System and method for detecting concentration distribution of doping elements in lithium iron phosphate cathode material and application

Abstract

The application discloses a detection system and method for concentration distribution of doped elements in a lithium iron phosphate positive electrode material and application, and relates to the technical field of battery material characterization. The detection system comprises an element determination module configured to determine the mass concentration of a matrix element and the mass concentration of a doped element in N filtrates; and a data processing module configured to: calculate the relative solubility of the matrix element according to the mass concentration of the matrix element, and convert the relative solubility into a particle radial position parameter based on a spherical particle geometric model; and determine the radial concentration distribution of the doped element according to the particle radial position parameter and a target parameter proportion, which is helpful to low-cost and high-efficiency characterization of the concentration distribution of the doped element.

Description

Technical Field

[0001] This application relates to the field of battery material characterization technology, and more specifically, to a detection system, method, and application for the concentration distribution of doped elements in lithium iron phosphate cathode materials. Background Technology

[0002] Lithium iron phosphate (LiFePO4, LFP) is one of the mainstream cathode materials for lithium-ion batteries, widely used in electric vehicles and energy storage due to its high safety, long cycle life, and low cost. To further improve the electrochemical performance of lithium iron phosphate materials, especially its rate performance (fast charging and discharging capability) and low-temperature performance, elemental doping (such as Ti, V, Nb, Zr, etc.) is typically introduced during the synthesis process. Doping elements, by entering the crystal lattice or modifying the particle surface / interface, can effectively improve the electronic conductivity and lithium-ion diffusion kinetics of the material.

[0003] However, existing research and manufacturing processes often focus only on the total content of dopants (i.e., doping amount), neglecting the geometrical distribution of dopants within lithium iron phosphate particles (i.e., concentration gradient). The enrichment degree of dopants on the particle surface or their gradient distribution within the particle directly affects the DC internal resistance (DCR) of the assembled battery. For example, excessive surface doping may increase lithium-ion insertion / extraction resistance, thereby reducing fast-charging performance; while uniform internal doping helps improve overall structural stability. Therefore, clearly defining the concentration distribution of dopants can directly predict the battery's fast-charging and discharging capabilities at the material level.

[0004] Currently, characterization of dopant concentration distribution mainly relies on high-end microstructure characterization techniques, such as scanning electrochemical microscopy and atomic probe tomography. While these methods offer high precision, they are expensive, have long detection cycles, are complex to operate, and require extremely high sample preparation standards, making them unsuitable for large-scale, rapid detection and quality control in industrial production. Therefore, there is an urgent need in this field for a low-cost, high-efficiency method to characterize the concentration distribution of dopant elements within materials, enabling rapid assessment of their fast charge / discharge capabilities and optimization of production processes. Summary of the Invention

[0005] The main objective of this application is to provide a detection system, method, and application for the concentration distribution of doped elements in lithium iron phosphate cathode materials, in order to solve the problem of the lack of a low-cost and high-efficiency method for characterizing the concentration distribution of doped elements inside lithium iron phosphate cathode materials in the prior art.

[0006] To achieve the above objectives, according to a first aspect of this application, a detection system for the concentration distribution of doped elements in a lithium iron phosphate cathode material is provided, comprising:

[0007] The element determination module is used to determine the mass concentration of matrix elements and dopant elements in N filtrates. The N hydrochloric acid filtrates are determined by gradient acid dissolution and dilution of N equal masses of lithium iron phosphate cathode material to the same mass, where N≥8.

[0008] The data processing module is used for:

[0009] The relative solubility of the matrix elements is calculated based on their mass concentration, and then converted into radial position parameters of the particles based on the geometric model of spherical particles.

[0010] The radial concentration distribution of the dopant element is determined based on the ratio of the particle radial position parameter to the target parameter. The target parameter ratio includes the molar ratio of the dopant element in the hydrochloric acid solution or the relative molar ratio of the dopant element in the hydrochloric acid solution. The target parameter ratio of the hydrochloric acid solution is determined based on the mass concentration of the matrix element in the hydrochloric acid solution and the mass concentration of the dopant element in the hydrochloric acid solution.

[0011] According to another aspect of this application, a method for detecting the concentration distribution of doped elements in a lithium iron phosphate cathode material is also provided, comprising:

[0012] N equal masses of lithium iron phosphate cathode material were subjected to gradient acid dissolution treatment and diluted to the same mass to obtain N filtrates; where N≥8;

[0013] Determine the mass concentration of matrix elements and dopant elements in N filtrates;

[0014] Calculate the relative solubility of the matrix element in N filtrates based on the mass concentration of the matrix element;

[0015] Based on the geometric model of spherical particles, the relative solubility is converted into the radial position parameter of the particles;

[0016] The target parameter ratio is determined based on the mass concentration of the matrix element and the mass concentration of the dopant element in the hydrochloric acid solution; wherein, the target parameter ratio of the hydrochloric acid solution includes the molar ratio of the dopant element or the relative molar ratio of the dopant element.

[0017] The radial concentration distribution of doped elements in hydrochloric acid solution is determined based on the ratio of the radial position parameters of particles in the hydrochloric acid solution to the target parameters of the hydrochloric acid solution.

[0018] According to another aspect of this application, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein the program, when executed, performs the above-described method for detecting the concentration distribution of doped elements in lithium iron phosphate cathode materials.

[0019] According to another aspect of this application, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to execute the above-described method for detecting the concentration distribution of doped elements in lithium iron phosphate cathode materials via the computer program.

[0020] According to another aspect of this application, a computer program product is also provided, including a computer program that executes the above-described method for detecting the concentration distribution of doped elements in lithium iron phosphate cathode materials via a processor.

[0021] According to another aspect of this application, a method for screening lithium iron phosphate cathode materials is also provided, comprising: obtaining a radial concentration distribution curve of dopant elements in the lithium iron phosphate cathode material to be tested according to the above-described detection method for the concentration distribution of dopant elements in lithium iron phosphate cathode materials;

[0022] At least one characteristic parameter is extracted from the radial concentration distribution curve of hydrochloric acid solution. Based on the comparison results of the characteristic parameters, the target cathode material is screened from multiple cathode materials to be tested.

[0023] According to another aspect of this application, a lithium iron phosphate cathode material is also provided, which is obtained by screening using the above-described screening method for lithium iron phosphate cathode materials.

[0024] According to another aspect of this application, a battery is also provided, including a positive electrode, a negative electrode, a separator, and an electrolyte; the hydrochloric acid solution positive electrode includes a positive current collector and a positive active material layer disposed on at least one side surface of the hydrochloric acid solution positive current collector; the hydrochloric acid solution positive active material comprises the above-mentioned lithium iron phosphate positive electrode material.

[0025] According to another aspect of this application, a battery pack is also provided, comprising a plurality of the above-described batteries, wherein the plurality of batteries are connected in series and / or in parallel.

[0026] According to another aspect of this application, a battery pack is also provided, including the battery pack described above.

[0027] By applying the technical solution of this application, the mass concentrations of matrix elements and dopant elements in N filtrates are determined by an elemental analysis module, providing basic data for distribution analysis. The data processing module calculates the relative solubility using the mass concentrations of matrix elements and converts the relative solubility into radial position parameters of the particles based on a spherical particle geometry model, realizing a mapping from macroscopic solubility to the radial position within the microscopic particles. Simultaneously, the data processing module determines the molar percentage or relative molar percentage of the dopant element based on the mass concentrations of the matrix elements and dopant elements, and determines the radial concentration distribution of the dopant element by combining the radial position parameters of the particles. The detection system provided by this application characterizes the concentration distribution of dopant elements within lithium iron phosphate cathode materials, solving the problem of the lack of low-cost, high-efficiency methods for characterizing the concentration distribution of dopant elements within lithium iron phosphate cathode materials in existing technologies. This facilitates the low-cost and high-efficiency characterization of the concentration distribution of dopant elements within lithium iron phosphate cathode materials. Attached Figure Description

[0028] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0029] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 This is a structural block diagram of a detection system for the concentration distribution of doped elements in a lithium iron phosphate cathode material according to an embodiment of this application;

[0031] Figure 2 This is a structural block diagram of a detection system for the concentration distribution of doped elements in another lithium iron phosphate cathode material according to an embodiment of this application.

