Battery cell temperature prediction method, device, computer equipment, storage medium and product

Abstract

The present application relates to a method, device, computer equipment, storage medium and product for predicting battery cell temperature. The method comprises: obtaining the surface temperature of any sampling point on the surface of the battery cell to be tested, and the position information of the sampling point on the battery cell to be tested, determining the vector value of the sampling point on different spatial axes according to the position information, inputting the surface temperature of the sampling point and the vector value of the sampling point on different spatial axes into the battery cell thermal conduction model to obtain the internal temperature of the battery cell to be tested; wherein the origin of different spatial axes is the heat source point in the battery cell to be tested; the battery cell thermal conduction model characterizes the thermal conduction relationship between the surface temperature and the internal temperature at different positions on the battery cell. In the above method, the battery cell thermal conduction model is an equivalent thermal physics model that characterizes the thermal conduction relationship between the surface temperature and the internal temperature of the battery cell, which can simulate the thermal conduction process of the battery cell, so inferring the internal temperature based on the thermal conduction relationship can improve the accuracy of the prediction result.

Description

Technical Field

[0001] The present application relates to the field of battery cell technology, and in particular to a method, device, computer equipment, storage medium and product for predicting battery cell temperature. Background Art

[0002] The internal temperature of the battery cells is a key parameter for the Battery Management System (BMS) to analyze battery performance.

[0003] In the related art, a large amount of measured data is usually used as training samples to train the neural network model, and the internal temperature of the battery cell is predicted based on the trained neural network model.

[0004] However, the prediction results of the internal temperature of the battery cell in the related art have the problem of low accuracy. Summary of the invention

[0005] Based on this, it is necessary to provide a battery cell temperature prediction method, device, computer equipment, storage medium and product to address the above technical problems.

[0006] In a first aspect, an embodiment of the present application provides a method for predicting a battery cell temperature, comprising:

[0007] Obtain the surface temperature of any sampling point on the surface of the battery cell to be tested, as well as the position information of the sampling point on the battery cell to be tested;

[0008] Determine the vector value of the sampling point on different spatial axes according to the position information; the origin of the different spatial axes is the heat source point in the battery cell to be tested;

[0009] The surface temperature of the sampling point and the vector value of the sampling point in different spatial axes are input into the battery cell thermal conduction model to obtain the internal temperature of the battery cell to be tested; wherein the battery cell thermal conduction model represents the thermal conduction relationship between the surface temperature and the internal temperature at different positions on the battery cell.

[0010] In the embodiment of the present application, the surface temperature of any sampling point on the surface of the battery cell to be tested and the position information of the sampling point on the battery cell to be tested are obtained, the vector value of the sampling point on different spatial axes is determined according to the position information, and the surface temperature of the sampling point and the vector value of the sampling point on different spatial axes are input into the battery cell thermal conduction model to obtain the internal temperature of the battery cell to be tested; wherein the origin of different spatial axes is the heat source point in the battery cell to be tested; the battery cell thermal conduction model characterizes the thermal conduction relationship between the surface temperature and the internal temperature at different positions on the battery cell. In the above method, the battery cell thermal conduction model is an equivalent thermal physics model that characterizes the thermal conduction relationship between the surface temperature and the internal temperature of the battery cell, which can simulate the thermal conduction process of the battery cell, so the internal temperature can be inferred based on the thermal conduction relationship to improve the accuracy of the prediction result.

[0011] In one embodiment, the method further comprises:

[0012] Obtaining the surface temperature of multiple reference sampling points on the reference cell, the position information of the multiple reference sampling points on the reference cell, and the internal temperature of the reference cell;

[0013] A cell heat conduction model is determined according to the surface temperatures of a plurality of reference sampling points, the position information of each reference sampling point, and the internal temperature of the reference cell.

[0014] In the embodiment of the present application, the surface temperature of multiple reference sampling points on the reference cell, the position information of multiple reference sampling points on the reference cell, and the internal temperature of the reference cell are obtained, so as to determine the cell thermal conduction model according to the surface temperature of multiple reference sampling points, the position information of each reference sampling point, and the internal temperature of the reference cell. In the above method, the cell thermal conduction model is constructed by measuring the internal temperature of the reference cell and the surface temperature and position information of multiple reference sampling points on the reference cell, which improves the matching degree between the cell thermal conduction model and the cell thermal conduction process, helps the cell thermal conduction model to simulate the cell thermal conduction process, and thus improves the reliability of cell temperature prediction based on the cell thermal conduction model.

[0015] In one embodiment, determining a thermal conduction model of a battery cell according to surface temperatures of a plurality of reference sampling points, location information of each reference sampling point, and an internal temperature of a reference battery cell includes:

[0016] According to the position information of each reference sampling point on the reference battery cell, the vector value of each reference sampling point on different spatial axes is determined; the origin of different spatial axes is the heat source point in the battery cell to be tested;

[0017] Determine the heat conduction relationship between the surface temperature at different positions on the reference cell and the internal temperature of the reference cell according to the surface temperature of each reference sampling point, the vector value of each reference sampling point in different spatial axes, and the internal temperature of the reference cell;

[0018] The thermal conduction model of the battery cell is determined according to the thermal conduction relationship.

[0019] In the embodiment of the present application, according to the position information of each reference sampling point on the reference battery cell, the vector value of each reference sampling point in different spatial axes is determined, and according to the surface temperature of each reference sampling point, the vector value of each reference sampling point in different spatial axes and the internal temperature of the reference battery cell, the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell is determined, and the battery cell heat conduction model is determined according to the heat conduction relationship. In the above method, a heat conduction model is constructed to characterize the heat conduction relationship between the surface temperature and the internal temperature at different spatial positions on the battery cell, so as to adapt to the actual heat transfer situation where the heat conduction conditions in various directions of the battery cell are not the same, thereby improving the reliability of the battery cell temperature prediction based on the battery cell heat conduction model.

[0020] In one embodiment, according to the position information of each reference sampling point on the reference cell, the vector value of each reference sampling point on different spatial axes is determined, including:

[0021] For each reference sampling point, a reference vector pointing from a heat source point in the reference cell to the reference sampling point is determined according to position information of the reference sampling point on the reference cell;

[0022] According to the reference vector, the vector value of the reference sampling point in different spatial axes is determined.

[0023] In the embodiment of the present application, for each reference sampling point, a reference vector pointing from the heat source point in the reference cell to the reference sampling point is determined based on the position information of the reference sampling point on the reference cell, and the vector value of the reference sampling point on different spatial axes is determined based on the reference vector. In the above method, the position information of the reference sampling point is decomposed on different spatial axes using the reference vector pointing from the heat source point to the reference sampling point, and the vector value of the reference sampling point on different spatial axes is obtained, which improves the accuracy of the spatial positioning of the reference sampling point, and helps to construct a heat conduction model that characterizes the heat conduction relationship between the surface temperature and the internal temperature at different spatial positions on the cell, thereby improving the accuracy and reliability of the prediction results.

[0024] In one embodiment, the different spatial axes include mutually perpendicular X-axis, Y-axis and Z-axis; and according to the reference vector, determining the vector value of the reference sampling point on the different spatial axes includes:

[0025] Project the reference vector onto the X-axis to obtain the vector value of the reference sampling point on the X-axis;

[0026] Project the reference vector onto the Y axis to obtain the vector value of the reference sampling point on the Y axis;

[0027] Project the reference vector onto the Z axis to obtain the vector value of the reference sampling point on the Z axis.

[0028] In the embodiment of the present application, different spatial axes include mutually perpendicular X-axis, Y-axis and Z-axis. The reference vector is projected to the X-axis to obtain the vector value of the reference sampling point on the X-axis; the reference vector is projected to the Y-axis to obtain the vector value of the reference sampling point on the Y-axis; the reference vector is projected to the Z-axis to obtain the vector value of the reference sampling point on the Z-axis. In the above method, the decomposition of the reference sampling point in three-dimensional space is realized, so as to accurately locate the position of the reference sampling point in three-dimensional space, thereby constructing a thermal conduction model of the battery cell that matches the actual thermal conduction environment, i.e., three-dimensional space, and simultaneously improving the accuracy and reliability of the prediction results.

[0029] In one embodiment, determining the heat conduction relationship between the surface temperature at different positions on the reference cell and the internal temperature of the reference cell according to the surface temperature of each reference sampling point, the vector value of the reference sampling point in different spatial axes, and the internal temperature of the reference cell includes:

[0030] The surface temperature of each reference sampling point, the vector value of the reference sampling point in different spatial axes, and the internal temperature of the reference battery cell are input into the initial heat conduction model to obtain the heat conduction relationship corresponding to each reference sampling point;

[0031] According to the heat conduction relationship corresponding to each reference sampling point, the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell is determined.

[0032] In the embodiment of the present application, the surface temperature of each reference sampling point, the vector value of each reference sampling point in different spatial axes, and the internal temperature of the reference battery cell are input into the initial heat conduction model to obtain the heat conduction relationship corresponding to each reference sampling point, and the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell is determined according to the heat conduction relationship corresponding to each reference sampling point. In the above method, the heat conduction relationship is determined based on multiple heat conduction relationship corresponding to multiple reference sampling points, and the data algorithm is used to solve it, which is convenient for program execution and improves the efficiency of determining the heat conduction relationship.

[0033] In one embodiment, the initial heat conduction model includes heat transfer coefficient characterization quantities in different spatial axes; the different spatial axes include mutually perpendicular X-axis, Y-axis and Z-axis; according to the heat conduction relationship corresponding to each reference sampling point, the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell is determined, including:

[0034] According to the heat conduction relationship corresponding to each reference sampling point, the heat transfer coefficient values ​​of the reference cell on the X-axis, Y-axis and Z-axis are obtained;

[0035] The heat transfer coefficient values ​​of the reference cell on the X-axis, Y-axis and Z-axis are substituted into the corresponding heat transfer coefficient characterization quantity in the initial heat conduction model to obtain the heat conduction relationship between the surface temperature at different positions on the reference cell and the internal temperature of the reference cell.

[0036] In the embodiment of the present application, when the initial heat conduction model includes heat transfer coefficient characterization quantities on different spatial axes, and the different spatial axes include mutually perpendicular X-axis, Y-axis and Z-axis, the heat transfer coefficient values ​​of the reference battery cell on the X-axis, Y-axis and Z-axis are solved according to the heat conduction relationship corresponding to each reference sampling point, and the heat transfer coefficient values ​​of the reference battery cell on the X-axis, Y-axis and Z-axis are substituted into the corresponding heat transfer coefficient characterization quantities in the initial heat conduction model to obtain the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell. In the above method, while using the polynomial solution algorithm to efficiently determine the heat conduction relationship, the decomposition and positioning of the reference sampling points in three-dimensional space are realized to construct a battery cell heat conduction model that matches the actual heat conduction environment, i.e., three-dimensional space, thereby improving the accuracy and reliability of the prediction results.

[0037] In one embodiment, determining a thermal conduction model of a battery cell according to a thermal conduction relationship includes:

[0038] Obtaining surface temperatures of multiple verification sampling points on a reference cell and location information of the multiple verification sampling points on the reference cell;

[0039] The heat conduction relationship is verified according to the surface temperatures of multiple verification sampling points, the position information of each verification sampling point and the internal temperature of the reference battery cell, and the verified heat conduction relationship is determined as the battery cell heat conduction model.

[0040] In the embodiment of the present application, the surface temperature of multiple verification sampling points on the reference cell and the position information of the multiple verification sampling points on the reference cell are obtained, the heat conduction relationship is verified according to the surface temperature of the multiple verification sampling points, the position information of each verification sampling point and the internal temperature of the reference cell, and the verified heat conduction relationship is determined as the cell heat conduction model. In the above method, the heat conduction relationship is verified using the verification sampling points on the reference cell, so that the verified heat conduction relationship is determined as the cell heat conduction model, thereby improving the reliability of the model.

