Control method of lithium ion battery ternary positive electrode material precursor production system

Abstract

The invention 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, which comprises the following steps: S1, modeling fluid behaviors in a reactor by using simulation software; s2, the feeding rate of a feeding unit is adjusted in real time, and the concentration of ions in all the partitions is kept consistent; s3, dynamically adjusting the stirring speed and mode in the reactor; s4, adjusting the feeding rate in the step S2 and the stirring parameters in the step S3; s5, performing crystal nucleus homogenization induction; s6, precursor material particles are separated out step by step; and S7, carrying out drying treatment on the separated precursor material particles. According to the preparation method, through multi-dimensional dynamic regulation and control and accurate distribution control, the ion uniformity and the structural stability of the ternary positive electrode material precursor are remarkably improved, and a high-quality material basis is provided for a high-performance lithium ion battery.

Description

Technical Field

[0001] The present invention relates to the technical field of lithium ion battery material production, and in particular to a control method for a lithium ion battery ternary positive electrode material precursor production system. Background Art

[0002] With the rapid development of the new energy industry, lithium-ion batteries, as high-energy-density, high-efficiency energy storage devices, are widely used in electric vehicles, energy storage power stations, portable electronic products and other fields. Ternary positive electrode materials (such as nickel-cobalt-manganese or nickel-cobalt-aluminum composite oxides) have become the mainstream choice of lithium-ion battery positive electrode materials due to their high specific capacity, better stability and longer cycle life. In the production of ternary positive electrode materials, the preparation of precursor materials is crucial. Its ion composition, particle uniformity and structural stability directly affect the overall performance of lithium-ion batteries. However, the traditional production method of ternary positive electrode material precursors is difficult to achieve precise control of key parameters such as concentration, distribution, and particle size in a complex process flow, resulting in difficulty in ensuring the quality and consistency of the materials, affecting the performance stability and life of battery products.

[0003] In the prior art, due to the interaction of multiple factors such as reaction environment, fluid dynamics, concentration distribution, etc., the precursor material faces problems such as uneven ion concentration, difficult to control crystal morphology, inconsistent particle size distribution, and agglomeration during drying during the preparation process. In particular, it is difficult to effectively control the entire production process through a single control method in the traditional production system, resulting in low uniformity and purity of the precursor material, and the ion distribution and particle morphology of the material are difficult to achieve the ideal state. Therefore, a new precursor production control method is urgently needed to solve the above problems. Summary of the invention

[0004] Based on the above purpose, the present invention provides a control method for a lithium-ion battery ternary positive electrode material precursor production system.

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

[0006] S1: According to the predetermined ternary cathode material ratio, the fluid behavior in the reactor is modeled using simulation software, and the reactor is divided into several partitions to obtain the fluid flow characteristics and ion concentration distribution in each partition;

[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 keep the concentration of ions in each partition consistent;

[0008] S3: Based on the partitioned fluid characteristics modeled in S1, the intelligent stirring unit is used to dynamically adjust the stirring speed and mode in the reactor, so that the solutions in each partition of the reactor can be fully mixed and the difference in ion concentration can be reduced;

[0009] S4: multiple ion selective electrodes are arranged in each partition to monitor the concentration of nickel, cobalt, manganese or aluminum ions, and the monitored concentration data is fed back to the closed-loop control unit to balance the ion concentration in each partition by adjusting the feed rate in S2 and the stirring parameters in S3;

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

[0011] S6: introducing the slurry after the reaction into a multi-stage slow-release solid-liquid separation unit to gradually separate the precursor material particles, and controlling the liquid flow rate to obtain a uniform solid sedimentation effect to ensure the separation integrity of the obtained precursor;

[0012] S7: Dry the separated precursor material particles and control the particle distribution through homogenized airflow so that the dried precursor particles maintain uniform ion concentration, and finally form a uniform lithium-ion battery ternary positive electrode material precursor product.

