Method and device for measuring heat conductivity coefficient of energy storage battery and medium

Abstract

The invention discloses a method and a device for measuring the heat conductivity coefficient of an energy storage battery and a medium, and relates to the technical field of energy storage batteries. The method for measuring the heat conductivity coefficient of the energy storage battery comprises the following steps: acquiring an electrochemical-thermal coupling model of a to-be-measured energy storage battery; based on the electrochemical-thermal coupling model, acquiring simulation temperatures and test heat conductivity coefficients of all test positions on the surface of the energy storage battery to be tested under all set working conditions; actual temperatures of all test positions on the surface of the to-be-tested energy storage battery under all set working conditions are obtained respectively; and determining the actual heat conductivity coefficient of the energy storage battery to be tested according to the simulated temperature, the actual temperature and the test heat conductivity coefficient under each set working condition. According to the simulation temperature and the test heat conductivity coefficient determined based on the electrochemical-thermal coupling model under each set working condition and the actually measured actual temperature of the surface of the energy storage battery to be measured, the actual heat conductivity coefficient of the energy storage battery to be measured is determined, and the measurement process of the conductivity coefficient of the energy storage battery is simplified; and the measurement precision of the heat conductivity coefficient of the energy storage battery is improved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of energy storage batteries, and in particular to a method, device, and medium for measuring the thermal conductivity of an energy storage battery. Background Art

[0002] As an efficient and environmentally friendly energy storage technology, energy storage batteries have been widely used in electric vehicles, grid energy storage, and consumer electronics. Their performance optimization and safety assessment are receiving increasing attention. Accurately measuring the anisotropic thermal conductivity of energy storage battery electrode groups is crucial for achieving efficient thermal management design, directly impacting the thermal stability and service life of energy storage batteries.

[0003] In the prior art, the measurement of the anisotropic thermal conductivity of the energy storage battery electrode group mainly adopts the hot wire method, the laser flash method, the steady-state plate method, etc. The steady-state plate method calculates the thermal conductivity by placing the energy storage battery between two parallel plates, heating one of the plates and measuring the temperature gradient on the other plate. However, the above measurement methods all require direct heating of the energy storage battery, which will change the heat transfer characteristics inside the energy storage battery electrode group and affect the accuracy of the measurement results. At the same time, the above measurement methods can only obtain the overall thermal conductivity of the battery cell, and cannot decompose the internal anisotropic parameters such as the axial thermal conductivity and radial thermal conductivity. In addition, the temperature acquisition is affected by the contact area and contact thermal resistance of the test equipment, resulting in reduced measurement accuracy. Summary of the Invention

[0004] The present invention provides a method, device and medium for measuring the thermal conductivity of an energy storage battery, so as to simplify the measurement process of the electrical conductivity of the energy storage battery and improve the measurement accuracy of the thermal conductivity of the energy storage battery.

[0005] A first aspect of the present invention provides a method for measuring the thermal conductivity of an energy storage battery. The method for measuring the thermal conductivity of an energy storage battery comprises:

[0006] Obtain an electrochemical-thermal coupling model of the energy storage battery to be tested;

[0007] Based on the electrochemical-thermal coupling model, obtaining the simulated temperature and test thermal conductivity at each test position on the surface of the energy storage battery to be tested under each set working condition;

[0008] Respectively obtaining the actual temperature at each test position on the surface of the energy storage battery to be tested under each set working condition;

[0009] The actual thermal conductivity of the energy storage battery to be tested is determined according to the simulated temperature, the actual temperature and the tested thermal conductivity under each of the set working conditions.

[0010] Optionally, the method for measuring the thermal conductivity of an energy storage battery further includes:

[0011] Adjusting the test thermal conductivity in the electrochemical-thermal coupling model under each of the set working conditions according to the simulated temperature and the actual temperature at each of the test positions on the surface of the energy storage battery to be tested under each of the set working conditions;

[0012] Based on the electrochemical-thermal coupling model after adjusting the test thermal conductivity, the temperature at each test position on the surface of the energy storage battery to be tested under each set working condition is obtained as the corrected simulation temperature.

[0013] Optionally, obtaining an electrochemical-thermal coupling model of the energy storage battery to be tested includes:

[0014] Obtaining electrochemical parameters and physical parameters of the energy storage battery to be tested;

[0015] Establishing a battery electrochemical model according to the electrochemical parameters of the energy storage battery to be tested;

[0016] Establishing a battery thermal model according to the physical parameters of the energy storage battery to be tested;

[0017] An electrochemical-thermal coupling model of the energy storage battery to be tested is determined according to the battery electrochemical model and the battery thermal model.

[0018] Optionally, after establishing a battery electrochemical model according to the electrochemical parameters of the energy storage battery to be tested, the method further includes:

[0019] Obtaining charge and discharge voltage curves of the energy storage battery to be tested under different operating conditions;

[0020] The battery electrochemical model is modified according to the charge and discharge voltage curve.

[0021] Optionally, determining the electrochemical-thermal coupling model of the energy storage battery to be tested according to the battery electrochemical model and the battery thermal model includes:

[0022] A closed-loop model formed by the battery electrochemical model and the battery thermal model is determined as an electrochemical-thermal coupling model of the energy storage battery to be tested.

