Battery simulation method, device, equipment and computer-readable storage medium

Abstract

The present application discloses a battery simulation method, device, equipment and computer-readable storage medium, the method comprising: obtaining concentration parameters and electrical parameters of the battery at each moment; and obtaining simulation results of the battery based on the concentration parameters and electrical parameters at each moment. In the above manner, the present application can realize efficient simulation of the battery.

Description

Technical Field

[0001] The present application relates to the field of battery technology, and in particular to a battery simulation method, device, equipment and computer-readable storage medium. Background Art

[0002] Currently, for the simulation of batteries (such as lithium batteries), it is necessary to solve the concentration parameters and electrical parameters of the battery at each moment.

[0003] Among them, for the iterative solution of electrical parameters and concentration parameters at each moment, each iteration uses the electrical parameters and concentration parameters of the previous iteration to determine the concentration parameters and electrical parameters in this iteration. Therefore, the iterative solution at each moment has a slow convergence speed and low efficiency, and the simulation efficiency of the battery is low. Summary of the invention

[0004] The present application at least provides a battery simulation method, apparatus, device and computer-readable storage medium.

[0005] In order to solve the above technical problems, a technical solution adopted in the present application is: to provide a battery simulation method, the method comprising: obtaining concentration parameters and electrical parameters of the battery at each moment, wherein the electrical parameters include body current density parameters, and the concentration parameters and electrical parameters at at least some moments are obtained by iterative solution based on the electrical parameters at the previous moment. In the iterative solution process, the concentration parameters obtained in this iteration are determined based on the estimated body current density parameters of this iteration, and the estimated body current density parameters of this iteration are determined by using the reference body current density parameters and the rate characterization value of the body current density parameters changing with the concentration parameters. The reference body current density parameters of non-first iterations are the body current density parameters obtained in the previous iteration, and the reference body current density parameters of the first iteration are the body current density parameters at the previous moment. The electrical parameters obtained in this iteration are determined based on the concentration parameters obtained in this iteration; based on the concentration parameters and electrical parameters at each moment, the simulation results of the battery are obtained.

[0006] Therefore, at least the concentration parameters and electrical parameters of some moments are obtained by iteratively solving based on the electrical parameters of the previous moment. For the iterative solution of any moment in the partial moments, the estimated volume current density parameters in each iteration are determined by using the reference current density parameters and the rate characterization value of the change of the volume current density parameters with the concentration parameters. The determined estimated volume current density parameters are closer to the actual volume current density parameters than the reference volume current density parameters. Therefore, using the estimated volume current density parameters in the current iteration to determine the concentration parameters in the current iteration can make it easier to obtain the optimal solution for the concentration parameters and accelerate the convergence speed of the iterative solution at each moment.

[0007] Since the convergence speed of the iterative solution at any moment in the partial moments is accelerated, the time required to determine the concentration parameters and electrical parameters at each moment is shortened and the efficiency is improved. Therefore, based on the concentration parameters and electrical parameters at each moment, the time required to determine the simulation results of the battery is shortened and the efficiency is improved, that is, efficient simulation of the battery is achieved.

[0008] Among them, the step of determining the estimated body current density parameters of this iteration includes: obtaining the reference body current density parameters and reference concentration parameters corresponding to this iteration, wherein the reference concentration parameters of non-first iterations are the concentration parameters obtained in the previous iteration, and the reference concentration parameters of the first iteration are the concentration parameters at the previous moment; using the rate characterization value, the reference body current density parameters and reference concentration parameters corresponding to this iteration to determine the estimated body current density parameters of this iteration.

[0009] Therefore, the estimated volume current density parameter of this iteration can be determined by combining the reference volume current density parameter, the rate characterization value of the volume current density parameter changing with the concentration parameter, and the reference concentration parameter.

[0010] Among them, the estimated body current density parameter of this iteration is determined by using the rate characterization value, the reference body current density parameter corresponding to this iteration and the reference concentration parameter, including: constructing a first relationship, wherein the first relationship characterizes the relationship between the rate characterization value and the body current density parameter change of this iteration, the concentration parameter change of this iteration, the body current density parameter change of this iteration is the difference between the estimated body current density parameter of this iteration and the reference body current density parameter, and the concentration parameter change of this iteration is the difference between the concentration parameter of this iteration and the reference concentration parameter; using the first relationship, a characterization function characterizing the estimated body current density parameter is obtained, and the characterization function takes the concentration parameter of this iteration as a variable.

[0011] Therefore, the estimated volume current density parameter of this iteration can be determined by using the relationship between the change of the volume current density parameter in this iteration, the change of the concentration parameter in this iteration, and the rate characterization value of the volume current density parameter changing with the concentration parameter.

[0012] Among them, the rate characterization value is the ratio between the change of the body current density parameter of the last iteration and the change of the concentration parameter of the last iteration, wherein the change of the body current density parameter of the last iteration is the difference between the body current density parameter of the last iteration and the reference body current density parameter of the last iteration, and the change of the concentration parameter of the last iteration is the difference between the concentration parameter of the last iteration and the reference concentration parameter of the last iteration, wherein the reference concentration parameter of the non-first iteration is the concentration parameter obtained in the last iteration, and the reference concentration parameter of the first iteration is the concentration parameter at the last moment.

[0013] Therefore, the rate characterization value is the ratio between the change in the volume current density parameter of the last iteration and the change in the concentration parameter of the last iteration, so the first-order derivative at the volume current density parameter of the last iteration is used to estimate the estimated volume current density parameter of this iteration. In addition, the change in the volume current density parameter of the last iteration is the difference between the volume current density parameter of the last iteration and the reference volume current density parameter of the last iteration, so for each iteration, the change in the volume current density parameter is the difference between the volume current density parameter of the corresponding iteration and the volume current density parameter obtained in the previous iteration or the volume current density parameter at the previous moment. The change in the concentration parameter of the last iteration is the difference between the concentration parameter of the last iteration and the reference concentration parameter of the last iteration, so for each iteration, the change in the concentration parameter is the difference between the concentration parameter of the corresponding iteration and the concentration parameter obtained in the previous iteration or the concentration parameter at the previous moment.

[0014] The step of determining the concentration parameter obtained in this iteration includes: substituting the estimated volume current density parameter of this iteration into a preset concentration field equation, and solving the preset concentration field equation after substitution to obtain the concentration parameter of this iteration.

[0015] Therefore, the estimated volume current density parameters of this iteration can be used to solve the preset concentration field equation to determine the concentration parameters of this iteration.

[0016] Among them, the preset concentration field equation includes at least one of the following: a first concentration field equation that uses Fick's diffusion law to describe the solid phase ion concentration parameters, a second concentration field equation that uses diffusion and electromigration to describe the ion concentration parameters in the electrolyte and the isolation membrane, and a conditional concentration field equation, wherein at least one parameter in the conditional concentration field equation is determined based on the current simulation operating conditions of the battery; and / or, the electrical parameters also include potential parameters, and the estimated body current density parameters of this iteration are substituted into the preset concentration field equation, including: substituting the potential parameters and the estimated body current density parameters of this iteration into the preset concentration field equation respectively.

[0017] Therefore, the preset concentration field equation can be flexibly selected. And / or, the preset concentration field equation can be solved using the estimated volume current density parameters and battery parameters of this iteration to determine the concentration parameters of this iteration.

[0018] Among them, the electrical parameters also include potential parameters; the steps for determining the potential parameters obtained in this iteration include: substituting the concentration parameters of this iteration and the reference body current density parameters of this iteration into the preset potential field equation, and solving the preset potential field equation after substitution to obtain the potential parameters of this iteration.

[0019] Therefore, the concentration parameters of this iteration and the reference body current density parameters can be used to solve the preset potential field equation to determine the potential parameters of this iteration.

[0020] Among them, the preset potential field equation includes at least one of the following: a first potential field equation that uses Ohm's law to describe the solid phase potential parameters in the electrode, a second potential field equation that uses Ohm's law and Kirchhoff's law to describe the liquid phase potential parameters in the electrolyte and the isolation membrane, and a conditional potential field equation, wherein at least one parameter in the conditional potential field equation is determined based on the current simulation operating conditions of the battery.

