Electrochemical model acquisition method and apparatus, terminal, and storage medium

Abstract

The present disclosure relates to the technical field of battery energy storage system modeling, and particularly relates to an electrochemical model acquisition method and device, a terminal and a storage medium. The electrochemical model acquisition method comprises: obtaining an initial electrochemical model corresponding to a target battery; determining a transfer function corresponding to the initial electrochemical model; and performing dimensionality upgrading on the initial electrochemical model according to the transfer function to obtain a target electrochemical model. The present disclosure can improve the accuracy of electrochemical model acquisition.

Description

Technical Field

[0001] This disclosure relates to the field of computer technology, and in particular to a method, apparatus, terminal and storage medium for obtaining an electrochemical model. Background Technology

[0002] With the development of science and technology and the widespread application of energy storage technology, people's lives and work have been enriched. The main energy storage methods can be divided into mechanical energy storage, electrochemical energy storage, and electromagnetic energy storage. Among them, electrochemical energy storage has the widest application range and the greatest development potential, currently dominated by lithium batteries. Electrochemical energy storage systems are far superior to other types of energy storage in terms of technological accumulation and advancement, featuring precise tracking, fast response speed, and bidirectional regulation capabilities. They can effectively solve the problem of power system frequency stability caused by a high proportion of clean energy generation during the energy transition.

[0003] Batteries play a crucial role in renewable energy generation, and lithium-ion batteries for energy storage are widely used in energy storage systems due to their high energy transfer efficiency, long lifespan, and low self-discharge rate. Mathematical modeling of batteries is a multidisciplinary and multi-field problem; accurate modeling is essential to accurately describe the external characteristics of energy storage batteries.

[0004] Therefore, improving the accuracy of obtaining electrochemical models corresponding to batteries has become a key focus of attention. Summary of the Invention

[0005] This disclosure provides a method, apparatus, terminal, and storage medium for obtaining electrochemical models, with the main objective of improving the accuracy of obtaining electrochemical models.

[0006] According to one aspect of this disclosure, a method for obtaining an electrochemical model is provided, comprising:

[0007] Obtain the initial electrochemical model corresponding to the target battery;

[0008] Determine the transfer function corresponding to the initial electrochemical model;

[0009] The initial electrochemical model is upgraded based on the transfer function to obtain the target electrochemical model.

[0010] Optionally, the step of increasing the dimensionality of the initial electrochemical model based on the transfer function to obtain the target electrochemical model includes:

[0011] The initial electrochemical model is upgraded in dimensionality based on the transfer function to obtain an upgraded transfer function model.

[0012] The target electrochemical model is obtained by parameter identification of the upgraded transfer function model.

[0013] Optionally, obtaining the initial electrochemical model corresponding to the target battery includes:

[0014] Based on the electrochemical mechanism, an initial electrochemical model governing equation is constructed, which includes the liquid phase concentration distribution equation, the liquid phase potential equation, the solid phase charge distribution equation, the solid phase material distribution equation, the Bar-Volt equation, the voltage output equation, and the terminal voltage equation.

[0015] Based on the governing equations of the initial electrochemical model, the initial electrochemical model corresponding to the target battery is determined.

[0016] Optionally, the transfer function includes a current density distribution transfer function, and determining the transfer function corresponding to the initial electrochemical model includes:

[0017] Based on the Bar-Voltage equation, determine the first solid-liquid phase potential difference equation;

[0018] Based on the liquid phase potential equation, determine the second solid-liquid phase potential difference equation;

[0019] The current density distribution transfer function is obtained by simultaneously solving the first solid-liquid phase potential difference equation and the second solid-liquid phase potential difference equation.

[0020] Optionally, the transfer function includes the electrolyte potential transfer function, and determining the transfer function corresponding to the initial electrochemical model includes:

[0021] Determine the electrolyte model corresponding to the initial electrochemical model;

[0022] Based on the electrolyte model and the liquid phase potential equation, the electrolyte potential transfer function corresponding to the initial electrochemical model is determined.

[0023] Optionally, the upgraded transfer function model includes an upgraded transfer function model of lithium ion concentration on the particle surface in the negative electrode region, an upgraded transfer function model of solid-state potential in the negative electrode region, and an upgraded transfer function model of internal state in the positive electrode region. The transfer function includes a transfer function of current density distribution in the positive electrode region and a transfer function of current density distribution in the negative electrode region. Upgrading the initial electrochemical model based on the transfer function to obtain the upgraded transfer function model includes:

[0024] Based on the current density distribution transfer function in the negative electrode region and the solid phase material distribution equation, the lithium ion concentration dimensionality transfer function model on the particle surface in the negative electrode region is determined.

[0025] Based on the current density distribution transfer function in the negative electrode region and the solid-phase charge distribution equation, the model of the solid-phase potential up-dimensional transfer function in the negative electrode region is determined.

[0026] Based on the current density distribution transfer function of the positive electrode region and the solid phase charge distribution equation, the state-level-up transfer function model of the positive electrode region is determined.

[0027] Optionally, the step of parameter identification of the upgraded transfer function model to obtain the target electrochemical model includes:

[0028] The target terminal voltage equation is determined based on the lithium ion concentration up-dimensional transfer function model on the particle surface of the negative electrode domain, the solid phase potential up-dimensional transfer function model of the negative electrode domain, and the internal state up-dimensional transfer function model of the positive electrode domain.

[0029] Obtain the first terminal voltage of the target battery at any given time and the second terminal voltage corresponding to the target terminal voltage equation;

[0030] If the first terminal voltage and the second terminal voltage satisfy the parameter identification conditions, then the upgraded transfer function model is determined to be the target electrochemical model;

[0031] If the first terminal voltage and the second terminal voltage do not meet the parameter identification conditions, then the model parameters corresponding to the upgraded transfer function model are adjusted until the first terminal voltage and the second terminal voltage meet the parameter identification conditions.

[0032] According to another aspect of this disclosure, an electrochemical model acquisition device is provided, comprising:

[0033] The model acquisition unit is used to acquire the initial electrochemical model corresponding to the target battery.

[0034] A function determination unit is used to determine the transfer function corresponding to the initial electrochemical model;

[0035] The model determination unit is used to increase the dimensionality of the initial electrochemical model based on the transfer function to obtain the target electrochemical model.

