Carbon fiber and sodium iron phosphate composite positive electrode material and preparation method thereof

Abstract

The application relates to the technical field of electrode positive material preparation, in particular to a carbon fiber and sodium iron phosphate composite positive material and a preparation method thereof. The method comprises the following steps: mixing a NaFePO4 base body, aluminum oxide and multi-walled carbon nanotubes, adding deionized water to stir to obtain a mixture, then performing coarse grinding treatment, fine grinding treatment and spray drying to obtain powder material; collecting infrared thermal imaging images at each moment in the spray drying process, obtaining a powder adsorption index and a dust adsorption influence coefficient of the infrared thermal imaging images at each moment, completing prediction of a next moment material liquid conveying flow in the spray drying process, and performing carbon coating treatment, crushing and magnetic field removal on the powder material to obtain the carbon fiber and sodium iron phosphate composite positive material. The application aims to improve the cycle stability and electrochemical performance of the material.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electrode positive material preparation, in particular to a carbon fiber and sodium iron phosphate composite positive material and a preparation method thereof. BACKGROUND

[0002] The carbon fiber and sodium iron phosphate composite positive material plays a key role in sodium-ion batteries. Compared with lithium-ion batteries, sodium-ion batteries use abundant sodium resources, have higher safety and environmental friendliness. However, sodium-ion batteries still face challenges such as insufficient energy density and short cycle life. By continuously developing high-performance positive materials such as carbon fiber and sodium iron phosphate composite materials, and improving battery material science and electrochemical technology, sodium-ion batteries are expected to make greater breakthroughs in the field of energy storage. In the future, with the growth of energy demand and the increasing demand for renewable energy, sodium-ion batteries as a cheap and sustainable energy storage solution will have broad application prospects, providing reliable support for electric vehicles, energy storage systems and other fields, and promoting the sustainable development of the energy field.

[0003] In the preparation of the carbon fiber and sodium iron phosphate composite positive material, a spray dryer is usually used to dry the prepared liquid, and the size of the liquid flow will directly affect the thickness of the liquid thin layer and the residence time in the drying chamber. Larger liquid flow will result in the formation of thicker liquid thin layer, which will reduce the residence time of the liquid in the drying chamber, and accordingly the heating time will also be reduced. This may cause part of the liquid to be discharged from the spray dryer without being fully heated, affecting the drying effect, while too small liquid flow may cause the drying air in the drying chamber to be unable to effectively transfer heat, also affecting the drying effect, and thus reducing the cycle stability and electrochemical performance of the carbon fiber and sodium iron phosphate composite positive material. SUMMARY

[0004] To solve the above technical problems, the purpose of the present application is to provide a carbon fiber and sodium iron phosphate composite positive material and a preparation method thereof, and the technical solution adopted is as follows:

[0005] In a first aspect, the present application provides a preparation method of a carbon fiber and sodium iron phosphate composite positive material, which comprises the following steps:

[0006] S1: mixing NaFePO4 matrix, aluminum oxide and multi-walled carbon nanotubes, and then adding deionized water to stir to obtain a mixture;

[0007] S2: after the coarse grinding treatment of the mixed material in S1, fine grinding treatment is performed, and then powder material is obtained by spray drying; infrared thermal imaging images at each moment in the spray drying process are collected; a powder adsorption index of the infrared thermal imaging image at each moment is obtained according to the temperature distribution characteristics of each data point and the adjacent data points in the infrared thermal imaging image at each moment; a dust adsorption influence coefficient of the infrared thermal imaging image at each moment is obtained according to the powder adsorption index of the infrared thermal imaging image at each moment and the temperature change of the data points in the infrared thermal imaging image at adjacent moments; and the prediction of the material liquid conveying flow at the next moment in the spray drying process is completed according to the dust adsorption influence coefficient of the infrared thermal imaging image at each moment.

[0008] S3: the powder material in S2 is subjected to carbon coating treatment.

[0009] S4: after the carbon coating treatment in S3, crushing and magnetic removal are performed to obtain a carbon fiber and sodium iron phosphate composite positive electrode material.

[0010] Preferably, in the process of obtaining the mixed material, the mass ratio of the NaFePO4 base body, aluminum oxide, multi-walled carbon nanotubes and deionized water is 65.38:0.35:1:153.85.

[0011] Preferably, the coarse grinding treatment is performed by using a stirring mill with internal zirconium balls with a diameter of 0.5 mm to obtain slurry with a D50 particle size of 3.0 μm.

