Method, device, equipment and medium for efficiently dissociating electrode materials from lithium battery waste

Abstract

The present invention relates to artificial intelligence technology and discloses a method, device, equipment and medium for efficiently dissociating electrode materials from lithium battery waste residue. The method comprises: grouping preset experimental data to obtain electrode material characteristics of the experimental data, and extracting a temperature data set, a dissociation efficiency data set and a dissociation purity data set from the electrode material characteristics; calculating the decomposition temperature of each electrode material characteristic; calculating the metal vapor pressure of each electrode material characteristic using the decomposition temperature; performing an optimal temperature analysis on the material characteristics based on the metal vapor pressure, decomposition temperature, dissociation efficiency data set and dissociation purity data set to obtain optimal dissociation temperature data. The present invention also proposes an efficient dissociation device, electronic equipment and storage medium for electrode materials from lithium battery waste residue. The present invention can solve the problems of low electrode material dissociation efficiency and low dissociation purity in electrode material dissociation caused by the inability to accurately determine the pyrolysis temperature.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to a method, device, equipment and computer-readable storage medium for efficiently dissociating electrode materials from lithium battery waste. Background Art

[0002] The core value of lithium-ion batteries lies in their abundant content of high-value metallic elements such as lithium (Li), cobalt (Co), nickel (Ni), and manganese (Mn). However, these metals are limited in natural reserves, expensive to mine, and their supply fluctuates frequently. Therefore, effectively recycling these metals from used batteries is crucial to alleviating pressure on the supply and demand of raw materials and reducing reliance on newly mined mineral resources.

[0003] At present, the recycling technology of waste lithium-ion batteries mainly refers to the hydrometallurgical method, which is to use solvents to extract metals from waste batteries. However, the existing wet metallurgical recycling process of waste lithium-ion batteries is often based on certain process conditions, focusing on one or several key process parameters, such as temperature, reaction time, etc., treating each parameter as an independent variable, and adjusting it separately to reduce the impact of process parameters on metal extraction efficiency, but this method lacks systematic consideration of the synergistic effect of multiple factors. For example, increasing the temperature may accelerate the dissolution of metals, but it may also accelerate the volatilization of solvents or the occurrence of side reactions, resulting in the recovery efficiency in actual operation being lower than the theoretical optimal value. Therefore, the existing waste lithium-ion battery recycling technology has the problems of low metal recovery efficiency and high energy consumption. Summary of the Invention

[0004] The present invention provides a method, device, equipment and medium for efficiently dissociating electrode materials from lithium battery waste residue, the main purpose of which is to solve the problems of low metal recovery efficiency and high energy consumption in waste lithium-ion battery recycling technology.

[0005] To achieve the above object, the present invention provides a method for efficiently dissociating electrode materials from lithium battery waste residue, the method comprising:

[0006] Obtaining dissociation experimental data of the lithium battery waste residue, grouping the experimental data to obtain electrode material characteristics of the experimental data, and extracting a temperature data set, a dissociation efficiency data set, and a dissociation purity data set from the electrode material characteristics;

[0007] Calculating a decomposition temperature of each electrode material characteristic based on the temperature data set, the dissociation purity data set, and the dissociation efficiency data set;

[0008] calculating a metal vapor pressure characteristic of each electrode material using the decomposition temperature;

[0009] performing an optimal temperature analysis on material characteristics according to the metal vapor pressure, the decomposition temperature, the dissociation efficiency data set, and the dissociation purity data set to obtain dissociation optimal temperature data;

[0010] An efficient dissociation strategy for electrode materials in lithium battery waste is generated based on the optimal dissociation temperature data.

[0011] Optionally, grouping the experimental data to obtain electrode material characteristics of the experimental data includes:

[0012] performing data correction on the experimental data to obtain corrected data;

[0013] Grouping the correction data using the experimental time in the experimental data to obtain grouped data;

[0014] The electrode material type in the experimental data is used to perform feature extraction on the grouped data to obtain electrode material features.

[0015] Optionally, calculating the decomposition temperature of each electrode material characteristic based on the temperature dataset, the dissociation purity dataset, and the dissociation efficiency dataset includes:

[0016] constructing a dissociation temperature change curve according to the temperature data set, the dissociation purity data set, and the dissociation efficiency data set;

[0017] Calculating the temperature extreme point of the dissociation temperature change curve;

[0018] The decomposition temperature is selected from the temperature extreme points.

[0019] Optionally, calculating the metal vapor pressure of each electrode material characteristic using the decomposition temperature includes:

[0020] Calculating the saturation partial pressure of different electrode material types in the electrode material characteristics at the decomposition temperature one by one;

[0021] The saturated partial pressure is subjected to data correction to obtain the metal vapor pressure.

