Quick charging performance evaluation method, device and system of battery active material and storage medium

Abstract

The invention discloses a fast charging performance evaluation method, device and system for a battery active material and a storage medium. The method comprises the following steps: acquiring ion impedance related to a mold battery; wherein the mold battery has an asymmetric layered structure, and is formed by laminating electrode plates with the same active material but different sizes; determining a diffusion control current density of the active material based on the ion impedance; a maximum charge rate of the active material is determined using the diffusion controlled current density in combination with an area capacity of the active material. According to the method, the fast charging potential of the active material can be predicted in a short time only by assembling the mold battery and rapidly testing the electrochemical impedance spectroscopy in combination with theoretical calculation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of batteries, in particular to a method, device, system and storage medium for evaluating the fast-charging performance of battery active materials. BACKGROUND

[0002] With the rapid development and popularization of the electric vehicle market, users have increasingly demanding requirements for the fast-charging capability of power batteries. Developing lithium-ion batteries with excellent fast-charging performance has become the focus of attention of all links in the industry chain. The fast-charging performance of a battery ultimately depends on the intrinsic kinetic characteristics of its core components, namely the positive and negative active materials. Therefore, during the material research and selection stage, it is of great significance to quickly and accurately evaluate the fast-charging potential of a new type of active material in order to accelerate the development process of high-performance batteries and reduce research and development costs.

[0003] Currently, the industry's conventional approach to evaluating the fast-charging performance of materials is to manufacture full batteries and perform a series of electrochemical tests. However, this method has significant limitations: the existing tests cannot effectively obtain the intrinsic safety boundary and kinetic window of the material. At the same time, the test process is tedious and time-consuming, and researchers usually need to prepare multiple full batteries and perform cycle tests at different charging rates to determine whether lithium is precipitated through techniques such as disassembling the battery. This process is labor-intensive, time-consuming, and costly.

[0004] Therefore, there is an urgent need in the art for an evaluation method and device that can accurately predict the fast-charging potential of battery active materials to overcome the inherent defects of full battery testing, provide efficient theoretical guidance and data support for early screening and performance optimization of materials, and reduce testing costs and cycles. SUMMARY

[0005] To achieve the above-mentioned purpose, the present application discloses a method, device, system and storage medium for evaluating the fast-charging performance of battery active materials. The fast-charging performance evaluation method can predict the fast-charging potential of the material in a short time by assembling a mold battery and performing a rapid electrochemical impedance spectroscopy (EIS) test combined with theoretical calculations. This shortens the research and development cycle and reduces testing costs and material consumption.

[0006] The first aspect of the present application provides a method for evaluating the fast-charging performance of battery active materials. The method comprises: obtaining an ionic impedance related to a mold battery; wherein the mold battery has an asymmetric layered structure and is stacked by electrode sheets with the same active material but different sizes; determining a diffusion-controlled current density of the active material based on the ionic impedance; and determining a maximum charging rate of the active material using the diffusion-controlled current density combined with the area capacity of the active material.

[0007] According to some embodiments of the present application, the ion impedance is obtained after electrochemical impedance spectroscopy is performed on the mold cell.

[0008] According to some embodiments of the present application, the determining the diffusion-controlled current density of the active material comprises: determining a MacMullin number based on the ion impedance; and substituting the MacMullin number into a diffusion-controlled current density calculation model to output the diffusion-controlled current density.

[0009] According to some embodiments of the present application, the method further comprises: obtaining a temperature factor, and correcting the maximum charging rate using the temperature factor to determine the actual maximum charging rate of the active material at different temperatures.

[0010] According to some embodiments of the present application, the temperature factor shows a correspondence between the MacMullin number and different temperatures; and the determining the actual maximum charging rate of the active material at different temperatures comprises: using the correspondence to convert the MacMullin number into a corrected value determined using a target temperature; substituting the corrected value for the MacMullin number into the diffusion-controlled current density calculation model to output a corrected diffusion-controlled current density at the target temperature; and using the corrected diffusion-controlled current density and combining the area capacity of the active material to determine the actual maximum charging rate of the active material at the target temperature.