[0012] Preferably, the fine grinding treatment is performed by using a sand mill with internal zirconium balls with a diameter of 0.2 mm to obtain slurry with a D50 particle size of 0.6 μm.

[0013] Preferably, the spray drying comprises:

[0014] The spray drying is performed by using a spray dryer, the frequency of the atomizer of the spray dryer is 25 Hz, the material liquid flow is 10-15 L / h, the air supply temperature is 280℃, and the exhaust air temperature is 100℃.

[0015] Preferably, the powder adsorption index of the infrared thermal imaging image at each moment comprises:

[0016] Each data point in the infrared thermal imaging image corresponds to each position in the drying chamber of the spray dryer, and each micro-position is recorded; the temperature values of any data point and the data points on the 4 adjacent domains of the any data point in the infrared thermal imaging image at each moment are arranged in descending order to form a position sequence of the any data point; a fitting curve of the temperature values of each data point and the same position data points in all previous infrared thermal imaging images is obtained; and the second-order difference value of each data point is calculated by using the fitting curve.

[0017] For each infrared thermal imaging image, the DTW distance of the position sequence of the same position data points in the infrared thermal imaging images of any two time points is calculated, the inverse of the DTW distance is taken as the index of the exponential function with the natural constant as the base number, the difference between 1 and the calculation result of the exponential function is calculated, if the difference is less than or equal to the preset distance threshold, the external invariance judgment function value of the micro position of the corresponding data point is the difference, otherwise, the external invariance judgment function value of the micro position of the corresponding data point is 0;

[0018] The external invariance factor of the i-th micro position in the infrared thermal imaging image at the Z-th time point is denoted as The expression is:

[0019]

[0020] In the formula, K is the number of external invariance judgment function values of 0 in the infrared thermal imaging image at the Z-th time point, Z is the serial number of the infrared thermal imaging image collected at each time point, is the DTW distance of the position sequence of the data points corresponding to the i-th micro position in the infrared thermal imaging images at the p-th time point and the q-th time point, is the external invariance judgment function value of the i-th micro position in the infrared thermal imaging images at the p-th time point and the q-th time point;

[0021] The powder confidence factor of the i-th micro position in the infrared thermal imaging image at the Z-1-th time point is denoted as The expression is:

[0022]

[0023] In the formula, X is the number of micro positions contained in the infrared thermal imaging image, f i is the second-order difference value of the data points corresponding to the i-th micro position in the infrared thermal imaging image at the Z-1-th time point, and sig() is a sigmoid function;

[0024] The powder adsorption index of the infrared thermal imaging image at the Z-th time point is denoted as Fz Z , and the expression is:

[0025]

[0026] In the formula, is the DTW distance of the position sequence of the data points corresponding to the i-th micro position in the infrared thermal imaging images at the Z-th time point and the Z-1-th time point.

[0027] Preferably, the dust adsorption influence coefficient of the infrared thermal imaging image at each time point comprises:

[0028] For each infrared thermal imaging image, a preset window is constructed with each data point as the center, all data points in the window are clustered to obtain each cluster by using a clustering algorithm, the cluster containing the most data points is recorded as a main cluster, all data points in the main cluster are obtained as each vertex by using a convex hull algorithm, a sum value of a number of the vertices and a preset adjustment parameter greater than 0 is calculated, a ratio of a number of data points in the main cluster to the sum value is calculated, and a product of the ratio and a powder confidence factor of a corresponding micro position of a data point in a previous infrared thermal imaging image is taken as an adsorptive dust existence characteristic value of each micro position in each infrared thermal imaging image.

[0029] For each micro position in each infrared thermal imaging image, a standard deviation of temperature values of all data points in the main cluster is calculated, a negative of the standard deviation is taken as an index of an exponential function with a natural constant as a base number, and a product of a calculation result of the exponential function and the adsorptive dust existence characteristic value of the corresponding micro position in the previous infrared thermal imaging image is taken as an adsorptive characteristic value of each micro position in each infrared thermal imaging image.

[0030] A product of a mean value of the adsorptive characteristic values of all micro positions in each infrared thermal imaging image and the powder adsorption index is calculated and recorded as a first product, a negative of the first product is taken as an index of a first exponential function with a natural constant as a base number, and a calculation result of the first exponential function is taken as a dust adsorption influence coefficient of each infrared thermal imaging image.

[0031] Preferably, the prediction of the next-time feed liquid delivery flow in the spray drying process comprises:

[0032] For each infrared thermal imaging image, a negative of the dust adsorption influence coefficient is taken as an index of an exponential function with a natural constant as a base number, a product of a calculation result of the exponential function and a first preset value is calculated, and a sum value of the product and a second preset value is taken as a next-time feed liquid delivery flow value.