[0023] Optionally, after obtaining the electrochemical-thermal coupling model of the energy storage battery to be tested, the method further includes:

[0024] Obtaining a surface temperature distribution curve of the energy storage battery to be tested under various test conditions;

[0025] Determining the test temperature at each test position on the surface of the energy storage battery to be tested according to the surface temperature distribution curve;

[0026] When the thermal conductivity in the electrochemical-thermal coupling model is set to a preset coefficient value, obtaining the simulated temperature at each test position on the surface of the energy storage battery to be tested under each test condition based on the electrochemical-thermal coupling model;

[0027] The electrochemical-thermal coupling model is modified according to the test temperature at each test position and the simulation temperature.

[0028] Optionally, the testing of thermal conductivity includes testing of axial thermal conductivity and testing of radial thermal conductivity;

[0029] Adjusting the test thermal conductivity in the electrochemical-thermal coupling model under each of the set working conditions according to the simulated temperature and the actual temperature at each of the test positions on the surface of the energy storage battery to be tested under each of the set working conditions includes:

[0030] Determining whether the difference between the simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested is within an error range under the same set working conditions;

[0031] If not, adjusting the tested axial thermal conductivity under the set working condition by a first preset step size, and adjusting the tested radial thermal conductivity under the set working condition by a second preset step size;

[0032] After executing the electrochemical-thermal coupling model after adjusting the test thermal conductivity to obtain the temperature at each test position on the surface of the energy storage battery to be tested under the set operating condition as the corrected simulated temperature, returning to the step of determining whether the difference between the simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested under the same set operating condition is within an error range, until the difference between the corrected simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested is within the error range under the set operating condition.

[0033] Optionally, determining the actual thermal conductivity of the energy storage battery to be tested according to the simulated temperature, the actual temperature and the tested thermal conductivity under each of the set working conditions includes:

[0034] Calculating the sum of squares of the errors between the actual temperature and the simulated temperature at each of the test positions under the same set working condition;

[0035] Determine the set operating condition corresponding to the minimum value of the sum of squared errors as the first set operating condition;

[0036] The test thermal conductivity determined under the first set working condition is determined as the actual thermal conductivity of the energy storage battery to be tested.

[0037] A second aspect of the present invention provides a device for measuring the thermal conductivity of an energy storage battery. The device for measuring the thermal conductivity of an energy storage battery comprises:

[0038] Electrochemical-thermal coupling model module, used to obtain the electrochemical-thermal coupling model of the energy storage battery to be tested;

[0039] A simulated temperature and test thermal conductivity acquisition module, configured to acquire, based on the electrochemical-thermal coupling model, the simulated temperature and test thermal conductivity at each test position on the surface of the energy storage battery to be tested under each set operating condition;

[0040] An actual temperature acquisition module, used to respectively acquire the actual temperature at each test position on the surface of the energy storage battery to be tested under each set working condition;

[0041] The actual thermal conductivity determination module is used to determine the actual thermal conductivity of the energy storage battery to be tested according to the simulated temperature, the actual temperature and the test thermal conductivity under each of the set working conditions.

[0042] A third aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the above-mentioned method for measuring the thermal conductivity of an energy storage battery.

[0043] The technical solution of the present invention obtains an electrochemical-thermal coupling model of the energy storage battery under test, including a battery electrochemical model and a battery thermal model. The battery electrochemical model is used to describe the electrochemical behavior of the energy storage battery under test during the charge and discharge process. The battery thermal model is used to simulate the temperature distribution and heat conduction behavior of the energy storage battery under test during the charge and discharge process. The parameters of the battery thermal model include thermal conductivity. Therefore, based on the electrochemical-thermal coupling model, the simulated temperature and test thermal conductivity at each test position on the surface of the energy storage battery under test under various set operating conditions can be obtained. The electrochemical-thermal coupling model avoids the interference of direct heating on the internal heat transfer characteristics of the electrode group of the energy storage battery under test, ensures the authenticity of the test thermal conductivity, and can accurately determine the axial thermal conductivity and radial thermal conductivity of the energy storage battery under test, providing support for accurate thermal management of anisotropic energy storage batteries. At the same time, by obtaining the actual temperature at each test location on the surface of the energy storage battery under test under each set operating condition, the test thermal conductivity determined under the set operating condition where the error between the simulated temperature and the actual temperature at each test location is minimized can be determined as the actual thermal conductivity of the energy storage battery under test, based on the simulated temperature, actual temperature, and test thermal conductivity under each set operating condition. This significantly improves the measurement accuracy of the thermal conductivity and simplifies the measurement process. In addition, by determining the test thermal conductivity of the energy storage battery under test under each set operating condition, it provides a basis for studying the relationship between the thermal conductivity of the energy storage battery under test and factors such as discharge rate and ambient temperature, which helps to develop more intelligent thermal management strategies for energy storage batteries.