[0013] Optionally, the S1 specifically includes:

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

[0015] S12: inputting the material ratio parameters and process parameters set in S11 into the fluid simulation software, and generating a fluid dynamics model in the reactor by means of a computational fluid dynamics method. The fluid dynamics model can accurately describe the flow velocity, pressure and shear rate in different regions, and provide a data basis for the zoning;

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

[0017] S14: importing the preliminary partitions in S13 into the simulation software for multiple simulations, adjusting the partition boundaries to a stable state until the fluid flow state and ion concentration in each partition remain consistent;

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

[0019] Optionally, the S15 specifically includes:

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

[0021] S152: Based on the data collected in S151, the time step is set, and the rate of change of the ion concentration over time is calculated with the metal ions nickel, cobalt, manganese or aluminum as the target;

[0022] S153: Based on the concentration change rate calculated in S152, the ion concentration of each partition is gradually updated and corrected by 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 value of each monitoring point is numerically integrated to generate concentration distribution data for each partition, and the data is stored in a table form.

[0024] Optionally, the S2 specifically includes:

[0025] S21: According to the partition positions divided in S1, an independent feed port is installed at the entrance position of each partition so that the solution can be accurately delivered to the designated partition. Each feed port is connected to its own flow control valve to ensure that the solution injection position of each partition corresponds to the concentration control requirements of the partition;

[0026] S22: installing an ion concentration sensor and a flow sensor on the fluid pipeline of each partition, obtaining the concentration data of nickel, cobalt, manganese or aluminum ions in real time through the ion concentration sensor, and monitoring the flow value of each feed port through the flow sensor;

[0027] S23: According to the ion concentration data of each partition collected in S22 and the preset target concentration value, the feed rate adjustment parameter of each partition is calculated by a proportional integral differential control algorithm to determine the real-time adjustment value of the 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 adjusting the flow control valve to ensure that the ion concentration of each partition gradually approaches the target concentration.

[0029] Optionally, the S3 specifically includes:

[0030] S31: according to the fluid dynamics model established in S1, initial stirring parameters are set according to the flow characteristics of each partition, including stirring speed and angle of stirring blades;

[0031] S32: Based on the concentration sensor installed in S22, the concentration data of nickel, cobalt, manganese or aluminum ions are collected in real time, the current ion concentration of each partition is obtained, and the concentration difference value between the partitions is calculated using the data;

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

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

[0034] Optionally, the S4 specifically includes:

[0035] S41: arranging ion selective electrodes at predetermined positions within each partition, each electrode being specifically used to detect the corresponding nickel, cobalt, manganese or aluminum ion concentration;

[0036] S42: Real-time concentration data is obtained through the ion selective electrodes in each partition to form the instantaneous ion concentration C of each electrode. i,j , where C i,j represents the target ion concentration at the jth electrode in the i-th partition;

[0037] S43: Compare the electrode data collected in S42 with the preset target concentration and calculate the concentration deviation ΔC of each partition i ;

[0038] S44: The concentration deviation ΔC calculated in S43 is 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: According to the adjustment parameters in S44, instructions are sent to the multi-point feeding unit in S2 and the intelligent stirring unit in S3 respectively, so as to dynamically adjust the feeding rate, stirring speed and blade angle of each partition so that the ion concentration of each partition gradually approaches the target value.

[0040] Optionally, the S44 specifically includes:

[0041] S441: Receive the concentration deviation ΔC of each partition in the closed-loop control unit iThe concentration deviation of each partition is analyzed to determine the size and direction of the deviation. The partitions that need incremental adjustment or decremental adjustment are classified by comparing the deviation data with the preset adjustment threshold T. The comparison formula is:

[0042]

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

[0044] S442: According to the deviation analysis results obtained in S441, the final feed adjustment rate of each partition is calculated for optimization based on the preliminary adjustment parameters in S23; when D i =1, increase the feeding rate; when D i = -1, reduce the feed rate; when D i =0, maintain the current feeding rate; the final feeding rate adjustment formula is: Q i,final =Q i,adjust +K q ΔC i ·D i , where Q i,final is the final feed adjustment rate of the i-th partition; Q i,adjust K is the feed rate initially adjusted in S23; q is the feed adjustment factor, which is used to further optimize the feed rate according to the deviation;

[0045] S443: For stirring speed adjustment, based on concentration deviation ΔC i Calculate the final adjustment value of stirring speed for each partition ω i,final , according to D i In the direction of the stirring speed of each partition, increase or decrease the adjustment value, the formula is: ω i,final =ω i +K ω ΔC i ·D i , where ω i,final is the final adjustment value of the stirring speed of the i-th partition; ω i is the current stirring speed; K ω is the stirring speed adjustment coefficient;

[0046] S444: Based on the concentration deviation ΔC i and adjust direction D i , calculate the final adjustment value θ of the stirring blade angle i,final , to ensure that the mixing effect of each partition is more uniform; the formula is: θ i,final =θi +K θ ΔC i ·D i , where θ i,final is the final adjustment value of the stirring blade angle in the i-th partition; θ i is the current blade angle; K θ is the blade angle adjustment factor.