[0033] Preferably, the carbon coating treatment is to set the CVD furnace temperature to 800 DEG C, adjust the nitrogen and methane flow rates to 100 m3 / h and 150 m3 / h respectively, add the powder material for CVD coating when the oxygen content is reduced to below 10 ppm, and the coating time is 10 h; the pulverization is to use airflow pulverization, the gas source is high-temperature nitrogen at 120 DEG C, the airflow mill classification frequency is 25 Hz, the pulverization pressure is 0.40 Mpa, and the particle size of the obtained classified material is 2.0 μm; and the magnetic removal is to use an electromagnetic iron remover to remove the magnetism.

[0034] In a second aspect, the embodiments of the present application also provide a carbon fiber and sodium iron phosphate composite positive electrode material, which is prepared by the steps of the method described in any one of the above embodiments.

[0035] The present application has at least the following beneficial effects:

[0036] The present application analyzes the infrared thermal imaging images at different times in the drying chamber, constructs the powder adsorption index of the infrared thermal imaging images at each time based on the temperature distribution of adjacent data points and the DTW distance, reflects the influence degree of the adsorption of the powder in the drying chamber on the heat conduction performance of the surface in the drying chamber, thereby more accurately controls the flow of the liquid, then constructs the dust adsorption influence coefficient of the infrared thermal imaging images at each time based on the convex hull algorithm and the density clustering algorithm, reflects the influence relationship between each micro position and the surrounding area and the flow of the liquid, improves the uniformity in the drying process of the liquid, and combines the powder adsorption index and the dust adsorption influence coefficient to adaptively adjust the flow of the liquid, so that the spray dryer can accurately control the conveying flow of the liquid according to the probability of the adsorptive powder appearing in the drying chamber and its influence on the liquid, improve the drying effect of the liquid and the product quality, and further improve the cycle stability and the electrochemical performance of the carbon fiber and sodium iron phosphate composite positive electrode material. BRIEF DESCRIPTION OF DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art and the advantages thereof, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0038] Figure 1 A step flow chart of a carbon fiber and sodium iron phosphate composite positive electrode material preparation method provided by an embodiment of the present application is shown in the figure.

[0039] Figure 2 An infrared thermal imaging image acquisition schematic diagram is shown in the figure.

[0040] Figure 3 A carbon fiber and sodium iron phosphate composite positive electrode material industrial preparation flow chart is shown in the figure.

[0041] Figure 4 A schematic diagram of adjacent i micro positions is shown in the figure. DETAILED DESCRIPTION

[0042] In order to further clarify the technical means and effects taken by the present application to achieve the predetermined inventive purpose, the following describes in detail the specific implementation, structure, features and effects of a carbon fiber and sodium iron phosphate composite positive electrode material and a preparation method thereof according to the present application, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0043] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0044] The specific scheme of the carbon fiber and sodium iron phosphate composite positive electrode material and the preparation method thereof provided by the present application is described in detail below in combination with the accompanying drawings.

[0045] Embodiment 1 provides a preparation method of a carbon fiber and sodium iron phosphate composite positive electrode material. The preparation flow chart is shown in Figure 1 , and the specific preparation process is as follows:

[0046] Embodiment 1

[0047] S1: Prepare the slurry. Put 17 kg of NaFePO4 matrix, 90 g of aluminum oxide and 260 g of multi-walled carbon nanotubes into a premixing tank for mixing. Then, add 40 kg of deionized water and stir for 3 hours to obtain a mixture.

[0048] S2: Transfer the mixture to a stirring mill for coarse grinding, wherein zirconium balls with a diameter of 0.5 mm are used in the stirring mill. After coarse grinding, the obtained slurry has a D50 particle size of 3.0 μm. Then, transfer the slurry to a sand mill for fine grinding, wherein zirconium balls with a diameter of 0.2 mm are used in the sand mill. After fine grinding, the particle size D50 value of the slurry is reduced to 0.6 μm. Spray dry the slurry after fine grinding. The atomizer frequency of the spray dryer is 25 Hz, the feed liquid flow rate is 10-15 L / h, the air supply temperature is 280°C, and the exhaust air temperature is 100°C. After drying treatment, the final powder material is obtained. The specific value of the feed liquid flow rate is controlled by the following steps.

[0049] Step S001: Collect the infrared thermal imaging image in the drying chamber of the spray dryer and perform preprocessing.

