Method and system for simulating small mass changes during the preparation of high-nickel cathode materials

Abstract

The present invention discloses a method and system for simulating minute mass changes during the preparation of a high-nickel cathode material. The method comprises the following steps: subdividing the two main reaction processes of the high-nickel cathode material based on chemical reaction mechanisms and expert knowledge; studying the precursor element and the lithium source LiOH·H2O element involved in the sintering process of the high-nickel cathode material based on the segmented results; obtaining the particle number variation pattern of each chemical substance based on the Arrhenius formula and reaction kinetics formula in combination with corresponding experimental data; studying the differences between the reaction processes of the element and the mixture based on data and information from non-isothermal thermogravimetric experiments and differential scanning calorimetry thermal analysis experiments; and finding the coupling parts between the reactions based on the differences between the two types of element reactions and the mixture reactions in combination with mechanism analysis; studying the coupling parts, and proposing a modeling method for the corresponding coupling parts based on experimental data and chemical mechanisms. The variation relationship of the reaction coupling parts at different heating rates is obtained, and a parameter identification method is used to solve the parameters within the functional relationship obtained for each reaction coupling part.

Description

Technical Field

[0001] The present invention relates to the technical field of preparation of high-nickel positive electrode materials, and in particular discloses a method and system for simulating slight mass changes under dual main reaction coupling during the preparation of high-nickel positive electrode materials. Background Art

[0002] Lithium-ion batteries (LIBs) play a crucial role in addressing environmental pollution and resource scarcity. Their high capacity and pollution-free nature make them one of the most important energy storage devices of the future, sparking a wave of research. Cathode materials are crucial to the development of LIBs. However, due to the long sintering time and complex sintering environment, ensuring the quality of LIB materials is difficult. Understanding the microscopic state of cathode materials throughout the sintering process is crucial to the performance of the final product.

[0003] High-nickel positive electrode materials are mainly sintered in a roller kiln. The roller kiln consists of two front and rear gas exchange chambers and 27 heating zones. Each heating zone is 1.62 meters long, with a total length of 47 meters. The batch material sintering cycle is 24.99 hours. During sintering, the temperature required for the reaction is supplied by electric heating through two sets of upper and lower silicon carbon rods. Oxygen is supplied through the bottom air inlet and the top air exhaust port to provide the required atmosphere conditions for the reaction. A thermocouple temperature sensor is also provided to measure the temperature information in the furnace. In the roller kiln, the temperature of each temperature zone is determined according to the sintering system. The sintering of the roller kiln is a long-term and spatial span process, which makes the actual reaction evolution process of the material in the furnace complex and unclear, and the energy quality requirements are unclear. The temperature and oxygen flow rates between the many temperature zones in the furnace are different, and they are interconnected and coupled with each other, resulting in uneven material reaction evolution and a very complex chemical reaction process.

[0004] Due to the influence of these factors, the oxidation reaction process of high-nickel cathode materials also suffers from unclear reaction mechanisms and coupling with thermal decomposition reactions. Furthermore, the mass change during the oxidation reaction is too flat, inconsistent with the corresponding mechanism.

[0005] Therefore, the existing technology does not address the coupling between the oxidation reaction and thermal decomposition reaction of high-nickel positive electrode materials. The reason for the quality change in the oxidation process is unclear, and the mechanism and research methods of the coupling process are not clear. This is a technical problem that needs to be solved urgently. Summary of the Invention

[0006] The present invention provides a method and system for simulating tiny mass changes during the preparation process of high-nickel positive electrode materials, aiming to solve the technical problems in the prior art that there is no mutual coupling between the oxidation reaction and thermal decomposition reaction of high-nickel positive electrode materials, the cause of the mass change during the oxidation process is unclear, and the mechanism and research method of the coupling process are unclear.

[0007] One aspect of the present invention relates to a method for simulating slight mass changes during the preparation of a high-nickel positive electrode material, comprising the following steps:

[0008] The two main reaction processes of high nickel cathode materials are subdivided based on chemical reaction mechanisms and expert knowledge;

[0009] According to the segmented results, the precursor and lithium source LiOH·H2O involved in the sintering process of high nickel cathode materials were studied separately.

[0010] According to the Arrhenius formula and reaction kinetics formula, combined with the corresponding experimental data, the variation law of the number of particles of each chemical substance is obtained;

[0011] Based on the data and information from non-isothermal thermogravimetric experiments and differential scanning calorimetry thermal analysis experiments, the differences between the reaction processes of the single substance and the mixture are studied. Based on the differences between the two types of single substance reactions and the mixture reactions, combined with mechanism analysis, the coupling parts between the reactions are found;

[0012] Focusing on the coupling part, the experimental data and chemical mechanism were combined to propose a modeling method for the corresponding coupling part, and the changing relationship of the reaction coupling part under different heating rates was obtained. The parameter identification method was used to solve the parameters in the functional relationship obtained for each reaction coupling part.

[0013] Furthermore, according to the Arrhenius formula and the reaction kinetics formula, combined with the corresponding experimental data, in the step of obtaining the change law of the number of particles of each chemical substance, the rate constant of the relevant reaction is calculated according to the Arrhenius formula. The rate constant of the relevant reaction is:

[0014]

[0015] Where k is the reaction rate, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, and T is the reaction temperature;

[0016] Assume that at time t, the number of particles of reactant a is The number of generated particles is Then define the reaction rate α at that moment t for:

[0017]

[0018] Among them, α t is the reaction rate, is the number of particles of reactant a, is the number of particles of reactant a at the initial moment.