[0036] Optionally, when the model determination unit is used to increase the dimensionality of the initial electrochemical model based on the transfer function to obtain the target electrochemical model, it is specifically used for:

[0037] The initial electrochemical model is upgraded in dimensionality based on the transfer function to obtain an upgraded transfer function model.

[0038] The target electrochemical model is obtained by parameter identification of the upgraded transfer function model.

[0039] Optionally, when the model acquisition unit acquires the initial electrochemical model corresponding to the target battery, it is specifically used for:

[0040] Based on the electrochemical mechanism, an initial electrochemical model governing equation is constructed, which includes the liquid phase concentration distribution equation, the liquid phase potential equation, the solid phase charge distribution equation, the solid phase material distribution equation, the Bar-Volt equation, the voltage output equation, and the terminal voltage equation.

[0041] Based on the governing equations of the initial electrochemical model, the initial electrochemical model corresponding to the target battery is determined.

[0042] Optionally, the transfer function includes a current density distribution transfer function, and the function determination unit, when determining the transfer function corresponding to the initial electrochemical model, is specifically used for:

[0043] Based on the Bar-Voltage equation, determine the first solid-liquid phase potential difference equation;

[0044] Based on the liquid phase potential equation, determine the second solid-liquid phase potential difference equation;

[0045] The current density distribution transfer function is obtained by simultaneously solving the first solid-liquid phase potential difference equation and the second solid-liquid phase potential difference equation.

[0046] Optionally, the transfer function includes the electrolyte potential transfer function, and the function determination unit, when determining the transfer function corresponding to the initial electrochemical model, is specifically used for:

[0047] Determine the electrolyte model corresponding to the initial electrochemical model;

[0048] Based on the electrolyte model and the liquid phase potential equation, the electrolyte potential transfer function corresponding to the initial electrochemical model is determined.

[0049] Optionally, the upgraded transfer function model includes an upgraded transfer function model of lithium-ion concentration on the particle surface in the negative electrode domain, an upgraded transfer function model of solid-state potential in the negative electrode domain, and an upgraded transfer function model of internal state in the positive electrode domain. The transfer function includes a transfer function of current density distribution in the positive electrode domain and a transfer function of current density distribution in the negative electrode domain. The model determination unit is used to upgrade the initial electrochemical model according to the transfer function to obtain the upgraded transfer function model, specifically for:

[0050] Based on the current density distribution transfer function in the negative electrode region and the solid phase material distribution equation, the lithium ion concentration dimensionality transfer function model on the particle surface in the negative electrode region is determined.

[0051] Based on the current density distribution transfer function in the negative electrode region and the solid-phase charge distribution equation, the model of the solid-phase potential up-dimensional transfer function in the negative electrode region is determined.

[0052] Based on the current density distribution transfer function of the positive electrode region and the solid phase charge distribution equation, the state-level-up transfer function model of the positive electrode region is determined.

[0053] Optionally, when the model determination unit performs parameter identification on the upgraded transfer function model to obtain the target electrochemical model, it is specifically used for:

[0054] The target terminal voltage equation is determined based on the lithium ion concentration up-dimensional transfer function model on the particle surface of the negative electrode domain, the solid phase potential up-dimensional transfer function model of the negative electrode domain, and the internal state up-dimensional transfer function model of the positive electrode domain.

[0055] Obtain the first terminal voltage of the target battery at any given time and the second terminal voltage corresponding to the target terminal voltage equation;

[0056] If the first terminal voltage and the second terminal voltage satisfy the parameter identification conditions, then the upgraded transfer function model is determined to be the target electrochemical model;

[0057] If the first terminal voltage and the second terminal voltage do not meet the parameter identification conditions, then the model parameters corresponding to the upgraded transfer function model are adjusted until the first terminal voltage and the second terminal voltage meet the parameter identification conditions.

[0058] According to another aspect of this disclosure, a terminal is provided, comprising:

[0059] At least one processor; and

[0060] A memory communicatively connected to the at least one processor; wherein,

[0061] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in any one of the preceding aspects.

[0062] According to another aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are used to cause the computer to perform the method described in any one of the preceding aspects.

[0063] According to another aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method described in any one of the preceding aspects.

[0064] In one or more embodiments of this disclosure, an initial electrochemical model corresponding to the target battery is obtained; the transfer function corresponding to the initial electrochemical model is determined; and the initial electrochemical model is upgraded in dimensionality based on the transfer function to obtain the target electrochemical model. Therefore, by upgrading the initial electrochemical model based on the transfer function, the obtained target electrochemical model can reflect the state differences between particles, output near-experimental conditions at low temperatures, and improve the accuracy of electrochemical model acquisition.

[0065] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0066] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein:

[0067] Figure 1 A flowchart illustrating the first electrochemical model acquisition method provided in this disclosure is shown.

[0068] Figure 2 A flowchart illustrating the second electrochemical model acquisition method provided in this embodiment is shown.

[0069] Figure 3 This diagram illustrates a particle distribution along the electrode thickness direction according to an embodiment of the present disclosure.

[0070] Figure 4 This diagram illustrates a parameter identification process provided in an embodiment of the present disclosure.

[0071] Figure 5 This diagram illustrates the structure of an electrochemical model acquisition device provided in an embodiment of the present disclosure.

[0072] Figure 6 This is a block diagram of a terminal used to implement the electrochemical model acquisition method of the embodiments of this disclosure. Detailed Implementation

[0073] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0074] The present disclosure will now be described in detail with reference to specific embodiments.

[0075] In the first embodiment, such as Figure 1 As shown, Figure 1 The diagram illustrates a flowchart of a first electrochemical model acquisition method provided in this embodiment. This method can be implemented using a computer program and can run on an apparatus for performing electrochemical model acquisition. The computer program can be integrated into an application or run as a standalone utility application.

[0076] The electrochemical model acquisition device can be a terminal with electrochemical model acquisition capabilities, including but not limited to: wearable devices, handheld devices, personal computers, tablets, in-vehicle devices, smartphones, computing devices, or other processing devices connected to a wireless modem. In different networks, the terminal may be called by different names, such as: user equipment, access terminal, user unit, user station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication equipment, user agent or user device, cellular phone, cordless phone, personal digital assistant (PDA), 5G network, 4G network, 3G network, or terminals in future evolved networks.