[0044] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0046] Figure 1 This is a flow chart of a method for measuring the thermal conductivity of an energy storage battery provided in Example 1 of the present invention;

[0047] Figure 2 This is a flow chart of a method for measuring the thermal conductivity of an energy storage battery provided in the second embodiment of the present invention;

[0048] Figure 3This is a schematic diagram showing the trend of actual temperature and simulated temperature at a surface test position of an energy storage battery under various set working conditions over time, provided by the second embodiment of the present invention;

[0049] Figure 4 This is a flow chart of a method for measuring the thermal conductivity of an energy storage battery provided in the third embodiment of the present invention;

[0050] Figure 5 This is a schematic diagram showing the trend of measured voltage and simulated voltage of an energy storage battery under different working conditions over time provided by the third embodiment of the present invention;

[0051] Figure 6 This is a flow chart of a method for measuring the thermal conductivity of an energy storage battery provided in the fourth embodiment of the present invention;

[0052] Figure 7 This is a schematic structural diagram of a device for measuring thermal conductivity of an energy storage battery provided in a fifth embodiment of the present invention;

[0053] Figure 8 This is a structural diagram of a controller of a thermal conductivity measurement system for an energy storage battery provided in Example 6 of the present invention. DETAILED DESCRIPTION

[0054] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0055] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0056] Example 1

[0057] Figure 1This is a flow chart of a method for measuring the thermal conductivity of an energy storage battery provided by the first embodiment of the present invention. This embodiment can be used to measure the thermal conductivity of an energy storage battery. The method can be performed by a thermal conductivity measuring device for an energy storage battery. The device can be implemented by software and / or hardware and can generally be integrated into a controller of a thermal conductivity measuring system for an energy storage battery. Figure 1 As shown, the method for measuring the thermal conductivity of the energy storage battery may include:

[0058] S101. Obtain an electrochemical-thermal coupling model of the energy storage battery to be tested.

[0059] Among them, the electrochemical-thermal coupling model can be specifically understood as a simulation system that can fully simulate the electrochemical behavior and thermal effects of the energy storage battery to be tested during the charging and discharging process. Specifically, the electrochemical-thermal coupling model can be quickly acquired based on the empirical data of the electrochemical-thermal coupling model of the energy storage battery to be tested, or can be coupled and established based on the battery electrochemical model of the energy storage battery to be tested and the battery thermal model of the battery to be tested. The present invention does not make specific restrictions on this. The electrochemical-thermal coupling model can include a battery electrochemical model and a battery thermal model. The battery electrochemical model can describe the electrochemical behavior of the energy storage battery to be tested during the charging and discharging process. The battery thermal model can simulate the temperature distribution and heat conduction behavior of the energy storage battery to be tested during the charging and discharging process. The parameters of the battery thermal model include thermal conductivity. Therefore, by obtaining the electrochemical-thermal coupling model of the energy storage battery to be tested, the simulated temperature and test thermal conductivity at each test position on the surface of the energy storage battery to be tested under the set working conditions can be obtained.

[0060] S102. Based on the electrochemical-thermal coupling model, obtain the simulated temperature and test thermal conductivity at each test position on the surface of the energy storage battery to be tested under each set working condition.

[0061] Specifically, the electrochemical-thermal coupling model can combine the battery electrochemical model with the battery thermal model to form a dynamic interactive simulation system, so that by loading each set working condition in the electrochemical-thermal coupling model, such as a discharge rate of 0.25C, 0.5C or 1C, the simulated temperature and test thermal conductivity at each test position on the surface of the energy storage battery to be tested under each set working condition can be obtained. Exemplarily, the electrochemical-thermal coupling model can calculate the electrochemical heat generation rate of the energy storage battery to be tested under specific working conditions based on the battery electrochemical model. The electrochemical heat generation rate can be determined by the polarization voltage and current in the simulation results of the electrochemical model. After calculating the electrochemical heat generation rate, the electrochemical heat generation rate can be allocated as a heat source to the three-dimensional digital model corresponding to the energy storage battery to be tested in the battery thermal model to drive the simulation of the temperature field in the battery thermal model. In the battery thermal model, the three-dimensional temperature distribution of the energy storage battery to be tested can be simulated by the solid heat transfer physical field, and the simulated temperature at each test position in the three-dimensional temperature distribution of the energy storage battery to be tested can be obtained by using the integral operator. At the same time, the parameters of the battery thermal model include thermal conductivity, and the test thermal conductivity in the electrochemical-thermal coupling model can be obtained to determine the corresponding test thermal conductivity under each set working condition.

[0062] Optionally, the test position may include the positive pole, negative pole and large surface of the energy storage battery to be tested. Among them, the positive pole and the negative pole are located on the top of the outer shell of the energy storage battery to be tested, the positive pole is connected to the positive current collector, and the negative pole is connected to the negative current collector. The positive pole and the negative pole have higher heat due to the concentration of current; the large surface can be specifically understood as a large area on the side of the energy storage battery to be tested, which reflects the overall thermal conductivity characteristics of the electrode group of the energy storage battery to be tested. By obtaining the simulated temperature of the positive pole, negative pole and large surface of the energy storage battery to be tested, the simulated temperature of the key areas of heat generation, output and heat dissipation of the energy storage battery to be tested can be obtained, thereby ensuring that the obtained simulated temperature can comprehensively cover the overall temperature of the energy storage battery to be tested, so as to improve the accuracy of the actual thermal conductivity coefficient of the energy storage battery to be tested determined subsequently.