[0019] Furthermore, according to the Arrhenius formula and the reaction kinetics formula, combined with the corresponding experimental data, the reaction kinetics discretization model of the decomposition reaction in the step of the variation law of the number of particles of each chemical substance is obtained as follows:

[0020]

[0021] Among them, α t+1 is the reaction rate at time t+1, α t is the reaction rate, Δt is the unit time interval, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, T t is the temperature at time t; f(α t ) is the mechanism function at time t;

[0022] Then in a discrete time step, the change in the reaction rate of substance a is Δα t for:

[0023]

[0024] Among them, Δα t is the change in the reaction rate of substance a, α t+1 is the reaction rate at time t+1, α t is the reaction rate, Δt is the unit time interval, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, T t is the temperature at time t; f(α t ) is the mechanism function at time t;

[0025] According to the reaction rate α t The change in the reaction rate with substance a, Δα t , calculate the change in the number of particles of reactant a at time t. The change in the number of particles of reactant a at time t is:

[0026]

[0027] in, is the change in the number of particles of reactant a at time t, is the number of particles of reactant a at the initial moment; Δt is the unit time interval, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, T t is the temperature at time t; f(α t ) is the mechanism function at time t.

[0028] Furthermore, we studied the coupling part, combined the experimental data with the chemical mechanism, and proposed a modeling method for the corresponding coupling part. We obtained the change relationship of the reaction coupling part under different heating rates. In the step of solving the parameters in the functional relationship obtained for each reaction coupling part using the parameter identification method, we combined the mass changes of the decomposition and oxidation reactions to obtain the slight mass change in the final oxidation stage. The calculation formula is as follows:

[0029]

[0030] Where m(%) is the small mass change during the oxidation stage. NCM 811 O2 thermal decomposition mass, m LiOH (%) is the thermal decomposition mass of LiOH.

[0031] Furthermore, we studied the coupling part, combined the experimental data with the chemical mechanism, and proposed a modeling method for the corresponding coupling part. We obtained the changing relationship of the reaction coupling part under different heating rates, and used the parameter identification method to solve the parameters in the functional relationship obtained for each reaction coupling part. We considered using the PSO algorithm to identify the model parameters. The fitness function of the particle swarm algorithm is shown in the following formula:

[0032]

[0033] Among them, J is the fitness function of the particle swarm algorithm, T is the temperature data obtained from actual experiments, is the temperature estimate obtained by the mechanism function;

[0034] In order to prevent the algorithm from falling into local optimality, a local adaptive mutation operator is added for adjustment:

[0035]

[0036]

[0037] Where, j = 1, 2, ..., G is the number of iterations, i = 1, 2, ..., Size is the population size; r1, r2 are random values ​​from 0 to 1; c1 is the local learning factor, c2 is the global learning factor, V i 、X i are the particle speed and position respectively, p is the optimal position of the individual, BestS is the optimal position of the population, V i j+1 is the particle speed at the next moment, is the particle position at the next moment, and w(t) is the weight transferred at moment t.

[0038] Another aspect of the present invention relates to a system for simulating small mass changes during the preparation of high-nickel positive electrode materials, comprising:

[0039] A subdivision module is used to subdivide the two main reaction processes of high-nickel cathode materials based on chemical reaction mechanisms and expert knowledge;

[0040] The research module is used to study the precursor element and lithium source LiOH·H2O element involved in the sintering process of high-nickel cathode materials based on the segmented results.

[0041] The acquisition module is used to obtain the variation pattern of the number of particles of each chemical substance based on the Arrhenius formula and reaction kinetics formula combined with the corresponding experimental data;

[0042] The search module is used to study the differences between the reaction processes of single substances and mixtures based on the data and information of non-isothermal thermogravimetric experiments and differential scanning calorimetry thermal analysis experiments. Based on the differences between the two types of single substance reactions and the reactions of mixtures, combined with mechanism analysis, the coupling parts between the reactions are found;

[0043] The calculation module is used to study the coupling part, combine experimental data with chemical mechanisms, propose a modeling method for the corresponding coupling part, obtain the change relationship of the reaction coupling part under different heating rates, and use parameter identification methods to solve the parameters in the functional relationship obtained for each reaction coupling part.

[0044] Furthermore, in the acquisition module, the rate constant of the relevant reaction is calculated according to the Arrhenius formula. The rate constant of the relevant reaction is:

[0045]

[0046] Where k is the reaction rate, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, and T is the reaction temperature;

[0047] Assume that at time t, the number of particles of reactant a is The number of generated particles is Then define the reaction rate α at that moment t for:

[0048]

[0049] Among them, α t is the reaction rate, is the number of particles of reactant a, is the number of particles of reactant a at the initial moment.

[0050] Furthermore, in the acquisition module, the reaction kinetics discretization model of the decomposition reaction is:

[0051]

[0052] Among them, α t+1 is the reaction rate at time t+1, α t is the reaction rate, Δt is the unit time interval, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, T t is the temperature at time t; f(α t ) is the mechanism function at time t;

[0053] Then in a discrete time step, the change in the reaction rate of substance a is Δα t for:

[0054]

[0055] Among them, Δα t is the change in the reaction rate of substance a, α t+1 is the reaction rate at time t+1, α t is the reaction rate, Δt is the unit time interval, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, T t is the temperature at time t; f(α t ) is the mechanism function at time t;

[0056] According to the reaction rate α t The change in the reaction rate with substance a, Δα t , calculate the change in the number of particles of reactant a at time t. The change in the number of particles of reactant a at time t is:

[0057]

[0058] in, is the change in the number of particles of reactant a at time t, is the number of particles of reactant a at the initial moment; Δt is the unit time interval, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, T t is the temperature at time t; f(α t ) is the mechanism function at time t.

[0059] Furthermore, in the calculation module, the mass changes of the decomposition and oxidation reactions are combined to obtain the small mass change in the final oxidation stage. The calculation formula is as follows:

[0060]

[0061] Where m(%) is the small mass change during the oxidation stage. NCM 811 O2 thermal decomposition mass, mLiOH (%) is the thermal decomposition mass of LiOH.