[0077] Specifically, the method for obtaining this electrochemical model includes:

[0078] S101, Obtain the initial electrochemical model corresponding to the target battery;

[0079] According to some embodiments, the target battery refers to the battery that the terminal is targeting when acquiring an electrochemical model. The target battery does not specifically refer to a particular fixed battery. For example, the target battery could be an energy storage battery.

[0080] In some embodiments, the initial electrochemical model refers to the Doyle-Fuller-Newman (DFN) model. The DFN model is the foundation for the development of electrochemical mechanism models, but its calculations are complex and it is based on the assumption that all particles are in the same state. At low temperatures, the DFN model ignores the state differences between particles due to the thickness of the electrode, which leads to model failure.

[0081] It is easy to understand that when the terminal acquires the electrochemical model, the terminal can acquire the initial electrochemical model corresponding to the target battery.

[0082] S102, determine the transfer function corresponding to the initial electrochemical model;

[0083] In some embodiments, the transfer function is also called the system function, transfer function, or network function. The curve plotted by the transfer function is called the transfer curve. The transfer function is a mathematical representation used to fit or describe the relationship between the input and output of a model. The transfer function does not specifically refer to a single fixed function. For example, the transfer function includes, but is not limited to, the current density distribution transfer function.

[0084] It is easy to understand that when the terminal obtains the initial electrochemical model corresponding to the target battery, the terminal can determine the transfer function corresponding to the initial electrochemical model.

[0085] S103, the initial electrochemical model is upgraded in dimensionality based on the transfer function to obtain the target electrochemical model.

[0086] According to some embodiments, the target electrochemical model refers to the electrochemical model obtained by increasing the dimensionality of the initial electrochemical model based on the transfer function. This target electrochemical model is not specifically defined as a fixed model. For example, the target electrochemical model can change when the initial electrochemical model changes. It can also change when the transfer function changes.

[0087] In some embodiments, the target electrochemical model can be used for battery modeling and calculating battery state in the battery management system (BMS) or cloud platform of an energy storage power station.

[0088] It is easy to understand that when the terminal obtains the transfer function corresponding to the initial electrochemical model, the terminal can upgrade the dimensionality of the initial electrochemical model according to the transfer function to obtain the target electrochemical model.

[0089] In summary, the method provided in this disclosure obtains the initial electrochemical model corresponding to the target battery; determines the transfer function corresponding to the initial electrochemical model; and increases the dimensionality of the initial electrochemical model based on the transfer function to obtain the target electrochemical model. Therefore, by increasing the dimensionality of the initial electrochemical model based on the transfer function, the obtained target electrochemical model can reflect the state differences between particles, output near-experimental conditions at low temperatures, and improve the accuracy of electrochemical model acquisition. Simultaneously, the computational complexity of this target electrochemical model is low, which solves the problem of high computational complexity in DFN models.

[0090] Please see Figure 2 , Figure 2 This diagram illustrates a second electrochemical model acquisition method provided in an embodiment of the present disclosure. The method can be executed by a terminal. Specifically, the electrochemical model acquisition method includes:

[0091] S201, based on the electrochemical mechanism, construct the initial electrochemical model governing equations;

[0092] According to some embodiments, the initial electrochemical model governing equation refers to the governing equation corresponding to the initial electrochemical model. This initial electrochemical model governing equation does not specifically refer to a single fixed equation. It includes, but is not limited to, the liquid phase concentration distribution equation, the liquid phase potential equation, the solid phase charge distribution equation, the solid phase material distribution equation, the Bar-Volt equation, the voltage output equation, and the terminal voltage equation.

[0093] In some embodiments, Figure 3 This diagram illustrates a particle distribution along the electrode thickness direction according to an embodiment of the present disclosure. Figure 3 As shown, an x-axis is established from the outer side of the negative electrode region to the outer side of the positive electrode region. The electrolyte passes through the positive electrode region, the membrane, and the negative electrode region sequentially along the x-axis; where the negative electrode region is defined as 0 ≤ x ≤ L. n The diaphragm is L n ≤x≤L n + m The region corresponding to the positive electrode is L. n + m ≤x≤L n + m + p The subscript "n" represents the variable in the negative electrode, the subscript "m" represents the variable in the separator (sep), the subscript "p" represents the variable in the positive electrode, the subscript "s" represents the solid phase, the subscript "e" represents the solid phase, the superscript "surf" represents the surface, and c is the lithium ion concentration.

[0094] In some embodiments, such as Figure 2 As shown, the positive electrode region is a positive porous electrode, and the negative electrode region is a negative porous electrode. Both the positive and negative porous electrodes include spherical electrode particles. In the domain of the spherical electrode particles, R s,k Let k be the radius of the particle, where k ∈ {n = negative, p = positive}.

[0095] In some embodiments, Table (1) is a parameter table for the DFN model.

[0096]

[0097] Table (1)

[0098] According to some embodiments, in order to simplify the initial electrochemical model, before constructing the governing equations of the initial electrochemical model, the electrode solid phase is regarded as an equivalent single particle, and the state differences between particles are not considered due to the plate thickness. It is assumed that all particles are in the same state, that is, the particle current density of all particles is equal and directly proportional to the load current. The mathematical expression is as follows:

[0099]

[0100] Where j is the particle current density, a s Where is the electrode specific surface area, and I is the load current.

[0101] According to some embodiments, the mathematical expression of the liquid phase concentration distribution equation is as follows:

[0102]

[0103] Where, ε e The value represents the volume fraction of the electrolyte, c represents the lithium ion concentration, the subscript "e" indicates the liquid phase, the superscript "eff" indicates the effective phase, and t represents time. denoted as the lithium ion transfer number, and F as the Faraday constant.

[0104] In some embodiments, in, This represents the volume fraction of the electrolyte.

[0105] In some embodiments, It can be 0.363.

[0106] According to some embodiments, the mathematical expression of the liquid phase potential equation is as follows:

[0107]

[0108] Where φ represents electric potential, yes In short, R is the resistance and T is the preset time.

[0109] According to some embodiments, the mathematical expression of the solid-phase charge distribution equation is as follows:

[0110]

[0111] According to some embodiments, the mathematical expression of the solid phase material distribution equation is as follows:

[0112]

[0113] Where r is from 0 to the particle radius R s The coefficients between them.

