Battery tab parameter determination method and apparatus based on electrochemical simulation model

Abstract

The present application relates to the technical field of batteries. Disclosed are a battery tab parameter determination method and apparatus based on an electrochemical simulation model. The method comprises: acquiring a plurality of schemes to be simulated, wherein all of said schemes correspond to the same battery structure, and each of said schemes has a corresponding battery structure parameter, the battery structure parameter comprising a battery tab width / battery tab quantity; inputting the battery structure parameter corresponding to each of said schemes into an electrochemical simulation model having a pre-constructed battery structure for simulation, so as to obtain a simulation result of each of said schemes; on the basis of the simulation results corresponding to all of said schemes, determining an optimal simulation scheme from among all of said schemes; and determining a battery tab parameter of the optimal simulation scheme to be an optimal tab parameter of the battery structure.

Description

Method and device for determining battery tab parameters based on electrochemical simulation model

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on February 21, 2024, with application number 2024101945223. The entire contents of the above application are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of battery technology, and in particular to a method and device for determining battery tab parameters based on an electrochemical simulation model. Background Art

[0003] Against the backdrop of carbon neutrality, new energy batteries have experienced rapid development. With the current market share of prismatic aluminum-cased batteries reaching 90%, the design of prismatic aluminum-cased batteries has drawn considerable attention.

[0004] During the use of square batteries, heat loss directly determines the energy efficiency of the battery. Therefore, it is crucial to optimize the design of the battery structure to reduce the heat loss of the battery during use. For example, the design of the tab parameters of the battery structure is crucial. However, the design of the battery structure in related technologies is usually carried out using the orthogonal experimental method. However, the orthogonal experimental method has many factors that reduce the efficiency of determining the tab parameters in the battery structure, such as the large number of required solutions, high sample preparation costs, and long subsequent sample testing cycles. This can easily reduce the development efficiency of battery products. Therefore, it is particularly important to propose a technical solution to improve the efficiency of determining the tab parameters in the battery structure. Technical issues

[0005] This application aims to solve the problems of multiple schemes required for battery tab parameter design, high sample preparation costs, and long subsequent sample testing cycles, and to provide a method and device for determining battery tab parameters based on an electrochemical simulation model to improve the efficiency of determining tab parameters in the battery structure, thereby facilitating the improvement of battery product development efficiency. Technical Solutions

[0006] In a first aspect, the present application provides a method for determining battery tab parameters based on an electrochemical simulation model, the method comprising:

[0007] Acquire multiple schemes to be simulated, all of which correspond to the same battery structure, and each of which has corresponding battery structure parameters, wherein the battery structure parameters include at least a battery tab width and / or a battery tab number;

[0008] Inputting the battery structure parameters corresponding to each of the schemes to be simulated into a pre-built electrochemical simulation model of the battery structure for simulation, and obtaining simulation results for each of the schemes to be simulated;

[0009] Determining an optimal simulation scheme from all the schemes to be simulated according to the simulation results corresponding to all the schemes to be simulated;

[0010] The battery tab parameters of the optimal simulation solution are determined as the optimal tab parameters of the battery structure.

[0011] In a second aspect, the present application provides a device for determining battery tab parameters based on an electrochemical simulation model, the device comprising:

[0012] an acquisition module, configured to acquire a plurality of schemes to be simulated, wherein all the schemes to be simulated correspond to the same battery structure, and each scheme to be simulated has corresponding battery structure parameters, wherein the battery structure parameters include at least a battery tab width and / or a battery tab number;

[0013] A simulation module, configured to input the battery structure parameters corresponding to each of the schemes to be simulated into a pre-built electrochemical simulation model of the battery structure to perform simulation and obtain simulation results for each of the schemes to be simulated;

[0014] A determination module, configured to determine an optimal simulation scheme from all the schemes to be simulated based on the simulation results corresponding to all the schemes to be simulated;

[0015] The determination module is further configured to determine the battery tab parameters of the optimal simulation solution as the optimal tab parameters of the battery structure.

[0016] In a third aspect, the present application provides a device for determining battery tab parameters based on an electrochemical simulation model, the device comprising:

[0017] a memory storing executable program code;

[0018] a processor coupled to the memory;

[0019] The processor calls the executable program code stored in the memory to execute the method for determining battery tab parameters based on the electrochemical simulation model disclosed in the first aspect of the present application.

[0020] In a fourth aspect, the present application further provides a computer storage medium storing computer instructions, which, when called, are used to execute the method for determining battery tab parameters based on the electrochemical simulation model disclosed in the first aspect of the present application. Beneficial effects

[0021] The present application obtains multiple schemes to be simulated, all of which correspond to the same battery structure, and each scheme to be simulated has corresponding battery structure parameters, and the battery structure parameters include at least the width of the battery tab and / or the number of battery tabs; the battery structure parameters corresponding to each scheme to be simulated are input into an electrochemical simulation model of a pre-built battery structure for simulation, and the simulation results of each scheme to be simulated are obtained; based on the simulation results corresponding to all schemes to be simulated, the optimal simulation scheme is determined from all schemes to be simulated; the battery tab parameters of the optimal simulation scheme are determined as the optimal tab parameters of the battery structure. It can be seen that the implementation of the present application can obtain multiple schemes to be simulated, and the battery structure parameters corresponding to each scheme to be simulated are input into an electrochemical simulation model of a pre-built battery structure for simulation, and the simulation results of each scheme to be simulated are obtained, which can improve the simulation efficiency and accuracy of each scheme to be simulated, and then determine the optimal simulation scheme from all schemes to be simulated based on the simulation results corresponding to all schemes to be simulated, which can improve the efficiency and accuracy of determining the optimal simulation scheme from all schemes to be simulated based on the simulation results corresponding to all schemes to be simulated quickly, and then determine the battery tab parameters of the optimal simulation scheme as the optimal tab parameters of the battery structure. The method of quickly determining the optimal tab parameters through the electrochemical simulation model can improve the efficiency and accuracy of determining the optimal tab parameters in the battery structure based on the rapidly determined optimal simulation scheme, thereby facilitating the improvement of the development efficiency of the battery product based on the rapidly determined tab parameters. Compared with the orthogonal experimental method used in related technologies, the method of quickly determining the optimal tab parameters through the electrochemical simulation model can simplify each scheme to be simulated, thereby improving the simulation efficiency and speed of each scheme to be simulated to a certain extent, thereby facilitating the improvement of the efficiency and speed of determining the optimal simulation scheme. The electrochemical simulation model can reduce the sample preparation cost of the battery and improve the development efficiency of the battery product to a certain extent. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] FIG1 is a flow chart of a method for determining battery tab parameters based on an electrochemical simulation model disclosed in an embodiment of the present application;

[0023] FIG2 is a flow chart of another method for determining battery tab parameters based on an electrochemical simulation model disclosed in an embodiment of the present application;

[0024] FIG3 is a schematic diagram showing the relationship between the DC internal resistance of a battery and its internal resistance change rate and all the simulation schemes disclosed in an embodiment of the present application;

[0025] FIG4 is a chart of temperature rise data of all simulation schemes disclosed in an embodiment of the present application;

[0026] FIG5 is a graph showing the SOC differences of all the schemes to be simulated according to an embodiment of the present application;

[0027] FIG6 is a schematic structural diagram of a device for determining battery tab parameters based on an electrochemical simulation model disclosed in an embodiment of the present application;

[0028] FIG7 is a schematic structural diagram of another device for determining battery tab parameters based on an electrochemical simulation model disclosed in an embodiment of the present application;

[0029] FIG8 is a schematic structural diagram of another device for determining battery tab parameters based on an electrochemical simulation model disclosed in an embodiment of the present application. Modes for Carrying Out the Invention

[0030] In one embodiment, in the first aspect of the present application, determining the optimal simulation scheme of the battery structure from all the schemes to be simulated based on the simulation results corresponding to all the schemes to be simulated includes:

[0031] Analyze a performance parameter set of the battery structure in each of the schemes to be simulated according to the simulation results corresponding to each of the schemes to be simulated, where the performance parameter set includes one or more performance parameters;

[0032] Performing a comprehensive analysis on the performance parameter sets of the battery structure in all the schemes to be simulated to obtain comprehensive analysis results of all the schemes to be simulated;

[0033] According to the comprehensive analysis result, one of the to-be-simulated schemes of the battery structure is selected as the optimal simulation scheme of the battery structure.

