A lignite-based hard carbon negative electrode material preparation method and device

Abstract

The application provides a lignite-based hard carbon negative electrode material preparation method and device. The scheme of the application is that lignite raw materials are subjected to pre-oxidation treatment in an oxygen-containing atmosphere through a pre-oxidation process; the pre-oxidation product of the coal is subjected to pre-carbonization treatment in an inert atmosphere through a pre-carbonization process; the pre-carbonization product is subjected to superfine crushing through a superfine crushing process; after the coal powder is subjected to acid washing treatment to remove impurities through an acid washing purification process, high-purity hard carbon negative electrode material is obtained; and through an intelligent control platform, cross-process parameter collaborative regulation is realized through an LSTM neural network and a full-link digital twin model. The application greatly improves the carbonization yield, the first coulomb efficiency of the hard carbon material, the 100-cycle capacity retention rate and the batch performance fluctuation and other key parameters, and provides an industrialization scheme for preparing high-performance battery negative electrode material from low-cost lignite.

Description

Technical Field

[0001] This invention relates to a method and apparatus for preparing hard carbon anode materials based on lignite, belonging to the field of hard carbon anode material preparation technology, and is applicable to the industrial production of high-performance hard carbon anode materials for lithium-ion batteries or sodium-ion batteries. Background Technology

[0002] Low-rank lignite, represented by Xinjiang lignite, has abundant reserves, with global reserves exceeding 3 trillion tons. Lignite is inexpensive, but its structure is young, characterized by low carbonization, high volatile matter, and high oxygen content. Moreover, the volatile matter and ash content of different batches of lignite raw materials fluctuate greatly. Although it can meet the low-cost requirements for the production of hard carbon anode materials, it is insufficient for the requirements of high stability and high consistency.

[0003] In current research on the production process of hard carbon anode materials from lignite, the mismatch between the characteristics of lignite raw materials and the anode material production process includes:

[0004] First, the high volatile matter in lignite raw materials tends to escape explosively during high-temperature carbonization. Laboratory tests have shown that directly carbonizing lignite at high temperatures leads to the rapid escape of volatile matter within 10 minutes, causing the carbon skeleton to collapse and the carbonization yield falling far short of commercial hard carbon requirements. Simultaneously, impurities such as Fe2O3 and SiO2 in lignite remain as oxide particles in the negative electrode material after carbonization, resulting in a decrease in the cycle capacity retention rate of sodium-ion batteries.

[0005] Secondly, in the traditional process of physical crushing and direct carbonization of lignite, the particle size distribution of the crushed coal particles is relatively wide. During carbonization, the volatilization of large coal particles is hindered, and the small particles are over-burned, resulting in uneven product structure. Moreover, the surface of the lignite particles processed by conventional crushing is smooth, making it difficult to penetrate during acid washing, resulting in insufficient ash removal rate and failing to meet the requirements for high purity.

[0006] Furthermore, the hard carbon anode materials produced by the traditional physical crushing and direct carbonization process have been tested and found to have substandard initial coulombic efficiency, poor rate performance, and large batch capacity deviations. The current production process faces several core challenges, including controlling the stability of the carbon skeleton, deep ash removal, and product consistency control. Summary of the Invention

[0007] To address the shortcomings of the existing technology, the present invention aims to provide a method and apparatus for preparing hard carbon anode materials based on lignite.

[0008] According to an embodiment of the present invention, the first embodiment is provided as follows: a method for preparing a hard carbon anode material based on lignite, comprising the following steps:

[0009] S101: Pre-oxidation process, in which lignite raw material is placed in an oxygen-containing atmosphere for pre-oxidation treatment to form coal pre-oxidation products with a stable initial structure;

[0010] S102: Pre-carbonization process, which pre-carbonizes the coal pre-oxidation products under an inert atmosphere to form pre-carbonized products with a disordered layer structure;

[0011] S103: Ultrafine grinding process, which involves ultrafine grinding of pre-carbonized products to obtain coal powder with high specific surface area and uniform particle size;

[0012] S104: Acid washing and purification process, in which coal powder is acid washed with an acidic solution to remove impurities and obtain high-purity hard carbon anode material.

[0013] Furthermore, the pre-oxidation process includes the following steps: placing the lignite raw material in a pre-oxidation furnace, introducing an O2 / N2 mixture, heating it to 200℃-400℃ at a heating rate of 2℃-5℃ / min, and holding it at that temperature for 1h-3h.

[0014] Furthermore, the pre-carbonization process includes the following steps: transferring the coal pre-oxidation product into a pre-carbonization furnace, introducing an inert N2 atmosphere, heating it to 500℃-700℃ at a heating rate of 1℃-3℃ / min, holding it at that temperature for 2h-4h, and obtaining a pre-carbonized product with a disordered layer structure and a d002 interlayer spacing range of 0.35nm-0.40nm.