[0114] According to some embodiments, the mathematical expression of the Butler-Volmer (BV) equation is as follows:

[0115]

[0116] Where i0 is the exchange current density, α aη is the positive electrode reaction conversion coefficient, η is the overpotential (i.e., the additional force required to overcome the surface reaction), and α is the positive electrode reaction conversion coefficient. c is the conversion coefficient of the negative electrode reaction.

[0117] In some embodiments, Among them, c s,max For the maximum lithium-ion concentration, c s,e The concentration of lithium ions on the surface of the solid particles is denoted as .

[0118] According to some embodiments, the mathematical expression of the voltage output equation is as follows:

[0119]

[0120] Where Ucell(t) is the output voltage, φ s (L,t) represents the positive current collector potential, φ s (0,t) represents the negative electrode current collector potential, R f It is the DC resistance of the membrane.

[0121] According to some embodiments, the mathematical expression of the terminal voltage equation is as follows:

[0122]

[0123] Among them, U ocp,k c is the open-circuit potential corresponding to electrode k. s,max,k η represents the maximum lithium-ion concentration corresponding to electrode k. k φ is the overpotential corresponding to electrode k. e (L,t) represents the positive electrode electrolyte potential, φ e (0,t) represents the potential of the negative electrode electrolyte.

[0124] It is easy to understand that when the terminal acquires an electrochemical model, it can construct the initial electrochemical model governing equations based on the electrochemical mechanism.

[0125] S202, Based on the governing equations of the initial electrochemical model, determine the initial electrochemical model corresponding to the target battery;

[0126] It is easy to understand that when the terminal obtains the initial electrochemical model governing equation, the terminal can determine the initial electrochemical model corresponding to the target battery based on the initial electrochemical model governing equation.

[0127] S203, determine the transfer function corresponding to the initial electrochemical model;

[0128] According to some embodiments, the transfer function includes, but is not limited to, the current density distribution transfer function and the electrolyte potential transfer function. The current density distribution transfer function includes, but is not limited to, the positive electrode domain current density distribution transfer function and the negative electrode domain current density distribution transfer function.

[0129] According to some embodiments, when the terminal determines the current density distribution transfer function corresponding to the initial electrochemical model, the terminal can first determine the first solid-liquid phase potential difference equation based on the Barton-Voltaire equation. Simultaneously, it can determine the second solid-liquid phase potential difference equation based on the liquid phase potential equation. Then, the first and second solid-liquid phase potential difference equations are solved simultaneously to obtain the current density distribution transfer function. Therefore, the externally loaded battery current I can be... app (s) Lithium-ion current density J at any z-position (plate thickness) in the negative electrode solid phase neg The correspondence between (z, s) is established and expressed by the transfer function.

[0130] In some embodiments, when the terminal determines the first solid-liquid phase potential difference equation according to the Bar-Voltage equation, the terminal can first substitute formula (6) into φ. s-e =φ s -φ e and overpotential equation η k =φ s，k -φ e，k -U ocp，k Then, the terminal can linearize the new reaction kinetic equation to obtain the following mathematical expression:

[0131]

[0132] Where j0 is the solid phase concentration c s The function, For the potential difference between the solid and liquid phases, c s，0 This represents the initial equilibrium volume-average concentration of lithium particles in the solid. R represents the molar concentration of lithium ions in the solid active material. film This represents the solid-liquid contact resistance.

[0133] According to formula (9), we can obtain and Relationship:

[0134]

[0135] Among them, R ct For the reaction polarization linearization resistance of the Barton-Voltaire equation, R ct =RT / j0F 2 .

[0136] Secondly, the terminal can define the solid-liquid interphase impedance R according to the following mathematical expression. s，e :

[0137] R s，e =R ct +R film(11)

[0138] Therefore, the terminal can determine the mathematical expression of the first solid-liquid phase potential difference equation as follows:

[0139]

[0140] Therefore, the terminal can obtain the following mathematical expression based on formula (10):

[0141] F(R ct +R film )j=φ s -φ e -U ocp (c s，e (13)

[0142] Finally, the terminal can obtain the relationship between the overpotential and the charge transfer resistance of the linearized model:

[0143] FR ct j = φ s -φ e -U ocp (c s，e )-FR film j=η (14)

[0144] The relationship between the overpotential and charge transfer resistance in this linearized model can model and characterize the voltage drop beyond the open-circuit potential between the solid and the electrolyte.

[0145] In some embodiments, when the terminal determines the second solid-liquid phase potential difference equation based on the liquid phase potential equation, the terminal can standardize the equation (3), that is, convert x into a standardized variable z, to obtain the following mathematical expression:

[0146]

[0147] The terminal can also obtain the boundary conditions under the new dimensions:

[0148]

[0149]

[0150] Among them, i app This represents the external load current, measured in amperes (A).

[0151] Secondly, the electrolyte concentration c in the liquid phase charge conservation can be ignored at the terminal. e The influence of the (x, t) term yields:

[0152]

[0153] The boundary conditions corresponding to formula (16) are:

[0154]

[0155] Finally, the second solid-liquid phase potential difference equation can be obtained at the terminal:

[0156]

[0157] The boundary conditions corresponding to formula (18) are:

[0158]

[0159] At the same time, for ease of expression, a dimensionless variable v can be defined. neg (s), where the superscript "neg" indicates that the transfer function applies to the negative pole region. The unlabeled 's' represents the Laplace operator. In the remaining part describing the negative pole transfer function, v... neg (s) is abbreviated as v(s); where,

[0160]

[0161] In some embodiments, when the terminal solves the first solid-liquid phase potential difference equation and the second solid-liquid phase potential difference equation simultaneously to obtain the current density distribution transfer function, the terminal can determine the relevant information based on formulas (12) and (19). Homogeneous partial differential equations:

[0162]

[0163] The general solution of formula (20) is:

[0164]

[0165] Where K1 and K2 are the unknowns to be solved.

