Battery simulation method, parameter identification method, curve generation method and device

Abstract

The invention provides a battery simulation method, a parameter identification method and a curve generation method and device. The method comprises the following steps: acquiring parameter information of a battery in the thickness direction and the density of current flowing into the battery; and performing simulation based on the battery simulation model according to the parameter information and the current density to obtain a simulation result of the battery. Wherein the simulation result comprises the distribution condition of the overpotential, the battery simulation model comprises a transmission line model, and the transmission line model is used for simulating the distribution condition of the overpotential; the transmission line model comprises equivalent circuits of particles corresponding to the positive electrode and the negative electrode of the battery based on single particle hypothesis. According to the embodiment of the invention, the transmission line model based on the single-particle hypothesis is used for simulating the overpotential distribution condition of the battery, and the simulation precision is improved under the condition that the calculated amount is slightly increased.

Description

Technical Field

[0001] The present application relates to the technical field of batteries, and in particular, to a battery simulation method, a parameter identification method, a curve generation method and a device. Background Art

[0002] Batteries represented by lithium-ion batteries have been widely used as energy storage carriers, such as mobile phones, laptop computers, medical devices, electric vehicles, energy storage power stations, signal base stations, etc. In order to ensure the safe and efficient operation of the battery, a battery management system (BMS) is generally equipped to manage the battery, such as state estimation, fault diagnosis, and charge equalization.

[0003] At present, many BMSs adopt model-based control technologies, which require the establishment of a simulation model for the controlled battery. The commonly used simulation model of lithium-ion batteries is the single particle model with electrolyte (SPMe), and the calculation accuracy of SPMe is relatively low. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to provide a battery simulation method, a parameter identification method, a curve generation method and a device, so as to improve the accuracy of battery simulation.

[0005] In a first aspect, the embodiments of the present application provide a battery simulation method, including:

[0006] Obtain parameter information of the battery in the thickness direction and the current density flowing into the battery; based on the parameter information and the current density, perform simulation based on the battery simulation model to obtain the simulation result of the battery.

[0007] Among them, the simulation result includes the distribution of overpotential, and the battery simulation model includes a transmission line model, and the transmission line model is used to simulate the distribution of overpotential; the transmission line model includes equivalent circuits of particles respectively corresponding to the positive electrode and the negative electrode of the battery constructed based on the single particle hypothesis.

[0008] The embodiments of the present application use a transmission line model based on the single particle hypothesis to simulate the overpotential distribution of the battery, and improve the simulation accuracy with less increase in the amount of calculation.

[0009] In any embodiment, the equivalent circuit includes a negative electrode mesh circuit; the negative electrode mesh circuit includes a plurality of parallel first sub-mesh circuits; each first sub-mesh circuit includes a first solid-phase resistance, a first liquid-phase resistance and a first charge transfer resistance;

[0010] Based on the parameter information and the current density, perform simulation based on the transmission line model to obtain the simulation result of the battery, including:

[0011] Calculate the first solid-phase resistance, the first charge-transfer resistance, and the electrode particle equilibrium voltage of each first sub-mesh circuit according to the parameter information corresponding to the battery negative electrode; calculate the first liquid-phase resistance according to the parameter information and the current density;

[0012] Construct the first mesh equation corresponding to each first sub-mesh circuit according to the first solid-phase resistance, the first liquid-phase resistance, the first charge-transfer resistance, and the first electrode particle equilibrium voltage;

[0013] Calculate the first charge-transfer current corresponding to each first sub-mesh circuit based on each first mesh equation;

[0014] Calculate the first overpotential of the corresponding mesh according to the first charge-transfer current.

[0015] In the embodiment of the present application, by equivalenting the negative electrode of the battery into multiple first sub-mesh circuits and solving the first charge-transfer current on each first sub-mesh circuit, the first overpotential at each position of the battery negative electrode can be obtained, thereby improving the accuracy of calculating the first overpotential.

[0016] In any embodiment, calculating the first overpotential of the corresponding mesh according to the first charge-transfer current includes:

[0017] Substitute the first charge-transfer current into the Butler-Volmer equation to calculate the first overpotential.

[0018] In the embodiment of the present application, the first overpotential is calculated by substituting the first charge-transfer current into the Butler-Volmer equation. Compared with the overpotential calculated by the single-particle model, the method of the embodiment of the present application improves the accuracy of overpotential calculation.

[0019] In any embodiment, calculating the first solid-phase resistance according to the parameter information corresponding to the battery negative electrode includes:

[0020] Calculate the first solid-phase resistance according to the grid size of the battery negative electrode and the conductivity of the negative electrode plate; the grid size is obtained by dividing the battery negative electrode in the thickness direction.

[0021] In the embodiment of the present application, the first solid-phase resistance in each sub-mesh circuit is calculated by the mesh method, providing a data basis for subsequent calculation of the overpotential corresponding to the sub-mesh circuit.

[0022] In any embodiment, calculating the first electrode particle equilibrium voltage according to the parameter information corresponding to the battery negative electrode includes:

[0023] Calculate the solid-phase lithium-ion concentration according to the solid-phase lithium-ion diffusion coefficient;

[0024] Look up the table according to the solid-phase lithium-ion concentration to obtain the first electrode particle equilibrium voltage.

[0025] In the embodiments of the present application, the solid-phase lithium-ion concentration is obtained by calculating the solid-phase lithium-ion diffusion coefficient, and the equilibrium voltage of the first electrode particles is obtained based on a look-up table, providing a data basis for subsequent calculation of the overpotential.

[0026] In any embodiment, calculating the first liquid-phase resistance according to the parameter information corresponding to the battery negative electrode and the current density includes:

[0027] Calculating the local volumetric current density based on the current density and the dimension in the thickness direction of the battery negative electrode;

[0028] Calculating the liquid-phase potential based on the local volumetric current density, the liquid-phase ionic conductivity, and the liquid-phase ion flux density;

[0029] Calculating the first liquid-phase resistance based on the grid size of the battery negative electrode, the first liquid-phase current calculated in the previous step, and the liquid-phase potential; the grid size is obtained by dividing the battery negative electrode in the thickness direction.

[0030] In the embodiments of the present application, the local volumetric current density is calculated based on the current density and the dimension in the thickness direction. Compared with the method of calculating the local volumetric current density in the P2D model, the embodiments of the present application improve the calculation speed, and thus can quickly calculate the first liquid-phase resistance, providing a data basis for subsequent calculation of the overpotential.

[0031] In any embodiment, calculating the first charge transfer resistance according to the parameter information corresponding to the battery negative electrode and the current density includes:

[0032] Obtaining the first overpotential and the first charge transfer current calculated in the previous step;

[0033] Calculating the first charge transfer resistance based on the dimension in the thickness direction of the battery negative electrode, the first overpotential calculated in the previous step, and the first charge transfer current.

[0034] In the embodiments of the present application, the first charge transfer resistance is obtained through calculation, providing a data basis for subsequent calculation of the overpotential.