[0015] Furthermore, the ultrafine grinding process includes: grinding the pre-carbonized product using an air jet mill, adjusting the air jet mill nozzle pressure to 0.6MPa-1.0MPa, the classifier wheel speed to 3000rpm-6000rpm, and the grinding time to 30min-45min; the median particle size D50 of the coal powder is 1.5μm, and the particle size distribution satisfies D10≥0.8μm and D90≤3.0μm.

[0016] Furthermore, the acid washing and purification process includes the following steps: adding coal powder to an acid washing tank, adding a mixed acid solution of hydrochloric acid and hydrofluoric acid with a liquid-to-solid ratio of 5:1-10:1, stirring and reacting at 25℃-60℃ for 2-4 hours, filtering, washing with deionized water until the pH of the filtrate is 6.5-7.0, and drying to obtain a hard carbon anode material with ash residue <100ppm.

[0017] Furthermore, before the pre-oxidation process, a drying pretreatment process is also included, in which the lignite raw material is dried at 105℃-120℃ for 4-6 hours to remove more than 80% of the free water in the raw material and control the moisture content of the dried lignite to ≤5%.

[0018] Furthermore, the pre-oxidation process, pre-carbonization process, ultrafine pulverization process, and acid washing and purification process are controlled by an intelligent control platform. The intelligent control platform collects the process parameters of each process in real time and analyzes and dynamically adjusts the process parameters to ensure the continuity of each process and improve the stability of the hard carbon anode material.

[0019] Furthermore, the intelligent control platform monitors the volatile matter escape rate in the pre-oxidation furnace in real time using an infrared spectral sensor. Combined with the LSTM neural network model pre-trained by the intelligent control platform, it dynamically adjusts the heating rate and oxygen volume fraction of the pre-oxidation process with a volatile matter escape rate of ≤0.5% / min as the target.

[0020] Furthermore, the training data of the LSTM neural network model includes the volatile matter content, initial oxygen functional group content, and historical process parameters of the lignite raw material. The output parameters of the LSTM neural network model include: optimal heating rate, oxygen volume fraction, and holding time. The temperature distribution in the pre-oxidation furnace is corrected in real time through a thermocouple array. When the predicted volatile matter escape rate is greater than 0.5% / min, the heating rate is automatically reduced by ≥1℃ / min and the oxygen volume fraction is increased by ≥2% until the volatile matter escape rate returns to the target range.

[0021] According to an embodiment of the present invention, utilizing the lignite-based hard carbon anode material preparation method of the first embodiment provided by the present invention, a second embodiment is provided as follows:

[0022] A device for preparing hard carbon anode material based on lignite includes a pre-oxidation unit, a pre-carbonization unit, an ultrafine grinding unit, an acid washing and purification unit, and an intelligent control platform connected in sequence.

[0023] The pre-oxidation unit includes a pre-oxidation furnace, an O2 / N2 mixed gas supply device, an infrared spectral sensor, and a heating rate controller. The pre-oxidation unit is used to place lignite raw material in an oxygen-containing atmosphere for pre-oxidation treatment to form a coal pre-oxidation product with a stable initial structure.

[0024] The pre-carbonization unit includes a pre-carbonization furnace, an N2 inert gas supply device, a gas chromatograph, and a PID temperature controller. The pre-carbonization unit is used to pre-carbonize the coal pre-oxidation products under an inert atmosphere to form pre-carbonized products with a disordered layer structure.

[0025] An ultrafine grinding unit, comprising an air jet mill, a dynamic light scattering instrument, and a grinding time controller, is used to ultrafine grind pre-carbonized products to obtain coal powder with high specific surface area and uniform particle size.

[0026] The acid washing and purification unit includes an acid washing tank, a mixed acid supply device, an X-ray fluorescence spectrometer, and a pH meter. The acid washing and purification unit removes impurities from coal powder by acid washing with an acidic solution, thereby obtaining high-purity hard carbon anode material.

[0027] Intelligent control platform: includes a central processing module, a data acquisition module, and an execution module that integrates an LSTM neural network model.

[0028] Compared with the prior art, the unique advantages of the technical solution provided in this application are as follows:

[0029] This embodiment provides a method for preparing hard carbon anode materials based on lignite. By redesigning the preparation process, the traditional preparation method is optimized to first perform pre-oxidation and pre-carbonization steps, then perform ultrafine grinding, and finally acid washing and purification to obtain hard carbon anode materials. This solves several core limitations of the traditional production scheme.

