A control method of a lithium ion battery ternary cathode material precursor production system

Abstract

The present application relates to the technical field of lithium ion battery material production, in particular to a control method of a lithium ion battery ternary positive electrode material precursor production system, comprising the following steps: S1: modeling fluid behavior in the reactor by using simulation software; S2: adjusting the feeding rate of the feeding unit in real time to keep the ion concentration in each partition consistent; S3: dynamically adjusting the stirring speed and mode in the reactor; S4: adjusting the feeding rate in S2 and the stirring parameters in S3; S5: performing crystal nucleus homogenization induction; S6: gradually separating out the precursor material particles; S7: drying the separated precursor material particles. Through multi-dimensional dynamic regulation and precise distribution control, the present application significantly improves the ion uniformity and structural stability of the ternary positive electrode material precursor, providing high-quality material basis for high-performance lithium ion batteries.

Description

Technical Field

[0001] This invention relates to the field of lithium-ion battery material production technology, and in particular to a control method for a lithium-ion battery ternary cathode material precursor production system. Background Technology

[0002] With the rapid development of the new energy industry, lithium-ion batteries, as high-energy-density and high-efficiency energy storage devices, are widely used in electric vehicles, energy storage power stations, and portable electronic products. Ternary cathode materials (such as nickel-cobalt-manganese or nickel-cobalt-aluminum composite oxides) have become the mainstream choice for lithium-ion battery cathode materials due to their high specific capacity, superior stability, and long cycle life. In the production of ternary cathode materials, the preparation of precursor materials is crucial, as their ionic composition, particle uniformity, and structural stability directly affect the overall performance of lithium-ion batteries. However, traditional ternary cathode material precursor production methods struggle to achieve precise control over key parameters such as concentration, distribution, and particle size in complex processes, making it difficult to guarantee the quality and consistency of materials and affecting the performance stability and lifespan of battery products.

[0003] In existing technologies, the preparation of precursor materials faces challenges due to the interaction of multiple factors such as reaction environment, fluid dynamics, and concentration distribution. These problems include uneven ion concentration, difficulty in controlling crystal morphology, inconsistent particle size distribution, and agglomeration during drying. In particular, traditional production systems struggle to effectively control the entire production process using a single regulatory method, resulting in low uniformity and purity of the precursor materials, and making it difficult to achieve ideal ion distribution and particle morphology. Therefore, a novel precursor production control method is urgently needed to address these issues. Summary of the Invention

[0004] To achieve the above objectives, the present invention provides a control method for a lithium-ion battery ternary cathode material precursor production system.

[0005] A control method for a lithium-ion battery ternary cathode material precursor production system includes the following steps:

[0006] S1: Based on the predetermined ternary cathode material ratio, the fluid behavior in the reactor is modeled using simulation software, and the reactor is divided into several zones to obtain the fluid flow characteristics and ion concentration distribution in each zone.

[0007] S2: Based on the partitioning of S1, a solution containing nickel, cobalt, manganese or aluminum is injected into each partition of the reactor from multiple inlets through a multi-point feeding unit, and the feeding rate of the feeding unit is adjusted in real time to maintain the same ion concentration in each partition.

[0008] S3: Based on the partitioned fluid characteristics modeled in S1, the stirring speed and mode in the reactor are dynamically adjusted by the intelligent stirring unit to ensure that the solution in each partition of the reactor is fully mixed and to reduce the difference in ion concentration.

[0009] S4: Arrange multiple ion-selective electrodes in each zone to monitor the concentration of nickel, cobalt, manganese or aluminum ions, and feed the monitored concentration data back to the closed-loop control unit. Adjust the feeding rate in S2 and the stirring parameters in S3 to balance the ion concentration in each zone.

[0010] S5: In the solution environment after the closed-loop control of S4, the uniform generation of crystal nuclei is achieved through the precise injection of crystal nuclei inducing agents; then, the ultrasonic vibration unit is used to assist in the uniform distribution of crystal nuclei, providing consistent initial conditions for the subsequent crystallization process;

[0011] S6: The slurry after the reaction is completed is introduced into a multi-stage slow-release solid-liquid separation unit to gradually separate the precursor material particles, and the liquid flow rate is controlled to obtain a uniform solid sedimentation effect, ensuring the separation integrity of the obtained precursor.

[0012] S7: The separated precursor material particles are dried, and the particle distribution is controlled by homogenizing airflow to maintain the uniformity of ion concentration in the dried precursor particles, ultimately forming a uniform lithium-ion battery ternary cathode material precursor product.

[0013] Optionally, S1 specifically includes:

[0014] S11: Based on the composition requirements of the target ternary cathode material, set the molar ratio and concentration range of nickel, cobalt, manganese or aluminum, and determine the parameters in the reaction process, including solution flow rate, stirring speed and reaction temperature;

[0015] S12: Input the material ratio parameters and process parameters set in S11 into the fluid simulation software, and generate a fluid dynamics model in the reactor through computational fluid dynamics. The fluid dynamics model can accurately describe the flow velocity, pressure and shear rate in different regions, providing a data basis for partitioning.

[0016] S13: Based on the fluid dynamics model of S12, the reactor is divided into several preliminary zones. Each zone is set as a high-velocity zone, a medium-velocity zone, and a low-velocity zone according to the difference in flow rate and shear rate, and the initial boundary of each zone is determined.

[0017] S14: Import the preliminary partitioning in S13 into the simulation software for multiple simulations, adjust the partition boundaries to a stable state, and keep the fluid flow state and ion concentration in each partition consistent.

[0018] S15: Based on the simulation results of S14, numerical calculations are performed on the ion concentration distribution in each partition to generate the corresponding concentration distribution data.

[0019] Optionally, S15 specifically includes:

[0020] S151: In the simulation software, based on the partition model optimized in S14, set up ion concentration monitoring points for each partition and define the coordinates and position of each monitoring point;

[0021] S152: Based on the data acquisition in S151, set the time step and calculate the rate of change of ion concentration over time, targeting metal ions such as nickel, cobalt, manganese or aluminum.

[0022] S153: Based on the concentration change rate calculated in S152, the ion concentration of each partition is updated and corrected step by step using a numerical iteration method until the ion concentration of each partition converges to a stable state.