[0035] In any embodiment, the equivalent circuit includes a positive electrode mesh circuit; the positive electrode mesh circuit includes a plurality of parallel second sub-mesh circuits;

[0036] Each second sub-mesh circuit includes a second solid-phase resistance, a second liquid-phase resistance, and a second charge transfer resistance;

[0037] Based on the parameter information and the current density, performing simulation on a battery simulation model to obtain the distribution of the overpotential of the battery, including:

[0038] Calculate the second solid-phase resistance, the second electrode particle equilibrium voltage, and the second charge transfer resistance according to the parameter information corresponding to the battery positive electrode; calculate the second liquid-phase resistance according to the parameter information and the current density;

[0039] Construct the second mesh equations corresponding to each second subnet hole circuit according to the second solid-phase resistance, the second liquid-phase resistance, the second charge transfer resistance, and the second electrode particle equilibrium voltage;

[0040] Calculate the second charge transfer current corresponding to each second mesh circuit based on each second mesh equation;

[0041] Calculate the second overpotential of the corresponding mesh according to the second charge transfer current.

[0042] The embodiment of the present application is based on the single-particle hypothesis and uses the transmission line model to calculate the second overpotential at each position of the battery positive electrode. Compared with simply using the single-particle model to calculate the overpotential, the calculation accuracy of the overpotential is improved.

[0043] In any embodiment, the battery simulation model further includes a single-particle model. Based on the battery simulation model for simulation, the simulation results of the battery are obtained, including:

[0044] Based on the parameter information and the current density, perform simulation based on the single-particle model to obtain the solid-phase lithium-ion concentration and the liquid-phase lithium-ion concentration of the battery.

[0045] The embodiment of the present application calculates the solid-phase lithium-ion concentration and the liquid-phase lithium-ion concentration through the single-particle model. Compared with the P2D model, the calculation amount of battery simulation is reduced, and the efficiency of battery simulation is improved.

[0046] In any embodiment, the parameter information includes the size of the electrode in the thickness direction, the lithium-ion diffusion coefficient of the solid-phase particles corresponding to the electrode, the liquid-phase lithium-ion diffusion coefficient, and the porosity; based on the parameter information and the current density, perform simulation based on the single-particle model to obtain the solid-phase lithium-ion concentration and the liquid-phase lithium-ion concentration of the battery, including:

[0047] Calculate the solid-phase lithium-ion concentration corresponding to the electrode according to the size of the electrode in the thickness direction, the lithium-ion diffusion coefficient of the solid-phase particles corresponding to the electrode, and the solid-phase lithium-ion concentration equation in the single-particle model;

[0048] Calculate the local body current density of the electrode according to the current density and the size;

[0049] Calculate the liquid-phase lithium-ion concentration according to the liquid-phase lithium-ion diffusion coefficient, the porosity, and the local body current density of the electrode, and the liquid-phase lithium-ion concentration equation in the single-particle model.

[0050] In the embodiment of the present application, the local volumetric current density is calculated based on the current density and the size of the battery in the thickness direction of the electrode. Compared with the P2D model, the embodiment of the present application can quickly calculate the local volumetric current density, thereby improving the efficiency of calculating the liquid-phase lithium-ion concentration.

[0051] In a second aspect, the embodiment of the present application provides a method for identifying battery parameters, including:

[0052] Substituting the parameters to be identified into the battery simulation model described in the first aspect to obtain the predicted values output by the battery simulation model;

[0053] Identifying the battery parameters based on the predicted values and the measured values of the battery.

[0054] In the embodiment of the present application, the battery simulation model is used to identify the battery parameters. Since the battery simulation model can quickly output the simulation results, the efficiency of battery parameter identification can be improved.

[0055] In a third aspect, the embodiment of the present application provides a method for generating the SOC voltage curve of a battery, including:

[0056] Substituting the battery parameters and the rate of the battery to be estimated into the battery simulation model described in the first aspect to obtain the SOC and voltage values corresponding to each moment output by the battery simulation model;

[0057] Generating an SOC voltage curve based on the SOC and voltage values corresponding to each moment.

[0058] In the embodiment of the present application, since the battery simulation model can quickly output the simulation results, the SOC voltage curve can be obtained based on the simulation results, improving the efficiency of generating the SOC voltage curve.

[0059] In a fourth aspect, the embodiment of the present application provides a battery simulation device, including:

[0060] A parameter acquisition module for acquiring the parameter information of the battery in the thickness direction and the current density flowing into the battery;

[0061] A second simulation module for performing simulation based on the battery simulation model according to the parameter information and the current density to obtain the simulation results of the battery, where the simulation results include the distribution of overpotential; wherein, the battery simulation model includes a transmission line model; the transmission line model is formed by constructing equivalent circuits of the particles corresponding to the positive electrode and the negative electrode of the battery based on the single-particle hypothesis.

[0062] In a fifth aspect, the embodiment of the present application provides an electronic device, including: a processor, a memory, and a bus, where

[0063] The processor and the memory communicate with each other through the bus;

[0064] The memory stores program instructions executable by the processor, and the processor can execute the methods of the first aspect, the second aspect or the third aspect by invoking the program instructions.

[0065] In a sixth aspect, an embodiment of the present application provides a non-transitory computer-readable storage medium, including:

[0066] The non-transitory computer-readable storage medium stores computer instructions, and the computer instructions cause the computer to execute the methods of the first aspect, the second aspect or the third aspect.

[0067] Other features and advantages of the present application will be described in the subsequent specification, and, in part, will be obvious from the specification, or will be understood by implementing the embodiments of the present application. The objectives and other advantages of the present application can be achieved and obtained by the structures specifically pointed out in the written specification, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required to be used in the embodiments of the present application. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can also be obtained based on these drawings without creative efforts.

[0069] Figure 1 It is a schematic diagram of a traditional P2D model;

[0070] Figure 2 It is a schematic diagram of the change of the solid-phase current density inside the battery;

[0071] Figure 3 It is a schematic diagram divided along the thickness direction of the battery cell;

[0072] Figure 4 It is a schematic diagram of the grid division of solid-phase particles;

[0073] Figure 5 It is a schematic diagram of the lithium-ion concentration in the liquid-phase region;

[0074] Figure 6 It is a schematic diagram of the change of the solid-phase current density inside the battery under the single-particle model;

[0075] Figure 7 It is a schematic diagram of the ion flow density distribution in the electrolyte;

[0076] Figure 8 It is a schematic diagram of the flow of a battery simulation method provided by an embodiment of the present application;

[0077] Figure 9 Schematic diagram of the equivalent circuit of the negative electrode plate provided by the embodiment of the present application;

[0078] Figure 10 Schematic diagram of the equivalent circuit of the transmission line model provided by the embodiment of the present application;

[0079] Figure 11 Schematic diagram of the process flow of another battery simulation method provided by the embodiment of the present application;

[0080] Figure 12 Schematic diagram of the process flow of a battery parameter identification method provided by the embodiment of the present application;

[0081] Figure 13 Schematic diagram of the process flow of a method for generating the SOC voltage curve of a battery provided by the embodiment of the present application;

[0082] Figure 14 Schematic diagram of the structure of a battery simulation device provided by the embodiment of the present application;

[0083] Figure 15 Schematic diagram of the structure of a battery parameter identification device provided by the embodiment of the present application;

[0084] Figure 16 Schematic diagram of the structure of a device for generating the SOC voltage curve of a battery provided by the embodiment of the present application;

[0085] Figure 17 Schematic diagram of the physical structure of an electronic device provided by the embodiment of the present application. Detailed implementation manners

[0086] The embodiments of the technical solutions of the present application will be described in detail below with reference to the accompanying drawings. The following embodiments are only used to illustrate the technical solutions of the present application more clearly, and thus are only examples and cannot be used to limit the protection scope of the present application.