[0030] By introducing oxygen-containing functional groups and carrying out cross-linking reactions through the pre-oxidation process, the violent release of volatiles from lignite particles during subsequent high-temperature treatment is suppressed. Combined with the pre-carbonization process to remove small molecule volatiles from lignite particles and solidify the carbon skeleton, the carbonization absorption rate is greatly improved. Moreover, the pre-carbonized products have good uniformity of interlayer spacing and stable structure in their disordered layer structure, providing a channel for ion intercalation of hard carbon anode materials.

[0031] This preparation method uses an ultrafine grinding process to grind the pre-carbonized product into a uniform powder with a median particle size D50 of approximately 1.5 micrometers, thereby significantly increasing the specific surface area and reactivity. Combined with the deep cleaning of the mixed acid solution in the subsequent acid washing and purification process, it not only effectively removes various inorganic impurities, but also results in a large ash residue in the final product, which is sufficient to meet the requirements of industrial production.

[0032] Finally, this preparation method also introduces a coordinated control approach for the preceding and following processes, which enables the hard carbon anode material to exhibit excellent ion diffusion kinetics and cycle stability due to its disordered layer structure, low ash content, and uniform particle size distribution. This provides a cost-effective commercial method for preparing high-value battery materials from low-cost lignite raw materials. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] in:

[0035] Figure 1 This is a flowchart of a method for preparing hard carbon anode material based on lignite in one embodiment;

[0036] Figure 2 This is a structural block diagram of a lignite-based hard carbon anode material preparation device in one embodiment;

[0037] Figure 3 This is an industrial production architecture diagram of a lignite-based hard carbon anode material preparation apparatus in one embodiment.

[0038] Figure 4 This is a structural block diagram of a computer device in one embodiment. Detailed Implementation

[0039] To enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0040] Example 1

[0041] This embodiment provides a specific method for preparing hard carbon anode materials based on lignite, mainly applied to the industrial production of hard carbon anode materials for batteries. The specific scenario involves a customer's project to prepare high-performance hard carbon anode materials using low-rank lignite from Xinjiang. Research indicates that low-rank lignite reserves are abundant, with a cost per ton approximately 20%-30% of that of lignin raw materials. The project requires a batch production capacity of at least 500 kg, an initial coulombic efficiency ≥85%, a cycle retention rate ≥90% after 100 cycles, and ash residue <100 ppm.

[0042] The existing production process of mass production using traditional methods such as lignite crushing, direct carbonization, and acid washing for impurity removal has at least the following problems:

[0043] First, Xinjiang lignite has a high initial volatile matter content. When carbonizing at 800℃, the volatile matter escapes violently before reaching 800℃, causing the carbon skeleton to collapse and the carbonization yield to be too low to meet industrial needs.

[0044] Second, the ash content of lignite raw materials is usually greater than 12%, and the ash components include impurities such as Fe2O3 and SiO2. After acid washing, the ash residue exceeds 300ppm, resulting in a battery capacity retention rate of less than 70% after 100 cycles.

[0045] Third, the structural stability is poor. The initial coulombic efficiency is around 70%.

[0046] Traditional processes cannot meet battery performance requirements.

[0047] The method for preparing hard carbon anode materials based on lignite in this embodiment is as follows: Figure 1 As shown, it includes the following steps:

[0048] I. Pre-drying process

[0049] Random sampling of lignite raw materials from the Zhundong mining area in Xinjiang revealed an initial moisture content of 18%, volatile matter of 28%, and ash content of 12%.

[0050] The lignite raw material was initially crushed to a particle size of ≤5mm and placed in a circulating hot air drying oven. The temperature was set at 105℃ and the drying time was 2h.

[0051] This step can remove most of the free water, reduce the moisture content of lignite raw materials, and prevent moisture from reacting with oxygen functional groups to generate byproducts during subsequent pre-oxidation processes.

[0052] II. Pre-oxidation process

[0053] The equipment used is a continuous rotary oxidation furnace. The dried lignite is fed into the oxidation furnace, and an O2 / N2 mixture is introduced, with an oxygen volume fraction of 15%. The mixture is heated to 300°C at a heating rate of 3°C / min and held at that temperature for 2 hours.

[0054] In an oxygen atmosphere, oxygen-containing functional groups such as hydroxyl and carboxyl groups in lignite undergo partial oxidative cross-linking reactions to form stable structures such as ester bonds (-COO-) and ether bonds (-O-). These ester and ether bond structures can suppress the violent and rapid release of volatiles during subsequent carbonization.

[0055] This step can reduce the content of initial oxidized functional groups in lignite feedstock, thereby suppressing the subsequent volatile matter release rate.