[0032] Figure 3 This is a flowchart illustrating a method for detecting the concentration distribution of doped elements in a lithium iron phosphate cathode material according to an embodiment of this application.

[0033] Figure 4 This is the radial concentration distribution curve of titanium and vanadium elements inside the lithium iron phosphate cathode material particles according to Example 1 of this application.

[0034] Explanation of reference numerals in the attached figures:

[0035] 100 - Sample processing module; 200 - Elemental analysis module; 300 - Data processing module; 400 - Performance evaluation module. Detailed Implementation

[0036] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0037] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0038] The following appropriately discloses an embodiment of a battery according to this application. However, unnecessary detailed descriptions may be omitted. For example, detailed descriptions of well-known matters and repetitive descriptions of practically identical structures may be omitted. This is to avoid making the following description unnecessarily lengthy and to facilitate understanding by those skilled in the art. Furthermore, the following description is provided to enable those skilled in the art to fully understand this application and is not intended to limit the subject matter of the claims.

[0039] The lithium iron phosphate cathode material in this application refers to a LiFePO4-based cathode active material with an olivine-type crystal structure. This material is typically synthesized by solid-state method, sol-gel method or solvothermal method, and at least one doping element (such as Ti, V, Nb, etc.) is introduced during the synthesis process to optimize its electrochemical performance.

[0040] The lithium iron phosphate cathode material involved in this application can be a single doped lithium iron phosphate particle or a doped lithium iron phosphate particle with surface coating treatment. This application aims to characterize the concentration distribution characteristics of doped elements in the radial direction of a single particle in the above-mentioned lithium iron phosphate cathode material, thereby providing a basis for material process optimization and battery performance prediction.

[0041] Figure 1 This is a structural block diagram of a detection system for the concentration distribution of doped elements in a lithium iron phosphate cathode material according to an embodiment of this application; as shown... Figure 1 As shown, it includes:

[0042] The element determination module 200 is used to determine the mass concentration of matrix elements and dopant elements in N filtrates. The N hydrochloric acid filtrates are determined by gradient acid dissolution and dilution of N equal masses of lithium iron phosphate cathode material to the same mass, where N≥8.

[0043] Data processing module 300 is used for:

[0044] The relative solubility of the matrix elements is calculated based on their mass concentration, and then converted into radial position parameters of the particles based on the geometric model of spherical particles.

[0045] The radial concentration distribution of dopant elements in hydrochloric acid solution is determined based on the ratio of radial position parameters of particles in hydrochloric acid solution to target parameters. The ratio of target parameters in hydrochloric acid solution includes the molar percentage of dopant elements or the relative molar percentage of dopant elements. The ratio of target parameters in hydrochloric acid solution is determined based on the mass concentration of matrix elements and the mass concentration of dopant elements in hydrochloric acid solution.

[0046] The aforementioned detection system for the concentration distribution of dopant elements in lithium iron phosphate cathode materials comprises an element determination module used to measure the mass concentrations of matrix elements and dopant elements in N filtrates, acquiring basic data to ensure accurate information. A data processing module performs logical operations and transformations on the aforementioned data. First, it calculates the relative solubility of the matrix elements based on their mass concentrations, and then converts the relative solubility into radial position parameters of the particles based on a spherical particle geometry model. Simultaneously, it combines the mass concentrations of the matrix elements and the dopant elements to determine the molar percentage or relative molar percentage of the dopant elements. Finally, it combines the radial position parameters of the particles with the molar percentage or relative molar percentage of the dopant elements to determine the radial concentration distribution of the dopant elements in the material, thereby characterizing the internal doping distribution of the lithium iron phosphate cathode material. This detection system directly solves the technical problem of the lack of a low-cost, high-efficiency method for characterizing the concentration distribution of dopant elements within lithium iron phosphate cathode materials in existing technologies.

[0047] In one exemplary embodiment, such as Figure 2 As shown, it also includes a sample processing module 100, which is used to: place N equal masses of lithium iron phosphate cathode material into N independent containers, add an acidic solution with increasing volume to each container, stir and react for the same time, and then dilute to the same mass to obtain N mixed solutions; filter the N mixed solutions to obtain N filtrates.

[0048] In this embodiment, the sample processing module is used to place N equal masses of lithium iron phosphate cathode material into N independent containers. An acidic solution with increasing volume is added to each container. By setting different volumes of acidic solution, the total amount of reactants contacted by each sample in the initial stage of the reaction varies, thereby inducing different degrees of dissolution on the particle surface during the stirring reaction, forming a dissolution gradient from shallow to deep. Increasing volume means that the amount of acid in subsequent containers is greater than that in previous containers, ensuring that the dissolution driving force in each independent container changes in a stepwise manner, thus obtaining dissolved phases representing different radial depths. After stirring for the same amount of time, dilution to the same mass means that after the reaction in each container has been fully completed, solvent (such as water) is added to all the mixtures until the total mass of liquid in each container is equal. This helps to eliminate the difference in total solution volume caused by the different initial acid volumes, so that the elemental mass concentrations obtained in subsequent measurements can directly reflect the solute content per unit mass of solution, providing a unified benchmark for lateral comparison between samples of different gradients. Filtering the N mixtures separately utilizes filter media such as filter paper or filter membranes to intercept undissolved solid residues suspended in the mixture after the reaction, allowing only the liquid phase containing dissolved elements to pass through. This separates a pure filtrate that reflects only the elemental composition of the dissolved phase. Through these steps, the detection system can accurately acquire N filtrates corresponding to different degrees of solubility. Combined with subsequent elemental determination and data processing modules, this helps to further improve the accuracy of characterization and reduce errors.

[0049] In an exemplary embodiment, the acidic dissolving solution includes aqua regia and hydrogen peroxide. The hydrochloric acid solution is added by sequentially introducing different volumes of the acidic dissolving solution into each container according to an arithmetic or geometric sequence, with a fixed volume of hydrogen peroxide added to each container. In this embodiment, the sample processing module is used to increase the volume of the acidic dissolving solution in each container sequentially according to an arithmetic or geometric sequence. Specifically, the amount of acid added to the N independent containers is arranged in a mathematically ordered manner. For example, if an arithmetic sequence is used, the difference in acid volume between adjacent containers remains constant (e.g., adding 10mL, 20mL, 30mL, 40mL, 50mL, 60mL, etc.). If a geometric sequence is used, the acid volume between adjacent containers is a fixed multiple (e.g., adding 10mL, 20mL, 40mL, 80mL, etc.). This stepwise acid addition method creates a clear and quantifiable difference in the concentration gradient of the reaction system in the acidic environment within different containers. As a result, during the stirring reaction, the dopant elements and matrix elements on the surface of the lithium iron phosphate cathode material particles are gradually released according to the preset dissolution rate gradient. This avoids large differences in the degree of dissolution caused by random or irregular changes in the amount of acid added. It helps to improve the accuracy of the data and the smoothness of the distribution curve when calculating the radial position parameters of the particles through the relative solubility of the matrix elements, thereby further improving the accuracy of the characterization of the radial concentration distribution of dopant elements.