[0011] According to some embodiments of the present application, the diffusion-controlled current density calculation model is constructed based on Fick's law and Faraday's law, and reflects an inverse proportional relationship between the diffusion-controlled current density and the MacMullin number.

[0012] According to some embodiments of the present application, the inverse proportional relationship is formed based on a proportional relationship between the diffusion-controlled current density and an effective diffusion rate of the active material, and an inverse proportional relationship between the effective diffusion rate and the MacMullin number.

[0013] The second aspect of the present application provides a device for evaluating fast charging performance of a battery active material, the device comprising: a measurement module configured to measure an ion impedance related to a mold cell; wherein the mold cell has an asymmetric layered structure formed by stacking electrode sheets with the same active material but different sizes; a calculation module configured to determine a diffusion-controlled current density of the active material based on the ion impedance; and a determination module configured to determine a maximum charging rate of the active material using the diffusion-controlled current density and combining an area capacity of the active material.

[0014] The third aspect of the present application provides a computing system, which can include a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the computer program can implement the steps of the method for evaluating the fast-charging performance of a battery active material when executed by the processor.

[0015] The fourth aspect of the present application provides a computer-readable storage medium, which stores a computer program, wherein the computer program can implement the steps of the method for evaluating the fast-charging performance of a battery active material when executed by a processor.

[0016] The fifth aspect of the present application provides a computer program product, which includes a computer program, wherein the computer program can implement the steps of the method for evaluating the fast-charging performance of a battery active material when executed by a processor.

[0017] The method for evaluating the fast-charging performance of a battery active material disclosed in the present application has high accuracy and low cost. Without the multiple-rate and long-cycle cyclic tests in the traditional full-cell test, the fast-charging performance of the active material can be predicted in a short time, which effectively shortens the research and development cycle, reduces the test cost and material consumption.

[0018] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter. BRIEF DESCRIPTION OF DRAWINGS

[0019] The present application will be further described in the manner of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, the same reference numbers represent the same structures, wherein: Figure 1 is an exemplary flowchart of the method for evaluating the fast-charging performance of a battery active material according to some embodiments of the present application; Figure 2 is an exemplary structural diagram of a mold cell according to some embodiments of the present application; Figure 3 is an exemplary schematic diagram of an electrochemical impedance spectroscopy test according to some embodiments of the present application; Figure 4 is an exemplary relationship diagram between the MacMullin number and the compaction density of an active material according to some embodiments of the present application; Figure 5 is an exemplary comparison diagram of the theoretical calculation results and the actual test results of the fast-charging capability of a battery active material according to some embodiments of the present application; Figure 6This is an exemplary schematic diagram showing the theoretical calculation results of the fast charging capability of the battery active material at different temperatures according to some embodiments of this application; Figure 7 This is an exemplary block diagram of a processing apparatus for implementing a fast-charging performance evaluation method for the battery active material, according to some embodiments of this application; and, Figure 8 These are exemplary block diagrams of computing devices shown in some embodiments according to this application. Detailed Implementation

[0020] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, the specific embodiments of this application are described in detail below. Many specific details are set forth in the following description to provide a thorough understanding of this application. However, this application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of this application. Therefore, this application is not limited to the specific embodiments disclosed below.

[0021] Unless otherwise defined, all technical and scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in this application and in its specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The terms "comprising" or "including," as used in this application, mean that an element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. The terms "and / or" or "and / or" as used in this application include any and all combinations of one or more of the associated listed items.

[0022] The terms “comprising,” “having,” and their cognates used in this application are intended only to indicate a particular feature, number, step, operation, element, component, or combination thereof, and should not be construed as excluding, firstly, the presence of one or more other features, numbers, steps, operations, elements, components, or combinations thereof, or adding the possibility of one or more features, numbers, steps, operations, elements, components, or combinations thereof.