[0063] It can also be understood that using the heat generation rate calculated by the battery electrochemical model as a heat source avoids direct heating of the energy storage battery under test by traditional methods, reduces interference with the internal heat transfer characteristics of the battery electrode group, and improves the accuracy of the thermal conductivity measurement of the energy storage battery under test. Furthermore, the electrochemical-thermal coupling model can simulate the three-dimensional temperature distribution of the energy storage battery under various set operating conditions, thereby reflecting the differences in heat conduction in the axial and radial directions of the energy storage battery under test. This provides a basis for measuring the anisotropic thermal conductivity of the energy storage battery under test and simplifies the measurement process.

[0064] S103 , respectively obtaining the actual temperature at each test position on the surface of the energy storage battery to be tested under each set working condition.

[0065] Specifically, in order to determine the actual thermal conductivity of the energy storage battery to be tested, the actual temperature at each test location on the surface of the energy storage battery to be tested under each set operating condition can also be obtained respectively, providing a data basis for subsequently determining the actual thermal conductivity of the energy storage battery to be tested based on the simulated temperature, actual temperature, and test thermal conductivity under each set operating condition. For example, multiple temperature sensors, such as thermocouples or thermistors, can be arranged at each test location on the surface of the energy storage battery to be tested, for example, at each test location on the surface of a lithium iron phosphate (LFP) battery cell with a battery capacity of 314 Ah. When the energy storage battery to be tested is placed under each set operating condition, by recording the actual temperature data detected by each temperature sensor during the discharge process of the energy storage battery to be tested, a surface temperature distribution curve of the energy storage battery to be tested can be obtained. The surface temperature distribution curve reflects the actual temperature at each test location on the surface of the energy storage battery to be tested under each set operating condition and the changing trend of the actual temperature.

[0066] In addition, the actual temperature of each test position on the surface of the energy storage battery to be tested under each set working condition is obtained through a temperature sensor, so as to obtain the actual temperature distribution data at each test position on the surface of the energy storage battery to be tested in various usage scenarios such as low-rate stable discharge and high-rate heat accumulation. In this way, the relationship between the thermal conductivity of the energy storage battery to be tested and factors such as discharge rate and current density can be analyzed through the actual temperature data under each set working condition, so as to optimize the battery design and improve the thermal management performance.

[0067] S104: Determine the actual thermal conductivity of the energy storage battery to be tested according to the simulated temperature, the actual temperature, and the tested thermal conductivity under each set working condition.

[0068] Specifically, after obtaining the simulated temperature at each test position on the surface of the energy storage battery to be tested under each set working condition according to the electrochemical-thermal coupling model provided with the test thermal conductivity, and obtaining the actual temperature at each test position on the surface of the energy storage battery to be tested under each set working condition, the simulated temperature and the actual temperature corresponding to each test position under the same set working condition can be compared point by point, and the actual thermal conductivity of the energy storage battery to be tested can be determined based on the error between the simulated temperature and the actual temperature corresponding to each test position. For example, the sum of squares of the errors between the simulated temperature and the actual temperature corresponding to each test position under the same set working condition can be calculated so that the test thermal conductivity determined under the set working condition corresponding to the minimum sum of squares of the errors can be determined as the actual thermal conductivity of the energy storage battery to be tested. At this time, the matching degree between the simulated temperature and the actual temperature is the highest. By minimizing the sum of squares of the errors to determine the actual thermal conductivity of the energy storage battery to be tested, the influence of experimental measurement errors is eliminated, the measurement accuracy of the thermal conductivity is significantly improved, and the measurement process is simplified.

[0069] It can also be understood that compared to traditional methods of measuring thermal conductivity by directly heating the energy storage battery under test, using the heat generation rate of the electrochemical-thermal coupling model as a heat source avoids direct heating from interfering with the internal heat transfer characteristics of the electrode assembly under test, ensuring the authenticity of the measured thermal conductivity. At the same time, the three-dimensional digital model established by the electrochemical-thermal coupling model can accurately simulate the temperature field inside and on the surface of the energy storage battery under test, thereby reflecting the differences in heat conduction in the axial and radial directions and accurately determining the axial and radial thermal conductivity of the energy storage battery under test, providing support for the precise design of anisotropic thermal management of the energy storage battery under test. In addition, by determining the simulated and actual temperatures at each test location on the surface of the energy storage battery under test under various set operating conditions, the measured thermal conductivity of the energy storage battery under test can be determined. This provides a basis for studying the relationship between the thermal conductivity of the energy storage battery under test and factors such as discharge rate and ambient temperature, and facilitates the development of more intelligent thermal management strategies for energy storage batteries.