[0047] Optionally, the S5 specifically includes:

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

[0049] S52: During the injection process of S51, the concentration sensor is used to monitor the concentration of the crystal 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 a stop time point for the inducer injection, and stops the inducer injection at this time point, so that the metal ions in the reactor form crystal nuclei under the action of the inducer;

[0051] S54: After the crystal nucleus is initially generated, the ultrasonic vibration unit is started, and the ultrasonic frequency and power are set;

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

[0053] Optionally, the 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 V is set. 0 , to ensure that particles begin to settle in the first-stage separator;

[0055] S62: According to the multi-stage design of the solid-liquid separation unit, the flow rate is lowered in each stage of the separator; let the flow rate of the nth stage be V n, the flow rate of each stage of the separator is reduced proportionally to achieve the step-by-step sedimentation of particles; the formula is: V n+1 =V n ×(1-R), where V n+1 V is the flow rate of the n+th stage separator; n is the flow rate of the nth stage separator; R is the flow rate reduction ratio;

[0056] S63: A flow rate sensor is installed at the liquid outlet of each stage separator to monitor the current liquid flow rate V in real time. n,real , and calculate the set value V n When a difference is detected, the flow rate difference is adjusted through 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 multiple stages of slow-release separation, the settled precursor particles are finally collected at the bottom of the last stage separator.

[0058] Optionally, the S7 specifically includes:

[0059] S71: Before the precursor particles separated from the multi-stage slow-release solid-liquid separation unit are fed into the drying device, the particles are pre-distributed in the feed area through a vibrating screen to eliminate particle agglomeration and allow the particles to be evenly spread in the drying device;

[0060] S72: according to the particle size distribution, density and target drying rate of the precursor particles, a multi-point homogenizing airflow nozzle is arranged in the drying device, including setting the flow rate, temperature and humidity parameters of the airflow;

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

[0062] S74: During the drying process, use optical or laser particle distribution monitoring equipment to monitor the distribution of particles in the drying device in real time to ensure that the distribution uniformity of particles in the drying area meets the preset requirements; if the particle distribution deviates from the set state, make subtle adjustments through the homogenized airflow;

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

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

[0065] Beneficial effects of the present invention:

[0066] The present invention realizes 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, ultrasonic vibration homogenization and other technologies. In the reaction, separation, drying and other stages, relying on real-time concentration monitoring and feedback control, it can effectively reduce the ion concentration gradient and ensure uniform ion distribution in each partition. At the same time, through the dynamic adjustment of stirring rate, feeding rate, inducer injection and other conditions, the uniform generation and distribution of crystal nuclei are further guaranteed, providing consistent basic conditions for subsequent crystallization.

[0067] The present invention reduces the problems of particle agglomeration and uneven sedimentation by introducing multi-stage flow rate control and homogenized airflow drying technology in the solid-liquid separation and drying process, so that the precursor particles maintain a highly uniform ion distribution and a stable structure after drying. Finally, by using precise parameter regulation and distribution control means, the quality consistency and purity of the ternary positive electrode material precursor are significantly improved, providing a reliable material basis for the manufacture of high-performance lithium-ion batteries, extending the service life of the battery and improving its overall performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

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

[0070] Figure 2 This is a schematic diagram of the flow of modeling the fluid behavior in a reactor according to an embodiment of the present invention. DETAILED DESCRIPTION

[0071] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and 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 references to "one embodiment", "an embodiment", "an exemplary embodiment", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

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

[0074] like Figure 1-Figure 2 As shown, a control method for a lithium-ion battery ternary positive electrode material precursor production system comprises the following steps:

[0075] S1: According to the predetermined ternary cathode material ratio, the fluid behavior in the reactor is modeled using simulation software, and the reactor is divided into several partitions to obtain the fluid flow characteristics and ion concentration distribution in each partition;

[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 keep the concentration of ions in each partition consistent;

[0077] S3: Based on the partitioned fluid characteristics modeled in S1, the intelligent stirring unit is used to dynamically adjust the stirring speed and mode in the reactor, so that the solutions in each partition of the reactor can be fully mixed and the difference in ion concentration can be reduced;

[0078] S4: multiple ion selective electrodes are arranged in each partition to monitor the concentration of nickel, cobalt, manganese or aluminum ions, and the monitored concentration data is fed back to the closed-loop control unit to balance the ion concentration in each partition by adjusting the feed rate in S2 and the stirring parameters in S3;

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

[0080] S6: introducing the slurry after the reaction into a multi-stage slow-release solid-liquid separation unit to gradually separate the precursor material particles, and controlling the liquid flow rate to obtain a uniform solid sedimentation effect to ensure the separation integrity of the obtained precursor;

[0081] S7: Dry the separated precursor material particles and control the particle distribution through homogenized airflow so that the dried precursor particles maintain uniform ion concentration, and finally form a uniform lithium-ion battery ternary positive electrode material precursor product.

[0082] S1 specifically includes:

[0083] S11: according to the composition requirements of the target ternary cathode material, the molar ratio and concentration range of nickel, cobalt, manganese or aluminum are set, and the parameters in the reaction process are determined, 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 by means of computational fluid dynamics (CFD) method. The fluid dynamics model can accurately describe the flow velocity, pressure and shear rate in different areas, and provide a data basis for zoning;

[0085] S13: Based on the fluid dynamics model of S12, the reactor is divided into several preliminary partitions, each of which is set as a high flow rate zone, a medium flow rate zone and a low flow rate zone according to the difference in flow rate and shear rate, and the initial boundary of each partition 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, and refine the boundaries of each partition based on the simulation results in this step to ensure that the ion concentration gradient in the reactor is minimized;

[0087] S15: Based on the simulation results of S14, the ion concentration distribution in each partition is numerically calculated to generate corresponding concentration distribution data, which is used as basic data of the multi-point dynamic feeding unit to achieve uniform feeding in each partition.

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

[0089] S151: In the simulation software, based on the partition model optimized by S14, set the ion concentration monitoring points of each partition, define the coordinates and position of each monitoring point to ensure that the key positions of each partition are covered; the formula is: P i =(x i ,y i ,z i ), where P i represents the position coordinates of the i-th monitoring point; xi ,y i ,z i Respectively represent the horizontal, vertical and height coordinates of the i-th monitoring point in three-dimensional space, which are used to determine the specific position of the monitoring point in the reactor;

[0090] S152: Based on the data collected in S151, set the time step Δt, take the metal ions nickel, cobalt, manganese or aluminum as the target, and calculate the ion concentration C i The rate of change over time; the formula is: in, represents the rate of change of ion concentration at the i-th monitoring point over time; C i,t and C i,t+Δt They 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 represents the ion concentration of the ith monitoring point at the n+1th iteration, C i,n is the ion concentration at the nth iteration, is the rate of change of ion concentration calculated in S152, Δt is the time interval;

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

[0093] S2 specifically includes:

[0094] S21: According to the partition positions divided in S1, an independent feed port is installed at the entrance position of each partition so that the solution can be accurately delivered to the designated partition. Each feed port is connected to its own flow control valve to ensure that the solution injection position of each partition corresponds to the concentration control requirements of the partition;

[0095] S22: installing an ion concentration sensor and a flow sensor on the fluid pipeline of each partition, obtaining the concentration data of nickel, cobalt, manganese or aluminum ions in real time through the ion concentration sensor, and monitoring the flow value of each feed port through the flow sensor;

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

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

[0098] S3 specifically includes:

[0099] S31: according to the fluid dynamics model established in S1, initial stirring parameters are set according to the flow characteristics of each partition, including the stirring speed and the angle of the stirring blade, to ensure that the initial mixing effect meets the requirements of the partition flow characteristics;