[0087] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above drawings are intended to cover non-exclusive inclusion.

[0088] In the description of the embodiments of the present application, technical terms such as "first" and "second" are only used to distinguish different objects and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity, specific order or primary-secondary relationship of the indicated technical features. In the description of the embodiments of the present application, "a plurality of" means two or more unless otherwise specifically defined.

[0089] As used herein, the mention of "embodiments" means that the specific features, structures, or characteristics described in connection with the embodiments can be included in at least one embodiment of the present application. The phrase appears in various places in the specification and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0090] In the description of the embodiments of the present application, the term "and / or" is merely a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after.

[0091] In the description of the embodiments of the present application, the term "plurality" refers to two or more (including two). Similarly, "multiple groups" refers to two or more groups (including two groups), and "multiple sheets" refers to two or more sheets (including two sheets).

[0092] In the description of the embodiments of the present application, the orientation or positional relationship indicated by technical terms such as "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the embodiments of the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the embodiments of the present application.

[0093] In the description of the embodiments of the present application, unless otherwise clearly specified and limited, technical terms such as "installation", "connection", "connection", "fixation", etc. should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or integrated; it can also be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present application can be understood according to specific circumstances.

[0094] Since the invention of lithium-ion batteries, people have been committed to developing simulation models of lithium-ion batteries. The pseudo-two-dimensional (P2D) model is established based on the porous electrode theory and the concentrated solution theory, and uses one dimension in the thickness direction of a battery electrode and an additional dimension (pseudo-dimension) in the radial direction of a solid-phase particle assumed to be spherical to describe the behavior of the battery. Figure 1It is a schematic diagram of the traditional P2D model. In the thickness direction of the battery cell, there are successively: the negative electrode neg region (anode), the separator region (sep), and the positive electrode pos region (cathode). The negative and positive electrode regions are represented by solid-phase particles of the electrode for the porous electrode. The classical P2D model mainly includes five parts:

[0095] ① Using Fick's diffusion law to describe the solid-phase lithium-ion concentration in spherical particles;

[0096] ② Using diffusion and electromigration to describe the lithium-ion concentration in the electrolyte and the separator;

[0097] ③ Using Ohm's law to describe the solid-phase potential in the electrode;

[0098] ④ Using Ohm's law and Kirchhoff's law to describe the liquid-phase potential in the electrolyte and the separator;

[0099] ⑤ Using the Butler-Volmer equation to describe the electrochemical reaction at the solid-liquid interface.

[0100] Figure 2 It is a schematic diagram of the change in the solid-phase current density inside the battery. Figure 2 It shows that when a current with a magnitude of I A flows through the battery, the current density i s in the solid-phase part inside the battery changes in the thickness x direction. Among them, L_neg is the region in the thickness direction of the negative electrode, L_sep is the region of the separator in the thickness direction, and L_pos is the region in the thickness direction of the positive electrode. As the current flows into the battery from the negative electrode, after passing through the solid-liquid interface, it is converted into an ion current and flows into the liquid phase. The current density in the solid phase becomes smaller and smaller until it reaches the separator and drops to 0. At this time, all the current is converted into an ion current. The ion current passes through the separator and comes to the positive electrode region, and then is converted into an electron current and flows into the solid phase, and finally returns to a current with a magnitude of I A .

[0101] The local volume current density j is defined as:

[0102]

[0103] It can be simply understood as the decrease in i s within a unit length dx. The reduced part of this current is the part that undergoes a chemical reaction and flows into the electrolyte as an ion current here. The magnitude of j represents the intensity of the chemical reaction here.

[0104] The Butler-Volmer equation:

[0105]

[0106] Among them, i oIt can be calculated through the following formula:

[0107]

[0108] The relationship between the magnitude of the overpotential η and the local volume current density j is described by the BV formula (2), where a is the surface area of the electrode particles, and i o is the exchange current density, and α c is the charge transfer coefficient. After calculating j, the overpotential can be calculated by inversely solving formula (2).

[0109] In formula (3), k is the chemical reaction constant, is the maximum concentration of lithium-ion particles. C e is the lithium-ion concentration of the liquid-phase electrolyte at that place. For the convenience of calculation, it is considered that α c = α a = 0.5.

[0110] In practical applications, the P2D model consists of a series of partial differential equations and has no analytical solution, so only numerical solution methods can be used. Numerical solution requires dividing the space into grids, Figure 3 is a schematic diagram of the division in the thickness direction of the battery cell, as Figure 3 shown. It is assumed that the thickness direction is divided into nl grids, and the size of each grid is h:

[0111]

[0112] It is considered that there is a solid-phase particle on each grid, representing the solid-phase particles in that area. Since the electrode reaction is not uniform in the thickness direction, the lithium-ion concentration C s in each particle is different. The lithium-ion concentration C s inside each solid-phase particle can be described by the following equation:

[0113]

[0114] where C s is the solid-phase lithium-ion concentration, t is the time, r is the distance in the radial direction of the particle, and D s is the effective diffusion coefficient of lithium ions in the solid-phase particles.

[0115] Since this equation is a partial differential equation and has no analytical solution, only numerical solution methods can be used. Numerical solution requires dividing the space into grids, and the grid division of the solid-phase particles is as Figure 4 shown. There are n s grids in the figure, and the size of each grid is m:

[0116]

[0117] where Rs is the particle radius.

[0118] The boundary conditions of Equation (5) are:

[0119]

[0120]

[0121] where a is the particle surface area, F is the Faraday constant, and j is the local volume current density at the location of the particle. If j at the location of the particle can be obtained, the concentration distribution within the solid-phase particle at that moment can be obtained.

[0122] Figure 5 is a schematic diagram of the lithium-ion concentration in the liquid phase region, as Figure 5 shown. The lithium-ion concentrations in the electrolytes in the positive and negative electrode regions of the liquid phase satisfy the following partial differential equation:

[0123]

[0124] The lithium-ion concentration in the electrolyte in the separator region of the liquid phase satisfies the following partial differential equation:

[0125]

[0126] where C e is the lithium-ion concentration in the liquid phase, x is the distance in the battery thickness direction, ε is the porosity, D e is the effective diffusion coefficient of lithium ions in the liquid phase, t 0 is the transference number, F is the Faraday constant, and j is the local volume current density.

[0127] Since it was proposed in 1993, the P2D model has undergone decades of testing and verification and has now become one of the important models for lithium-ion battery simulation. However, the form of the governing equations of the P2D model is complex and no complete analytical solution can be obtained. Only numerical methods can be used for solving, such as the finite difference method and the finite volume method, etc. The calculation consumption is large and the single calculation time is long, which limits its application in many scenarios, such as scenarios that require large-scale calculations like life prediction and tolerance prediction, and scenarios with limited computing power like in-vehicle BMS.