[0023] It should be noted that the terms "first," "second," "third," etc., used in this application are for distinguishing descriptions only and should not be construed as indicating or implying relative importance. When a component is referred to as being "fixed to," "installed on," or "set on" another component, it may be directly on the other component or may be interposed with other components. When a component is considered to be "connected to" another component, it may be directly connected to the other component or may be interposed with other components. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only.

[0024] The following describes some preferred embodiments of this application. It should be noted that the following description is for illustrative purposes only and is not intended to limit the scope of protection of this application. The steps involved in this application may be performed precisely in sequence, or various steps may be processed in reverse order or simultaneously. Furthermore, other operations may be added to these processes, or one or more steps may be removed from these processes.

[0025] The fast-charging performance evaluation method for the battery active materials provided in this application can be referenced. Figure 1 The process 100 shown can be implemented in a computing device, such as an industrial computer, server, computer, tablet, or smart mobile device. In some embodiments, the process 100 can be stored in a storage device (such as the built-in storage unit of the computing device or an external storage device) in the form of a program or instructions, which, when executed, can implement the process 100. Figure 1 As shown, process 100 may include the following operations.

[0026] Step 110: Measure the ionic impedance associated with the mold cell.

[0027] In some embodiments, the mold battery may have a layered structure, consisting of stacked electrode sheets having the same active material but different sizes. (Reference) Figure 2 The exemplary structural diagram of a mold battery according to some embodiments of this application is shown. The mold battery 200 includes a first electrode sheet 210, a separator 220, and a second electrode sheet 230 stacked sequentially along the thickness direction. The electrode active layers of the first electrode sheet 210 and the second electrode sheet 230 are prepared using the same active material, and the preparation formula, i.e., the components constituting the electrode active layers, are identical in both quantity and proportion. For example, the electrode sheet can be prepared into a slurry from the active material, binder, conductive agent, and other necessary components, coated onto a current collector, and then subjected to drying, rolling, and cutting operations.

[0028] In some embodiments, by setting different parameters during the cutting operation, electrode sheets of the same or different sizes can be cut to serve as the first electrode sheet 210 and the second electrode sheet 230. For example, the first electrode sheet 210 and the second electrode sheet 230 are electrode sheets of the same size. Alternatively, the first electrode sheet 210 and the second electrode sheet 230 are electrode sheets of different sizes. For example, the first electrode sheet 210 has a size of 25mm × 25mm × 140μm, while the second electrode sheet 230 has a smaller size than the first electrode sheet 210, which is 20mm × 20mm × 130μm. Using electrode sheets of different sizes to assemble the mold battery can prevent assembly errors. The mold battery obtained even if the assembly is incomplete can still be used.

[0029] The separator 220 can be a commonly used separator for lithium-ion batteries, such as a polymer membrane, including but not limited to polyethylene (PE) membrane and polypropylene (PP) membrane. Alternatively, it can be a composite membrane consisting of a polymer layer and a polyolefin substrate, formed by coating a polyethylene film or polypropylene film with polymers such as polyvinylidene fluoride (PVDF) or polymethyl methacrylate (PMMA). The first electrode plate 210 and the second electrode plate 230 are respectively disposed on both sides of the separator 220, and the electrode active layer composed of active materials can face away from the separator 220. That is, the separator 220 is in contact with the current collectors of the first electrode plate 210 and the second electrode plate 230, respectively, while the electrode active layers of the first electrode plate 210 and the second electrode plate 230 face the positive electrode side (P) and the negative electrode side (N).