[0100] S32: Based on the concentration sensor installed in S22, the concentration data of nickel, cobalt, manganese or aluminum ions are collected in real time to obtain the current ion concentration of each partition, and the concentration difference value between the partitions is calculated using the data to determine the concentration deviation between different partitions;

[0101] S33: Based on the concentration difference value obtained in S32, the stirring speed adjustment value and the blade angle adjustment value of each partition are calculated through the feedback control algorithm to reduce the concentration difference within the partition and achieve a more uniform ion distribution; the adjustment value formula is: ω i =ω 0 +K c ΔC i θ i =θ 0 +K a ΔC i , where ω i is the stirring speed of the ith partition; ω 0 is the initial stirring speed; K c is the speed adjustment coefficient, which is used to adjust the speed according to the concentration difference; ΔC i is the concentration difference of the ith partition, that is, the deviation between the ion concentration of the partition and the target concentration; θ i is the stirring blade angle of the i-th partition; θ 0 is the initial blade angle; K a is the angle adjustment coefficient, used to adjust the blade angle;

[0102] S34: Using the stirring speed and blade angle adjustment parameters calculated by S33, the speed and angle of the stirrer are adjusted in real time through the intelligent stirring unit to optimize the stirring state of each partition to achieve 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 reduce the difference in ion concentration within the partition, and ensure the uniformity of the solution.

[0103] S4 specifically includes:

[0104] S41: Arranging ion selective electrodes at predetermined positions in each partition, each electrode is specifically used to detect the corresponding nickel, cobalt, manganese or aluminum ion concentration to ensure the specific monitoring of the target ion concentration, each electrode is numbered and connected to the monitoring system to collect and identify the ion concentration data in each partition in real time;

[0105] S42: Real-time concentration data is obtained through the ion selective electrodes in each partition to form the instantaneous ion concentration C of each electrode. i,j , where C i,j represents the target ion concentration at the jth electrode in the i-th partition;

[0106] S43: Compare the electrode data collected in S42 with the preset target concentration and calculate the concentration deviation ΔC of each partition i , the formula is: ΔC i =C avg,i -C target , where ΔC iis the concentration deviation of the ith partition; C avg,i is the average concentration of the ith partition, which is calculated by the mean of all electrode data in the partition; C target is the preset target ion concentration;

[0107] S44: The concentration deviation ΔC calculated in S43 is 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: According to the adjustment parameters in S44, instructions are sent to the multi-point feeding unit in S2 and the intelligent stirring unit in S3 respectively, so as to dynamically adjust the feeding rate, stirring speed and blade angle of each partition, so that the ion concentration of each partition gradually approaches the target value; through the above steps, the multi-point ion selective electrode can be used to monitor the ion concentration in each partition in real time, and the feeding and stirring can be dynamically adjusted through the closed-loop control unit to ensure that the ion concentration of each partition reaches a balanced state.

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

[0110] S441: Receive the concentration deviation ΔC of each partition in the closed-loop control unit i The concentration deviation of each partition is analyzed to determine the size and direction of the deviation. The partitions that need incremental adjustment or decremental adjustment are classified by comparing the deviation data with the preset adjustment threshold T. The comparison formula is:

[0111]

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

[0113] S442: According to the deviation analysis results obtained in S441, the final feed adjustment rate of each partition is calculated for optimization based on the preliminary adjustment parameters in S23; when D i =1, increase the feeding rate; when D i = -1, reduce the feed rate; when D i =0, maintain the current feeding rate; the final feeding rate adjustment formula is: Q i,final =Q i,adjust +K q ΔC i ·D i , where Q i,final is the final feed adjustment rate of the i-th partition; Q i,adjustK is the feed rate initially adjusted in S23; q is the feed adjustment factor, which is used to further optimize the feed rate according to the deviation;

[0114] S443: For stirring speed adjustment, based on concentration deviation ΔC i Calculate the final adjustment value of stirring speed for each partition ω i,final , according to D i In the direction of the stirring speed of each partition, increase or decrease the adjustment value, the formula is: ω i,final =ω i +K ω ΔC i ·D i , where ω i,final is the final adjustment value of the stirring speed of the i-th partition; ω i is the current stirring speed; K ω is the stirring speed adjustment coefficient, which is used to control the stirring speed adjustment amount;

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

[0116] S5 specifically includes:

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

[0118] S52: During the injection process of S51, the concentration of the crystal nucleation inducer in the reactor is monitored in real time using a concentration sensor to ensure that it is maintained within the set range. 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, and stops the inducer injection at this time point, so that the metal ions in the reactor form crystal nuclei under the action of the inducer, thereby achieving the initial generation of crystal nuclei;

[0120] S54: After the crystal nucleus is initially generated, the ultrasonic vibration unit is started, and the ultrasonic frequency and power are set;

[0121] S55: After the ultrasonic parameters of S54 are set, the solution inside the reactor is subjected to uniform vibration using an ultrasonic vibration unit, 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, precise injection of the crystal nucleus inducing agent and ultrasonic-assisted uniform distribution 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: 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 V is set. 0 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 sedimentation;

[0124] S62: According to the multi-stage design of the solid-liquid separation unit, the flow rate is lowered in each stage of the separator; let the flow rate of the nth stage be V n , the flow rate of each stage of the separator is reduced proportionally to achieve the step-by-step sedimentation of particles; the formula is: V n+1 =V n ×(1-R), where V n+1 V is the flow rate of the n+th stage separator; n is the flow rate of the nth stage separator; R is the flow rate reduction ratio, which is set according to the sedimentation rate and separator design parameters to ensure uniform sedimentation of particles;

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

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

[0127] S7 specifically includes:

[0128] S71: Before the precursor particles separated from the multi-stage slow-release solid-liquid separation unit are fed into the drying device, the particles are pre-distributed in the feed area through a vibrating screen to eliminate particle agglomeration and allow the particles to be evenly spread in the drying device;

[0129] S72: according to the particle size distribution, density and target drying rate of the precursor particles, a multi-point homogenizing airflow nozzle is arranged in the drying device, including setting the flow rate, temperature and humidity parameters of the airflow, so that the airflow flows stably during the drying process to ensure uniform distribution of the particles in the entire drying area;

[0130] S73: The air flow distribution and flow rate of each nozzle are monitored in real time by an air flow sensor installed in the drying device. If uneven air flow is detected, the nozzle air flow is automatically adjusted according to the sensor feedback to eliminate local air flow fluctuations and ensure that the air flow evenly covers all particle surfaces;

[0131] S74: During the drying process, use optical or laser particle distribution monitoring equipment to monitor the distribution state of particles in the drying device in real time to ensure that the distribution uniformity of particles in the drying area meets the preset requirements; if the particle distribution deviates from the set state, make slight adjustments through the homogenizing airflow to make the particles evenly distributed again;

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

[0133] S76: After drying is completed, the uniformly dried precursor particles are collected from the drying device and finally packaged to ensure that the collected precursor materials meet the standard requirements in terms of ion concentration and particle uniformity, and provide high-quality precursor products for the subsequent production of lithium-ion battery ternary positive electrode materials; through the above steps, using homogenized airflow control and real-time distribution monitoring, the uniformity of the precursor particles after drying and the consistency of ion concentration can be effectively guaranteed, forming a lithium-ion battery ternary positive electrode material precursor product with stable quality and uniformity.

[0134] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0135] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as 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: The following steps are involved: S1: According to the predetermined ternary cathode material ratio, the fluid behavior in the reactor is modeled using simulation software, and the reactor is divided into several partitions to obtain the fluid flow characteristics and ion concentration distribution in each partition; 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 keep the concentration of ions in each partition consistent; S3: Based on the partitioned fluid characteristics modeled in S1, the intelligent stirring unit is used to dynamically adjust the stirring speed and mode in the reactor, so that the solutions in each partition of the reactor can be fully mixed and the difference in ion concentration can be reduced; S4: multiple ion selective electrodes are arranged in each partition to monitor the concentration of nickel, cobalt, manganese or aluminum ions, and the monitored concentration data is fed back to the closed-loop control unit to balance the ion concentration in each partition by adjusting the feed rate in S2 and the stirring parameters in S3; S5: In the solution environment after S4 closed-loop control, the uniform generation of crystal nuclei is achieved through the precise injection of crystal nucleation inducing agents; then the ultrasonic vibration unit is used to assist the uniform distribution of crystal nuclei, providing consistent initial conditions for the subsequent crystallization process; S6: introducing the slurry after the reaction into a multi-stage slow-release solid-liquid separation unit to gradually separate the precursor material particles, and controlling the liquid flow rate to obtain a uniform solid sedimentation effect to ensure the separation integrity of the obtained precursor; S7: Dry the separated precursor material particles and control the particle distribution through homogenized airflow so that the dried precursor particles maintain uniform ion concentration, and finally form a uniform lithium-ion battery ternary positive electrode material precursor product.