[0128] The single particle model with electrolyte (SPMe) is simplified based on the P2D model. It uses a single spherical particle to represent the electrode of the lithium battery and assumes that the insertion and extraction process of lithium ions occurs on the spherical particle. The single particle model with electrolyte has a simple structure, small amount of calculation, and is easy to implement online application. At present, the single particle model with electrolyte is mainly used in the charge state diagnosis research of lithium-ion batteries. However, there are some inevitable shortcomings of the single particle model of lithium-ion batteries, that is, under the condition of high-rate charge and discharge, the assumptions of the model are unreasonable, which leads to excessive simulation deviation.

[0129] The single particle hypothesis assumes that the electrode reaction in the positive and negative electrode regions is uniform, so the change in the solid phase current density inside the battery is linear. Figure 6 Shown is the schematic diagram of the change of solid phase current density inside the battery under the single particle model.

[0130] Therefore, j can be easily obtained by the following formula:

[0131]

[0132]

[0133] That is, j at each position in the positive and negative electrode regions is equal, so the state of each particle is also consistent. It is only necessary to solve the lithium ion concentration inside a particle in the positive and negative electrode regions respectively.

[0134] After obtaining j, the concentration distribution of liquid lithium ions and the distribution of lithium ions in the solid phase particles of the positive and negative electrodes can be obtained by solving formulas (5), (9), and (10).

[0135] The liquid phase potential can be obtained by the liquid phase potential equation:

[0136]

[0137] Where σ l is the liquid phase ionic conductivity, i e is the ion current density in the liquid phase, f A is the activity. Integrating x on both sides of formula (14) gives the liquid phase potential φ e Distribution.

[0138] The overpotential η can be obtained by inversely solving the BV equation, namely:

[0139]

[0140] The electrode particle equilibrium potential U can be obtained by looking up the table of electrode particle surface concentration:

[0141]

[0142] The single-particle hypothesis assumes that j is equal at each position. Therefore, the ion current density in the electrolyte shows a linear distribution, as Figure 7 shown. This causes the overpotential η obtained by back-solving the BV equation to deviate seriously from the actual situation, resulting in a large deviation in the battery voltage obtained finally at high rates.

[0143] Based on the above problems, the embodiments of the present application provide a battery simulation method, which is based on the single-particle hypothesis and uses a transmission line model to calculate the overpotential.

[0144] Figure 8 FIG. is a schematic flow chart of a battery simulation method provided by an embodiment of the present application, as Figure 8 shown. The method includes:

[0145] Step 801: Obtain the parameter information of the battery and the current density flowing into the battery;

[0146] Step 802: Based on the parameter information and the current density, perform simulation using a battery simulation model to obtain the simulation result of the battery.

[0147] In a specific implementation process, the parameter information of the battery refers to the relevant parameters of the battery itself, such as: the size in the thickness direction of the battery positive electrode, the size in the thickness direction of the battery negative electrode, the positive electrode material, the negative electrode material, the liquid-phase lithium-ion conductivity, the lithium-ion diffusion coefficient of the solid-phase particles, the liquid-phase lithium-ion diffusion coefficient, the porosity, etc. The current density of the battery refers to the amount of current passing through per unit area, usually expressed in A / cm^2.

[0148] The battery simulation model includes a transmission line model, and the transmission line model includes equivalent circuits of particles respectively corresponding to the positive electrode and the negative electrode of the battery constructed based on the single-particle hypothesis. After inputting the parameter information and the current density of the battery into the battery simulation model, the overpotential in the equivalent circuit is solved respectively based on the parameter information and the current density. Therefore, the simulation result includes the overpotential corresponding to each position in the thickness direction of the electrode sheet in the battery.

[0149] The embodiments of the present application use a transmission line model based on the single-particle hypothesis to simulate the overpotential distribution of the battery. Compared with the single-particle model, since the single-particle model cannot reflect the non-uniformity of the electrode reaction, the simulation accuracy is relatively low. On the basis of the single-particle model, the present application couples the transmission line model, which can better reflect the non-uniformity of the electrode reaction and improves the simulation accuracy with a relatively small increase in the calculation amount.

[0150] On the basis of the above embodiments, the equivalent circuit includes a negative electrode mesh circuit; the negative electrode mesh circuit includes a plurality of parallel first sub-mesh circuits; each first sub-mesh circuit includes a first solid-phase resistance, a first liquid-phase resistance, and a first charge transfer resistance;

[0151] Based on the parameter information and the current density, simulations are carried out based on the battery simulation model to obtain the simulation results of the battery, including:

[0152] Calculate the first solid-phase resistance, the first charge transfer resistance, and the first electrode particle equilibrium voltage of each first sub-mesh circuit according to the parameter information corresponding to the battery negative electrode; calculate the first liquid-phase resistance according to the parameter information and the current density;

[0153] Construct the first mesh equation corresponding to each first sub-mesh circuit according to the first solid-phase resistance, the first liquid-phase resistance, the first charge transfer resistance, and the first electrode particle equilibrium voltage;

[0154] Calculate the first charge transfer current corresponding to each first sub-mesh circuit based on each first mesh equation;

[0155] Calculate the first overpotential of the corresponding mesh according to the first charge transfer current.

[0156] In a specific implementation process, Figure 9 For the schematic diagram of the equivalent circuit of the negative electrode sheet provided by the embodiment of the present application, as Figure 9 shown, the negative electrode is divided into n grids in the thickness direction, and each first sub-mesh circuit in the equivalent circuit corresponds to a grid. Where I is the total current, R s is the first solid-phase resistance, R l is the first liquid-phase resistance, R CT is the first charge transfer resistance; U is the electrode equilibrium potential on each mesh.

[0157] In order to calculate the overpotential corresponding to each mesh, it is necessary to calculate the current flowing through R CT on each mesh, and the current flowing through R CT on each mesh is calculated based on the first solid-phase resistance, the first liquid-phase resistance, the first charge transfer resistance, and the electrode equilibrium potential.

[0158] Among them, the first solid-phase resistance, the first charge transfer resistance, and the electrode equilibrium potential can be calculated according to the parameter information corresponding to the battery negative electrode. The first liquid-phase resistance can be calculated according to the parameter information corresponding to the battery negative electrode and the current density.

[0159] The first solid-phase resistance can be calculated according to the following formula:

[0160]

[0161] Among them, h is the grid size of the battery negative electrode, which is obtained by dividing the battery negative electrode in the thickness direction, and σ s is the conductivity of the negative electrode sheet.

[0162] The equilibrium voltage of the first electrode particles can be used to calculate the solid-phase lithium-ion concentration based on the solid-phase lithium-ion diffusion coefficient; the equilibrium voltage of the first electrode particles can be obtained by looking up the table according to the solid-phase lithium-ion concentration, and specifically, reference can be made to formula (15).

[0163] The first liquid-phase resistance can be calculated according to the following steps:

[0164] The local volumetric current density can be calculated based on the current density and the size in the thickness direction of the battery negative electrode; among them, the local volumetric current density can be calculated according to the above formula (11).

[0165] The liquid-phase electric potential can be calculated based on the local volumetric current density, the liquid-phase ionic conductivity, and the liquid-phase ion flux density. Among them, the liquid-phase electric potential can be calculated according to the above formulas (9), (10), and (14).