[0056] III. Pre-carbonization process

[0057] The equipment used is a tubular pre-carbonization furnace. The pre-oxidized product is fed into the pre-carbonization furnace, and an inert N2 atmosphere is introduced. The purity should be as high as possible. The product is heated to 600°C at a heating rate of 2°C / min, held at that temperature for 2 hours, and then allowed to cool naturally to room temperature.

[0058] Under an inert atmosphere, small volatile molecules in the pre-oxidized product are gradually removed and reduced, and the carbon skeleton can be further cross-linked and solidified to form a stable disordered layer structure. The pre-carbonization yield of the pre-carbonized product obtained in this process is 35% higher than the standard, and the d200 interlayer spacing of the disordered layer structure measured by XRD is 0.38 nm.

[0059] IV. Ultrafine Grinding Process

[0060] Using a fluidized bed air jet mill, the pre-carbonized product is fed into the mill, and the nozzle pressure, classifying wheel speed, and pulverization time are adjusted. The particles are impacted by high-speed airflow and separated by the classifying wheel to achieve ultrafine pulverization.

[0061] The median particle size of the coal powder was D50 = 1.5 μm, and the particle size distribution was D10 = 0.9 μm and D90 = 2.8 μm. The specific surface area also increased significantly by 2-3 times.

[0062] V. Acid washing and purification process

[0063] Use a corrosion-resistant stirring pickling tank with a capacity of 2000L.

[0064] The pulverized coal powder is added to the pickling tank, and a mixed acid solution is added at a liquid-to-solid ratio of 8:1, with hydrochloric acid having a mass concentration of 6% and hydrofluoric acid having a mass concentration of 3%.

[0065] The temperature in the pickling tank is controlled at 40℃, the stirring speed is 400rpm, and the reaction time is 2h. After the reaction is completed, the solution is filtered, for example, by washing with deionized water, until the pH of the filtrate is tested to be 6.5.

[0066] Place in a drying oven and dry for 12 hours.

[0067] Hydrochloric acid can fuse various metal oxide impurities, while hydrofluoric acid etches silicon dioxide. The large specific surface area of ​​the ultrafine powder increases the reaction contact area, ensuring the deep removal of impurities.

[0068] The final performance parameters of the anode material are as follows: the ash residue of the hard carbon anode material is 85 ppm, which is less than the standard of 100 ppm, and the main metal ion impurities also meet the requirements.

[0069] In the above scheme, drying pretreatment removes moisture interference, pre-oxidation causes the phased and intense release of volatiles, pre-carbonization can obtain a stable disordered layer structure and improve the yield, ultrafine grinding enhances the reactivity of acid washing, and final acid washing purification can deeply remove ash. Combined with the high reactivity of ultrafine powder, high-quality hard carbon anode material with low ash residue is obtained.

[0070] Example 2

[0071] In the industrial production of hard carbon anode materials for batteries, a major characteristic of Xinjiang lignite raw materials is the large batch-to-batch variation, with significant fluctuations in volatile matter and ash content. This leads to the adoption of standardized or phased standardized production processes. Although the various properties of the final product can meet the standards, the differences are significant, making it difficult to achieve the stability and consistency requirements of key parameters of hard carbon anode materials produced from multiple batches of lignite raw materials.

[0072] To address this technical problem, the main objectives of this embodiment are: controlling the heating rate and oxygen volume fraction during the pre-oxidation stage, maintaining a fixed holding time during the pre-carbonization stage, and maintaining a fixed acid concentration ratio during the pickling stage.

[0073] Specifically, this embodiment provides a method for preparing hard carbon anode materials based on lignite, which achieves high stability and consistency of the final product through intelligent solutions.

[0074] The Intelligent Control Platform 500 includes platform architecture and sensor configuration. The specific deployment configuration of the distributed sensor network and execution units is shown in the table below:

[0075]

[0076] The software layer of the Intelligent Control Platform 500 uses an LSTM neural network model for pre-oxidation algorithm optimization. Specifically, a genetic algorithm can be used to optimize crushing parameters, and an isolation forest algorithm is employed for anomaly detection. Ultimately, multiple software layers are integrated into the Industrial Internet platform.

[0077] Specifically, the LSTM neural network model training steps in this embodiment include:

[0078] The features of 100 batches of production data collected and input into the neural network model include: volatile matter content of lignite raw materials, initial oxygen functional group content, historical heating rate, and oxygen volume fraction.

[0079] The output labels are: carbonization yield, volatile matter escape rate, and residual oxygen functional groups in pre-oxidized products.

[0080] The specific neural network model uses a 3-layer LSTM network with 128, 64, and 32 hidden neurons.