[0041] In one embodiment, verifying the thermal conductivity relationship according to the surface temperatures of a plurality of verification sampling points, the position information of each verification sampling point, and the internal temperature of a reference battery cell includes:

[0042] According to the position information of each verification sampling point, the vector value of each verification sampling point on different spatial axes is determined;

[0043] The surface temperature of each verification sampling point, the vector value of each verification sampling point in different spatial axes, and the internal temperature of the reference battery cell are input into the heat conduction relationship to obtain the predicted internal temperature corresponding to each verification sampling point;

[0044] The heat conduction relationship is verified according to the predicted internal temperature corresponding to each verification sampling point to obtain the verification result.

[0045] In the embodiment of the present application, according to the position information of each verification sampling point, the vector value of each verification sampling point in different spatial axes is determined, the surface temperature of each verification sampling point, the vector value of each verification sampling point in different spatial axes and the internal temperature of the reference battery cell are input into the heat conduction relationship, the predicted internal temperature corresponding to each verification sampling point is obtained, and the heat conduction relationship is verified according to the predicted internal temperature corresponding to each verification sampling point to obtain the verification result. In the above method, the universality and reliability of the heat conduction relationship are verified using verification sampling points at different spatial positions, thereby improving the universality and reliability of the battery cell heat conduction model obtained based on the heat conduction relationship.

[0046] In one embodiment, the heat conduction relationship is verified according to the predicted internal temperature corresponding to each verification sampling point to obtain a verification result, including:

[0047] Obtain the temperature difference reference range of each verification sampling point;

[0048] Determine the preliminary verification results based on the predicted internal temperature and surface temperature corresponding to each verification sampling point and the temperature difference reference range of each verification sampling point;

[0049] When the preliminary verification result is that the verification is passed, the verification result is determined based on the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell.

[0050] In the embodiment of the present application, the temperature difference reference range of each verification sampling point is obtained, and the preliminary verification result is determined according to the predicted internal temperature and surface temperature corresponding to each verification sampling point and the temperature difference reference range of each verification sampling point. If the preliminary verification result is passed, the verification result is determined based on the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell. In the above method, the thermal conduction relationship is verified successively using the temperature difference reference range of the verification sampling point and the measured internal temperature of the reference battery cell, which realizes the double verification of the thermal conduction relationship and improves the reliability of the verification result.

[0051] In one embodiment, the preliminary verification result is determined according to the predicted internal temperature and surface temperature corresponding to each verification sampling point and the temperature difference reference range of each verification sampling point, including:

[0052] Obtain the temperature difference between the predicted internal temperature and the surface temperature corresponding to each verification sampling point;

[0053] When all temperature differences meet the temperature difference reference range of the corresponding verification sampling points, the preliminary verification result is determined to have passed the verification;

[0054] In the event that any temperature difference value does not meet the temperature difference reference range of the corresponding verification sampling point, the preliminary verification result is determined to be failed verification.

[0055] In the embodiment of the present application, the temperature difference between the predicted internal temperature and the surface temperature corresponding to each verification sampling point is obtained, and when all temperature differences meet the temperature difference reference range of the corresponding verification sampling point, the preliminary verification result is determined to pass the verification, and when any temperature difference does not meet the temperature difference reference range of the corresponding verification sampling point, the preliminary verification result is determined to fail the verification. In the above method, the thermal conduction relationship is preliminarily verified based on the temperature difference reference range obtained by big data statistics, and a higher preliminary passing verification condition is adopted, which improves the model verification condition and correspondingly improves the reliability of the obtained battery cell thermal conduction model.

[0056] In one embodiment, determining a verification result based on the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell includes:

[0057] Obtain the maximum temperature difference according to the temperature difference between the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell;

[0058] When the maximum temperature difference is less than or equal to the temperature difference threshold, the verification result is determined to be passed;

[0059] When the maximum temperature difference is greater than the temperature difference threshold, the verification result is determined to be failure to pass the verification.

[0060] In the embodiment of the present application, the maximum temperature difference is obtained according to the temperature difference between the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell. When the maximum temperature difference is less than or equal to the temperature difference threshold, the verification result is determined to be passed, and when the maximum temperature difference is greater than the temperature difference threshold, the verification result is determined to be failed. In the above method, the thermal conductivity relationship is verified by using the measured internal temperature, which helps to obtain a thermal conductivity relationship that can reflect the actual internal temperature of the battery cell, so as to improve the reliability of the model and thus improve the accuracy of the prediction results.

[0061] In one embodiment, the battery cell thermal conduction model represents the thermal conduction relationship between the surface temperature at different positions on the battery cell and the maximum temperature inside the battery cell and the minimum temperature inside the battery cell.

[0062] In the embodiment of the present application, the cell heat conduction model characterizes the heat conduction relationship between the surface temperature at different positions on the cell and the maximum temperature inside the cell and the minimum temperature inside the cell. In the above method, the cell heat conduction model can be used to achieve simultaneous prediction of the maximum temperature inside the cell and the minimum temperature inside the cell, thereby improving the data comprehensiveness of the prediction results.

[0063] In a second aspect, an embodiment of the present application further provides a battery core temperature prediction device, comprising:

[0064] A data acquisition module is used to obtain the surface temperature of any sampling point on the surface of the battery cell to be tested, as well as the position information of the sampling point on the battery cell to be tested;

[0065] A vector determination module is used to determine the vector value of the sampling point on different spatial axes according to the position information; the origin of the different spatial axes is the heat source point in the battery cell to be tested;

[0066] The temperature prediction module is used to input the surface temperature of the sampling point and the vector value of the sampling point in different spatial axes into the battery cell thermal conduction model to obtain the internal temperature of the battery cell to be tested; wherein the battery cell thermal conduction model represents the thermal conduction relationship between the surface temperature and the internal temperature at different positions on the battery cell.

[0067] In a third aspect, an embodiment of the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps in the battery cell temperature prediction method provided in any embodiment of the first aspect are implemented.

[0068] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps in the battery cell temperature prediction method provided in any one of the embodiments in the first aspect above are implemented.

[0069] In a fifth aspect, an embodiment of the present application further provides a computer program product, including a computer program, which, when executed by a processor, implements the steps in the battery cell temperature prediction method provided in any embodiment of the first aspect above.

[0070] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 is an internal structure diagram of a computer device in one embodiment;

[0072] Figure 2Schematic diagram of a flow chart of a method for predicting battery core temperature in one embodiment;

[0073] Figure 3 A schematic diagram of a process for constructing a thermal conduction model of a battery cell in one embodiment;

[0074] Figure 4 A schematic diagram of a process for determining a thermal conduction model of a battery cell in one embodiment;

[0075] Figure 5 A schematic diagram of a process for determining a vector value on a spatial axis in one embodiment;

[0076] Figure 6 A schematic diagram of the structure of a reference battery cell according to an embodiment;

[0077] Figure 7 A schematic diagram of a process for determining a spatial axial upward vector value in another embodiment;

[0078] Figure 8 A schematic diagram of a process for determining a heat conduction relationship in one embodiment;

[0079] Fig. 9 A schematic diagram of a process for determining a heat conduction relationship in another embodiment;

[0080] Fig.10 A schematic diagram of a flow chart for determining a thermal conduction model of a battery cell in another embodiment;

[0081] Fig.11 A schematic diagram of a process for verifying a heat conduction relationship in an embodiment;

[0082] Fig.12 A schematic diagram of a process for obtaining a verification result in an embodiment;

[0083] Fig.13 A schematic diagram of a process for determining a preliminary verification result in one embodiment;

[0084] Fig.14 A schematic diagram of a process for determining a verification result in one embodiment;

[0085] Fig.15 is a schematic flow chart of a method for predicting battery core temperature in another embodiment;

[0086] Fig.16 FIG. 4 is a structural block diagram of a battery cell temperature prediction device in an embodiment. DETAILED DESCRIPTION

[0087] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0088] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the term "including" and any variations thereof in the specification and claims of this application and the above-mentioned figure descriptions are intended to cover non-exclusive inclusions.

[0089] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0090] In the description of the embodiments of the present application, the term "and / or" is only a way to describe the heat conduction relationship of the associated objects, indicating that there may be three relationships, for example, A and / or B, which may represent: A exists alone, A and B exist at the same time, and B exists alone. In the description of the embodiments of the present application, the term "plurality" refers to more than two (including two), unless otherwise clearly and specifically defined.

[0091] With the development of new energy technology, batteries have been increasingly used in people's production and life, and battery performance analysis has become a research focus for technicians. The internal temperature of the battery cell is a key parameter for the battery management system (BMS) to perform battery performance analysis.

[0092] In the related art, measured data such as the surface temperature of a large number of sampling points on the battery cell and the internal temperature of the battery cell are usually used as training samples to train the neural network model, and the internal battery cell temperature is predicted based on the trained neural network model.

[0093] However, in the related art, the prediction of the internal temperature of the battery cell is strongly dependent on the actual measured data in the past. When there are abnormal jumps in the test data, it will affect the trained neural network model, thereby affecting the accuracy of the prediction results. And because the surface temperature of the sampling points at the same type of position (such as the bus bar in the battery cell) is used when training the neural network model, the trained neural network model is not suitable for predicting the internal temperature of the battery cell based on the surface temperature of any sampling point on the surface of the battery cell. If the neural network model is still used to predict the internal temperature of the battery cell based on the surface temperature of other sampling points, there will be a large error between the predicted internal temperature of the battery cell and the actual internal temperature of the battery cell, resulting in poor accuracy of the prediction results.

[0094] Based on this, the present application provides a method for predicting battery cell temperature, which predicts the internal temperature of the battery cell by using a battery cell thermal conduction model that can simulate the thermal conduction process of the battery cell, thereby achieving the technical effect of improving the accuracy of the prediction result.

[0095] In one embodiment, a method for predicting battery core temperature is provided. Figure 1 The computing device in is used as an example for explanation. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for predicting the temperature of a battery cell is implemented.

[0096] Those skilled in the art will understand that Figure 1 The structure shown in the figure is only a block diagram of a partial structure related to the embodiment of the present application, and does not constitute a limitation on the computer device to which the embodiment of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0097] In one embodiment, the present application provides a method for predicting the temperature of a battery cell, so as to predict the internal temperature of the battery cell by the surface temperature of the battery cell. Figure 2 As shown, the method comprises the following steps:

[0098] S210, obtaining the surface temperature of any sampling point on the surface of the battery cell to be tested, and the position information of the sampling point on the battery cell to be tested.

[0099] The cell to be tested is a jellyroll. For example, the cell to be tested may be a rectangular cell, a cylindrical cell or a blade cell. The sampling point is any position point on the surface of the cell to be tested. The surface temperature of the sampling point is the surface temperature of the cell to be tested at the sampling point.

[0100] Optionally, the sampling point may be any position point on the top cover surface of the cell to be tested, any position point on the bottom surface of the cell to be tested, any position point on the side surface (usually with the largest area) of the cell to be tested that contacts the external cooling component, or any position point on other sides of the cell to be tested. Exemplarily, in order to facilitate sampling and reduce the temperature interference of the surrounding environment on the sampling point, a position point on the top cover surface may be selected as the sampling point.

[0101] The position information of the sampling point on the cell to be tested represents the positional relationship of the sampling point relative to the cell to be tested. The position information of the sampling point on the cell to be tested may include the spatial coordinates of the sampling point relative to a preset reference point on the cell to be tested. For example, the preset reference point may be a corner point, a center point of a surface, or a geometric center of the cell to be tested.