[0021] Therefore, the preset potential field equation can be flexibly selected.

[0022] Among them, the electrical parameters also include potential parameters; the steps for determining the volume current density parameters obtained in this iteration include: substituting the concentration parameters of this iteration and the potential parameters of this iteration into the concentration potential field connection equation, and solving the substituted concentration potential field connection equation to obtain the volume current density parameters of this iteration.

[0023] Therefore, the concentration parameters and potential parameters of this iteration can be used to solve the preset concentration potential field connection equation to determine the volume current density parameters of this iteration.

[0024] Among them, the concentration potential field connection equation includes at least one of the following: a concentration potential field connection equation that uses the Butler-Volmer equation to describe the electrochemical reaction at the solid-liquid interface, and a conditional concentration potential field connection equation, wherein at least one parameter in the conditional concentration potential field connection equation is determined based on the current simulation operating conditions of the battery.

[0025] Therefore, the concentration potential field connection equation can be flexibly selected.

[0026] Among them, the battery simulation method also includes: in the iterative solution process, based on the concentration parameters and electrical parameters of this iteration, detecting whether this iteration meets the convergence conditions; in response to the current iteration not meeting the convergence conditions, executing the concentration parameters and electrical parameters of the next iteration The step of determining the parameters; and / or, in response to the current iteration satisfying the convergence conditions, using the concentration parameters and electrical parameters of this iteration as the concentration parameters and electrical parameters at the current moment.

[0027] Therefore, for the iterative solution at each moment, when the current iteration does not meet the convergence condition, it means that the iterative solution process at the current moment has not converged, and the concentration parameters and electrical parameters obtained by the iterative solution may be constantly fluctuating or changing, and cannot produce stable and consistent concentration parameters and electrical parameters. The concentration parameters and electrical parameters obtained in the current iteration cannot accurately reflect the concentration parameters and electrical parameters at the current moment; therefore, when the current iteration does not meet the convergence condition, it is necessary to perform the determination steps of the concentration parameters and electrical parameters of the next iteration until the iterative solution process converges. When the current iteration meets the convergence condition, it means that the iterative solution process at the current moment has converged, and the concentration parameters and electrical parameters obtained by the iterative solution are basically stable and unchanged, and the concentration parameters and electrical parameters obtained in the current iteration can accurately reflect the concentration parameters and electrical parameters at the current moment; therefore, when the current iteration meets the convergence condition, the concentration parameters and electrical parameters of this iteration are used as the concentration parameters and electrical parameters at the current moment.

[0028] Wherein, based on the concentration parameters and electrical parameters of this iteration, detecting whether this iteration meets the convergence conditions includes: obtaining the change value of the battery parameters of this iteration, wherein the battery parameters include the concentration parameters and at least one of the electrical parameters, and the change value of the battery parameters of this iteration is the difference between the battery parameters of this iteration and the battery parameters corresponding to the previous iteration; detecting whether the change value of each battery parameter of this iteration is less than the change threshold value corresponding to each battery parameter; in response to the change value of each battery parameter being less than the change threshold value corresponding to each battery parameter, determining that this iteration meets the convergence conditions.

[0029] Therefore, for the iterative solution at each moment, the change value of each battery parameter is less than the change threshold corresponding to each battery parameter, indicating that the concentration parameters and electrical parameters obtained by the iterative solution at the current moment may be basically stable and unchanged, indicating that the iterative solution process at the current moment has not converged.

[0030] Among them, the concentration parameters and electrical parameters of at least part of the time are the concentration parameters and electrical parameters of the battery at least part of the time under simulated working conditions, wherein the simulated working conditions include at least one of the following: the ambient temperature of the battery is lower than a preset temperature, the charge and discharge rate of the battery is greater than a preset rate, and the battery state of charge of the battery is greater than a preset state of charge value.

[0031] Therefore, the simulation operating conditions of the battery can be flexibly selected.

[0032] In order to solve the above technical problems, another technical solution adopted by the present application is: providing a battery simulation device, which includes a simulation module and a determination module; the simulation module is used to obtain the concentration parameters and electrical parameters of the battery at each moment, wherein the electrical parameters include body current density parameters, and the concentration parameters and electrical parameters at at least some moments are iteratively solved based on the electrical parameters at the previous moment. During the iterative solution process, the concentration parameters obtained in this iteration are determined based on the estimated body current density parameters of this iteration, and the estimated body current density parameters of this iteration are determined using the reference body current density parameters and the rate characterization value of the body current density parameters changing with the concentration parameters. The reference body current density parameters of non-first iterations are the body current density parameters obtained in the previous iteration, and the reference body current density parameters of the first iteration are the body current density parameters at the previous moment. The electrical parameters obtained in this iteration are determined based on the concentration parameters obtained in this iteration; the determination module is used to obtain the simulation results of the battery based on the concentration parameters and electrical parameters at each moment.

[0033] To solve the above technical problems, another technical solution adopted in the present application is: to provide a battery simulation device, the battery simulation device includes a memory and a processor, the memory stores program instructions, and the processor is used to execute the program instructions to implement the above battery simulation method.

[0034] In order to solve the above technical problem, another technical solution adopted by the present application is: providing a computer-readable storage medium, wherein the computer-readable storage medium is used to store program instructions, and the program instructions can be executed to implement the above battery simulation method.

[0035] In the above technical scheme, the concentration parameters and electrical parameters of at least some moments are obtained by iteratively solving based on the electrical parameters of the previous moment. For the iterative solution of any moment in the partial moments, the estimated volume current density parameters in each iteration are determined by using the reference current density parameters and the rate characterization value of the change of the volume current density parameters with the concentration parameters. The determined estimated volume current density parameters are closer to the actual volume current density parameters than the reference volume current density parameters. Therefore, by using the estimated volume current density parameters in the current iteration to determine the concentration parameters in the current iteration, it is easier to obtain the optimal solution for the concentration parameters and accelerate the convergence speed of the iterative solution at each moment.

[0036] Since the convergence speed of the iterative solution at any moment in the partial moments is accelerated, the time required to determine the concentration parameters and electrical parameters at each moment is shortened and the efficiency is improved. Therefore, based on the concentration parameters and electrical parameters at each moment, the time required to determine the simulation results of the battery is shortened and the efficiency is improved, that is, efficient simulation of the battery is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1It is a flowchart of an embodiment of a battery simulation method provided by the present application;

[0038] Figure 2 It is a schematic diagram of the spatial discretization of partial differential equations;

[0039] Figure 3 This is a flowchart of an embodiment of detecting whether the iterative solution process has converged provided by the present application;

[0040] Figure 4 It is a structural schematic diagram of an embodiment of a battery simulation device provided by the present application;

[0041] Figure 5 It is a structural schematic diagram of an embodiment of a battery simulation device provided by the present application;

[0042] Figure 6 It is a structural schematic diagram of an embodiment of a computer-readable storage medium provided by the present application. DETAILED DESCRIPTION

[0043] The scheme of the embodiment of the present application is described in detail below in conjunction with the drawings of the specification.

[0044] In the following description, for the purpose of explanation rather than limitation, specific details such as specific system structures, interfaces, and technologies are provided to facilitate a thorough understanding of the present application.

[0045] The term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there may be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the objects associated before and after are in an "or" relationship. In addition, "many" in this article means two or more than two. In addition, the term "at least one" in this article means any combination of at least two of any one or more of a plurality of, for example, including at least one of A, B, and C, can mean including any one or more elements selected from the set consisting of A, B, and C.

[0046] See also Figure 1 , Figure 1 1 is a flow chart of an embodiment of a battery simulation method provided by the present application. It should be noted that if there are substantially the same results, the embodiments of the present application are not necessarily Figure 1 The process sequence shown is limited. Figure 1 As shown, this embodiment includes:

[0047] Step S11: Obtaining the concentration parameters and electrical parameters of the battery at each moment.

[0048] In this embodiment, concentration parameters and electrical parameters of the battery at each moment are obtained, wherein the electrical parameters include volume current density parameters, and the concentration parameters and electrical parameters at at least some moments are obtained by iteratively solving the electrical parameters at the previous moment.