[0022] Optionally, performing optimal temperature analysis on material characteristics according to the metal vapor pressure, the decomposition temperature, the dissociation efficiency data set, and the dissociation purity data set to obtain dissociation optimal temperature data includes:

[0023] Filtering the temperature data with the maximum decomposition temperature from the decomposition temperatures as the initial temperature;

[0024] constructing an acceptance probability function based on the dissociation efficiency data set, the dissociation purity data set, and the metal vapor pressure;

[0025] Performing a nearest neighbor search on the initial temperature to obtain a candidate temperature value;

[0026] Calculating the acceptance probability of the temperature candidate value using the acceptance probability function;

[0027] Performing an acceptance judgment on the candidate temperature value using the acceptance probability function, and updating the initial temperature according to the judgment result to obtain a temperature variable;

[0028] The temperature variable is used as the initial temperature, and the process returns to the step of "performing a nearest neighbor search on the initial temperature to obtain a candidate temperature value" until the updated temperature exceeds a preset temperature threshold, thereby obtaining the dissociation optimal temperature data.

[0029] Optionally, constructing an acceptance probability function according to the dissociation efficiency dataset, the dissociation purity dataset, and the metal vapor pressure includes:

[0030] Performing weighted summation on the dissociation efficiency dataset and the dissociation purity dataset to obtain a reward function;

[0031] constructing a penalty function based on the metal vapor pressure;

[0032] Performing functional integration on the reward function and the objective function to obtain an objective function;

[0033] The target value of the candidate temperature value and the target value of the initial temperature are calculated respectively using the target function, and an acceptance probability function is constructed according to the target value of the initial temperature, the target value of the candidate temperature value, the initial temperature, and the candidate temperature value.

[0034] Optionally, generating an efficient dissociation strategy for electrode materials in lithium battery waste residue according to the dissociation optimal temperature data includes:

[0035] Determining the temperature parameters during the pyrolysis operation of lithium battery waste residue according to the dissociation optimal temperature data;

[0036] The temperature parameters are uploaded to the control system software of the preset pyrolysis equipment to obtain an efficient dissociation strategy for electrode materials in lithium battery waste.

[0037] In order to solve the above problems, the present invention also provides a highly efficient dissociation device for electrode materials in lithium battery waste residue, the device comprising:

[0038] a data extraction module for obtaining dissociation experimental data of the lithium battery waste residue, grouping the experimental data, obtaining electrode material characteristics of the experimental data, and extracting a temperature data set, a dissociation efficiency data set, and a dissociation purity data set from the electrode material characteristics;

[0039] a decomposition temperature calculation module, configured to calculate the decomposition temperature of each electrode material characteristic based on the temperature data set, the dissociation purity data set, and the dissociation efficiency data set;

[0040] a vapor pressure calculation module for calculating the metal vapor pressure of each electrode material characteristic using the decomposition temperature;

[0041] an optimal temperature calculation module, configured to perform an optimal temperature analysis on material characteristics according to the metal vapor pressure, the decomposition temperature, the dissociation efficiency data set, and the dissociation purity data set, to obtain dissociation optimal temperature data;

[0042] A strategy generation module is used to generate an efficient dissociation strategy for electrode materials in lithium battery waste according to the dissociation optimal temperature data.

[0043] In order to solve the above problem, the present invention further provides an electronic device, comprising:

[0044] at least one processor; and,

[0045] a memory communicatively connected to the at least one processor; wherein,

[0046] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the above-mentioned method for efficiently dissociating electrode materials in lithium battery waste.

[0047] In order to solve the above problems, the present invention also provides a computer-readable storage medium, which stores at least one computer program. The at least one computer program is executed by a processor in an electronic device to implement the above-mentioned method for efficiently dissociating electrode materials in lithium battery waste.

[0048] The embodiment of the present invention determines the temperature threshold at which the electrode material begins to decompose significantly, and the decomposition temperature obtained according to the temperature threshold can provide an accurate basis for the setting of the pyrolysis process, avoid insufficient dissociation or increased side reactions due to improper temperature, and thus improve the dissociation efficiency and dissociation purity of the dissociation; by comprehensively considering multiple key factors such as metal vapor pressure, decomposition temperature, dissociation efficiency and dissociation purity, find the optimal operating temperature that can provide the actual lithium battery waste slag dissociation process with both effective dissociation of all electrode materials and consideration of its key performance indicators (such as efficiency and purity), reduce insufficient dissociation and side reactions, improve the recovery rate and purity of the target metal element, and enhance resource recycling efficiency. Therefore, the efficient dissociation method, device, equipment and medium of electrode materials in lithium battery waste proposed by the present invention can solve the problems of low metal recovery efficiency and high energy consumption in waste lithium-ion battery recycling technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A schematic flow chart of a method for efficiently dissociating electrode materials from lithium battery waste provided by one embodiment of the present invention;

[0050] Figure 2 A schematic diagram of a process for calculating metal vapor pressure according to an embodiment of the present invention;

[0051] Figure 3 A schematic diagram of a process for constructing an acceptance probability function according to an embodiment of the present invention;

[0052] Figure 4 This is a functional module diagram of a highly efficient dissociation device for electrode materials in lithium battery waste provided by one embodiment of the present invention;

[0053] Figure 5 A schematic structural diagram of an electronic device for realizing the efficient dissociation method of electrode materials in lithium battery waste provided by one embodiment of the present invention.