[0166] The first liquid-phase resistance can be calculated based on the grid size of the battery negative electrode, the first liquid-phase current calculated in the previous step, and the liquid-phase electric potential. Among them, the first charge transfer current is the current flowing through R CT The calculation formula of the first liquid-phase resistance is as follows:

[0167]

[0168] Among them, i l is the first liquid-phase current calculated in the previous step.

[0169] The first charge transfer resistance can be calculated according to the following steps:

[0170] Obtain the first overpotential and the first charge transfer current calculated in the previous step;

[0171] The first charge transfer resistance can be calculated based on the size in the thickness direction of the battery negative electrode, the first overpotential calculated in the previous step, and the first charge transfer current.

[0172] Among them, the calculation formula of the first charge transfer resistance is as follows:

[0173]

[0174] Among them, I ct is the first charge transfer current calculated in the previous step; η is the first overpotential calculated in the previous step. When calculating the first overpotential corresponding to the mesh according to the first charge transfer current, the first charge transfer current can be substituted into the Butler-Volmer equation to solve for the first overpotential, and specifically, reference can be made to formula (14).

[0175] After calculating the first solid-phase resistance, the first liquid-phase resistance, the first charge transfer resistance, and the equilibrium voltage of the first electrode particles, the following mesh equations can be listed for all meshes:

[0176]

[0177] Converting formula (19) into matrix form gives:

[0178]

[0179]

[0180] By solving the above two matrix equations, the mesh currents of each mesh can be obtained:

[0181]

[0182] Furthermore, the first charge transfer current I of each mesh can be obtained CT :

[0183] I CT,1 = I - I 1

[0184] I CT,1 = I 1 - I 2 ...

[0186] I CT,n = I n-1 - I n

[0187] I CT,n+1 = I n

[0188] After obtaining the first charge transfer current I CT , substituting it into the BV equation, the first overpotential at different mesh positions can be obtained. Among them, the BV equation can be seen in formula (2).

[0189] In the embodiment of the present application, by equivalently replacing the negative electrode of the battery with multiple first sub-mesh circuits, and by solving the first charge transfer current on each first sub-mesh circuit, the first overpotential at each position of the battery negative electrode can be obtained, thereby improving the accuracy of calculating the first overpotential.

[0190] On the basis of the above embodiment, the equivalent circuit includes a positive electrode mesh circuit; the positive electrode mesh circuit includes a plurality of parallel second sub-mesh circuits;

[0191] Each second sub-mesh circuit includes a second solid-phase resistance, a second liquid-phase resistance, and a second charge transfer resistance;

[0192] According to the parameter information and the current density, based on the battery simulation model for simulation, the distribution of the overpotential of the battery is obtained, including:

[0193] Calculate the second solid-phase resistance, the second electrode particle equilibrium voltage, and the second charge transfer resistance according to the parameter information corresponding to the positive electrode of the battery; calculate the second liquid-phase resistance according to the parameter information and the current density;

[0194] Construct a second mesh equation corresponding to each second subnet circuit according to the second solid-phase resistance, the second liquid-phase resistance, the second charge transfer resistance, and the second electrode particle equilibrium voltage;

[0195] Calculate the second charge transfer current corresponding to each second subnet circuit based on each second mesh equation;

[0196] Calculate the second overpotential corresponding to the corresponding mesh according to the second charge transfer current.

[0197] Figure 10 Schematic diagram of the equivalent circuit of the transmission line model provided by the embodiment of the present application, as Figure 10 shown, the equivalent circuit includes a negative electrode mesh circuit and a positive electrode mesh circuit, the positive electrode mesh circuit; the positive electrode mesh circuit includes a plurality of parallel second subnet circuits; each second subnet circuit includes a second solid-phase resistance, a second liquid-phase resistance, and a second charge transfer resistance. The number of second subnet circuits included in the positive electrode mesh circuit may be the same as or different from the number of first subnet circuits included in the negative electrode mesh circuit, and the specific number can be determined according to the actual situation. However, it should be noted that the more the number of second subnet circuits, the more accurate the obtained second overpotential distribution, and correspondingly, the greater the calculation amount.

[0198] It should be noted that the calculation method of the second overpotential corresponding to each mesh position based on the positive electrode mesh circuit is the same as that of the first overpotential corresponding to the negative electrode mesh circuit, and will not be elaborated here.

[0199] The embodiment of the present application is based on the single-particle hypothesis and uses the transmission line model to calculate the second overpotential at each position of the positive electrode of the battery, which improves the calculation accuracy of the overpotential compared with simply using the single-particle model to calculate the overpotential.

[0200] On the basis of the above embodiment, during the simulation of the battery, in addition to calculating the distribution of the overpotential, the solid-phase lithium-ion concentration and the liquid-phase lithium-ion concentration of the battery can also be simulated, and the method is as follows:

[0201] Based on the single-particle model, perform simulation according to the parameter information and the current density to obtain the solid-phase lithium-ion concentration and the liquid-phase lithium-ion concentration of the battery.

[0202] In a specific implementation process, the parameter information includes the size of the electrode in the thickness direction, the lithium-ion diffusion coefficient of the solid-phase particles corresponding to the electrode, the liquid-phase lithium-ion diffusion coefficient, and the porosity, etc. It should be noted that the electrode can be a positive electrode or a negative electrode. Inputting the parameter information and the current density into the single-particle model, the single-particle model can output the solid-phase lithium-ion concentration and the liquid-phase lithium-ion concentration of the battery.

[0203] When the single-particle model calculates the solid-phase lithium-ion concentration, it substitutes the size of the electrode in the thickness direction and the lithium-ion diffusion coefficient of the solid-phase particles corresponding to the electrode into the solid-phase lithium-ion concentration equation to calculate and obtain the solid-phase lithium-ion concentration. Specifically, reference can be made to formula (5).

[0204] When the single-particle model calculates the liquid-phase lithium-ion concentration, the current density and the size can be substituted into formula (11) and formula (12). Among them, according to formula (11), the local body current density corresponding to the negative electrode can be calculated, and according to formula (12), the local body current density corresponding to the positive electrode can be calculated.

[0205] Substitute the liquid-phase lithium-ion diffusion coefficient, the porosity, and the local body current density of the electrode into the liquid-phase lithium-ion concentration equation to calculate and obtain the liquid-phase lithium-ion concentration. Specifically, reference can be made to formula (9) and formula (10).

[0206] In the embodiment of the present application, the solid-phase lithium-ion concentration and the liquid-phase lithium-ion concentration are calculated through the single-particle model. Compared with the P2D model, the calculation amount of battery simulation is reduced, and the efficiency of battery simulation is improved.

[0207] Figure 11 It is a schematic flow chart of another battery simulation method provided by the embodiment of the present application. As Figure 11 shown, the method includes:

[0208] Step 1101: Initialization; the calculation of each circuit element depends on the result of the previous step, and the calculation of the first step depends on the transmission line current distribution at time 0. The process of solving the transmission line at time 0 is called the initialization process. At time 0:

[0209]

[0210]

[0211]

[0212]

[0213] Step 1102: Calculate the solid-phase lithium-ion concentration and the liquid-phase lithium-ion concentration based on the single-particle model; for the calculation methods of the solid-phase lithium-ion concentration and the liquid-phase lithium-ion concentration, reference can be made to the above embodiments, and details will not be repeated here.