[0030] The electrolyte used in assembling the mold battery 200 can be an organic electrolyte, including organic solvents, electrolyte salts, and additives. Any known and suitable organic electrolyte can be used in this application. For example, one or more of the following organic solvents can be used: ethylene carbonate (EC), propylene carbonate (PC), ethyl methyl carbonate (EMC), diethyl carbonate (DEC), dimethyl carbonate (DMC), dipropyl carbonate (DPC), methyl propyl carbonate (MPC), and ethyl propyl carbonate (EPC). The following electrolyte salts can be used: lithium hexafluorophosphate (LiPF6), lithium hexafluoroborate (LiBF6), lithium bis(oxalato)borate (LiBOB), lithium difluorooxalatoborate (LiDFOB), lithium trifluoromethanesulfonate (LiOTF), lithium bis(trifluoromethanesulfonyl)imide (LiTFSI), and lithium bis(fluorosulfonyl)imide (LiFSI). The following additives can be used: vinylene carbonate (VC), ethylene ethylene carbonate (VEC), fluoroethylene carbonate (FEC), succinic anionyl (SN), and adiponitrile (AND). Adding electrolyte and assembling the battery will yield a mold battery 200.

[0031] In some embodiments, electrochemical impedance spectroscopy (EIS) testing of the mold battery can yield the ionic impedance of the electrode active layer composed of the active material. For example, this EIS testing can yield results such as... Figure 3 The Nyquist plot. The curve shown in the Nyquist plot intersects the real part (i.e., the horizontal axis Z') at the point where the electronic contact impedance obtained from the electrochemical impedance spectroscopy test is located, denoted as... Let the ionic impedance be . Then, based on the following equation (1), the above can be obtained. : (1) in, The value at the intersection of the reverse extension of the curve and the real part can characterize the total impedance related to ion transport.

[0032] Step 120: Determine the diffusion control current density of the active material based on the ionic impedance.

[0033] In some embodiments, the McMarin number can be introduced to determine the diffusion control current density and can be determined based on the ion impedance. McMarin number It can be used to quantify the ease of lithium ion migration in electrode coatings and is defined as the ratio of electrode tortuosity to electrode porosity. Combining ionic impedance in electrochemical systems to describe the obstruction of current during ion transport and to reflect the physical meaning of charge transfer and diffusion characteristics at the electrolyte-electrode interface, parameters such as the effective working area of ​​the electrode, electrolyte ionic conductivity, and electrode coating thickness are introduced to obtain the McMarin number as shown in the following formula (2). The expression: (2) in, Indicates the porosity in the electrode. Indicates the tortuosity of the electrode. This indicates the effective working area of ​​the electrode active layer composed of active materials in the mold battery. This indicates the ionic conductivity of the electrolyte used. It represents the sum of the thicknesses of the electrode coatings (i.e., the active electrode layers) of the two electrode layers.

[0034] In some embodiments, McMallin number This can be input into a diffusion-controlled current density calculation model to output the diffusion-controlled current density. This model can be constructed based on Fick's law and Faraday's law, and reflects the relationship between the diffusion-controlled current density and the McMullin number. The inverse proportional relationship between them. Fick's law describes the law of ion diffusion, showing that the ion diffusion rate is positively correlated with the effective diffusion rate of the active material and the lithium ion concentration gradient. This indicates that the McMurlin number... It is inversely proportional to the effective diffusion rate of the active material. The effective diffusion rate can be determined based on the diffusion rate of the active material itself and the microstructure factors characterizing the electrode. For example, the effective diffusion rate... It can be determined based on the following equation (3): (3) in, Indicates the effective diffusion rate. This indicates the inherent diffusion rate of the active material itself.

[0035] It can be seen that the above reciprocal Characterizing McMallin numbers Combining equations (2) and (3), the effective diffusion rate is... It can be converted into the following formula (4): (4) Equation (4) can also reflect the above McMullin number. The inverse relationship between the effective diffusion rate of the active material and the effective diffusion rate of the active material.