[0050] When the slurry is sent into the spray dryer, the spray dryer first atomizes the slurry through a sprayer, and the liquid slurry is atomized into tiny droplets by the atomizer, so that the surface area is increased. The tiny droplets after atomization enter the drying chamber and are in contact with hot air. The drying chamber of the spray dryer is provided with a hot air generator or a heater. By heating the air, the temperature is increased. When the hot air contacts the tiny droplets, the water on the surface of the droplets evaporates rapidly, so that the droplets gradually decrease and form solid particles.

[0051] An endoscopic infrared thermal imager is installed above the drying chamber, which can collect infrared thermal images of the entire drying chamber. The specific position can be adjusted by the implementer. The infrared thermal imager is used to collect infrared thermal images of the interior of the drying chamber during the drying process at intervals. The collection interval is 0.5s. Non-local mean denoising algorithm and adaptive histogram equalization algorithm are used to denoise and enhance the collected infrared thermal images. The non-local mean denoising algorithm and adaptive histogram equalization algorithm are prior art, which will not be described in detail in this embodiment. The implementer can select other algorithms to denoise and enhance the acquired images according to the actual situation. The infrared thermal image acquisition schematic diagram is shown in Figure 2 .

[0052] In step S002, the powder adsorption index and the dust adsorption influence coefficient of the infrared thermal image at each time are obtained, and the next time liquid delivery flow in the spray drying process is predicted according to the dust adsorption influence coefficient of the infrared thermal image at each time.

[0053] Specifically, the infrared thermal images at each time in the slurry spray drying process are first collected; the powder adsorption index of the infrared thermal image at each time is obtained according to the temperature distribution characteristics of each data point and the adjacent data points in the infrared thermal image at each time; the dust adsorption influence coefficient of the infrared thermal image at each time is obtained according to the powder adsorption index of the infrared thermal image at each time and the temperature change of the data points in the adjacent infrared thermal image; and the next time liquid delivery flow in the spray drying process is predicted according to the dust adsorption influence coefficient of the infrared thermal image at each time. The specific carbon fiber and sodium iron phosphate composite positive electrode material industrial preparation process is shown in Figure 3 . The construction process of the predicted value of the liquid flow at each time is as follows:

[0054] When the slurry passes through the sprayer to the drying chamber for drying, the moisture evaporates rapidly, and in the process of moisture evaporation, the surface-attached salts or other ions may be taken away, especially in the case of faster drying speed, the migration speed of ions may not be able to keep up with the evaporation speed of moisture, and when the powders or particles move or contact in the drying chamber, they may rub against the inner surface of the drying chamber or other particles, causing the transfer of electrons, in the process, some materials may lose electrons and become positively charged, while other materials may gain electrons and become negatively charged. The imbalance of such charges leads to the accumulation of static electricity, causing the powders obtained after the evaporation of the slurry to be mutually adsorbed, resulting in dust accumulation and blockage of components such as the drying chamber and the spraying device, thereby affecting the normal operation of the spray dryer.

[0055] In the drying chamber, powder adsorption can cause local temperature changes. Since the adsorption of powder will affect the heat conduction performance of the inner surface of the drying chamber, a temperature difference will occur between the adsorbed area and the non-adsorbed area. The infrared thermal imager can detect these small temperature differences, and the adsorbed powder may exhibit different thermal radiation characteristics in the infrared spectrum range. The surface of the adsorbed powder may have different emissivity or reflectivity, which may cause a temperature difference compared to the non-adsorbed inner surface of the drying chamber.

[0056] From the moment the drying chamber starts working, the infrared thermal images in the drying chamber are collected using an infrared thermal imager. Assuming that Z infrared thermal images are collected from the moment the drying chamber starts working to the present moment, and there are X data points in each infrared thermal image, each data point in the image is mapped to a micro position inside the drying chamber. Taking the i-th micro position as an example, the four micro positions in the 4-neighborhood direction of the i-th micro position are denoted as neighbor i micro positions, as shown in the neighbor i micro position schematic diagram. Figure 4 The temperature values of any data point in the infrared thermal image at each time and the data points in the 4-neighborhood of the any data point are arranged in descending order to form the position sequence of the any data point. For the Z-th infrared thermal image, the temperature values of the i-th micro position at all previous times are obtained. Taking time as the horizontal axis and temperature value as the vertical axis, a fitting curve of all temperature values of the i-th micro position is obtained using the least squares method. The second-order difference value of the corresponding data point of the i-th micro position in the infrared thermal image at each time is obtained using the fitting curve, wherein the least squares method and the calculation of the second-order difference value are both known technologies, and this embodiment will not be described in detail.