[0214] Step 1103: Update the numerical values of circuit elements in the transmission line; calculate and obtain the equilibrium potential of the first electrode particles, the first solid-phase resistance, the first liquid-phase resistance, and the first charge transfer resistance according to formulas (15), (16), (17), and (18).

[0215] Step 1104: Solve the transmission line model to obtain the overpotential and voltage at each location; the method for calculating the overpotential at each position of the positive and negative electrodes can be referred to the above embodiments and will not be elaborated here. Figure 10 The potential difference between the Upos point and the Uneg point is the finally output voltage.

[0216] Step 1105: Determine whether the cut-off condition is reached; the cut-off condition can include whether the maximum / minimum battery voltage is reached, whether the maximum calculation time is reached, whether a calculation error occurs, etc. If the cut-off condition is reached, stop the simulation; otherwise, return to execute Step 1102.

[0217] Figure 12 This is a schematic flowchart of a battery parameter identification method provided by an embodiment of the present application. As Figure 12 shown, the method includes:

[0218] Step 1201: Substitute the parameters to be identified into the battery simulation model to obtain the predicted values output by the battery simulation model;

[0219] Step 1202: Identify the battery parameters according to the predicted values and the measured values of the battery.

[0220] In the specific implementation process, the battery simulation model refers to the battery simulation model described in the above embodiments, which can simulate relevant parameters such as the solid-phase lithium-ion concentration, the liquid-phase lithium-ion concentration, the overpotential distribution, and the voltage of the battery according to the parameter information of the battery.

[0221] Before performing the simulation calculation of the lithium battery, data calibration is required. Usually, different parameter identification algorithms are used to obtain the correct model input parameters. The data-driven parameter identification mainly uses an algorithm to continuously try new parameter values within a reasonable range of parameter values, substitute the parameter values into the model, and compare the output value of the model with the actual measurement of the battery until a set of parameter values is found such that the output value of the model coincides with the measured value of the battery. Therefore, during the parameter identification process, thousands of attempts may be required, which places high requirements on the simulation efficiency and accuracy of the battery simulation model. The battery simulation model proposed by the embodiment of the present application can improve the simulation accuracy on the premise of increasing less computational effort and can meet the requirements of parameter identification.

[0222] Figure 13 This is a schematic flowchart of a method for generating the SOC voltage curve of a battery provided by an embodiment of the present application. AsFigure 13 As shown in the figure, the method includes:

[0223] Step 1301: Substitute the battery parameters and rate of the battery to be estimated into the battery simulation model to obtain the SOC and voltage values corresponding to each moment output by the battery simulation model;

[0224] Step 1302: Generate an SOC voltage curve based on the SOC and voltage values corresponding to each moment.

[0225] In a specific implementation process, the battery simulation model refers to the battery simulation model described in the above embodiment, which can simulate relevant parameters such as the solid-phase lithium-ion concentration, liquid-phase lithium-ion concentration, overpotential distribution, and voltage of the battery according to the parameter information of the battery. The rate can refer to the rate of charging the battery or the rate of discharging the battery. It can be specifically set according to actual simulation requirements. The value of the rate can be 1C, 2C, 3C, etc.

[0226] After inputting the parameter information of the battery into the battery simulation model, relevant parameters such as the solid-phase lithium-ion concentration, liquid-phase lithium-ion concentration, overpotential distribution, and voltage corresponding to each step can be obtained. The SOC of the battery is related to the solid-phase lithium-ion concentration. Therefore, the corresponding SOC value can be obtained according to the solid-phase lithium-ion concentration at each moment, and an SOC voltage curve is constructed based on the SOC and voltage values at each moment.

[0227] It can be understood that after obtaining the SOC voltage curve, the SOC can be estimated based on the SOC voltage curve, that is, the SOC value at a certain moment is estimated.

[0228] In the embodiment of the present application, since the battery simulation model can quickly output simulation results, an SOC voltage curve can be obtained based on the simulation results, improving the efficiency of generating the SOC voltage curve.

[0229] Figure 14 It is a schematic structural diagram of a battery simulation device provided by an embodiment of the present application. The device can be a module, program segment, or code on an electronic device. It should be understood that the device corresponds to the above Figure 8 method embodiment and can execute Figure 8 each step involved in the method embodiment. The specific functions of the device can be referred to the description above. To avoid repetition, the detailed description is appropriately omitted here. The device includes: a parameter acquisition module 1401 and a simulation module 1402, where:

[0230] The parameter acquisition module 1401 is used to acquire the parameter information of the battery and the current density flowing into the battery;

[0231] The simulation module 1402 is used to perform a simulation based on the battery simulation model according to the parameter information and the current density, so as to obtain the simulation result of the battery, where the simulation result includes the distribution of overpotential; wherein, the battery simulation model includes a transmission line model; the transmission line model is formed by constructing equivalent circuits of particles corresponding to the positive electrode and the negative electrode of the battery based on the single-particle hypothesis.

[0232] Based on the above embodiments, the equivalent circuit includes a negative electrode mesh circuit; the negative electrode mesh circuit includes a plurality of parallel first sub-mesh circuits; each of the first sub-mesh circuits includes a first solid-phase resistance, a first liquid-phase resistance, and a first charge transfer resistance.

[0233] Specifically, the simulation module 1402 is configured to:

[0234] Calculate the first solid-phase resistance and the equilibrium voltage of the electrode particles of each of the first sub-mesh circuits according to the parameter information corresponding to the negative electrode of the battery; calculate the first liquid-phase resistance and the first charge transfer resistance according to the parameter information and the current density.

[0235] Construct a first mesh equation corresponding to each first sub-mesh circuit according to the first solid-phase resistance, the first liquid-phase resistance, the first charge transfer resistance, and the first electrode particle equilibrium voltage.

[0236] Calculate the first charge transfer current corresponding to each first sub-mesh circuit based on each first mesh equation.

[0237] Calculate the first overpotential corresponding to the corresponding mesh according to the first charge transfer current.

[0238] Based on the above embodiments, specifically, the simulation module 1402 is configured to:

[0239] Substitute the first charge transfer current into the Butler-Volmer equation to calculate the first overpotential.

[0240] Based on the above embodiments, specifically, the simulation module 1402 is configured to:

[0241] Calculate the first solid-phase resistance according to the grid size of the negative electrode of the battery and the conductivity of the negative electrode plate; the grid size is obtained by dividing the negative electrode of the battery in the thickness direction.

[0242] Based on the above embodiments, specifically, the simulation module 1402 is configured to:

[0243] Calculate the solid-phase lithium-ion concentration according to the solid-phase lithium-ion diffusion coefficient.

[0244] Look up the table according to the solid-phase lithium-ion concentration to obtain the equilibrium voltage of the electrode particles.