[0034] In one embodiment, in the first aspect of the present application, the simulation result includes simulated voltage data and / or SOC data and / or temperature field data; wherein, when the simulation result includes the simulated voltage data, the simulation result also includes measured voltage data, wherein the measured voltage data of all the schemes to be simulated are the same;

[0035] Furthermore, analyzing the performance parameter set of the battery structure in each of the schemes to be simulated based on the simulation results corresponding to each of the schemes to be simulated includes:

[0036] When the simulation result includes the simulated voltage data, calculating the battery DC internal resistance of each of the schemes to be simulated according to the simulated voltage data corresponding to each of the schemes to be simulated and the measured voltage data; and / or,

[0037] When the simulation result includes the SOC data, analyzing the SOC data corresponding to each of the schemes to be simulated to obtain the SOC distribution of each of the schemes to be simulated; and / or,

[0038] When the simulation result includes the temperature field data, analyzing the temperature field data corresponding to each of the schemes to be simulated to obtain the temperature rise data of each of the schemes to be simulated;

[0039] The performance parameter set includes the battery DC internal resistance and / or the SOC distribution and / or the temperature rise data.

[0040] In one embodiment, in the first aspect of the present application, the battery structure parameters corresponding to each of the schemes to be simulated are input into a pre-built electrochemical simulation model of the battery structure for simulation, and the simulation results of each of the schemes to be simulated are obtained, including:

[0041] For any of the schemes to be simulated, inputting battery structure parameters corresponding to the scheme to be simulated into a pre-built electrochemical simulation model of the battery structure, and simulating to obtain a lithium ion concentration set of the battery structure in the scheme to be simulated, wherein the lithium ion concentration set of the battery structure includes the surface lithium ion concentration of coating particles of the electrode coating of the battery structure and the average lithium ion concentration of the coating particles;

[0042] Calculating SOC data corresponding to the scheme to be simulated based on the surface lithium ion concentration of the coating particles and the average lithium ion concentration of the coating particles in the scheme to be simulated, and determining the SOC data corresponding to the scheme to be simulated as a simulation result of the scheme to be simulated;

[0043] and / or,

[0044] For any of the schemes to be simulated, the battery structure parameters corresponding to the scheme to be simulated are input into a pre-built electrochemical simulation model of the battery structure, and the temperature calculation parameters of the scheme to be simulated are obtained by simulation, wherein the temperature calculation parameters include the parameters required by a preset temperature field calculation formula;

[0045] The temperature calculation parameters of the scheme to be simulated are input into the temperature field calculation formula for calculation to obtain the temperature field data of the scheme to be simulated, and the temperature field data of the scheme to be simulated is determined as the simulation result of the scheme to be simulated.

[0046] In one embodiment, in the first aspect of the present application, the comprehensive analysis result of each of the schemes to be simulated includes one or more combinations of the internal resistance change rate of each of the schemes to be simulated, the temperature rise data of each of the schemes to be simulated, and the SOC distribution uniformity of each of the schemes to be simulated;

[0047] Furthermore, selecting one of all the to-be-simulated schemes of the battery structure according to the comprehensive analysis result as the optimal simulation scheme of the battery structure includes:

[0048] When the comprehensive analysis result includes the internal resistance change rate, the temperature rise data and the SOC distribution uniformity, one of the schemes to be simulated for the battery structure is selected as the optimal simulation scheme for the battery structure, in which the internal resistance change rate is greater than or equal to the preset change rate, the temperature rise data is less than or equal to the preset temperature rise data, and the SOC distribution uniformity meets the preset distribution conditions.

[0049] In one embodiment, in the first aspect of the present application, the simulated voltage data includes a simulated voltage at each of a plurality of simulation moments within a preset simulation duration, and the measured voltage data includes a measured voltage at each of a plurality of test moments within a preset test duration;

[0050] And, the method further comprises:

[0051] generating a voltage correction coefficient for each of the schemes to be simulated according to all the measured voltages of the battery structure in each of the schemes to be simulated and all the simulated voltages corresponding to each of the schemes to be simulated;

[0052] According to the voltage correction coefficient of each of the schemes to be simulated, the simulation voltage data corresponding to each of the schemes to be simulated is corrected to obtain the target simulation voltage data corresponding to each of the schemes to be simulated.

[0053] In one embodiment, in the first aspect of the present application, generating a voltage correction coefficient for each of the schemes to be simulated based on all the measured voltages of the battery structure in each of the schemes to be simulated and all the simulated voltages corresponding to each of the schemes to be simulated includes:

[0054] Establishing a first relationship curve of the battery structure in each of the scenarios to be simulated based on all the measured voltages of the battery structure in each of the scenarios to be simulated, wherein the first relationship curve is used to represent a correspondence between the measured voltage and time;

[0055] Establishing a second relationship curve of the battery structure in each of the schemes to be simulated according to all the simulation voltages corresponding to each of the schemes to be simulated, wherein the second relationship curve is used to represent a corresponding relationship between simulation voltage and time;

[0056] For each of the schemes to be simulated, a voltage correction coefficient of the scheme to be simulated is generated according to a first relationship curve of the battery structure in the scheme to be simulated and a second relationship curve of the battery structure in the scheme to be simulated.

[0057] In one embodiment, in the second aspect of the present application, the determination module determines the optimal simulation scheme of the battery structure from all the schemes to be simulated based on the simulation results corresponding to all the schemes to be simulated, specifically including:

[0058] Analyze a performance parameter set of the battery structure in each of the schemes to be simulated according to the simulation results corresponding to each of the schemes to be simulated, where the performance parameter set includes one or more performance parameters;

[0059] Performing a comprehensive analysis on the performance parameter sets of the battery structure in all the schemes to be simulated to obtain comprehensive analysis results of all the schemes to be simulated;

[0060] According to the comprehensive analysis result, one of the to-be-simulated schemes of the battery structure is selected as the optimal simulation scheme of the battery structure.

[0061] In one embodiment, in the second aspect of the present application, the simulation result includes simulated voltage data and / or SOC data and / or temperature field data; wherein, when the simulation result includes the simulated voltage data, the simulation result also includes measured voltage data, wherein the measured voltage data of all the schemes to be simulated are the same;

[0062] Furthermore, the determining module analyzes the performance parameter set of the battery structure in each of the schemes to be simulated based on the simulation results corresponding to each of the schemes to be simulated, including:

[0063] When the simulation result includes the simulated voltage data, calculating the battery DC internal resistance of each of the schemes to be simulated according to the simulated voltage data corresponding to each of the schemes to be simulated and the measured voltage data; and / or,

[0064] When the simulation result includes the SOC data, analyzing the SOC data corresponding to each of the schemes to be simulated to obtain the SOC distribution of each of the schemes to be simulated; and / or,

[0065] When the simulation result includes the temperature field data, analyzing the temperature field data corresponding to each of the schemes to be simulated to obtain the temperature rise data of each of the schemes to be simulated;

[0066] The performance parameter set includes the battery DC internal resistance and / or the SOC distribution and / or the temperature rise data.

[0067] In one embodiment, in the second aspect of the present application, the determination module inputs the battery structure parameters corresponding to each of the schemes to be simulated into a pre-built electrochemical simulation model of the battery structure for simulation, and obtains the simulation results of each of the schemes to be simulated in a manner specifically including:

[0068] For any of the schemes to be simulated, inputting battery structure parameters corresponding to the scheme to be simulated into a pre-built electrochemical simulation model of the battery structure, and simulating to obtain a lithium ion concentration set of the battery structure in the scheme to be simulated, wherein the lithium ion concentration set of the battery structure includes the surface lithium ion concentration of coating particles of the electrode coating of the battery structure and the average lithium ion concentration of the coating particles;

[0069] Calculating SOC data corresponding to the scheme to be simulated based on the surface lithium ion concentration of the coating particles and the average lithium ion concentration of the coating particles in the scheme to be simulated, and determining the SOC data corresponding to the scheme to be simulated as a simulation result of the scheme to be simulated;

[0070] and / or,

[0071] For any of the schemes to be simulated, the battery structure parameters corresponding to the scheme to be simulated are input into a pre-built electrochemical simulation model of the battery structure, and the temperature calculation parameters of the scheme to be simulated are obtained by simulation, wherein the temperature calculation parameters include the parameters required by a preset temperature field calculation formula;

[0072] The temperature calculation parameters of the scheme to be simulated are input into the temperature field calculation formula for calculation to obtain the temperature field data of the scheme to be simulated, and the temperature field data of the scheme to be simulated is determined as the simulation result of the scheme to be simulated.