[0081] The objective function is: volatile matter escape rate ≤ 0.5%, carbonization yield ≥ 35%.

[0082] After training the Adam optimizer for 1000 epochs, the loss function converged to 0.002.

[0083] The intelligent control and adjustment logic for each process is as follows:

[0084] I. Intelligent Control Process of Pre-oxidation Step

[0085] The volatile matter escape rate is monitored in real time using an infrared spectral sensor. If the escape rate exceeds 0.8% / min within the next minute as predicted by an LSTM model, an adjustment command is triggered. Specifically, the adjustment command uses a thermocouple array to provide feedback on the furnace temperature distribution, reducing the heating rate from 3℃ / min to 2℃ / min. Simultaneously, the oxygen volume fraction is increased by 2% to enhance the cross-linking reaction and stabilize the carbon skeleton structure.

[0086] II. Intelligent Control Process of Pre-carbonization

[0087] The CH4 concentration at the outlet of the pre-carbonization furnace was monitored in real time using a gas chromatograph.

[0088] When the CH4 concentration is greater than 0.2 vol%, the adaptive PID controller extends the holding time by 0.5 h to ensure that small molecule volatiles are fully removed, and the final d002 interlayer spacing of the pre-carbonized product is stabilized at 0.38 ± 0.01 nm.

[0089] III. Linkage Control of Ultrafine Grinding and Pickling Processes

[0090] For example, the DLS monitoring during the pulverization process showed a D50 of 1.7 micrometers. The genetic algorithm was used to automatically optimize the process: the nozzle pressure was reduced and the speed of the classifier wheel was increased. After 30 minutes, the D50 recovered to 1.5 micrometers.

[0091] XRF monitoring during the pickling process showed that the iron ion concentration exceeded 80 ppm. The intelligent control platform increased the hydrochloric acid concentration and the stirring speed to reduce the ash residue to 90 ppm.

[0092] The control process of the Intelligent Control Platform 500 essentially replaces traditional experience-based control parameters with the nonlinear mapping relationship between raw material characteristics, process parameters, and final product performance mined by the LSTM model. Specifically, the oxygen functional group content of the pre-oxidized product is pushed to the pre-carbonization unit in real time as a feedforward parameter for the PID temperature controller, thereby improving the performance of key parameters of the final product.

[0093] This embodiment utilizes the intelligent control process of the 500 intelligent control platform to ensure that the batch stability of Xinjiang lignite-based hard carbon meets commercial requirements, while also reducing production costs to a certain extent. It provides a replicable industrial production solution for the high-value utilization of low-rank lignite.

[0094] Example 3

[0095] In the traditional process and the carbonization process of Example 1, temperature / time is usually controlled in a single dimension. It is difficult to improve the reversible capacity stability of the final negative electrode material by controlling the interlayer spacing distribution and the heating rate during the production process. In addition, the concentrated release of volatiles can easily lead to the appearance of a large number of microporous structures in the grains, which will interrupt the ion diffusion path of the battery and reduce the rate performance.

[0096] To address the aforementioned technical issues, this embodiment provides a method for preparing hard carbon anode materials based on lignite. Through a gradient carbonization process involving stepped cooling and synergistic heat preservation, the thermal stress is released through slow cooling, while simultaneously promoting the secondary generation of mesoporous networks / mesh, thereby improving the reversible capacity and rate performance of the sodium-ion anode material.

[0097] The specific steps include:

[0098] Volatile matter is pre-removed by low-temperature pre-carbonization. The temperature is increased to 450℃ at a rate of 2℃ / min, and N2 atmosphere is introduced simultaneously, with the pressure linearly increasing from atmospheric pressure to 0.3MPa. The temperature is maintained for 60 minutes. By suppressing the explosive escape of volatile matter in a low-pressure environment, small molecule impurities are carried away by the N2 gas flow to reduce surface defects of the carbon skeleton.

[0099] A preliminary disordered layer structure was formed by constructing a medium-temperature structure. The temperature was increased to 650°C at a rate of 3°C / min, the pressure was increased to 0.5MPa, the N2 flow rate was reduced, and the temperature was maintained for 60 minutes. The medium-pressure environment can promote the orderly arrangement of carbon atoms and initially form a disordered layer structure with a d002 interlayer spacing of 0.38-0.39nm. At the same time, the surface etching of carbon particles was reduced by a low airflow rate to preserve the mesoporous precursor.

[0100] High-temperature densification is used to achieve directional growth of pores. The temperature is increased to 800℃ at 1℃ / min, the pressure is rapidly increased to 0.7MPa, the N2 flow rate is increased to 3L / min, and the temperature is maintained for 60-120 minutes. High pressure inhibits bubble merging and forces volatiles to slowly escape along the weak areas of the carbon skeleton, directionally generating mesopores with a pore size distribution concentrated between 10-20nm, so that ion transport falls within the optimal range.