[0057] According to the above analysis, the powder adsorption index of the infrared thermal image at each time is calculated, and the expression is:

[0058]

[0059]

[0060]

[0061]

[0062] In the formula, Let be the DTW distance between the data points corresponding to the i-th micro-position in the infrared thermal imaging images at time p and time q, where e is a natural constant and T1 is a preset distance threshold. In this embodiment, T1 = 0.3. Implementers can set this value according to actual conditions, and this embodiment does not impose any restrictions on it. Let be the external invariant judgment function value of the i-th micro-position in the infrared thermal imaging images at time p and time q;

[0063] Wp i Let K be the external invariant factor of the i-th micro-position in the infrared thermal image at time Z, K be the number of external invariant judgment function values ​​of 0 in the infrared thermal image at time Z, and Z be the sequence number of the infrared thermal image acquired at each time.

[0064] Let f be the powder confidence factor at the i-th micro-location in the infrared thermal image at time Z-1, where X is the number of micro-locations in the infrared thermal image, and f is the powder confidence factor at the i-th micro-location in the infrared thermal image. i Let be the second-order difference value of the data point corresponding to the i-th micro-position in the infrared thermal image at time Z-1, and sig() be the sigmoid function;

[0065] Fz Z Let Z be the powder adsorption index of the infrared thermal image at time Z. is the DTW distance of the position sequence of the data point corresponding to the i-th micro-position in the infrared thermal imaging images at time Z and time Z-1.

[0066] In the calculation of powder adsorption index, The similarity between two sequences is measured using the Dynamic Time Warped (DTW) distance. When the DTW distance is less than or equal to a preset distance threshold T1, the function returns a similarity value; when the distance is greater than the preset threshold T1, the function returns 0. This function is used to determine the similarity between sequences. Then Wp... i right The summation represents the similarity of infrared radiation at the same micro-location at different times. The greater the similarity, the more likely the i-th micro-location is in a long-term constant temperature state. When sig(f i The larger the value of Wp, the more drastic the temperature change at the i-th micro-location. i The smaller, The larger it becomes; The greater the value is, the greater the probability that the i-th micro position belongs to the adsorptive powder is, The greater the value is, the more likely two similar adsorptive powders exist at different time points, which means that the movement of the same adsorptive powder exists at the two time points, and the powder adsorption index Fz Z The greater the value is.

[0067] In the running drying chamber, the shape of the powder adsorption and the infrared radiation characteristics generated by the electrostatic force are random and uneven because the electrostatic force acting on the powder particles is affected by various factors, such as the randomness of the interaction between charges, the change of environmental conditions, the characteristics of the powder particles, etc. In addition, there is a random temperature distribution pattern inside the drying furnace, which makes the heat distribution at different positions similar to the heat distribution at the dust. In addition, the similarity of the surface conditions of the drying chamber and the electrostatic effect can also cause similar infrared radiation performance at different positions. Because the electrostatic force is uniformly distributed on the surface of the dust, the dust at different positions receives similar electrostatic force, resulting in consistent adsorption morphology and similar infrared radiation response after being heated. In addition, due to factors such as consistent surface characteristics and thermal conductivity, the temperature values of the dust at different positions are also close. Therefore, the temperature values of the adsorptive dust surface show a relatively close state.

[0068] In this embodiment, the infrared thermal imaging image at the Z-th time point collected is taken as an example, and a window with a size of N x N is constructed with each data point as the center. In this embodiment, N = 7, and the implementer can set it according to the actual situation, which is not limited in this embodiment. All data points in the window are clustered by using the DBSCAN density clustering algorithm. In this embodiment, the minimum point MinPT is set to 1, and the maximum radius is set to 0.3. The implementer can set it according to the actual situation, which is not limited in this embodiment. Each cluster is obtained, and the cluster containing the most data points is recorded as the main cluster. The GrahamScan convex hull algorithm is used for the main cluster. The convex hull algorithm outputs the vertices of the convex hull in a certain order. The order of these vertices constitutes the boundary of the convex hull. The number of vertices detected by the convex hull algorithm is recorded as R i The DBSCAN density clustering algorithm and the Graham Scan convex hull algorithm are both prior art known technologies, and will not be described in detail in this embodiment. The adsorptive feature value of each micro position in the infrared thermal imaging image at each time point is constructed, and the expression is as follows:

[0069]

[0070]

[0071] In the formula, Fz(i) is the adsorptive dust existence feature value of the i-th micro position in the infrared thermal imaging image at the Z-th time point, ​R is the powder confidence factor at the i-th micro-location in the infrared thermal image at time Z-1. i Let I be the number of vertices detected by the main cluster within the window corresponding to the data point at the i-th micro-location in the infrared thermal image at time Z. i ε is the number of data points in the window corresponding to the data point at the i-th micro-position in the infrared thermal imaging image at time Z. ε is a preset adjustment parameter greater than 0. In this embodiment, ε = 0.01. Implementers can set it according to the actual situation. This embodiment does not limit it.