[0070] This embodiment obtains an electrochemical-thermal coupling model of the energy storage battery under test, including a battery electrochemical model and a battery thermal model. The battery electrochemical model describes the electrochemical behavior of the energy storage battery under test during the charge and discharge process, and the battery thermal model simulates the temperature distribution and heat conduction behavior of the energy storage battery under test during the charge and discharge process. The battery thermal model parameters include thermal conductivity. Based on the electrochemical-thermal coupling model, simulated temperatures and test thermal conductivity at various test locations on the surface of the energy storage battery under test under various set operating conditions can be obtained. The electrochemical-thermal coupling model avoids direct heating from interfering with the internal heat transfer characteristics of the electrode assembly of the energy storage battery under test, ensuring the authenticity of the test thermal conductivity. It can also accurately determine the axial and radial thermal conductivity of the energy storage battery under test, providing support for precise anisotropic thermal management of energy storage batteries. At the same time, by obtaining the actual temperature at each test location on the surface of the energy storage battery under test under each set operating condition, the test thermal conductivity determined under the set operating condition where the error between the simulated temperature and the actual temperature at each test location is minimized can be determined as the actual thermal conductivity of the energy storage battery under test, based on the simulated temperature, actual temperature, and test thermal conductivity under each set operating condition. This significantly improves the measurement accuracy of the thermal conductivity and simplifies the measurement process. In addition, by determining the test thermal conductivity of the energy storage battery under test under each set operating condition, it provides a basis for studying the relationship between the thermal conductivity of the energy storage battery under test and factors such as discharge rate and ambient temperature, which helps to develop more intelligent thermal management strategies for energy storage batteries.

[0071] Example 2

[0072] Figure 2This is a flow chart of a method for measuring the thermal conductivity of an energy storage battery provided by the second embodiment of the present invention. Based on the above embodiment, this embodiment describes in detail the method for adjusting the test thermal conductivity in the electrochemical-thermal coupling model. Figure 2 As shown, the method for measuring the thermal conductivity of the energy storage battery of this embodiment may include:

[0073] S201. Obtain an electrochemical-thermal coupling model of the energy storage battery to be tested.

[0074] S202. Based on the electrochemical-thermal coupling model, obtain the simulated temperature and test thermal conductivity at each test position on the surface of the energy storage battery to be tested under each set working condition.

[0075] S203 , respectively obtaining the actual temperature at each test position on the surface of the energy storage battery to be tested under each set working condition.

[0076] S204 , adjusting the test thermal conductivity in the electrochemical-thermal coupling model under each set working condition according to the simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested under each set working condition.

[0077] Specifically, after obtaining the simulated temperature at each test location on the surface of the energy storage battery to be tested under each set operating condition based on the electrochemical-thermal coupling model set with the test thermal conductivity, and obtaining the actual temperature at each test location on the surface of the energy storage battery to be tested under each set operating condition, the accuracy of the test thermal conductivity set in the electrochemical-thermal coupling model can be evaluated by comparing the simulated temperature and actual temperature corresponding to the same test location under the same set operating condition, and the test thermal conductivity in the electrochemical-thermal coupling model under each set operating condition can be adaptively adjusted. This improves the accuracy of subsequent measurements of the actual thermal conductivity of the energy storage battery to be tested based on the simulated temperature, actual temperature, and test thermal conductivity under each set operating condition.

[0078] Optionally, the tested thermal conductivity includes tested axial thermal conductivity and tested radial thermal conductivity; and adjusting the tested thermal conductivity in the electrochemical-thermal coupling model under each set operating condition according to the simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested under each set operating condition, including: determining whether the difference between the simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested is within an error range under the same set operating condition; if not, adjusting the tested axial thermal conductivity under the set operating condition by a first preset step size, and adjusting the tested radial thermal conductivity under the set operating condition by a second preset step size; after executing the electrochemical-thermal coupling model based on the adjusted tested thermal conductivity to obtain the temperature at each test position on the surface of the energy storage battery to be tested under the set operating condition as the corrected simulated temperature, returning to the step of determining whether the difference between the simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested is within the error range under the same set operating condition, until the difference between the corrected simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested is within the error range under the set operating condition.

[0079] Specifically, after obtaining the simulated temperature at each test location on the surface of the energy storage battery to be tested under each set operating condition based on an electrochemical-thermal coupling model equipped with a test thermal conductivity coefficient, and obtaining the actual temperature at each test location on the surface of the energy storage battery to be tested under each set operating condition, it can be first determined whether the difference between the simulated temperature and the actual temperature at each test location on the surface of the energy storage battery to be tested under the same set operating condition is within an error range. The error range can be set according to actual needs and is not specifically limited in the present invention. For example, the error range can be a difference of less than 1°C. If the difference between the simulated temperature and the actual temperature at each test location on the surface of the energy storage battery to be tested under the same set operating condition exceeds the error range, it indicates that the simulated temperature obtained based on the electrochemical-thermal coupling model differs too much from the actual temperature, and the test thermal conductivity coefficient of the electrochemical-thermal coupling model determined under the set operating condition needs to be adjusted to ensure that the simulated temperature matches the actual temperature.