[0049] The electrical parameters of the battery at each moment include the volume current density parameter, which refers to the current intensity flowing through the cross-sectional area of ​​the battery per unit area. The size of the volume current density parameter affects the rate of chemical reactions inside the battery (a higher volume current density parameter means that the battery can charge and discharge faster, improving the battery's efficiency), battery performance (the larger the volume current density parameter, the better the performance) and battery operating conditions (when the internal resistance of the battery is larger, the current flow will be restricted, resulting in a decrease in the volume current density parameter, affecting the battery's operating conditions), etc.

[0050] In one embodiment, the concentration parameter of the battery may be a solid phase ion concentration parameter, which refers to an ion concentration parameter in a solid electrolyte, usually expressed in mol / kg. Of course, the concentration parameter of the battery may also be a liquid phase ion concentration parameter, that is, an ion concentration parameter in an electrolyte and a separator. During the charge and discharge process of the battery, the ion concentration parameter in the liquid phase electrolyte will change; specifically, when the battery is discharged, a delithiation reaction occurs in the negative electrode region, and the ions removed enter the liquid phase electrolyte, resulting in an increase in the liquid phase ion concentration parameter on the negative electrode side. On the contrary, in the positive electrode region, the ions undergo an embedding reaction, resulting in a decrease in the liquid phase ion concentration parameter on the positive electrode side. Therefore, from the negative electrode to the positive electrode, the ion concentration parameter in the liquid phase electrolyte shows a downward trend.

[0051] In one embodiment, for the concentration parameters and electrical parameters of the battery at each moment, the concentration parameters and electrical parameters at some moments may be obtained by iterative solution based on the electrical parameters at the previous moment, and the concentration parameters and electrical parameters at the remaining moments may be obtained through actual testing. The number of moments corresponding to the iterative solution and the specific iterative solution moments and the number of moments corresponding to the actual test and the specific actual test moments are not limited, and can be specifically set according to actual use needs.

[0052] Of course, in other implementations, the concentration parameters and electrical parameters of the battery at each moment may all be obtained by iteratively solving based on the electrical parameters at the previous moment.

[0053] In addition, in this embodiment, during the iterative solution process, the concentration parameter obtained in this iteration is determined based on the estimated body current density parameter of this iteration, the estimated body current density parameter of this iteration is determined using the reference body current density parameter and the rate characterization value of the change of the body current density parameter with the concentration parameter, the reference body current density parameter of the non-first iteration is the body current density parameter obtained in the previous iteration, the reference body current density parameter of the first iteration is the body current density parameter at the previous moment, and the electrical parameters obtained in this iteration are determined based on the concentration parameter obtained in this iteration.

[0054] The estimated volume current density parameters in this iteration are determined by using the reference current density parameters and the rate characterization value of the volume current density parameters changing with the concentration parameters. The determined estimated volume current density parameters are closer to the actual volume current density parameters than the reference volume current density parameters. Therefore, using the estimated volume current density parameters in this iteration to determine the concentration parameters in this iteration can more easily obtain the optimal solution for the concentration parameters and accelerate the convergence speed.

[0055] It should be noted that multiple iterative solutions will be performed within a step. For the first iterative solution within this step, there is no previous iterative solution. Therefore, the estimated body current density parameter is determined using the body current density parameter of the previous step and the rate characterization value of the body current density parameter changing with the concentration parameter. For the non-first iterative solution within this step, since there is a previous iterative solution within the step, the estimated body current density parameter is determined using the body current density parameter obtained from the previous iteration and the rate characterization value of the body current density parameter changing with the concentration parameter.

[0056] Regarding the determination of the estimated volume current density parameter of this iteration, it can be obtained by combining the reference volume current density parameter, the rate characterization value of the volume current density parameter changing with the concentration parameter, and the reference concentration parameter. Specifically, in one embodiment, the determination of the estimated volume current density parameter of this iteration is specifically as follows: obtaining the reference volume current density parameter and the reference concentration parameter corresponding to this iteration, wherein the reference concentration parameter of the non-first iteration is the concentration parameter obtained in the previous iteration, and the reference concentration parameter of the first iteration is the concentration parameter at the previous moment; using the rate characterization value, the reference volume current density parameter corresponding to this iteration, and the reference concentration parameter, the estimated volume current density parameter of this iteration is determined.

[0057] That is to say, in the case of non-first iteration, the estimated volume current density parameter of this iteration is determined by combining the rate characterization value of the volume current density parameter changing with the concentration parameter, the concentration parameter obtained in the previous iteration, and the volume current density parameter obtained in the previous iteration. In the case of the first iteration, the estimated volume current density parameter of this iteration is determined by combining the rate characterization value of the volume current density parameter changing with the concentration parameter, the concentration parameter at the previous moment, and the volume current density parameter at the previous moment.

[0058] Further, the determination of the estimated volume current density parameter of this iteration can be obtained by combining the rate characterization value of the volume current density parameter changing with the concentration parameter, the change of the volume current density parameter in this iteration, and the change of the concentration parameter in this iteration. Specifically, in a specific embodiment, the estimated volume current density parameter of this iteration is determined using the rate characterization value, the reference volume current density parameter corresponding to this iteration, and the reference concentration parameter, specifically as follows: a first relationship is constructed, wherein the first relationship characterizes the relationship between the rate characterization value and the volume current density parameter change of this iteration, and the concentration parameter change of this iteration, the volume current density parameter change of this iteration is the difference between the estimated volume current density parameter of this iteration and the reference volume current density parameter, and the concentration parameter change of this iteration is the difference between the concentration parameter of this iteration and the reference concentration parameter; using the first relationship, a characterization function characterizing the estimated volume current density parameter is obtained, and the characterization function uses the concentration parameter of this iteration as a variable.

[0059] That is, the estimated volume current density parameter of this iteration is determined by using the relationship between the change of the volume current density parameter in this iteration, the change of the concentration parameter in this iteration, and the rate characterization value of the volume current density parameter changing with the concentration parameter.

[0060] In one embodiment, the first relationship is that the rate characterization value is equal to the ratio between the volume current density parameter change of this iteration and the concentration parameter change of this iteration; the characterization function is the sum of the reference volume current density parameter and the concentration term, and the concentration term is the product of the rate characterization value and the concentration parameter change of this iteration. Wherein, when the reference concentration parameter is the volume current density parameter obtained in the previous iteration and the reference concentration parameter is the concentration parameter obtained in the previous iteration, the specific formula of the estimated volume current density parameter of this iteration is as follows:

[0061]

[0062] in, represents the estimated volume current density parameter of this iteration; represents the volume current density parameter obtained in the last iteration; represents a rate characterization value; Represents the concentration parameter of this iteration; Represents the concentration parameter obtained in the last iteration; Indicates the concentration parameter change of this iteration, that is, the difference between the concentration parameter of this iteration and the concentration parameter of the previous iteration.

[0063] In one embodiment, the rate characterization value is the ratio between the change in the volume current density parameter of the last iteration and the change in the concentration parameter of the last iteration, wherein the change in the volume current density parameter of the last iteration is the difference between the volume current density parameter of the last iteration and the reference volume current density parameter of the last iteration, and the change in the concentration parameter of the last iteration is the difference between the concentration parameter of the last iteration and the reference concentration parameter of the last iteration, wherein the reference concentration parameter of the non-first iteration is the concentration parameter obtained in the last iteration, and the reference concentration parameter of the first iteration is the concentration parameter at the last moment.

[0064] The rate characterization value is the ratio between the change in the volume current density parameter of the last iteration and the change in the concentration parameter of the last iteration, so the first-order derivative at the volume current density parameter of the last iteration is used to estimate the estimated volume current density parameter of this iteration. In addition, the change in the volume current density parameter of the last iteration is the difference between the volume current density parameter of the last iteration and the reference volume current density parameter of the last iteration, so for each iteration, the change in the volume current density parameter is the difference between the volume current density parameter of the corresponding iteration and the volume current density parameter obtained in the previous iteration or the volume current density parameter at the previous moment. The change in the concentration parameter of the last iteration is the difference between the concentration parameter of the last iteration and the reference concentration parameter of the last iteration, so for each iteration, the change in the concentration parameter is the difference between the concentration parameter of the corresponding iteration and the concentration parameter obtained in the previous iteration or the concentration parameter at the previous moment.

