Modeling method for liquid metal battery electrode diffusion process based on pade approximation

Abstract

The application discloses a modeling method of an electrode diffusion process of a liquid metal battery based on a Pade approximation, and belongs to the technical field of liquid metal battery applications. The method comprises the following steps: setting a 1-D simplified model of the battery according to the layered structure characteristics of the liquid metal battery, and acquiring a diffusion coefficient corresponding to a positive electrode material in the liquid metal battery, and then acquiring a ratio of a positive electrode Li diffusion concentration to a current density; the ratio describes the dynamic performance of the positive electrode; the ratio is simplified by using a partial differential equation of the Pade approximation to simulate the electrode diffusion process of the liquid metal battery, so that an electrode diffusion process model is obtained. The application uses the partial differential equation of the Pade approximation to simplify the parameters for describing the dynamic performance of the positive electrode, so as to simulate the electrode diffusion process of the liquid metal battery, and the electrode diffusion process is simplified, and the calculation efficiency is improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of liquid metal battery application, and more particularly relates to a modeling method for electrode diffusion process of liquid metal battery based on pade approximation. BACKGROUND

[0002] Liquid metal battery is a new type of electrochemical energy storage technology developed in recent years for large-scale energy storage of power system, which has the advantages of long cycle life, low cost and large capacity. At a working temperature of 300-700 DEG C, the positive and negative electrode metal materials and the molten salt electrolyte are all in liquid state, and are automatically stratified due to the density difference. The all-liquid structure discards the separator structure of the traditional battery, and also avoids the shortcomings of the traditional battery that the cycle life is affected by the change of the solid electrode structure. At the same time, the liquid metal battery is easy to scale up and has stable performance, so it has good prospects for large-scale and long-time energy storage applications.

[0003] The electrode reaction process of liquid metal battery is mainly the diffusion of lithium metal, and the electrode diffusion research is of great significance for clarifying the battery reaction, building the battery model and efficiently managing the battery. However, the electrode reaction of liquid metal battery is composed of partial differential equations, and the traditional finite element analysis method has large amount of calculation and is difficult to be applied to the actual battery management system. Therefore, it is necessary to simplify the electrode diffusion process on the basis of ensuring the accuracy. Based on the characteristics that the positive and negative electrodes of lithium ion battery are both solid structures, the battery electrode is represented by a spherical particle, and the movement of matter in the spherical particle is used to represent the solid diffusion process of the battery. However, due to the particularity of the three-layer structure of liquid metal battery, the electrode is not equivalent to the spherical particle, and the modeling of the electrode of liquid metal battery is not applicable.

[0004] In view of the above problems, it is necessary to develop a simple and feasible modeling method for electrode diffusion process according to the special structure of liquid metal battery, so as to lay a foundation for efficient management and state estimation of liquid metal battery. SUMMARY

[0005] In view of the above defects or improvement needs of the prior art, the present application provides a modeling method for electrode diffusion process of liquid metal battery based on pade approximation, which aims to use the pade approximation of partial differential equation to simplify the parameters for describing the dynamic performance of the positive electrode, so as to simulate the electrode diffusion process of the liquid metal battery, simplify the electrode diffusion process and improve the calculation efficiency, thereby solving the technical problems that the electrode diffusion process of liquid metal battery is complex, the traditional finite element analysis method has large amount of calculation and is difficult to be applied to the battery management system.

[0006] To achieve the above purpose, according to one aspect of the present application, a modeling method for electrode diffusion process of liquid metal battery based on pade approximation is provided, which comprises:

[0007] S1: setting a battery 1-D simplified model according to the characteristics of the liquid metal battery layered structure, the battery 1-D simplified model being set as follows: the movement of substances only occurs in the horizontal direction and the electrochemical reaction occurring in the horizontal direction is uniform; the negative electrode diffusion process is ignored and the negative electrode potential is regarded as zero; the electrode capacity of the positive and negative electrodes does not change during the reaction process; the effect of gravity on the substances is ignored;

[0008] S2: obtaining the diffusion coefficient D of the positive electrode material corresponding to the liquid metal battery according to the battery 1-D simplified model p ;

[0009] S3: describing the positive electrode diffusion process by using the Fick second law and the diffusion coefficient to obtain the ratio of the positive electrode Li diffusion concentration to the current density, which is used to describe the dynamic performance of the positive electrode;

[0010] S4: simplifying the ratio by using the partial differential equation of the Pade approximation to simulate the electrode diffusion process of the liquid metal battery, so as to obtain an electrode diffusion process model.