[0101] A gradient cooling and depressurization stage can be added to achieve thermal stress release and re-regulation of interlayer spacing. The temperature is reduced to 600℃ at a rate of 1℃ / min, and the pressure is reduced to 0.4MPa at a rate of 0.1MPa / min. This pressure gradient drives carbon atom migration, repairing interlayer defects. The isothermal depressurization step involves holding at 600℃ for 90 minutes, reducing the pressure to 0.2MPa, at which point the d002 interlayer spacing is locked at 0.375-0.385nm. Finally, the temperature is reduced to room temperature at a rate of 0.5℃ / min, and the pressure naturally decreases to atmospheric pressure.

[0102] By controlling pressure, atmosphere, and temperature, the volatile matter escape process is precisely regulated by pressure gradient, which solves the problem that traditional temperature control cannot simultaneously address structural stability and low porosity, and also reduces defects in the carbon skeleton.

[0103] By suppressing bubble coalescence under high pressure and guiding the orderly escape of volatiles, precise control of mesopore size is achieved, ultimately increasing the particle diffusion coefficient of the anode material by more than 2 times. Furthermore, by coordinating gradient cooling and depressurization, uniform release of thermal stress is achieved, further reducing d002 interlayer spacing fluctuations, improving ion intercalation stability during cycling, and increasing capacity retention by more than 10% after 100 cycles.

[0104] Example 4

[0105] In the process of preparing hard carbon materials using intelligent control methods, the parameters of each process are independently controlled, and the entire production process is an assembly line operation. Therefore, fluctuations in raw material characteristics will inevitably lead to changes in the state of the preceding products. If subsequent processes are not adapted, the non-linked control of the preceding and following processes will result in quality fluctuations in the final product due to raw material fluctuations.

[0106] This embodiment provides a method for preparing hard carbon anode materials based on lignite, including the following steps:

[0107] S51: Build a full-process digital twin model.

[0108] The raw material characteristic parameters of lignite are integrated, including volatile matter parameters, ash parameters, moisture content parameters, equipment status and product status of each process. Among them, the equipment status includes nozzle wear and agitator speed deviation, and the product status of each process includes oxygen functional group content, d002 interlayer spacing and particle size distribution. A dynamic database is constructed, and virtual mapping is realized based on the mechanism model and random forest regression model.

[0109] S52: Deploy multivariate learning algorithms.

[0110] A deep deterministic strategy gradient algorithm is adopted, with the ash residue fluctuation of the final product ≤ ±10ppm and the cycle life standard deviation ≤2% as the reward function. The state space contains 28 real-time features, including 3 dimensions of raw materials, 18 dimensions of process, and 7 dimensions of equipment. The action space outputs the coordinated adjustment parameters of pre-oxidation heating rate / oxygen content, pre-carbonization heating rate / pressure, crushing nozzle pressure / classifying wheel speed, and pickling acid concentration / liquid-solid ratio.

[0111] S53: Implement cross-process collaborative control.

[0112] By using real-time sensing and digital twin simulation to predict the impact of fluctuations in preceding products on subsequent processes, and by using algorithms to output optimal parameter adjustment instructions and execution feedback, with the lag time of the execution feedback being less than 30 seconds, global parameter adaptive optimization under the conditions of raw material characteristic fluctuations and equipment status changes is ultimately achieved.

[0113] This method constructs a virtual mapping of the entire "raw material-process-product" chain through digital twins, and combines reinforcement learning to achieve proactive prediction and collaborative control of cross-process parameters. It fundamentally solves the problem of "the lag response to the impact of preceding fluctuations on subsequent processes", and reduces product performance fluctuations by 60% compared to single-process control (e.g., ash residue fluctuations are reduced from ±30ppm to ±12ppm).

[0114] The hard carbon anode material preparation method in this embodiment uses a dynamic demand-driven parameter adjustment mechanism to dynamically adjust the local target values ​​of parameters in each process, with the final product performance as the ultimate goal. For example, when the ash content of the raw material is too high, the software automatically increases the target value of the acid concentration for acid washing while decreasing the target value of the pre-carbonization heating rate. By synergistically compensating for raw material defects through multiple process parameters, the overall performance of the hard carbon anode material is optimized, rather than optimized for a single process.

[0115] Example 5

[0116] This embodiment provides a device for preparing hard carbon anode materials based on lignite, such as... Figure 2 , Figure 3 As shown, it includes a pre-oxidation unit 100, a pre-carbonization unit 200, an ultrafine grinding unit 300, an acid washing and purification unit 400, and an intelligent control platform 500 connected in sequence.