[0054] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0055] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0056] Reference Figure 1 FIG. 1 is a flow chart of a method for efficiently dissociating electrode materials from lithium battery waste residue according to an embodiment of the present invention. In this embodiment, the method for efficiently dissociating electrode materials from lithium battery waste residue comprises:

[0057] S1. Obtain dissociation experimental data of the lithium battery waste residue, group the experimental data, obtain electrode material characteristics of the experimental data, and extract a temperature data set, a dissociation efficiency data set, and a dissociation purity data set from the electrode material characteristics.

[0058] In the embodiment of the present invention, the dissociation experimental data of the lithium battery waste residue refers to the result data obtained when the lithium battery waste residue is dissociated by high-temperature pyrolysis, including the experimental time, experimental conditions (such as temperature, pressure, reaction time, etc.), electrode material type, amount and composition of dissociation products, dissociation efficiency and dissociation purity, etc.

[0059] In the embodiment of the present invention, the electrode material characteristics refer to electrode material data sets of different groups of electrode materials obtained by grouping the experimental data according to electrode material properties in the experimental data.

[0060] In an embodiment of the present invention, by extracting electrode material characteristics from the experimental data, and extracting a temperature data set, a dissociation efficiency data set, and a dissociation purity data set from each electrode material characteristic, each performance indicator can be presented separately, and the influence of the temperature factor on the dissociation effect can be accurately obtained, thereby avoiding inaccurate analysis results caused by mixing data of different types of electrode materials.

[0061] In an embodiment of the present invention, grouping the experimental data to obtain electrode material characteristics of the experimental data includes:

[0062] performing data correction on the experimental data to obtain corrected data;

[0063] Grouping the correction data using the experimental time in the experimental data to obtain grouped data;

[0064] The electrode material type in the experimental data is used to perform feature extraction on the grouped data to obtain electrode material features.

[0065] In the embodiment of the present invention, by performing unit conversion on the experimental data, the same type of data in the experimental data, such as reaction time data, is converted into a unified unit standard to obtain calibration data.

[0066] In an embodiment of the present invention, by utilizing the experimental time in the experimental data, all experimental data within the same time interval are added to the same data set to obtain a time data set, and the time data set is sorted in chronological order and assigned a unique group number to obtain grouped data.

[0067] In an embodiment of the present invention, electrode material type data is screened out from the grouped data, type matching is performed on the grouped data according to the electrode material type data, and the group number, temperature, pressure, reaction time, amount and composition of dissociation products, dissociation efficiency and dissociation purity corresponding to the electrode material type in each grouped data are extracted. The group number, temperature, pressure, reaction time, amount and composition of dissociation products, dissociation efficiency and dissociation purity corresponding to the same electrode material type are added to the same data set to obtain electrode material characteristics.

[0068] In an embodiment of the present invention, by performing data correction on the experimental data and grouping the materials, the unique behavior patterns of different electrode material characteristics during the dissociation process can be integrated. Based on the temperature data set, dissociation efficiency data set, and dissociation purity data set of the different electrode material characteristics formed, the influence of the temperature factor on the dissociation process can be analyzed in a targeted manner.

[0069] S2. Calculate the characteristic decomposition temperature of each electrode material according to the temperature data set, the dissociation purity data set, and the dissociation efficiency data set.

[0070] In the embodiment of the present invention, the decomposition temperature refers to the inflection point where the dissociation efficiency or dissociation purity corresponding to different electrode materials in the electrode material characteristics changes with temperature, and the temperature corresponding to the inflection point is the decomposition temperature.

[0071] In an embodiment of the present invention, since different temperatures can affect the reaction efficiency and reaction purity of the electrode material, the calculated decomposition temperature can be used as a benchmark for determining the operating temperature of the dissociation process. According to the benchmark, inaccurate temperatures leading to insufficient dissociation or increased side reactions can be avoided, so that different electrode materials can be fully dissociated.

[0072] In an embodiment of the present invention, calculating the characteristic decomposition temperature of each electrode material according to the temperature dataset, the dissociation purity dataset, and the dissociation efficiency dataset includes:

[0073] constructing a dissociation temperature change curve according to the temperature data set, the dissociation purity data set, and the dissociation efficiency data set;

[0074] Calculating the temperature extreme point of the dissociation temperature change curve;

[0075] The decomposition temperature is selected from the temperature extreme points.