[0050] In one exemplary embodiment, aqua regia comprises concentrated hydrochloric acid and concentrated nitric acid, with a volume ratio of concentrated hydrochloric acid to concentrated nitric acid of (2~4):1, and a mass fraction of hydrogen peroxide of 5%~30%. In this embodiment, concentrated hydrochloric acid and concentrated nitric acid are mixed in this specific volume ratio to form aqua regia with strong oxidizing and complexing capabilities, which can effectively destroy the crystal structure of lithium iron phosphate materials and dissolve the iron matrix. The 5%~30% hydrogen peroxide acts as an auxiliary oxidant, further accelerating the oxidation and dissolution process and stabilizing the reaction environment. The synergistic effect of the two ensures that the matrix elements (e.g., iron) can be gradually dissolved in a highly repeatable manner and in accordance with stoichiometric laws during acid dissolution steps at different volume gradients. By controlling this specific acid composition and ratio, the problem of unstable dissolution rate or insufficient selectivity caused by fluctuations in acid type or concentration is avoided. This makes the relative solubility calculated based on the mass concentration of matrix elements more accurate and reliable, thereby improving the characterization accuracy and reproducibility of the particle radial position parameters obtained from the spherical particle geometric model conversion and the finally determined radial concentration distribution of doped elements.

[0051] Specifically, the volume ratio of concentrated hydrochloric acid to concentrated nitric acid can be 2:1, 2.5:1, 3:1, 3.5:1, 4:1, or any combination thereof, and the mass fraction of hydrogen peroxide can be 5%, 10%, 15%, 20%, 25%, 30%, or any combination thereof.

[0052] In one exemplary embodiment, the element determination module is used to determine the mass concentration of the matrix element and the mass concentration of the dopant element in N filtrates using inductively coupled plasma atomic emission spectrometry (ICP-AES). In this embodiment, the element determination module is used to perform component analysis of the filtrate using ICP-AES, where ICP-AES refers to using high-temperature plasma to excite atoms or ions in the sample, causing them to emit spectral signals of characteristic wavelengths, thereby achieving simultaneous quantitative detection of multiple elements. In the specific implementation of this application, the sample processing module is used to introduce the output N filtrates sequentially or simultaneously into the sample introduction system of the spectrometer. The instrument directly obtains the mass concentration data of the matrix elements (such as iron, lithium, and phosphorus) and dopants (such as titanium and vanadium) in the solution by scanning and exciting the matrix elements (such as iron, lithium, and phosphorus) and dopants (such as titanium and vanadium) in each filtrate. This process does not require multiple independent chemical titrations or separation operations for different elements as in traditional methods. By introducing this measurement method, this application achieves high-precision synchronous acquisition of matrix elements and dopants in a single test process. This not only greatly improves the efficiency of multi-element data sampling, but also effectively avoids the accumulation of errors caused by multiple independent measurements. It helps to provide a reliable and highly time-synchronous raw data foundation for the subsequent data processing module to accurately calculate the relative solubility, molar proportion, and reconstruct the radial concentration distribution of dopants based on the spherical particle geometric model.

[0053] In an exemplary embodiment, the matrix element is iron, and the dopant element includes at least one of titanium and vanadium. In this embodiment, the matrix element is specifically defined as iron, and the dopant element is specifically defined as at least one of titanium or vanadium. Iron, as a backbone component of lithium iron phosphate cathode material, exhibits uniform distribution among particles and can serve as a benchmark for measuring particle dissolution progress. Titanium and vanadium are key dopants used to improve the material's conductivity and structural stability. This allows the calculation logic based on a spherical geometry model to be directly applied to actual lithium iron phosphate systems. By measuring the relative solubility of iron in the filtrate, the radial position parameters of the particles can be inferred. Simultaneously, the molar ratio of titanium or vanadium to iron is measured, thereby converting the dissolution data into a specific radial concentration distribution map of the dopant element. This specific definition helps achieve specific and precise detection of the dopant distribution, further improving the applicability and detection efficiency of this method in actual production process control.

[0054] In one exemplary embodiment, the data processing module is configured to: determine the maximum concentration value of the matrix element based on the mass concentration of the matrix element in N filtrates, and calculate the relative solubility of the matrix element in each of the N filtrates based on the maximum concentration value. In this embodiment, the data processing module is configured to: select the highest concentration value from the N sets of mass concentration data of matrix elements (such as iron) output by the element determination module, and use this as a unified benchmark value (i.e., the denominator) reflecting the complete dissolution or dissolution limit state of the material; subsequently, using this maximum concentration value as a reference, perform a ratio calculation on the mass concentration (i.e., the numerator) of the matrix element measured in each filtrate, thereby obtaining the relative solubility corresponding to each filtrate. Specifically, during the gradient acid dissolution process, as the amount of acid added increases, the degree of material dissolution gradually deepens, and the absolute concentration of matrix elements in each filtrate also changes accordingly. If the absolute concentration is directly used to map the particle position, the radial position calculation will be distorted due to the difference in the total amount of dissolution per unit volume. By introducing the maximum concentration value as a normalization benchmark, the relative solubility of all filtrates is converted into a ratio relative to the maximum concentration value (between 0 and 1). This helps to eliminate the absolute numerical deviation caused by fluctuations in sample dilution factor or acid addition efficiency, ensuring the comparability of data under different amounts of acid. Consequently, when the relative solubility is converted into particle radial position parameters using the spherical particle geometric model, it can accurately reflect the true distribution gradient of dopant elements from the surface to the core inside the material, which helps to further improve the accuracy and reliability of concentration distribution characterization.

[0055] In one exemplary embodiment, the data processing module is configured to determine the relative solubility of matrix elements in N filtrates by:

[0056] R Fe,i =(Fe i / Fe max ) × 100%;

[0057] Among them, R Fe,i Let Fe be the relative solubility of the matrix element in the i-th filtrate. max The maximum concentration value of the matrix element, Fe i Let N be the mass concentration of the matrix element in the i-th filtrate, where 1 ≤ i ≤ N.

[0058] In this embodiment, the data processing module is used to identify Fe from the measurement results of N filtrates. max Then, the Fe corresponding to each filtrate was... i Divide by Fe respectively maxMultiply by 100% to normalize the matrix element content of each filtrate to a relative solubility value between 0 and 100%. This calculation process allows for accurate mapping of the radial position inside the particles through relative proportions, even if the absolute concentration fluctuates due to slight differences in particle solubility in different acid dissolution steps. This effectively further improves the accuracy and comparability of the characterization of doped element concentration distribution in lithium iron phosphate cathode materials.

[0059] In an exemplary embodiment, the data processing module is configured to convert relative solubility into particle radial position parameters in the following manner:

[0060] X i =[1-(1-R Fe,i ) 1 / 3 ×100%;

[0061] Among them, X i R is the radial position parameter corresponding to the i-th filtrate. Fe,i denoted as , where is the relative solubility of the matrix element in the i-th filtrate.

[0062] In this embodiment, the data processing module is used to process the calculated relative solubility R based on the spherical particle geometric model. Fe,i Substituting these values ​​into the formula, we can determine the radial position parameter X corresponding to the i-th filtrate. i By directly utilizing the mass concentration change of matrix elements during the macroscopic dissolution process, and through the cubic relationship between the volume and radius of the sphere (i.e. the geometric correspondence between the proportion of dissolved volume and the proportion of the radius of the remaining undissolved core), the cumulative dissolution rate is accurately converted into the radial distance coordinates inside the particle, so that the final radial concentration distribution can accurately reflect the real gradient change of dopant elements from the surface to the core inside the particle.

[0063] In one exemplary embodiment, the data processing module is configured to determine the molar percentage of the dopant element by:

[0064] M i =n d,i / (n d,i +n Fe,i )×100%;

[0065] Among them, M i Let n be the molar percentage of the dopant element in the i-th filtrate. d,i Let n be the molar number of the dopant element in the i-th filtrate. Fe,i The molar number of matrix elements in the i-th filtrate;

[0066] The data processing module is used to determine the relative molar percentage of dopant elements in the following ways:

[0067] Yi =(M i / M min ) × 100%;

[0068] Among them, Y i M represents the relative molar percentage of the dopant element in the i-th filtrate. i M represents the molar percentage of the dopant element in the i-th filtrate. min This represents the minimum molar percentage of the dopant element.