[0036] Faraday's law describes the charge transfer mechanism in electrode reactions, showing a positive correlation between charge transfer and current density. Current density, in turn, is positively correlated with the effective diffusion rate of the active material. The greater the effective diffusion rate, the greater the current density. Combining Fick's law and Faraday's law, the resulting diffusion-controlled current density calculation model can be expressed based on the following equation (5): (5) in, This represents the diffusion control current density. This indicates the chemical valence; in lithium-ion battery applications, the number of electrons transferred is 1. =1. Denotes Faraday's constant. This indicates the initial lithium-ion concentration in the electrolyte. For in 0- ( This refers to the variable between the coating thickness of a single-layer electrode (i.e., the thickness of the electrode active layer), specifically the different thickness locations of the active material (electrode active layer). Different thickness locations correspond to different... (State of charge, or remaining charge). The above... Transformed from and The numerical value represented is denoted as .

[0037] Substituting equation (4) into equation (5), we obtain the diffusion control current density shown in equation (6). The expression: (6) As shown in equation (6), its reaction diffusion control current density With McMalin The inverse proportional relationship.

[0038] Step 130: Determine the maximum charging rate of the active material by using the diffusion control current density and combining it with the areal capacity of the active material.

[0039] In some embodiments, the maximum charge rate of the active material This can be determined based on the quotient between the diffusion control current density and the areal capacity. For example, the maximum charge rate... The expression for can be shown in the following equation (7): (7) in, This indicates the area capacity.

[0040] It is known that the McMahon number is significantly correlated with temperature. As temperature increases, electrolyte viscosity decreases. Lower viscosity leads to increased ion migration rate, thus decreasing the McMahon number. Simultaneously, temperature fluctuations affect the electrode pore structure; higher temperatures increase electrode compaction density and decrease porosity, thereby increasing ion transport impedance and the McMahon number. This application introduces a temperature factor to address the issue at the maximum charge rate. The calibration is performed to determine the actual maximum charge rate of the active material at different temperatures.

[0041] In some embodiments, the temperature factor may display a McMarin number. The correspondence between different temperatures. For example, this correspondence can be expressed using the following equation (8): (8) Based on the above equation (8), the McMarin number at different temperatures It will be corrected to obtain the corresponding correction value, that is Substituting this correction value into the diffusion current density calculation model, the obtained value is... Let be the corrected diffusion control current density at the corresponding temperature. Substituting this corrected diffusion control current density into equation (7) will yield the actual maximum charge rate at the corresponding temperature. It can be expressed as the following formula (9): (9) This allows us to obtain different temperatures. The actual maximum charging rate of the active material is used as its corresponding fast charging performance.

[0042] The above process is illustrated below with specific implementation details. It should be noted that the following content is for illustrative purposes only and is not intended to limit the scope of this application.

[0043] 1. Assemble the mold battery: 92.0 wt% of graphite anode active material, 5.0 wt% of binder (CMC:SBR=1:1) and 3.0 wt% of conductive agent (SP) are added to deionized water and mixed into a slurry. The slurry is then coated onto copper foil using a transfer coating machine. After drying, rolling, and cutting, the electrode sheet of the required diameter is obtained and assembled with a separator to form a mold battery.

[0044] Specifically, the upper layer uses a 14mm diameter graphite negative electrode sheet (facing the positive electrode side), the 18mm diameter PE separator, and the lower layer uses a 16mm diameter graphite negative electrode sheet (facing the negative electrode side). The coating thickness of the upper electrode sheet is 76.25μm, and the coating thickness of the lower electrode sheet is 76.25μm.

[0045] The electrolyte used for assembling the battery is: 1M lithium hexafluorophosphate as the solute, EC:DMC = 1:1 as the solvent, and K = 9 mS / cm as the electrolyte ionic conductivity.

[0046] 2. EIS test The battery underwent EIS testing at 25°C. The point where the impedance extension line intersects the real axis. This refers to the electronic contact impedance measured by EIS. According to... The ionic impedance of the electrode active material layer was calculated. .

[0047] Three EIS tests were conducted on graphite anodes with the same formulation but different compaction densities at 25℃. The ionic impedance and McMurlin number were calculated according to the formula, and the results are shown in Table 1 below. Table 1. EIS test results and ion impedance calculation results under different compaction densities The average value of the three sets of tests was taken to obtain the McMarin number under different compaction densities. The result may be as follows Figure 4 As shown. Reference Figure 4 It is known that compaction density affects the McMurlin number, which in turn affects the fast-charging capability of the active material.