[0076] In an embodiment of the present invention, a dissociation temperature-dissociation purity conversion curve is constructed by taking the dissociation temperature in the temperature data set as the horizontal coordinate and the dissociation purity in the dissociation purity data set as the vertical coordinate. Each point on the curve represents a dissociation experiment performed at a specific temperature (horizontal coordinate value), and its dissociation purity (vertical coordinate value) reflects the purity of the product obtained after the electrode material dissociates at this temperature; with the dissociation temperature as the horizontal coordinate, but the dissociation efficiency as the vertical coordinate, another curve is drawn according to the aligned data set to obtain a dissociation temperature-dissociation efficiency conversion curve. Each point on the curve represents the degree to which the electrode material is successfully separated when the dissociation experiment is performed at the corresponding temperature, that is, the dissociation efficiency.

[0077] In an embodiment of the present invention, the first-order derivative value corresponding to each point in the dissociation temperature-dissociation purity conversion curve and the dissociation temperature-dissociation efficiency conversion curve is calculated, and the temperature value corresponding to the point where the first-order derivative value is 0 is taken as the temperature extreme point.

[0078] In an embodiment of the present invention, a point corresponding to a positive first-order derivative on the left and a negative first-order derivative on the right of the temperature extreme point is screened out from the temperature extreme point, and the point is taken as the local maximum value. A temperature point where the dissociation purity and dissociation efficiency are both higher than a preset value is screened out from the local maximum point, and the temperature point is taken as the decomposition temperature.

[0079] In an embodiment of the present invention, by calculating the decomposition temperature in the dissociation purity dataset and the dissociation efficiency dataset through the constructed temperature dataset, the temperature threshold at which the electrode material begins to significantly decompose under specific dissociation conditions can be determined, thereby reducing the probability of insufficient dissociation results and reducing the side reactions generated during the dissociation process.

[0080] S3. Calculate the metal vapor pressure characteristic of each electrode material using the decomposition temperature.

[0081] In the embodiments of the present invention, the metal vapor pressure refers to the gas phase partial pressure of the electrode material in the electrode material characteristics at the decomposition temperature when the electrode material component exists in a gaseous form in equilibrium with its solid or liquid form. The equilibrium state means that under given temperature (decomposition temperature) and total pressure conditions, the conversion rate between the metal vapor of the electrode material and the solid or liquid metal is equal, that is, the rate at which the metal atoms of the electrode material evaporate from the solid and liquid phases into the gas phase is equal to the rate at which the metal atoms condense from the gas phase back to the solid and liquid phases.

[0082] In the embodiments of the present invention, the metal vapor pressure is directly related to the volatility of the metal element. A higher vapor pressure means that the metal is more easily volatilized into the gas phase, which is conducive to recovery by gas capture. Calculating the metal vapor pressure helps predict the recovery efficiency of the metal element at different temperatures. Selecting or adjusting the dissociation conditions accordingly can maximize the recovery efficiency of the target metal.

[0083] Ginseng Figure 2 As shown, the method of calculating the metal vapor pressure of each electrode material characteristic using the decomposition temperature includes:

[0084] S21, calculating the saturated partial pressure of different electrode material types in the electrode material characteristics at the decomposition temperature one by one;

[0085] S22. Perform data correction on the saturated partial pressure to obtain metal vapor pressure.

[0086] In an embodiment of the present invention, the standard formation enthalpy and standard entropy of each electrode material characteristic under the chemical reaction at the decomposition temperature are obtained, the product value of the decomposition temperature and the standard entropy is calculated, and then the difference between the standard formation enthalpy and the product value is calculated, and the difference is calculated and divided by the negative value of the product of the preset gas constant and the decomposition temperature. The saturation partial pressure is obtained by taking the natural logarithm e as the base and the negative value as the exponent, wherein the standard formation enthalpy refers to the heat change occurring under standard conditions and the standard entropy refers to the change in the degree of disorder of the system before and after the reaction in the electrolysis reaction.

[0087] In the embodiment of the present invention, the ratio between the pressure data in the electrode material characteristics and the standard pressure is calculated, the ratio is used as a correction coefficient, and the product between the correction coefficient and the saturated partial pressure is calculated to obtain the actual partial pressure.

[0088] In the embodiment of the present invention, the calculated metal vapor pressure can reflect the trend and intensity of the metal elements in the electrode material being converted into gas during the dissociation process, thereby improving the recovery rate and purity of the target metal elements.

[0089] S4. Performing an optimal temperature analysis on material characteristics according to the metal vapor pressure, the decomposition temperature, the dissociation efficiency data set, and the dissociation purity data set to obtain dissociation optimal temperature data.