[0072] Let be the adsorption characteristic value of the i-th micro-location in the infrared thermal image at time Z. Let be the characteristic value of adsorbed dust at the i-th micro-location in the infrared thermal image at time Z-1, where e is the natural constant and σ is the characteristic value of adsorbed dust. max Let be the standard deviation of the temperature values ​​of all data points in the main cluster within the window corresponding to the data point at the i-th micro-location in the infrared thermal image at time Z.

[0073] The characteristic value of adsorbent dust comprehensively considers confidence level, data density, and geometry, quantifying the degree of presence of adsorbent dust in the current image. The larger the value, the greater the probability that the i-th micro-position is subject to powder adsorption. This measures the shape characteristics of the main clusters. A larger value indicates that more data points within the primary cluster have fewer vertices in the enclosing polygon, resulting in a more regular shape of the primary cluster. The higher the probability that the corresponding window contains adsorbent dust, the better. The larger, It increases accordingly; while σ max This represents the degree of dispersion of temperature values ​​within the main clusters, σ max A larger value indicates a more uneven distribution, and it is less consistent with the characteristic of similar surface temperature values ​​of adsorbent dust. The smaller.

[0074] Step S003: Based on the adsorption characteristic values ​​of each micro-position in the infrared thermal imaging image at each time, control the flow rate of the liquid conveying and adaptively adjust the flow rate of the liquid.

[0075] When the powder adsorption effect occurs in the drying chamber, the method of reducing the flow rate of the feed liquid is usually adopted to reduce or avoid the occurrence of the powder adsorption problem. Reducing the flow rate of the feed liquid can effectively reduce the amount of dust generated in the drying chamber, thereby reducing the deposition of dust on the inner surface of the drying chamber. In addition, the lower flow rate of the feed liquid can also reduce the diffusion speed of the dust and reduce the distribution range of the dust in the drying chamber. At the same time, reducing the flow rate of the feed liquid can also help to reduce the friction and collision between dust particles, thereby reducing the generation of static electricity effect and further reducing the possibility of dust adsorption on the inner surface of the drying chamber. In summary, by reducing the flow rate of the feed liquid, the powder adsorption problem can be effectively controlled, the drying effect can be improved, the risk of failure of the spray dryer can be reduced, and the production safety can be ensured.

[0076] The dust adsorption influence coefficient of the infrared thermal imaging image at each moment is constructed, and the expression is:

[0077]

[0078] In the formula, FT Z is the dust adsorption influence coefficient of the infrared thermal imaging image at the Zth moment, is the adsorption characteristic value of the i th micro position in the infrared thermal imaging image at the Zth moment, X is the number of micro positions contained in the infrared thermal imaging image, and Fz Z is the powder adsorption index of the infrared thermal imaging image at the Zth moment, and e is a natural constant. The product is denoted as the first product, and the exponential function is denoted as the first exponential function.

[0079] When the feed liquid is transported, the flow rate of the transported feed liquid is between 10-15 L / h, and the control rule for transporting the flow rate of the feed liquid is:

[0080]

[0081] In the formula, Fr Z+1 is the flow rate of the feed liquid at the Z+1th moment, γ1 is the first preset value, γ2 is the second preset value, FT Z is the dust adsorption influence coefficient of the infrared thermal imaging image at the Zth moment, e is a natural constant, γ1=5 and γ2=10 in this embodiment, and the flow rate of the feed liquid is ensured to be between 10-15 L / h. The implementer can set it according to the actual situation, and this embodiment does not limit it.

[0082] When the dust adsorption influence coefficient is smaller, it represents that the powder adsorption effect caused by static electricity in the drying chamber is more serious. At this time, the flow rate of the feed liquid is reduced, and vice versa. The flow rate of the feed liquid is increased, and the adaptive adjustment of the flow rate of the feed liquid is completed.

[0083] ​S3: set the temperature of the CVD furnace to 800 DEG C, while adjusting the flow of nitrogen and methane to 100 m 3 and 150 m 3 After the oxygen content is reduced to below 10 ppm, start adding powder material to the CVD furnace for coating treatment, and the coating time is 10 hours.