[0065] In one embodiment, the concentration parameter obtained in this iteration is determined by substituting the estimated volume current density parameter of this iteration into a preset concentration field equation, and solving the preset concentration field equation after substitution to obtain the concentration parameter of this iteration. In other words, the concentration parameter obtained in this iteration can be obtained using some concentration field equations.

[0066] In a specific implementation, the electrical parameters also include potential parameters, and the estimated volume current density parameters of this iteration are substituted into the preset concentration field equation, specifically: the potential parameters and the estimated volume current density parameters of this iteration are substituted into the preset concentration field equation respectively. That is to say, for the concentration parameters obtained in this iteration, the potential parameters and the estimated volume current density parameters of this iteration can be introduced into some concentration field equations at the same time to solve them.

[0067] It should be noted that the preset concentration field equations include but are not limited to a first concentration field equation that uses Fick's diffusion law to describe the solid phase ion concentration parameters, a second concentration field equation that uses diffusion and electromigration to describe the ion concentration parameters in the electrolyte and the isolation membrane, and a conditional concentration field equation, wherein at least one parameter in the conditional concentration field equation is determined based on the current simulation operating conditions of the battery.

[0068] In a specific embodiment, the first concentration field equation describing the solid phase ion concentration parameter is described using Fick's diffusion law, as shown below:

[0069] (1)

[0070] in, represents the ion concentration parameter in the solid phase particles, that is, the solid phase ion concentration parameter; represents radial distance; Indicates the moment; is the diffusion coefficient of the solid particles.

[0071] In a specific embodiment, the second concentration field equation describing the ion concentration parameters in the electrolyte and the isolation membrane using diffusion and electromigration is as follows:

[0072] (2)

[0073] in, It represents the ion concentration parameter in the liquid electrolyte; Indicates distance; Indicates the moment; It represents the diffusion coefficient of ions in liquid electrolyte; represents the number of migrations; j represents the volume current density parameter; is the Faraday constant.

[0074] The electrical parameters also include potential parameters. In one embodiment, the potential parameters of the battery may be the solid phase potential parameters of the battery, which refer to the potentials of various points inside the solid electrode (e.g., lithium cobalt oxide of the positive electrode, graphite of the negative electrode, etc.). Of course, the potential parameters of the battery at each moment may also be the liquid phase potential in the electrolyte and the isolation membrane, which refers to the potential difference formed in the electrolyte and the isolation membrane due to the distribution and migration of charged particles.

[0075] In one embodiment, the electrical parameters include potential parameters, and the potential parameters obtained in this iteration are determined by substituting the concentration parameter of this iteration and the reference body current density parameter of this iteration into a preset potential field equation, and solving the preset potential field equation after substitution to obtain the potential parameters of this iteration. In other words, the potential parameters obtained in this iteration can be obtained using some potential field equations.

[0076] Among them, the preset potential field equations include but are not limited to a first potential field equation that uses Ohm's law to describe the solid phase potential parameters in the electrode, a second potential field equation that uses Ohm's law and Kirchhoff's law to describe the liquid phase potential parameters in the electrolyte and the isolation membrane, and a conditional potential field equation, wherein at least one parameter in the conditional potential field equation is determined based on the current simulation operating conditions of the battery.

[0077] In one embodiment, Ohm's law is used to describe the first potential field equation of the solid phase potential parameters in the electrode, as shown below:

[0078] (3)

[0079] in, represents the volume current density parameter; represents the effective conductivity of the solid phase; represents the solid phase potential parameter.

[0080] In a specific embodiment, a second potential field equation using Ohm's law and Kirchhoff's law is used to describe the liquid phase potential parameters in the electrolyte and the isolation membrane, as shown below:

[0081] (4)

[0082] in, represents the volume current density parameter; It represents the effective conductivity of liquid phase; represents the liquid phase potential parameter; represents the gas constant; Indicates temperature; represents the Faraday constant; represents the activity coefficient; represents the number of migrations; Represents the ion concentration parameter in the liquid electrolyte.

[0083] In one embodiment, the electrical parameters include potential parameters, and the determination of the volume current density parameters obtained in this iteration is specifically as follows: the concentration parameters of this iteration and the potential parameters of this iteration are substituted into the concentration potential field connection equation, and the concentration potential field connection equation after substitution is solved to obtain the volume current density parameters of this iteration. In other words, the volume current density parameters obtained in this iteration can be obtained using some concentration potential field connection equations.

[0084] Among them, the concentration potential field connection equation includes but is not limited to the concentration potential field connection equation that uses the Butler-Volmer equation to describe the electrochemical reaction at the solid-liquid interface and the conditional concentration potential field connection equation, wherein at least one parameter in the conditional concentration potential field connection equation is determined based on the current simulation operating conditions of the battery.

[0085] In one embodiment, the concentration potential field connection equation of the electrochemical reaction at the solid-liquid interface is described using the Butler-Volmer equation as shown below:

[0086] (5)

[0087] in, represents the volume current density parameter; Represents the surface area of ​​solid particles; represents the exchange current density parameter; and represents the forward and reverse reaction coefficients, usually taken as 0.5; The equilibrium potential of the material itself, which usually varies with the solid phase ion concentration parameter Change, recorded as ; represents the ion concentration parameter in the solid phase particles, that is, the solid phase ion concentration parameter; represents the gas constant; Indicates temperature; represents the Faraday constant; represents the solid phase potential parameter; represents the liquid phase potential parameter.

[0088] It should be noted that the first concentration field equation (Equation (1)) that uses Fick's diffusion law to describe the solid phase ion concentration parameters, the second concentration field equation (Equation (2)) that uses diffusion and electromigration to describe the ion concentration parameters in the electrolyte and the isolation membrane, the conditional concentration field equation, the first potential field equation (Equation (3)) that uses Ohm's law to describe the solid phase potential parameters in the electrode, the second potential field equation (Equation (4)) that uses Ohm's law and Kirchhoff's law to describe the liquid phase potential parameters in the electrolyte and the isolation membrane, the conditional potential field equation, the concentration potential field connection equation that uses the Butler-Volmer equation to describe the electrochemical reaction at the solid-liquid interface (Equation (5)), and the conditional concentration potential field connection equation are all partial differential equations with complex forms and cannot be completely solved analytically. Therefore, the first concentration field equation (Equation (1)) that uses Fick's diffusion law to describe the solid phase ion concentration parameters, the second concentration field equation (Equation (2)) that uses diffusion and electromigration to describe the ion concentration parameters in the electrolyte and the isolation membrane, and the conditional concentration field equation are not directly used as the preset concentration field equations; the first potential field equation (Equation (3)) that uses Ohm's law to describe the solid phase potential parameters in the electrode, the second potential field equation (Equation (4)) that uses Ohm's law and Kirchhoff's law to describe the liquid phase potential parameters in the electrolyte and the isolation membrane, and the conditional potential field equation are not directly used as the preset potential field equations; the concentration potential field connection equation (Equation (5)) that uses the Butler-Volmer equation to describe the electrochemical reaction at the solid-liquid interface is not directly used as the concentration potential field connection equation.

[0089] The second concentration field equation (Equation (2)) and the conditional concentration field equation are used to describe the ion concentration parameters in the electrolyte and the isolation membrane by diffusion and electromigration.

[0090] The finite volume method can be used to discretize the partial differential equation of equation (2) in space, and obtain a set of ordinary differential equations with only time differential terms. The finite difference method and other methods can also be used to transform the equation. Among them, the specific method of using the finite volume method to discretize the partial differential equation of equation (2) in space and obtain the ordinary differential equation is as follows:

[0091] like Figure 2 As shown, Figure 2 This is a schematic diagram of the spatial discretization of the partial differential equation, which is divided into n grids along the thickness direction of the battery:

[0092] Each grid has its own Variable (parameter of ion concentration in liquid electrolyte), from arrive There are n variables in total. Take the i-th grid as an example, The variables also satisfy equation (2), that is:

[0093] (6)

[0094] in, represents the ion concentration parameter corresponding to the i-th network; Indicates distance; Indicates the moment; It represents the diffusion coefficient of ions in liquid electrolyte; represents the number of migrations; represents the volume current density parameter; is the Faraday constant.