[0102] Optionally, the computer device can obtain the surface temperature of any sampling point on the surface of the battery cell to be tested through a temperature sensor, and obtain the spatial coordinates of the sampling point relative to a preset reference point in the battery cell to be tested as the position information of the sampling point on the battery cell to be tested.

[0103] S220, determining the vector values ​​of the sampling points on different spatial axes according to the position information; the origins of the different spatial axes are the heat source points in the battery cell to be tested.

[0104] Optionally, after obtaining the position information of the sampling point, the computer device may perform spatial transformation on the position information to obtain the vector value of the sampling point on each spatial axis with the heat source point in the tested battery cell as the origin. Exemplarily, when the position information of the sampling point is the spatial coordinate of the sampling point relative to the heat source point, the computer device may project the sampling point to each spatial axis according to the spatial coordinate of the sampling point, and use the coordinate value of the sampling point on each spatial axis as the vector value of the sampling point on the corresponding spatial vector; when the position information of the sampling point is the spatial coordinate of the sampling point relative to a non-heat source point, the computer device may first convert the spatial coordinate of the sampling point into the spatial coordinate relative to the heat source point, and then use the above process to determine the vector value of the sampling point on each spatial axis.

[0105] S230, inputting the surface temperature of the sampling point and the vector value of the sampling point in different spatial axes into the battery cell heat conduction model to obtain the internal temperature of the battery cell to be measured;

[0106] Among them, the battery cell thermal conduction model characterizes the thermal conduction relationship between the surface temperature and the internal temperature at different positions on the battery cell.

[0107] The battery cell heat conduction model is an equivalent thermal physics model of battery cell heat transfer, which is used to simulate the heat conduction process from the heat source point in the battery cell to the battery cell surface. It can usually be constructed based on the battery cell heat generation calculation and Fourier heat transfer law.

[0108] Optionally, after obtaining the surface temperature of the sampling point and the vector value of the sampling point in each spatial axis, the computer can input the surface temperature of the sampling point and each vector value into the battery cell thermal conduction model, and use the thermal conduction relationship between the surface temperature and the internal temperature at different positions on the battery cell represented by the battery cell thermal conduction model to determine the internal temperature corresponding to the sampling point as the internal temperature of the battery cell to be tested.

[0109] It should be noted that when determining the internal temperature of the battery cell to be tested based on the battery cell thermal conduction model, in addition to inputting the surface temperature of the sampling point and the vector value in different spatial axes, other relevant data can also be input, such as the current, voltage, remaining power (State Of Charge, SOC) of the battery cell to be tested, etc.

[0110] In the embodiment of the present application, the surface temperature of any sampling point on the surface of the battery cell to be tested and the position information of the sampling point on the battery cell to be tested are obtained, the vector value of the sampling point on different spatial axes is determined according to the position information, and the surface temperature of the sampling point and the vector value of the sampling point on different spatial axes are input into the battery cell heat conduction model to obtain the internal temperature of the battery cell to be tested; wherein, the origin of different spatial axes is the heat source point in the battery cell to be tested; the battery cell heat conduction model characterizes the heat conduction relationship between the surface temperature and the internal temperature at different positions on the battery cell. In the above method, the battery cell heat conduction model is an equivalent thermal physics model that characterizes the heat conduction relationship between the surface temperature and the internal temperature of the battery cell, which can simulate the heat conduction process of the battery cell, so the internal temperature can be inferred based on the heat conduction relationship to improve the accuracy of the prediction result. At the same time, determining the vector value of the sampling point on different spatial axes according to the position information is equivalent to decomposing the position of the sampling point on different spatial axes, which improves the accuracy of the spatial positioning of the sampling point, and also improves the accuracy of predicting the internal temperature based on the heat conduction relationship between the surface temperature and the internal temperature of the battery cell at different positions.

[0111] The cell thermal conduction model can be constructed based on the surface temperature at different locations on the cell and the actual internal temperature of the cell. Figure 3 As shown, the above method also includes:

[0112] S310, obtaining surface temperatures of a plurality of reference sampling points on a reference cell, position information of the plurality of reference sampling points on the reference cell, and an internal temperature of the reference cell.

[0113] Among them, the reference battery cell is a prefabricated battery cell with a built-in thermocouple.

[0114] Optionally, the computer device can obtain the surface temperature of multiple reference sampling points on the reference battery cell through a temperature sensor, obtain the spatial coordinates of each reference sampling point relative to a preset reference point in the reference battery cell as the position information of the corresponding reference sampling point on the reference battery cell, and simultaneously obtain the internal temperature of the reference battery cell measured by the thermocouple inside the reference battery cell.

[0115] S320 , determining a cell heat conduction model according to the surface temperatures of a plurality of reference sampling points, the position information of each reference sampling point, and the internal temperature of the reference cell.

[0116] Optionally, after obtaining the surface temperature, position information of each reference sampling point and the measured internal temperature of the reference battery cell, the computer device can use the surface temperature, position information of all reference sampling points and the internal temperature of the reference battery cell to construct a heat conduction relationship that characterizes the surface temperature and internal temperature at different positions on the battery cell based on the battery cell heat generation calculation and Fourier heat transfer law, and use the heat conduction relationship as the battery cell heat conduction model.

[0117] Exemplarily, when the battery cell thermal conduction model characterizes the thermal conduction relationship between the surface temperature and the internal temperature of the battery cell at different thermal conduction distances, for each reference sampling point, the computer device can determine the distance between the reference sampling point and the heat source point according to the position information of the reference sampling point as the thermal conduction distance, and input the thermal conduction distance, the surface temperature of the reference sampling point and the internal temperature of the reference battery cell into the initial thermal conduction model to solve the thermal conduction coefficient in the initial thermal conduction model, and determine the target thermal conduction coefficient according to the multiple thermal conduction coefficients corresponding to the multiple reference sampling points, such as obtaining the average value of the multiple thermal conduction coefficients as the target thermal conduction coefficient, and then substituting the target thermal conduction coefficient back into the initial thermal conduction model to obtain the battery cell thermal conduction model.

[0118] In the embodiment of the present application, the surface temperature of multiple reference sampling points on the reference cell, the position information of multiple reference sampling points on the reference cell, and the internal temperature of the reference cell are obtained, so as to determine the cell thermal conduction model according to the surface temperature of multiple reference sampling points, the position information of each reference sampling point, and the internal temperature of the reference cell. In the above method, the cell thermal conduction model is constructed by measuring the internal temperature of the reference cell and the surface temperature and position information of multiple reference sampling points on the reference cell, which improves the matching degree between the cell thermal conduction model and the cell thermal conduction process, helps the cell thermal conduction model to simulate the cell thermal conduction process, and thus improves the reliability of cell temperature prediction based on the cell thermal conduction model.

[0119] The conduction of heat in different directions of the battery cell is not the same. The position information of the reference sampling point can be converted into the vector value of the reference sampling point in different spatial axes, so as to construct a battery cell heat conduction model that characterizes the heat conduction relationship between the surface temperature and the internal temperature at different spatial positions on the battery cell. Based on this, in one embodiment, Figure 4 As shown, the above S320, according to the surface temperatures of multiple reference sampling points, the position information of each reference sampling point and the internal temperature of the reference battery cell, determines the battery cell heat conduction model, including:

[0120] S410, determining the vector value of each reference sampling point on different spatial axes according to the position information of each reference sampling point on the reference battery cell; the origin of the different spatial axes is the heat source point in the battery cell to be tested.

[0121] The spatial axes are pre-constructed spatial coordinate axes, and the origins of different spatial axes are the same.

[0122] Optionally, after obtaining the position information of each reference sampling point, the computer device may perform spatial transformation on the position information of each reference sampling point to obtain the vector value of the reference sampling point on each preset spatial axis, thereby obtaining the vector value of each reference sampling point on different spatial axes.

[0123] S420, determining a heat conduction relationship between surface temperatures at different positions on the reference cell and the internal temperature of the reference cell according to the surface temperature of each reference sampling point, the vector value of each reference sampling point in different spatial axes, and the internal temperature of the reference cell.

[0124] Optionally, the computer device may input the surface temperature of each reference sampling point, the vector value in different spatial axes, and the internal temperature of the reference battery cell into the initial heat conduction model to obtain a set of heat conduction equations with unknown heat conduction coefficients in each spatial axis, and multiple sets of heat conduction equations may be obtained for multiple reference sampling points. The computer device may jointly solve multiple heat conduction equations to obtain the heat conduction coefficient value of the reference battery cell in each spatial axis, and then substitute the heat conduction coefficient value in each spatial axis back into the initial heat conduction model to obtain the battery cell heat conduction model.

[0125] S430, determining a thermal conduction model of the battery cell according to a thermal conduction relationship.

[0126] Optionally, after obtaining the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell, the computer device can directly use the heat conduction relationship as the battery cell heat conduction model, or further verify the heat conduction relationship and determine the verified heat conduction relationship as the battery cell heat conduction model.

[0127] In the embodiment of the present application, according to the position information of each reference sampling point on the reference battery cell, the vector value of each reference sampling point in different spatial axes is determined, and according to the surface temperature of each reference sampling point, the vector value of each reference sampling point in different spatial axes and the internal temperature of the reference battery cell, the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell is determined, and the battery cell heat conduction model is determined according to the heat conduction relationship. In the above method, a heat conduction model is constructed to characterize the heat conduction relationship between the surface temperature and the internal temperature at different spatial positions on the battery cell, so as to adapt to the actual heat transfer situation where the heat conduction conditions in various directions of the battery cell are not the same, thereby improving the reliability of the battery cell temperature prediction based on the battery cell heat conduction model.

[0128] The vector values ​​of the reference sampling point on different spatial axes can be determined based on the reference vector pointing from the heat source point in the reference cell to the reference sampling point. Figure 5 As shown, the above S410, according to the position information of each reference sampling point on the reference cell, determines the vector value of each reference sampling point on different spatial axes, including:

[0129] S510 . For each reference sampling point, determine a reference vector pointing from a heat source point in the reference cell to the reference sampling point according to position information of the reference sampling point on the reference cell.

[0130] Optionally, for each reference sampling point, the computer device may determine the reference sampling point in the reference cell according to the position information of the reference sampling point on the reference cell, and then connect the heat source point in the reference cell with the reference sampling point to form a reference vector pointing from the heat source point to the reference sampling point. Figure 6 As shown, the geometric center point O of the reference cell is the heat source point, and A, B, and C are sampling points at different positions on the surface of the reference cell. The heat source point O is connected with the sampling point A to form a reference vector , the heat source point O is connected with the sampling point B to form a reference vector , the heat source point O is connected with the sampling point C to form a reference vector .

[0131] S520: Determine the vector value of the reference sampling point on different spatial axes according to the reference vector.

[0132] Optionally, after obtaining the reference vector of the reference sampling point, the computer device may project the reference vector of the reference sampling point onto the corresponding spatial axis to obtain the coordinate values ​​of the reference sampling point on different spatial axes as the vector value of the reference sampling point on the corresponding spatial axis.

[0133] In the embodiment of the present application, for each reference sampling point, a reference vector pointing from the heat source point in the reference cell to the reference sampling point is determined based on the position information of the reference sampling point on the reference cell, and the vector value of the reference sampling point on different spatial axes is determined based on the reference vector. In the above method, the position information of the reference sampling point is decomposed on different spatial axes using the reference vector pointing from the heat source point to the reference sampling point, and the vector value of the reference sampling point on different spatial axes is obtained, which improves the accuracy of the spatial positioning of the reference sampling point, and helps to construct a heat conduction model that characterizes the heat conduction relationship between the surface temperature and the internal temperature at different spatial positions on the cell, thereby improving the accuracy and reliability of the prediction results.