[0011] In one embodiment, the S2 includes:

[0012] Since the negative electrode pure lithium of the liquid metal battery is regarded as zero potential, the measured open circuit voltage is the equilibrium potential of the positive electrode; the diffusion coefficient is obtained by using the relationship between the change of the battery voltage and the relaxation time.

[0013] In one embodiment, the S2 includes:

[0014] The diffusion coefficient D is calculated by using the formula p ;

[0015] Wherein, τ represents the relaxation time, n m represents the number of moles; V m represents the molar volume of the electrode material; S represents the electrode / electrolyte contact area; ΔE s is the voltage change caused by the pulse; ΔE t is the voltage change of the constant current charge and discharge.

[0016] In one embodiment, the S4 includes:

[0017] S41: obtaining the transcendental function term H(s) in the ratio G(s);

[0018] S42: approximating and simplifying H(s) by using the function H app (s) based on the partial differential equation of the Pade approximation; a i is the molecular coefficient, b i ​is the denominator coefficient, N and M are integer terms;

[0019] S43: solving H app the coefficient a of (s) i .

[0020] In one embodiment, the S2 comprises:

[0021] S21: using Fick's second law and the diffusion coefficient to describe the positive electrode diffusion process to obtain the positive electrode surface lithium concentration and the ratio of the current density I(s); and obtain the average lithium concentration of the positive electrode and the ratio of the current density I(s);

[0022] S22: using obtain the Li diffusion concentration and the ratio G(s) of the current density I(s) to describe the parameters of the positive electrode dynamic performance.

[0023] In one embodiment, the S21 comprises:

[0024] using to describe the positive electrode diffusion process, and obtain the positive electrode surface lithium concentration combined with the boundary conditions of the positive electrode diffusion and the ratio of the current density I(s):

[0025] using the formula characterize the average lithium concentration of the positive electrode and the ratio G(s) of the current density I(s);

[0026] wherein C P represents the Li concentration, x represents the corresponding x-axis position, t represents time, A is the cross-sectional area of the positive electrode, F is the Faraday constant, and L is the length of the positive electrode.

[0027] In one embodiment, the S41 comprises:

[0028] substitute λ = L 2 / D p into the ratio obtain H(s) is a transcendental function term.

[0029] In one embodiment, the S43 comprises:

[0030] for a1: using the formula a1 = H app (s) s→0 = H(s) s→0 to solve a1;

[0031] for the remaining a i: fixing N and M, in the initial population generation stage, setting a range according to an initial value, randomly generating k vectors, each vector being composed of a coefficient group to be identified; the population evolution stage is divided into four parts of parent selection, gene crossing, gene mutation and introduction of foreign individuals to update and iterate the initial value; when the iteration times are greater than a preset time, the iteration is stopped; and the individual with the minimum evaluation index in the last population is taken as the optimal coefficient solution to be identified;

[0032] wherein the evaluation index is O H =||Re[H app (s)]-Re[H(s)]||+||Im[H app (s)]-Im[H(s)]||; and ||.|| represents the Euclidean distance between vectors.