[0073] In one embodiment, in the second aspect of the present application, the comprehensive analysis result of each of the schemes to be simulated includes one or more combinations of the internal resistance change rate of each of the schemes to be simulated, the temperature rise data of each of the schemes to be simulated, and the SOC distribution uniformity of each of the schemes to be simulated;

[0074] Furthermore, the determination module selects one of all the to-be-simulated schemes of the battery structure as the optimal simulation scheme of the battery structure according to the comprehensive analysis result, specifically including:

[0075] When the comprehensive analysis result includes the internal resistance change rate, the temperature rise data and the SOC distribution uniformity, one of the schemes to be simulated for the battery structure is selected as the optimal simulation scheme for the battery structure, in which the internal resistance change rate is greater than or equal to the preset change rate, the temperature rise data is less than or equal to the preset temperature rise data, and the SOC distribution uniformity meets the preset distribution conditions.

[0076] In one embodiment, in the second aspect of the present application, the simulated voltage data includes a simulated voltage at each of a plurality of simulation moments within a preset simulation duration, and the measured voltage data includes a measured voltage at each of a plurality of test moments within a preset test duration;

[0077] And, the device further comprises:

[0078] a generating module, configured to generate a voltage correction coefficient for each of the schemes to be simulated based on all the measured voltages of the battery structure in each of the schemes to be simulated and all the simulated voltages corresponding to each of the schemes to be simulated;

[0079] The correction module is used to correct the simulation voltage data corresponding to each of the schemes to be simulated according to the voltage correction coefficient of each of the schemes to be simulated, so as to obtain the target simulation voltage data corresponding to each of the schemes to be simulated.

[0080] In one embodiment, in the second aspect of the present application, the generation module generates the voltage correction coefficient for each of the schemes to be simulated based on all the measured voltages of the battery structure in each of the schemes to be simulated and all the simulated voltages corresponding to each of the schemes to be simulated, specifically including:

[0081] Establishing a first relationship curve of the battery structure in each of the scenarios to be simulated based on all the measured voltages of the battery structure in each of the scenarios to be simulated, wherein the first relationship curve is used to represent a correspondence between the measured voltage and time;

[0082] Establishing a second relationship curve of the battery structure in each of the schemes to be simulated according to all the simulation voltages corresponding to each of the schemes to be simulated, wherein the second relationship curve is used to represent a corresponding relationship between simulation voltage and time;

[0083] For each of the schemes to be simulated, a voltage correction coefficient of the scheme to be simulated is generated according to a first relationship curve of the battery structure in the scheme to be simulated and a second relationship curve of the battery structure in the scheme to be simulated.

[0084] The present application discloses a method and device for determining battery tab parameters based on an electrochemical simulation model, which can obtain multiple schemes to be simulated, and input the battery structure parameters corresponding to each scheme to be simulated into an electrochemical simulation model of a pre-built battery structure for simulation, thereby obtaining a simulation result for each scheme to be simulated, thereby improving the simulation efficiency and accuracy of each scheme to be simulated, and then determining the optimal simulation scheme from all schemes to be simulated based on the simulation results corresponding to all schemes to be simulated. The method and device can improve the efficiency and accuracy of determining the optimal simulation scheme from all schemes to be simulated based on the simulation results corresponding to all schemes to be simulated that are quickly determined, and then determine the battery tab parameters of the optimal simulation scheme. As the optimal tab parameters of the battery structure, the efficiency and accuracy of determining the optimal tab parameters in the battery structure can be improved based on the rapidly determined optimal simulation scheme, thereby facilitating the improvement of the efficiency of battery product development based on the rapidly determined tab parameters. Furthermore, the method of rapidly determining the optimal tab parameters through the electrochemical simulation model, compared to the orthogonal experimental method used in related technologies, can simplify each scheme to be simulated, thereby improving the simulation efficiency and speed of each scheme to be simulated to a certain extent, thereby facilitating the improvement of the efficiency and speed of determining the optimal simulation scheme. Furthermore, the use of the electrochemical simulation model can reduce the cost of battery sample preparation and improve the efficiency of battery product development to a certain extent. These are described in detail below.

[0085] Example 1

[0086] Please refer to Figure 1, which is a flow chart of a method for determining battery tab parameters based on an electrochemical simulation model disclosed in an embodiment of the present application. The method for determining battery tab parameters based on an electrochemical simulation model described in Figure 1 can be applied to a device for determining battery tab parameters based on an electrochemical simulation model, wherein the device may include a determination device or a determination server, wherein the determination server may include a cloud server or a local server, which is not limited in the embodiment of the present application. As shown in Figure 1, the method for determining battery tab parameters based on an electrochemical simulation model may include the following operations:

[0087] 101. Obtain multiple solutions to be simulated.

[0088] In the embodiment of the present application, all the schemes to be simulated correspond to the same battery structure. Among them, the battery structure can be composed of a positive electrode current collector, a positive electrode coating, a separator, a negative electrode coating, a negative electrode current collector, a positive electrode tab and a negative electrode tab, etc. There are corresponding battery structure parameters for each scheme to be simulated. Among them, the battery structure parameters include at least the width of the battery tab and / or the number of battery tabs. Specifically, all the schemes to be simulated can be schemes generated after configuring different battery structure parameters for the above-mentioned battery structure. Among them, the battery structure parameters of each scheme to be simulated can be obtained by the simulation personnel according to the historical test experience of the battery samples, or can be obtained by the computer through statistics of the historical test experience of the battery samples, and the embodiment of the present application does not limit this.

[0089] 102. Input the battery structure parameters corresponding to each to-be-simulated scheme into a pre-built electrochemical simulation model of the battery structure for simulation, and obtain the simulation results of each to-be-simulated scheme.

[0090] In an embodiment of the present application, before inputting the battery structure parameters corresponding to each to-be-simulated scenario into a pre-built electrochemical simulation model of the battery structure for simulation and obtaining the simulation results of each to-be-simulated scenario, the method may further include: constructing a geometric model of the battery structure in finite element drawing software, and then inputting the geometric model of the battery structure into an initialized electrochemical simulation model to obtain the electrochemical simulation model of the constructed battery structure. This can improve the accuracy of establishing the electrochemical simulation model including the battery structure based on the geometric model of the battery structure, and can improve the update efficiency and speed of the electrochemical simulation model when the battery structure parameters are subsequently updated to update the electrochemical model.

[0091] 103. According to the simulation results corresponding to all the schemes to be simulated, the optimal simulation scheme is determined from all the schemes to be simulated.

[0092] 104. Determine the battery tab parameters of the optimal simulation solution as the optimal tab parameters of the battery structure.

[0093] In the embodiment of the present application, the optimal tab width and / or the optimal number of tabs included in the optimal tab parameters can be put into the production of actual batteries corresponding to the battery structure.

[0094] It can be seen that the method for determining the battery tab parameters based on the electrochemical simulation model described in FIG1 can obtain multiple schemes to be simulated, and input the battery structure parameters corresponding to each scheme to be simulated into the electrochemical simulation model of the battery structure that has been pre-built for simulation, and obtain the simulation results of each scheme to be simulated, which can improve the simulation efficiency and simulation accuracy of each scheme to be simulated, and then determine the optimal simulation scheme from all schemes to be simulated based on the simulation results corresponding to all schemes to be simulated quickly. The efficiency and accuracy of determining the optimal simulation scheme from all schemes to be simulated can be improved based on the simulation results corresponding to all schemes to be simulated that are quickly determined, and then the battery tab parameters of the optimal simulation scheme can be determined. As the optimal tab parameters of the battery structure, the efficiency and accuracy of determining the optimal tab parameters in the battery structure can be improved based on the rapidly determined optimal simulation scheme, which is beneficial to improving the development efficiency of battery products based on the rapidly determined tab parameters. The method of rapidly determining the optimal tab parameters through the electrochemical simulation model can simplify each scheme to be simulated, thereby improving the simulation efficiency and simulation speed of each scheme to be simulated to a certain extent, compared with the orthogonal experimental method used in related technologies, and thus is beneficial to improving the efficiency and speed of determining the optimal simulation scheme. The use of the electrochemical simulation model can reduce the sample preparation cost of the battery and can improve the development efficiency of the battery product to a certain extent.