[0023] S154: After the ion concentration converges in S153, the final concentration values ​​of each monitoring point are numerically integrated to generate concentration distribution data for each zone, and this data is stored in tabular form.

[0024] Optionally, S2 specifically includes:

[0025] S21: Based on the partition locations defined in S1, install an independent feed port at the inlet of each partition to ensure that the solution can be accurately delivered to the designated partition. Each feed port is connected to its respective flow control valve to ensure that the solution injection location of each partition corresponds to the concentration control requirements of the partition.

[0026] S22: Install ion concentration sensors and flow sensors on the fluid pipelines of each zone. The ion concentration sensors acquire real-time concentration data of nickel, cobalt, manganese or aluminum ions, and the flow sensors monitor the flow rate of each feed port.

[0027] S23: Based on the ion concentration data of each zone collected in S22 and the preset target concentration value, the feed rate adjustment parameter of each zone is calculated by the proportional integral derivative control algorithm to determine the real-time adjustment value of feed increment or decrement.

[0028] S24: Using the feed rate adjustment parameters calculated in S23, the feed rate of each feed port is adjusted by regulating the flow control valve to ensure that the ion concentration in each zone gradually approaches the target concentration.

[0029] Optionally, S3 specifically includes:

[0030] S31: Based on the fluid dynamics model established in S1, set the initial stirring parameters for the flow characteristics of each zone, including stirring speed and stirring blade angle;

[0031] S32: Based on the concentration sensor installed in S22, it collects the concentration data of nickel, cobalt, manganese or aluminum ions in real time, obtains the current ion concentration of each zone, and uses the data to calculate the concentration difference between each zone.

[0032] S33: Based on the concentration difference value obtained in S32, the stirring speed adjustment value and blade angle adjustment value of each zone are calculated through feedback control algorithm to reduce the concentration difference within the zone;

[0033] S34: Using the stirring speed and blade angle adjustment parameters calculated by S33, the stirring speed and angle of the stirrer are adjusted in real time by the intelligent stirring unit to achieve the optimal stirring state of each zone.

[0034] Optionally, S4 specifically includes:

[0035] S41: Ion-selective electrodes are arranged at predetermined positions within each zone, each electrode being specifically designed to detect the corresponding concentration of nickel, cobalt, manganese, or aluminum ions;

[0036] S42: Real-time concentration data is acquired through the ion-selective electrodes within each zone to form the instantaneous ion concentration C for each electrode. i,j C i,j This represents the target ion concentration at the j-th electrode within the i-th partition;

[0037] S43: Compare the electrode data collected in S42 with the preset target concentration, and calculate the concentration deviation ΔC for each zone. i ;

[0038] S44: The concentration deviation ΔC calculated in S43 i The data is sent to the closed-loop control unit, and the deviation data is analyzed to generate feeding adjustment parameters and stirring adjustment parameters.

[0039] S45: Based on the adjustment parameters in S44, send instructions to the multi-point feeding unit in S2 and the intelligent stirring unit in S3 respectively, to dynamically adjust the feeding rate, stirring speed and blade angle of each zone, so that the ion concentration of each zone gradually approaches the target value.

[0040] Optionally, S44 specifically includes:

[0041] S441: Receive the concentration deviation ΔC of each zone in the closed-loop control unit. iThe data is collected, and the concentration deviation of each partition is analyzed to determine the magnitude and direction of the deviation. By comparing the deviation data with a preset adjustment threshold T, partitions requiring incremental or decremental adjustment are classified. The comparison formula is as follows:

[0042]

[0043] Among them, D i Indicates the adjustment direction of the i-th partition; ΔC i Let be the concentration deviation of the i-th partition; T is the preset concentration deviation threshold.

[0044] S442: Based on the deviation analysis results obtained in S441, calculate the final feeding adjustment rate for each zone, which is used for optimization based on the preliminary adjustment parameters in S23; when D i When D = 1, increase the feeding rate; when D i When D = -1, reduce the feeding rate; when D i When Q = 0, maintain the current feeding rate; the formula for the final feeding adjustment rate is: Q i,final =Q i,adjust +K q ·ΔC i ·D i , where Q i,final Q represents the final feed adjustment rate for the i-th partition; i,adjust The initial feed rate adjusted in S23; K q This is a feeding adjustment coefficient, used to further optimize the feeding rate based on the deviation.

[0045] S443: For stirring speed adjustment, based on concentration deviation ΔC i Calculate the final adjustment value ω of the stirring speed for each zone. i,final According to D i The direction of the stirring speed in each zone is adjusted by increasing or decreasing the stirring speed using the formula: ω i,final =ω i +K ω ·ΔC i ·D i , where ω i,final ω is the final adjustment value for the stirring speed of the i-th partition; i K represents the current stirring speed. ω This is the stirring speed adjustment coefficient;

[0046] S444: Based on concentration deviation ΔC i and adjust direction D i Calculate the final adjustment value θ of the agitator blade angle. i,final This ensures a more uniform blending effect in each partition; the formula is: θ i,final =θi +K θ ·ΔC i ·D i , where θ i,final θ represents the final adjustment value of the impeller angle for the i-th partition; i K represents the current blade angle. θ This is the blade angle adjustment coefficient.

[0047] Optionally, S5 specifically includes:

[0048] S51: Calculate the injection rate of the nucleation inducing agent based on the target ion concentration in the solution and the volume within the reactor to ensure that the concentration of the inducing agent in the reactor reaches the preset induction concentration to induce the initial formation of crystal nuclei; the formula is: Among them, R induce V represents the injection rate of the nucleation inducer. reactor C is the total volume of the reactor; induce The target concentration of the inducer; t induce The time period for inducing agent injection;

[0049] S52: During the injection process in S51, a concentration sensor is used to monitor the concentration of the nucleation inducer in the reactor in real time to ensure that it is maintained within the set range. If a deviation is detected, the injection rate R will be automatically adjusted. induce To achieve precise injection;

[0050] S53: After the inducer concentration reaches the target concentration, the control system sets the inducer injection stop time point, and stops the inducer injection at this time point, so that the metal ions in the reactor can form crystal nuclei under the action of the inducer.