[0080] It can be understood that the thermal conductivity of the energy storage battery includes the axial thermal conductivity and the radial thermal conductivity. The axial direction can be specifically understood as the direction parallel to the surface of the electrode. Heat is mainly conducted through the current collector and the electrode material, and the axial thermal conductivity is relatively high. The radial direction can be specifically understood as the direction perpendicular to the surface of the electrode and passing through the diaphragm. Due to the low thermal conductivity of the diaphragm, the radial thermal conductivity is usually low. The electrochemical-thermal coupling model establishes a three-dimensional digital model and a solid heat transfer physical field, so that the battery thermal model can accurately simulate the temperature field inside and on the surface of the energy storage battery to be tested, thereby reflecting the difference in heat conduction in the axial and radial directions. Therefore, the test thermal conductivity in the electrochemical-thermal coupling model can include the test axial thermal conductivity and the test radial thermal conductivity, and the test axial thermal conductivity and the radial thermal conductivity can be adjusted separately. The process of adjusting the test axial thermal conductivity and the radial thermal conductivity separately can be specifically as follows: first, the adjustment range of the test axial thermal conductivity and the test radial thermal conductivity is set based on the material properties and existing experimental data. For example, the first upper limit of adjustment for the axial thermal conductivity test can be set to 30W / (m·k), and the first lower limit of adjustment for the axial thermal conductivity test can be set to -10W / (m·k); the second upper limit of adjustment for the radial thermal conductivity test can be set to -4W / (m·k), and the second lower limit of adjustment for the radial thermal conductivity test can be set to -1W / (m·k). By presetting reasonable upper and lower limits of adjustment for the axial thermal conductivity test and the radial thermal conductivity test, the adjustment range of the thermal conductivity test can be limited, avoiding blindly testing all possible values ​​and significantly reducing the number of iterations, thereby reducing computing resources and time costs.

[0081] After determining the first upper adjustment limit and the first lower adjustment limit of the test axial thermal conductivity and the second upper adjustment limit and the second lower adjustment limit of the test radial thermal conductivity, the test axial thermal conductivity can be adjusted between the first upper adjustment limit and the first lower adjustment limit by a first preset step size, and the test radial thermal conductivity can be adjusted between the second upper adjustment limit and the second lower adjustment limit by a second preset step size. For example, the test axial thermal conductivity can be adjusted from 10W / (m·k) to 30W / (m·k) in steps of 1W / (m·k); the test radial thermal conductivity can be adjusted from 1W / (m·k) to 4W / (m·k) in steps of 0.1W / (m·k), thereby obtaining multiple groups of thermal conductivity test groups consisting of each test axial thermal conductivity and each test radial thermal conductivity, so as to sequentially obtain the temperature at each test position on the surface of the energy storage battery to be tested when the electrochemical-thermal coupling model adjusted to each thermal conductivity test group is executed under the set working condition, and the temperature can be used as the corrected simulation temperature.

[0082] After determining the corrected simulated temperature at each test position on the surface of the energy storage battery to be tested, it is possible to continue to determine whether the difference between the corrected simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested is within the error range under the set working conditions. When the difference between the corrected simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested is within the error range, it indicates that the simulated temperature at this time matches the actual temperature, so that the adjusted test thermal conductivity corresponding to the electrochemical-thermal coupling model at this time can be determined as the test thermal conductivity of the electrochemical-thermal coupling model under the set working conditions. This ensures that the electrochemical-thermal coupling model can accurately simulate the electrochemical behavior and thermal effects of the energy storage battery to be tested during the charging and discharging process, and improves the accuracy of the thermal conductivity measurement of the energy storage battery to be tested. At the same time, the test axial thermal conductivity and the test radial thermal conductivity can be determined separately through the electrochemical-thermal coupling model, which provides a basis for the measurement of the anisotropic thermal conductivity of the energy storage battery to be tested and simplifies the measurement process.

[0083] S205 , based on the electrochemical-thermal coupling model after adjusting the test thermal conductivity, obtaining the temperature at each test position on the surface of the energy storage battery to be tested under each set working condition as a corrected simulation temperature.

[0084] Specifically, after determining the adjusted test thermal conductivity of the electrochemical-thermal coupling model, each set working condition can be loaded into the electrochemical-thermal coupling model based on the adjusted test thermal conductivity to obtain the simulated temperature at each test position on the surface of the energy storage battery to be tested under each set working condition, and the simulated temperature can be determined as the corrected simulated temperature. For example, Figure 3 As shown in the figure, the solid lines correspond to the actual temperature variation over time at the large surface of the energy storage battery under test at discharge rates of 0.25C, 0.5C, and 1C, respectively. The dotted lines correspond to the corrected simulated temperature variation over time at the large surface of the energy storage battery under test obtained by the electrochemical-thermal coupling model at 0.25C, 0.5C, and 1C, respectively. As can be seen from the figure, the corrected simulated temperature matches the actual temperature, ensuring that the electrochemical-thermal coupling model can accurately simulate the electrochemical behavior and thermal effects of the energy storage battery under test during the charge and discharge process, thereby ensuring the accuracy of the actual thermal conductivity of the energy storage battery under test when subsequently measured based on the simulated temperature, actual temperature, and tested thermal conductivity under each set operating condition.