[0095] Example 2

[0096] Please refer to Figure 2, which is a flow chart of a method for determining battery tab parameters based on an electrochemical simulation model disclosed in an embodiment of the present application. The method for determining battery tab parameters based on an electrochemical simulation model described in Figure 2 can be applied to a device for determining battery tab parameters based on an electrochemical simulation model, wherein the device may include a determination device or a determination server, wherein the determination server may include a cloud server or a local server, which is not limited in the embodiment of the present application. As shown in Figure 2, the method for determining battery tab parameters based on an electrochemical simulation model may include the following operations:

[0097] 201. Obtain multiple solutions to be simulated.

[0098] 202. Input the battery structure parameters corresponding to each to-be-simulated scheme into a pre-built electrochemical simulation model of the battery structure for simulation, and obtain simulation results for each to-be-simulated scheme.

[0099] In an embodiment of the present application, the simulation result may include simulated voltage data and / or SOC data and / or temperature field data. Wherein, when the simulation result includes simulated voltage data, the simulation result also includes measured voltage data. Wherein, the measured voltage data of all the schemes to be simulated are the same, that is, the measured voltage data will not change with the change of the scheme to be simulated. Wherein, the measured voltage data may be the static open circuit voltage (OCV) data obtained when simulating any scheme to be simulated, or may be the data obtained by measuring the actual battery sample corresponding to any scheme to be simulated. Specifically, when the measured voltage data is simulated by a certain scheme to be simulated, or the measured voltage data is measured by the actual battery sample corresponding to a certain scheme to be simulated, when simulating the remaining schemes to be simulated except the above-mentioned certain scheme to be simulated in all the schemes to be simulated, since the measured voltage data of all the schemes to be simulated are the same, there is no need to simulate the measured voltage data of the remaining schemes to be simulated.

[0100] 203. Analyze the performance parameter set of the battery structure in each to-be-simulated scheme based on the simulation results corresponding to each to-be-simulated scheme.

[0101] In an embodiment of the present application, the performance parameter set includes one or more performance parameters. Each performance parameter can be used to represent the performance of the above-mentioned battery structure in the scheme to be simulated. The performance parameter set may include the battery DC internal resistance and / or SOC distribution and / or temperature rise data. Specifically, when the simulation result corresponding to any scheme to be simulated includes simulation voltage data, the performance parameter set of the battery structure in the scheme to be simulated includes the battery DC internal resistance; when the simulation result corresponding to any scheme to be simulated includes SOC data, the performance parameter set of the battery structure in the scheme to be simulated includes SOC distribution; when the simulation result corresponding to any scheme to be simulated includes temperature field data, the performance parameter set of the battery structure in the scheme to be simulated includes temperature rise data, which is not limited in the embodiment of the present application.

[0102] 204. Comprehensively analyze the performance parameter sets of the battery structure in all the schemes to be simulated to obtain comprehensive analysis results of all the schemes to be simulated.

[0103] In an embodiment of the present application, the comprehensive analysis results of each scheme to be simulated may include one or more combinations of the internal resistance change rate of each scheme to be simulated, the temperature rise data of each scheme to be simulated, and the SOC distribution uniformity of each scheme to be simulated, which is not limited in the embodiment of the present application.

[0104] 205. Based on the comprehensive analysis results, one of the battery structure schemes to be simulated is selected as the optimal simulation scheme for the battery structure.

[0105] 206. Determine the battery tab parameters of the optimal simulation solution as the optimal tab parameters of the battery structure.

[0106] In the embodiment of the present application, for other descriptions of steps 201 to 206, please refer to the detailed description of steps 101 to 104 in embodiment 1, and the embodiment of the present application will not be repeated.

[0107] It can be seen that the method for determining the battery tab parameters based on the electrochemical simulation model described in Figure 2 can obtain multiple schemes to be simulated, and input the battery structure parameters corresponding to each scheme to be simulated into the electrochemical simulation model of the battery structure that has been pre-built for simulation, and obtain the simulation results of each scheme to be simulated, which can improve the simulation efficiency and simulation accuracy of each scheme to be simulated. Subsequently, according to the simulation results corresponding to all the schemes to be simulated, the optimal simulation scheme is determined from all the schemes to be simulated, which can improve the efficiency and accuracy of determining the optimal simulation scheme from all the schemes to be simulated based on the simulation results corresponding to all the schemes to be simulated that are quickly determined, and then determine the battery tab parameters of the optimal simulation scheme. As the optimal tab parameters of the battery structure, the efficiency and accuracy of determining the optimal tab parameters in the battery structure can be improved based on the rapidly determined optimal simulation scheme, which is beneficial to improving the development efficiency of battery products based on the rapidly determined tab parameters. The method of rapidly determining the optimal tab parameters through the electrochemical simulation model can simplify each scheme to be simulated, thereby improving the simulation efficiency and simulation speed of each scheme to be simulated to a certain extent, compared with the orthogonal experimental method used in related technologies, and thus is beneficial to improving the efficiency and speed of determining the optimal simulation scheme. The use of the electrochemical simulation model can reduce the sample preparation cost of the battery and can improve the development efficiency of the battery product to a certain extent. In addition, it is also possible to analyze the performance parameter set of the battery structure in each scheme to be simulated based on the simulation results corresponding to each scheme to be simulated, and to improve the analysis accuracy of the performance parameter set of each scheme to be simulated based on the simulation results corresponding to each scheme to be simulated. Subsequently, the performance parameter set of the battery structure obtained by accurate analysis in all schemes to be simulated is comprehensively analyzed to obtain a comprehensive analysis result of all schemes to be simulated, which can improve the accuracy of the comprehensive analysis of the performance parameter set of the scheme to be simulated, and then, based on the accurate comprehensive analysis result obtained by comprehensive analysis, select one of the schemes to be simulated from all the schemes to be simulated for the battery structure as the optimal simulation scheme for the battery structure, which can improve the accuracy of selecting the optimal simulation scheme.

[0108] In an optional embodiment, the above step 203 analyzes the performance parameter set of the battery structure in each to-be-simulated scheme according to the simulation results corresponding to each to-be-simulated scheme, including:

[0109] When the simulation results include simulated voltage data, the DC internal resistance of the battery for each to-be-simulated solution is calculated based on the simulated voltage data and the measured voltage data corresponding to each to-be-simulated solution; and / or

[0110] When the simulation results include SOC data, analyzing the SOC data corresponding to each to-be-simulated solution to obtain the SOC distribution of each to-be-simulated solution; and / or,

[0111] When the simulation results include temperature field data, the temperature field data corresponding to each to-be-simulated scheme is analyzed to obtain the temperature rise data of each to-be-simulated scheme.

[0112] In the embodiment of the present application, the calculation formula of the battery DC internal resistance is as follows:

[0113]

[0114] in, is the DC internal resistance of the battery, is the measured voltage data (i.e. the battery open circuit voltage), is the simulated voltage data (i.e. battery operating voltage), For current.

[0115] It can be seen that this optional embodiment can calculate the battery DC internal resistance of the scheme based on the measured voltage data and the simulated voltage data of each scheme when the simulation results include the measured voltage data of the battery structure and the simulated voltage data of the battery structure in each scheme to be simulated, and use it as the simulation result of the scheme, thereby improving the calculation accuracy of the battery DC internal resistance; and / or, when the simulation results include the SOC data of each scheme, analyze the SOC data of each scheme to obtain the SOC distribution, and use it as the simulation result of the scheme, thereby improving the analysis accuracy of the SOC distribution; and / or, when the simulation results include the temperature field data of each scheme, analyze the temperature field data of each scheme to obtain the temperature rise data of the scheme, and use it as the simulation result of the scheme, thereby improving the analysis accuracy of the temperature rise data, and can also improve the diversity and flexibility of each simulation result, and is conducive to improving the richness of each simulation result.