[0166] Next, based on the boundary conditions at z=1, we can obtain K1:

[0167]

[0168] Meanwhile, the boundary condition at z=0 of the root can be obtained as K2:

[0169]

[0170] Therefore, by substituting the values ​​of K1 and K2 into formula (21), the terminal can obtain... For I app The transfer function of (s):

[0171]

[0172] Finally, the terminal can obtain the transfer function of the negative pole current density distribution according to formula (24):

[0173]

[0174] According to some embodiments, when the terminal determines the transfer function corresponding to the initial electrochemical model, the terminal can determine the electrolyte model corresponding to the initial electrochemical model, and determine the electrolyte potential transfer function corresponding to the initial electrochemical model based on the electrolyte model and the liquid phase potential equation.

[0175] In some embodiments, when the terminal determines the electrolyte model corresponding to the initial electrochemical model, the terminal can perform a Laplace transform on the mass conservation in the electrolyte to obtain:

[0176]

[0177]

[0178]

[0179] Formulas (26), (27), and (28) satisfy the following conditions:

[0180]

[0181]

[0182] C e，m ((L n +L m )-)=C e，p ((L n +L m ) + )

[0183]

[0184]

[0185] As can be seen from formulas (26), (27), and (28), after the Laplace transform, the conservation of matter in the electrolyte is a standard parabolic partial differential equation with homogeneous boundary conditions.

[0186] Next, the terminal can calculate the transfer function of the negative electrode at x = 0:

[0187]

[0188]

[0189] Simultaneously, the terminal can calculate the lithium concentration transfer function at x = L:

[0190]

[0191]

[0192] Next, the terminal can use the Padé approximation to transform the transfer function of lithium concentration at x = 0 for the negative electrode and x = L for the positive electrode into a reduced-order rational expression. Specifically, firstly, the terminal can linearize the definition... Next, the terminal can perform Taylor expansion on it. get:

[0193]

[0194] Among them, c e，0 It is the initial concentration of the electrolyte.

[0195] Next, the terminal can integrate equation (3) with respect to x to obtain the ionic current i flowing through the electrolyte. e Definition:

[0196]

[0197] Therefore, the terminal can obtain the new mathematical expression corresponding to formula (3):

[0198]

[0199] Secondly, the terminal can integrate formula (33) from 0 to x to obtain:

[0200]

[0201] Where, φ e The calculation formula is as follows:

[0202]

[0203] Finally, the terminal can determine the electrolyte potential transfer function, that is, the transfer function of the electrolyte potential at x = L, as follows:

[0204]

[0205] It is easy to understand that when the terminal obtains the initial electrochemical model corresponding to the target battery, the terminal can determine the transfer function corresponding to the initial electrochemical model.

[0206] S204, the initial electrochemical model is upgraded based on the transfer function to obtain the upgraded transfer function model;

[0207] According to some embodiments, the upgraded transfer function model includes, but is not limited to, the upgraded transfer function model of lithium ion concentration on the particle surface in the negative electrode region, the upgraded transfer function model of solid-state potential in the negative electrode region, and the upgraded transfer function model of internal state in the positive electrode region.

[0208] In some embodiments, when the terminal upgrades the initial electrochemical model based on the transfer function to obtain an upgraded transfer function model, the terminal can determine the upgraded transfer function model of lithium ion concentration on the particle surface in the negative electrode region based on the negative electrode region current density distribution transfer function and the solid phase material distribution equation; determine the upgraded transfer function model of solid phase potential in the negative electrode region based on the negative electrode region current density distribution transfer function and the solid phase charge distribution equation; and determine the upgraded transfer function model of the internal state in the positive electrode region based on the positive electrode region current density distribution transfer function and the solid phase charge distribution equation.

[0209] According to some embodiments, when the terminal determines the dimensional transfer function model of lithium ion concentration on the particle surface in the negative electrode region based on the negative electrode region current density distribution transfer function and the solid phase material distribution equation, the terminal can first perform a Laplace transform on formula (5) to obtain the surface concentration of the solid phase active material particles at position z. The transfer function for J(z, s). Then, the terminal can determine the surface concentration of the solid-phase active material particles at position z. For the transfer function of J(z, s) and Equation (25), we get For I app The transfer function of (s):

[0210]

[0211] Next, the terminal can expand formula (37) to obtain the transfer function model of lithium ion concentration on the particle surface in the negative electrode region:

[0212]

[0213] According to some embodiments, when the terminal determines the upgraded transfer function model of the solid-state potential in the negative electrode domain based on the transfer function of the current density distribution in the negative electrode domain and the solid-state charge distribution equation, firstly, in order to obtain the potential of the solid-state potential in the negative electrode domain φ, s (z, t), the terminal needs to integrate z in formula (34) twice to determine the negative electrode solid-phase potential. The second-order partial differential equation with respect to j(z,t) is as follows:

[0214]

[0215] Next, the terminal can define the current i passing through the solid-phase active material. s , Therefore, we get:

[0216]

[0217] Secondly, the terminal can change the dimensions to make z = x / L, thus obtaining:

[0218]

[0219] Rearranging formula (41), we get:

[0220]

[0221] Because i s (0, t) = i app (t) / (ε s A) and i s (1, t) = 0. To obtain the solid-state potential in transfer function form, it is necessary to derive the average current I. s The transfer functions of (z, s) and J(z, s) can be used to obtain the differential equation by performing a Laplace transform on equation (42):

[0222]

[0223] Next, the terminal can perform integral calculation I on J(z, s) from 0 to z. s The expression for (z, s):

[0224]

[0225] Therefore, the terminal can substitute the negative polarity current density distribution transfer function, i.e., formula (25), into formula (44) to obtain I. s The transfer function of (z, s):

[0226]

[0227] Then, the terminal can perform a Laplace transform on formula (40) and substitute it into formula (45) to calculate φ. s (z, t), we get:

[0228]

[0229] Next, the terminal can apply formula (46) from 0 to z to I. s The expression for integrating (z, s):

[0230]

[0231] Finally, the terminal can define the voltage drop across the plate of the solid-state potential. The potential difference in the negative electrode solid phase region is obtained. For the transfer function of the applied current, that is, the upgraded transfer function model of the solid-state potential in the negative electrode domain:

[0232]

[0233] According to some embodiments, when the terminal determines the upgraded transfer function model of the internal state of the positive electrode domain based on the current density distribution transfer function of the positive electrode domain and the solid-state charge distribution equation, the steps are similar to the process of obtaining the upgraded transfer function model of the solid-state potential of the negative electrode domain. First, the terminal can determine the current density distribution transfer function of the positive electrode domain:

[0234]

[0235] in,

[0236]

[0237]

[0238] Next, the terminal can use formulas Obtain the actual lithium-ion concentration equivalent of the active material in the solid phase.