[0134] In the case where different spatial axes include mutually perpendicular X-axis, Y-axis and Z-axis, in one embodiment, as Figure 7 As shown, the above S520, determining the vector value of the reference sampling point on different spatial axes according to the reference vector, includes:

[0135] S710 , project the reference vector onto the X-axis to obtain the vector value of the reference sampling point on the X-axis.

[0136] Among them, the X-axis, Y-axis and Z-axis are the three coordinate axes of the spatial coordinate system formed with the heat source point in the reference cell as the origin. The reference vector is a line segment vector starting from the heat source point and ending at the reference sampling point. Therefore, the reference vector can be directly projected to the X-axis, Y-axis and Z-axis respectively to obtain the vector values ​​of the reference sampling point on the X-axis, Y-axis and Z-axis respectively.

[0137] Optionally, the computer device projects the reference vector onto the X-axis to obtain a coordinate value of the reference sampling point on the X-axis as the vector value of the reference sampling point on the X-axis.

[0138] S720: Project the reference vector onto the Y axis to obtain the vector value of the reference sampling point on the Y axis.

[0139] Optionally, along with the X-axis, the computer device projects the reference vector onto the Y-axis to obtain a coordinate value of the reference sampling point on the Y-axis as the vector value of the reference sampling point on the Y-axis.

[0140] S730 , project the reference vector onto the Z axis to obtain the vector value of the reference sampling point on the Z axis.

[0141] Optionally, as with the X-axis and the Y-axis, the computer device projects the reference vector onto the Z-axis to obtain a coordinate value of the reference sampling point on the Z-axis as the vector value of the reference sampling point on the Z-axis.

[0142] In the embodiment of the present application, different spatial axes include mutually perpendicular X-axis, Y-axis and Z-axis. The reference vector is projected to the X-axis to obtain the vector value of the reference sampling point on the X-axis; the reference vector is projected to the Y-axis to obtain the vector value of the reference sampling point on the Y-axis; the reference vector is projected to the Z-axis to obtain the vector value of the reference sampling point on the Z-axis. In the above method, the decomposition of the reference sampling point in three-dimensional space is realized, so as to accurately locate the position of the reference sampling point in three-dimensional space, thereby constructing a thermal conduction model of the battery cell that matches the actual thermal conduction environment, i.e., three-dimensional space, and simultaneously improving the accuracy and reliability of the prediction results.

[0143] To determine the heat transfer relationship between the surface temperature at different locations on the reference cell and the internal temperature of the reference cell, in one embodiment, Figure 8 As shown, the above S420, according to the surface temperature of each reference sampling point, the vector value of each reference sampling point in different spatial axes, and the internal temperature of the reference cell, determines the heat conduction relationship between the surface temperature at different positions on the reference cell and the internal temperature of the reference cell, including:

[0144] S810, inputting the surface temperature of each reference sampling point, the vector value of each reference sampling point in different spatial axes, and the internal temperature of the reference battery cell into an initial heat conduction model to obtain a heat conduction relationship corresponding to each reference sampling point.

[0145] Among them, the initial heat conduction model also characterizes the heat conduction relationship between the surface temperature and the internal temperature at different positions on the battery cell, but some parameters in the initial heat conduction model are yet to be determined.

[0146] Optionally, for each reference sampling point, the computer device may input the surface temperature of the reference sampling point, the vector values ​​on different spatial axes, and the internal temperature of the reference battery cell into the initial heat conduction model, and bring the surface temperature, the vector values ​​on different spatial axes, and the internal temperature into the positions of corresponding parameters in the heat conduction relationship represented by the initial heat conduction model to obtain the heat conduction relationship corresponding to the reference sampling point. Multiple reference sampling points will obtain multiple sets of heat conduction relationship.

[0147] S820. Determine the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell according to the heat conduction relationship equation corresponding to each reference sampling point.

[0148] Optionally, the computer device can list the heat conduction relationship equations corresponding to all reference sampling points, and use a polynomial solving algorithm to obtain the values ​​of the undetermined parameters in the heat conduction relationship equations, and then substitute the values ​​of the undetermined parameters back into the corresponding parameters in the initial heat conduction model, thereby obtaining the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell.

[0149] In the embodiment of the present application, the surface temperature of each reference sampling point, the vector value of each reference sampling point in different spatial axes, and the internal temperature of the reference battery cell are input into the initial heat conduction model to obtain the heat conduction relationship corresponding to each reference sampling point, and the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell is determined according to the heat conduction relationship corresponding to each reference sampling point. In the above method, the heat conduction relationship is determined based on multiple heat conduction relationship corresponding to multiple reference sampling points, and the data algorithm is used to solve it, which is convenient for program execution and improves the efficiency of determining the heat conduction relationship.

[0150] In the case where the initial heat conduction model includes heat transfer coefficient characterization quantities in different spatial axes, and the different spatial axes include mutually perpendicular X-axis, Y-axis and Z-axis, in one embodiment, as Fig. 9 As shown, the above S820, according to the heat conduction relationship corresponding to each reference sampling point, determines the heat conduction relationship between the surface temperature at different positions on the reference cell and the internal temperature of the reference cell, including:

[0151] S910, according to the heat conduction relationship corresponding to each reference sampling point, solve and obtain the heat transfer coefficient value of the reference battery cell on the X-axis, Y-axis and Z-axis.

[0152] Among them, the heat transfer coefficient characterization quantity in different spatial axes is the undetermined parameter in the initial heat conduction model. Different spatial axes include mutually perpendicular X-axis, Y-axis and Z-axis, and the corresponding heat transfer coefficients include the heat transfer coefficient Kx corresponding to the X-axis, the heat transfer coefficient Ky corresponding to the Y-axis and the heat transfer coefficient Kz corresponding to the Z-axis.

[0153] Optionally, since there are three parameters to be determined, namely the heat transfer coefficient corresponding to the X-axis, the heat transfer coefficient corresponding to the Y-axis, and the heat transfer coefficient corresponding to the Z-axis, the computer device can use a polynomial solving algorithm to solve the heat transfer coefficient values ​​of the reference battery cell on the X-axis, Y-axis, and Z-axis based on the thermal conduction relationship corresponding to at least three reference sampling points.

[0154] S920, substituting the heat transfer coefficient values ​​of the reference battery cell on the X-axis, Y-axis and Z-axis into the corresponding heat transfer coefficient characterization quantity in the initial heat conduction model to obtain the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell.

[0155] Optionally, after obtaining the heat transfer coefficient values ​​of the reference battery cell on the X-axis, Y-axis and Z-axis, the computer device can substitute the heat transfer coefficient values ​​on the X-axis, Y-axis and Z-axis back into the corresponding heat transfer coefficient characterization quantities in the initial thermal conduction model, that is, obtain the thermal conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell.

[0156] In the embodiment of the present application, when the initial heat conduction model includes heat transfer coefficient characterization quantities on different spatial axes, and the different spatial axes include mutually perpendicular X-axis, Y-axis and Z-axis, the heat transfer coefficient values ​​of the reference battery cell on the X-axis, Y-axis and Z-axis are solved according to the heat conduction relationship corresponding to each reference sampling point, and the heat transfer coefficient values ​​of the reference battery cell on the X-axis, Y-axis and Z-axis are substituted into the corresponding heat transfer coefficient characterization quantities in the initial heat conduction model to obtain the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell. In the above method, while using the polynomial solution algorithm to efficiently determine the heat conduction relationship, the decomposition and positioning of the reference sampling points in three-dimensional space are realized to construct a battery cell heat conduction model that matches the actual heat conduction environment, i.e., three-dimensional space, thereby improving the accuracy and reliability of the prediction results.

[0157] To improve the reliability of the model, in one embodiment, Fig.10 As shown, the above S430, determining the thermal conduction model of the battery cell according to the thermal conduction relationship, includes:

[0158] S1010, obtaining surface temperatures of a plurality of verification sampling points on a reference battery cell, and location information of the plurality of verification sampling points on the reference battery cell.

[0159] The verification sampling point is used to verify the thermal conduction model of the battery cell, and may be a sampling point on the reference battery cell that is different from the reference sampling point.

[0160] Optionally, the computer device can obtain the surface temperature of multiple verification sampling points on the surface of the reference battery cell through a temperature sensor, and obtain the spatial coordinates of each verification sampling point relative to a preset reference point in the reference battery cell as the position information of the corresponding verification sampling point on the reference battery cell.

[0161] S1020, verifying the heat conduction relationship according to the surface temperatures of the plurality of verification sampling points, the position information of each verification sampling point, and the internal temperature of the reference battery cell, and determining the verified heat conduction relationship as the battery cell heat conduction model.

[0162] Optionally, in the case where the thermal conduction model of the battery cell characterizes the thermal conduction relationship between the surface temperature and the internal temperature of the battery cell at different thermal conduction distances, after obtaining the surface temperature and position information of multiple newly collected verification sampling points, for each verification sampling point, the computer device can determine the thermal conduction distance of the verification sampling point based on the position information of the verification sampling point, and input the surface temperature and thermal conduction distance of the verification sampling point into the thermal conduction relationship obtained above to predict the battery cell temperature, and obtain the predicted internal temperature of the reference battery cell. The computer device then uses the predicted internal temperature and the internal temperature of the reference battery cell actually measured to verify the thermal conduction relationship, so as to determine the verified thermal conduction relationship as the battery cell thermal conduction model.

[0163] For example, the computer device may obtain the temperature difference between the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell, obtain the average value of all temperature differences, and compare the average value with the preset temperature difference, and determine the verification result of the heat conduction relationship according to the comparison result. Wherein, if the average value is less than or equal to the preset temperature difference, it is determined that the heat conduction relationship has passed the verification; otherwise, if the average value is greater than the preset temperature difference, it is determined that the heat conduction relationship has not passed the verification.

[0164] Optionally, if the thermal conduction relationship fails to pass verification, the computer device may obtain the surface temperature and position information of a new reference sampling point on the reference cell and the internal temperature of the reference cell to redetermine the thermal conduction relationship between the surface temperature at different positions on the reference cell and the internal temperature of the reference cell until verification is passed.

[0165] In the embodiment of the present application, the surface temperature of multiple verification sampling points on the reference cell and the position information of the multiple verification sampling points on the reference cell are obtained, the heat conduction relationship is verified according to the surface temperature of the multiple verification sampling points, the position information of each verification sampling point and the internal temperature of the reference cell, and the verified heat conduction relationship is determined as the cell heat conduction model. In the above method, the heat conduction relationship is verified using the verification sampling points on the reference cell, so that the verified heat conduction relationship is determined as the cell heat conduction model, thereby improving the reliability of the model.

[0166] The position information of the verification sampling point can be converted into the vector value of the verification sampling point on different spatial axes. Based on this, in one embodiment, Fig.11 As shown, the above S1020 verifies the heat conduction relationship according to the surface temperatures of multiple verification sampling points, the position information of each verification sampling point, and the internal temperature of the reference battery cell, including:

[0167] S1110 . Determine the vector value of each verification sampling point on different spatial axes according to the position information of each verification sampling point.

[0168] Optionally, after obtaining the position information of each verification sampling point, the computer device may perform spatial transformation on the position information of each verification sampling point to obtain the vector value of the verification sampling point on each preset spatial axis as the vector value of the verification sampling point on the corresponding spatial axis.

[0169] Exemplarily, when different spatial axes include an X-axis, a Y-axis, and a Z-axis that are perpendicular to each other and have a heat source point of the reference cell as the origin, for each verification sampling point, the computer device can determine the verification sampling point in the reference cell based on the position information of the verification sampling point on the reference cell, and connect the heat source point in the reference cell with the verification sampling point to form a verification vector pointing from the heat source point to the verification sampling point, and then project the verification vector to the X-axis, the Y-axis, and the Z-axis, respectively, to obtain the vector value of the verification sampling point on the X-axis, the vector value on the Y-axis, and the vector value on the Z-axis.