[0095] According to the finite difference method, Can be used Substituting, the equation is transformed into:

[0096] (7)

[0097] In short:

[0098]

[0099] Perform the above operations on n networks respectively, and obtain n equations of similar form, as shown below:

[0100]

[0101]

[0102]

[0103] …

[0104]

[0105] At this point, equation (2) is transformed into a set of constant differential equations with only time differential terms.

[0106] Furthermore, by combining the ordinary differential equations corresponding to equation (2) with only the time differential term and the conditional concentration field equation corresponding to equation (2), the variables are rearranged and transformed into a set of algebraic differential equations, as shown below:

[0107]

[0108]

[0109] …

[0110] Based on the algebraic differential equations, the ion concentration parameter variable is recorded as a vector C, and the potential parameter variable is recorded as a vector , the volume current density parameter is recorded as a vector j. Therefore, the algebraic differential equations corresponding to equation (2) can be recorded as:

[0111] (8)

[0112] At this point, equation (2) is transformed into a system of algebraic differential equations.

[0113] Furthermore, the time discretization of equation (8) is performed so that the algebraic differential equation system is transformed into an algebraic equation system. In this application, the time partial derivative is discretized using the backward Euler method, and finally transformed into an algebraic equation system (equation (9)) as shown below:

[0114]

[0115] (9)

[0116] Among them, k represents the current moment; k-1 represents the previous moment; dt represents the time step.

[0117] It should be noted that if the second concentration field equation (Formula (2)) that uses diffusion and electromigration to describe the ion concentration parameters in the electrolyte and the isolation membrane and the conditional concentration field equation are used as the preset concentration field equation, then the algebraic equation group (Formula (9)) obtained by combining Formula (2) with the conditional concentration field equation is used as the preset concentration field equation.

[0118] The first concentration field equation (Equation (1)) uses Fick's diffusion law to describe the solid phase ion concentration parameters.

[0119] Under the same grid division, equation (1) is transformed, and it passes through the ordinary differential equations and algebraic differential equations with time differential terms in turn, and finally transforms into an algebraic equation system; then, the algebraic equation system obtained by the final transformation is further discretized in time, and the algebraic equation system after time discretization is as follows:

[0120] (10)

[0121] It should be noted that if the first concentration field equation (Formula (1)) that uses Fick's diffusion law to describe the solid phase ion concentration parameters and the conditional concentration field equation are used as the preset concentration field equation, then the algebraic equation group (Formula (10)) obtained by combining Formula (1) and the conditional concentration equation is used as the preset concentration field equation.

[0122] The first potential field equation (Equation (3)) and the conditional potential field equation that use Ohm's law to describe the solid phase potential parameters in the electrode.

[0123] Under the same grid division, equation (3) is transformed. Since equation (3) does not contain time partial derivatives, the transformation results in a set of algebraic equations. Then, the conditional electric potential field equation corresponding to equation (3) is further transformed to obtain a new set of algebraic equations. Then, the ion concentration parameter variable is recorded as a vector C, and the potential parameter variable is recorded as a vector , the volume current density parameter is recorded as a vector j, and the final algebraic equation system is obtained; then, the final algebraic equation system is further time discretized, and the algebraic equation system after time discretization is as follows:

[0124] (11)

[0125] It should be noted that if the first potential field equation (Equation (3)) and the conditional potential field equation that use Ohm's law to describe the solid phase potential parameters in the electrode are used as the concentration potential field equation, then the algebraic equation group (Equation (11)) obtained by combining Equation (3) and the conditional potential field equation is used as the preset potential field equation.

[0126] The transformation operation of the second potential field equation (Equation (4)) and the conditional potential field equation using Ohm's law and Kirchhoff's law to describe the liquid phase potential parameters in the electrolyte and the isolation membrane is similar to the transformation of Equation (3) and will not be repeated here.

[0127] The concentration potential field connection equation (Equation (5)) and the conditional concentration potential field connection equation for describing the electrochemical reaction at the solid-liquid interface using the Butler-Volmer equation.

[0128] Under the same grid division, each grid has its own Variables (parameters of ion concentration in liquid electrolyte), Variables (solid phase ion concentration parameters), variables (liquid phase potential parameters) and Variable (solid phase potential parameter). Taking the i-th grid as an example, variable, variable, Variables and The variables also satisfy formula (5), that is:

[0129] (12)

[0130] in, represents the volume current density parameter corresponding to the i-th grid; Represents the surface area of ​​solid particles; represents the exchange current density parameter; and represents the forward and reverse reaction coefficients, usually taken as 0.5; The equilibrium potential of the material itself, which usually varies with the solid phase ion concentration parameter Change, recorded as ; represents the ion concentration parameter in the solid phase particles corresponding to the i-th grid, that is, the solid phase ion concentration parameter corresponding to the i-th grid; represents the gas constant; Indicates temperature; represents the Faraday constant; represents the solid phase potential parameter corresponding to the i-th grid; Represents the liquid phase potential parameter corresponding to the i-th grid.

[0131] In short:

[0132]

[0133] Perform the above operations on n networks respectively, and obtain n equations of similar form, as shown below:

[0134]

[0135]

[0136]

[0137] …

[0138]

[0139] At this point, since equation (5) does not contain time partial derivatives, equation (5) is transformed into a system of algebraic equations.

[0140] Furthermore, by combining the algebraic equations corresponding to equation (5) and the conditional concentration potential field connection equation corresponding to equation (5), the variables are rearranged to obtain a new algebraic equation system, as shown below:

[0141]

[0142]

[0143] …

[0144] On the basis of the algebraic equations, the ion concentration parameter variable is recorded as a vector C, and the potential parameter variable is recorded as a vector , the volume current density parameter is recorded as a vector j. Therefore, the algebraic differential equations corresponding to equation (5) can be recorded as:

[0145] (13)

[0146] At this point, equation (5) is transformed into a set of algebraic equations.

[0147] Furthermore, the time discretization of equation (5) is performed, and the discretization result is as follows:

[0148] (14)

[0149] It should be noted that if the concentration potential field connection equation (Equation (5)) and the conditional concentration potential field connection equation that use the Butler-Volmer equation to describe the electrochemical reaction at the solid-liquid interface are used as the concentration potential field connection equation, then the algebraic equation group (Equation (14)) obtained by combining Equation (5) and the conditional concentration potential field connection equation is used as the preset concentration potential field equation.

[0150] In one embodiment, if Figure 3 As shown, Figure 3 This is a flow chart of an embodiment of detecting whether the iterative solution process has converged provided by the present application, which specifically includes the following sub-steps:

[0151] Step S31: During the iterative solution process, based on the concentration parameters and electrical parameters of this iteration, it is detected whether this iteration meets the convergence condition.

[0152] In this embodiment, during the iterative solution process, based on the concentration parameters and electrical parameters of this iteration, it is detected whether this iteration meets the convergence condition. If this iteration does not meet the convergence condition, step S32 is executed; if this iteration meets the convergence condition, step S33 is executed.

[0153] In one embodiment, based on the concentration parameters and electrical parameters of this iteration, it is detected whether this iteration meets the convergence conditions, specifically: obtaining the change value of the battery parameters of this iteration, wherein the battery parameters include the concentration parameters and at least one of the electrical parameters, and the change value of the battery parameters of this iteration is the difference between the battery parameters of this iteration and the battery parameters corresponding to the previous iteration; detecting whether the change value of each battery parameter of this iteration is less than the change threshold value corresponding to each battery parameter; in response to the change value of each battery parameter being less than the change threshold value corresponding to each battery parameter, determining that this iteration meets the convergence conditions.

[0154] For the iterative solution at each moment, the change value of each battery parameter is less than the change threshold corresponding to each battery parameter, indicating that the concentration parameters and electrical parameters obtained by the iterative solution at the current moment may be basically stable and unchanged, indicating that the iterative solution process at the current moment has not converged.

[0155] There is no limitation on the size of the change threshold, and it can be set according to actual use needs.

[0156] Step S32: In response to the current iteration not satisfying the convergence condition, executing the concentration parameter and each electrical parameter determination step of the next iteration.