[0245] Based on the above embodiments, the simulation module 1402 is specifically configured to:

[0246] Calculate the local volumetric current density based on the current density and the dimension in the thickness direction of the battery negative electrode;

[0247] Calculate the liquid-phase potential based on the local volumetric current density, the liquid-phase ionic conductivity, and the liquid-phase ionic current density;

[0248] Calculate the first liquid-phase resistance based on the grid size of the battery negative electrode, the first liquid-phase current calculated in the previous step, and the liquid-phase potential; the grid size is obtained by dividing the battery negative electrode in the thickness direction.

[0249] Based on the above embodiments, the simulation module 1402 is specifically configured to:

[0250] Calculate the local volumetric current density based on the current density and the dimension in the thickness direction of the battery negative electrode;

[0251] Calculate the overpotential by inversely solving the Butler-Volmer equation based on the local volumetric current density, the particle surface area, and the exchange current density;

[0252] Calculate the first charge transfer resistance based on the overpotential, the grid size of the battery negative electrode, and the local volumetric current density calculated in the previous step.

[0253] Based on the above embodiments, the equivalent circuit includes a positive electrode mesh circuit; the positive electrode mesh circuit includes a plurality of parallel second sub-mesh circuits;

[0254] Each of the second sub-mesh circuits includes a second solid-phase resistance, a second liquid-phase resistance, and a second charge transfer resistance;

[0255] The simulation module 1402 is specifically configured to:

[0256] Calculate the second solid-phase resistance, the second liquid-phase resistance, the second charge transfer resistance, and the electrode particle equilibrium voltage of each of the second sub-mesh circuits based on the parameter information corresponding to the battery positive electrode and the current density;

[0257] Construct second mesh equations corresponding to each of the second sub-mesh circuits based on the second solid-phase resistance, the second liquid-phase resistance, the second charge transfer resistance, and the second electrode particle equilibrium voltage;

[0258] Calculate the second charge transfer current corresponding to each of the second sub-mesh circuits based on the second mesh equations;

[0259] The second overpotential of the corresponding mesh is calculated based on the second charge transfer current.

[0260] Based on the above embodiments, the battery simulation model further includes a single particle model. The simulation module 1402 is specifically configured to:

[0261] Perform simulation based on the single particle model according to the parameter information and the current density to obtain the solid-phase lithium ion concentration and the liquid-phase lithium ion concentration of the battery.

[0262] Based on the above embodiments, the parameter information includes the size of the electrode in the thickness direction, the lithium ion diffusion coefficient of the solid-phase particles corresponding to the electrode, the liquid-phase lithium ion diffusion coefficient, and the porosity; the simulation module 1402 is specifically configured to:

[0263] Calculate the solid-phase lithium ion concentration corresponding to the electrode according to the size of the electrode in the thickness direction, the lithium ion diffusion coefficient of the solid-phase particles corresponding to the electrode, and the solid-phase lithium ion concentration equation in the single particle model;

[0264] Calculate the local volume current density of the electrode according to the current density and the size;

[0265] Calculate the liquid-phase lithium ion concentration according to the liquid-phase lithium ion diffusion coefficient, the porosity, the local volume current density of the electrode, and the liquid-phase lithium ion concentration equation in the single particle model.

[0266] Figure 15 The figure is a schematic structural diagram of a battery parameter identification device provided by an embodiment of the present application. The device can be a module, a program segment, or code on an electronic device. It should be understood that the device corresponds to the above Figure 11 method embodiment and can execute Figure 11 each step involved in the method embodiment. The specific functions of the device can be seen in the above description. To avoid repetition, the detailed description is appropriately omitted here. The device includes: a first parameter substitution module 1501 and an identification module 1502, where:

[0267] The first parameter substitution module 1501 is used to substitute the parameter to be identified into the battery simulation model provided by the above embodiments to obtain the predicted value output by the battery simulation model;

[0268] The identification module 1502 is used to identify the battery parameters according to the predicted value and the measured value of the battery.

[0269] Figure 16 The figure is a schematic structural diagram of a device for generating the SOC voltage curve of a battery provided by an embodiment of the present application. The device can be a module, a program segment, or code on an electronic device. It should be understood that the device corresponds to the above Figure 13corresponding to the method embodiments and capable of executing Figure 13 each step involved in the method embodiments. For the specific functions of the device, reference may be made to the descriptions in the foregoing text. To avoid repetition, the detailed descriptions are appropriately omitted here. The device includes: a second parameter substitution module 1601 and a curve generation module 1602, where:

[0270] The second parameter substitution module 1601 is configured to substitute the battery parameters and the rate of the battery to be estimated into the battery simulation model described in the foregoing embodiments, and obtain the SOC and voltage values corresponding to each moment output by the battery simulation model;

[0271] The curve generation module 1602 is configured to generate an SOC voltage curve based on the SOC and voltage values corresponding to each moment.

[0272] Figure 17 is a schematic structural diagram of an electronic device entity provided by an embodiment of the present application. As Figure 17 shown, the electronic device includes: a processor 1701, a memory 1702, and a bus 1703; where

[0273] The processor 1701 and the memory 1702 communicate with each other through the bus 1703;

[0274] The processor 1701 is configured to call program instructions in the memory 1702 to execute the methods provided in the foregoing method embodiments, for example, including: obtaining parameter information of the battery and the current density flowing into the battery; based on the parameter information and the current density, performing simulation based on a battery simulation model to obtain a simulation result of the battery, where the simulation result includes the distribution of overpotential; where the battery simulation model includes a transmission line model; and the transmission line model includes equivalent circuits of particles corresponding to the positive electrode and the negative electrode of the battery constructed based on a single particle hypothesis.

[0275] The processor 1701 may be an integrated circuit chip with signal processing capabilities. The foregoing processor 1701 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0276] The memory 1702 may include, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc.

[0277] This embodiment discloses a computer program product. The computer program product includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the methods provided in the above method embodiments, for example, including: obtaining parameter information of a battery and a current density flowing into the battery; based on the parameter information and the current density, performing a simulation based on a battery simulation model to obtain a simulation result of the battery, where the simulation result includes a distribution of overpotential; wherein, the battery simulation model includes a transmission line model; and the transmission line model includes equivalent circuits of particles respectively corresponding to the positive electrode and the negative electrode of the battery constructed based on a single particle assumption.

[0278] This embodiment provides a non-transitory computer-readable storage medium. The non-transitory computer-readable storage medium stores computer instructions. The computer instructions cause the computer to execute the methods provided in the above method embodiments, for example, including: obtaining parameter information of a battery and a current density flowing into the battery; based on the parameter information and the current density, performing a simulation based on a battery simulation model to obtain a simulation result of the battery, where the simulation result includes a distribution of overpotential; wherein, the battery simulation model includes a transmission line model; and the transmission line model includes equivalent circuits of particles respectively corresponding to the positive electrode and the negative electrode of the battery constructed based on a single particle assumption.

[0279] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For another example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some communication interfaces. The indirect coupling or communication connection of the devices or units can be in electrical, mechanical or other forms.

[0280] In addition, the units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or they can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0281] Furthermore, in each embodiment of the present application, the various functional modules can be integrated together to form an independent part, or each module can exist alone, or two or more modules can be integrated to form an independent part.