[0117] The pre-oxidation unit 100 includes a pre-oxidation furnace, an O2 / N2 mixed gas supply device, an infrared spectral sensor, and a heating rate controller. The pre-oxidation unit 100 is used to place lignite raw material in an oxygen-containing atmosphere for pre-oxidation treatment to form a coal pre-oxidation product with a stable initial structure.

[0118] The pre-carbonization unit 200 includes a pre-carbonization furnace, an N2 inert gas supply device, a gas chromatograph, and a PID temperature controller. The pre-carbonization unit 200 is used to pre-carbonize the coal pre-oxidation products under an inert atmosphere to form pre-carbonized products with a disordered layer structure.

[0119] The ultrafine grinding unit 300 includes an air jet mill, a dynamic light scattering instrument, and a grinding time controller. The ultrafine grinding unit 300 is used to ultrafine grind the pre-carbonized products to obtain coal powder with high specific surface area and uniform particle size.

[0120] Acid washing and purification unit 400 includes an acid washing tank, a mixed acid supply device, an X-ray fluorescence spectrometer, and a pH meter. The acid washing and purification unit 400 removes impurities from coal powder by acid washing with an acidic solution to obtain high-purity hard carbon anode material.

[0121] Intelligent Control Platform 500: Includes a central processing module, a data acquisition module, and an execution module that integrates an LSTM neural network model.

[0122] Example 6

[0123] Figure 4 An internal structural diagram of a computer device in one embodiment is shown. This computer device can specifically be a terminal or a server. Figure 4As shown, the computer device includes a processor, memory, and network interface connected via a system bus. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and may also store a computer program. When executed by the processor, this computer program enables the processor to implement a method for preparing hard carbon anode materials. The memory may also store a computer program, which, when executed by the processor, enables the processor to implement a method for preparing hard carbon anode materials. Those skilled in the art will understand that... Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0124] In one embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the following steps:

[0125] The pre-oxidation process involves placing lignite raw material in an oxygen-containing atmosphere for pre-oxidation treatment to form coal pre-oxidation products with a stable initial structure.

[0126] The pre-carbonization process involves pre-carbonizing the pre-oxidized coal products under an inert atmosphere to form pre-carbonized products with a disordered layer structure.

[0127] The ultrafine grinding process involves ultrafine grinding of the pre-carbonized products to obtain coal powder with high specific surface area and uniform particle size.

[0128] The acid washing and purification process involves washing coal powder with an acidic solution to remove impurities, thereby obtaining high-purity hard carbon anode material.

[0129] In one embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, causes the processor to perform the following steps:

[0130] The pre-oxidation process involves placing lignite raw material in an oxygen-containing atmosphere for pre-oxidation treatment to form coal pre-oxidation products with a stable initial structure.

[0131] The pre-carbonization process involves pre-carbonizing the pre-oxidized coal products under an inert atmosphere to form pre-carbonized products with a disordered layer structure.

[0132] The ultrafine grinding process involves ultrafine grinding of the pre-carbonized products to obtain coal powder with high specific surface area and uniform particle size.

[0133] The acid washing and purification process involves washing coal powder with an acidic solution to remove impurities, thereby obtaining high-purity hard carbon anode material.

[0134] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0135] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0136] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for preparing hard carbon anode material based on lignite, characterized in that, Includes the following steps: The pre-oxidation process involves placing lignite raw material in an oxygen-containing atmosphere for pre-oxidation treatment to form coal pre-oxidation products with a stable initial structure. The pre-carbonization process involves pre-carbonizing the pre-oxidized coal products under an inert atmosphere to form pre-carbonized products with a disordered layer structure. The ultrafine grinding process involves ultrafine grinding of the pre-carbonized products to obtain coal powder with high specific surface area and uniform particle size. The acid washing and purification process involves washing coal powder with an acidic solution to remove impurities, thereby obtaining high-purity hard carbon anode material. The pre-oxidation process, pre-carbonization process, ultrafine grinding process, and acid washing and purification process are controlled by an intelligent control platform. The intelligent control platform collects the process parameters of each process in real time, including the volatile matter escape rate and furnace temperature distribution monitored in the pre-oxidation process, the small molecule volatile matter concentration monitored in the pre-carbonization process, the particle size distribution monitored in the ultrafine grinding process, and the ash content monitored in the acid washing and purification process. The platform also analyzes and dynamically adjusts each process parameter to ensure the continuity of each process and improve the stability of the hard carbon anode material. The intelligent control platform monitors the volatile matter escape rate in the pre-oxidation furnace in real time using an infrared spectral sensor. Combined with the LSTM neural network model pre-trained by the intelligent control platform, it dynamically adjusts the heating rate and oxygen volume fraction of the pre-oxidation process with a volatile matter escape rate of ≤0.5% / min as the target.