[0090] In the embodiment of the present invention, the optimal temperature analysis refers to finding an operating condition that can achieve the best efficiency, purity, etc. during the entire process of dissociating the electrode material of the lithium battery waste.

[0091] In detail, the optimal dissociation temperature data refers to the optimal operating temperature in the actual lithium battery waste dissociation process, which can not only ensure the effective dissociation of all electrode materials in the lithium battery waste, but also take into account the key performance indicators (such as efficiency and purity) of all its electrode materials. The decomposition temperature refers to the optimal temperature of the key performance indicators of different electrode materials.

[0092] In the embodiment of the present invention, a dissociation temperature that achieves the best balance of various indicators is found by integrating multiple key factors, thereby optimizing the overall process and providing the best process conditions for electrode materials in lithium battery waste.

[0093] In an embodiment of the present invention, performing optimal temperature analysis on material characteristics based on the metal vapor pressure, the decomposition temperature, the dissociation efficiency dataset, and the dissociation purity dataset to obtain dissociation optimal temperature data includes:

[0094] Filtering the temperature data with the maximum decomposition temperature from the decomposition temperatures as the initial temperature;

[0095] Performing a nearest neighbor search on the initial temperature to obtain a candidate temperature value;

[0096] constructing an acceptance probability function based on the dissociation efficiency data set, the dissociation purity data set, and the metal vapor pressure;

[0097] Calculating the acceptance probability of the temperature candidate value using the acceptance probability function;

[0098] Performing an acceptance judgment on the candidate temperature value using the acceptance probability function, and updating the initial temperature according to the judgment result to obtain a temperature variable;

[0099] The temperature variable is used as the initial temperature, and the process returns to the step of "performing a nearest neighbor search on the initial temperature to obtain a candidate temperature value" until the updated temperature exceeds a preset temperature threshold, thereby obtaining the dissociation optimal temperature data.

[0100] Ginseng Figure 3 As shown, constructing an acceptance probability function according to the dissociation efficiency data set, the dissociation purity data set, and the metal vapor pressure includes:

[0101] S31, performing weighted summation on the dissociation efficiency dataset and the dissociation purity dataset to obtain a reward function;

[0102] S32, constructing a penalty function according to the metal vapor pressure;

[0103] S33, performing function integration based on the reward function and the objective function to obtain an objective function;

[0104] S34. Calculate the target value of the candidate temperature value and the target value of the initial temperature using the target function, and construct an acceptance probability function based on the target value of the initial temperature, the target value of the candidate temperature value, the initial temperature, and the candidate temperature value.

[0105] In an embodiment of the present invention, a piecewise function is constructed by utilizing the calculated metal vapor pressure. That is, when the calculated metal vapor pressure is greater than a preset maximum value, the value of the penalty function is a negative value. When the calculated metal vapor pressure is less than the preset maximum value, the value of the penalty function is a positive value.

[0106] In the embodiment of the present invention, the objective function is obtained by adding the penalty function to the reward function result.

[0107] In the embodiment of the present invention, the acceptance probability function is as follows:

[0108]

[0109] Among them, A(T new ,T current ) is the acceptance probability, T new is the candidate temperature value, T current represents the initial temperature, F(T new ) is the target value of the candidate temperature value, F(T current ) is the target value of the initial temperature, a is the preset proportional coefficient, and min is the operator that takes the minimum of two numbers.

[0110] In the embodiment of the present invention, by taking the initial temperature as the search starting point and utilizing the preset search step length and boundary range, all dissociation temperatures within the boundary range are screened out in sequence to obtain the temperature candidate value.

[0111] In the embodiment of the present invention, first, it is determined one by one whether the reward function value corresponding to the temperature candidate value is greater than the reward function value of the initial temperature. If it is less than the reward function value of the initial temperature, the temperature candidate value is rejected, and the next temperature candidate value is judged; if it is greater than the reward function value of the initial temperature, the next judgment is performed; then, it is determined one by one whether the acceptance probability of the temperature candidate value is less than 0. If the acceptance probability is less than 0, the temperature candidate value is rejected, and the next temperature candidate value is judged. If the acceptance probability of the temperature candidate value is within the range of (0, 1), the temperature of the temperature candidate value is updated to obtain the temperature variable.

[0112] In the embodiment of the present invention, the temperature candidate value is updated using the following formula:

[0113] T(k)=T0*e -γk

[0114] Wherein, T(k) represents the temperature variable obtained by the kth update, T0 is the candidate temperature value, and γ is the preset cooling rate.

[0115] In an embodiment of the present invention, by determining the optimal dissociation temperature data for the material characteristics based on the metal vapor pressure, the decomposition temperature, the dissociation efficiency data set, and the dissociation purity data set, the temperature point at which the dissociation efficiency and purity are optimally balanced can be achieved, thereby reducing unnecessary side reactions and the generation of harmful substances during the dissociation of lithium battery waste residue, and achieving overall optimization of the electrode material recycling process.