[0084] S4: finally, perform airflow milling classification treatment, adjust the high-temperature nitrogen temperature to 120 DEG C, set the classification frequency to 25 Hz, and the crushing pressure is 0.40 Mpa, after laser particle size instrument testing, the particle size of the classified material is 2.0 mu m, after collecting the classified material, perform magnetic removal treatment through an electromagnetic iron remover, and obtain the carbon fiber and sodium iron phosphate composite positive electrode material.

[0085] Based on the same inventive concept as the above method, the present application also provides a carbon fiber and sodium iron phosphate composite positive electrode material, which is prepared by the steps of any one of the above-mentioned carbon fiber and sodium iron phosphate composite positive electrode material preparation method.

[0086] In summary, the present application combines the powder adsorption index and the dust adsorption influence coefficient to adaptively adjust the flow of the material liquid, so that the spray dryer can accurately control the delivery flow of the material liquid according to the probability of the adsorptive powder in the drying chamber and its influence, improve the drying effect of the material liquid and the product quality, and further improve the cycle stability and electrochemical performance of the carbon fiber and sodium iron phosphate composite positive electrode material.

[0087] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. The above describes a specific embodiment of the present application. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0088] Each embodiment in the present application is described in a progressive manner, and the same or similar parts between each embodiment can be referred to each other, and each embodiment mainly describes the difference from other embodiments.

[0089] The above-mentioned is only the preferred embodiment of the present application, and does not limit the present application, any modification, equivalent replacement, improvement, etc. made within the principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for preparing a composite cathode material of carbon fiber and sodium iron phosphate, characterized in that, The method includes the following steps: S1: Mix NaFePO4 matrix, alumina, and multi-walled carbon nanotubes, then add deionized water and stir to obtain a mixture; S2: The mixture in S1 is coarsely ground and then finely ground, followed by spray drying to obtain powder. Infrared thermal imaging images are collected at various times during the spray drying process. The powder adsorption index of the infrared thermal imaging images at each time moment is obtained based on the temperature distribution characteristics of each data point and its neighboring data points in the infrared thermal imaging images at each time moment. The dust adsorption influence coefficient of the infrared thermal imaging images at each time moment is obtained based on the powder adsorption index of the infrared thermal imaging images at each time moment and the temperature change of the data points in the infrared thermal imaging images at adjacent times moment. The flow rate of the liquid material at the next moment in the spray drying process is predicted based on the dust adsorption influence coefficient of the infrared thermal imaging images at each time moment. S3: Carbon coating treatment is applied to the powder material in S2; S4: After carbon coating treatment in S3, the material is crushed and demagnetized to obtain carbon fiber and sodium iron phosphate composite cathode material.

2. The method for preparing a carbon fiber and sodium iron phosphate composite cathode material according to claim 1, characterized in that, In the process of obtaining the mixture, the mass ratio of NaFePO4 matrix, alumina, multi-walled carbon nanotubes, and deionized water is 65.38:0.35:1:153.

85.

3. The method for preparing a carbon fiber and sodium iron phosphate composite cathode material according to claim 1, characterized in that, The coarse grinding process is carried out using a stirred mill with an internal zircon ball diameter of 0.5 mm to obtain a slurry with a D50 particle size of 3.0 μm.

4. The method for preparing a carbon fiber and sodium iron phosphate composite cathode material according to claim 1, characterized in that, The fine grinding process involves using a sand mill with an internal zirconium ball diameter of 0.2 mm to obtain a slurry with a D50 particle size of 0.6 μm.

5. The method for preparing a carbon fiber and sodium iron phosphate composite cathode material according to claim 1, characterized in that, The spray drying includes: Spray drying is performed using a spray dryer with an atomizer frequency of 25Hz, a liquid flow rate of 10-15L / h, an air supply temperature of 280℃, and an exhaust temperature of 100℃.