[0170] S1120, inputting the surface temperature of each verification sampling point, the vector value of each verification sampling point in different spatial axes, and the internal temperature of the reference battery cell into the heat conduction relationship to obtain the predicted internal temperature corresponding to each verification sampling point.

[0171] Optionally, after obtaining the surface temperature of each verification sampling point and the vector value of each verification sampling point on different spatial axes, for each verification sampling point, the computer device may input the surface temperature of the verification sampling point and the vector value on different spatial axes into the aforementioned obtained heat conduction relationship to predict the cell temperature, and obtain the predicted internal temperature of the reference cell. Multiple verification sampling points correspondingly obtain multiple predicted internal temperatures.

[0172] S1130, verifying the heat conduction relationship according to the predicted internal temperature corresponding to each verification sampling point to obtain a verification result.

[0173] Optionally, after obtaining the predicted internal temperature corresponding to each verification sampling point, the computer device may compare each predicted internal temperature with the internal temperature of the reference battery cell actually measured to determine the verification result. Exemplarily, the computer device may obtain the first temperature difference between each predicted internal temperature and the internal temperature of the reference battery cell, and determine that the thermal conduction relationship has passed the verification when the number of first temperature differences that meet the temperature difference range accounts for a greater than or equal to a preset ratio; and determine that the thermal conduction relationship has not passed the verification when the number of first temperature differences that meet the temperature difference range accounts for a less than preset ratio.

[0174] Optionally, after the computer device obtains the predicted internal temperature corresponding to each verification sampling point, it can also obtain each predicted internal temperature and compare it with the measured external temperature of the corresponding verification sampling point to determine the verification result. Exemplarily, the computer device can obtain the second temperature difference between each predicted internal temperature and the external temperature of the corresponding verification sampling point, and determine that the heat conduction relationship has passed the verification when the number of second temperature differences that meet the temperature difference range accounts for more than or equal to a preset ratio; and determine that the heat conduction relationship has not passed the verification when the number of second temperature differences that meet the temperature difference range accounts for less than a preset ratio.

[0175] In the embodiment of the present application, according to the position information of each verification sampling point, the vector value of each verification sampling point in different spatial axes is determined, the surface temperature of each verification sampling point, the vector value of each verification sampling point in different spatial axes and the internal temperature of the reference battery cell are input into the heat conduction relationship, the predicted internal temperature corresponding to each verification sampling point is obtained, and the heat conduction relationship is verified according to the predicted internal temperature corresponding to each verification sampling point to obtain the verification result. In the above method, the universality and reliability of the heat conduction relationship are verified using verification sampling points at different spatial positions, thereby improving the universality and reliability of the battery cell heat conduction model obtained based on the heat conduction relationship.

[0176] The verification of the thermal conductivity relationship includes a two-step verification process. In one embodiment, Fig.12 As shown, the above S1130 verifies the heat conduction relationship according to the predicted internal temperature corresponding to each verification sampling point to obtain a verification result, including:

[0177] S1210, obtaining the temperature difference reference range of each verification sampling point.

[0178] The temperature difference reference range is the temperature difference range between the surface temperature of the sampling point and the internal temperature of the battery cell obtained based on a large amount of measured data. The temperature difference reference ranges corresponding to verification sampling points at different locations are different.

[0179] For example, taking a rectangular reference cell as an example, the verification sampling points may be sampling points located on different surfaces of the reference cell, and the temperature difference reference ranges corresponding to the sampling points on different surfaces are shown in the following table:

[0180]

[0181] The above table also includes the heat conduction distance corresponding to different sampling points, the vector values ​​on the X-axis, Y-axis and Z-axis, and the heat transfer coefficient of the reference cell in each spatial axis.

[0182] Optionally, for each verification sampling point, the computer device may first determine the surface to which the verification sampling point belongs on the reference battery cell, so as to obtain a temperature difference reference range corresponding to the surface as the temperature difference reference range of the corresponding verification sampling point.

[0183] S1220. Determine a preliminary verification result based on the predicted internal temperature and surface temperature corresponding to each verification sampling point and the temperature difference reference range of each verification sampling point.

[0184] Optionally, the computer device may use the temperature difference reference range of each verification sampling point to verify whether the temperature difference between the predicted internal temperature and the surface temperature corresponding to each verification sampling point satisfies the temperature difference reference range, so as to perform a preliminary verification of the heat conduction relationship and obtain a preliminary verification result.

[0185] S1230: When the preliminary verification result is that the verification is passed, determine the verification result based on the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell.

[0186] Optionally, when the preliminary verification result is passed, the computer device may perform a secondary verification on the heat conduction relationship based on the predicted internal temperature corresponding to each verification sampling point and the measured internal temperature of the reference battery cell to obtain a verification result.

[0187] Optionally, in the case where the preliminary verification result is that the verification has not been passed, the computer device may directly determine that the verification result of the thermal conduction relationship is that the verification has not been passed.

[0188] In the embodiment of the present application, the temperature difference reference range of each verification sampling point is obtained, and the preliminary verification result is determined according to the predicted internal temperature and surface temperature corresponding to each verification sampling point and the temperature difference reference range of each verification sampling point. If the preliminary verification result is passed, the verification result is determined based on the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell. In the above method, the thermal conduction relationship is verified successively using the temperature difference reference range of the verification sampling point and the measured internal temperature of the reference battery cell, which realizes the double verification of the thermal conduction relationship and improves the reliability of the verification result.

[0189] To determine the preliminary verification results, in one embodiment, as Fig.13 As shown, the above S1220, according to the predicted internal temperature and surface temperature corresponding to each verification sampling point and the temperature difference reference range of each verification sampling point, determines the preliminary verification result, including:

[0190] S1310. Obtain the temperature difference between the predicted internal temperature and the surface temperature corresponding to each verification sampling point.

[0191] Optionally, for each verification sampling point, the computer device may obtain the temperature difference between the predicted internal temperature obtained based on the thermal conduction relationship of the verification sampling point and the surface temperature of the verification sampling point. Exemplarily, the verification sampling points include 1 to 3, corresponding to surface temperatures T1 to T3, and predicted internal temperatures T1' to T3', respectively. The computer device may calculate the temperature difference between the surface temperature of the verification sampling points 1 to 3 and the predicted internal temperature as △T1=T1'-T1, △T2=T2'-T2, and △T3=T3'-T3, respectively.

[0192] S1320. When all temperature differences satisfy the temperature difference reference range of the corresponding verification sampling points, determine that the preliminary verification result is passed.

[0193] Optionally, after obtaining the temperature difference corresponding to each verification sampling point, the computer device may compare the temperature difference of each verification sampling point with the temperature difference reference range of the corresponding sampling point to determine the preliminary verification result of the heat conduction relationship according to the comparison result. Wherein, when all temperature difference values ​​satisfy the temperature difference reference range of the corresponding verification sampling point, the computer device determines that the preliminary verification result of the heat conduction relationship is passed. Continuing with the above example, when △T1, △T2 and △T3 all satisfy the corresponding temperature difference reference range, the computer device determines that the preliminary verification result is passed.

[0194] S1330. When any temperature difference value does not satisfy the temperature difference reference range of the corresponding verification sampling point, determine that the preliminary verification result is failed verification.

[0195] Optionally, after obtaining the temperature difference corresponding to each verification sampling point, the computer device may compare the temperature difference of each verification sampling point with the temperature difference reference range of the corresponding sampling point to determine the preliminary verification result of the heat conduction relationship according to the comparison result. Wherein, in the case where any temperature difference does not meet the temperature difference reference range of the corresponding verification sampling point, the computer device determines that the preliminary verification result of the heat conduction relationship is not verified. Continuing with the above example, in the case where any one of △T1, △T2, and △T3 does not meet the corresponding temperature difference reference range, the computer device determines that the preliminary verification result is not verified.

[0196] In the embodiment of the present application, the temperature difference between the predicted internal temperature and the surface temperature corresponding to each verification sampling point is obtained, and when all temperature differences meet the temperature difference reference range of the corresponding verification sampling point, the preliminary verification result is determined to pass the verification, and when any temperature difference does not meet the temperature difference reference range of the corresponding verification sampling point, the preliminary verification result is determined to fail the verification. In the above method, the thermal conduction relationship is preliminarily verified based on the temperature difference reference range obtained by big data statistics, and a higher preliminary passing verification condition is adopted, which improves the model verification condition and correspondingly improves the reliability of the obtained battery cell thermal conduction model.

[0197] To determine the verification result, in one embodiment, as Fig.14 As shown, in the above S1230, when the preliminary verification result is passed, the verification result is determined based on the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell, including:

[0198] S1410 . Obtain a maximum temperature difference according to the temperature difference between the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell.

[0199] Optionally, when the preliminary verification result is that the verification is passed, for each verification reference point, the computer device can further obtain the temperature difference between the predicted internal temperature obtained based on the thermal conduction relationship of the verification sampling point and the measured internal temperature of the reference battery cell, and determine the maximum temperature difference among the temperature differences corresponding to all verification reference points. Exemplarily, continuing the above example, verification sampling points 1 to 3 correspond to the predicted internal temperatures T1' to T3', and the measured internal temperature T of the reference battery cell. The computer device can calculate the temperature difference between the preset internal temperature and the measured internal temperature of verification sampling points 1 to 3 as △T1'=T1'-T, △T2'=T2'-T, △T3'=T3'-T, respectively, and compare △T1', △T2' and △T3' to determine the maximum temperature difference △Tmax=△T2'.

[0200] S1420: When the maximum temperature difference is less than or equal to the temperature difference threshold, determine that the verification result is passed.

[0201] Among them, the maximum temperature difference is less than or equal to the temperature difference threshold, which indicates that the deviation between the predicted internal temperature obtained based on the heat conduction relationship and the actual internal temperature of the reference battery cell is small, and the prediction accuracy is high.

[0202] Optionally, after obtaining the maximum temperature difference, the computer device may compare the maximum temperature difference with a preset temperature difference threshold value to determine the verification result for the heat conduction relationship according to the comparison result. Wherein, when the maximum temperature difference is less than or equal to the temperature difference threshold value, the computer device determines that the verification result for the heat conduction relationship is passed.

[0203] S1430: When the maximum temperature difference is greater than the temperature difference threshold, determine that the verification result is failed.

[0204] Among them, the maximum temperature difference is greater than the temperature difference threshold, which indicates that the predicted internal temperature obtained based on the heat conduction relationship deviates greatly from the actual internal temperature of the reference battery cell, and the prediction accuracy is low.

[0205] Optionally, after obtaining the maximum temperature difference, the computer device may compare the maximum temperature difference with a preset temperature difference threshold to determine the verification result for the heat conduction relationship according to the comparison result. Wherein, when the maximum temperature difference is greater than the temperature difference threshold, the computer device determines that the verification result for the heat conduction relationship is not verified.

[0206] In the embodiment of the present application, the maximum temperature difference is obtained according to the temperature difference between the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell. When the maximum temperature difference is less than or equal to the temperature difference threshold, the verification result is determined to be passed, and when the maximum temperature difference is greater than the temperature difference threshold, the verification result is determined to be failed. In the above method, the thermal conductivity relationship is verified by using the measured internal temperature, which helps to obtain a thermal conductivity relationship that can reflect the actual internal temperature of the battery cell, so as to improve the reliability of the model and thus improve the accuracy of the prediction results.