[0069] In this embodiment, the data processing module is used to convert the mass concentration data obtained by the element determination module into a molar ratio. This aims to eliminate the distortion of the stoichiometric relationship caused by directly using the mass concentration ratio due to the significant difference in molar mass between the matrix element and the dopant element. This ensures that the radial position parameters of the particles obtained based on the spherical particle geometric model correspond to the molar ratio of the dopant element, thereby helping to accurately reflect the concentration distribution curve of the true chemical composition of the dopant element at different radial positions inside the lithium iron phosphate cathode material. This further effectively improves the accuracy and reliability of the low-cost characterization method.

[0070] In an exemplary embodiment, the data processing module is configured to determine the radial concentration distribution of the dopant element by plotting a two-dimensional curve with the radial position parameter of the particle as the abscissa and the molar percentage or relative molar percentage of the dopant element as the ordinate, to characterize the radial concentration distribution of the dopant element within the particle. In this embodiment, the data processing module is configured to establish a two-dimensional coordinate system with the radial position parameter of the particle as the abscissa and the molar percentage or relative molar percentage of the dopant element as the ordinate, transforming the discrete values ​​calculated in the preceding steps into a continuous two-dimensional curve. The abscissa intuitively reflects the relative depth position of the dopant element from the center to the surface within the lithium iron phosphate particle, while the ordinate corresponds to the specific content ratio of the dopant element at each position. This facilitates the direct construction of a visualized concentration distribution map based on the radial position parameter converted from the relative solubility of the matrix elements and the molar percentage data determined by the mass concentration, thereby transforming the abstract numerical calculation results into an intuitive geometric form. This allows for the rapid identification of enriched or depleted regions of the dopant element within the particle through the curve's trend, achieving an efficient and intuitive characterization of the radial concentration distribution morphology of the dopant element.

[0071] In one exemplary embodiment, such as Figure 2As shown, the detection system also includes a performance evaluation module 400, used to determine the enrichment degree of dopant elements on the particle surface or the gradient distribution morphology inside the particle based on the radial concentration distribution of the dopant elements; and to evaluate the fast-charging performance or DC internal resistance characteristics of the lithium iron phosphate cathode material based on the enrichment degree or distribution morphology of the hydrochloric acid solution. In this embodiment, the performance evaluation module is used to receive the radial concentration distribution data of dopant elements determined by the data processing module, aiming to directly map the microscopic material structure characteristics to the macroscopic electrochemical performance. The performance evaluation module analyzes the radial distribution uniformity, gradient change trend, or local enrichment of dopant elements in lithium iron phosphate particles from the core to the surface through a built-in evaluation algorithm or model, and then predicts or quantifies the influence of the microstructure on the lithium-ion diffusion path and electronic conduction efficiency, thereby evaluating the polarization degree (fast-charging performance) or internal ion migration resistance (DC internal resistance characteristics) of the material under fast charging conditions. For example, if the distribution data shows that the doping elements are abnormally scarce on the particle surface, it may lead to an increase in surface impedance. Based on this, the evaluation module can determine that the DC internal resistance characteristics are poor or the fast charging rate is limited. This direct correlation evaluation from microscopic distribution to macroscopic performance helps to improve the efficiency and pertinence of performance evaluation in the research and development of lithium iron phosphate cathode materials, and avoids the screening lag problem caused by long testing cycles and high costs in traditional methods.

[0072] This embodiment provides a method for detecting the concentration distribution of doped elements in lithium iron phosphate cathode materials, such as... Figure 3 As shown, Figure 3 This is a flowchart illustrating a method for detecting the concentration distribution of doped elements in a lithium iron phosphate cathode material according to an embodiment of this application, comprising the following steps:

[0073] N equal masses of lithium iron phosphate cathode material were subjected to gradient acid dissolution treatment and diluted to the same mass to obtain N filtrates; where N≥8;

[0074] Determine the mass concentration of matrix elements and dopant elements in N filtrates;

[0075] Calculate the relative solubility of the matrix element in N filtrates based on the mass concentration of the matrix element;

[0076] Based on the geometric model of spherical particles, the relative solubility is converted into the radial position parameter of the particles;

[0077] The target parameter ratio is determined based on the mass concentration of the matrix element and the mass concentration of the dopant element in the hydrochloric acid solution; wherein, the target parameter ratio in the hydrochloric acid solution includes the molar ratio of the dopant element in the hydrochloric acid solution or the relative molar ratio of the dopant element in the hydrochloric acid solution.

[0078] The radial concentration distribution of doped elements in hydrochloric acid solution is determined based on the ratio of the radial position parameters of particles in the hydrochloric acid solution to the target parameters of the hydrochloric acid solution.

[0079] The method for detecting the concentration distribution of doped elements in lithium iron phosphate cathode materials provided in this application involves setting a gradient acid dissolution treatment step with N≥8, so that equal masses of lithium iron phosphate cathode material powder undergo a dissolution reaction of increasing degree in a solution with different volumes of acid, thereby obtaining N filtrates with a clear dissolution depth gradient. Subsequently, the mass concentration of matrix elements and doped elements in each filtrate are measured, and the relative solubility of matrix elements is converted into radial position parameters of particles based on a spherical particle geometry model. Then, the molar proportion of doped elements or the relative molar proportion of doped elements is calculated by combining the mass concentration of matrix elements and the mass concentration of doped elements, and finally the concentration distribution curve of doped elements as the radial position of particles is obtained. By introducing multiple discrete and gradient-defined dissolution samples, this method can capture the concentration variation trend of dopant elements from the surface to the core within material particles. Compared with detection methods that rely solely on a single or limited number of dissolutions, this method helps improve the resolution and characterization accuracy of concentration distribution data. It also makes the radial position parameters derived from the spherical model more closely match the actual particle geometry, thus achieving low-cost, high-efficiency, and high-precision characterization of the internal concentration distribution of dopant elements. This provides more reliable data support for optimizing material synthesis processes and evaluating battery fast-charging performance.

[0080] In an exemplary embodiment, the step of subjecting N equal masses of lithium iron phosphate cathode material to gradient acid dissolution treatment and diluting them to the same mass to obtain N filtrates includes: placing N equal masses of lithium iron phosphate cathode material into N independent containers, adding an increasing volume of acidic dissolution solution to each container, stirring and reacting for the same time, and then diluting them to the same mass to obtain N mixed solutions; and filtering each of the N mixed solutions to obtain N filtrates.

[0081] In this embodiment, N equal masses of lithium iron phosphate cathode material are placed in N independent containers. An increasing volume of acidic solution is added to each container. By setting different volumes of acidic solution, the total amount of reactants contacted by each sample in the initial stage of the reaction varies, thus inducing different degrees of dissolution on the particle surface during the stirring reaction, forming a dissolution gradient from shallow to deep. The increasing volume means that the amount of acid in subsequent containers is greater than that in previous containers, ensuring that the dissolution driving force in each independent container changes in a stepwise manner, thereby obtaining dissolved phases representing different radial depths. After stirring for the same amount of time, dilution to the same mass means that after the reaction in each container has been fully completed, solvent (such as water) is added to all the mixtures until the total mass of liquid in each container is equal. This helps eliminate the difference in the total amount of solution caused by the different initial acid volumes, and helps to further improve the accuracy of characterization and reduce errors.

[0082] Specifically, prepare N containers and add equal masses of lithium iron phosphate cathode material powder to each container; prepare an acidic solution, which includes aqua regia and hydrogen peroxide; add different volumes of aqua regia to each container in increasing volume order, and add a fixed volume of hydrogen peroxide to each container, then dilute and bring to a final volume to obtain N reaction mixtures; stir the N reaction mixtures to react; bring the volume of the stirred mixtures to the same total mass, and filter them to obtain N filtrates.