[0157] For the iterative solution at each moment, when the current iteration does not meet the convergence conditions, it means that the iterative solution process at the current moment has not converged, and the concentration parameters and electrical parameters obtained by the iterative solution may be constantly fluctuating or changing, and cannot produce stable and consistent concentration parameters and electrical parameters. The concentration parameters and electrical parameters obtained in the current iteration cannot accurately reflect the concentration parameters and electrical parameters at the current moment. Therefore, when the current iteration does not meet the convergence conditions, it is necessary to execute the concentration parameter and electrical parameter determination steps of the next iteration until the iterative solution process converges.

[0158] Step S33: In response to the current iteration satisfying the convergence condition, the concentration parameter and each electrical parameter of the current iteration are used as the concentration parameter and each electrical parameter of the current moment.

[0159] For the iterative solution at each moment, when the current iteration meets the convergence condition, it means that the iterative solution process at the current moment has converged, and the concentration parameters and electrical parameters obtained by the iterative solution are basically stable and unchanged, and the concentration parameters and electrical parameters obtained by the current iteration can accurately reflect the concentration parameters and electrical parameters at the current moment. Therefore, when the current iteration meets the convergence condition, the concentration parameters and electrical parameters of this iteration are used as the concentration parameters and electrical parameters at the current moment.

[0160] In one embodiment, the concentration parameters and electrical parameters of at least part of the time are the concentration parameters and electrical parameters of the battery at at least part of the time under simulated operating conditions, wherein the simulated operating conditions include at least one of the following: the ambient temperature of the battery is lower than a preset temperature, the charge and discharge rate of the battery is greater than a preset rate, and the battery state of charge of the battery is greater than a preset state of charge value.

[0161] By obtaining the concentration parameters and electrical parameters of the battery at least at part of the time under the simulated working condition, the simulation result of the battery under the simulated working condition can be obtained based on the electrical parameters and concentration parameters under the simulated working condition, thereby realizing the simulation of the battery under the simulated working condition.

[0162] Among them, the simulation working condition can be that the ambient temperature of the battery is lower than the preset temperature, that is, the simulation working condition is low temperature, which can realize the simulation of the battery at low temperature. The simulation working condition can also be that the charge and discharge rate of the battery is greater than the preset rate, that is, the simulation working condition is high rate charge and discharge, which can realize the simulation of the battery under high rate charge and discharge. The simulation working condition can also be that the battery state of charge of the battery is greater than the preset state of charge value, that is, the simulation working condition is high state of charge, which can realize the simulation of the battery at a high state of charge.

[0163] It should be noted that there is no limitation on the preset temperature, preset ratio and preset state of charge value, and they can be set according to actual use needs.

[0164] Step S12: obtaining the simulation result of the battery based on the concentration parameters and electrical parameters at each moment.

[0165] In this embodiment, based on the concentration parameters and electrical parameters at each moment, the simulation result of the battery is obtained to achieve the simulation of the battery.

[0166] At least the concentration parameters and electrical parameters of some moments are obtained by iteratively solving based on the electrical parameters of the previous moment. For the iterative solution of any moment in the partial moments, the estimated volume current density parameters in each iteration are determined by using the reference current density parameters and the rate characterization value of the change of the volume current density parameters with the concentration parameters. The determined estimated volume current density parameters are closer to the actual volume current density parameters than the reference volume current density parameters. Therefore, using the estimated volume current density parameters in the current iteration to determine the concentration parameters in the current iteration can make it easier to obtain the optimal solution for the concentration parameters and accelerate the convergence speed of the iterative solution at each moment.

[0167] Since the convergence speed of the iterative solution at any moment in the partial moments is accelerated, the time required to determine the concentration parameters and electrical parameters at each moment is shortened and the efficiency is improved. Therefore, based on the concentration parameters and electrical parameters at each moment, the time required to determine the simulation results of the battery is shortened and the efficiency is improved, that is, efficient simulation of the battery is achieved.

[0168] In a specific example, for a constant current discharge condition simulation, MATLAB is used to implement the original solution and the present solution (a solution using the battery simulation method provided in the present application) respectively.

[0169] In this scheme, the time step length dt selected in this scheme is 5s, which can calculate to the discharge cut-off time. In the original scheme, the time step length dt selected is 0.5s, and it still cannot converge at 1500s, resulting in calculation crash. Among them, the time statistics of this scheme are: total calculation time-4.4s, time step length-5s, number of time steps-330, total number of iterations-1203; the time statistics of the original scheme are: total calculation time-14.3s, time step length-0.5s, number of time steps-3030, total number of iterations-2030.

[0170] It can be seen that although this scheme performs iterative calculations in the solution of each time step, thanks to the estimated volume current density parameters added during iteration, the convergence speed is very fast, the average number of iterations does not exceed 5 times, and a larger time step length (5s) can be used, and the total number of iterations is only 1203 times. In the original scheme, it can be considered that there is no complete iteration in each time step, so the number of time steps is the total number of iterations, but the original scheme has a higher requirement for the time step length (0.5s), so the total number of iterations reaches 3030 times. Therefore, the total calculation time is far less than this scheme. Even at a time step length of 0.5s, the original scheme still cannot converge at the end of the discharge, and the step length needs to be further reduced.

[0171] See also Figure 4 , Figure 4 It is a structural schematic diagram of an embodiment of a battery simulation device provided by the present application. The battery simulation device 40 includes a simulation module 41 and a determination module 42. The simulation module 41 is used to obtain the concentration parameters and electrical parameters of the battery at each moment, wherein the electrical parameters include the body current density parameters, and the concentration parameters and electrical parameters at least part of the moment are obtained by iterative solution based on the electrical parameters at the previous moment. In the iterative solution process, the concentration parameters obtained in this iteration are determined based on the estimated body current density parameters of this iteration, and the estimated body current density parameters of this iteration are determined by using the reference body current density parameters and the rate characterization value of the body current density parameters changing with the concentration parameters. The reference body current density parameters of non-first iterations are the body current density parameters obtained in the previous iteration, and the reference body current density parameters of the first iteration are the body current density parameters at the previous moment. The electrical parameters obtained in this iteration are determined based on the concentration parameters obtained in this iteration; the determination module 42 is used to obtain the simulation results of the battery based on the concentration parameters and electrical parameters at each moment.

[0172] Among them, the simulation module 41 is also used to determine the estimated body current density parameters of this iteration, including: obtaining the reference body current density parameters and reference concentration parameters corresponding to this iteration, wherein the reference concentration parameters of non-first iterations are the concentration parameters obtained in the previous iteration, and the reference concentration parameters of the first iteration are the concentration parameters at the previous moment; using the rate characterization value, the reference body current density parameters and reference concentration parameters corresponding to this iteration to determine the estimated body current density parameters of this iteration.

[0173] Among them, the simulation module 41 is used to use the rate characterization value, the reference body current density parameter corresponding to this iteration and the reference concentration parameter to determine the estimated body current density parameter of this iteration, including: constructing a first relationship, wherein the first relationship characterizes the relationship between the rate characterization value and the change of the body current density parameter of this iteration, and the change of the concentration parameter of this iteration, the change of the body current density parameter of this iteration is the difference between the estimated body current density parameter of this iteration and the reference body current density parameter, and the change of the concentration parameter of this iteration is the difference between the concentration parameter of this iteration and the reference concentration parameter; using the first relationship, obtaining a characterization function that characterizes the estimated body current density parameter, and the characterization function uses the concentration parameter of this iteration as a variable.

[0174] Among them, the above-mentioned first relationship is that the rate characterization value is equal to the ratio between the change in the volume current density parameter of this iteration and the change in the concentration parameter of this iteration; the characterization function is the sum of the reference volume current density parameter and the concentration term, and the concentration term is the product of the rate characterization value and the change in the concentration parameter of this iteration.

[0175] Among them, the above-mentioned rate characterization value is the ratio between the change of the body current density parameter of the last iteration and the change of the concentration parameter of the last iteration, wherein the change of the body current density parameter of the last iteration is the difference between the body current density parameter of the last iteration and the reference body current density parameter of the last iteration, and the change of the concentration parameter of the last iteration is the difference between the concentration parameter of the last iteration and the reference concentration parameter of the last iteration, wherein the reference concentration parameter of the non-first iteration is the concentration parameter obtained in the last iteration, and the reference concentration parameter of the first iteration is the concentration parameter at the previous moment.