[0033] According to another aspect of the present application, there is provided a modeling device for the electrode diffusion process of a liquid metal battery based on Pade approximation, for performing the above modeling method, comprising:

[0034] a setting module configured to set a battery 1-D simplified model according to the layered structure characteristics of the liquid metal battery, the battery 1-D simplified model being set as: the movement of substances only occurs in the horizontal direction and the electrochemical reaction occurring in the horizontal direction is uniform; the negative electrode diffusion process is ignored and the negative electrode potential is considered as zero; the electrode capacity of the positive and negative electrodes does not change during the reaction process; and the influence of gravity on the substances is ignored;

[0035] an acquisition module configured to acquire the diffusion coefficient D p of the positive electrode material corresponding to the liquid metal battery according to the battery 1-D simplified model;

[0036] a description module configured to describe the positive electrode diffusion process by using Fick's second law and the diffusion coefficient, so as to obtain the ratio of the positive electrode Li diffusion concentration to the current density, the ratio being used to describe the positive electrode dynamic performance;

[0037] a simplification module configured to simplify the ratio by using the partial differential equation of Pade approximation, so as to simulate the electrode diffusion process of the liquid metal battery, thereby obtaining the electrode diffusion process model.

[0038] According to another aspect of the present application, there is provided an electronic device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the steps of the above method when executing the computer program.

[0039] Overall, the above technical solutions conceived by the present application can achieve the following beneficial effects compared with the prior art:

[0040] (1) Based on the partial differential equation simplification method of pade approximation, the electrode diffusion process of the liquid metal battery can be effectively simulated. Compared with the traditional finite element analysis method, the calculation efficiency can be improved on the basis of ensuring the model precision. At the same time, the response curves under different orders are analyzed to determine the optimal order of the model.

[0041] (2) The solution process of the diffusion coefficient is simplified, the relationship between the full battery voltage change and the relaxation time is used to realize the rapid acquisition of the positive electrode diffusion coefficient, which is more convenient in practical application. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 The structure schematic diagram of the liquid metal battery provided by an embodiment of the application is shown in the figure;

[0043] Figure 2 The structure schematic diagram of the liquid metal battery 1-D provided by an embodiment of the application is shown in the figure;

[0044] Figure 3 The fitting diagram of the diffusion equation frequency domain response and the simplified equation provided by an embodiment of the application is shown in the figure;

[0045] Figure 4 The fitting diagram of the diffusion equation time domain response and the simplified equation provided by an embodiment of the application is shown in the figure;

[0046] Figure 5 The diffusion coefficient solving diagram based on the full battery relaxation time provided by an embodiment of the application is shown in the figure;

[0047] Figure 6 The voltage response diagram of the liquid metal battery under the constant current condition provided by an embodiment of the application is shown in the figure. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical scheme and advantages of the application clearer, the application is further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the application and do not limit the application. In addition, the technical features involved in each embodiment of the application described below can be combined with each other as long as they do not conflict with each other.

[0049] The application provides a modeling method of the electrode diffusion process of the liquid metal battery based on pade approximation, comprising:

[0050] S1: A battery 1-D simplified model is set according to the layered structure characteristics of the liquid metal battery, and the battery 1-D simplified model is set as follows: the movement of the material only occurs in the horizontal direction and the electrochemical reaction occurring in the horizontal direction is uniform; the negative electrode diffusion process is ignored and the negative electrode potential is considered as zero; the positive and negative electrode capacities do not change during the reaction process; the influence of gravity on the material is ignored;

[0051] S2: Obtain the diffusion coefficient D of the positive electrode material in the liquid metal battery for the battery 1-D simplified model p ;

[0052] S3: Use Fick's second law and the diffusion coefficient to describe the positive electrode diffusion process to obtain the positive electrode Li diffusion concentration The ratio G(s) of the current density I(s), G(s) is used to describe the positive electrode dynamic performance, and s is a complex variable in Laplace transform;

[0053] S4: Use Pade approximation to simplify the partial differential equation ratio to simulate the electrode diffusion process of the liquid metal battery, thereby obtaining the electrode diffusion process model.

[0054] A battery 1-D simplified model is proposed for the layered structure characteristics of the liquid metal battery. Taking discharging as an example, during discharging, the negative lithium ions pass through the salt to reach the positive electrode surface, react with the positive metal (Bi or SbSn alloy, etc.), causing the change of Li concentration in the electrode, thereby forming a concentration gradient.