[0083] In an exemplary embodiment, adding increasing volumes of acidic solution to each container includes sequentially increasing the volume of the acidic solution in each container according to an arithmetic or geometric sequence. In this embodiment, the volume of the acidic solution in each container is set to increase sequentially according to an arithmetic or geometric sequence. Specifically, the amount of acid added to the N independent containers is arranged in a mathematically ordered manner. For example, if an arithmetic sequence is used, the difference in acid volume between adjacent containers remains constant (e.g., adding 10mL, 20mL, 30mL, 40mL, 50mL, 60mL, etc.). If a geometric sequence is used, the acid volume between adjacent containers is in a fixed multiple relationship (e.g., adding 10mL, 20mL, 40mL, 60mL, etc.). This stepwise acid addition method creates a clear and quantifiable difference in the concentration gradient of the reaction system in the acidic environment within different containers. This promotes the gradual release of dopant and matrix elements on the surface of lithium iron phosphate cathode material particles according to a preset dissolution rate gradient during the stirring reaction. It avoids large differences in the degree of dissolution caused by random or irregular changes in the amount of acid added, which helps to improve the accuracy of the data and the smoothness of the distribution curve when calculating the radial position parameters of the particles through the relative solubility of matrix elements. This further improves the accuracy of characterizing the radial concentration distribution of dopant elements.

[0084] In one exemplary embodiment, the acidic dissolving solution includes aqua regia and hydrogen peroxide. The aqua regia comprises concentrated hydrochloric acid and concentrated nitric acid, with a volume ratio of concentrated hydrochloric acid to concentrated nitric acid of (2~4):1. The mass fraction of hydrogen peroxide is 5%~30%. In this embodiment, concentrated hydrochloric acid and concentrated nitric acid are mixed in this specific volume ratio to form aqua regia, which has strong oxidizing and complexing capabilities. This aqua regia can effectively destroy the crystal structure of lithium iron phosphate materials and dissolve the iron matrix. The 5%~30% hydrogen peroxide acts as an auxiliary oxidant, further accelerating the oxidation and dissolution process and stabilizing the reaction environment. The synergistic effect of the two ensures that the matrix elements (e.g., iron) can be gradually dissolved in a highly repeatable manner and in accordance with stoichiometry in the acid dissolution steps with different volume gradients.

[0085] In an exemplary embodiment, the step of determining the mass concentration of the matrix element and the mass concentration of the dopant element in N filtrates includes: determining the mass concentration of the matrix element and the mass concentration of the dopant element in the N filtrates using inductively coupled plasma atomic emission spectrometry (ICP-AES). In this embodiment, ICP-AES is used to perform component analysis on the filtrates. ICP-AES refers to using high-temperature plasma to excite atoms or ions in the sample, causing them to emit spectral signals of characteristic wavelengths, thereby achieving simultaneous quantitative detection of multiple elements. In the specific implementation of this application, N filtrates are introduced into the sample introduction system of the spectrometer sequentially or simultaneously. The instrument directly obtains the mass concentration data of the matrix elements (such as iron, lithium, and phosphorus) and dopants (such as titanium and vanadium) in the solution by scanning and exciting the matrix elements (such as iron, lithium, and phosphorus) and dopants (such as titanium and vanadium) in each filtrate. This process does not require multiple independent chemical titrations or separation operations for different elements as in traditional methods. By introducing this measurement method, this application achieves high-precision synchronous acquisition of matrix elements and dopants in a single test process. This not only significantly improves the efficiency of multi-element data sampling, but also effectively avoids the accumulation of errors caused by multiple independent measurements. It helps to provide a reliable and highly time-synchronous original data foundation for subsequent accurate calculation of relative solubility, molar proportion, and reconstruction of the radial concentration distribution of dopants based on the spherical particle geometric model.

[0086] Specifically, the steps for determining elemental mass concentration using inductively coupled plasma optical emission spectrometry (ICP-OES) include: preparing a series of standard solutions containing matrix elements (such as Li, Fe, P) and dopant elements (such as Ti, V); establishing a standard curve of elemental concentration versus signal intensity; injecting N filtrates into the ICP-OES instrument; measuring the mass concentrations of Fe, Ti, and V in each filtrate; and recording the mass concentrations of Fe, Ti, and V in the i-th filtrate, denoted as Fei, Tii, and Vi, respectively. i Ti i V i , where 1≤i≤N.

[0087] In an exemplary embodiment, the matrix element is iron, and the dopant element includes at least one of titanium and vanadium. In this embodiment, the matrix element is specifically defined as iron, and the dopant element is specifically defined as at least one of titanium or vanadium. Iron, as a backbone component of lithium iron phosphate cathode material, exhibits uniform distribution among particles and can serve as a benchmark for measuring particle dissolution progress. Titanium and vanadium are key dopants used to improve the material's conductivity and structural stability. This allows the calculation logic based on a spherical geometry model to be directly applied to actual lithium iron phosphate systems. By measuring the relative solubility of iron in the filtrate, the radial position parameters of the particles can be inferred. Simultaneously, the molar ratio of titanium or vanadium to iron is measured, thereby converting the dissolution data into a specific radial concentration distribution map of the dopant element. This specific definition helps achieve specific and precise detection of the dopant distribution, further improving the applicability and detection efficiency of this method in actual production process control.

[0088] In an exemplary embodiment, the step of calculating the relative solubility of the matrix element in N filtrates based on the mass concentration of the matrix element includes: determining the maximum concentration value of the matrix element based on the mass concentration of the matrix element in the N filtrates, and calculating the relative solubility of the matrix element in the N filtrates based on the maximum concentration value. In this embodiment, firstly, based on the N sets of mass concentration data of the matrix element (such as iron) detected in the N filtrates, the highest concentration value is selected and used as a unified benchmark value (i.e., the denominator) reflecting the complete dissolution or dissolution limit state of the material; then, using this maximum concentration value as a reference, the ratio of the measured mass concentration (i.e., the numerator) of the matrix element in each filtrate is calculated to obtain the relative solubility corresponding to each filtrate. Specifically, during the gradient acid dissolution process, as the amount of acid added increases, the degree of material dissolution gradually deepens, and the absolute concentration of matrix elements in each filtrate also changes accordingly. If the absolute concentration is directly used to map the particle position, the radial position calculation will be distorted due to the difference in the total amount of dissolution per unit volume. By introducing the maximum concentration value as a normalization benchmark, the relative solubility of all filtrates is converted into a ratio relative to the maximum concentration value (between 0 and 1). This helps to eliminate the absolute numerical deviation caused by fluctuations in sample dilution factor or acid addition efficiency, ensuring the comparability of data under different amounts of acid. Consequently, when the relative solubility is converted into particle radial position parameters using the spherical particle geometric model, it can accurately reflect the true distribution gradient of dopant elements from the surface to the core inside the material, which helps to further improve the accuracy and reliability of concentration distribution characterization.

[0089] In one exemplary embodiment, the relative solubility of the matrix elements in the N filtrates is determined by the following method:

[0090] R Fe,i=(Fe i / Fe max ) × 100%;

[0091] Among them, R Fe,i Let Fe be the relative solubility of the matrix element in the i-th filtrate. max The maximum concentration value of the matrix element, Fe i Let N be the mass concentration of the matrix element in the i-th filtrate, where 1 ≤ i ≤ N.

[0092] In this embodiment, Fe was first identified from the measurement results of N filtrates. max Then, the Fe corresponding to each filtrate was... i Divide by Fe respectively max Multiply by 100% to normalize the matrix element content of each filtrate to a relative solubility value between 0 and 100%. This calculation process allows for accurate mapping of the radial position inside the particles through relative proportions, even if the absolute concentration fluctuates due to slight differences in particle solubility in different acid dissolution steps. This effectively further improves the accuracy and comparability of the characterization of doped element concentration distribution in lithium iron phosphate cathode materials.

[0093] In one exemplary embodiment, relative solubility is converted into particle radial position parameters in the following manner:

[0094] X i =[1-(1-R Fe,i ) 1 / 3 ×100%;

[0095] Among them, X i R is the radial position parameter corresponding to the i-th filtrate. Fe,i denoted as , where is the relative solubility of the matrix element in the i-th filtrate.