[0062] Furthermore, in the calculation module, the PSO algorithm is considered to identify the model parameters. The fitness function of the particle swarm algorithm is shown in the following formula:

[0063]

[0064] Among them, J is the fitness function of the particle swarm algorithm, T is the temperature data obtained from actual experiments, is the temperature estimate obtained by the mechanism function;

[0065] In order to prevent the algorithm from falling into local optimality, a local adaptive mutation operator is added for adjustment:

[0066]

[0067]

[0068] Where, j = 1, 2, ..., G is the number of iterations, i = 1, 2, ..., Size is the population size; r1, r2 are random values ​​from 0 to 1; c1 is the local learning factor, c2 is the global learning factor, V i 、X i are the particle speed and position respectively, p is the optimal position of the individual, BestS is the optimal position of the population, V i j+1 is the particle speed at the next moment, is the particle position at the next moment, and w(t) is the weight transferred at moment t.

[0069] The beneficial effects achieved by the present invention are:

[0070] The present invention provides a method and system for simulating minute mass changes during the preparation of a high-nickel cathode material. The method comprises the following steps: subdividing the two main reaction processes of the high-nickel cathode material based on chemical reaction mechanisms and expert knowledge; studying the precursor element and the lithium source LiOH·H2O element involved in the sintering process of the high-nickel cathode material based on the segmented results; obtaining the particle number variation pattern of each chemical substance based on the Arrhenius formula and reaction kinetics formula in combination with corresponding experimental data; studying the differences between the reaction processes of the element and the mixture based on data and information from non-isothermal thermogravimetric experiments and differential scanning calorimetry thermal analysis experiments; and finding the coupling parts between the reactions based on the differences between the two types of element reactions and the mixture reactions in combination with mechanism analysis; studying the coupling parts, and proposing a modeling method for the corresponding coupling parts based on experimental data and chemical mechanisms. The variation relationship of the reaction coupling parts at different heating rates is obtained, and a parameter identification method is used to solve the parameters within the functional relationship obtained for each reaction coupling part. The method and system for simulating tiny mass changes during the preparation of high-nickel positive electrode materials provided by the present invention innovatively analyze the coupling parts between the main reactions of high-nickel positive electrode materials. It not only studies the reactions of single substances, but also effectively solves the coupling problems between various reactions. At the same time, it obtains the mass change law of the oxidation stage during the sintering process of high-nickel materials, which provides a basis for subsequent in-depth research on the oxidation reaction process and the mass change law of the entire microscopic reaction process. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 A schematic flow chart of an embodiment of a method for simulating slight mass changes during the preparation of a high-nickel positive electrode material provided by the present invention;

[0072] Figure 2 A schematic diagram showing the segmentation of chemical reactions of high-nickel cathode materials at a certain heating rate based on chemical mechanisms and expert knowledge;

[0073] Figure 3 This is a comparison chart of the thermogravimetric changes during the thermal decomposition of LiOH·H2O and the oxidation process in the mixture;

[0074] Figure 4 This is a functional block diagram of an embodiment of a system for simulating small mass changes during the preparation of high-nickel positive electrode materials provided by the present invention.

[0075] Description of Figure Numbers:

[0076] 10. Segmentation module; 20. Research module; 30. Acquisition module; 40. Search module; 50. Calculation module. DETAILED DESCRIPTION

[0077] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0078] like Figures 1 to 3 As shown, the first embodiment of the present invention provides a method for simulating slight mass changes during the preparation of a high-nickel positive electrode material, comprising the following steps:

[0079] Step S100: subdividing the two main reaction processes of the high-nickel positive electrode material based on the chemical reaction mechanism and expert knowledge.

[0080] The experimental samples used were the 811 high-nickel cathode material precursor and the lithium source LiOH·H2O from a lithium-ion battery ternary cathode material manufacturer. The experimental data were obtained from non-isothermal thermogravimetric experiments and differential scanning calorimetry thermal analysis experiments conducted using this precursor and lithium source at different heating rates.

[0081] In view of the long time and complex and changeable sintering process of high nickel cathode materials, the microscopic chemical reaction process of high nickel cathode materials is segmented by using the thermogravimetric data obtained from non-isothermal thermogravimetric experiments at a certain heating rate and the unit heat flow rate data obtained from differential scanning calorimetry thermal analysis experiments, combined with chemical mechanisms and expert knowledge, such as Figure 2 shown.

[0082] The sintering process begins with the thermal decomposition of LiOH·H2O. As the temperature rises, LiOH·H2O decomposes into LiOH, and then dehydrates to decompose into Li2O. The process of dehydrated water is independent of the entire sintering process. At this time, the temperature is low and the other substances have basically not reacted. When lithium hydroxide dehydrates, the temperature is high and the precursor has undergone complex chemical reactions, including the preferential oxidation of cobalt and manganese and the dehydration of nickel hexahedrons. This part is the stage with the greatest quality loss. Subsequently, with the infiltration of lithium, nickel begins to oxidize, and the structure gradually takes shape, forming the final product, as shown in formulas (1)-(7):

[0083] ①LiOH·H2O thermal decomposition process

[0084] In the kiln, LiOH·H2O undergoes a two-stage decomposition reaction: LiOH·H2O removes crystal water to generate LiOH, which occurs at 40-60°C; LiOH decomposes to generate Li2O, which occurs at 460-470°C:

[0085] 2LiOH·H2O→2LiOH+2H2O(1)

[0086] 2LiOH (s) →Li2O (s) +H2O (g) (2)

[0087] ②Precursor thermal decomposition process

[0088] The precursor is a high nickel material. Comparing the thermogravimetric curves of the precursor and Ni(OH)2, we can see that they have similar thermodynamic properties. Therefore, cobalt and manganese hydroxides are used as auxiliary means to study the properties of Ni(OH)2. The thermal decomposition of Ni(OH)2 mainly occurs at around 210-800℃:

[0089] Ni(OH)2→NiO+H2O(3)

[0090] Ni(OH)2+OH - →NiOOH+H2O(4)

[0091] ③Oxidation process

[0092] At about 60-217℃, cobalt and manganese are preferentially oxidized. The hydrogen ions around the cobalt atoms are removed, and Li + Occupy H + Theoretically, the mass of the vacancy created remains unchanged, but in reality, the mass is slightly reduced.