[0048] 3. Fast charging capability calculation According to the formula: Calculate the compacted density at 25℃ using 1.655 g / cm³. -3 , A graphite anode sheet with a capacitance of 14.05 μm achieves fast charging capabilities at different SOCs. Initial lithium-ion concentration in the electrolyte: =1M / L; Chemical valence: =1; The inherent diffusion rate of the active material itself: =2.0×10 -8 cm 2 / s; Electrode coating thickness: =76.25μm; Active material surface area capacity: =3.792 mAh / cm 2 .

[0049] Calculation results Figure 5 As shown. The calculation results are compared with the measured charging capacity after the graphite anode active material is assembled into a battery cell, as shown. Figure 5 As shown, the two results are highly consistent. However, after assembly into a battery cell, the maximum charging rate is slightly lower than the calculated value due to limitations imposed by the positive electrode active material, demonstrating the effectiveness of this calculation method.

[0050] 4. Temperature Correction Furthermore, the fast-charging capability calculation formula with a temperature factor is used for correction.

[0051] According to the formula: The fast-charging capability of the negative electrode graphite active material at different temperatures was obtained, and the results are as follows: Figure 6 As shown, increased temperature will affect the fast-charging capability of active materials, which is consistent with the fact that increased temperature increases the proportion of activated molecules inside the battery, thereby promoting the migration speed of lithium ions and improving charging and discharging efficiency.

[0052] The fast-charging performance evaluation method for battery active materials disclosed in this application first constructs a mold battery with a symmetrical / asymmetrical layered structure to define a clear ion transport path and eliminate the interference of edge effects on the test. Electrochemical impedance spectroscopy (EIS) is performed on this battery to obtain the ion impedance reflecting the internal ion transport characteristics of the material, and the McMaurin number is introduced and calculated. A theoretical model is constructed based on Fick's law and Faraday's law, and the McMaurin number is substituted into the model to directly calculate the diffusion control current density characterizing the intrinsic fast-charging performance of the material. Then, combined with the areal capacity of the active material, the maximum charging rate under different states of charge is determined. Finally, the fast-charging capability calculation formula is corrected by introducing a temperature factor to obtain the actual fast-charging capability of the material under different temperature conditions. This method can quickly and accurately predict the upper limit of the fast-charging performance of active materials under different compaction densities and temperature conditions without the need to fabricate a full cell, greatly improving the screening efficiency of material development.

[0053] The fast-charging performance evaluation method for battery active materials disclosed in this application is based on theoretical derivation using physical laws. It correlates easily measurable ionic impedance with the material's diffusion capacity through the McMarin number, making the method easy to implement. Furthermore, the accuracy and scientific validity of the method have been verified experimentally.

[0054] It should be noted that the above-mentioned Figure 1 The descriptions of the various steps in this specification are for illustrative purposes only and do not limit the scope of this specification. Those skilled in the art can, under the guidance of this specification, [perform certain tasks / activities]. Figure 1 Various modifications and changes have been made to the steps described herein. However, these modifications and changes remain within the scope of this specification.

[0055] This application also discloses a processing apparatus for implementing a fast-charging performance evaluation method for the battery active material. This processing apparatus can be used to perform, for example... Figure 1 For details on each step shown, please refer to the corresponding accompanying drawings. Figure 7 These are exemplary block diagrams of a processing apparatus shown according to some embodiments of this application, such as... Figure 7 As shown, the processing device 700 may include an acquisition module 710, a calculation module 720, and a determination module 730.

[0056] The acquisition module 710 can measure the ionic impedance associated with the mold battery. The ionic impedance can be obtained by performing electrochemical impedance spectroscopy on the mold battery. The acquisition module 710 can acquire the ionic impedance by communicating with the testing equipment.