[0051] S54: After the initial formation of crystal nuclei, start the ultrasonic vibration unit and set the ultrasonic frequency and power;

[0052] S55: After the ultrasonic parameters are set in S54, the ultrasonic vibration unit is used to apply uniform vibration to the solution inside the reactor, so that the crystal nuclei are evenly distributed in the solution under the action of ultrasonic vibration, avoiding local concentration.

[0053] Optionally, S6 specifically includes:

[0054] S61: The slurry after the reaction is completed is introduced from the reactor into the first stage separator of the multi-stage slow-release solid-liquid separation unit, and the initial flow rate V0 is set to ensure that the particles begin to settle in the first stage separator.

[0055] S62: Based on the multi-stage design of the solid-liquid separation unit, the flow rate is successively reduced in each stage separator; let the flow rate of the nth stage be V. nThen the flow velocity in each stage of the separator is reduced proportionally to achieve stepwise particle settling; the formula is: V n+1 =V n ×(1-R), where V n+1 V is the flow velocity of the (n+)th stage separator; n R represents the flow velocity of the nth stage separator; R is the flow velocity reduction ratio.

[0056] S63: Install a flow rate sensor at the liquid outlet of each stage separator to monitor the current liquid flow rate V in real time. n,real And calculate the value V. n When a difference is detected, the flow rate difference is adjusted by the feedback control unit to ensure that the actual flow rate is always maintained within the allowable range of the target flow rate.

[0057] S64: After multi-stage slow-release separation, the sedimented precursor particles are finally collected at the bottom of the last stage separator.

[0058] Optionally, S7 specifically includes:

[0059] S71: Before the precursor particles separated from the multi-stage slow-release solid-liquid separation unit are sent into the drying device, the particles are pre-distributed in the feeding area by a vibrating screen to eliminate particle agglomeration and make the particles spread evenly in the drying equipment.

[0060] S72: Based on the particle size distribution, density, and target drying rate of the precursor particles, a multi-point homogenizing airflow nozzle is set in the drying device, including setting the airflow velocity, temperature, and humidity parameters.

[0061] S73: The airflow distribution and velocity of each nozzle are monitored in real time by the airflow sensor installed in the drying device. If uneven airflow is detected, the airflow of the nozzle is automatically adjusted according to the sensor feedback to eliminate local airflow fluctuations.

[0062] S74: During the drying process, optical or laser particle distribution monitoring equipment is used to monitor the particle distribution status in the drying device in real time to ensure that the uniformity of particle distribution in the drying area meets the preset requirements; if the particle distribution deviates from the set state, fine adjustments are made by homogenizing the airflow.

[0063] S75: During the drying process, the temperature gradient inside the drying device is monitored by thermocouple temperature sensors to ensure uniform temperature distribution. The temperature inside the device is controlled within a predetermined range according to the requirements of particle moisture content and drying rate.

[0064] S76: After drying is complete, the uniformly dried precursor particles are collected from the drying device for final packaging.

[0065] The beneficial effects of this invention are:

[0066] This invention achieves precise control of key parameters in the production process of ternary cathode material precursors through multi-point dynamic feeding control, intelligent stirring adjustment, closed-loop ion concentration monitoring, and ultrasonic vibration homogenization. In each stage, such as reaction, separation, and drying, the ion concentration gradient can be effectively reduced by real-time concentration monitoring and feedback control, ensuring uniform ion distribution in each zone. At the same time, by dynamically adjusting the stirring rate, feeding rate, and inducing agent injection, the uniform generation and distribution of crystal nuclei are further guaranteed, providing consistent basic conditions for subsequent crystallization.

[0067] This invention reduces particle agglomeration and uneven sedimentation by introducing multi-stage flow rate control and homogenized airflow drying technology during solid-liquid separation and drying processes. This ensures that the precursor particles maintain a highly uniform ion distribution and stable structure after drying. Ultimately, by utilizing precise parameter regulation and distribution control, the quality consistency and purity of the ternary cathode material precursor are significantly improved, providing a reliable material basis for the manufacture of high-performance lithium-ion batteries, extending battery life, and enhancing their overall performance. Attached Figure Description

[0068] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only for this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0069] Figure 1 This is a schematic diagram of the control method of the precursor production system according to an embodiment of the present invention;

[0070] Figure 2 This is a schematic diagram of the process for modeling fluid behavior within a reactor according to an embodiment of the present invention. Detailed Implementation

[0071] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. It should also be noted that, to make the embodiments more comprehensive, the following embodiments are the best and preferred embodiments, and those skilled in the art can use other alternative methods to implement some well-known technologies; moreover, the accompanying drawings are only for more specific description of the embodiments and are not intended to specifically limit the present invention.

[0072] It should be noted that the use of terms such as "an embodiment," "an embodiment," "an exemplary embodiment," and "some embodiments" in the specification indicates that the described embodiment may include a specific feature, structure, or characteristic, but not every embodiment necessarily includes that specific feature, structure, or characteristic. Furthermore, when a specific feature, structure, or characteristic is described in connection with an embodiment, implementing such a feature, structure, or characteristic in conjunction with other embodiments (whether explicitly described or not) should be within the knowledge of those skilled in the art.

[0073] Generally, terms can be understood at least partly from their use in context. For example, depending at least partly on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in a singular sense, or a combination of features, structures, or characteristics in a plural sense. Additionally, the term "based on" can be understood not necessarily to convey an exclusive set of factors, but rather, alternatively, depending at least partly on the context, to allow for the presence of other factors that are not necessarily explicitly described.

[0074] like Figures 1-2 As shown, a control method for a lithium-ion battery ternary cathode material precursor production system includes the following steps:

[0075] S1: Based on the predetermined ternary cathode material ratio, the fluid behavior in the reactor is modeled using simulation software, and the reactor is divided into several zones to obtain the fluid flow characteristics and ion concentration distribution in each zone.

[0076] S2: Based on the partitioning of S1, a solution containing nickel, cobalt, manganese or aluminum is injected into each partition of the reactor from multiple inlets through a multi-point feeding unit, and the feeding rate of the feeding unit is adjusted in real time to maintain the same ion concentration in each partition.