[0116] S5. Generate an efficient dissociation strategy for electrode materials in lithium battery waste according to the optimal dissociation temperature data.

[0117] In the embodiment of the present invention, by utilizing the obtained optimal temperature to guide the dissociation process of the electrode material in the lithium battery waste residue, the efficiency of the electrode material recovery in the lithium battery waste residue can be guaranteed, the purity of the recovered electrode material can be maximized, and the resource recycling efficiency can be improved.

[0118] In an embodiment of the present invention, the efficient dissociation strategy of electrode materials in lithium battery waste residue generated according to the dissociation optimal temperature data includes:

[0119] Determining the temperature parameters during the pyrolysis operation of lithium battery waste residue according to the dissociation optimal temperature data;

[0120] The temperature parameters are uploaded to the control system software of the preset pyrolysis equipment to obtain an efficient dissociation strategy for electrode materials in lithium battery waste.

[0121] In an embodiment of the present invention, the optimal dissociation temperature data reveals that the electrode material can achieve the highest dissociation efficiency at a specific temperature. Using the optimal dissociation temperature data as a temperature parameter to generate an efficient dissociation strategy for electrode materials in lithium battery waste can ensure that electrode material metals such as lithium, cobalt, nickel, and manganese are effectively separated from the waste under optimal conditions, thereby greatly improving the metal recovery rate.

[0122] like Figure 4 1 is a functional module diagram of a highly efficient dissociation device for electrode materials in lithium battery waste provided by one embodiment of the present invention.

[0123] The highly efficient dissociation device 100 for electrode materials from lithium battery waste residue described in the present invention can be installed in an electronic device. Depending on the functionality to be implemented, the highly efficient dissociation device 100 for electrode materials from lithium battery waste residue can include a data extraction module 101, a decomposition temperature calculation module 102, a vapor pressure calculation module 103, an optimal temperature calculation module 104, and a strategy generation module 105. The modules described in the present invention, also referred to as units, refer to a series of computer program segments that can be executed by an electronic device processor and perform a fixed function, and are stored in the electronic device's memory.

[0124] In this embodiment, the functions of each module / unit are as follows:

[0125] The data extraction module 101 is used to obtain the dissociation experimental data of the lithium battery waste, group the experimental data, obtain the electrode material characteristics of the experimental data, and extract the temperature data set, the dissociation efficiency data set, and the dissociation purity data set from the electrode material characteristics;

[0126] The decomposition temperature calculation module 102 is used to calculate the decomposition temperature of each electrode material characteristic based on the temperature data set, the dissociation purity data set, and the dissociation efficiency data set;

[0127] The vapor pressure calculation module 103 is used to calculate the metal vapor pressure of each electrode material characteristic using the decomposition temperature;

[0128] The optimal temperature calculation module 104 is configured to perform optimal temperature analysis on material characteristics according to the metal vapor pressure, the decomposition temperature, the dissociation efficiency data set, and the dissociation purity data set to obtain dissociation optimal temperature data;

[0129] The strategy generation module 105 is used to generate an efficient dissociation strategy for electrode materials in lithium battery waste according to the dissociation optimal temperature data.

[0130] In detail, each module of the highly efficient dissociation device 100 for electrode materials in lithium battery waste according to the embodiment of the present invention is used in the same manner as above. Figures 1 to 3The same technical means as the efficient dissociation method of electrode materials in lithium battery waste described in and can produce the same technical effects are used, which will not be repeated here.

[0131] like Figure 5 1 is a schematic structural diagram of an electronic device for realizing a method for efficiently dissociating electrode materials from lithium battery waste provided by one embodiment of the present invention.

[0132] The electronic device 1 may include a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a program for efficiently dissociating electrode materials from lithium battery waste.

[0133] In some embodiments, the processor 10 may be composed of an integrated circuit, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and a combination of various control chips. The processor 10 is the control core (Control Unit) of the electronic device, connecting the various components of the entire electronic device using various interfaces and lines, and executing or executing programs or modules stored in the memory 11 (for example, executing a program for the efficient dissociation of electrode materials in lithium battery waste, etc.), as well as calling data stored in the memory 11, to execute various functions of the electronic device and process data.

[0134] The memory 11 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a mobile hard disk, a multimedia card, a card-type memory (for example, an SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. The memory 11 can be an internal storage unit of an electronic device in some embodiments, such as a mobile hard disk of the electronic device. The memory 11 can also be an external storage device of an electronic device in other embodiments, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Further, the memory 11 can also include both an internal storage unit of the electronic device and an external storage device. The memory 11 can not only be used to store application software and various types of data installed in the electronic device, such as the code of the efficient dissociation program of electrode materials in lithium battery waste, but can also be used to temporarily store data that has been output or is to be output.