[0057] The calculation module 720 can be configured to determine the diffusion control current density of the active material based on the ionic impedance. The calculation module 720 can determine the McMahring number based on the ionic impedance and substitute the McMahring number into the diffusion control current density calculation model to output the diffusion control current density.

[0058] The determining module 730 can determine the maximum charging rate of the active material using the diffusion current density and the areal capacity of the active material. The determining module 730 can use the quotient between the diffusion current density and the areal capacity of the active material as the maximum charging rate.

[0059] Further descriptions of the aforementioned components can be found in this application. Figures 1-6 part.

[0060] It should be understood that Figure 7 The systems and modules shown can be implemented in various ways. For example, in some embodiments, the systems and modules can be implemented by hardware, software, or a combination of both. The hardware portion can be implemented using dedicated logic; the software portion can be stored in memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated-design hardware. Those skilled in the art will understand that the methods and systems described above can be implemented using computer-executable instructions and / or included in processor control code, for example, on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The systems and modules of this application can be implemented not only by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field-programmable gate arrays, programmable logic devices, etc., but also by software executed by various types of processors, or by a combination of the aforementioned hardware circuits and software (e.g., firmware).

[0061] It should be noted that the above description of the modules is for convenience only and should not be construed as limiting this application to the scope of the embodiments described. It is understood that those skilled in the art, after understanding the principle of the system, may arbitrarily combine the modules or construct subsystems connected to other modules without departing from this principle. For example, the acquisition module 710, calculation module 720, and determination module 730 are the same module to simultaneously implement their corresponding functions. As another example, the modules may share a single storage module, or each module may have its own separate storage module. Such variations are all within the scope of protection of this application.

[0062] This application also provides a computing device. (See reference...)Figure 8 The diagram shown is an exemplary block diagram of a computing device according to some embodiments of this application. The computing device 800 may include components for implementing the processes described in the embodiments of this application (e.g., Figures 1-6 The content shown) or system (e.g., Figure 7 Any component of the contents shown. For example, computing device 800 can be implemented using hardware, software programs, firmware, or a combination thereof. For convenience, Figure 8 Only one computing device is shown in the figure, but the computing functions related to the process and / or system / device described in the embodiments of this application can be implemented in a distributed manner by a set of similar platforms to distribute the processing load of the system.

[0063] In some embodiments, computing device 800 may include processor 810, memory 820, input / output 830, and communication port 840. In some embodiments, the processor (e.g., CPU) 810 may execute program instructions as one or more processors. In some embodiments, the memory 820 may include different forms of program memory and data memory, such as hard disk, read-only memory (ROM), random access memory (RAM), etc., for storing various data files processed and / or transmitted by the computer. In some embodiments, the input / output 830 may be used to support input / output between computing device 800 and other components. In some embodiments, the communication port 840 may be connected to a network for data communication. Exemplary computing devices may include program instructions executed by processor 810 stored in read-only memory (ROM), random access memory (RAM), and / or other types of non-transitory storage media. The methods and / or processes of the embodiments of this application may be implemented in the form of program instructions. Computing device 800 may also receive programs and data disclosed in this application via network communication.

[0064] For ease of understanding, Figure 8 Only one processor is illustrated in the illustration. However, it should be noted that the computing device 800 in this embodiment may include multiple processors. Therefore, the operations and / or methods implemented by one processor as described in this embodiment may also be implemented jointly or independently by multiple processors. For example, if, in this application, the processor of computing device 800 executes operations A and B, it should be understood that operations A and B may also be executed jointly or independently by two different processors of computing device 800 (e.g., the first processor executes operation A, the second processor executes operation B, or the first and second processors jointly execute operations A and B).

[0065] This application has described the basic concepts. Obviously, for those skilled in the art, the above detailed disclosure is merely illustrative and does not constitute a limitation of this application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and corrections to this application. Such modifications, improvements, and corrections are suggested in this application, and therefore such modifications, improvements, and corrections still fall within the spirit and scope of the exemplary embodiments of this application.