[0096] In this embodiment, based on the spherical particle geometric model, the calculated relative solubility R is... Fe,i Substituting these values ​​into the formula, we can determine the radial position parameter X corresponding to the i-th filtrate. i By directly utilizing the mass concentration change of matrix elements during the macroscopic dissolution process, and through the cubic relationship between the volume and radius of the sphere (i.e. the geometric correspondence between the proportion of dissolved volume and the proportion of the radius of the remaining undissolved core), the cumulative dissolution rate is accurately converted into the radial distance coordinates inside the particle, so that the final radial concentration distribution can accurately reflect the real gradient change of dopant elements from the surface to the core inside the particle.

[0097] In one exemplary embodiment, the molar percentage of the dopant element is determined by the following method:

[0098] M i =n d,i / (nd,i +n Fe,i )×100%;

[0099] Among them, M i Let n be the molar percentage of the dopant element in the i-th filtrate. d,i Let n be the molar number of the dopant element in the i-th filtrate. Fe,i The molar number of matrix elements in the i-th filtrate;

[0100] The data processing module is used to determine the relative molar percentage of dopant elements in the following ways:

[0101] Y i =(M i / M min ) × 100%;

[0102] Among them, Y i M represents the relative molar percentage of the dopant element in the i-th filtrate. i M represents the molar percentage of the dopant element in the i-th filtrate. min This represents the minimum molar percentage of the dopant element.

[0103] In this embodiment, the acquired mass concentration data is converted into a molar ratio to eliminate the stoichiometric distortion caused by directly using the mass concentration ratio due to the significant difference in molar mass between the matrix element and the dopant element. This ensures that the radial position parameters of the particles obtained based on the spherical particle geometric model correspond accurately to the molar ratio of the dopant element, thereby helping to accurately reflect the concentration distribution curve of the true chemical composition of the dopant element at different radial positions inside the lithium iron phosphate cathode material, and further effectively improving the accuracy and reliability of the low-cost characterization method.

[0104] M i M represents the mole fraction of the dopant element relative to the sum of the dopant element and the matrix element in the i-th filtrate. i Reflects the particle's radial position X i The local chemical composition at the location.

[0105] In an exemplary embodiment, the radial concentration distribution of the dopant element is determined by plotting a two-dimensional curve with the radial position parameter of the particle as the abscissa and the molar percentage or relative molar percentage of the dopant element as the ordinate, to characterize the radial concentration distribution of the dopant element within the particle. In this embodiment, by establishing a two-dimensional coordinate system with the radial position parameter of the particle as the abscissa and the molar percentage or relative molar percentage of the dopant element as the ordinate, the discrete values ​​calculated in the preceding steps are transformed into a continuous two-dimensional curve. The abscissa intuitively reflects the relative depth position of the dopant element from the center to the surface within the lithium iron phosphate particle, while the ordinate corresponds to the specific content ratio of the dopant element at each position. This facilitates the direct construction of a visualized concentration distribution map based on the radial position parameter converted from the relative solubility of the matrix elements and the molar percentage data determined by the mass concentration. This transforms the abstract numerical calculation results into an intuitive geometric form, allowing for the rapid identification of enriched or depleted regions of the dopant element within the particle through the curve's trend, thus achieving an efficient and intuitive characterization of the radial concentration distribution morphology of the dopant element.

[0106] In an exemplary embodiment, the detection method further includes: evaluating the fast-charging performance or DC internal resistance characteristics of the lithium iron phosphate cathode material based on the radial concentration distribution of the dopant elements. In this embodiment, based on the radial concentration distribution data of the dopant elements, the uniformity of the radial distribution of the dopant elements from the core to the surface of the lithium iron phosphate particles, the gradient change trend, or the local enrichment of the dopant elements is analyzed. This allows for the prediction or quantification of the impact of the microstructure on the lithium-ion diffusion path and electronic conduction efficiency, thereby evaluating the polarization degree (fast-charging performance) or internal ion migration resistance (DC internal resistance characteristics) of the material under fast-charging conditions. For example, if the distribution data shows an abnormal depletion of dopant elements on the particle surface, it may lead to an increase in surface impedance, thus determining that the DC internal resistance characteristics are poor or the fast-charging rate is limited. This direct correlation evaluation from microscopic distribution to macroscopic performance helps improve the efficiency and specificity of performance evaluation during the research and development of lithium iron phosphate cathode materials, avoiding the screening lag problem caused by long testing cycles and high costs in traditional methods.

[0107] Embodiments of this application also provide a computer-readable storage medium comprising a stored program, wherein the program, when executed, performs any of the methods described above.

[0108] Embodiments of this application also provide an electronic device including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0109] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0110] Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0111] Optionally, embodiments of this application also provide a computer program product, which includes a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0112] Optionally, embodiments of this application also provide another computer program product, including a non-volatile computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps in any of the above method embodiments.

[0113] Optionally, embodiments of this application also provide a computer program that includes computer instructions stored in a computer-readable storage medium; a processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps in any of the above method embodiments.

[0114] Optionally, embodiments of this application also provide a screening method for lithium iron phosphate cathode materials, comprising: obtaining the radial concentration distribution curve of dopant elements in the lithium iron phosphate cathode material to be tested according to the above-described detection method for the concentration distribution of dopant elements in lithium iron phosphate cathode materials;

[0115] At least one characteristic parameter is extracted from the radial concentration distribution curve of the hydrochloric acid solution. Based on the comparison results of the characteristic parameters of the hydrochloric acid solution, the target cathode material is screened from multiple cathode materials to be tested.

[0116] Specifically, using the particle radial position parameter X i The x-axis represents the percentage of the relative molar number of doped elements, Y. i Using the vertical axis as the ordinate, a four-parameter Logistic equation was used to perform nonlinear regression fitting on the experimental data points in order to quantitatively characterize the distribution characteristics of doped elements and predict battery performance. The fitting equation is as follows: Four-parameter Logistic equation: Where: X is the radial position parameter of the particle, Y is the relative molar percentage of the dopant element at the corresponding radial position; A is the baseline value (relative percentage at the core, i.e., the relative percentage of the dopant element at X=0), B is the maximum value (relative percentage at the surface, i.e., the relative percentage of the dopant element at X=100%); C is the inflection point, i.e., the radial position parameter corresponding to when the concentration drops to 50% of the surface concentration; D is the slope of the curve.

[0117] Based on the above characteristic parameters, the distribution characteristics of doped elements are classified into surface-enriched, core-enriched, and uniformly distributed types. The surface-enriched distribution characteristics are as follows: the fitted curve shows that the Y value increases significantly with increasing X (i.e., B > A, and the slope D > 0), indicating that doped elements (such as Ti and V) are mainly enriched on the particle surface. This distribution is beneficial for reducing the charge transfer impedance of the particle surface, increasing the lithium-ion diffusion rate, and thus endowing the material with lower DC internal resistance (DCR) and excellent fast-charging performance. In this case, the smaller the C value, the closer the doped element concentration distribution is to the surface region (when X = C, it indicates that the doped element concentration distribution has decreased to the median concentration during the process of decreasing from the particle shell to the core). Furthermore, the larger the D value, the more drastic the decrease in doped element concentration distribution from the shell to the core. The core-enriched distribution characteristics are as follows: the fitted curve shows that the Y value decreases significantly with increasing X (i.e., B < A, and the slope D < 0). Specifically, the Y value is higher in the particle core region (X < 50%) and lower in the surface region (X > 50%), indicating that the dopant element is mainly distributed inside the particle, with insufficient surface doping concentration. This may lead to slow surface reaction kinetics and high interfacial impedance, resulting in high DC internal resistance (DCR) and poor fast charging performance. In this case, a smaller C value indicates that the dopant element concentration distribution is further away from the surface region (when X = C, it means that the dopant element concentration has increased to the median concentration as the particle progresses from the shell to the core). Furthermore, a larger D value indicates a more dramatic increase in dopant element concentration from the shell to the core. The distribution characteristics of the uniformly distributed type are as follows: the fitted curve is approximately a straight line parallel to the X-axis, the slope D is approximately 0, B is close to A, and the Y value at all radial positions is close to 100% (normalized baseline), indicating that the dopant element is uniformly distributed inside the particle. The dopant element concentration distribution is such that the particle does not change with radial position from the outer shell to the core. The fast charging performance of the uniformly distributed dopant element is between the two types mentioned above, usually better than the core-enriched type, but slightly inferior to the surface-enriched type, depending on the intrinsic conductivity enhancement effect of the specific dopant element.