[0176] The simulation module 41 is used to determine the concentration parameters obtained in this iteration, including: substituting the estimated volume current density parameters of this iteration into the preset concentration field equation, and solving the preset concentration field equation after substitution to obtain the concentration parameters of this iteration.

[0177] Among them, the above-mentioned preset concentration field equation includes at least one of the following: a first concentration field equation that uses Fick's diffusion law to describe the solid phase ion concentration parameters, a second concentration field equation that uses diffusion and electromigration to describe the ion concentration parameters in the electrolyte and the isolation membrane, and a conditional concentration field equation, wherein at least one parameter in the conditional concentration field equation is determined based on the current simulation operating conditions of the battery; and / or, the above-mentioned electrical parameters also include potential parameters, and the simulation module 41 is used to substitute the estimated body current density parameters of this iteration into the preset concentration field equation, including: substituting the potential parameters and the estimated body current density parameters of this iteration into the preset concentration field equation respectively.

[0178] Among them, the above-mentioned electrical parameters also include potential parameters; the simulation module 41 is used to determine the potential parameters obtained in this iteration, including: substituting the concentration parameters of this iteration and the reference body current density parameters of this iteration into the preset potential field equation, and solving the preset potential field equation after substitution to obtain the potential parameters of this iteration.

[0179] Among them, the above-mentioned preset potential field equations include at least one of the following: a first potential field equation that uses Ohm's law to describe the solid phase potential parameters in the electrode, a second concentration field equation that uses Ohm's law and Kirchhoff's law to describe the liquid phase potential parameters in the electrolyte and the isolation membrane, and a conditional potential field equation, wherein at least one parameter in the conditional potential field equation is determined based on the current simulation operating conditions of the battery.

[0180] Among them, the above-mentioned electrical parameters also include potential parameters; the simulation module 41 is used to determine the body current density parameters obtained in this iteration, including: substituting the concentration parameters of this iteration and the potential parameters of this iteration into the concentration potential field connection equation, and solving the substituted concentration potential field connection equation to obtain the body current density parameters of this iteration.

[0181] Among them, the above-mentioned concentration potential field connection equation includes at least one of the following: a concentration potential field connection equation that uses the Butler-Volmer equation to describe the electrochemical reaction at the solid-liquid interface, and a conditional concentration potential field connection equation, wherein at least one parameter in the conditional concentration potential field connection equation is determined based on the current simulation operating conditions of the battery.

[0182] Among them, the simulation module 41 is used to detect whether the current iteration meets the convergence conditions based on the concentration parameters and electrical parameters of the current iteration during the iterative solution process; in response to the current iteration not meeting the convergence conditions, execute the steps of determining the concentration parameters and electrical parameters of the next iteration; and / or, in response to the current iteration meeting the convergence conditions, use the concentration parameters and electrical parameters of the current iteration as the concentration parameters and electrical parameters at the current moment.

[0183] Among them, the simulation module 41 is used to detect whether this iteration meets the convergence conditions based on the concentration parameters and electrical parameters of this iteration, including: obtaining the change value of the battery parameters of this iteration, wherein the battery parameters include the concentration parameters and at least one of the electrical parameters, and the change value of the battery parameters of this iteration is the difference between the battery parameters of this iteration and the battery parameters corresponding to the previous iteration; detecting whether the change value of each battery parameter of this iteration is less than the change threshold value corresponding to each battery parameter; in response to the change value of each battery parameter being less than the change threshold value corresponding to each battery parameter, determining that this iteration meets the convergence conditions.

[0184] Among them, the concentration parameters and electrical parameters of at least part of the time mentioned above are the concentration parameters and electrical parameters of the battery at least part of the time under simulated working conditions, wherein the simulated working conditions include at least one of the following: the ambient temperature of the battery is lower than the preset temperature, the charge and discharge rate of the battery is greater than the preset rate, and the battery state of charge of the battery is greater than the preset state of charge value.

[0185] See also Figure 5 , Figure 5 : is a schematic diagram of the structure of an embodiment of a battery simulation device provided by the present application. The battery simulation device 50 includes a memory 51 and a processor 52 coupled to each other, and the processor 52 is used to execute program instructions stored in the memory 51 to implement the steps of any of the above-mentioned battery simulation method embodiments. In a specific implementation scenario, the battery simulation device 50 may include but is not limited to: a microcomputer, a server, and in addition, the battery simulation device 50 may also include mobile devices such as laptops and tablet computers, which are not limited here.

[0186] Specifically, the processor 52 is used to control itself and the memory 51 to implement the steps of any of the above-mentioned battery simulation method embodiments. The processor 52 can also be called a CPU (Central Processing Unit). The processor 52 may be an integrated circuit chip with signal processing capabilities. The processor 52 can also be a general-purpose processor, a digital signal processor (Digital Signal Processor, DSP), an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), a field-programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. In addition, the processor 52 can be implemented by an integrated circuit chip.

[0187] See also Figure 6 , Figure 6It is a structural diagram of an embodiment of a computer-readable storage medium provided by the present application. The computer-readable storage medium 60 of the embodiment of the present application stores a program instruction 61, and when the program instruction 61 is executed, it implements the method provided by any embodiment of the battery simulation method of the present application and any non-conflicting combination. Among them, the program instruction 61 can form a program file and be stored in the above-mentioned computer-readable storage medium 60 in the form of a software product, so that a computer device (which can be a personal computer, a server, or a network device, etc.) executes all or part of the steps of the methods of each embodiment of the present application. The aforementioned computer-readable storage medium 60 includes: various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a disk or an optical disk, or a terminal device such as a computer, a server, a mobile phone, and a tablet.

[0188] If the technical solution of this application involves personal information, the product using the technical solution of this application has clearly informed the personal information processing rules and obtained the individual's voluntary consent before processing the personal information. If the technical solution of this application involves sensitive personal information, the product using the technical solution of this application has obtained the individual's separate consent before processing the sensitive personal information, and at the same time meets the "explicit consent" requirement. For example, on personal information collection devices such as cameras, clear and prominent signs are set to inform that the personal information collection scope has been entered and personal information will be collected. If the individual voluntarily enters the collection scope, it is deemed that he or she agrees to the collection of his or her personal information; or on the device that processes personal information, the personal information processing rules are notified by obvious signs / information, and the individual's authorization is obtained through pop-up information or by asking the individual to upload his or her personal information; among them, the personal information processing rules may include information such as the personal information processor, the purpose of personal information processing, the processing method, and the type of personal information processed.

[0189] The above description is only an implementation method of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A battery simulation method, characterized in that: The method comprises: Acquire concentration parameters and electrical parameters of the battery at each moment, wherein the electrical parameters include a body current density parameter, and the concentration parameters and electrical parameters at at least some moments are obtained by iteratively solving based on the electrical parameters at the previous moment. In the iterative solving process, the concentration parameter obtained in this iteration is determined based on the estimated body current density parameter of this iteration, and the estimated body current density parameter of this iteration is determined by using a reference body current density parameter and a rate characterization value of the body current density parameter changing with the concentration parameter. The reference body current density parameter of a non-first iteration is the body current density parameter obtained in the previous iteration, and the reference body current density parameter of the first iteration is the body current density parameter at the previous moment. Each of the electrical parameters obtained in this iteration is determined based on the concentration parameter obtained in this iteration; Based on the concentration parameters and electrical parameters at each moment, obtaining simulation results of the battery; The step of determining the estimated volume current density parameter in this iteration includes: Obtain the reference volume current density parameter and reference concentration parameter corresponding to this iteration, wherein the reference concentration parameter for a non-first iteration is the concentration parameter obtained in the last iteration, and the reference concentration parameter for the first iteration is the concentration parameter at the last moment; Constructing a first relationship; wherein the first relationship represents the relationship between the rate characterization value and the volume current density parameter change of this iteration, and the concentration parameter change of this iteration, wherein the volume current density parameter change of this iteration is the difference between the estimated volume current density parameter of this iteration and the reference volume current density parameter, and the concentration parameter change of this iteration is the difference between the concentration parameter of this iteration and the reference concentration parameter; Using the first relationship, a characterization function characterizing the estimated volume current density parameter is obtained, wherein the characterization function uses the concentration parameter of this iteration as a variable; wherein the first relationship is that the rate characterization value is equal to the ratio between the volume current density parameter change of this iteration and the concentration parameter change of this iteration, the characterization function is the sum of the reference volume current density parameter and a concentration term, and the concentration term is the product of the rate characterization value and the concentration parameter change of this iteration; The steps for determining the concentration parameters obtained in this iteration include: Substitute the characterization function characterizing the estimated volume current density parameter into a preset concentration field equation, and solve the preset concentration field equation after substitution to obtain the concentration parameter of this iteration; wherein the preset concentration field equation is obtained by transforming a first concentration field equation and a conditional concentration field equation that use Fick's diffusion law to describe the solid phase ion concentration parameter, or by transforming a second concentration field equation and a conditional concentration field equation that use diffusion and electromigration to describe the ion concentration parameter in the electrolyte and the isolation membrane, at least one parameter in the conditional concentration field equation is determined based on the current simulation operating condition of the battery, and the preset concentration field equation is , represents the estimated volume current density parameter of this iteration, and dt represents the time step.