[0055] Preferably, based on the characteristics of the liquid metal battery, the 1-D simplified model is assumed as follows: (1) Assume that the material movement only occurs in the x-axis direction, and the electrochemical reaction occurring in the x direction is uniform, that is, the material concentration in the y-axis direction is equal; (2) Since the negative electrode material is generally pure Li, no concentration gradient is formed, so the diffusion process in the negative electrode can be ignored, and the negative electrode potential can be considered as 0; (3) Assume that the positive and negative electrode capacities do not change during the reaction process; (4) Assume that the effect of gravity on the material can be ignored.

[0056] Preferably, according to assumption (2), the negative electrode diffusion process can be ignored, and the negative electrode potential will not be affected, so only the positive electrode diffusion process needs to be considered. The positive electrode diffusion is described by Fick's second law:

[0057]

[0058] In the formula, D p represents the diffusion coefficient of Li in the positive electrode material, C P represents the Li concentration, x represents the corresponding x-axis position, and t represents the time.

[0059] Further, the boundary condition of the positive electrode diffusion is related to the current density J, as shown in formulas (2)-(3):

[0060]

[0061]

[0062] In the formula, L is the length of the positive electrode. The lithium concentration on the surface of the positive electrode of the liquid metal battery with average lithium concentration is an important parameter for studying diffusion process. The surface lithium concentration determines the potential of the positive electrode, while the average lithium concentration in the electrode determines the SOC of the electrode. The difference between the surface lithium concentration and the average lithium concentration is the diffusion concentration which can be expressed by equation (4):

[0063]

[0064] Further, by taking the Lagrange transformation of equation (1) and substituting the boundary equations of equations (2)-(3), the surface Li concentration of the positive electrode can be obtained as The relationship between the surface Li concentration and the current density I(s) is shown in equation (5):

[0065]

[0066] where A is the cross-sectional area of the positive electrode, and F is the Faraday constant.

[0067] Further, the average lithium concentration in the positive electrode and the average current density j avg which can be expressed by equations (6)-(7):

[0068]

[0069]

[0070] By taking the derivative of equation (6) with respect to variable t and taking the Lagrange transformation, and then substituting equation (7), the relationship between the average lithium concentration and the current can be obtained as shown in equation:

[0071]

[0072] Further, by equations (4), (5), (8), the relationship between the lithium diffusion concentration and the current can be obtained as shown in equation (9):

[0073] G(s) represents the dynamic performance of the positive electrode, which describes the change of the battery diffusion concentration with the current. For the convenience of calculation, let λ = L 2 / D, which is substituted into equation (9), G λ (s) can be obtained as shown in equation (10).

[0074]

[0075] Further, for the convenience of subsequent simplification, the H(s) containing transcendental function items in equation (10) is arranged as shown in equation (11).

[0076]

[0077] The transcendental function in H(s) is difficult to be parameter identified and has low computational efficiency, which restricts the application of the model in actual battery management system, and therefore it is necessary to approximate and simplify H(s) by using a function H app (s).

[0078] Preferably, the present application uses the Pade approximation method to simplify the diffusion process. The Pade approximation is an effective method for solving the rational approximation of an arbitrary function, and its standard form is as follows:

[0079]

[0080] In the formula, a i is the numerator coefficient, b i is the denominator coefficient, and N and M are integer terms.

[0081] In the formula, a1 can be obtained by frequency response characteristics, and the coefficient a1 can be obtained by the system response when s approaches 0:

[0082] a1 = H app (s)| s→0 = H(s)| s→0 (13)

[0083] Preferably, in the present application, other coefficients can be identified by using a genetic algorithm. The genetic algorithm is a search algorithm for solving the optimal solution of an optimization problem, and the optimal solution is obtained by iteration of processes such as initial value selection, crossover and mutation.