[0239] Ultimately, the terminal can obtain the upgraded transfer function model of the internal state of the positive pole domain:

[0240]

[0241] Similar to the process of obtaining the upgraded transfer function model of the solid-state potential in the negative electrode domain, we can obtain:

[0242]

[0243] It is easy to understand that when the terminal determines the transfer function corresponding to the initial electrochemical model, the terminal can increase the dimensionality of the initial electrochemical model based on the transfer function to obtain an increased-dimensional transfer function model.

[0244] S205, parameter identification is performed on the upgraded transfer function model to obtain the target electrochemical model.

[0245] According to some embodiments, when the terminal performs parameter identification on the upgraded transfer function model to obtain the target electrochemical model, firstly, the terminal can determine the target terminal voltage equation based on the upgraded transfer function model of lithium ion concentration on the particle surface of the negative electrode domain, the upgraded transfer function model of solid-state potential in the negative electrode domain, and the upgraded transfer function model of internal state in the positive electrode domain. Next, the terminal can obtain the first terminal voltage corresponding to the target battery at any given time and the second terminal voltage corresponding to the target terminal voltage equation. If the terminal determines that the first terminal voltage and the second terminal voltage satisfy the parameter identification conditions, then the terminal can determine the upgraded transfer function model as the target electrochemical model. If the terminal determines that the first terminal voltage and the second terminal voltage do not satisfy the parameter identification conditions, then the terminal can adjust the model parameters corresponding to the upgraded transfer function model until the first terminal voltage and the second terminal voltage satisfy the parameter identification conditions.

[0246] In some embodiments, when the terminal determines the target terminal voltage equation based on the lithium-ion concentration up-dimensional transfer function model of the negative electrode region particle surface, the solid-phase potential up-dimensional transfer function model of the negative electrode region, and the internal state up-dimensional transfer function model of the positive electrode region, the terminal can obtain the following mathematical expression:

[0247]

[0248] in, The positive solid-phase reference potential, The negative electrode solid-phase reference potential, This represents the lithium-ion concentration at the positive electrode current collector. η represents the lithium-ion concentration at the negative electrode current collector. pos (0, t) is the overpotential at the positive current collector, η neg (0, t) represents the overpotential at the negative electrode current collector. This represents the liquid phase potential at the positive current collector. R is the liquid phase potential at the negative electrode current collector. f It is a DC resistance.

[0249] According to some embodiments, when the terminal obtains the upgraded transfer function model, the terminal can take the operating condition data at time t and use an intelligent algorithm (GA) to identify the parameters of the upgraded transfer function model. Figure 4 This diagram illustrates a parameter identification process according to an embodiment of the present disclosure. Figure 4 As shown, when the terminal obtains the upgraded transfer function model, it can take the operating condition data corresponding to the target battery at time t to obtain the first terminal voltage U. Simultaneously, the terminal can input a preset current value into the upgraded transfer function model to obtain the second terminal voltage Um. Then, the terminal can input the first terminal voltage U and the second terminal voltage Um into the objective function to obtain the voltage error between the first terminal voltage U and the second terminal voltage Um: e(θ) = (U...m -U) 2 If the voltage error meets the parameter identification conditions, the terminal can determine the upgraded transfer function model as the target electrochemical model and terminate the parameter identification process. If the voltage error does not meet the parameter identification conditions, the terminal can adjust the model parameter θ corresponding to the upgraded transfer function model according to the identification algorithm until the voltage error meets the parameter identification conditions.

[0250] In some embodiments, the model parameter θ includes, but is not limited to, all parameters involved in formulas (1) to (54).

[0251] In some embodiments, the parameter identification condition does not specifically refer to a fixed condition. For example, the parameter identification condition can be that the voltage error is less than an error threshold ε. The error threshold does not specifically refer to a fixed threshold. For example, the error threshold can change when a threshold modification instruction for the error threshold is received.

[0252] It is easy to understand that when the terminal obtains the upgraded transfer function model, it can perform parameter identification on the upgraded transfer function model to obtain the target electrochemical model. Unlike the models of a single electrode or a point on an electrode in related technologies, the target electrochemical model obtained in this embodiment is a new lithium-ion concentration C with a differential distribution in the electrode thickness dimension. s，e (z, t), overpotential η pos (z,t) and η neg (z, t), and the corresponding new U ocp (z, c) s，e The model.

[0253] In summary, the method provided in this disclosure constructs an initial electrochemical model governing equation based on electrochemical mechanisms. Based on this equation, it determines the initial electrochemical model corresponding to the target battery, identifies the transfer function corresponding to the initial electrochemical model, and then upgrades the initial electrochemical model using the transfer function to obtain an upgraded transfer function model. Finally, it performs parameter identification on the upgraded transfer function model to obtain the target electrochemical model. Therefore, by upgrading the initial electrochemical model based on the transfer function and refining the model structure through parameter identification, the obtained target electrochemical model can reflect the state differences between particles, output near-experimental conditions at low temperatures, prevent model inaccuracies at low temperatures, and obtain a model that more closely resembles the energy storage battery under experimental conditions. Furthermore, it reduces the likelihood of model failure under extreme conditions, thereby improving the accuracy of the electrochemical model acquisition. Simultaneously, the computational complexity of this target electrochemical model is low, solving the problem of high computational complexity in DFN models and facilitating parameter identification.

[0254] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in the technical solution disclosed herein comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0255] The following are embodiments of the apparatus disclosed herein, which can be used to execute embodiments of the method disclosed herein. For details not disclosed in the apparatus embodiments of this disclosure, please refer to the embodiments of the method disclosed herein.

[0256] Please see Figure 5 This illustration shows a schematic diagram of an electrochemical model acquisition device provided in an embodiment of the present disclosure. The electrochemical model acquisition device can be implemented as all or part of a device through software, hardware, or a combination of both. The electrochemical model acquisition device 500 includes a model acquisition unit 501, a function determination unit 502, and a model determination unit 503, wherein:

[0257] The model acquisition unit 501 is used to acquire the initial electrochemical model corresponding to the target battery.