[0207] In practical applications, there is more than one internal temperature of the reference cell. In one embodiment, the internal temperature of the reference cell includes a maximum internal temperature and a minimum internal temperature. The cell thermal conduction model characterizes the thermal conduction relationship between the surface temperature at different positions on the cell and the maximum internal temperature and the minimum internal temperature of the cell.

[0208] Affected by the external environment of the battery cell (such as placement and connection relationship), the internal temperature of the battery cell is also unevenly distributed, and there is a corresponding maximum internal temperature and a minimum internal temperature. Normally, the maximum internal temperature of the battery cell is the temperature at the location of the heat source in the battery cell. Exemplarily, the heat source point can be the geometric center of the battery cell, or the location of the mechanical parts on the battery cell (such as the positive pole tab, or the negative pole tab). The minimum internal temperature of the battery cell is the temperature at the position in the battery cell that is closest to the external cooling component. Exemplarily, the external cooling component can be a cooling plate in contact with the surface of the battery cell (such as a large surface).

[0209] Taking the heat source point of the reference cell as the geometric center and the side surface A as the surface in contact with the cooling plate as an example, a thermocouple needs to be arranged at the geometric center inside the reference cell to collect the maximum internal temperature of the reference cell, and a thermocouple needs to be arranged at the position inside the reference cell closest to the side surface A to collect the minimum internal temperature of the reference cell.

[0210] When the internal temperature of the reference battery cell includes the maximum internal temperature and the minimum internal temperature, the battery cell thermal conduction model correspondingly characterizes the thermal conduction relationship between the surface temperature at different positions on the battery cell and the maximum internal temperature of the battery cell and the minimum internal temperature of the battery cell, thereby achieving simultaneous prediction of the maximum internal temperature and the minimum internal temperature of the battery cell to be tested.

[0211] In the embodiment of the present application, the cell heat conduction model characterizes the heat conduction relationship between the surface temperature at different positions on the cell and the maximum temperature inside the cell and the minimum temperature inside the cell. In the above method, the cell heat conduction model can be used to achieve simultaneous prediction of the maximum temperature inside the cell and the minimum temperature inside the cell, thereby improving the data comprehensiveness of the prediction results.

[0212] In order to facilitate the understanding of those skilled in the art, the battery core temperature prediction method provided in this application is described in detail below. Fig.15 As shown, the method may include:

[0213] S1501, obtaining the surface temperature of multiple reference sampling points on the reference battery cell, the position information of the multiple reference sampling points on the reference battery cell, and the internal temperature of the reference battery cell;

[0214] S1502: for each reference sampling point, determine a reference vector pointing from a heat source point in the reference cell to the reference sampling point according to position information of the reference sampling point on the reference cell;

[0215] S1503, projecting the reference vector to the X-axis to obtain the vector value of the reference sampling point on the X-axis; projecting the reference vector to the Y-axis to obtain the vector value of the reference sampling point on the Y-axis; projecting the reference vector to the Z-axis to obtain the vector value of the reference sampling point on the Z-axis; the X-axis, Y-axis and Z-axis are perpendicular to each other and take the heat source point as the origin;

[0216] S1504, inputting the surface temperature of each reference sampling point, the vector value of the reference sampling point on the X-axis, Y-axis and Z-axis, and the internal temperature of the reference cell into the initial heat conduction model to obtain the heat conduction relationship corresponding to each reference sampling point;

[0217] S1505, according to the heat conduction relationship corresponding to each reference sampling point, solve and obtain the heat transfer coefficient value of the reference battery cell on the X-axis, Y-axis and Z-axis;

[0218] S1506, substituting the heat transfer coefficient values ​​of the reference cell on the X-axis, Y-axis and Z-axis into the corresponding heat transfer coefficient characterization quantity in the initial heat conduction model to obtain the heat conduction relationship between the surface temperature at different positions on the reference cell and the internal temperature of the reference cell;

[0219] S1507, obtaining the surface temperature of multiple verification sampling points on the reference battery cell, and the position information of the multiple verification sampling points on the reference battery cell;

[0220] S1508, verifying the heat conduction relationship according to the surface temperatures of the plurality of verification sampling points, the position information of each verification sampling point, and the internal temperature of the reference battery cell, and determining the verified heat conduction relationship as the battery cell heat conduction model;

[0221] S1509, obtaining the surface temperature of any sampling point on the surface of the battery cell to be tested, and the position information of the sampling point on the battery cell to be tested;

[0222] S1510, determining the vector value of the sampling point on the X-axis, Y-axis and Z-axis according to the position information;

[0223] S1511, input the surface temperature of the sampling point and the vector value of the sampling point on the X-axis, Y-axis and Z-axis into the battery cell thermal conduction model to obtain the internal temperature of the battery cell to be measured.

[0224] It should be noted that for the description in the above S1501-S1511, reference can be made to the relevant description in the above embodiment, and the effects are similar, so this embodiment will not be repeated here.

[0225] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0226] In one embodiment, Fig.16 As shown, a battery core temperature prediction device is provided, including: a data acquisition module 1601, a vector determination module 1602 and a temperature prediction module 1603; wherein:

[0227] The data acquisition module 1601 is used to obtain the surface temperature of any sampling point on the surface of the battery cell to be tested, and the position information of the sampling point on the battery cell to be tested;

[0228] The vector determination module 1602 is used to determine the vector values ​​of the sampling points on different spatial axes according to the position information; the origins of the different spatial axes are the heat source points in the battery cell to be tested;

[0229] The temperature prediction module 1603 is used to input the surface temperature of the sampling point and the vector value of the sampling point in different spatial axes into the battery cell thermal conduction model to obtain the internal temperature of the battery cell to be tested; wherein the battery cell thermal conduction model characterizes the thermal conduction relationship between the surface temperature and the internal temperature at different positions on the battery cell.

[0230] In one embodiment, the above device further comprises:

[0231] A reference data module, used to obtain the surface temperature of multiple reference sampling points on the reference cell, the position information of the multiple reference sampling points on the reference cell, and the internal temperature of the reference cell;

[0232] The model building module is used to determine the thermal conduction model of the battery cell according to the surface temperature of multiple reference sampling points, the position information of each reference sampling point and the internal temperature of the reference battery cell.

[0233] In one embodiment, the model building module includes:

[0234] The position submodule is used to determine the vector value of each reference sampling point on different spatial axes according to the position information of each reference sampling point on the reference battery cell; the origin of different spatial axes is the heat source point in the battery cell to be tested;

[0235] A relationship submodule, for determining a heat conduction relationship between the surface temperature at different positions on the reference cell and the internal temperature of the reference cell according to the surface temperature of each reference sampling point, the vector value of each reference sampling point in different spatial axes, and the internal temperature of the reference cell;

[0236] The model submodule is used to determine the thermal conduction model of the battery cell based on the thermal conduction relationship.

[0237] In one embodiment, the location submodule includes:

[0238] A vector unit, for determining, for each reference sampling point, a reference vector pointing from a heat source point in the reference cell to the reference sampling point according to position information of the reference sampling point on the reference cell;

[0239] The numerical unit is used to determine the vector value of the reference sampling point in different spatial axes according to the reference vector.

[0240] In one embodiment, the different spatial axes include mutually perpendicular X-axis, Y-axis and Z-axis; the numerical unit includes:

[0241] The first subunit is used to project the reference vector onto the X-axis to obtain the vector value of the reference sampling point on the X-axis;

[0242] The second subunit is used to project the reference vector onto the Y axis to obtain the vector value of the reference sampling point on the Y axis;

[0243] The third subunit is used to project the reference vector onto the Z axis to obtain the vector value of the reference sampling point on the Z axis.

[0244] In one embodiment, the relationship submodule includes:

[0245] A data input unit is used to input the surface temperature of each reference sampling point, the vector value of the reference sampling point in different spatial axes, and the internal temperature of the reference battery cell into the initial heat conduction model to obtain the heat conduction relationship corresponding to each reference sampling point;

[0246] The relationship determination unit is used to determine the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell according to the heat conduction relationship corresponding to each reference sampling point.

[0247] In one embodiment, the initial heat conduction model includes heat transfer coefficient characterization quantities in different spatial axes; the different spatial axes include mutually perpendicular X-axis, Y-axis and Z-axis; the relationship determination unit includes:

[0248] The coefficient subunit is used to solve the heat transfer coefficient values ​​of the reference cell on the X-axis, Y-axis and Z-axis according to the heat conduction relationship corresponding to each reference sampling point;

[0249] The relationship subunit is used to substitute the heat transfer coefficient values ​​of the reference cell on the X-axis, Y-axis and Z-axis into the corresponding heat transfer coefficient characterization quantity in the initial heat conduction model to obtain the heat conduction relationship between the surface temperature at different positions on the reference cell and the internal temperature of the reference cell.

[0250] In one embodiment, the model submodule includes:

[0251] A data acquisition unit, used to acquire the surface temperature of a plurality of verification sampling points on the reference battery cell, and the position information of the plurality of verification sampling points on the reference battery cell;

[0252] The model verification unit is used to verify the heat conduction relationship according to the surface temperature of multiple verification sampling points, the position information of each verification sampling point and the internal temperature of the reference battery cell, and determine the verified heat conduction relationship as the battery cell heat conduction model.

[0253] In one embodiment, the model verification unit includes:

[0254] A vector subunit, used to determine the vector value of each verification sampling point on different spatial axes according to the position information of each verification sampling point;

[0255] The prediction subunit is used to input the surface temperature of each verification sampling point, the vector value of each verification sampling point in different spatial axes, and the internal temperature of the reference battery cell into the heat conduction relationship to obtain the predicted internal temperature corresponding to each verification sampling point;

[0256] The result subunit is used to verify the heat conduction relationship according to the predicted internal temperature corresponding to each verification sampling point to obtain a verification result.

[0257] In one embodiment, the result subunit includes:

[0258] A temperature difference acquisition micro unit is used to obtain a temperature difference reference range for each verification sampling point;

[0259] A preliminary verification micro-unit, used to determine preliminary verification results based on the predicted internal temperature and surface temperature corresponding to each verification sampling point and the temperature difference reference range of each verification sampling point;

[0260] The secondary verification micro unit is used to determine the verification result based on the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell when the preliminary verification result is passed.

[0261] In one embodiment, the preliminary verification of the microunit includes:

[0262] The first acquisition item is used to obtain the temperature difference between the predicted internal temperature and the surface temperature corresponding to each verification sampling point;

[0263] The first pass item is used to determine that the preliminary verification result is passed when all temperature difference values ​​meet the temperature difference reference range of the corresponding verification sampling point;

[0264] The first failed item is used to determine that the preliminary verification result is failed verification when any temperature difference value does not meet the temperature difference reference range of the corresponding verification sampling point.

[0265] In one embodiment, the secondary verification microunit includes:

[0266] The second acquisition item is used to obtain the maximum temperature difference according to the temperature difference between the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell;

[0267] The second pass item is used to determine that the verification result is passed when the maximum temperature difference is less than or equal to the temperature difference threshold;

[0268] The second failed item is used to determine that the verification result is failed verification when the maximum temperature difference value is greater than the temperature difference threshold.

[0269] In one embodiment, the battery cell thermal conduction model represents the thermal conduction relationship between the surface temperature at different positions on the battery cell and the maximum temperature inside the battery cell and the minimum temperature inside the battery cell.

[0270] Each module in the above-mentioned battery core temperature prediction device can be implemented in whole or in part by software, hardware and their combination. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[0271] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0272] The surface temperature of any sampling point on the surface of the battery cell to be tested and the position information of the sampling point on the battery cell to be tested are obtained; the vector value of the sampling point in different spatial axes is determined according to the position information; the surface temperature of the sampling point and the vector value of the sampling point in different spatial axes are input into the battery cell thermal conduction model to obtain the internal temperature of the battery cell to be tested; wherein the origin of different spatial axes is the heat source point in the battery cell to be tested; the battery cell thermal conduction model characterizes the thermal conduction relationship between the surface temperature and the internal temperature at different positions on the battery cell.