[0084] Preferably, the values of N and M are fixed, and in the initial population generation stage, k vectors are randomly generated according to the initial value setting range, and each vector is composed of the coefficients to be identified. Further, the population evolution stage is divided into four parts of parent selection, gene crossover, gene mutation and introduction of foreign individuals to update and iterate the initial value.

[0085] Preferably, since the frequency domain system parameters need to be identified in the present application, the identification effect needs to be evaluated in the real part and the imaginary part, and therefore the evaluation index of the present application is:

[0086] O H = ||Re[H app (s)]-Re[H(s)]||+||Im[H app (s)]-Im[H(s)]|| (14)

[0087] In the formula, ||.|| represents the Euclidean distance between vectors.

[0088] Preferably, in the present application, the iteration is stopped when the number of iterations is greater than 10,000, and the individual with the minimum evaluation index in the last population is taken as the optimal coefficient solution identified.

[0089] Furthermore, in order to improve computational efficiency while meeting accuracy requirements, the optimal order of the approximate electrode diffusion process is analyzed by taking different values ​​for N and M, combined with system response analysis.

[0090] According to another aspect of the present invention, a simple method for obtaining the diffusion coefficient of the positive electrode based on the characteristics of liquid metal batteries is provided. Traditional methods for obtaining the diffusion coefficient of liquid metal batteries require designing a reference electrode and building a titration experimental platform in a high-temperature environment, a process that is complex and difficult to operate.

[0091] Preferably, this invention utilizes a full-cell constant-current intermittent titration technique to solve for the diffusion coefficient. Since the pure lithium anode of a liquid metal battery can be considered to have zero potential, by allowing the battery to stand for a sufficiently long time, the measured open-circuit voltage is the equilibrium potential of the positive electrode. The diffusion coefficient is obtained using the relationship between the battery voltage change and the relaxation time; the formula for solving the diffusion coefficient is:

[0092]

[0093] Where τ represents the relaxation time, and n m This refers to the number of moles; V m The molar volume of the electrode material is represented by S; the electrode / electrolyte contact area is represented by ΔE. s It is the voltage change caused by the pulse; ΔE t It is the voltage change during constant current charging (discharging).

[0094] Figure 1 This is a schematic diagram of the liquid metal battery structure provided by the present invention. Preferably, in one embodiment of the present invention, a Li||Sb4Sn6 liquid metal battery with a rated capacity of 20Ah is selected.

[0095] Figure 2 This is a schematic diagram of the 1-D structure of the liquid metal battery provided by the present invention. x = L and x = L + Ls are the contact surfaces of the positive electrode / molten salt and the negative electrode / molten salt, respectively, where electrochemical reactions occur. Taking discharge as an example, the lithium metal at the negative electrode loses electrons at x = L + Ls and becomes Li. + Li + The molten salt reacts with the cathode material at x = L to form an alloy. When the Li concentration changes on the cathode / molten salt surface, a concentration gradient is formed, which causes Li to diffuse in the cathode.

[0096] Figure 3 , Figure 4 The solid lines in the graph represent the frequency and time domain responses of formula (11), respectively, while the dotted line graph shows the fitting results using the Pade approximation method. Analyzing formula (11) at a frequency of 10... -5 -10 5The amplitude-frequency and phase-frequency response of the interval, in the high frequency region, the amplitude-frequency curve slope is -10dB / octave. The phase of G(s) is close to 0° at low frequency, and close to -45° at high frequency, and the integer order polynomial cannot realize the fitting of the Bode diagram. Therefore, the base term of the above polynomial needs to be changed to a fractional order, with 1 / 2 as the base order.

[0097] Preferably, in the application, the form of Pade approximation is shown in formula (16):

[0098]

[0099] By analyzing the Pade approximation fitting results of N=1, 2, 3, it can be known that with the increase of the order, the model accuracy is also improved. When N=2, 3, the fitting accuracy of the model is obviously higher than that when N=1, and the model accuracy of N=2 and N=3 is not obviously improved. Therefore, considering the accuracy and model complexity, the Pade approximation order is selected as N=2.