[0077] S3: Based on the partitioned fluid characteristics modeled in S1, the stirring speed and mode in the reactor are dynamically adjusted by the intelligent stirring unit to ensure that the solution in each partition of the reactor is fully mixed and to reduce the difference in ion concentration.

[0078] S4: Arrange multiple ion-selective electrodes in each zone to monitor the concentration of nickel, cobalt, manganese or aluminum ions, and feed the monitored concentration data back to the closed-loop control unit. Adjust the feeding rate in S2 and the stirring parameters in S3 to balance the ion concentration in each zone.

[0079] S5: In the solution environment after the closed-loop control of S4, the uniform generation of crystal nuclei is achieved through the precise injection of crystal nuclei inducing agents; then, the ultrasonic vibration unit is used to assist in the uniform distribution of crystal nuclei, providing consistent initial conditions for the subsequent crystallization process;

[0080] S6: The slurry after the reaction is completed is introduced into a multi-stage slow-release solid-liquid separation unit to gradually separate the precursor material particles, and the liquid flow rate is controlled to obtain a uniform solid sedimentation effect, ensuring the separation integrity of the obtained precursor.

[0081] S7: The separated precursor material particles are dried, and the particle distribution is controlled by homogenizing airflow to maintain the uniformity of ion concentration in the dried precursor particles, ultimately forming a uniform lithium-ion battery ternary cathode material precursor product.

[0082] S1 specifically includes:

[0083] S11: Based on the composition requirements of the target ternary cathode material, set the molar ratio and concentration range of nickel, cobalt, manganese or aluminum, and determine the parameters in the reaction process, including solution flow rate, stirring speed and reaction temperature;

[0084] S12: Input the material ratio parameters and process parameters set in S11 into the fluid simulation software, and generate a fluid dynamics model in the reactor through computational fluid dynamics (CFD) method. The fluid dynamics model can accurately describe the flow velocity, pressure and shear rate in different regions, providing a data basis for partitioning.

[0085] S13: Based on the fluid dynamics model of S12, the reactor is divided into several preliminary zones. Each zone is set as a high-velocity zone, a medium-velocity zone, and a low-velocity zone according to the difference in flow rate and shear rate, and the initial boundary of each zone is determined.

[0086] S14: Import the preliminary partitions in S13 into the simulation software for multiple simulations, adjust the partition boundaries to a stable state, until the fluid flow state and ion concentration in each partition are consistent. In this step, the boundaries of each partition are refined based on the simulation results to ensure that the ion concentration gradient in the reactor is minimized.

[0087] S15: Based on the simulation results of S14, numerical calculations are performed on the ion concentration distribution in each zone to generate corresponding concentration distribution data, which is then used as the basic data for the multi-point dynamic feeding unit to achieve uniform feeding in each zone.

[0088] The calculation of ion concentration distribution in S15 specifically includes:

[0089] S151: In the simulation software, based on the optimized partitioning model of S14, ion concentration monitoring points are set for each partition, and the coordinates and location of each monitoring point are defined to ensure coverage of key locations in each partition; the formula is: P i =(x i ,y i ,z i ), where P i x represents the location coordinates of the i-th monitoring point;i ,y i ,z i These represent the horizontal, vertical, and height coordinates of the i-th monitoring point in three-dimensional space, respectively, which are used to determine the specific location of the monitoring point within the reactor;

[0090] S152: Based on the data acquisition in S151, set the time step Δt, and calculate the ion concentration C using metal ions nickel, cobalt, manganese, or aluminum as the target. i The rate of change over time; the formula is: in, C represents the rate of change of ion concentration at the i-th monitoring point over time; i,t and C i,t+Δt Let represent the ion concentrations at the i-th monitoring point at time t and t+Δt, respectively, where Δt is the time interval;

[0091] S153: Based on the concentration change rate calculated in S152, the ion concentration of each partition is gradually updated and corrected using a numerical iteration method until the ion concentration of each partition converges to a stable state; the update formula is: Among them, C i,n+1 C represents the ion concentration at the i-th monitoring point in the (n+1)-th iteration. i,n The ion concentration at the nth iteration. Δt represents the rate of change of ion concentration calculated in S152, where Δt is the time interval.

[0092] S154: After the ion concentration convergence in S153, the final concentration values ​​of each monitoring point are numerically integrated to generate concentration distribution data for each zone. This data is then stored in tabular form for use in setting the feeding rate of the multi-point dynamic feeding system in subsequent S2. The integration formula is: Among them, C avg C represents the average ion concentration within the partition. i,final Let N be the final ion concentration at the i-th monitoring point, and N be the total number of monitoring points. Through the above steps, the ion concentration distribution of each zone can be accurately calculated, forming a numerical model of the ion concentration within the zone, providing data support for subsequent feed control, and effectively ensuring the concentration balance of each zone.

[0093] S2 specifically includes:

[0094] S21: Based on the partition locations defined in S1, install an independent feed port at the inlet of each partition to ensure that the solution can be accurately delivered to the designated partition. Each feed port is connected to its respective flow control valve to ensure that the solution injection location of each partition corresponds to the concentration control requirements of the partition.

[0095] S22: Install ion concentration sensors and flow sensors on the fluid pipelines of each zone. The ion concentration sensors acquire real-time concentration data of nickel, cobalt, manganese or aluminum ions, and the flow sensors monitor the flow rate of each feed port.

[0096] S23: Based on the ion concentration data of each zone collected in S22 and the preset target concentration value, the feed rate adjustment parameter for each zone is calculated using a proportional-integral-derivative (PID) control algorithm to determine the real-time adjustment value for feed increment or decrement; the PID control algorithm formula is: Among them, Q i,adjust K is the feed rate adjustment for the i-th partition; p K is the proportional control coefficient used to adjust the current error. i K is the integral control coefficient used to adjust for error accumulation. d e is the differential control coefficient used to adjust the rate of change of error. i Let be the concentration deviation value of the i-th partition, i.e., the difference between the current concentration and the target concentration; ∫e i dt is the error e i The integral is used to calculate the impact of error accumulation on the control. For error e i The derivative of the error, i.e., the rate of change of the error with time t, is used to calculate the impact of error changes on the control.