2. The method for preparing hard carbon anode material based on lignite according to claim 1, characterized in that, The pre-oxidation process includes the following steps: The lignite raw material is placed in a pre-oxidation furnace, and an O2 / N2 mixture is introduced. The temperature is increased to 200℃-400℃ at a heating rate of 2℃-5℃ / min, and then held for 1h-3h.

3. The method for preparing hard carbon anode material based on lignite according to claim 1, characterized in that, The steps of the pre-carbonization process include: The coal pre-oxidation product was transferred to a pre-carbonization furnace, and an inert N2 atmosphere was introduced. The temperature was increased to 500℃-700℃ at a heating rate of 1℃-3℃ / min and held for 2h-4h. The d002 interlayer spacing of the disordered layer structure of the obtained pre-carbonization product ranged from 0.35nm to 0.40nm.

4. The method for preparing hard carbon anode material based on lignite according to claim 1, characterized in that, The steps of the ultrafine grinding process include: The pre-carbonized products were pulverized using an air jet mill. The nozzle pressure of the air jet mill was adjusted to 0.6MPa-1.0MPa, the classifier speed was adjusted to 3000rpm-6000rpm, and the pulverization time was 30min-45min. The median particle size D50 of the coal powder was 1.5μm, and the particle size distribution satisfied D10≥0.8μm and D90≤3.0μm.

5. The method for preparing hard carbon anode material based on lignite according to claim 1, characterized in that, The acid washing and purification process includes the following steps: Coal powder is added to an acid washing tank, and a mixed acid solution of hydrochloric acid and hydrofluoric acid is added with a liquid-solid ratio of 5:1-10:

1. The mixture is stirred and reacted at 25℃-60℃ for 2-4 hours. After filtration, the mixture is washed with deionized water until the pH of the filtrate is 6.5-7.

0. After drying, a hard carbon anode material with ash residue of <100ppm is obtained.

6. The method for preparing hard carbon anode material based on lignite according to claim 1, characterized in that, The process preceding the pre-oxidation step also includes: The drying pretreatment process involves drying the lignite raw material at 105℃-120℃ for 4-6 hours to remove more than 80% of the free water in the raw material, and controlling the moisture content of the dried lignite to be ≤5%.

7. The method for preparing hard carbon anode material based on lignite according to claim 1, characterized in that, The training data for the LSTM neural network model includes the volatile matter content, initial oxygen functional group content, and historical process parameters of the lignite raw material. The output parameters of the LSTM neural network model include: optimal heating rate, oxygen volume fraction, and holding time. The temperature distribution inside the pre-oxidation furnace is corrected in real time by using a thermocouple array. When the predicted volatile matter escape rate is greater than 0.5% / min, the heating rate is automatically reduced by ≥1℃ / min and the oxygen volume fraction is increased by ≥2% until the volatile matter escape rate returns to the target range.

8. A device for preparing hard carbon anode materials based on lignite, characterized in that, The method for preparing lignite-based hard carbon anode material according to any one of claims 1 to 7 includes a pre-oxidation unit, a pre-carbonization unit, an ultrafine grinding unit, an acid washing and purification unit, and an intelligent control platform connected in sequence. The pre-oxidation unit includes a pre-oxidation furnace, an O2 / N2 mixed gas supply device, an infrared spectral sensor, and a heating rate controller. The pre-oxidation unit is used to place lignite raw material in an oxygen-containing atmosphere for pre-oxidation treatment to form a coal pre-oxidation product with a stable initial structure. The pre-carbonization unit includes a pre-carbonization furnace, an N2 inert gas supply device, a gas chromatograph, and a PID temperature controller. The pre-carbonization unit is used to pre-carbonize the coal pre-oxidation products under an inert atmosphere to form pre-carbonized products with a disordered layer structure. An ultrafine grinding unit, comprising an air jet mill, a dynamic light scattering instrument, and a grinding time controller, is used to ultrafine grind pre-carbonized products to obtain coal powder with high specific surface area and uniform particle size. The acid washing and purification unit includes an acid washing tank, a mixed acid supply device, an X-ray fluorescence spectrometer, and a pH meter. The acid washing and purification unit removes impurities from coal powder by acid washing with an acidic solution, thereby obtaining high-purity hard carbon anode material. Intelligent control platform: includes a central processing module, a data acquisition module, and an execution module that integrates an LSTM neural network model.

Images