[0118] Based on the above judgment results, the target cathode material was selected from multiple batches of cathode materials to be tested and used for subsequent battery manufacturing.

[0119] Optionally, embodiments of this application also provide a lithium iron phosphate cathode material, obtained by screening using the above-described lithium iron phosphate cathode material screening method.

[0120] Optionally, embodiments of this application also provide a battery, including a positive electrode, a negative electrode, a separator, and an electrolyte; the hydrochloric acid solution positive electrode includes a positive current collector and a positive active material layer disposed on at least one side of the surface of the hydrochloric acid solution positive current collector; the hydrochloric acid solution positive active material comprises the above-mentioned lithium iron phosphate positive electrode material.

[0121] Optionally, embodiments of this application also provide a battery pack, including multiple batteries as described above, with the hydrochloric acid solution batteries connected in series and / or in parallel. The batteries can be connected in series, parallel, or mixed configurations, where mixed configuration refers to the simultaneous presence of series and parallel connections in the connection relationship of multiple batteries.

[0122] Optionally, embodiments of this application also provide a battery pack, including the aforementioned battery pack and battery management system. The battery pack in this embodiment includes multiple battery packs, with one battery pack disposed within each sub-accommodating space. Each battery pack includes multiple stacked battery cells, the stacking direction of which can be parallel to the plane of the base plate. The battery pack also includes a battery management system (BMS), a thermal management system, an electrical connection system (high-voltage / low-voltage connectors, wiring harnesses, etc.), structural components (casing, brackets, etc.), and protective components, etc., and these components are placed inside a housing and sealed with a cover plate, forming a complete functional unit capable of directly outputting electrical energy.

[0123] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated here.

[0124] Obviously, those skilled in the art should understand that the modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuits, or multiple modules or steps can be fabricated as a single integrated circuit. Thus, this application is not limited to any particular hardware and software combination.

[0125] The above are merely preferred embodiments of this application. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

[0126] The present application will be further described in detail below with reference to specific embodiments, which should not be construed as limiting the scope of protection claimed in the present application.

[0127] Example 1

[0128] This embodiment provides a method for detecting the concentration distribution of doping elements in lithium iron phosphate cathode materials. The specific steps are as follows:

[0129] Lithium iron phosphate cathode material includes LiFePO4 and is doped with titanium and vanadium. It is obtained through the following steps: grinding lithium carbonate, iron phosphate, sucrose, titanium dioxide, and vanadium pentoxide, followed by spray drying, high-temperature calcination, and air jet milling.

[0130] S1. Prepare 10 clean 50mL beakers numbered i=1 to i=10. Accurately weigh 1.000g (accurate to 0.001g) of lithium iron phosphate cathode material powder from the same batch and add it to each of the 10 beakers.

[0131] S2. Prepare aqua regia solution by mixing concentrated hydrochloric acid (analytical grade, density approximately 1.19 g / mL) and concentrated nitric acid (analytical grade, density approximately 1.42 g / mL) in a volume ratio of 3:1. Following an arithmetic progression, add different volumes of aqua regia to 10 beakers as follows: Beaker i=1: 1.0 mL aqua regia solution; Beaker i=2: 2.0 mL aqua regia solution; Beaker i=3: 3.0 mL aqua regia solution; Beaker i=4: 4.0 mL aqua regia solution; Beaker i=5: 5.0 mL aqua regia solution; Beaker i=6: 6.0 mL aqua regia solution; Beaker i=7: 7.0 mL aqua regia solution; Beaker i=8: 8.0 mL aqua regia solution. Water; Beaker i=9: Add 9.0 mL of aqua regia; Beaker i=10: Add 10.0 mL of aqua regia; then add hydrogen peroxide: Add 2.0 mL of 27% hydrogen peroxide solution to each of the above beakers, then add deionized water to each beaker, bring the volume to 20 mL, and shake well; place a magnetic stir bar in each beaker, place the beaker on a magnetic stirrer, set the stirring speed to 600 rpm, and continuously stir the reaction for 2 hours at room temperature (25±2℃) to allow the solid powder to fully contact the acid solution and dissolve to different degrees. After the reaction is complete, remove the beakers, add deionized water to each beaker, and dilute the solution in all beakers with deionized water to 50 g to obtain 10 mixed solutions;

[0132] The filtration was performed using a polytetrafluoroethylene (PTFE) microporous membrane with a pore size of 0.22 μm. The filtrate was collected, and 10 filtrates were obtained to be tested, which were labeled as filtrate 1 to filtrate 10, respectively.

[0133] S3. The elemental content of the 10 filtrates was determined using an inductively coupled plasma optical emission spectrometer (ICP-OES, model: Agilent 5110). The 10 filtrates were sequentially injected into the ICP-OES instrument, and the mass concentrations of Li, Fe, P, Ti, and V in each filtrate were measured (unit: ppm, i.e., mg / kg; since the fixed volume was 50g, this value directly reflects the relative content). The measured mass concentrations of Fe, Ti, and V in each filtrate were recorded as Fe ≤ 0.5%. i Ti i V i (i=1 to 10);

[0134] S4, find Fe in all samples i The maximum value is denoted as Fe. max The relative solubility of iron in 10 filtrates was calculated using the following method:

[0135] R Fe,i =(Fe i / Fe max ) × 100%;

[0136] Among them, R Fe,i Let Fe be the relative solubility of iron in the i-th filtrate. max This represents the maximum concentration of iron, Fe. i Let be the mass concentration of iron in the i-th filtrate;

[0137] S5, based on a spherical geometry model, assuming the particles are uniform spheres and dissolution occurs from the surface to the center, converts the relative solubility into a radial position parameter of the particles in the following way:

[0138] X i =[1-(1-R Fe,i ) 1 / 3 ×100%;

[0139] Among them, X i R is the radial position parameter corresponding to the i-th filtrate. Fe,i Let be the relative solubility of iron in the i-th filtrate;

[0140] S6, based on the molar masses of Fe, Ti, and V (M Fe =55.85 g / mol, M Ti =47.87 g / mol, M V =50.94 g / mol), calculate the molar percentage; since all samples are diluted by the same mass, the ratio of mass concentrations equals the ratio of masses, and the molar percentage of the dopant element is determined as follows:

[0141] M i =nd,i / (n d,i +n Fe,i )×100%;

[0142] Among them, M i Let n be the molar percentage of the dopant element in the i-th filtrate. d,i Let n be the molar number of the dopant element in the i-th filtrate. Fe,i Let be the number of moles of iron in the i-th filtrate;

[0143] The relative molar percentage of dopant elements is determined as follows:

[0144] Y i =(M i / M min ) × 100%;

[0145] Among them, Y i M represents the relative molar percentage of the dopant element in the i-th filtrate. i M represents the molar percentage of the dopant element in the i-th filtrate. min This represents the minimum molar percentage of the dopant element.

[0146] S7, with particle radial position parameter X i Y is the relative molar percentage of Ti element, with the x-axis representing the total molar amount of Ti. Ti,i Or the molar percentage of element V Y V,i Using the vertical axis as the ordinate, plot points in a two-dimensional coordinate system and connect them to obtain the radial concentration distribution curves of titanium and vanadium elements within the lithium iron phosphate cathode material particles, as shown below. Figure 4 As shown.

[0147] The test data are shown in Tables 1 and 2.