[0093] Co(OH)2→CoO+H2O(5)

[0094] Mn(OH)2→MnO+H2O(6)

[0095] At around 380-800℃, nickel oxidation reaction occurs to form product LiNi 0.8 Co 0.1 Mn 0.1 O2.

[0096] Ni x Co y Mn 1-x-y O+0.5Li2O+0.25O2→LiNi x Co y Mn 1-x-y O2(7)

[0097] Through the above segmentation, the complex microscopic mechanism of the material is analyzed, which provides great help for the exploration of microscopic mechanism, simulation of microscopic evolution and judgment of the quality of sintered material products.

[0098] Step S200: studying the precursor element and the lithium source LiOH·H2O element involved in the sintering process of the high-nickel positive electrode material according to the segmented results.

[0099] Based on previous research, the chemical properties of the precursor and the lithium source element when reacting alone were obtained using the experimental data of the precursor and the lithium source element when reacting alone.

[0100] Step S300: According to the Arrhenius formula and the reaction kinetics formula, combined with the corresponding experimental data, the variation pattern of the number of particles of each chemical substance is obtained.

[0101] According to the Arrhenius formula and the reaction kinetics formula, combined with the corresponding experimental data, the law of particle number change is obtained. According to the Arrhenius formula, the rate constant of the relevant reaction is calculated. The rate constant of the relevant reaction is:

[0102]

[0103] In formula (8), k is the reaction rate, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, and T is the reaction temperature;

[0104] Assume that at time t, the number of particles of reactant a is The number of generated particles is Then define the reaction rate α at that moment t for:

[0105]

[0106] In formula (9), α t is the reaction rate, is the number of particles of reactant a, is the number of particles of reactant a at the initial moment.

[0107] The reaction kinetics discretization model of the decomposition reaction is:

[0108]

[0109] In formula (10), α t+1 is the reaction rate at time t+1, α t is the reaction rate, Δt is the unit time interval, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, T t is the temperature at time t; f(α t ) is the mechanism function at time t;

[0110] Then in a discrete time step, the change in the reaction rate of substance a is Δα t for:

[0111]

[0112] In formula (11), Δα t is the change in the reaction rate of substance a, α t+1 is the reaction rate at time t+1, α tis the reaction rate, Δt is the unit time interval, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, T t is the temperature at time t; f(α t ) is the mechanism function at time t;

[0113] According to the reaction rate α t The change in the reaction rate with substance a, Δα t , calculate the change in the number of particles of reactant a at time t. The change in the number of particles of reactant a at time t is:

[0114]

[0115] In formula (12), is the change in the number of particles of reactant a at time t, is the number of particles of reactant a at the initial moment; Δt is the unit time interval, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, T t is the temperature at time t; f(α t ) is the mechanism function at time t.

[0116] Step S400: Based on the data and information of the non-isothermal thermogravimetric experiment and the differential scanning calorimetry thermal analysis experiment, the differences between the reaction processes of the single substance and the mixture are studied. Based on the differences between the two types of single substance reactions and the mixture reactions, combined with mechanism analysis, the coupling parts between the reactions are found.

[0117] By comparing the differences between the single substance and the mixture, we can find the coupling between the multiple reactions of the high nickel cathode material. In particular, to solve the problem that the mass of the oxidation reaction process remains basically unchanged, we compare the thermogravimetric changes of the thermal decomposition process of LiOH·H2O with the thermogravimetric changes of the oxidation process in the mixture. Figure 2 Comparative research revealed that during the oxidation process, the thermal decomposition of the LiOH·H2O element showed a significant mass decrease, while the mass of the mixture remained relatively steady, with no downward trend. Analysis of chemical mechanisms and expert knowledge suggests that this gradual mass change is due to the offsetting effect of the mass increase during oxidation and the mass loss during thermal decomposition.

[0118] Step S500: Study the coupling part, combine experimental data with chemical mechanism, propose a modeling method for the corresponding coupling part, obtain the change relationship of the reaction coupling part under different heating rates, and use parameter identification method to solve the parameters in the functional relationship obtained for each reaction coupling part.

[0119] The coupling between the main reactions of the high-nickel cathode materials found was studied, and corresponding solutions were proposed. Among them, in order to solve the problem that the mass of the oxidation reaction process basically does not change, a simulation method for small mass changes under the coupling of two main reactions was proposed. Combined with the thermal decomposition model, the mass dropped significantly during the dehydration process from 450 to 500 ° C. However, there was no obvious mass drop in the mixture. This phenomenon of small mass changes is because the decomposition reaction and the oxidation reaction occur simultaneously, resulting in mass complementarity, which is manifested as the increase in mass of the oxidation process occurring at this stage is offset by the decrease in mass of the thermal decomposition process. From the perspective of thermal decomposition, the thermal decomposition mass reduced in this stage can be further calculated based on the thermal decomposition process of LiOH, as shown in formula (13):

[0120]

[0121] In formula (13), is the initial mass of LiOH, is the mass of LiOH at time t, k LiOH is the mass loss ratio of LiOH M LiOH is the molar mass of LiOH.

[0122] From the perspective of oxidation, the mass change of this process is closely related to the progress of oxidation. Oxidation is related to the phase change of the material, which is manifested as a change in the number of reactant and product particles. Therefore, the progress of the oxidation reaction can be obtained. The number of particles at time t and the total number of initial precursor particles Determine, where the number of particles is determined by formula (12), so that the mass increased by the oxidation reaction can be obtained, as shown in formula (14).

[0123]

[0124] In formula (14), is the mass assigned to the unit oxidation reaction product particle, represents the molar mass of the generated oxide, NCM at time t 811 The number of particles of O2, α t represents the oxidation progress at time t, Indicates the mass of the generated oxide.