[0258] Function determination unit 502 is used to determine the transfer function corresponding to the initial electrochemical model;

[0259] The model determination unit 503 is used to increase the dimensionality of the initial electrochemical model based on the transfer function to obtain the target electrochemical model.

[0260] Optionally, the model determination unit 503 is used to increase the dimensionality of the initial electrochemical model based on the transfer function to obtain the target electrochemical model, specifically for:

[0261] The initial electrochemical model is upgraded in dimensionality based on the transfer function to obtain an upgraded transfer function model.

[0262] The parameters of the upgraded transfer function model are identified to obtain the target electrochemical model.

[0263] Optionally, when the model acquisition unit 501 is used to acquire the initial electrochemical model corresponding to the target battery, it is specifically used for:

[0264] Based on the electrochemical mechanism, an initial electrochemical model governing equation was constructed, which includes the liquid phase concentration distribution equation, liquid phase potential equation, solid phase charge distribution equation, solid phase material distribution equation, Bar-V equation, voltage output equation, and terminal voltage equation.

[0265] Based on the governing equations of the initial electrochemical model, the initial electrochemical model corresponding to the target battery is determined.

[0266] Optionally, the transfer function includes the current density distribution transfer function. When the function determination unit 502 is used to determine the transfer function corresponding to the initial electrochemical model, it is specifically used for:

[0267] Based on the Barton-Voltaire equation, determine the first solid-liquid phase potential difference equation;

[0268] Based on the liquid phase potential equation, determine the second solid-liquid phase potential difference equation;

[0269] The current density distribution transfer function is obtained by simultaneously solving the first solid-liquid phase potential difference equation and the second solid-liquid phase potential difference equation.

[0270] Optionally, the transfer function includes the electrolyte potential transfer function. When the function determination unit 502 is used to determine the transfer function corresponding to the initial electrochemical model, it is specifically used for:

[0271] Determine the electrolyte model corresponding to the initial electrochemical model;

[0272] Based on the electrolyte model and the liquid phase potential equation, the electrolyte potential transfer function corresponding to the initial electrochemical model is determined.

[0273] Optionally, the upgraded transfer function model includes an upgraded transfer function model of lithium-ion concentration on the particle surface in the negative electrode region, an upgraded transfer function model of solid-state potential in the negative electrode region, and an upgraded transfer function model of internal state in the positive electrode region. The transfer function includes the transfer function of current density distribution in the positive electrode region and the transfer function of current density distribution in the negative electrode region. The model determination unit 503 is used to upgrade the initial electrochemical model according to the transfer function. When obtaining the upgraded transfer function model, it is specifically used for:

[0274] Based on the transfer function of current density distribution in the negative electrode region and the solid phase material distribution equation, a model for the dimensional transfer function of lithium ion concentration on the particle surface in the negative electrode region is determined.

[0275] Based on the transfer function of current density distribution in the negative electrode region and the solid-phase charge distribution equation, the model of the dimension-upgrading transfer function of solid-phase potential in the negative electrode region is determined.

[0276] Based on the current density distribution transfer function in the positive electrode region and the solid-phase charge distribution equation, the state-upgrading transfer function model inside the positive electrode region is determined.

[0277] Optionally, the model determination unit 503 is used to perform parameter identification on the upgraded transfer function model to obtain the target electrochemical model, specifically for:

[0278] The target terminal voltage equation is determined based on the lithium ion concentration up-dimensional transfer function model on the particle surface of the negative electrode domain, the solid phase potential up-dimensional transfer function model of the negative electrode domain, and the internal state up-dimensional transfer function model of the positive electrode domain.

[0279] Obtain the first terminal voltage of the target battery at any given time and the second terminal voltage corresponding to the target terminal voltage equation;

[0280] If the first terminal voltage and the second terminal voltage satisfy the parameter identification conditions, then the upgraded transfer function model is determined as the target electrochemical model.

[0281] If the first terminal voltage and the second terminal voltage do not meet the parameter identification conditions, then adjust the model parameters corresponding to the upgraded transfer function model until the first terminal voltage and the second terminal voltage meet the parameter identification conditions.

[0282] It should be noted that the electrochemical model acquisition device provided in the above embodiments is only illustrated by the division of the above functional modules when performing the electrochemical model acquisition method. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the electrochemical model acquisition device and the electrochemical model acquisition method embodiments provided in the above embodiments belong to the same concept, and the implementation process is detailed in the method embodiments, which will not be repeated here.

[0283] In summary, the apparatus provided in this embodiment acquires an initial electrochemical model corresponding to the target battery through a model acquisition unit; a function determination unit determines the transfer function corresponding to the initial electrochemical model; and the model determination unit increases the dimensionality of the initial electrochemical model based on the transfer function to obtain the target electrochemical model. Therefore, by increasing the dimensionality of the initial electrochemical model based on the transfer function, the obtained target electrochemical model can reflect the state differences between particles, output near-experimental conditions at low temperatures, and improve the accuracy of electrochemical model acquisition. Simultaneously, the computational load of this target electrochemical model is small, which solves the problem of the large computational load of the DFN model.

[0284] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in the technical solution disclosed herein comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0285] According to embodiments of this disclosure, this disclosure also provides a terminal, a readable storage medium, and a computer program product.

[0286] Figure 6 A schematic block diagram of an example terminal 600 that can be used to implement embodiments of the present disclosure is shown. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0287] like Figure 6As shown, terminal 600 includes a computing unit 601, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 602 or a computer program loaded from storage unit 608 into random access memory (RAM) 603. RAM 603 may also store various programs and data required for the operation of terminal 600. The computing unit 601, ROM 602, and RAM 603 are interconnected via bus 604. Input / output (I / O) interface 605 is also connected to bus 604.

[0288] Multiple components in terminal 600 are connected to I / O interface 605, including: input unit 606, such as keyboard, mouse, etc.; output unit 607, such as various types of displays, speakers, etc.; storage unit 608, such as disk, optical disk, etc.; and communication unit 609, such as network card, modem, wireless transceiver, etc. Communication unit 609 allows terminal 600 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0289] The computing unit 601 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as the electrochemical model acquisition method. For example, in some embodiments, the electrochemical model acquisition method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on terminal 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into RAM 603 and executed by the computing unit 601, one or more steps of the electrochemical model acquisition method described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the electrochemical model acquisition method by any other suitable means (e.g., by means of firmware).