[0085] S206 , determining the actual thermal conductivity of the energy storage battery to be tested according to the simulated temperature, the actual temperature, and the tested thermal conductivity under each set working condition.

[0086] In this embodiment, the test thermal conductivity in the electrochemical-thermal coupling model under each set operating condition is adjusted based on the simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested under each set operating condition. When the difference between the simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested under the same set operating condition exceeds an error range, the test axial thermal conductivity under the set operating condition is adjusted with a first preset step size, and the test radial thermal conductivity under the set operating condition is adjusted with a second preset step size. This is done until, under the set operating condition, the difference between the corrected simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested, as determined by the electrochemical-thermal coupling model after adjusting the test thermal conductivity, falls within the error range. This ensures that the electrochemical-thermal coupling model can accurately simulate the electrochemical behavior and thermal effects of the energy storage battery to be tested during the charging and discharging process. Based on the electrochemical-thermal coupling model after adjusting the test thermal conductivity, the temperature at each test position on the surface of the energy storage battery to be tested under each set working condition is obtained as the corrected simulated temperature to ensure that the corrected simulated temperature matches the actual temperature, thereby ensuring the accuracy of the actual thermal conductivity of the energy storage battery to be tested when subsequently measured based on the simulated temperature, actual temperature and test thermal conductivity under each set working condition.

[0087] Example 3

[0088] Figure 4 This is a flow chart of a method for measuring the thermal conductivity of an energy storage battery provided by the third embodiment of the present invention. Based on the above embodiment, this embodiment describes in detail the method for obtaining the electrochemical-thermal coupling model of the energy storage battery to be measured. Figure 4 As shown, the method for measuring the thermal conductivity of the energy storage battery of this embodiment may include:

[0089] S301. Obtain electrochemical parameters and physical parameters of the energy storage battery to be tested.

[0090] Specifically, in order to obtain the electrochemical-thermal coupling model of the energy storage battery to be tested, the electrochemical parameters and physical parameters of the energy storage battery to be tested can be obtained first, so that the battery electrochemical model can be established according to the electrochemical parameters of the energy storage battery to be tested, and the battery thermal model can be established according to the physical parameters of the energy storage battery to be tested. For example, the energy storage battery to be tested may include a lithium iron phosphate battery cell with a battery capacity of 314Ah. The electrochemical parameters of the energy storage battery to be tested may include: the curve of the open circuit voltage of the positive electrode material, i.e., LFP, as a function of the state of charge, the curve of the open circuit voltage of the negative electrode material, i.e., graphite, as a function of the state of charge, the diffusion coefficient, the reaction rate constant, and the electrical conductivity, etc. The physical parameters of the energy storage battery to be tested may include: the thermal conductivity, specific heat capacity, density, geometric dimensions, and heat transfer coefficient of each structural component of the energy storage battery to be tested, such as the electrode group, the shell, and the pole. Among them, the shell can be specifically understood as a protective structure that wraps the electrode group, and the pole can be specifically understood as the current output terminal of the positive and negative poles of the energy storage battery to be tested, which is usually located at the top of the shell and connected to the current collector. The electrochemical parameters and physical parameters of the energy storage battery to be tested can be measured experimentally or obtained from a material database.

[0091] S302: Establish a battery electrochemical model based on the electrochemical parameters of the energy storage battery to be tested.

[0092] Among them, the battery electrochemical model can be specifically understood as a simulation tool based on mathematical and physical principles, which is used to describe the electrochemical behavior of the energy storage battery to be tested during the charging and discharging process. The lithium battery electrode group usually adopts a wound electrode group structure. The electrode group structure of the lithium battery may include a positive electrode sheet, a negative electrode sheet, a separator arranged between the positive electrode sheet and the negative electrode sheet, and a current collector. The current collector is used to collect the current of the positive electrode sheet and the negative electrode sheet and transmit it to the external circuit. The battery electrochemical model can predict the voltage, current and heat generation characteristics of the lithium battery by simulating the diffusion of lithium ions in the electrode material, the electrochemical reaction at the interface and the charge transfer. In lithium battery research, the battery electrochemical model usually adopts a one-dimensional simplified form, such as a pseudo-two-dimensional (Pseudo-2D, P2D) model. The P2D model describes the lithium ion concentration, potential distribution and reaction kinetics through partial differential equations to dynamically reflect the electrochemical process inside the lithium battery and its interaction with the external working conditions, laying the foundation for the construction of an electrochemical-thermal coupling model.

[0093] Specifically, after obtaining the electrochemical parameters of the energy storage battery to be tested, the electrochemical parameters can be input into the simulation software to establish a battery electrochemical model, so that the initial conditions can be set, including the initial temperature and discharge rate of the energy storage battery to be tested, such as 0.25C, 0.5C or 1C, and the battery electrochemical model can be run to generate corresponding voltage and heat generation rate data. It can be understood that by establishing a battery electrochemical model, the electrochemical heat generation rate generated, such as ohmic heat, reaction heat and polarization heat, can be calculated by simulating the electrochemical reaction inside the energy storage battery to be tested. In this way, the calculated electrochemical heat generation rate can be used as a heat source input to the battery thermal model, without the need to physically heat the energy storage battery to be tested, thus avoiding the interference of heating on the internal heat transfer characteristics of the electrode group of the energy storage battery to be tested, improving the accuracy of the thermal conductivity measurement, and simplifying the measurement process.