[0125] Finally, combining the mass changes of the decomposition and oxidation reactions, the formula for the small mass change in the final oxidation stage is as follows:

[0126]

[0127] In formula (15), m (%) is the small mass change during the oxidation stage, NCM 811 O2 thermal decomposition mass, m LiOH (%) is the thermal decomposition mass of LiOH.

[0128] Regarding the relationship between oxidation progress and quality change during the oxidation process represented by formula (15), traditional parameter selection methods such as k-fold cross-validation are highly subjective, computationally time-consuming, and have a limited range of manually set parameters. These methods often do not provide optimal parameters and cannot optimize the combined performance of mean square error, mean absolute error, and maximum absolute error. The particle swarm optimization algorithm (PSO) has the advantages of easy implementation, high accuracy, and fast convergence. Therefore, the PSO algorithm is considered for model parameter identification. The fitness function of the particle swarm algorithm is shown in formula (16):

[0129]

[0130] In formula (16), J is the fitness function of the particle swarm algorithm, T is the temperature data obtained from actual experiments, Is the temperature estimate obtained by the mechanism function. To prevent the algorithm from falling into local optimality, a local adaptive mutation operator is added for adjustment:

[0131]

[0132] In formula (17), j = 1, 2, ..., G is the number of iterations, i = 1, 2, ..., Size is the population size; r1, r2 are random values ​​from 0 to 1; c1 is the local learning factor, c2 is the global learning factor, V i 、X i are the particle speed and position respectively, p is the optimal position of the individual, BestS is the optimal position of the population, V i j+1 is the particle speed at the next moment, is the particle position at the next moment, and w(t) is the weight transferred at moment t.

[0133] The present invention provides a method for simulating minute mass changes during the preparation of high-nickel cathode materials. Compared with the prior art, the method subdivides the two main reaction processes of the high-nickel cathode material based on chemical reaction mechanisms and expert knowledge. According to the segmented results, a precursor element and a lithium source LiOH·H2O element involved in the sintering process of the high-nickel cathode material are studied separately. According to the Arrhenius formula and the reaction kinetics formula, combined with corresponding experimental data, the variation pattern of the particle number of each chemical substance is obtained. According to the data and information of non-isothermal thermogravimetric experiments and differential scanning calorimetry thermal analysis experiments, the differences between the reaction processes of the element and the mixture are studied. Based on the differences between the two types of element reactions and the reaction of the mixture, the coupling parts between the reactions are found in combination with mechanism analysis. The coupling parts are studied, and a modeling method for the corresponding coupling parts is proposed in combination with experimental data and chemical mechanisms. The variation relationship of the reaction coupling parts at different heating rates is obtained, and the parameters within the functional relationship obtained for each reaction coupling part are solved using a parameter identification method. The method for simulating tiny mass changes during the preparation of high-nickel positive electrode materials provided by the present invention innovatively analyzes the coupling parts between the main reactions of high-nickel positive electrode materials. It not only studies the reactions of single substances, but also effectively solves the coupling problems between various reactions. At the same time, it obtains the mass change law of the oxidation stage during the sintering process of high-nickel materials, which provides a basis for subsequent in-depth research on the oxidation reaction process and the mass change law of the entire microscopic reaction process.

[0134] like Figure 4 As shown, Figure 4The functional block diagram of an embodiment of a system for simulating small mass changes in the preparation process of high-nickel positive electrode materials provided by the present invention. In this embodiment, the system for simulating small mass changes in the preparation process of high-nickel positive electrode materials provided by the present invention includes a segmentation module 10, a research module 20, an acquisition module 30, a search module 40 and a calculation module 50, wherein the segmentation module 10 is used to segment the two main reaction processes of the high-nickel positive electrode material based on the chemical reaction mechanism and expert knowledge; the research module 20 is used to study the precursor element and the lithium source LiOH·H2O element involved in the sintering process of the high-nickel positive electrode material according to the segmentation results; the acquisition module 30 is used to calculate the mass change of the precursor element according to the Arrhenius formula and the lithium source LiOH·H2O element ... The reaction kinetics formula is combined with the corresponding experimental data to obtain the variation law of the number of particles of each chemical substance; the search module 40 is used to study the difference between the reaction process of the single substance and the mixture based on the data and information of the non-isothermal thermogravimetric experiment and the differential scanning calorimetry thermal analysis experiment, and according to the difference between the two types of single substance reactions and the mixture reactions, combined with the mechanism analysis, to find the coupling part between the reactions; the calculation module 50 is used to study the coupling part, combine the experimental data with the chemical mechanism, propose the modeling method of the corresponding coupling part, obtain the variation relationship of the reaction coupling part under different heating rates, and use the parameter identification method to solve the parameters in the functional relationship obtained for each reaction coupling part.

[0135] The experimental samples used in subdivision module 10 come from the 811-type high-nickel cathode material precursor and lithium source LiOH·H2O produced by a lithium-ion battery ternary cathode material manufacturer. The experimental data comes from non-isothermal thermogravimetric experiments and differential scanning calorimetry thermal analysis experiments conducted at different heating rates using this precursor and lithium source.

[0136] In view of the long time and complex and changeable sintering process of high nickel cathode materials, the microscopic chemical reaction process of high nickel cathode materials is segmented by using the thermogravimetric data obtained from non-isothermal thermogravimetric experiments at a certain heating rate and the unit heat flow rate data obtained from differential scanning calorimetry thermal analysis experiments, combined with chemical mechanisms and expert knowledge, such as Figure 2 shown.