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

3. The control method of a lithium-ion battery ternary cathode material precursor production system according to claim 1, characterized in that: The S15 specifically includes: S151: In the simulation software, based on the partition model optimized in S14, the ion concentration monitoring points of each partition are set, and the coordinates and position of each monitoring point are defined; S152: Based on the data collected in S151, the time step is set, and the rate of change of the ion concentration over time is calculated with the metal ions nickel, cobalt, manganese or aluminum as the target; S153: Based on the concentration change rate calculated in S152, the ion concentration of each partition is gradually updated and corrected by 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 value of each monitoring point is numerically integrated to generate concentration distribution data for each partition, and the data is stored in a table form.

4. The control method of a lithium-ion battery ternary cathode material precursor production system according to claim 1, characterized in that: The S2 specifically includes: S21: According to the partition positions divided in S1, an independent feed port is installed at the entrance position of each partition so that the solution can be accurately delivered to the designated partition. Each feed port is connected to its own flow control valve to ensure that the solution injection position of each partition corresponds to the concentration control requirements of the partition; S22: installing an ion concentration sensor and a flow sensor on the fluid pipeline of each partition, obtaining the concentration data of nickel, cobalt, manganese or aluminum ions in real time through the ion concentration sensor, and monitoring the flow value of each feed port through the flow sensor; S23: According to the ion concentration data of each partition collected in S22 and the preset target concentration value, the feed rate adjustment parameter of each partition is calculated by a proportional integral differential control algorithm to determine the real-time adjustment value of the feed increment or decrement; S24: Using the feed rate adjustment parameters calculated in S23, the feed rate of each feed port is adjusted by adjusting the flow control valve to ensure that the ion concentration of each partition gradually approaches the target concentration.

5. The control method of a lithium-ion battery ternary cathode material precursor production system according to claim 1, characterized in that: The S3 specifically includes: S31: according to the fluid dynamics model established in S1, initial stirring parameters are set according to the flow characteristics of each partition, including stirring speed and angle of stirring blades; S32: Based on the concentration sensor installed in S22, the concentration data of nickel, cobalt, manganese or aluminum ions are collected in real time, the current ion concentration of each partition is obtained, and the concentration difference value between the partitions is calculated using the data; S33: Based on the concentration difference value obtained in S32, a stirring speed adjustment value and a blade angle adjustment value of each partition are calculated by a feedback control algorithm to reduce the concentration difference within the partition; S34: Using the stirring speed and blade angle adjustment parameters calculated by S33, the speed and angle of the stirrer are adjusted in real time through the intelligent stirring unit to achieve the optimal stirring state of each partition.

6. The control method of a lithium-ion battery ternary cathode material precursor production system according to claim 1, characterized in that: The S4 specifically includes: S41: arranging ion selective electrodes at predetermined positions within each partition, each electrode being specifically used to detect the corresponding nickel, cobalt, manganese or aluminum ion concentration; S42: Real-time concentration data is obtained through the ion selective electrodes in each partition to form the instantaneous ion concentration C of each electrode. i,j , where C i,j represents the target ion concentration at the jth electrode in the i-th partition; S43: Compare the electrode data collected in S42 with the preset target concentration and calculate the concentration deviation ΔC of each partition i ; S44: The concentration deviation ΔC calculated in S43 is 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; S45: According to the adjustment parameters in S44, instructions are sent to the multi-point feeding unit in S2 and the intelligent stirring unit in S3 respectively, so as to dynamically adjust the feeding rate, stirring speed and blade angle of each partition so that the ion concentration of each partition gradually approaches the target value.