6. The method for preparing a carbon fiber and sodium iron phosphate composite cathode material according to claim 5, characterized in that, The powder adsorption index of the infrared thermal imaging images at each time point includes: Each data point in the infrared thermal imaging image corresponds to a position in the drying chamber of the spray dryer, and is denoted as a micro-position. With each data point as the center, the temperature values ​​of any data point in the infrared thermal imaging image at each time moment and the data points in the 4-neighborhood of the data point are arranged in descending order to form the position sequence of the data point. The fitting curve of the temperature value of each data point in the infrared thermal imaging image at each time moment and the data points at the same position in the infrared thermal imaging images at all previous times is obtained. The second difference value of each data point is calculated using the fitting curve. For infrared thermal imaging images at each time point, calculate the DTW distance of the position sequence of data points at the same position in infrared thermal imaging images at any two previous time points. Take the negative of the DTW distance as the exponent of an exponential function with the natural constant as the base, and calculate the difference between 1 and the calculation result of the exponential function. If the difference is less than or equal to a preset distance threshold, the external invariance judgment function value of the micro position of the corresponding data point is the difference; otherwise, the external invariance judgment function value of the micro position of the corresponding data point is 0. The external invariant factor at the i-th micro-position in the infrared thermal image at time Z is denoted as Wp. i The expression is: In the formula, K is the number of external invariant judgment function values ​​of 0 in the infrared thermal imaging image at time Z, and Z is the sequence number of the infrared thermal imaging image acquired at each time. Let be the DTW distance between the data points corresponding to the i-th micro-position in the infrared thermal imaging images at time p and time q. Let be the external invariant judgment function value of the i-th micro-position in the infrared thermal imaging images at time p and time q; The powder confidence factor at the i-th micro-location in the infrared thermal image at time Z-1 is denoted as . The expression is: In the formula, X is the number of micro-positions contained in the infrared thermal imaging image, and f i Let be the second-order difference value of the data point corresponding to the i-th micro-position in the infrared thermal image at time Z-1, and sig() be the sigmoid function; The powder adsorption index of the infrared thermal image at time Z is denoted as Fz. Z The expression is: In the formula, is the DTW distance of the position sequence of the data point corresponding to the i-th micro-position in the infrared thermal imaging images at time Z and time Z-1.

7. The method for preparing a carbon fiber and sodium iron phosphate composite cathode material according to claim 6, characterized in that, The dust adsorption influence coefficients of the infrared thermal imaging images at each time point include: For infrared thermal imaging images at each time moment, a preset window is constructed with each data point as the center. All data points within the window are clustered using a clustering algorithm to obtain each cluster. The cluster containing the most data points is recorded as the main cluster. All data points within the main cluster are obtained using a convex hull algorithm to obtain each vertex. The sum of the number of vertices and a preset adjustment parameter greater than 0 is calculated. The ratio of the number of data points in the main cluster to the sum is calculated. The product of the ratio and the powder confidence factor at the corresponding micro-position of the data point in the infrared thermal imaging image at the previous time moment is used as the characteristic value of the presence of adsorbed dust at each micro-position in the infrared thermal imaging image at each time moment. For each micro-location in the infrared thermal imaging image at each time moment, the standard deviation of the temperature values ​​of all data points in the main cluster is calculated. The negative of the standard deviation is used as the exponent of an exponential function with the natural constant as the base. The product of the calculated result of the exponential function and the adsorbent dust presence characteristic value of the corresponding micro-location in the infrared thermal imaging image at the previous time moment is used as the adsorbent characteristic value of each micro-location in the infrared thermal imaging image at each time moment. The product of the mean of the adsorption characteristic values ​​of all micro-locations in the infrared thermal imaging image at each time point and the powder adsorption index is calculated and denoted as the first product. The negative of the first product is taken as the exponent of the exponential function with the natural constant as the base and denoted as the first exponential function. The calculation result of the first exponential function is taken as the dust adsorption influence coefficient of the infrared thermal imaging image at each time point.

8. The method for preparing a carbon fiber and sodium iron phosphate composite cathode material according to claim 1, characterized in that, The process of predicting the liquid delivery flow rate at the next moment during the spray drying process includes: For the infrared thermal imaging images at each time point, the negative number of the dust adsorption influence coefficient is used as the exponent of an exponential function with the natural constant as the base. The product of the calculated result of the exponential function and the first preset value is calculated, and the sum of the product and the second preset value is used as the liquid conveying flow rate value at the next time point.

9. The method for preparing a carbon fiber and sodium iron phosphate composite cathode material according to claim 1, characterized in that, The carbon coating process involves setting the CVD furnace temperature to 800℃, adjusting the nitrogen and methane flow rates to 100 m³ / h and 150 m³ / h respectively, and adding powder material for CVD coating when the oxygen content drops below 10 ppm. The coating time is 10 hours. The pulverization process uses air jet milling with high-temperature nitrogen at 120℃ as the gas source. The air jet milling frequency is 25 Hz, and the pulverization pressure is 0.40 MPa. The resulting graded material has a particle size of 2.0 μm. The demagnetization process uses an electromagnetic separator.

10. A composite cathode material of carbon fiber and sodium iron phosphate, characterized in that, The carbon fiber and sodium iron phosphate composite cathode material is produced by the method described in any one of claims 1-9.

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