[0137] The sintering process begins with the thermal decomposition of LiOH·H2O. As the temperature rises, LiOH·H2O decomposes into LiOH, and then dehydrates into Li2O. The process of dehydrated water is independent of the entire sintering process. At this time, the temperature is low and the other substances have basically not reacted. When lithium hydroxide dehydrates, the temperature is high and the precursor has undergone complex chemical reactions, including the preferential oxidation of cobalt and manganese and the dehydration of nickel hexahedrons. This part is the stage with the greatest quality loss. Subsequently, with the infiltration of lithium, nickel begins to oxidize, and the structure gradually takes shape, forming the final product, as shown in equations (18)-(24):

[0138] ①LiOH·H2O thermal decomposition process

[0139] In the kiln, LiOH·H2O undergoes a two-stage decomposition reaction: LiOH·H2O removes crystal water to generate LiOH, which occurs at 40-60°C; LiOH decomposes to generate Li2O, which occurs at 460-470°C:

[0140] 2LiOH·H2O→2LiOH+2H2O(18)

[0141] 2LiOH (s) →Li2O (s) +H2O (g) (19)

[0142] ②Precursor thermal decomposition process

[0143] The precursor is a high nickel material. Comparing the thermogravimetric curves of the precursor and Ni(OH)2, we can see that they have similar thermodynamic properties. Therefore, cobalt and manganese hydroxides are used as auxiliary means to study the properties of Ni(OH)2. The thermal decomposition of Ni(OH)2 mainly occurs at around 210-800℃:

[0144] Ni(OH)2→NiO+H2O(20)

[0145] Ni(OH)2+OH - →NiOOH+H2O(21)

[0146] ③Oxidation process

[0147] At about 60-217℃, cobalt and manganese are preferentially oxidized. The hydrogen ions around the cobalt atoms are removed, and Li + Occupy H + Theoretically, the mass of the vacancy created remains unchanged, but in reality, the mass is slightly reduced.

[0148] Co(OH)2→CoO+H2O (22)

[0149] Mn(OH)2→MnO+H2O (23)

[0150] At around 380-800℃, nickel oxidation reaction occurs to form product LiNi 0.8 Co 0.1 Mn 0.1 O2.

[0151] Ni x Co y Mn 1-x-y O+0.5Li2O+0.25O2→LiNi x Co y Mn 1-x-y O2 (24)

[0152] Through the above segmentation, the complex microscopic mechanism of the material is analyzed, which provides great help for the exploration of microscopic mechanism, simulation of microscopic evolution and judgment of the quality of sintered material products.

[0153] The research module 20 obtains the chemical properties of the precursor and the lithium source element when they react alone, based on the experimental data of the individual reactions of the precursor and the lithium source element, according to the previous research.

[0154] The acquisition module 30 obtains the particle number variation law based on the Arrhenius formula and the reaction kinetics formula in combination with the corresponding experimental data, and calculates the rate constant of the relevant reaction based on the Arrhenius formula. The rate constant of the relevant reaction is:

[0155]

[0156] In formula (25), k is the reaction rate, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, and T is the reaction temperature;

[0157] Assume that at time t, the number of particles of reactant a is The number of generated particles is Then define the reaction rate α at that moment t for:

[0158]

[0159] In formula (26), α t is the reaction rate, is the number of particles of reactant a, is the number of particles of reactant a at the initial moment.

[0160] The reaction kinetics discretization model of the decomposition reaction is:

[0161]

[0162] In formula (27), α t+1 is the reaction rate at time t+1, α t is the reaction rate, Δt is the unit time interval, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, T t is the temperature at time t; f(α t ) is the mechanism function at time t;

[0163] Then in a discrete time step, the change in the reaction rate of substance a is Δα t for:

[0164]

[0165] In formula (28), Δα t is the change in the reaction rate of substance a, α t+1 is the reaction rate at time t+1, α t is the reaction rate, Δt is the unit time interval, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, T t is the temperature at time t; f(α t ) is the mechanism function at time t;

[0166] According to the reaction rate α t The change in the reaction rate with substance a, Δα t , calculate the change in the number of particles of reactant a at time t. The change in the number of particles of reactant a at time t is:

[0167]

[0168] In formula (29), is the change in the number of particles of reactant a at time t, is the number of particles of reactant a at the initial moment; Δt is the unit time interval, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, T t is the temperature at time t; f(α t ) is the mechanism function at time t.

[0169] The search module 40 searches for the coupling between multiple reactions of the high nickel cathode material by comparing the differences between the single substance and the mixture. In order to solve the problem that the mass of the oxidation reaction process remains basically unchanged, the thermogravimetric change of the thermal decomposition process of LiOH·H2O is compared with the thermogravimetric change of the oxidation process in the mixture, such as Figure 2 Comparative research revealed that during the oxidation process, the thermal decomposition of the LiOH·H2O element showed a significant mass decrease, while the mass of the mixture remained relatively steady, with no downward trend. Analysis of chemical mechanisms and expert knowledge suggests that this gradual mass change is due to the offsetting effect of the mass increase during oxidation and the mass loss during thermal decomposition.

[0170] The calculation module 50 studies the coupling between the main reactions of the found high-nickel positive electrode materials and proposes corresponding solutions. Among them, in order to solve the problem that the mass of the oxidation reaction process does not change basically, a simulation method of small mass changes under the coupling of two main reactions is proposed. Combined with the thermal decomposition model, the mass decreases significantly during the dehydration process from 450 to 500 ° C. However, there is no obvious mass decrease in the mixture. This phenomenon of small mass changes is because the decomposition reaction and the oxidation reaction occur simultaneously, resulting in mass complementarity, which is manifested as the increase in mass of the oxidation process occurring at this stage is offset by the decrease in mass of the thermal decomposition process. From the perspective of thermal decomposition, the thermal decomposition mass reduced in this stage can be further calculated based on the thermal decomposition process of LiOH, as shown in formula (30):

[0171]

[0172] In formula (30), is the initial mass of LiOH, is the mass of LiOH at time t, k LiOH is the mass loss ratio of LiOH M LiOH is the molar mass of LiOH.