7. The control method of a lithium-ion battery ternary cathode material precursor production system according to claim 6, characterized in that: The S44 specifically includes: S441: Receive the concentration deviation ΔC of each partition in the closed-loop control unit i The concentration deviation of each partition is analyzed to determine the size and direction of the deviation. The partitions that need incremental adjustment or decremental adjustment are classified by comparing the deviation data with the preset adjustment threshold T. The comparison formula is: Among them, D i Indicates the adjustment direction of the i-th partition; ΔC i is the concentration deviation of the ith partition; T is the preset concentration deviation threshold; S442: According to the deviation analysis results obtained in S441, the final feed adjustment rate of each partition is calculated for optimization based on the preliminary adjustment parameters in S23; when D i =1, increase the feeding rate; when D i = -1, reduce the feed rate; when D i =0, maintain the current feeding rate; the final feeding rate adjustment formula is: Q i,final =Q i,adjust +K q ·ΔC i ·D i , where Q i,final is the final feed adjustment rate of the i-th partition; Q i,adjust K is the feed rate initially adjusted in S23; q is the feed adjustment factor, which is used to further optimize the feed rate according to the deviation; S443: For stirring speed adjustment, based on concentration deviation ΔC i Calculate the final adjustment value of stirring speed for each partition ω i,final , according to D i In the direction of the stirring speed of each partition, increase or decrease the adjustment value, the formula is: ω i,final =ω i +K ω ·ΔC i ·D i , where ω i,final is the final adjustment value of the stirring speed of the i-th partition; ω i is the current stirring speed; K ω is the stirring speed adjustment coefficient; S444: Based on the concentration deviation ΔC i and adjust direction D i , calculate the final adjustment value θ of the stirring blade angle i,final , to ensure that the mixing effect of each partition is more uniform; the formula is: θ i,final =θ i +K θ ·ΔC i ·D i , where θ i,final is the final adjustment value of the stirring blade angle in the i-th partition; θ i is the current blade angle; K θ is the blade angle adjustment factor.

8. The control method of a lithium-ion battery ternary cathode material precursor production system according to claim 1, characterized in that: The S5 specifically includes: S51: Calculate the injection rate of the crystal nucleus inducing agent according to the target ion concentration in the solution and the volume in the reactor to ensure that the concentration of the inducing agent in the reactor reaches the preset inducing concentration to induce the initial formation of crystal nuclei; the formula is: Among them, R induce is the injection rate of the crystal nucleus inducing agent; V reactor is the total volume of the reactor; C induce is the target concentration of the inducer; t induce The time period for induction agent infusion; S52: During the injection process of S51, the concentration sensor is used to monitor the concentration of the crystal 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; S53: After the inducer concentration reaches the target concentration, the control system sets a stop time point for the inducer injection, and stops the inducer injection at this time point, so that the metal ions in the reactor form crystal nuclei under the action of the inducer; S54: After the crystal nucleus is initially generated, the ultrasonic vibration unit is started, and the ultrasonic frequency and power are set; S55: After the ultrasonic parameters of S54 are set, the solution inside the reactor is subjected to uniform vibration by using an ultrasonic vibration unit, so that the crystal nuclei are evenly distributed in the solution under the action of ultrasonic vibration to avoid local concentration.

9. The control method of a lithium-ion battery ternary cathode material precursor production system according to claim 1, characterized in that: The S6 specifically includes: S61: introducing the slurry after the reaction is completed from the reactor into the first-stage separator of the multi-stage slow-release solid-liquid separation unit, and setting the initial flow rate V0 to ensure that the particles begin to settle in the first-stage separator; S62: According to the multi-stage design of the solid-liquid separation unit, the flow rate is lowered in each stage of the separator; let the flow rate of the nth stage be V n , the flow rate of each stage of the separator is reduced proportionally to achieve the step-by-step sedimentation of particles; the formula is: V n+1 =V n ×(1-R), where V n+1 V is the flow rate of the n+th stage separator; n is the flow rate of the nth stage separator; R is the flow rate reduction ratio; S63: A flow rate sensor is installed at the liquid outlet of each stage separator to monitor the current liquid flow rate V in real time. n,real , and calculate the set value V n When a difference is detected, the flow rate difference is adjusted through the feedback control unit to ensure that the actual flow rate is always maintained within the allowable range of the target flow rate. S64: After multiple stages of slow-release separation, the settled precursor particles are finally collected at the bottom of the last stage separator.

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

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