[0282] In this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0283] The above are only the embodiments of the present application and are not used to limit the protection scope of the present application. For those skilled in the art, the present application can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A battery simulation method, characterized in that: include: Acquiring parameter information of a battery and a current density flowing into the battery; According to the parameter information and the current density, simulation is performed based on a battery simulation model to obtain simulation results of the battery, wherein the simulation results include the distribution of overpotential; wherein the battery simulation model includes a transmission line model, and the transmission line model is used to simulate the distribution of the overpotential; the transmission line model includes equivalent circuits of particles corresponding to the positive and negative electrodes of the battery respectively constructed based on a single particle assumption.

2. The method according to claim 1, characterized in that The equivalent circuit includes a negative electrode mesh circuit; the negative electrode mesh circuit includes a plurality of first sub-mesh circuits connected in parallel; each of the first sub-mesh circuits includes a first solid phase resistor, a first liquid phase resistor and a first charge transfer resistor; The performing simulation based on a battery simulation model according to the parameter information and the current density to obtain a simulation result of the battery includes: Calculate the first solid phase resistance, the first charge transfer resistance and the first electrode particle equilibrium voltage of each of the first sub-mesh circuits according to the parameter information corresponding to the negative electrode of the battery; calculate the first liquid phase resistance according to the parameter information and the current density; Constructing first mesh equations corresponding to each first sub-mesh circuit according to the first solid phase resistance, the first liquid phase resistance, the first charge transfer resistance and the first electrode particle equilibrium voltage; Obtaining a first charge transfer current corresponding to each first mesh circuit by calculation based on each first mesh equation; The first overpotential of the corresponding mesh is calculated based on the first charge transfer current.

3. The method according to claim 2, characterized in that The step of calculating a first overpotential of a corresponding mesh according to the first charge transfer current comprises: Substitute the first charge transfer current into the Butler-Volmer equation to calculate and obtain the first overpotential.

4. The method according to claim 2, characterized in that: The calculating the first solid phase resistance according to the parameter information corresponding to the negative electrode of the battery includes: The first solid phase resistance is calculated according to the grid size of the battery negative electrode and the conductivity of the negative electrode plate; the grid size is obtained after dividing the battery negative electrode in the thickness direction.

5. The method according to claim 2, characterized in that: The calculating the first electrode particle equilibrium voltage according to the parameter information corresponding to the negative electrode of the battery includes: The solid phase lithium ion concentration is obtained by calculating the solid phase lithium ion diffusion coefficient; The first electrode particle equilibrium voltage is obtained by looking up a table according to the solid phase lithium ion concentration.

6. The method according to claim 2, characterized in that Calculating the first liquid phase resistance according to the parameter information corresponding to the negative electrode of the battery and the current density includes: The local volume current density is obtained by calculation according to the current density and the dimension of the negative electrode of the battery in the thickness direction; The liquid phase potential is obtained by calculation according to the local volume current density, liquid phase ion conductivity, and liquid phase ion current density; The first liquid phase resistance is calculated based on the grid size of the battery negative electrode, the first liquid phase current calculated in the previous step, and the liquid phase potential; the grid size is obtained after dividing the battery negative electrode in the thickness direction.

7. The method according to claim 2, characterized in that The calculating the first charge transfer resistance according to the parameter information corresponding to the negative electrode of the battery and the current density includes: Obtain the first overpotential and the first charge transfer current calculated in the previous step; The first charge transfer resistance is calculated based on the dimension of the battery negative electrode in the thickness direction, the first overpotential calculated in the previous step, and the first charge transfer current.

8. The method according to any one of claims 1 to 7, characterized in that: The equivalent circuit includes a positive mesh circuit; the positive mesh circuit includes a plurality of second sub-mesh circuits connected in parallel; Each of the second sub-mesh circuits includes a second solid phase resistor, a second liquid phase resistor, and a second charge transfer resistor; The step of performing simulation based on a battery simulation model according to the parameter information and the current density to obtain the distribution of the overpotential of the battery includes: Calculate the second solid phase resistance, the second electrode particle equilibrium voltage and the second charge transfer resistance according to the parameter information corresponding to the positive electrode of the battery; calculate the second liquid phase resistance according to the parameter information and the current density; Constructing second mesh equations corresponding to each second sub-mesh circuit according to the second solid phase resistance, the second liquid phase resistance, the second charge transfer resistance and the second electrode particle equilibrium voltage; Obtaining a second charge transfer current corresponding to each second mesh circuit by calculation based on each second mesh equation; The second overpotential of the corresponding mesh is calculated based on the second charge transfer current.

9. The method according to any one of claims 1 to 8, characterized in that: The battery simulation model also includes a single particle model, and the simulation based on the battery simulation model is performed to obtain the simulation result of the battery, including: According to the parameter information and the current density, simulation is performed based on the single particle model to obtain the solid phase lithium ion concentration and the liquid phase lithium ion concentration of the battery.

10. The method according to claim 9, characterized in that The parameter information includes the size of the electrode in the thickness direction, the lithium ion diffusion coefficient of the solid phase particles corresponding to the electrode, the liquid phase lithium ion diffusion coefficient and the porosity; The step of performing simulation based on a single particle model according to the parameter information and the current density to obtain a solid phase lithium ion concentration and a liquid phase lithium ion concentration of the battery includes: The solid-phase lithium ion concentration corresponding to the pole piece is obtained by calculating according to the size of the pole piece in the thickness direction and the lithium ion diffusion coefficient of the solid-phase particles corresponding to the pole piece, and the solid-phase lithium ion concentration equation in the single particle model; Calculate and obtain the local body current density of the pole piece according to the current density and the size; The liquid phase lithium ion concentration is obtained by calculating the liquid phase lithium ion concentration equation in the single particle model according to the liquid phase lithium ion diffusion coefficient, the porosity and the local body current density of the electrode.

11. A battery parameter identification method, characterized in that: include: Substituting the parameters to be identified into the battery simulation model according to any one of claims 1 to 10 to obtain a predicted value output by the battery simulation model; The battery parameters are identified according to the predicted values ​​and the actual measured values ​​of the battery.

12. A method for generating a SOC voltage curve of a battery, characterized in that: include: Substituting the battery parameters and rate of the battery to be estimated into the battery simulation model according to any one of claims 1 to 10, and obtaining the SOC and voltage values ​​corresponding to each moment output by the battery simulation model; The SOC-voltage curve is generated based on the SOC and voltage values ​​corresponding to each time.

13. A battery simulation device, characterized in that: include: A parameter acquisition module, used to acquire parameter information of a battery and a current density flowing into the battery; The second simulation module is used to perform simulation based on a battery simulation model according to the parameter information and the current density to obtain a simulation result of the battery, wherein the simulation result includes a distribution of overpotential; wherein the battery simulation model includes a transmission line model, and the transmission line model is used to simulate the distribution of the overpotential; the transmission line model includes an equivalent circuit of particles corresponding to the positive and negative electrodes of the battery respectively constructed based on a single particle assumption.

14. An electronic device, characterized in that: include: processor, memory and bus, wherein, The processor and the memory communicate with each other via the bus; The memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the method according to any one of claims 1 to 12.

15. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium stores computer instructions, which, when executed by a computer, cause the computer to perform the method according to any one of claims 1 to 12.

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