[0173] From the perspective of oxidation, the mass change of this process is closely related to the progress of oxidation. Oxidation is related to the phase change of the material, which is manifested as a change in the number of reactant and product particles. Therefore, the progress of the oxidation reaction can be obtained. The number of particles at time t and the total number of initial precursor particles Determine, where the number of particles is determined by formula (29), so that the mass increased by the oxidation reaction can be obtained as shown in formula (31).

[0174]

[0175] In formula (31), is the mass assigned to the unit oxidation reaction product particle, represents the molar mass of the generated oxide, NCM at time t 811 The number of particles of O2, α t represents the oxidation progress at time t, Indicates the mass of the generated oxide.

[0176] Finally, combining the mass changes of the decomposition and oxidation reactions, the formula for the small mass change in the final oxidation stage is as follows:

[0177]

[0178] In formula (32), m (%) is the small mass change during the oxidation stage, NCM 811 O2 thermal decomposition mass, m LiOH (%) is the thermal decomposition mass of LiOH.

[0179] Regarding the relationship between oxidation progress and quality change during the oxidation process represented by formula (32), traditional parameter selection methods such as k-fold cross-validation are highly subjective, computationally time-consuming, and have a limited range of manually set parameters. These methods often do not provide optimal parameters and cannot optimize the combined performance of mean square error, mean absolute error, and maximum absolute error. The particle swarm optimization algorithm (PSO) has the advantages of easy implementation, high accuracy, and fast convergence. Therefore, the PSO algorithm is considered for model parameter identification. The fitness function of the particle swarm algorithm is shown in formula (33):

[0180]

[0181] In formula (33), J is the fitness function of the particle swarm algorithm, T is the temperature data obtained from actual experiments, Is the temperature estimate obtained by the mechanism function. To prevent the algorithm from falling into local optimality, a local adaptive mutation operator is added for adjustment:

[0182]

[0183] In formula (34), j = 1, 2, ..., G is the number of iterations, i = 1, 2, ..., Size is the population size; r1, r2 are random values ​​from 0 to 1; c1 is the local learning factor, c2 is the global learning factor, V i 、X i are the particle speed and position respectively, p is the optimal position of the individual, BestS is the optimal position of the population, V i j+1 is the particle speed at the next moment, is the particle position at the next moment, and w(t) is the weight transferred at moment t.

[0184] Compared with the prior art, the system for simulating minute mass changes during the preparation of high-nickel cathode materials provided by the present invention employs a subdivision module 10, a research module 20, an acquisition module 30, a search module 40, and a calculation module 50 to subdivide the two main reaction processes of the high-nickel cathode material based on chemical reaction mechanisms and expert knowledge. Based on the segmentation results, the precursor element and the lithium source LiOH·H2O element involved in the sintering process of the high-nickel cathode material are studied separately. The particle number variation pattern of each chemical substance is obtained based on the Arrhenius formula and reaction kinetics formula in combination with corresponding experimental data. The differences between the reaction processes of the element and the mixture are studied based on data and information from non-isothermal thermogravimetric experiments and differential scanning calorimetry thermal analysis experiments. Based on the differences between the two types of element reactions and the reaction of the mixture, coupled components between the reactions are identified in combination with mechanism analysis. The coupled components are studied, and a modeling method for the corresponding coupled components is proposed in combination with experimental data and chemical mechanisms. The variation relationship of the reaction coupled components at different heating rates is obtained, and the parameters within the functional relationships obtained for each reaction coupled component are solved using a parameter identification method. The system for simulating minute mass changes during the preparation of high-nickel positive electrode materials provided by the present invention innovatively analyzes the coupling between the main reactions of high-nickel positive electrode materials. It not only studies the reactions of single substances, but also effectively solves the coupling problems between various reactions. At the same time, it obtains the mass change law of the oxidation stage during the sintering process of high-nickel materials, providing a basis for subsequent in-depth research on the oxidation reaction process and the mass change law of the entire microscopic reaction process.

[0185] Although preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they are aware of the basic inventive concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the invention. Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the invention. Thus, the present invention is intended to include such changes and modifications as fall within the scope of the claims and their equivalents.

Claims

1. A method for simulating small mass changes during the preparation of high-nickel positive electrode materials, characterized in that: The following steps are involved: The two main reaction processes of high nickel cathode materials are subdivided based on chemical reaction mechanisms and expert knowledge; According to the segmented results, the precursor and lithium source LiOH·H2O involved in the sintering process of high nickel cathode materials were studied separately. According to the Arrhenius formula and reaction kinetics formula, combined with the corresponding experimental data, the variation law of the number of particles of each chemical substance is obtained; Based on the data and information from non-isothermal thermogravimetric experiments and differential scanning calorimetry thermal analysis experiments, the differences between the reaction processes of the single substance and the mixture are studied. Based on the differences between the two types of single substance reactions and the mixture reactions, combined with mechanism analysis, the coupling parts between the reactions are found; Focusing on the coupling part, we combined experimental data with chemical mechanisms to propose a modeling method for the corresponding coupling part, obtained the changing relationship of the reaction coupling part at different heating rates, and used parameter identification methods to solve the parameters in the functional relationship obtained for each reaction coupling part. Among them, the small mass change in the final oxidation stage is obtained by combining the mass changes of decomposition and oxidation reactions, and the calculation formula is as follows: Where m(%) is the small mass change during the oxidation stage. NCM 811 O2 thermal decomposition mass, m LiOH (%) is the thermal decomposition mass of LiOH; Consider using the PSO algorithm to identify the model parameters. The fitness function of the particle swarm algorithm is shown in the following formula: Among them, J is the fitness function of the particle swarm algorithm, T is the temperature data obtained from actual experiments, is the temperature estimate obtained by the mechanism function; In order to prevent the algorithm from falling into local optimality, a local adaptive mutation operator is added for adjustment: Where, j = 1, 2, ..., G is the number of iterations, i = 1, 2, ..., Size is the population size; r1, r2 are random values ​​from 0 to 1; c1 is the local learning factor, c2 is the global learning factor, V i 、X i are the particle speed and position respectively, p is the optimal position of the individual, BestS is the optimal position of the population, V i j+1 is the particle speed at the next moment, is the particle position at the next moment, and w(t) is the weight transferred at moment t.