[0097] S24: Using the feed rate adjustment parameters calculated in S23, the feed rate of each feed port is adjusted by regulating the flow control valve, so that the solution injection rate of each zone meets the real-time requirements and ensures that the ion concentration of each zone gradually approaches the target concentration. Through the above steps, dynamic adjustment of the feed to each zone is achieved, ensuring that the ion concentration in each zone remains consistent, so as to meet the requirements of solution uniformity in subsequent steps.

[0098] S3 specifically includes:

[0099] S31: Based on the fluid dynamics model established in S1, set the initial stirring parameters for the flow characteristics of each zone, including stirring speed and stirring blade angle, to ensure that the initial mixing effect meets the requirements of the zone flow characteristics.

[0100] S32: Based on the concentration sensor installed in S22, it collects the concentration data of nickel, cobalt, manganese or aluminum ions in real time, obtains the current ion concentration of each zone, and uses the data to calculate the concentration difference value between each zone to determine the concentration deviation between different zones.

[0101] S33: Based on the concentration difference value obtained in S32, the stirring speed adjustment value and impeller angle adjustment value of each zone are calculated through a feedback control algorithm to reduce the concentration difference within the zone and achieve a more uniform ion distribution; the formula for the adjustment value is: ω i =ω0+K c ·ΔC i ;θ i =θ0+K a ·ΔC i , where ω i ωi is the stirring speed of the i-th partition; ω0 is the initial stirring speed; K c ΔC is the rotation speed adjustment coefficient, used to adjust the rotation speed according to concentration differences. i Let θ represent the concentration difference in the i-th partition, i.e., the deviation between the ion concentration in that partition and the target concentration; i Let θ be the angle of the impeller blade in the i-th partition; θ0 be the initial impeller angle; K a This is the angle adjustment coefficient, used to adjust the blade angle;

[0102] S34: Using the stirring speed and blade angle adjustment parameters calculated in S33, the intelligent stirring unit adjusts the stirring speed and angle of the stirrer in real time to optimize the stirring state of each zone, thereby achieving uniform mixing of the solution. Through the above steps, the intelligent stirring unit can adjust the stirring state in real time according to the concentration sensor data, effectively reducing the difference in ion concentration within the zone and ensuring the uniformity of the solution.

[0103] S4 specifically includes:

[0104] S41: Ion-selective electrodes are arranged at predetermined locations within each zone. Each electrode is specifically designed to detect the concentration of corresponding nickel, cobalt, manganese, or aluminum ions, ensuring specific monitoring of the target ion concentration. Each electrode is numbered and connected to the monitoring system to collect and identify ion concentration data within each zone in real time.

[0105] S42: Real-time concentration data is acquired through the ion-selective electrodes within each zone to form the instantaneous ion concentration C for each electrode. i,j C i,j This represents the target ion concentration at the j-th electrode within the i-th partition;

[0106] S43: Compare the electrode data collected in S42 with the preset target concentration, and calculate the concentration deviation ΔC for each zone. i The formula is: ΔC i =C avg,i -C target , where ΔC i C represents the concentration deviation of the i-th partition; avg,iThe average concentration of the i-th partition is calculated from the mean of all electrode data within that partition; C target The preset target ion concentration;

[0107] S44: The concentration deviation ΔC calculated in S43 i The data is sent to the closed-loop control unit, and the deviation data is analyzed to generate feeding adjustment parameters and stirring adjustment parameters.

[0108] S45: Based on the adjustment parameters in S44, commands are sent to the multi-point feeding unit in S2 and the intelligent stirring unit in S3 to dynamically adjust the feeding rate, stirring speed, and blade angle of each zone, so that the ion concentration of each zone gradually approaches the target value. Through the above steps, the ion concentration in each zone can be monitored in real time using multi-point ion selective electrodes, and the feeding and stirring can be dynamically adjusted through the closed-loop control unit to ensure that the ion concentration of each zone reaches a balanced state.

[0109] The closed-loop control unit in S44 specifically includes:

[0110] S441: Receive the concentration deviation ΔC of each zone in the closed-loop control unit. i The data is collected, and the concentration deviation of each partition is analyzed to determine the magnitude and direction of the deviation. By comparing the deviation data with a preset adjustment threshold T, partitions requiring incremental or decremental adjustment are classified. The comparison formula is as follows:

[0111]

[0112] Among them, D i Indicates the adjustment direction of the i-th partition; ΔC i is the concentration deviation of the i-th partition; T is the preset concentration deviation threshold, used to determine whether the feeding or stirring parameters need to be adjusted.

[0113] S442: Based on the deviation analysis results obtained in S441, calculate the final feeding adjustment rate for each zone, which is used for optimization based on the preliminary adjustment parameters in S23; when D i When D = 1, increase the feeding rate; when D i When D = -1, reduce the feeding rate; when D i When Q = 0, maintain the current feeding rate; the formula for the final feeding adjustment rate is: Q i,final =Q i,adjust +K q ·ΔC i ·D i , where Q i,final Q represents the final feed adjustment rate for the i-th partition; i,adjust The initial feed rate adjusted in S23; Kq This is a feeding adjustment coefficient, used to further optimize the feeding rate based on the deviation.

[0114] S443: For stirring speed adjustment, based on concentration deviation ΔC i Calculate the final adjustment value ω of the stirring speed for each zone. i,final According to D i The direction of the stirring speed in each zone is adjusted by increasing or decreasing the stirring speed using the formula: ω i,final =ω i +K ω ·ΔC i ·D i , where ω i,final ω is the final adjustment value for the stirring speed of the i-th partition; i K represents the current stirring speed. ω This is the stirring speed adjustment coefficient, used to control the amount of stirring rate adjustment;

[0115] S444: Based on concentration deviation ΔC i and adjust direction D i Calculate the final adjustment value θ of the agitator blade angle. i,final This ensures a more uniform blending effect in each partition; the formula is: θ i,final =θ i +K θ ·ΔC i ·D i , where θ i,final θ represents the final adjustment value of the impeller angle for the i-th partition; i K represents the current blade angle. θ The blade angle adjustment coefficient is used to adjust the angle based on the concentration deviation. Through the above steps, the closed-loop control unit can generate specific parameters for the final feed adjustment rate, stirring speed and blade angle based on the concentration deviation of each zone, so as to achieve precise feed and stirring control in S2 and S3, and ensure that the ion concentration of each zone gradually approaches the target concentration.