[0135] The communication bus 12 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable communication between the memory 11 and at least one processor 10, etc.

[0136] The communication interface 13 is used for communication between the above-mentioned electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a display (Display), an input unit (such as a keyboard (Keyboard)), optionally, the user interface may also be a standard wired interface, a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode, organic light-emitting diode) touch device, etc. Among them, the display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device and to display a visual user interface.

[0137] The figure only shows an electronic device with components. Those skilled in the art will understand that the structure shown in the figure does not constitute a limitation on the electronic device, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0138] For example, although not shown, the electronic device may further include a power source (such as a battery) for powering various components. Preferably, the power source may be logically connected to the at least one processor 10 via a power management device, thereby implementing functions such as charge management, discharge management, and power consumption management through the power management device. The power source may further include any components such as one or more DC or AC power sources, a recharging device, a power failure detection circuit, a power converter or inverter, a power status indicator, etc. The electronic device may further include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0139] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0140] The efficient dissociation program of electrode materials in lithium battery waste stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When executed in the processor 10, it can achieve the following:

[0141] a data extraction module for obtaining dissociation experimental data of the lithium battery waste residue, grouping the experimental data, obtaining electrode material characteristics of the experimental data, and extracting a temperature data set, a dissociation efficiency data set, and a dissociation purity data set from the electrode material characteristics;

[0142] a decomposition temperature calculation module, configured to calculate the decomposition temperature of each electrode material characteristic based on the temperature data set, the dissociation purity data set, and the dissociation efficiency data set;

[0143] a vapor pressure calculation module for calculating the metal vapor pressure of each electrode material characteristic using the decomposition temperature;

[0144] an optimal temperature calculation module, configured to perform an optimal temperature analysis on material characteristics according to the metal vapor pressure, the decomposition temperature, the dissociation efficiency data set, and the dissociation purity data set, to obtain dissociation optimal temperature data;

[0145] A strategy generation module is used to generate an efficient dissociation strategy for electrode materials in lithium battery waste according to the dissociation optimal temperature data.

[0146] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to the description of the relevant steps in the corresponding embodiment of the accompanying drawings, which will not be repeated here.

[0147] Furthermore, if the modules / units integrated into the electronic device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0148] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program. When the computer program is executed by a processor of an electronic device, the computer program can implement:

[0149] a data extraction module for obtaining dissociation experimental data of the lithium battery waste residue, grouping the experimental data, obtaining electrode material characteristics of the experimental data, and extracting a temperature data set, a dissociation efficiency data set, and a dissociation purity data set from the electrode material characteristics;

[0150] a decomposition temperature calculation module, configured to calculate the decomposition temperature of each electrode material characteristic based on the temperature data set, the dissociation purity data set, and the dissociation efficiency data set;

[0151] a vapor pressure calculation module for calculating the metal vapor pressure of each electrode material characteristic using the decomposition temperature;

[0152] an optimal temperature calculation module, configured to perform an optimal temperature analysis on material characteristics according to the metal vapor pressure, the decomposition temperature, the dissociation efficiency data set, and the dissociation purity data set, to obtain dissociation optimal temperature data;

[0153] A strategy generation module is used to generate an efficient dissociation strategy for electrode materials in lithium battery waste according to the dissociation optimal temperature data.

[0154] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the module division is merely a logical function division, and other division methods may be used in actual implementation.

[0155] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network elements. Some or all of the modules may be selected to achieve the purpose of the solution of this embodiment according to actual needs.

[0156] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional modules.

[0157] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0158] Therefore, no matter from which point of view, the embodiments should be regarded as illustrative and non-restrictive, and the scope of the present invention is not limited only according to the above description, and it is intended that all changes within the meaning and scope of equivalent elements falling within the scope of protection are included in the present invention.

[0159] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to achieve optimal results.

[0160] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in a system may also be implemented by a single unit or device through software or hardware. Terms such as first and second are used to indicate names and do not imply any particular order.

[0161] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for efficiently dissociating electrode materials from lithium battery waste residue, characterized in that: The method comprises: Obtaining dissociation experimental data of the lithium battery waste residue, grouping the experimental data to obtain electrode material characteristics of the experimental data, and extracting a temperature data set, a dissociation efficiency data set, and a dissociation purity data set from the electrode material characteristics; Calculating a decomposition temperature of each electrode material characteristic based on the temperature data set, the dissociation purity data set, and the dissociation efficiency data set; calculating a metal vapor pressure characteristic of each electrode material using the decomposition temperature; performing an optimal temperature analysis on material characteristics according to the metal vapor pressure, the decomposition temperature, the dissociation efficiency data set, and the dissociation purity data set to obtain dissociation optimal temperature data; An efficient dissociation strategy for electrode materials in lithium battery waste is generated based on the optimal dissociation temperature data.