[0100] Figure 5 The positive electrode diffusion coefficient diagram based on the full battery relaxation time provided by the application contains the battery voltage change with the working condition and the diffusion coefficient calculation result. The specific battery experiment steps are as follows:

[0101] S1: charge the battery to full capacity in a constant current and constant voltage charging mode.

[0102] S2: stand for 20min to make the internal electrochemical reaction of the battery stable;

[0103] S3: discharge at 0.2C for 20min;

[0104] S4: repeat steps S2-S3 until the battery is reduced to the discharge cut-off voltage.

[0105] S5: stand for 20min to make the internal electrochemical reaction of the battery stable;

[0106] S6: charge at 0.2C for 20min;

[0107] S7: repeat steps S5-S6 until the battery is raised to the charge cut-off voltage.

[0108] Based on the positive electrode diffusion process simplification method provided by the application, a battery model embodiment is built, Figure 6 The model simulation and experimental result comparison chart under constant current condition is shown. Under the constant current discharge condition of 1A, 2A and 4A, the average error is 1.8mV, 1mV and 3.4mV respectively. It shows that the positive electrode diffusion simplification method provided by the application can effectively simulate the dynamic response process of the battery, and has wide practical application prospect.

[0109] According to another aspect of the present application, there is provided a modeling device for liquid metal battery electrode diffusion process based on Pade approximation, for performing the above modeling method, comprising:

[0110] a setting module configured to set a battery 1-D simplified model according to the hierarchical structure characteristics of the liquid metal battery, the battery 1-D simplified model being set as: the movement of substances only occurs in the horizontal direction and the electrochemical reaction occurring in the horizontal direction is uniform; the negative electrode diffusion process is ignored and the negative electrode potential is considered as zero; the electrode capacity of the positive and negative electrodes does not change during the reaction process; and the influence of gravity on the substances is ignored;

[0111] an acquisition module configured to acquire the diffusion coefficient D p of the positive electrode material corresponding to the liquid metal battery according to the battery 1-D simplified model;

[0112] a description module configured to describe the positive electrode diffusion process by using the Fick second law and the diffusion coefficient to obtain the positive electrode Li diffusion concentration and the ratio G(s) of the current density I(s), G(s) is used to describe the positive electrode dynamic performance, and s is a complex variable in Laplace transform;

[0113] a simplification module configured to simplify the ratio by using the Pade approximation partial differential equation to simulate the electrode diffusion process of the liquid metal battery, so as to obtain the electrode diffusion process model.

[0114] According to another aspect of the present application, there is provided an electronic device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the steps of the above method when executing the computer program.

[0115] Those skilled in the art will easily understand that the above description is only a preferred embodiment of the present application, and is not intended to limit the present application, and any modification, equivalent replacement and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A modeling method for the diffusion process of liquid metal battery electrodes based on the Pade approximation, characterized in that, include: S1: A simplified 1-D model of the battery is set up based on the layered structure characteristics of liquid metal batteries. The simplified 1-D model of the battery is set as follows: the movement of matter only occurs in the horizontal direction and the electrochemical reaction in the horizontal direction is uniform; the diffusion process of the negative electrode is ignored and the potential of the negative electrode is regarded as zero; the capacity of the positive and negative electrodes does not change during the reaction; and the influence of gravity on the matter is ignored. S2: For the simplified 1-D model of the battery, obtain the diffusion coefficient of the positive electrode material in the liquid metal battery. ; S3: The diffusion process of the cathode is described using Fick's second law and the diffusion coefficient to obtain the ratio of the cathode Li diffusion concentration to the current density, which is used to describe the dynamic performance of the cathode. S4: Simplify the ratio using the Pade approximation partial differential equation to simulate the electrode diffusion process of the liquid metal battery, thereby obtaining the electrode diffusion process model. S4 includes: S41: Obtaining the ratio transcendental function terms in s is the complex parameter variable in the Laplace transform; S42: Partial differential equations based on the Pade approximation utilize functions right Perform approximate simplification; , It is the numerator coefficient. These are the denominator coefficients, where N and M are integer terms; S43: Solve coefficient ; S41 includes: Will Substitute the ratio get ; ; It is a transcendental function term; Li diffusion concentration; Current density; A, F, L These are the positive electrode cross-sectional area, Faraday constant, and positive electrode length, respectively. S43 includes: targeting Using formulas Solve ; Regarding the rest With N and M fixed, during the initial population generation phase, k vectors are randomly generated based on a set range of initial values. Each vector consists of coefficients to be identified. The population evolution phase is divided into four parts: parent selection, gene crossover, gene mutation, and introduction of foreign individuals, which update and iterate the initial values. Iteration stops when the number of iterations exceeds a preset number. The individual with the smallest evaluation index in the last generation is selected as the optimal coefficient solution. The evaluation index is: ; Re represents the Euclidean distance between vectors, Re[] represents the real part of the function inside [ ], and Im[] represents the imaginary part of the function inside [ ].