[0116] S5 specifically includes:

[0117] S51: Calculate the injection rate of the nucleation inducing agent based on the target ion concentration in the solution and the volume within the reactor to ensure that the concentration of the inducing agent in the reactor reaches the preset induction concentration to induce the initial formation of crystal nuclei; the formula is: Among them, R induce V is the injection rate of the nucleation inducer. reactor C is the total volume of the reactor; induce The target concentration of the inducer is used to ensure crystal nucleation; t induce The time period for injecting the inducer is used to control the injection rate;

[0118] S52: During the injection process in S51, a concentration sensor is used to monitor the concentration of the nucleation inducer in the reactor in real time to ensure that it is maintained within the set range C. induce ±δ, where δ is the allowable concentration fluctuation range. If a deviation is detected, the injection rate R will be automatically adjusted. induce To achieve precise injection;

[0119] S53: After the inducer concentration reaches the target concentration, the control system sets the inducer injection stop time point. At this time point, the inducer injection is stopped, so that the metal ions in the reactor can form crystal nuclei under the action of the inducer, thus realizing the initial generation of crystal nuclei.

[0120] S54: After the initial formation of crystal nuclei, start the ultrasonic vibration unit and set the ultrasonic frequency and power;

[0121] S55: After the ultrasonic parameters are set in S54, the ultrasonic vibration unit is used to apply uniform vibration to the solution inside the reactor, so that the crystal nuclei are evenly distributed in the solution under the action of ultrasonic vibration, avoiding local concentration and providing consistent initial conditions for subsequent crystal growth. Through the above steps, the precise injection of the crystal nucleus inducer and the uniform distribution assisted by ultrasound can be achieved, so that the crystal nuclei are evenly generated and distributed in the reactor, ensuring the particle size consistency and structural stability in the subsequent crystallization process.

[0122] S6 specifically includes:

[0123] S61: After the reaction is completed, the slurry is introduced from the reactor into the first stage separator of the multi-stage slow-release solid-liquid separation unit, and the initial flow rate V0 is set to ensure that the particles begin to settle in the first stage separator, avoiding excessive flow rate causing particle suspension or excessive flow rate causing excessive settling.

[0124] S62: Based on the multi-stage design of the solid-liquid separation unit, the flow rate is successively reduced in each stage separator; let the flow rate of the nth stage be V. n Then the flow velocity in each stage of the separator is reduced proportionally to achieve stepwise particle settling; the formula is: V n+1 =V n ×(1-R), where V n+1 V is the flow velocity of the (n+)th stage separator; n R is the flow velocity of the nth stage separator; R is the flow velocity reduction ratio, which is set according to the settling rate and separator design parameters to ensure uniform particle settling.

[0125] S63: Install a flow rate sensor at the liquid outlet of each stage separator to monitor the current liquid flow rate V in real time. n,real And calculate the value V. nThe difference in flow rate is monitored, and when a difference is detected, the flow rate is adjusted via a feedback control unit to ensure that the actual flow rate is always maintained within the allowable range of the target flow rate. n ±ΔV, where ΔV is the allowable flow velocity fluctuation range;

[0126] S64: After multi-stage slow-release separation, the sedimented precursor particles are finally collected at the bottom of the last stage separator to ensure uniform particle sedimentation and high-purity solid-liquid separation. Through the above steps, the liquid flow rate can be controlled step by step to achieve uniform sedimentation of precursor particles, ensure consistent solid-liquid separation effect, and provide a suitable particle morphology for subsequent drying steps.

[0127] S7 specifically includes:

[0128] S71: Before the precursor particles separated from the multi-stage slow-release solid-liquid separation unit are sent into the drying device, the particles are pre-distributed in the feeding area by a vibrating screen to eliminate particle agglomeration and make the particles spread evenly in the drying equipment.

[0129] S72: Based on the particle size distribution, density and target drying rate of the precursor particles, multi-point homogenizing airflow nozzles are set in the drying device, including setting the airflow velocity, temperature and humidity parameters to ensure stable airflow during the drying process, so as to ensure uniform distribution of particles throughout the drying area.

[0130] S73: The airflow distribution and velocity of each nozzle are monitored in real time by the airflow sensor installed in the drying device. If uneven airflow is detected, the airflow of the nozzle is automatically adjusted according to the sensor feedback to eliminate local airflow fluctuations and ensure that the airflow evenly covers the surface of all particles.

[0131] S74: During the drying process, optical or laser particle distribution monitoring equipment is used to monitor the distribution of particles in the drying device in real time to ensure that the uniformity of particle distribution in the drying area meets the preset requirements; if the particle distribution deviates from the set state, fine adjustments are made by homogenizing airflow to make the particles redistribute uniformly.

[0132] S75: During the drying process, the temperature gradient inside the drying device is monitored by thermocouple temperature sensors to ensure uniform temperature distribution. According to the requirements of particle moisture content and drying rate, the temperature inside the device is controlled within a predetermined range to avoid particle decomposition due to excessively high temperature or incomplete drying due to excessively low temperature.

[0133] S76: After drying, the uniformly dried precursor particles are collected from the drying device and packaged for final processing. This ensures that the collected precursor materials meet the standard requirements in terms of ion concentration and particle uniformity, providing high-quality precursor products for the subsequent production of ternary cathode materials for lithium-ion batteries. Through the above steps, by utilizing homogenized airflow control and real-time distribution monitoring, the uniformity of the dried precursor particles and the consistency of ion concentration can be effectively guaranteed, forming a stable and uniform precursor product for ternary cathode materials of lithium-ion batteries.

[0134] This invention encompasses any substitutions, modifications, equivalent methods, and solutions made within the spirit and scope of this invention. To provide the public with a thorough understanding of this invention, specific details are described in detail in the following preferred embodiments; however, those skilled in the art will fully understand the invention even without these details. Furthermore, to avoid unnecessary misunderstanding of the essence of this invention, well-known methods, processes, procedures, components, and circuits are not described in detail.