[0273] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0274] The surface temperatures of multiple reference sampling points on the reference cell, the position information of the multiple reference sampling points on the reference cell, and the internal temperature of the reference cell are obtained; and the cell heat conduction model is determined according to the surface temperatures of the multiple reference sampling points, the position information of each reference sampling point, and the internal temperature of the reference cell.

[0275] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0276] According to the position information of each reference sampling point on the reference battery cell, the vector value of each reference sampling point in different spatial axes is determined; the origin of different spatial axes is the heat source point in the battery cell to be tested; according to the surface temperature of each reference sampling point, the vector value of each reference sampling point in different spatial axes and the internal temperature of the reference battery cell, the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell is determined; according to the heat conduction relationship, the battery cell heat conduction model is determined.

[0277] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0278] For each reference sampling point, a reference vector pointing from the heat source point in the reference cell to the reference sampling point is determined according to the position information of the reference sampling point on the reference cell; and based on the reference vector, the vector value of the reference sampling point on different spatial axes is determined.

[0279] In one embodiment, the different spatial axes include an X-axis, a Y-axis, and a Z-axis that are perpendicular to each other; when the processor executes the computer program, the following steps are also implemented:

[0280] Project the reference vector onto the X-axis to obtain the vector value of the reference sampling point on the X-axis; project the reference vector onto the Y-axis to obtain the vector value of the reference sampling point on the Y-axis; project the reference vector onto the Z-axis to obtain the vector value of the reference sampling point on the Z-axis.

[0281] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0282] The surface temperature of each reference sampling point, the vector value of the reference sampling point in different spatial axes, and the internal temperature of the reference cell are input into the initial heat conduction model to obtain the heat conduction relationship corresponding to each reference sampling point; according to the heat conduction relationship corresponding to each reference sampling point, the heat conduction relationship between the surface temperature at different positions on the reference cell and the internal temperature of the reference cell is determined.

[0283] In one embodiment, the initial heat conduction model includes heat transfer coefficient characterization quantities in different spatial axes; the different spatial axes include mutually perpendicular X-axis, Y-axis and Z-axis; when the processor executes the computer program, the following steps are also implemented:

[0284] According to the heat conduction relationship corresponding to each reference sampling point, the heat transfer coefficient values ​​of the reference battery cell on the X-axis, Y-axis and Z-axis are solved; the heat transfer coefficient values ​​of the reference battery cell on the X-axis, Y-axis and Z-axis are substituted into the corresponding heat transfer coefficient characterization quantity in the initial heat conduction model to obtain the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell.

[0285] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0286] The surface temperatures of multiple verification sampling points on the reference battery cell and the position information of the multiple verification sampling points on the reference battery cell are obtained; the heat conduction relationship is verified according to the surface temperatures of the multiple verification sampling points, the position information of each verification sampling point and the internal temperature of the reference battery cell, and the verified heat conduction relationship is determined as the battery cell heat conduction model.

[0287] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0288] According to the position information of each verification sampling point, the vector value of each verification sampling point in different spatial axes is determined; the surface temperature of each verification sampling point, the vector value of each verification sampling point in different spatial axes and the internal temperature of the reference battery cell are input into the heat conduction relationship to obtain the predicted internal temperature corresponding to each verification sampling point; the heat conduction relationship is verified according to the predicted internal temperature corresponding to each verification sampling point to obtain the verification result.

[0289] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0290] Obtain the temperature difference reference range of each verification sampling point; determine the preliminary verification result according to the predicted internal temperature and surface temperature corresponding to each verification sampling point and the temperature difference reference range of each verification sampling point; when the preliminary verification result is passed, determine the verification result based on the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell.

[0291] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0292] Obtain the temperature difference between the predicted internal temperature and the surface temperature corresponding to each verification sampling point;

[0293] When all temperature difference values ​​meet the temperature difference reference range of the corresponding verification sampling points, the preliminary verification result is determined to have passed the verification; when any temperature difference value does not meet the temperature difference reference range of the corresponding verification sampling point, the preliminary verification result is determined to have failed the verification.

[0294] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0295] According to the temperature difference between the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell, the maximum temperature difference is obtained; when the maximum temperature difference is less than or equal to the temperature difference threshold, the verification result is determined to be passed; when the maximum temperature difference is greater than the temperature difference threshold, the verification result is determined to be failed.

[0296] In one embodiment, the battery cell thermal conduction model represents the thermal conduction relationship between the surface temperature at different positions on the battery cell and the maximum temperature inside the battery cell and the minimum temperature inside the battery cell.

[0297] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0298] The surface temperature of any sampling point on the surface of the battery cell to be tested and the position information of the sampling point on the battery cell to be tested are obtained; the vector value of the sampling point in different spatial axes is determined according to the position information; the surface temperature of the sampling point and the vector value of the sampling point in different spatial axes are input into the battery cell thermal conduction model to obtain the internal temperature of the battery cell to be tested; wherein the origin of different spatial axes is the heat source point in the battery cell to be tested; the battery cell thermal conduction model characterizes the thermal conduction relationship between the surface temperature and the internal temperature at different positions on the battery cell.

[0299] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0300] The surface temperatures of multiple reference sampling points on the reference cell, the position information of the multiple reference sampling points on the reference cell, and the internal temperature of the reference cell are obtained; and the cell heat conduction model is determined according to the surface temperatures of the multiple reference sampling points, the position information of each reference sampling point, and the internal temperature of the reference cell.

[0301] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0302] According to the position information of each reference sampling point on the reference battery cell, the vector value of each reference sampling point in different spatial axes is determined; the origin of different spatial axes is the heat source point in the battery cell to be tested; according to the surface temperature of each reference sampling point, the vector value of each reference sampling point in different spatial axes and the internal temperature of the reference battery cell, the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell is determined; according to the heat conduction relationship, the battery cell heat conduction model is determined.

[0303] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0304] For each reference sampling point, a reference vector pointing from the heat source point in the reference cell to the reference sampling point is determined according to the position information of the reference sampling point on the reference cell; and based on the reference vector, the vector value of the reference sampling point on different spatial axes is determined.

[0305] In one embodiment, the different spatial axes include mutually perpendicular X-axis, Y-axis and Z-axis; when the computer program is executed by the processor, the following steps are also implemented:

[0306] Project the reference vector onto the X-axis to obtain the vector value of the reference sampling point on the X-axis; project the reference vector onto the Y-axis to obtain the vector value of the reference sampling point on the Y-axis; project the reference vector onto the Z-axis to obtain the vector value of the reference sampling point on the Z-axis.

[0307] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0308] The surface temperature of each reference sampling point, the vector value of the reference sampling point in different spatial axes, and the internal temperature of the reference cell are input into the initial heat conduction model to obtain the heat conduction relationship corresponding to each reference sampling point; according to the heat conduction relationship corresponding to each reference sampling point, the heat conduction relationship between the surface temperature at different positions on the reference cell and the internal temperature of the reference cell is determined.

[0309] In one embodiment, the initial heat conduction model includes heat transfer coefficient characterization quantities in different spatial axes; the different spatial axes include mutually perpendicular X-axis, Y-axis and Z-axis; when the computer program is executed by the processor, the following steps are also implemented:

[0310] According to the heat conduction relationship corresponding to each reference sampling point, the heat transfer coefficient values ​​of the reference battery cell on the X-axis, Y-axis and Z-axis are solved; the heat transfer coefficient values ​​of the reference battery cell on the X-axis, Y-axis and Z-axis are substituted into the corresponding heat transfer coefficient characterization quantity in the initial heat conduction model to obtain the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell.

[0311] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0312] The surface temperatures of multiple verification sampling points on the reference battery cell and the position information of the multiple verification sampling points on the reference battery cell are obtained; the heat conduction relationship is verified according to the surface temperatures of the multiple verification sampling points, the position information of each verification sampling point and the internal temperature of the reference battery cell, and the verified heat conduction relationship is determined as the battery cell heat conduction model.

[0313] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0314] According to the position information of each verification sampling point, the vector value of each verification sampling point in different spatial axes is determined; the surface temperature of each verification sampling point, the vector value of each verification sampling point in different spatial axes and the internal temperature of the reference battery cell are input into the heat conduction relationship to obtain the predicted internal temperature corresponding to each verification sampling point; the heat conduction relationship is verified according to the predicted internal temperature corresponding to each verification sampling point to obtain the verification result.

[0315] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0316] Obtain the temperature difference reference range of each verification sampling point; determine the preliminary verification result according to the predicted internal temperature and surface temperature corresponding to each verification sampling point and the temperature difference reference range of each verification sampling point; when the preliminary verification result is passed, determine the verification result based on the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell.

[0317] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0318] Obtain the temperature difference between the predicted internal temperature and the surface temperature corresponding to each verification sampling point;

[0319] When all temperature difference values ​​meet the temperature difference reference range of the corresponding verification sampling points, the preliminary verification result is determined to have passed the verification; when any temperature difference value does not meet the temperature difference reference range of the corresponding verification sampling point, the preliminary verification result is determined to have failed the verification.

[0320] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0321] According to the temperature difference between the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell, the maximum temperature difference is obtained; when the maximum temperature difference is less than or equal to the temperature difference threshold, the verification result is determined to be passed; when the maximum temperature difference is greater than the temperature difference threshold, the verification result is determined to be failed.

[0322] In one embodiment, the battery cell thermal conduction model represents the thermal conduction relationship between the surface temperature at different positions on the battery cell and the maximum temperature inside the battery cell and the minimum temperature inside the battery cell.

[0323] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0324] The surface temperature of any sampling point on the surface of the battery cell to be tested and the position information of the sampling point on the battery cell to be tested are obtained; the vector value of the sampling point in different spatial axes is determined according to the position information; the surface temperature of the sampling point and the vector value of the sampling point in different spatial axes are input into the battery cell thermal conduction model to obtain the internal temperature of the battery cell to be tested; wherein the origin of different spatial axes is the heat source point in the battery cell to be tested; the battery cell thermal conduction model characterizes the thermal conduction relationship between the surface temperature and the internal temperature at different positions on the battery cell.

[0325] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0326] The surface temperatures of multiple reference sampling points on the reference cell, the position information of the multiple reference sampling points on the reference cell, and the internal temperature of the reference cell are obtained; and the cell heat conduction model is determined according to the surface temperatures of the multiple reference sampling points, the position information of each reference sampling point, and the internal temperature of the reference cell.

[0327] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0328] According to the position information of each reference sampling point on the reference battery cell, the vector value of each reference sampling point in different spatial axes is determined; the origin of different spatial axes is the heat source point in the battery cell to be tested; according to the surface temperature of each reference sampling point, the vector value of each reference sampling point in different spatial axes and the internal temperature of the reference battery cell, the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell is determined; according to the heat conduction relationship, the battery cell heat conduction model is determined.

[0329] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0330] For each reference sampling point, a reference vector pointing from the heat source point in the reference cell to the reference sampling point is determined according to the position information of the reference sampling point on the reference cell; and based on the reference vector, the vector value of the reference sampling point on different spatial axes is determined.

[0331] In one embodiment, the different spatial axes include mutually perpendicular X-axis, Y-axis and Z-axis; when the computer program is executed by the processor, the following steps are also implemented:

[0332] Project the reference vector onto the X-axis to obtain the vector value of the reference sampling point on the X-axis; project the reference vector onto the Y-axis to obtain the vector value of the reference sampling point on the Y-axis; project the reference vector onto the Z-axis to obtain the vector value of the reference sampling point on the Z-axis.