2. The method according to claim 1, characterized in that The rate characterization value is the ratio between the change in the body current density parameter of the last iteration and the change in the concentration parameter of the last iteration, wherein the change in the body current density parameter of the last iteration is the difference between the body current density parameter of the last iteration and the reference body current density parameter of the last iteration, and the change in the concentration parameter of the last iteration is the difference between the concentration parameter of the last iteration and the reference concentration parameter of the last iteration, wherein the reference concentration parameter of the non-first iteration is the concentration parameter obtained in the last iteration, and the reference concentration parameter of the first iteration is the concentration parameter at the last moment.

3. The method according to claim 1, characterized in that The electrical parameters also include potential parameters, and substituting the characterization function characterizing the estimated volume current density parameter into a preset concentration field equation includes: The potential parameter of this iteration and the characterization function characterizing the estimated volume current density parameter are respectively substituted into the preset concentration field equation.

4. The method according to claim 1, characterized in that: The electrical parameters also include potential parameters; the steps for determining the potential parameters obtained in this iteration include: Substitute the concentration parameter of this iteration and the reference body current density parameter of this iteration into the preset potential field equation, and solve the preset potential field equation after substitution to obtain the potential parameter of this iteration.

5. The method according to claim 4, characterized in that The preset potential field equation is obtained by transforming a first potential field equation and a conditional potential field equation that use Ohm's law to describe the solid phase potential parameters in the electrode, or by transforming a second potential field equation and a conditional potential field equation that use Ohm's law and Kirchhoff's law to describe the liquid phase potential parameters in the electrolyte and the isolation membrane, wherein at least one parameter in the conditional potential field equation is determined based on the current simulation operating conditions of the battery.

6. The method according to claim 1, characterized in that The electrical parameters also include potential parameters; the steps for determining the volume current density parameters obtained in this iteration include: Substitute the concentration parameter of this iteration and the potential parameter of this iteration into the concentration potential field connection equation, and solve the concentration potential field connection equation after substitution to obtain the volume current density parameter of this iteration.

7. The method according to claim 6, characterized in that The concentration potential field connection equation is obtained by transforming the concentration potential field connection equation that uses the Butler-Volmer equation to describe the electrochemical reaction at the solid-liquid interface and the conditional concentration potential field connection equation, wherein at least one parameter in the conditional concentration potential field connection equation is determined based on the current simulation operating conditions of the battery.

8. The method according to claim 1, characterized in that The method further comprises: In the iterative solution process, based on the concentration parameters and electrical parameters of this iteration, it is detected whether this iteration meets the convergence conditions; In response to the current iteration not satisfying the convergence condition, executing the step of determining the concentration parameter and each electrical parameter of the next iteration; and / or, In response to this iteration satisfying the convergence condition, the concentration parameter and each electrical parameter of this iteration are used as the concentration parameter and each electrical parameter at the current moment.

9. The method according to claim 8, characterized in that The step of detecting whether the current iteration satisfies the convergence condition based on the concentration parameter and each electrical parameter of the current iteration includes: Obtaining a change value of a battery parameter of this iteration, wherein the battery parameter includes the concentration parameter and at least one of the electrical parameters, and the change value of the battery parameter of this iteration is a difference between the battery parameter of this iteration and the battery parameter corresponding to the previous iteration; Detecting whether the change value of each battery parameter in this iteration is less than the change threshold corresponding to each battery parameter; In response to the change values ​​of each of the battery parameters being less than the change thresholds corresponding to the battery parameters, it is determined that the current iteration meets a convergence condition.

10. The method according to claim 8, characterized in that The concentration parameters and electrical parameters of at least part of the time are the concentration parameters and electrical parameters of the battery at least part of the time under simulated working conditions, wherein the simulated working conditions include at least one of the following: the ambient temperature of the battery is lower than a preset temperature, the charge and discharge rate of the battery is greater than a preset rate, and the battery state of charge of the battery is greater than a preset state of charge value.

11. A battery simulation device, characterized in that: The device comprises: A simulation module, used to obtain the concentration parameters and electrical parameters of the battery at each moment, wherein the electrical parameters include a body current density parameter, and the concentration parameters and electrical parameters at at least some moments are obtained by iteratively solving based on the electrical parameters at the previous moment. In the iterative solution process, the concentration parameter obtained in this iteration is determined based on the estimated body current density parameter of this iteration, and the estimated body current density parameter of this iteration is determined by using a reference body current density parameter and a rate characterization value of the body current density parameter changing with the concentration parameter. The reference body current density parameter of a non-first iteration is the body current density parameter obtained in the previous iteration, and the reference body current density parameter of the first iteration is the body current density parameter at the previous moment. Each of the electrical parameters obtained in this iteration is determined based on the concentration parameter obtained in this iteration; A determination module, used to obtain a simulation result of the battery based on the concentration parameters and electrical parameters at each moment; The step of determining the estimated volume current density parameter in this iteration includes: Obtain the reference volume current density parameter and reference concentration parameter corresponding to this iteration, wherein the reference concentration parameter for a non-first iteration is the concentration parameter obtained in the last iteration, and the reference concentration parameter for the first iteration is the concentration parameter at the last moment; Constructing a first relationship; wherein the first relationship represents the relationship between the rate characterization value and the volume current density parameter change of this iteration, and the concentration parameter change of this iteration, wherein the volume current density parameter change of this iteration is the difference between the estimated volume current density parameter of this iteration and the reference volume current density parameter, and the concentration parameter change of this iteration is the difference between the concentration parameter of this iteration and the reference concentration parameter; Using the first relationship, a characterization function characterizing the estimated volume current density parameter is obtained, wherein the characterization function uses the concentration parameter of this iteration as a variable; wherein the first relationship is that the rate characterization value is equal to the ratio between the volume current density parameter change of this iteration and the concentration parameter change of this iteration, the characterization function is the sum of the reference volume current density parameter and a concentration term, and the concentration term is the product of the rate characterization value and the concentration parameter change of this iteration; The steps for determining the concentration parameters obtained in this iteration include: Substitute the characterization function characterizing the estimated volume current density parameter into a preset concentration field equation, and solve the preset concentration field equation after substitution to obtain the concentration parameter of this iteration; wherein the preset concentration field equation is obtained by transforming a first concentration field equation and a conditional concentration field equation that use Fick's diffusion law to describe the solid phase ion concentration parameter, or by transforming a second concentration field equation and a conditional concentration field equation that use diffusion and electromigration to describe the ion concentration parameter in the electrolyte and the isolation membrane, at least one parameter in the conditional concentration field equation is determined based on the current simulation operating condition of the battery, and the preset concentration field equation is , represents the estimated volume current density parameter of this iteration, and dt represents the time step.

12. A battery simulation device, characterized in that: The battery simulation device comprises a memory and a processor, the memory stores program instructions, and the processor is used to execute the program instructions to implement the battery simulation method according to any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store program instructions, and the program instructions can be executed to implement the battery simulation method according to any one of claims 1 to 10.

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