2. The modeling method for the diffusion process of liquid metal battery electrodes based on the Pade approximation as described in claim 1, characterized in that, S2 includes: Since the negative electrode of the liquid metal battery, pure lithium, is considered to have zero potential, the measured open-circuit voltage is the equilibrium potential of the positive electrode; the diffusion coefficient is obtained by utilizing the relationship between battery voltage change and relaxation time.

3. The modeling method for the diffusion process of liquid metal battery electrodes based on the Pade approximation as described in claim 2, characterized in that, S2 includes: Using formula Calculate the diffusion coefficient ; in, Represents relaxation time. This refers to the number of moles; Represents the molar volume of the electrode material; Represents the electrode / electrolyte contact area; It is a voltage change caused by a pulse; It is the voltage change during constant current charging and discharging.

4. The modeling method for the diffusion process of liquid metal battery electrodes based on the Pade approximation as described in claim 1, characterized in that, S2 includes: S21: The cathode diffusion process is described using Fick's second law and the aforementioned diffusion coefficient to obtain the lithium concentration on the cathode surface. With current density The ratio; and obtain the average lithium concentration of the positive electrode. With current density The ratio; S22: Utilize Obtain the Li diffusion concentration With current density ratio , which are parameters used to describe the dynamic performance of the positive electrode.

5. The modeling method for the diffusion process of liquid metal battery electrodes based on the Pade approximation as described in claim 4, characterized in that, S21 includes: use Describe the cathode diffusion process and obtain the lithium concentration on the cathode surface by combining the boundary conditions of cathode diffusion. With current density The ratio: ; Using formula Characterizing the average lithium concentration of the cathode With current density ratio ; in, C p Indicates Li concentration. x Indicates correspondence x Axis position, t Indicates time, A These are the positive electrode cross-sectional areas, F It is Faraday's constant. L This is the length of the positive electrode.

6. A modeling device for the diffusion process of liquid metal battery electrodes based on the Pade approximation, characterized in that, For performing the modeling method according to any one of claims 1-5, comprising: The setting module is used to set a simplified 1-D model of the battery based on the layered structure characteristics of liquid metal batteries. The simplified 1-D model of the battery is set as follows: the movement of matter only occurs in the horizontal direction and the electrochemical reaction in the horizontal direction is uniform; the diffusion process of the negative electrode is ignored and the potential of the negative electrode is regarded as zero; the capacity of the positive and negative electrodes does not change during the reaction; and the influence of gravity on the matter is ignored. The acquisition module is used to obtain the diffusion coefficient of the positive electrode material in the liquid metal battery for the 1-D simplified model of the battery. ; The description module is used to describe the positive electrode diffusion process using Fick's second law and the diffusion coefficient to obtain the ratio of positive electrode Li diffusion concentration to current density, which is used to describe the dynamic performance of the positive electrode. The simplification module is used to simplify the ratio using the Pade approximation partial differential equation to simulate the electrode diffusion process of the liquid metal battery, thereby obtaining an electrode diffusion process model.

7. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.

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