[0333] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0334] The surface temperature of each reference sampling point, the vector value of the reference sampling point in different spatial axes, and the internal temperature of the reference cell are input into the initial heat conduction model to obtain the heat conduction relationship corresponding to each reference sampling point; according to the heat conduction relationship corresponding to each reference sampling point, the heat conduction relationship between the surface temperature at different positions on the reference cell and the internal temperature of the reference cell is determined.

[0335] In one embodiment, the initial heat conduction model includes heat transfer coefficient characterization quantities in different spatial axes; the different spatial axes include mutually perpendicular X-axis, Y-axis and Z-axis; when the computer program is executed by the processor, the following steps are also implemented:

[0336] According to the heat conduction relationship corresponding to each reference sampling point, the heat transfer coefficient values ​​of the reference battery cell on the X-axis, Y-axis and Z-axis are solved; the heat transfer coefficient values ​​of the reference battery cell on the X-axis, Y-axis and Z-axis are substituted into the corresponding heat transfer coefficient characterization quantity in the initial heat conduction model to obtain the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell.

[0337] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0338] The surface temperatures of multiple verification sampling points on the reference battery cell and the position information of the multiple verification sampling points on the reference battery cell are obtained; the heat conduction relationship is verified according to the surface temperatures of the multiple verification sampling points, the position information of each verification sampling point and the internal temperature of the reference battery cell, and the verified heat conduction relationship is determined as the battery cell heat conduction model.

[0339] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0340] According to the position information of each verification sampling point, the vector value of each verification sampling point in different spatial axes is determined; the surface temperature of each verification sampling point, the vector value of each verification sampling point in different spatial axes and the internal temperature of the reference battery cell are input into the heat conduction relationship to obtain the predicted internal temperature corresponding to each verification sampling point; the heat conduction relationship is verified according to the predicted internal temperature corresponding to each verification sampling point to obtain the verification result.

[0341] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0342] Obtain the temperature difference reference range of each verification sampling point; determine the preliminary verification result according to the predicted internal temperature and surface temperature corresponding to each verification sampling point and the temperature difference reference range of each verification sampling point; when the preliminary verification result is passed, determine the verification result based on the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell.

[0343] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0344] Obtain the temperature difference between the predicted internal temperature and the surface temperature corresponding to each verification sampling point;

[0345] When all temperature difference values ​​meet the temperature difference reference range of the corresponding verification sampling points, the preliminary verification result is determined to have passed the verification; when any temperature difference value does not meet the temperature difference reference range of the corresponding verification sampling point, the preliminary verification result is determined to have failed the verification.

[0346] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0347] According to the temperature difference between the predicted internal temperature corresponding to each verification sampling point and the internal temperature of the reference battery cell, the maximum temperature difference is obtained; when the maximum temperature difference is less than or equal to the temperature difference threshold, the verification result is determined to be passed; when the maximum temperature difference is greater than the temperature difference threshold, the verification result is determined to be failed.

[0348] In one embodiment, the battery cell thermal conduction model represents the thermal conduction relationship between the surface temperature at different positions on the battery cell and the maximum temperature inside the battery cell and the minimum temperature inside the battery cell.

[0349] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0350] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0351] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for predicting battery core temperature, characterized in that: The method comprises: Obtaining the surface temperature of any sampling point on the surface of the battery cell to be tested, and the position information of the sampling point on the battery cell to be tested; Determine the vector value of the sampling point on different spatial axes according to the position information; the origin of the different spatial axes is the heat source point in the battery cell to be tested; Inputting the surface temperature of the sampling point and the vector value of the sampling point in different spatial axes into the battery cell thermal conduction model to obtain the internal temperature of the battery cell to be tested; wherein the battery cell thermal conduction model represents the thermal conduction relationship between the surface temperature and the internal temperature at different positions on the battery cell; the battery cell thermal conduction model is determined based on a reference battery cell; The prediction method also includes two processes of preliminary verification and verification of the heat conduction relationship, including: Acquiring surface temperature and position information of a plurality of verification sampling points on the reference battery cell, so as to obtain the predicted internal temperature corresponding to each of the verification sampling points through the heat conduction relationship; Obtaining a temperature difference reference range for each of the verification sampling points, and obtaining a temperature difference between a predicted internal temperature and a surface temperature corresponding to each of the verification sampling points; If all temperature differences satisfy the temperature difference reference range of the corresponding verification sampling points, the preliminary verification result is determined to have passed the verification; if any temperature difference does not satisfy the temperature difference reference range of the corresponding verification sampling points, the preliminary verification result is determined to have failed the verification; When the preliminary verification result is that the verification is passed, a verification result is determined based on the predicted internal temperature corresponding to each of the verification sampling points and the internal temperature of the reference battery cell.

2. The method according to claim 1, characterized in that: The method further comprises: Acquire the surface temperature of a plurality of reference sampling points on a reference battery cell, the position information of the plurality of reference sampling points on the reference battery cell, and the internal temperature of the reference battery cell; The thermal conduction model of the battery cell is determined according to the surface temperatures of the plurality of reference sampling points, the position information of each of the reference sampling points, and the internal temperature of the reference battery cell.

3. The method according to claim 2, characterized in that The step of determining the thermal conduction model of the battery cell according to the surface temperatures of the plurality of reference sampling points, the position information of each of the reference sampling points, and the internal temperature of the reference battery cell comprises: According to the position information of each reference sampling point on the reference battery cell, the vector value of each reference sampling point on different spatial axes is determined; the origin of the different spatial axes is the heat source point in the battery cell to be tested; Determine a heat conduction relationship between the surface temperature at different positions on the reference cell and the internal temperature of the reference cell according to the surface temperature of each reference sampling point, the vector value of each reference sampling point in different spatial axes, and the internal temperature of the reference cell; The battery core thermal conduction model is determined according to the thermal conduction relationship.

4. The method according to claim 3, characterized in that Determining the vector value of each reference sampling point on different spatial axes according to the position information of each reference sampling point on the reference battery cell includes: For each reference sampling point, determining a reference vector pointing from a heat source point in the reference cell to the reference sampling point according to position information of the reference sampling point on the reference cell; According to the reference vector, vector values ​​of the reference sampling point in different spatial axes are determined.

5. The method according to claim 4, characterized in that The different spatial axes include an X-axis, a Y-axis, and a Z-axis that are perpendicular to each other; and determining the vector value of the reference sampling point on different spatial axes according to the reference vector includes: Projecting the reference vector onto the X-axis to obtain a vector value of the reference sampling point on the X-axis; Projecting the reference vector onto the Y axis to obtain a vector value of the reference sampling point on the Y axis; The reference vector is projected onto the Z axis to obtain a vector value of the reference sampling point on the Z axis.

6. The method according to claim 3, characterized in that: Determining the heat conduction relationship between the surface temperatures at different positions on the reference cell and the internal temperature of the reference cell according to the surface temperatures of the reference sampling points, the vector values ​​of the reference sampling points on different spatial axes, and the internal temperature of the reference cell, comprises: Inputting the surface temperature of each reference sampling point, the vector value of the reference sampling point in different spatial axes, and the internal temperature of the reference battery cell into an initial heat conduction model to obtain a heat conduction relationship corresponding to each reference sampling point; According to the heat conduction relationship corresponding to each of the reference sampling points, the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell is determined.

7. The method according to claim 6, characterized in that The initial heat conduction model includes heat transfer coefficient characterization quantities in different spatial axes; the different spatial axes include mutually perpendicular X-axis, Y-axis and Z-axis; the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell is determined according to the heat conduction relationship corresponding to each of the reference sampling points, including: According to the heat conduction relationship corresponding to each of the reference sampling points, the heat transfer coefficient values ​​of the reference battery cell on the X-axis, Y-axis and Z-axis are obtained; The heat transfer coefficient values ​​of the reference battery cell on the X-axis, Y-axis and Z-axis are substituted into the corresponding heat transfer coefficient characterization quantity in the initial heat conduction model to obtain the heat conduction relationship between the surface temperature at different positions on the reference battery cell and the internal temperature of the reference battery cell.

8. The method according to any one of claims 3 to 7, characterized in that: Determining the battery core thermal conduction model according to the thermal conduction relationship includes: Acquire the surface temperature of a plurality of verification sampling points on the reference battery cell, and the position information of the plurality of verification sampling points on the reference battery cell; The heat conduction relationship is verified according to the surface temperatures of the plurality of verification sampling points, the position information of each of the verification sampling points, and the internal temperature of the reference battery cell, and the verified heat conduction relationship is determined as the battery cell heat conduction model.

9. The method according to claim 8, characterized in that The verifying the heat conduction relationship according to the surface temperatures of the plurality of verification sampling points, the position information of each of the verification sampling points, and the internal temperature of the reference battery cell comprises: Determine the vector value of each verification sampling point on different spatial axes according to the position information of each verification sampling point; Inputting the surface temperature of each verification sampling point and the vector value of each verification sampling point in different spatial axes into the heat conduction relationship to obtain the predicted internal temperature corresponding to each verification sampling point; The heat conduction relationship is verified according to the predicted internal temperature corresponding to each of the verification sampling points and the internal temperature of the reference battery cell to obtain a verification result.

10. The method according to claim 1, characterized in that The determining of the verification result based on the predicted internal temperature corresponding to each of the verification sampling points and the internal temperature of the reference battery cell includes: Obtaining a maximum temperature difference according to a temperature difference between the predicted internal temperature corresponding to each of the verification sampling points and the internal temperature of the reference battery cell; When the maximum temperature difference is less than or equal to the temperature difference threshold, determining that the verification result is passed; When the maximum temperature difference is greater than the temperature difference threshold, it is determined that the verification result is failed.

11. The method according to claim 1, characterized in that: The battery core heat conduction model characterizes the heat conduction relationship between the surface temperature at different positions on the battery core and the maximum temperature inside the battery core and the minimum temperature inside the battery core.

12. A battery core temperature prediction device, characterized in that: The device comprises: A data acquisition module, used to acquire the surface temperature of any sampling point on the surface of the battery cell to be tested, and the position information of the sampling point on the battery cell to be tested; A vector determination module, used to determine the vector value of the sampling point on different spatial axes according to the position information; the origin of the different spatial axes is the heat source point in the battery cell to be tested; A temperature prediction module, used for inputting the surface temperature of the sampling point and the vector value of the sampling point in different spatial axes into a battery cell thermal conduction model to obtain the internal temperature of the battery cell to be measured; wherein the battery cell thermal conduction model represents the thermal conduction relationship between the surface temperature and the internal temperature at different positions on the battery cell; the battery cell thermal conduction model is determined based on a reference battery cell; The prediction device is also used to perform two processes of preliminary verification and verification of the heat conduction relationship, including: Acquiring surface temperature and position information of a plurality of verification sampling points on the reference battery cell, so as to obtain the predicted internal temperature corresponding to each of the verification sampling points through the heat conduction relationship; Obtaining a temperature difference reference range for each of the verification sampling points, and obtaining a temperature difference between a predicted internal temperature and a surface temperature corresponding to each of the verification sampling points; If all temperature differences satisfy the temperature difference reference range of the corresponding verification sampling points, the preliminary verification result is determined to have passed the verification; if any temperature difference does not satisfy the temperature difference reference range of the corresponding verification sampling points, the preliminary verification result is determined to have failed the verification; When the preliminary verification result is that the verification is passed, a verification result is determined based on the predicted internal temperature corresponding to each of the verification sampling points and the internal temperature of the reference battery cell.

13. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 11 are implemented.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 11 are implemented.

15. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 11 are implemented.

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