2. The method for simulating slight mass changes during the preparation of high-nickel cathode materials according to claim 1, characterized in that: In the step of obtaining the variation law of the number of particles of each chemical substance according to the Arrhenius formula and the reaction kinetics formula in combination with the corresponding experimental data, the rate constant of the relevant reaction is calculated according to the Arrhenius formula. The rate constant of the relevant reaction is: Where k is the reaction rate, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, and T is the reaction temperature; Assume that at time t, the number of particles of reactant a is The number of generated particles is Then define the reaction rate α at that moment t for: Among them, α t is the reaction rate, is the number of particles of reactant a, is the number of particles of reactant a at the initial moment.

3. The method for simulating slight mass changes during the preparation of high-nickel cathode materials according to claim 2, characterized in that: In the step of obtaining the variation law of the number of particles of each chemical substance according to the Arrhenius formula and the reaction kinetics formula in combination with the corresponding experimental data, the reaction kinetics discretization model of the decomposition reaction is: Among them, α t+1 is the reaction rate at time t+1, α t is the reaction rate, Δt is the unit time interval, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, T t is the temperature at time t; f(α t ) is the mechanism function at time t; Then in a discrete time step, the change in the reaction rate of substance a is Δα t for: Among them, Δα t is the change in the reaction rate of substance a, α t+1 is the reaction rate at time t+1, α t is the reaction rate, Δt is the unit time interval, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, T t is the temperature at time t; f(α t ) is the mechanism function at time t; According to the reaction rate α t The change in the reaction rate with substance a, Δα t , calculate the change in the number of particles of reactant a at time t. The change in the number of particles of reactant a at time t is: in, is the change in the number of particles of reactant a at time t, is the number of particles of reactant a at the initial moment; Δt is the unit time interval, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, T t is the temperature at time t; f(α t ) is the mechanism function at time t.

4. A system for simulating small mass changes during the preparation of high-nickel cathode materials, characterized in that: include: A research module (20) is used to study the precursor element and the lithium source LiOH·H2O element involved in the sintering process of the high nickel cathode material according to the segmented results; An acquisition module (30) is used to obtain the variation law of the number of particles of each chemical substance according to the Arrhenius formula and the reaction kinetics formula in combination with the corresponding experimental data; A search module (40) is used to study the difference between the reaction process of the single substance and the mixture based on the data and information of the non-isothermal thermogravimetric experiment and the differential scanning calorimetry thermal analysis experiment, and to find the coupling part between the reactions based on the difference between the two types of single substance reactions and the mixture reactions in combination with the mechanism analysis; A calculation module (50) is used to study the coupling part, combine experimental data with chemical mechanism, propose a modeling method for the corresponding coupling part, obtain the change relationship of the reaction coupling part under different heating rates, and use parameter identification method to solve the parameters in the functional relationship obtained for each reaction coupling part; Among them, the small mass change in the final oxidation stage is obtained by combining the mass changes of decomposition and oxidation reactions, and the calculation formula is as follows: Where m(%) is the small mass change during the oxidation stage. NCM 811 O2 thermal decomposition mass, m LiOH (%) is the thermal decomposition mass of LiOH; Consider using the PSO algorithm to identify the model parameters. The fitness function of the particle swarm algorithm is shown in the following formula: Among them, J is the fitness function of the particle swarm algorithm, T is the temperature data obtained from actual experiments, is the temperature estimate obtained by the mechanism function; In order to prevent the algorithm from falling into local optimality, a local adaptive mutation operator is added for adjustment: Where, j = 1, 2, ..., G is the number of iterations, i = 1, 2, ..., Size is the population size; r1, r2 are random values ​​from 0 to 1; c1 is the local learning factor, c2 is the global learning factor, V i 、X i are the particle speed and position respectively, p is the optimal position of the individual, BestS is the optimal position of the population, V i j+1 is the particle speed at the next moment, is the particle position at the next moment, and w(t) is the weight transferred at moment t.

5. The system for simulating minute mass changes during the preparation of high-nickel cathode materials according to claim 4, characterized in that: In the acquisition module (30), the rate constant of the relevant reaction is calculated according to the Arrhenius formula. The rate constant of the relevant reaction is: Where k is the reaction rate, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, and T is the reaction temperature; Assume that at time t, the number of particles of reactant a is The number of generated particles is Then define the reaction rate α at that moment t for: Among them, α t is the reaction rate, is the number of particles of reactant a, is the number of particles of reactant a at the initial moment.

6. The system for simulating minute mass changes during the preparation of high-nickel cathode materials according to claim 5, characterized in that: In the acquisition module (30), the reaction kinetics discretization model of the decomposition reaction is: Among them, α t+1 is the reaction rate at time t+1, α t is the reaction rate, Δt is the unit time interval, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, T t is the temperature at time t; f(α t ) is the mechanism function at time t; Then in a discrete time step, the change in the reaction rate of substance a is Δα t for: Among them, Δα t is the change in the reaction rate of substance a, α t+1 is the reaction rate at time t+1, α t is the reaction rate, Δt is the unit time interval, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, T t is the temperature at time t; f(α t ) is the mechanism function at time t; According to the reaction rate α t The change in the reaction rate with substance a, Δα t , calculate the change in the number of particles of reactant a at time t. The change in the number of particles of reactant a at time t is: in, is the change in the number of particles of reactant a at time t, is the number of particles of reactant a at the initial moment; Δt is the unit time interval, A is the pre-exponential factor, E is the activation energy, R is the molar gas constant, T t is the temperature at time t; f(α t ) is the mechanism function at time t.

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