[0066] Furthermore, this application uses specific terms to describe its embodiments. For example, "an embodiment," "one embodiment," and / or "some embodiments" refer to a particular feature, structure, or characteristic related to at least one embodiment of this application. Therefore, it should be emphasized and noted that "an embodiment," "one embodiment," or "an alternative embodiment" mentioned twice or more in different locations in this application do not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of this application can be appropriately combined.

[0067] Similarly, it should be noted that, in order to simplify the description of this application and thus aid in the understanding of one or more embodiments of the invention, the foregoing description of the embodiments of this application sometimes combines multiple features into one embodiment or its description. However, this disclosure method does not imply that the subject matter of this application requires more features than those mentioned in the claims. In fact, the embodiments have fewer features than all the features of the single embodiments disclosed above.

[0068] Finally, it should be understood that the embodiments described in this application are merely illustrative of the principles of the embodiments of this application. Other modifications may also fall within the scope of this application. Therefore, alternative configurations of the embodiments of this application are considered as examples and not limitations, and are regarded as consistent with the teachings of this application. Accordingly, the embodiments of this application are not limited to the embodiments explicitly described and illustrated in this application.

Claims

1. A method for evaluating the fast-charging performance of battery active materials, characterized in that, The method includes: Obtain the ion impedance associated with the mold battery; wherein the mold battery is composed of stacked electrode sheets having the same active material and different sizes; Based on the ionic impedance, the diffusion control current density of the active material is determined; The maximum charge rate of the active material is determined by using the diffusion-controlled current density and combining it with the areal capacity of the active material.

2. The fast charging performance evaluation method according to claim 1, characterized in that, The ionic impedance is obtained based on electrochemical impedance spectroscopy testing of the mold battery.

3. The fast charging performance evaluation method according to claim 1, characterized in that, Determining the diffusion control current density of the active material includes: The McMarin number is determined based on the ionic impedance. The McMullin number is substituted into the diffusion control current density calculation model to output the diffusion control current density.

4. The fast charging performance evaluation method according to claim 3, characterized in that, The method further includes: A temperature factor is obtained, and the maximum charge rate is corrected using the temperature factor to determine the actual maximum charge rate of the active material at different temperatures.

5. The fast charging performance evaluation method according to claim 4, characterized in that, The temperature factor shows the correspondence between the McMurlin number and different temperatures; Determining the actual maximum charge rate of the active material at different temperatures includes: Using the aforementioned correspondence, the McMarin number is converted into a correction value determined using the target temperature; The corrected value is substituted for the McMullin number and substituted into the diffusion control current density calculation model to output the corrected diffusion control current density at the target temperature. The actual maximum charge rate of the active material at the target temperature is determined by using the corrected diffusion control current density and combining it with the areal capacity of the active material.

6. The fast charging performance evaluation method according to any one of claims 3-5, characterized in that, The diffusion control current density calculation model is based on Fick's law and Faraday's law, and reflects the inverse proportional relationship between the diffusion control current density and the McMullin number.

7. The fast charging performance evaluation method according to claim 8, characterized in that, The inverse proportional relationship is based on the direct proportionality between the diffusion control current density and the effective diffusion rate of the active material, and the inverse proportionality between the effective diffusion rate and the McMurlin number.

8. A device for evaluating the fast-charging performance of battery active materials, characterized in that, The device includes: The measurement module is configured to measure the ion impedance associated with the mold battery; wherein the mold battery has an asymmetric layered structure and is composed of stacked electrode sheets having the same active material but different sizes; The calculation module is configured to determine the diffusion control current density of the active material based on the ionic impedance; The determination module uses the diffusion control current density and the areal capacity of the active material to determine the maximum charging rate of the active material.

9. A computing system, the computing system comprising: The memory, the processor, and the computer program stored in the memory and executable on the processor, wherein when executed by the processor, the computer program can implement the steps of the fast-charging performance evaluation method for battery active materials as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the steps of the fast-charging performance evaluation method for battery active materials as described in any one of claims 1-7.

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