[0135] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A control method for a lithium-ion battery ternary cathode material precursor production system, characterized in that, Includes the following steps: S1: Based on the predetermined ternary cathode material ratio, the fluid behavior in the reactor is modeled using simulation software, and the reactor is divided into several zones to obtain the fluid flow characteristics and ion concentration distribution in each zone. S2: Based on the partitioning of S1, a solution containing nickel, cobalt, manganese or aluminum is injected into each partition of the reactor from multiple inlets through a multi-point feeding unit, and the feeding rate of the feeding unit is adjusted in real time to maintain the same ion concentration in each partition. S3: Based on the partitioned fluid characteristics modeled in S1, the stirring speed and mode in the reactor are dynamically adjusted by the intelligent stirring unit to ensure that the solution in each partition of the reactor is fully mixed and to reduce the difference in ion concentration. S4: Arrange multiple ion-selective electrodes in each zone to monitor the concentration of nickel, cobalt, manganese or aluminum ions, and feed the monitored concentration data back to the closed-loop control unit. Adjust the feeding rate in S2 and the stirring parameters in S3 to balance the ion concentration in each zone. S5: In the solution environment after the closed-loop control of S4, the uniform generation of crystal nuclei is achieved through the precise injection of crystal nuclei inducing agents; then, the ultrasonic vibration unit is used to assist in the uniform distribution of crystal nuclei, providing consistent initial conditions for the subsequent crystallization process; S6: The slurry after the reaction is completed is introduced into a multi-stage slow-release solid-liquid separation unit to gradually separate the precursor material particles, and the liquid flow rate is controlled to obtain a uniform solid sedimentation effect, ensuring the separation integrity of the obtained precursor. S6 specifically includes: S61: The slurry after the reaction is completed is introduced from the reactor into the first stage separator of the multi-stage slow-release solid-liquid separation unit, and the initial flow rate is set. This is to ensure that the particles begin to settle in the first-stage separator; S62: Based on the multi-stage design of the solid-liquid separation unit, the flow rate is sequentially reduced in each stage separator; let the first stage... The flow rate of the stage is The flow velocity in each stage of the separator is reduced proportionally to achieve gradual particle settling; the formula is: ,in, For the first Flow rate of the first-stage separator; For the first The flow rate of the stage separator; The percentage reduction in flow rate; S63: Install a flow rate sensor at the liquid outlet of each stage separator to monitor the current liquid flow rate in real time. And calculate the value set. The system detects differences in flow rate and adjusts the flow rate accordingly via a feedback control unit to ensure that the actual flow rate remains within the allowable range of the target flow rate. S64: After multi-stage slow-release separation, the sedimented precursor particles are finally collected at the bottom of the last stage separator; S7: The separated precursor material particles are dried, and the particle distribution is controlled by homogenizing airflow to maintain the uniformity of ion concentration in the dried precursor particles, ultimately forming a uniform lithium-ion battery ternary cathode material precursor product.

2. The control method for a lithium-ion battery ternary cathode material precursor production system according to claim 1, characterized in that, S1 specifically includes: S11: Based on the composition requirements of the target ternary cathode material, set the molar ratio and concentration range of nickel, cobalt, manganese or aluminum, and determine the parameters in the reaction process, including solution flow rate, stirring speed and reaction temperature; S12: Input the material ratio parameters and process parameters set in S11 into the fluid simulation software, and generate a fluid dynamics model in the reactor through computational fluid dynamics. The fluid dynamics model can accurately describe the flow velocity, pressure and shear rate in different regions, providing a data basis for partitioning. S13: Based on the fluid dynamics model of S12, the reactor is divided into several preliminary zones. Each zone is set as a high-velocity zone, a medium-velocity zone, and a low-velocity zone according to the difference in flow rate and shear rate, and the initial boundary of each zone is determined. S14: Import the preliminary partitioning in S13 into the simulation software for multiple simulations, adjust the partition boundaries to a stable state, and keep the fluid flow state and ion concentration in each partition consistent. S15: Based on the simulation results of S14, numerical calculations are performed on the ion concentration distribution in each partition to generate the corresponding concentration distribution data.

3. The control method for a lithium-ion battery ternary cathode material precursor production system according to claim 2, characterized in that, S15 specifically includes: S151: In the simulation software, based on the partition model optimized in S14, set up ion concentration monitoring points for each partition and define the coordinates and position of each monitoring point; S152: Based on the data acquisition in S151, set the time step and calculate the rate of change of ion concentration over time, targeting metal ions such as nickel, cobalt, manganese or aluminum. S153: Based on the concentration change rate calculated in S152, the ion concentration of each partition is updated and corrected step by step using a numerical iteration method until the ion concentration of each partition converges to a stable state. S154: After the ion concentration converges in S153, the final concentration values ​​of each monitoring point are numerically integrated to generate concentration distribution data for each zone, and this data is stored in tabular form.

4. The control method for a lithium-ion battery ternary cathode material precursor production system according to claim 1, characterized in that, S2 specifically includes: S21: Based on the partition locations defined in S1, install an independent feed port at the inlet of each partition to ensure that the solution can be accurately delivered to the designated partition. Each feed port is connected to its respective flow control valve to ensure that the solution injection location of each partition corresponds to the concentration control requirements of the partition. S22: Install ion concentration sensors and flow sensors on the fluid pipelines of each zone. The ion concentration sensors acquire real-time concentration data of nickel, cobalt, manganese or aluminum ions, and the flow sensors monitor the flow rate of each feed port. S23: Based on the ion concentration data of each zone collected in S22 and the preset target concentration value, the feed rate adjustment parameter of each zone is calculated by the proportional integral derivative control algorithm to determine the real-time adjustment value of feed increment or decrement. S24: Using the feed rate adjustment parameters calculated in S23, the feed rate of each feed port is adjusted by regulating the flow control valve to ensure that the ion concentration in each zone gradually approaches the target concentration.

