module supports high-speed data transmission, ensuring that real-time device status data collected can be transmitted to the central control system in a timely manner. Wireless communication technology utilizes efficient coding and modulation schemes, as well as strong anti-interference capabilities, to maintain reliable data transmission in complex industrial environments. This instantaneous data transmission enables the central control system to monitor the production process in real time and respond promptly to potential anomalies, thereby optimizing production processes and improving production efficiency. It also provides data support for system fault diagnosis and maintenance.

[0035] Furthermore, the central controller 1 employs a multi-level control strategy, supporting switching between manual, semi-automatic, and fully automatic modes. This multi-level control strategy automatically adjusts the control strategy based on production needs. Manual mode allows operators to directly intervene in the control process, making it suitable for system debugging or handling special situations. Semi-automatic mode automatically executes portions of the production process based on preset parameters and conditions, while retaining the option for manual intervention. In fully automatic mode, the central controller 1 fully automatically controls the entire production process without manual intervention. The core advantage of this multi-level control strategy lies in its adaptability and intelligence. Based on the production line's real-time data, historical data, and production plan, the central controller 1 automatically adjusts the control strategy to accommodate varying production needs and environmental changes. When differences between batches of raw materials are detected, the central controller 1 automatically adjusts process parameters to ensure consistent product quality. When the production environment changes, the central controller 1 rapidly adjusts the control logic to maintain the stability and safety of the production process.

[0036] Working principle: By integrating the data acquisition and monitoring module, the model building module and the process optimization module, automatic adjustment and optimization of parameters are achieved. The data acquisition and monitoring module is used to collect key parameters such as temperature, concentration, pH value in real time. The model building module builds a dynamic mathematical model based on these data. The process optimization module then calculates the optimal process parameter combination according to the model, thereby reducing manual intervention, shortening the adjustment process, and achieving reduced energy consumption and improved recovery rate by optimizing parameters.

[0037] The data acquisition and monitoring module incorporates a data encryption transmission unit. This unit uses a highly efficient data encryption algorithm to encrypt collected data and transmit it via a strict secure communication protocol, ensuring data security during transmission. This encryption mechanism prevents data leakage and tampering in complex network environments, safeguarding production data security.

[0038] The central controller 1 adopts a multi-level control strategy and integrates a feedback correction module and an adaptive adjustment unit. It can monitor the real-time data of the production line in real time and automatically adjust the control strategy to adapt to different production needs and environmental changes. The multi-level interlocking safety protection mechanism can automatically cut off or adjust process parameters under abnormal circumstances to ensure the continuity and stability of the production process. This adaptive control strategy improves the flexibility and robustness of the system.

[0039] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

Claims

1. Intelligent optimization control system for battery-grade lithium carbonate precipitation production process, characterized by: It includes a data acquisition and monitoring module, a model building module, a process optimization module, an intelligent analysis and decision-making module, an automation control module, a feedback correction module, a visualization and remote monitoring module, a multi-level interlocking safety protection mechanism, an online monitoring system, and a system management module. The data acquisition and monitoring module is used to collect key parameters in the lithium precipitation process in real time, including temperature, concentration, pH value, and flow rate; the model building module constructs a dynamic mathematical model of the process based on the collected historical data; the process optimization module calculates the optimal process parameter combination according to the dynamic mathematical model; the intelligent analysis and decision-making module optimizes the process parameters through big data analysis and machine learning algorithms; the automation control module sends the optimized process parameters to the actuator to realize automatic adjustment of the process parameters; the feedback correction module corrects the model deviation in real time; the visualization and remote monitoring module is used to realize real-time monitoring and remote operation of the production process; the multi-level interlocking safety protection mechanism is used to automatically cut off or adjust the process parameters under abnormal circumstances; the online monitoring system is used to monitor the process parameters and product quality in real time; the system management module is used to store historical data, analyze production trends, and optimize production plans.

2. The intelligent optimization control system for the battery-grade lithium carbonate precipitation production process according to claim 1, characterized in that: The data acquisition and monitoring module includes multiple sensor nodes and a data encryption transmission unit. The sensor nodes have an anti-interference design, can operate stably in high temperature and high humidity environments, and ensure data accuracy through self-calibration function; the data encryption transmission unit is used to encrypt the collected data and transmit it to the central control system through a secure communication protocol.

3. The intelligent optimization control system and device for the battery-grade lithium carbonate precipitation production process according to claim 1, characterized in that: The intelligent analysis and decision-making module includes a data preprocessing unit, a machine learning model and an adaptive adjustment unit. The data preprocessing unit is used to clean and normalize the collected data; the machine learning model is used to optimize process parameters based on historical data and real-time data; and the adaptive adjustment unit is used to dynamically adjust the optimization strategy based on raw material characteristics and production environment.

4. The intelligent optimization control system for the battery-grade lithium carbonate precipitation production process according to claim 1, characterized in that: The automatic control module comprises an actuator and a feedback control unit, wherein the actuator is used to adjust the temperature, stirring speed and feeding speed of the lithium precipitation reactor (21); and the feedback control unit is used to dynamically adjust the working state of the actuator according to real-time data.

5. The intelligent optimization control system for the battery-grade lithium carbonate precipitation production process according to claim 1, characterized in that: The visualization and remote monitoring module includes an intelligent central control screen and a mobile terminal. The intelligent central control screen is used to display production data and equipment status in real time; the mobile terminal is used for remote monitoring and operation, and ensures system security through identity authentication and authority management.

6. Intelligent optimization control device for battery-grade lithium carbonate precipitation production process, characterized in that: The invention comprises an extraction device (2), a lithium precipitation reactor (21), a filtering device (22), a drying device (23), a central controller (1), an intelligent inspection robot (11), and an exhaust gas treatment device (3). The extraction device (2) is used for extracting and separating lithium salts; the lithium precipitation reactor (21) is used for realizing the precipitation of lithium carbonate under optimized process conditions; the filtering device (22) is used for separating the precipitate from the mother liquor; the drying device (23) is used for drying the filter cake into a finished product; the central controller (1) receives the optimized parameters and controls the operation of each device; the intelligent inspection robot (11) is used for replacing manual inspection; and the exhaust gas treatment device (3) is used for treating harmful gases generated during the production process.

7. The intelligent optimization control device for the production process of battery-grade lithium carbonate precipitation according to claim 6, characterized in that: The lithium precipitation reactor (21) is equipped with a high-precision temperature control system and a stirring device. The high-precision temperature control system adopts an advanced control algorithm and can accurately control the temperature of the reactor; the stirring device can automatically adjust the stirring speed according to the optimized process parameters to improve the reaction efficiency.

8. The intelligent optimization control device for the production process of battery-grade lithium carbonate precipitation according to claim 6, characterized in that: The intelligent control unit can dynamically adjust the operating parameters during the evaporation and crystallization process according to real-time data.

9. The intelligent optimization control device for the production process of battery-grade lithium carbonate precipitation according to claim 6, characterized in that: The multi-sensor fusion system includes a temperature sensor, a humidity sensor, and a gas concentration sensor; the wireless communication module supports high-speed data transmission, ensuring that the device status data collected in real time can be transmitted to the central control system in a timely manner.

10. The intelligent optimization control device for the production process of battery-grade lithium carbonate precipitation according to claim 6, characterized in that: The central controller (1) adopts a multi-level control strategy and supports manual, semi-automatic and fully automatic mode switching. The multi-level control strategy can automatically adjust the control strategy according to production requirements.

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