[0116] In this optional embodiment, in one embodiment, the battery structure parameters corresponding to each to-be-simulated scheme are input into a pre-built electrochemical simulation model of the battery structure for simulation in step 202 to obtain simulation results for each to-be-simulated scheme, including:

[0117] For any scenario to be simulated, the battery structure parameters corresponding to the scenario to be simulated are input into a pre-built electrochemical simulation model of the battery structure, and the lithium ion concentration set of the battery structure in the scenario to be simulated is obtained by simulation, wherein the lithium ion concentration set of the battery structure includes the surface lithium ion concentration of the coating particles of the electrode coating of the battery structure and the average lithium ion concentration of the coating particles;

[0118] Calculating SOC data corresponding to the scheme to be simulated based on the surface lithium ion concentration of the coating particles and the average lithium ion concentration of the coating particles in the scheme to be simulated, and determining the SOC data corresponding to the scheme to be simulated as a simulation result of the scheme to be simulated;

[0119] and / or,

[0120] For any scheme to be simulated, the battery structure parameters corresponding to the scheme to be simulated are input into the pre-built electrochemical simulation model of the battery structure, and the temperature calculation parameters of the scheme to be simulated are obtained by simulation. The temperature calculation parameters include the parameters required by the preset temperature field calculation formula;

[0121] The temperature calculation parameters of the scheme to be simulated are input into the temperature field calculation formula for calculation to obtain the temperature field data of the scheme to be simulated, and the temperature field data of the scheme to be simulated is determined as the simulation result of the scheme to be simulated.

[0122] In the embodiment of the present application, the calculation formula for the SOC data (i.e., state of charge) corresponding to each simulation scheme is specifically as follows:

[0123]

[0124] in, is the surface lithium ion concentration of the coating particles in the corresponding simulation scenario, is the average lithium ion concentration of the coating particles in the corresponding simulation scenario.

[0125] In the embodiment of the present application, the temperature field calculation formula may optionally include a temperature field calculation formula based on the law of conservation of energy. The temperature field calculation formula corresponding to each simulation scheme is as follows:

[0126]

[0127] in, is the density, is the specific heat capacity, is the temperature field data, for Thermal conductivity in the direction, for Thermal conductivity in the direction, for Thermal conductivity in the direction, is the heat production power.

[0128] In this optional embodiment, the calculation formula for heat generation power may include:

[0129]

[0130] in, is the polarization potential, is the electrode equilibrium potential.

[0131] It can be seen that this optional implementation method can accurately calculate the simulation results of each scheme to be simulated (the simulation results include simulation voltage data and / or SOC data and / or temperature field data) based on the rich calculation formulas contained in the pre-built electrochemical simulation model of the battery structure, which is conducive to improving the diversity and flexibility of the simulation results of each scheme to be simulated, and is conducive to improving the richness of the simulation results of each scheme to be simulated based on the comprehensive calculation formula.

[0132] In another optional embodiment, the above step 205 selects one of all battery structure simulation schemes as the optimal simulation scheme for the battery structure based on the comprehensive analysis results, which may include:

[0133] When the comprehensive analysis results include the internal resistance change rate, temperature rise data and SOC distribution uniformity, one of the battery structure simulation schemes to be simulated, in which the internal resistance change rate is greater than or equal to the preset change rate, the temperature rise data is less than or equal to the preset temperature rise data and the SOC distribution uniformity meets the preset distribution conditions, is selected as the optimal simulation scheme for the battery structure.

[0134] Optionally, when the comprehensive analysis result includes the internal resistance change rate, one of the internal resistance change rate greater than or equal to the preset change rate is selected from all the battery structure schemes to be simulated as the optimal simulation scheme for the battery structure; or, when the comprehensive analysis result includes temperature rise data, one of the temperature rise data less than or equal to the preset temperature rise data is selected from all the battery structure schemes to be simulated as the optimal simulation scheme for the battery structure; or, when the comprehensive analysis result includes SOC distribution uniformity, one of the SOC distribution uniformity meeting the preset distribution conditions is selected from all the battery structure schemes to be simulated as the optimal simulation scheme for the battery structure. This can improve the diversity and flexibility of the selection of the optimal simulation scheme based on the diversity of the comprehensive analysis results.

[0135] In an embodiment of the present application, optionally, the temperature rise data of each scheme to be simulated can be used to represent the temperature difference between the maximum temperature and the minimum temperature in each scheme to be simulated. Optionally, the preset distribution condition can be used to represent the condition corresponding to whether the SOC data of all positive electrode coating particles are uniformly distributed. Optionally, the SOC distribution uniformity of each scheme to be simulated can be represented by the SOC difference between the maximum SOC data in each scheme to be simulated and the minimum SOC data in the scheme to be simulated. Specifically, whether the SOC distribution uniformity meets the preset distribution condition is determined in the following manner: for each scheme to be simulated, it is determined whether the SOC difference of the scheme to be simulated is less than or equal to the preset SOC difference. When it is determined that the SOC difference of the scheme to be simulated is less than or equal to the preset SOC difference, it is determined that the SOC distribution uniformity of the scheme to be simulated meets the preset distribution condition; when it is determined that the SOC difference of the scheme to be simulated is greater than the preset SOC difference, it is determined that the SOC distribution uniformity of the scheme to be simulated does not meet the preset distribution condition. This can improve the accuracy of determining whether the SOC distribution uniformity of the scheme to be simulated meets the preset distribution condition.

[0136] In the embodiment of the present application, the preset rate of change can optionally be 12.5%, 13%, or any other set value. Alternatively, the preset temperature rise data can be 1°C, 0.8°C, or any other set value. Alternatively, the preset SOC difference can be 0.016, 0.0158, or any other set value, and this embodiment of the present application does not limit this.

[0137] In the embodiment of the present application, each scheme to be simulated optionally has a corresponding simulation order. Optionally, when each scheme to be simulated includes the battery tab width, all schemes to be simulated can be arranged from small to large according to the battery tab width. In this case, the internal resistance change rate obtained is positively correlated with the battery tab width of the scheme to be simulated.

[0138] For example, assuming there are tab solutions A, B, C, and D, and tab solution A includes tab width a, tab solution B includes tab width b, tab solution C includes tab width c, and tab solution D includes two tab widths b. Tab width a is smaller than tab width b, and tab width b is smaller than tab width c. When the comprehensive analysis result only includes the internal resistance change rate, as shown in FIG3 , for example, FIG3 is a schematic diagram of the relationship between the DC internal resistance of a battery and its internal resistance change rate for all simulated solutions disclosed in an embodiment of the present application, and all simulated solutions. In this case, the first internal resistance change rate (e.g., internal resistance decreasing rate) between tab solution A and tab solution B is smaller than the second internal resistance change rate between tab solution B and tab solution C, and the second internal resistance change rate between tab solution B and tab solution C is greater than the third internal resistance change rate between tab solution C and tab solution D. That is, the internal resistance change rate between tab solution B and tab solution C is the largest, and therefore tab solution C can be determined as the optimal tab solution. When the comprehensive analysis results only include temperature rise data, as shown in Figure 4, which is a chart of temperature rise data for all simulated solutions disclosed in the embodiments of this application, the temperature rise data for tab solution C is the smallest, so solution C can be determined as the optimal tab solution. When the comprehensive analysis results only include SOC distribution uniformity, as shown in Figure 5, which is a chart of SOC differences for all simulated solutions disclosed in the embodiments of this application, the SOC differences for solution C and solution D are both less than the preset SOC differences, so solution C or solution D can be determined as the optimal tab solution.

[0139] It can be seen that this optional embodiment can, when the comprehensive analysis results include the internal resistance change rate, temperature rise data and SOC distribution uniformity, select one of the schemes to be simulated for the battery structure, in which the internal resistance change rate is greater than or equal to the preset change rate, the temperature rise data is less than or equal to the preset temperature rise data, and the SOC distribution uniformity meets the preset distribution conditions, as the optimal simulation scheme for the battery structure, which can improve the accuracy and reliability of the selection of the optimal simulation scheme for the battery structure.

[0140] In another optional embodiment, the simulated voltage data includes the simulated voltage at each of multiple simulation moments within a preset simulation duration, and the measured voltage data includes the measured voltage at each of multiple test moments within a preset test duration. Furthermore, the method may further include:

[0141] Generate a voltage correction coefficient for each scheme to be simulated based on all measured voltages of the battery structure in each scheme to be simulated and all simulated voltages corresponding to each scheme to be simulated;

[0142] According to the voltage correction coefficient of each to-be-simulated scheme, the simulation voltage data corresponding to each to-be-simulated scheme is corrected to obtain the target simulation voltage data corresponding to each to-be-simulated scheme.