2. The method for efficiently dissociating electrode materials from lithium battery waste according to claim 1, wherein: The experimental data are grouped to obtain electrode material characteristics of the experimental data, including: performing data correction on the experimental data to obtain corrected data; Grouping the correction data using the experimental time in the experimental data to obtain grouped data; The electrode material type in the experimental data is used to perform feature extraction on the grouped data to obtain electrode material features.

3. The method for efficiently dissociating electrode materials from lithium battery waste according to claim 1, wherein: Calculating the decomposition temperature of each electrode material characteristic according to the temperature data set, the dissociation purity data set, and the dissociation efficiency data set includes: constructing a dissociation temperature change curve according to the temperature data set, the dissociation purity data set, and the dissociation efficiency data set; Calculating the temperature extreme point of the dissociation temperature change curve; The decomposition temperature is selected from the temperature extreme points.

4. The method for efficiently dissociating electrode materials from lithium battery waste according to claim 1, wherein: The calculating of the metal vapor pressure characteristic of each electrode material by using the decomposition temperature includes: Calculating the saturation partial pressure of different electrode material types in the electrode material characteristics at the decomposition temperature one by one; The saturated partial pressure is subjected to data correction to obtain the metal vapor pressure.

5. The method for efficiently dissociating electrode materials from lithium battery waste according to claim 1, wherein: The performing of an optimal temperature analysis on material characteristics according to the metal vapor pressure, the decomposition temperature, the dissociation efficiency data set, and the dissociation purity data set to obtain dissociation optimal temperature data includes: Filtering the temperature data with the maximum decomposition temperature from the decomposition temperatures as the initial temperature; Performing a nearest neighbor search on the initial temperature to obtain a candidate temperature value; constructing an acceptance probability function based on the dissociation efficiency data set, the dissociation purity data set, and the metal vapor pressure; Calculating the acceptance probability of the temperature candidate value using the acceptance probability function; Performing an acceptance judgment on the candidate temperature value using the acceptance probability function, and updating the initial temperature according to the judgment result to obtain a temperature variable; The temperature variable is used as the initial temperature, and the process returns to the step of "performing a nearest neighbor search on the initial temperature to obtain a candidate temperature value" until the temperature variable exceeds a preset temperature threshold, thereby obtaining the dissociation optimal temperature data.

6. The method for efficiently dissociating electrode materials from lithium battery waste as claimed in claim 5, characterized in that: The constructing an acceptance probability function according to the dissociation efficiency dataset, the dissociation purity dataset, and the metal vapor pressure includes: Performing weighted summation on the dissociation efficiency dataset and the dissociation purity dataset to obtain a reward function; constructing a penalty function based on the metal vapor pressure; Performing function integration based on the reward function and the penalty function to obtain an objective function; The target value of the candidate temperature value and the target value of the initial temperature are calculated respectively using the target function, and an acceptance probability function is constructed according to the target value of the initial temperature, the target value of the candidate temperature value, the initial temperature, and the candidate temperature value.

7. The method for efficiently dissociating electrode materials from lithium battery waste according to claim 1, wherein: The method of generating an efficient dissociation strategy for electrode materials in lithium battery waste residue according to the dissociation optimal temperature data includes: Determining the temperature parameters during the pyrolysis operation of lithium battery waste residue according to the dissociation optimal temperature data; The temperature parameters are uploaded to the control system software of the preset pyrolysis equipment to obtain an efficient dissociation strategy for electrode materials in lithium battery waste.

8. An efficient dissociation device for electrode materials in lithium battery waste residue, characterized in that: The device comprises: a data extraction module for obtaining dissociation experimental data of the lithium battery waste residue, grouping the experimental data, obtaining electrode material characteristics of the experimental data, and extracting a temperature data set, a dissociation efficiency data set, and a dissociation purity data set from the electrode material characteristics; a decomposition temperature calculation module, configured to calculate the decomposition temperature of each electrode material characteristic based on the temperature data set, the dissociation purity data set, and the dissociation efficiency data set; a vapor pressure calculation module for calculating the metal vapor pressure of each electrode material characteristic using the decomposition temperature; an optimal temperature calculation module, configured to perform an optimal temperature analysis on material characteristics according to the metal vapor pressure, the decomposition temperature, the dissociation efficiency data set, and the dissociation purity data set, to obtain dissociation optimal temperature data; A strategy generation module is used to generate an efficient dissociation strategy for electrode materials in lithium battery waste according to the dissociation optimal temperature data.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the efficient dissociation method of electrode materials in lithium battery waste as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the efficient dissociation method of electrode materials in lithium battery waste residue as claimed in any one of claims 1 to 7 is implemented.

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