[0290] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0291] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0292] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0293] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0294] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), the Internet, and blockchain networks.

[0295] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service ecosystem, addressing the shortcomings of traditional physical hosts and VPS (Virtual Private Server, or simply "VPS") services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0296] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0297] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for obtaining an electrochemical model, characterized in that, include: Obtain the initial electrochemical model corresponding to the target battery; Determine the transfer function corresponding to the initial electrochemical model; The initial electrochemical model is upgraded in dimensionality based on the transfer function to obtain the target electrochemical model. The step of increasing the dimensionality of the initial electrochemical model based on the transfer function to obtain the target electrochemical model includes: The initial electrochemical model is upgraded in dimensionality based on the transfer function to obtain an upgraded transfer function model. The target electrochemical model is obtained by performing parameter identification on the upgraded transfer function model. The upgraded transfer function model includes an upgraded transfer function model for lithium-ion concentration on the particle surface in the negative electrode region, an upgraded transfer function model for solid-state potential in the negative electrode region, and an upgraded transfer function model for the internal state in the positive electrode region. The transfer function includes a transfer function for current density distribution in the positive electrode region and a transfer function for current density distribution in the negative electrode region. Upgrading the initial electrochemical model based on the transfer function to obtain the upgraded transfer function model includes: Based on the current density distribution transfer function in the negative electrode region and the solid phase material distribution equation, the lithium ion concentration dimensionality transfer function model on the particle surface in the negative electrode region is determined. Based on the current density distribution transfer function and solid-phase charge distribution equation in the negative electrode domain, the model of the solid-phase potential up-dimensional transfer function in the negative electrode domain is determined. Based on the current density distribution transfer function of the positive electrode domain and the solid phase charge distribution equation, determine the state-level transfer function model inside the positive electrode domain; The parameter identification of the upgraded transfer function model to obtain the target electrochemical model includes: The target terminal voltage equation is determined based on the lithium ion concentration up-dimensional transfer function model on the particle surface of the negative electrode domain, the solid phase potential up-dimensional transfer function model of the negative electrode domain, and the internal state up-dimensional transfer function model of the positive electrode domain. Obtain the first terminal voltage of the target battery at any given time and the second terminal voltage corresponding to the target terminal voltage equation; If the first terminal voltage and the second terminal voltage satisfy the parameter identification conditions, then the upgraded transfer function model is determined to be the target electrochemical model; If the first terminal voltage and the second terminal voltage do not meet the parameter identification conditions, then the model parameters corresponding to the upgraded transfer function model are adjusted until the first terminal voltage and the second terminal voltage meet the parameter identification conditions.

2. The method according to claim 1, characterized in that, The process of obtaining the initial electrochemical model corresponding to the target battery includes: Based on the electrochemical mechanism, an initial electrochemical model governing equation is constructed, which includes the liquid phase concentration distribution equation, the liquid phase potential equation, the solid phase charge distribution equation, the solid phase material distribution equation, the Bar-Volt equation, the voltage output equation, and the terminal voltage equation. Based on the governing equations of the initial electrochemical model, the initial electrochemical model corresponding to the target battery is determined.

3. The method according to claim 2, characterized in that, The transfer function includes a current density distribution transfer function, and determining the transfer function corresponding to the initial electrochemical model includes: Based on the Bar-Voltage equation, determine the first solid-liquid phase potential difference equation; Based on the liquid phase potential equation, determine the second solid-liquid phase potential difference equation; The current density distribution transfer function is obtained by simultaneously solving the first solid-liquid phase potential difference equation and the second solid-liquid phase potential difference equation.

4. The method according to claim 2, characterized in that, The transfer function includes the electrolyte potential transfer function, and determining the transfer function corresponding to the initial electrochemical model includes: Determine the electrolyte model corresponding to the initial electrochemical model; Based on the electrolyte model and the liquid phase potential equation, the electrolyte potential transfer function corresponding to the initial electrochemical model is determined.

5. An electrochemical model acquisition device, characterized in that, include: The model acquisition unit is used to acquire the initial electrochemical model corresponding to the target battery. A function determination unit is used to determine the transfer function corresponding to the initial electrochemical model; The model determination unit is used to increase the dimensionality of the initial electrochemical model according to the transfer function to obtain the target electrochemical model. The model determination unit is used to increase the dimensionality of the initial electrochemical model based on the transfer function to obtain an increased-dimensional transfer function model. The target electrochemical model is obtained by performing parameter identification on the upgraded transfer function model. The upgraded transfer function model includes an upgraded transfer function model for lithium-ion concentration on the particle surface in the negative electrode region, an upgraded transfer function model for solid-state potential in the negative electrode region, and an upgraded transfer function model for the internal state in the positive electrode region. The transfer function includes a transfer function for current density distribution in the positive electrode region and a transfer function for current density distribution in the negative electrode region. Upgrading the initial electrochemical model based on the transfer function to obtain the upgraded transfer function model includes: Based on the current density distribution transfer function in the negative electrode region and the solid phase material distribution equation, the lithium ion concentration dimensionality transfer function model on the particle surface in the negative electrode region is determined. Based on the current density distribution transfer function and solid-phase charge distribution equation in the negative electrode domain, the model of the solid-phase potential up-dimensional transfer function in the negative electrode domain is determined. Based on the current density distribution transfer function of the positive electrode domain and the solid phase charge distribution equation, determine the state-level transfer function model inside the positive electrode domain; The parameter identification of the upgraded transfer function model to obtain the target electrochemical model includes: The target terminal voltage equation is determined based on the lithium ion concentration up-dimensional transfer function model on the particle surface of the negative electrode domain, the solid phase potential up-dimensional transfer function model of the negative electrode domain, and the internal state up-dimensional transfer function model of the positive electrode domain. Obtain the first terminal voltage of the target battery at any given time and the second terminal voltage corresponding to the target terminal voltage equation; If the first terminal voltage and the second terminal voltage satisfy the parameter identification conditions, then the upgraded transfer function model is determined to be the target electrochemical model; If the first terminal voltage and the second terminal voltage do not meet the parameter identification conditions, then the model parameters corresponding to the upgraded transfer function model are adjusted until the first terminal voltage and the second terminal voltage meet the parameter identification conditions.

6. A terminal, comprising: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-4.

7. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-4.

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