[0143] In the embodiment of the present application, the corrected target simulation voltage data can be used to recalculate the battery DC internal resistance, so that the calculated battery DC internal resistance is more accurate.

[0144] It can be seen that this optional embodiment can generate a voltage correction coefficient for each scheme to be simulated based on all measured voltages of the battery structure in each scheme to be simulated and all simulated voltages corresponding to each scheme to be simulated, which can improve the generation accuracy of each voltage correction coefficient. Subsequently, based on the calculated accurate voltage correction coefficient, the simulated voltage data corresponding to each scheme to be simulated is corrected to obtain the target simulated voltage data corresponding to each scheme to be simulated, which can improve the correction accuracy of the target simulated voltage data corresponding to each scheme to be simulated.

[0145] In this optional embodiment, in one embodiment, the above-mentioned generating a voltage correction coefficient for each scheme to be simulated based on all measured voltages of the battery structure in each scheme to be simulated and all simulated voltages corresponding to each scheme to be simulated may include:

[0146] Establishing a first relationship curve of the battery structure in each to-be-simulated scenario based on all measured voltages of the battery structure in each to-be-simulated scenario;

[0147] Establishing a second relationship curve of the battery structure in each to-be-simulated scheme according to all simulation voltages corresponding to each to-be-simulated scheme;

[0148] For each scheme to be simulated, a voltage correction coefficient of the scheme to be simulated is generated according to the first relationship curve of the battery structure in the scheme to be simulated and the second relationship curve of the battery structure in the scheme to be simulated.

[0149] In the embodiment of the present application, the first relationship curve is used to represent the correspondence between the measured voltage and the time, and the second relationship curve is used to represent the correspondence between the simulated voltage and the time.

[0150] It can be seen that this optional implementation method can establish a first relationship curve of the battery structure in each scheme to be simulated based on all measured voltages of the battery structure in each scheme to be simulated, which can improve the accuracy of establishing the first relationship curve of the battery structure in each scheme to be simulated, and establish a second relationship curve of the battery structure in each scheme to be simulated based on all simulated voltages corresponding to each scheme to be simulated, which can improve the accuracy of establishing the second relationship curve of the battery structure in each scheme to be simulated. Subsequently, based on the accurately established first relationship curve and second relationship curve of each scheme to be simulated, a voltage correction coefficient of each scheme to be simulated is generated, which can improve the accuracy and reliability of generating the voltage correction coefficient of each scheme to be simulated, thereby facilitating improving the accuracy and reliability of subsequent correction of the simulation voltage data based on the generated accurate voltage correction coefficient.

[0151] Example 3

[0152] Please refer to Figure 6, which is a schematic diagram of the structure of a device for determining battery tab parameters based on an electrochemical simulation model disclosed in an embodiment of the present application. The device for determining battery tab parameters based on an electrochemical simulation model described in Figure 6 may include a determination device or a determination server, wherein the determination server may include a cloud server or a local server, which is not limited in this embodiment of the present application. As shown in Figure 6, the device for determining battery tab parameters based on an electrochemical simulation model may include:

[0153] The acquisition module 301 is used to obtain multiple schemes to be simulated, all of which correspond to the same battery structure, and each scheme to be simulated has corresponding battery structure parameters, which at least include battery tab width and / or battery tab number.

[0154] The simulation module 302 is used to input the battery structure parameters corresponding to each to-be-simulated scheme into a pre-built electrochemical simulation model of the battery structure to perform simulation and obtain the simulation results of each to-be-simulated scheme.

[0155] The determination module 303 is configured to determine the optimal simulation scheme from all the schemes to be simulated according to the simulation results corresponding to all the schemes to be simulated.

[0156] The determination module 303 is further configured to determine the battery tab parameters of the optimal simulation solution as the optimal tab parameters of the battery structure.

[0157] It can be seen that the device for determining the battery tab parameters based on the electrochemical simulation model described in FIG6 can obtain multiple schemes to be simulated, and input the battery structure parameters corresponding to each scheme to be simulated into the electrochemical simulation model of the battery structure that has been pre-built for simulation, and obtain the simulation results of each scheme to be simulated, which can improve the simulation efficiency and simulation accuracy of each scheme to be simulated, and then determine the optimal simulation scheme from all schemes to be simulated based on the simulation results corresponding to all schemes to be simulated. It can improve the efficiency and accuracy of determining the optimal simulation scheme from all schemes to be simulated based on the simulation results corresponding to all schemes to be simulated that are quickly determined, and then determine the battery tab parameters of the optimal simulation scheme. As the optimal tab parameters of the battery structure, the efficiency and accuracy of determining the optimal tab parameters in the battery structure can be improved based on the rapidly determined optimal simulation scheme, which is beneficial to improving the development efficiency of battery products based on the rapidly determined tab parameters. The method of rapidly determining the optimal tab parameters through the electrochemical simulation model can simplify each scheme to be simulated, thereby improving the simulation efficiency and simulation speed of each scheme to be simulated to a certain extent, compared with the orthogonal experimental method used in related technologies, and thus is beneficial to improving the efficiency and speed of determining the optimal simulation scheme. The use of the electrochemical simulation model can reduce the sample preparation cost of the battery and can improve the development efficiency of the battery product to a certain extent.

[0158] In an optional embodiment, the determination module 303 determines the optimal simulation scheme for the battery structure from all the schemes to be simulated based on the simulation results corresponding to all the schemes to be simulated, which may specifically include:

[0159] Analyze the performance parameter set of the battery structure in each to-be-simulated scheme according to the simulation results corresponding to each to-be-simulated scheme, where the performance parameter set includes one or more performance parameters;

[0160] Comprehensively analyze the performance parameter sets of the battery structure in all the schemes to be simulated to obtain the comprehensive analysis results of all the schemes to be simulated;

[0161] According to the comprehensive analysis results, one of the battery structure schemes to be simulated is selected as the optimal simulation scheme of the battery structure.

[0162] It can be seen that this optional embodiment can analyze the performance parameter set of the battery structure in each scheme to be simulated based on the simulation results corresponding to each scheme to be simulated, and can improve the analysis accuracy of the performance parameter set of each scheme to be simulated based on the simulation results corresponding to each scheme to be simulated. Subsequently, the performance parameter set of the battery structure obtained by the accurate analysis is comprehensively analyzed in all schemes to be simulated to obtain the comprehensive analysis results of all schemes to be simulated, which can improve the accuracy of the comprehensive analysis of the performance parameter set of the scheme to be simulated, and then according to the accurate comprehensive analysis results obtained by the comprehensive analysis, select one of the schemes to be simulated from all the schemes to be simulated of the battery structure as the optimal simulation scheme of the battery structure, which can improve the accuracy of the selection of the optimal simulation scheme.

[0163] In this optional embodiment, in one embodiment, the simulation results include simulated voltage data and / or SOC data and / or temperature field data; wherein, when the simulation results include simulated voltage data, the simulation results also include measured voltage data, wherein the measured voltage data of all the schemes to be simulated are the same. Furthermore, the determination module 303 analyzes the performance parameter set of the battery structure in each scheme to be simulated based on the simulation results corresponding to each scheme to be simulated, specifically including:

[0164] When the simulation results include simulated voltage data, the DC internal resistance of the battery for each to-be-simulated solution is calculated based on the simulated voltage data and the measured voltage data corresponding to each to-be-simulated solution; and / or

[0165] When the simulation results include SOC data, analyzing the SOC data corresponding to each to-be-simulated solution to obtain the SOC distribution of each to-be-simulated solution; and / or,

[0166] When the simulation results include temperature field data, the temperature field data corresponding to each to-be-simulated scheme is analyzed to obtain the temperature rise data of each to-be-simulated scheme;

[0167] The performance parameter set includes battery DC internal resistance and / or SOC distribution and / or temperature rise data.