5. The control method for a lithium-ion battery ternary cathode material precursor production system according to claim 4, characterized in that, S3 specifically includes: S31: Based on the fluid dynamics model established in S1, set the initial stirring parameters for the flow characteristics of each zone, including stirring speed and stirring blade angle; S32: Based on the concentration sensor installed in S22, it collects the concentration data of nickel, cobalt, manganese or aluminum ions in real time, obtains the current ion concentration of each zone, and uses the data to calculate the concentration difference between each zone. S33: Based on the concentration difference value obtained in S32, the stirring speed adjustment value and blade angle adjustment value of each zone are calculated through feedback control algorithm to reduce the concentration difference within the zone; S34: Using the stirring speed and blade angle adjustment parameters calculated by S33, the stirring speed and angle of the stirrer are adjusted in real time by the intelligent stirring unit to achieve the optimal stirring state of each zone.

6. The control method for a lithium-ion battery ternary cathode material precursor production system according to claim 1, characterized in that, S4 specifically includes: S41: Ion-selective electrodes are arranged at predetermined positions within each zone, each electrode being specifically designed to detect the corresponding concentration of nickel, cobalt, manganese, or aluminum ions; S42: Real-time concentration data is acquired through the ion-selective electrodes within each zone to form the instantaneous ion concentration for each electrode. ,in Indicates the first Within the partition Instantaneous ion concentration at each electrode; S43: Compare the electrode data collected in S42 with the preset target concentration, and calculate the concentration deviation of each zone. ; S44: The concentration deviation calculated in S43 The data is sent to the closed-loop control unit, and the deviation data is analyzed to generate feeding adjustment parameters and stirring adjustment parameters. S45: Based on the adjustment parameters in S44, send instructions to the multi-point feeding unit in S2 and the intelligent stirring unit in S3 respectively, to dynamically adjust the feeding rate, stirring speed and blade angle of each zone, so that the ion concentration of each zone gradually approaches the target value.

7. The control method for a lithium-ion battery ternary cathode material precursor production system according to claim 6, characterized in that, S44 specifically includes: S441: Receives the concentration deviation of each zone in the closed-loop control unit. The data is analyzed, and the concentration deviation in each partition is determined to identify the magnitude and direction of the deviation. This is achieved by comparing the deviation data with a preset adjustment threshold. By comparing the data, we can categorize the partitions that require incremental or decremental adjustments. The comparison formula is as follows: ； in, Indicates the first The direction of partition adjustment; For the first Concentration deviation in different zones; This is the preset concentration deviation threshold; S442: Based on the deviation analysis results obtained in S441, calculate the final feeding adjustment rate for each zone, which is used for optimization based on the preliminary adjustment parameters in S23; when When, increase the feeding rate; when When, reduce the feeding rate; when At the same time, maintain the current feeding rate; the formula for the final feeding adjustment rate is: ,in, For the first Final feed rate adjustment for each zone; The initial feed rate adjusted in S23; This is a feeding adjustment coefficient, used to further optimize the feeding rate based on the deviation. S443: For stirring speed adjustment, based on concentration deviation Calculate the final adjustment value of the stirring speed for each zone. ,according to The direction of the stirring speed in each zone is adjusted by increasing or decreasing the stirring speed using the following formula: ,in, For the first The final adjustment value for the stirring speed of each zone; This refers to the current stirring speed; This is the stirring speed adjustment coefficient; S444: Based on concentration deviation and adjust direction Calculate the final adjustment value of the agitator blade angle. This ensures a more uniform blending effect in each partition; the formula is: ,in, For the first The final adjustment value for the stirring blade angle of the partition; The current blade angle; This is the blade angle adjustment coefficient.

8. The control method for a lithium-ion battery ternary cathode material precursor production system according to claim 1, characterized in that, S5 specifically includes: S51: Calculate the injection rate of the nucleation inducing agent based on the target ion concentration in the solution and the volume within the reactor to ensure that the concentration of the inducing agent in the reactor reaches the preset induction concentration to induce the initial formation of crystal nuclei; the formula is: ,in, The injection rate of the nucleation inducer; This refers to the total volume of the reactor; The target concentration of the inducer; The time period for inducing agent injection; S52: During the injection process in S51, a concentration sensor is used to monitor the concentration of the nucleation inducer in the reactor in real time to ensure that it is maintained within the set range. If a deviation is detected, the injection rate will be automatically adjusted. To achieve precise injection; S53: After the inducer concentration reaches the target concentration, the control system sets the inducer injection stop time point, and stops the inducer injection at this time point, so that the metal ions in the reactor can form crystal nuclei under the action of the inducer. S54: After the initial formation of crystal nuclei, start the ultrasonic vibration unit and set the ultrasonic frequency and power; S55: After the ultrasonic parameters are set in S54, the ultrasonic vibration unit is used to apply uniform vibration to the solution inside the reactor, so that the crystal nuclei are evenly distributed in the solution under the action of ultrasonic vibration, avoiding local concentration.

9. The control method for a lithium-ion battery ternary cathode material precursor production system according to claim 1, characterized in that, Specifically, S7 includes: S71: Before the precursor particles separated from the multi-stage slow-release solid-liquid separation unit are sent into the drying device, the particles are pre-distributed in the feeding area by a vibrating screen to eliminate particle agglomeration and make the particles spread evenly in the drying equipment. S72: Based on the particle size distribution, density, and target drying rate of the precursor particles, a multi-point homogenizing airflow nozzle is set in the drying device, including setting the airflow velocity, temperature, and humidity parameters. S73: The airflow distribution and velocity of each nozzle are monitored in real time by the airflow sensor installed in the drying device. If uneven airflow is detected, the airflow of the nozzle is automatically adjusted according to the sensor feedback to eliminate local airflow fluctuations. S74: During the drying process, optical or laser particle distribution monitoring equipment is used to monitor the particle distribution status in the drying device in real time to ensure that the uniformity of particle distribution in the drying area meets the preset requirements; if the particle distribution deviates from the set state, fine adjustments are made by homogenizing the airflow. S75: During the drying process, the temperature gradient inside the drying device is monitored by thermocouple temperature sensors to ensure uniform temperature distribution. The temperature inside the device is controlled within a predetermined range according to the requirements of particle moisture content and drying rate. S76: After drying is complete, the uniformly dried precursor particles are collected from the drying device for final packaging.

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