[0148] according to Figure 4 This allows for a direct assessment of whether titanium and vanadium are enriched on the particle surface or distributed within the particle. If the curve shows that the relative molar number on the surface is significantly higher than that inside, it indicates that the dopant elements are mainly distributed on the particle surface, which is beneficial for improving the surface reaction kinetics of the material. The distribution of dopant elements near the particle surface helps to change the lithium-ion diffusion channels on the surface and shorten the diffusion path of lithium ions in the solid phase. During rapid charging and discharging, lithium ions can be quickly inserted and removed, thereby reducing the DC internal resistance (DCR).

[0149] Table 1

[0150]

[0151] Table 2

[0152]

[0153] The four-parameter logistic equations obtained from the fitting are as follows:

[0154]

[0155] When X i When <50%, Y i All values ​​are greater than 100%, indicating that this material is surface-enriched, with dopants (such as Ti and V) mainly enriched on the particle surface. This distribution helps to reduce the charge transfer impedance on the particle surface and improve the lithium-ion diffusion rate, thereby giving the material lower DC internal resistance (DCR) and excellent fast charging performance.

[0156] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A detection system for the concentration distribution of doped elements in lithium iron phosphate cathode materials, characterized in that, include: The element determination module is used to determine the mass concentration of matrix elements and dopant elements in N filtrates, wherein the N filtrates are determined by gradient acid dissolution and dilution of N equal masses of lithium iron phosphate cathode material to the same mass, and N≥8; The data processing module is used for: The relative solubility of the matrix element is calculated based on the mass concentration of the matrix element, and the relative solubility is converted into a radial position parameter of the particle based on the spherical particle geometry model. The radial concentration distribution of the dopant element is determined based on the ratio of the radial position parameter of the particle to the target parameter, wherein the target parameter ratio includes the molar quantity ratio of the dopant element or the relative molar quantity ratio of the dopant element, and the target parameter ratio is determined based on the mass concentration of the matrix element and the mass concentration of the dopant element.

2. The detection system according to claim 1, characterized in that, It also includes a sample processing module, which is used for: N equal masses of lithium iron phosphate cathode material were placed in N independent containers. An acidic solution with increasing volume was added to each container. After stirring and reacting for the same time, the solutions were diluted to the same mass to obtain N mixtures. The N mixtures are filtered separately to obtain the N filtrates.

3. The detection system according to claim 2, characterized in that, The acidic dissolving solution includes aqua regia and hydrogen peroxide, and the specific method of adding the acidic dissolving solution is as follows: Following an arithmetic or geometric sequence, different volumes of acidic solution are introduced into each container in sequence, with a fixed volume of hydrogen peroxide added to each container.

4. The detection system according to claim 3, characterized in that, The aqua regia comprises concentrated hydrochloric acid and concentrated nitric acid, wherein the volume ratio of the concentrated hydrochloric acid to the concentrated nitric acid is (2~4):1, and the mass fraction of the hydrogen peroxide is 5%~30%.

5. The detection system according to claim 1, characterized in that, The element determination module is used for: The mass concentrations of matrix elements and dopant elements in the N filtrates were determined using inductively coupled plasma atomic emission spectrometry.

6. The detection system according to claim 1, characterized in that, The matrix element is iron, and the doping element includes at least one of titanium and vanadium.

7. The detection system according to any one of claims 1 to 6, characterized in that, The data processing module is used for: The maximum concentration of the matrix element is determined based on the mass concentration of the matrix element in the N filtrates, and the relative solubility of the matrix element in the N filtrates is calculated based on the maximum concentration.

8. The detection system according to claim 7, characterized in that, The data processing module is used to determine the relative solubility of the matrix elements in the N filtrates in the following manner: R Fe,i =(Fe i / Fe max )×100%; Among them, R Fe,i Let Fe be the relative solubility of the matrix element in the i-th filtrate. max The maximum concentration value of the matrix element, Fe. i Let N be the mass concentration of the matrix element in the i-th filtrate, where 1 ≤ i ≤ N.

9. The detection system according to claim 8, characterized in that, The data processing module is used to convert the relative solubility into particle radial position parameters in the following manner: X i =[1-(1-R Fe,i ) 1 / 3 ]×100%; Among them, X i R is the radial position parameter corresponding to the i-th filtrate. Fe,i denoted as , where is the relative solubility of the matrix element in the i-th filtrate.

10. The detection system according to any one of claims 1 to 6, characterized in that, The data processing module is used to determine the molar percentage of the dopant element in the following manner: M i =n d,i / (n d,i +n Fe,i )×100%; Among them, M i n represents the molar percentage of the dopant element in the i-th filtrate. d,i Let n be the molar number of the dopant element in the i-th filtrate. Fe,i The molar number of matrix elements in the i-th filtrate; The data processing module is used to determine the relative molar percentage of the dopant elements in the following manner: Y i =(M i / M min )×100%; Among them, Y i M represents the relative molar percentage of the dopant element in the i-th filtrate. i M represents the molar percentage of the dopant element in the i-th filtrate. min This represents the minimum molar percentage of the dopant element.

11. The detection system according to any one of claims 1 to 6, characterized in that, The data processing module is used to determine the radial concentration distribution of the dopant element in the following manner: A two-dimensional curve is plotted with the radial position parameter of the particle as the abscissa and the molar percentage of the dopant element or the relative molar percentage of the dopant element as the ordinate to characterize the radial concentration distribution of the dopant element inside the particle.

12. The detection system according to any one of claims 1 to 6, characterized in that, Also includes: The performance evaluation module is used to determine the enrichment degree of the dopant element on the particle surface or the gradient distribution morphology inside the particle based on the radial concentration distribution of the dopant element. The fast-charging performance or DC internal resistance characteristics of the lithium iron phosphate cathode material are evaluated based on the enrichment level or the distribution morphology.

13. A method for detecting the concentration distribution of doped elements in lithium iron phosphate cathode materials, characterized in that, A detection system for the concentration distribution of doped elements in the lithium iron phosphate cathode material according to any one of claims 1 to 12, comprising: N equal masses of lithium iron phosphate cathode material were subjected to gradient acid dissolution treatment and diluted to the same mass to obtain N filtrates; where N≥8; The mass concentrations of matrix elements and dopant elements in the N filtrates were determined. Calculate the relative solubility of the matrix element in the N filtrates based on the mass concentration of the matrix element; Based on the geometric model of spherical particles, the relative solubility is converted into the radial position parameter of the particles; The target parameter ratio is determined based on the mass concentration of the matrix element and the mass concentration of the dopant element; wherein the target parameter ratio includes the molar ratio of the dopant element or the relative molar ratio of the dopant element. The radial concentration distribution of the dopant element is determined based on the ratio of the particle radial position parameter to the target parameter.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program, when executed, performs the method for detecting the concentration distribution of doped elements in the lithium iron phosphate cathode material according to claim 13.

15. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to execute the method for detecting the concentration distribution of doped elements in the lithium iron phosphate cathode material according to claim 13 through the computer program.

16. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for detecting the concentration distribution of doped elements in the lithium iron phosphate cathode material as described in claim 13.

17. A method for screening lithium iron phosphate cathode materials, characterized in that, include: According to the detection method for the concentration distribution of doped elements in lithium iron phosphate cathode material as described in claim 13, the radial concentration distribution curve of doped elements in the lithium iron phosphate cathode material to be tested is obtained. At least one characteristic parameter is extracted from the radial concentration distribution curve, and the target cathode material is selected from multiple cathode materials to be tested based on the comparison results of the characteristic parameter.

18. A lithium iron phosphate cathode material, characterized in that, The lithium iron phosphate cathode material was obtained by screening using the screening method described in claim 17.

19. A battery, characterized in that, It includes a positive electrode, a negative electrode, a separator, and an electrolyte; the positive electrode includes a positive current collector and a positive active material layer disposed on at least one side surface of the positive current collector; the positive active material comprises the lithium iron phosphate positive electrode material as described in claim 18.

20. A battery pack, characterized in that, It includes a plurality of batteries as described in claim 19, wherein the plurality of batteries are connected in series and / or in parallel.

21. A battery pack, characterized in that, Includes the battery pack as described in claim 20.

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