[0168] It can be seen that this optional implementation method can calculate the battery DC internal resistance of the scheme based on the measured voltage data and the simulated voltage data of each scheme when the simulation results include the measured voltage data of the battery structure and the simulated voltage data of the battery structure in each scheme to be simulated, and use it as the simulation result of the scheme, thereby improving the calculation accuracy of the battery DC internal resistance; and / or, when the simulation results include the SOC data of each scheme, analyze the SOC data of each scheme to obtain the SOC distribution, and use it as the simulation result of the scheme, thereby improving the analysis accuracy of the SOC distribution; and / or, when the simulation results include the temperature field data of each scheme, analyze the temperature field data of each scheme to obtain the temperature rise data of the scheme, and use it as the simulation result of the scheme, thereby improving the analysis accuracy of the temperature rise data, and can also improve the diversity and flexibility of each simulation result, and is conducive to improving the richness of each simulation result.

[0169] In this optional embodiment, the simulation module 302 may optionally input the battery structure parameters corresponding to each to-be-simulated scheme into a pre-built electrochemical simulation model of the battery structure for simulation. The method of obtaining the simulation results of each to-be-simulated scheme may specifically include:

[0170] For any scenario to be simulated, the battery structure parameters corresponding to the scenario to be simulated are input into a pre-built electrochemical simulation model of the battery structure, and the lithium ion concentration set of the battery structure in the scenario to be simulated is obtained by simulation, wherein the lithium ion concentration set of the battery structure includes the surface lithium ion concentration of the coating particles of the electrode coating of the battery structure and the average lithium ion concentration of the coating particles;

[0171] Calculating SOC data corresponding to the scheme to be simulated based on the surface lithium ion concentration of the coating particles and the average lithium ion concentration of the coating particles in the scheme to be simulated, and determining the SOC data corresponding to the scheme to be simulated as a simulation result of the scheme to be simulated;

[0172] and / or,

[0173] For any scheme to be simulated, the battery structure parameters corresponding to the scheme to be simulated are input into the pre-built electrochemical simulation model of the battery structure, and the temperature calculation parameters of the scheme to be simulated are obtained by simulation. The temperature calculation parameters include the parameters required by the preset temperature field calculation formula;

[0174] The temperature calculation parameters of the scheme to be simulated are input into the temperature field calculation formula for calculation to obtain the temperature field data of the scheme to be simulated, and the temperature field data of the scheme to be simulated is determined as the simulation result of the scheme to be simulated.

[0175] It can be seen that this optional implementation method can also accurately calculate the simulation results of each scheme to be simulated (the simulation results include simulation voltage data and / or SOC data and / or temperature field data) based on the rich calculation formulas contained in the pre-built electrochemical simulation model of the battery structure, which is conducive to improving the diversity and flexibility of the simulation results of each scheme to be simulated, and is conducive to improving the richness of the simulation results of each scheme to be simulated based on the comprehensive calculation formula.

[0176] In this optional embodiment, as another optional implementation, the comprehensive analysis results of each to-be-simulated scheme include one or more combinations of the internal resistance change rate of each to-be-simulated scheme, the temperature rise data of each to-be-simulated scheme, and the SOC distribution uniformity of each to-be-simulated scheme. Furthermore, the determination module 303 selects one of all to-be-simulated battery structure schemes as the optimal simulation scheme for the battery structure based on the comprehensive analysis results, specifically including:

[0177] When the comprehensive analysis results include the internal resistance change rate, temperature rise data and SOC distribution uniformity, one of the battery structure simulation schemes to be simulated, in which the internal resistance change rate is greater than or equal to the preset change rate, the temperature rise data is less than or equal to the preset temperature rise data and the SOC distribution uniformity meets the preset distribution conditions, is selected as the optimal simulation scheme for the battery structure.

[0178] It can be seen that this optional implementation method can select one of the battery structure schemes to be simulated, in which the internal resistance change rate is greater than or equal to the preset change rate, the temperature rise data is less than or equal to the preset temperature rise data, and the SOC distribution uniformity meets the preset distribution conditions, when the comprehensive analysis results include the internal resistance change rate, temperature rise data, and SOC distribution uniformity. This can be used as the optimal simulation scheme for the battery structure, thereby improving the accuracy and reliability of the selection of the optimal simulation scheme for the battery structure.

[0179] In this optional embodiment, as another optional implementation, the simulated voltage data includes the simulated voltage at each of multiple simulation moments within a preset simulation duration, and the measured voltage data includes the measured voltage at each of multiple test moments within a preset test duration. Furthermore, as shown in FIG7 , FIG7 is a schematic structural diagram of another device for determining battery tab parameters based on an electrochemical simulation model disclosed in an embodiment of the present application. As shown in FIG4 , the device may further include:

[0180] The generating module 304 is configured to generate a voltage correction coefficient for each scheme to be simulated based on all measured voltages of the battery structure in each scheme to be simulated and all simulated voltages corresponding to each scheme to be simulated.

[0181] The correction module 305 is configured to correct the simulated voltage data corresponding to each to-be-simulated scheme according to the voltage correction coefficient of each to-be-simulated scheme, so as to obtain target simulated voltage data corresponding to each to-be-simulated scheme.

[0182] It can be seen that this optional implementation method can generate a voltage correction coefficient for each scheme to be simulated based on all measured voltages of the battery structure in each scheme to be simulated and all simulated voltages corresponding to each scheme to be simulated, which can improve the generation accuracy of each voltage correction coefficient. Subsequently, based on the calculated accurate voltage correction coefficient, the simulated voltage data corresponding to each scheme to be simulated is corrected to obtain the target simulated voltage data corresponding to each scheme to be simulated, which can improve the correction accuracy of the target simulated voltage data corresponding to each scheme to be simulated.

[0183] In this optional embodiment, the generation module 304 may generate the voltage correction coefficient for each to-be-simulated scheme based on all measured voltages of the battery structure in each to-be-simulated scheme and all simulated voltages corresponding to each to-be-simulated scheme, and may specifically include:

[0184] Establishing a first relationship curve of the battery structure in each to-be-simulated scenario based on all measured voltages of the battery structure in each to-be-simulated scenario, wherein the first relationship curve is used to represent a corresponding relationship between measured voltage and time;

[0185] According to all simulation voltages corresponding to each to-be-simulated scheme, a second relationship curve of the battery structure in each to-be-simulated scheme is established, where the second relationship curve is used to represent the corresponding relationship between simulation voltage and time;

[0186] For each scenario to be simulated, a voltage correction coefficient of the scenario to be simulated is generated according to a first relationship curve of the battery structure in the scenario to be simulated and a second relationship curve of the battery structure in the scenario to be simulated.

[0187] It can be seen that this optional implementation scheme can also establish a first relationship curve of the battery structure in each scheme to be simulated based on all measured voltages of the battery structure in each scheme to be simulated, which can improve the accuracy of establishing the first relationship curve of the battery structure in each scheme to be simulated, and establish a second relationship curve of the battery structure in each scheme to be simulated based on all simulated voltages corresponding to each scheme to be simulated, which can improve the accuracy of establishing the second relationship curve of the battery structure in each scheme to be simulated. Subsequently, based on the accurately established first relationship curve and second relationship curve of each scheme to be simulated, a voltage correction coefficient of each scheme to be simulated is generated, which can improve the accuracy and reliability of generating the voltage correction coefficient of each scheme to be simulated, thereby facilitating improving the accuracy and reliability of subsequent correction of the simulation voltage data based on the generated accurate voltage correction coefficient.

[0188] Example 4

[0189] Please refer to Figure 8, which is a schematic diagram of the structure of another device for determining battery tab parameters based on an electrochemical simulation model disclosed in an embodiment of the present application. As shown in Figure 8, the device for determining battery tab parameters based on an electrochemical simulation model may include:

[0190] A memory 401 storing executable program code;

[0191] a processor 402 coupled to the memory 401;

[0192] The processor 402 calls the executable program code stored in the memory 401 to execute the steps of the method for determining battery tab parameters based on the electrochemical simulation model described in the first embodiment or the second embodiment of the present application.

[0193] Example 5

[0194] An embodiment of the present application discloses a computer storage medium storing computer instructions. When the computer instructions are called, they are used to execute the steps of the method for determining battery tab parameters based on the electrochemical simulation model described in Example 1 or Example 2 of the present application.

[0195] Example 6

[0196] An embodiment of the present application discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps of the method for determining battery tab parameters based on an electrochemical simulation model described in Example 1 or Example 2.

[0197] The device embodiments described above are merely illustrative, wherein the modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, i.e., they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Those skilled in the art can understand and implement the present invention without inventive effort.

[0198] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course by hardware. Based on this understanding, the above technical solution, in essence, or the part that contributes to the relevant technology, can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, including a read-only memory. , random access memory , PROM , Erasable Programmable Read-Only Memory , one-time programmable read-only memory , Electronically Erasable Rewritable Read-Only Memory , CD-ROM Or other optical disk storage, magnetic disk storage, magnetic tape storage, or any other medium readable by a computer that can be used to carry or store data.

Claims

1. A method for determining battery tab parameters based on an electrochemical simulation model, the method comprising: Acquire multiple schemes to be simulated, all of which correspond to the same battery structure, and each of which has corresponding battery structure parameters, wherein the battery structure parameters include at least a battery tab width and / or a battery tab number; Inputting the battery structure parameters corresponding to each of the schemes to be simulated into a pre-built electrochemical simulation model of the battery structure for simulation, and obtaining simulation results for each of the schemes to be simulated; Determining an optimal simulation scheme from all the schemes to be simulated according to the simulation results corresponding to all the schemes to be simulated; The battery tab parameters of the optimal simulation solution are determined as the optimal tab parameters of the battery structure.

2. The method for determining battery tab parameters based on an electrochemical simulation model according to claim 1, wherein: Determining the optimal simulation scheme of the battery structure from all the schemes to be simulated based on the simulation results corresponding to all the schemes to be simulated includes: Analyze a performance parameter set of the battery structure in each of the schemes to be simulated according to the simulation results corresponding to each of the schemes to be simulated, where the performance parameter set includes one or more performance parameters; Performing a comprehensive analysis on the performance parameter sets of the battery structure in all the schemes to be simulated to obtain comprehensive analysis results of all the schemes to be simulated; According to the comprehensive analysis result, one of the to-be-simulated schemes of the battery structure is selected as the optimal simulation scheme of the battery structure.

3. The method for determining battery tab parameters based on an electrochemical simulation model according to claim 2, wherein: The simulation result includes simulated voltage data and / or SOC data and / or temperature field data; wherein, when the simulation result includes the simulated voltage data, the simulation result also includes measured voltage data, wherein the measured voltage data of all the schemes to be simulated are the same; Furthermore, analyzing the performance parameter set of the battery structure in each of the schemes to be simulated based on the simulation results corresponding to each of the schemes to be simulated includes: When the simulation result includes the simulated voltage data, calculating the battery DC internal resistance of each of the schemes to be simulated according to the simulated voltage data corresponding to each of the schemes to be simulated and the measured voltage data; and / or, When the simulation result includes the SOC data, analyzing the SOC data corresponding to each of the schemes to be simulated to obtain the SOC distribution of each of the schemes to be simulated; and / or, When the simulation result includes the temperature field data, analyzing the temperature field data corresponding to each of the schemes to be simulated to obtain the temperature rise data of each of the schemes to be simulated; The performance parameter set includes the battery DC internal resistance and / or the SOC distribution and / or the temperature rise data.

4. The method for determining battery tab parameters based on an electrochemical simulation model according to claim 3, wherein: Inputting the battery structure parameters corresponding to each of the schemes to be simulated into a pre-built electrochemical simulation model of the battery structure for simulation, and obtaining simulation results for each of the schemes to be simulated, includes: For any of the schemes to be simulated, inputting battery structure parameters corresponding to the scheme to be simulated into a pre-built electrochemical simulation model of the battery structure, and simulating to obtain a lithium ion concentration set of the battery structure in the scheme to be simulated, wherein the lithium ion concentration set of the battery structure includes the surface lithium ion concentration of coating particles of the electrode coating of the battery structure and the average lithium ion concentration of the coating particles; Calculating SOC data corresponding to the scheme to be simulated based on the surface lithium ion concentration of the coating particles and the average lithium ion concentration of the coating particles in the scheme to be simulated, and determining the SOC data corresponding to the scheme to be simulated as a simulation result of the scheme to be simulated; and / or, For any of the schemes to be simulated, the battery structure parameters corresponding to the scheme to be simulated are input into a pre-built electrochemical simulation model of the battery structure, and the temperature calculation parameters of the scheme to be simulated are obtained by simulation, wherein the temperature calculation parameters include the parameters required by a preset temperature field calculation formula; The temperature calculation parameters of the scheme to be simulated are input into the temperature field calculation formula for calculation to obtain the temperature field data of the scheme to be simulated, and the temperature field data of the scheme to be simulated is determined as the simulation result of the scheme to be simulated.

5. The method for determining battery tab parameters based on an electrochemical simulation model according to any one of claims 2 to 4, wherein: The comprehensive analysis results of each of the schemes to be simulated include one or more combinations of the internal resistance change rate of each of the schemes to be simulated, the temperature rise data of each of the schemes to be simulated, and the SOC distribution uniformity of each of the schemes to be simulated; Furthermore, selecting one of all the to-be-simulated schemes of the battery structure according to the comprehensive analysis result as the optimal simulation scheme of the battery structure includes: When the comprehensive analysis result includes the internal resistance change rate, the temperature rise data and the SOC distribution uniformity, one of the schemes to be simulated for the battery structure is selected as the optimal simulation scheme for the battery structure, in which the internal resistance change rate is greater than or equal to the preset change rate, the temperature rise data is less than or equal to the preset temperature rise data, and the SOC distribution uniformity meets the preset distribution conditions.

6. The method for determining battery tab parameters based on an electrochemical simulation model according to claim 3 or 4, wherein: The simulated voltage data includes the simulated voltage at each of the multiple simulation moments within a preset simulation duration, and the measured voltage data includes the measured voltage at each of the multiple test moments within a preset test duration; And, the method further comprises: generating a voltage correction coefficient for each of the schemes to be simulated according to all the measured voltages of the battery structure in each of the schemes to be simulated and all the simulated voltages corresponding to each of the schemes to be simulated; According to the voltage correction coefficient of each of the schemes to be simulated, the simulation voltage data corresponding to each of the schemes to be simulated is corrected to obtain the target simulation voltage data corresponding to each of the schemes to be simulated.

7. The method for determining battery tab parameters based on an electrochemical simulation model according to claim 6, wherein: Generating a voltage correction coefficient for each of the schemes to be simulated based on all the measured voltages of the battery structure in each of the schemes to be simulated and all the simulated voltages corresponding to each of the schemes to be simulated includes: Establishing a first relationship curve of the battery structure in each of the scenarios to be simulated based on all the measured voltages of the battery structure in each of the scenarios to be simulated, wherein the first relationship curve is used to represent a correspondence between the measured voltage and time; Establishing a second relationship curve of the battery structure in each of the schemes to be simulated according to all the simulated voltages corresponding to each of the schemes to be simulated, wherein the second relationship curve is used to represent a corresponding relationship between the simulated voltage and the time; For each of the schemes to be simulated, a voltage correction coefficient of the scheme to be simulated is generated according to a first relationship curve of the battery structure in the scheme to be simulated and a second relationship curve of the battery structure in the scheme to be simulated.

8. A device for determining battery tab parameters based on an electrochemical simulation model, the device comprising: an acquisition module, configured to acquire a plurality of schemes to be simulated, wherein all the schemes to be simulated correspond to the same battery structure, and each scheme to be simulated has corresponding battery structure parameters, wherein the battery structure parameters include at least a battery tab width and / or a battery tab number; A simulation module, configured to input the battery structure parameters corresponding to each of the schemes to be simulated into a pre-built electrochemical simulation model of the battery structure to perform simulation and obtain simulation results for each of the schemes to be simulated; A determination module, configured to determine an optimal simulation scheme from all the schemes to be simulated based on the simulation results corresponding to all the schemes to be simulated; The determination module is further configured to determine the battery tab parameters of the optimal simulation solution as the optimal tab parameters of the battery structure.

9. A device for determining battery tab parameters based on an electrochemical simulation model, the device comprising: a memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the method for determining battery tab parameters based on an electrochemical simulation model as described in any one of claims 1 to 7.

10. A computer storage medium storing computer instructions, wherein the computer instructions, when called, are used to execute the method for determining battery tab parameters based on an electrochemical simulation model according to any one of claims 1 to 7.

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