[0094] Optionally, after establishing the battery electrochemical model according to the electrochemical parameters of the energy storage battery to be tested, the method further includes: obtaining the charge and discharge voltage curves of the energy storage battery to be tested under different working conditions; and correcting the battery electrochemical model according to the charge and discharge voltage curves.

[0095] Specifically, after establishing the battery electrochemical model, the battery electrochemical model can also be corrected by measuring the charge and discharge voltage curves of the energy storage battery to be tested under different working conditions to ensure that the battery electrochemical model can accurately reflect the electrochemical behavior of the energy storage battery to be tested under different working conditions. For example, the energy storage battery to be tested, such as a lithium iron phosphate battery cell with a battery capacity of 314Ah, can be controlled to perform constant current discharge at multiple discharge rates, and at the same time, the voltage change of the battery terminal over time is obtained and recorded by a voltmeter to obtain the charge and discharge voltage curves of the energy storage battery to be tested under different working conditions. Figure 5 As shown, the scattered lines in the figure correspond to the charge and discharge voltage curves of the lithium battery at discharge rates of 0.25C, 0.5C and 1C, respectively, ensuring that the charge and discharge conditions of the lithium battery can cover low-rate and high-rate scenarios, thereby verifying the universality of the battery electrochemical model.

[0096] After determining the charge and discharge voltage curve, the battery electrochemical model can be used to simulate the voltage curve of the energy storage battery to be tested under different working conditions. Figure 5, the solid lines in the figure are the simulated voltage curves of the battery electrochemical model when the discharge rate of the lithium battery is 0.25C, 0.5C and 1C respectively. The deviation between the test voltage in the charge and discharge voltage curve and the simulated voltage in the simulated voltage curve corresponding to the same moment can be compared to see if it is within the preset error range. When the deviation between the measured voltage and the simulated voltage is large and exceeds the preset error range, it is necessary to optimize the electrochemical parameters of the battery electrochemical model, such as the diffusion coefficient, reaction rate constant and equilibrium potential curve. For example, when the measured discharge voltage is higher than the simulated voltage, the diffusion coefficient and reaction rate constant can be increased; when the measured discharge voltage is lower than the simulated voltage, the diffusion coefficient and reaction rate constant can be reduced. By adjusting the electrochemical parameters one by one or in combination and re-running the battery electrochemical model after each adjustment, the adjusted simulated voltage curve can be generated until the deviation between the test voltage and the simulated voltage at each moment is within the preset error range, and the optimization of the battery electrochemical model is completed. By comparing with the measured charge and discharge voltage curves, the electrochemical parameters in the battery electrochemical model are optimized, thereby reducing the deviation between the battery electrochemical model and the electrochemical behavior of the energy storage battery to be tested, ensuring the reliability of the subsequent heat generation rate calculation and improving the accuracy of the thermal conductivity measurement.

[0097] S303: Establish a battery thermal model based on the physical parameters of the energy storage battery to be tested.

[0098] The battery thermal model is specifically used to simulate the temperature distribution and heat conduction behavior of the energy storage battery under test during the charging and discharging process, thereby resolving the technical problem of the traditional direct heating measurement method that cannot dynamically reflect the thermal behavior inside the energy storage battery under test. This lays the foundation for the subsequent construction of an electrochemical-thermal coupling model and the determination of the actual thermal conductivity of the energy storage battery under test based on the electrochemical-thermal coupling model. Specifically, after obtaining the physical parameters of the energy storage battery under test, the physical parameters of the battery under test and the CAD three-dimensional digital model file of the battery under test can be imported into the simulation software to establish a battery thermal model whose digital model dimensions are consistent with the actual design dimensions of the energy storage battery under test.

[0099] After establishing the battery thermal model, a heat conduction equation can be established based on Fourier's law of heat conduction to define the solid heat transfer physical field in the battery thermal model. This allows the model initial temperature and ambient temperature to be set, the natural convection heat transfer coefficient to be applied as a boundary condition, and the electrochemical heat generation rate calculated by the one-dimensional battery electrochemical model to be used as a heat source and allocated to the electrode group area of ​​the battery thermal model. The three-dimensional digital model is meshed, and the temperature field is solved by numerical methods to simulate the three-dimensional temperature distribution of the energy storage battery to be tested under different set working conditions. By importing the three-dimensional digital model and establishing the solid heat transfer physical field, the battery thermal model can accurately simulate the temperature field inside and on the surface of the energy storage battery to be tested, thereby reflecting the difference in heat conduction in the axial and radial directions, providing a basis for the measurement of anisotropic thermal conductivity, improving the accuracy of the thermal conductivity measurement of the energy storage battery to be tested, and simplifying the measurement process.

[0100] S304: Determine an electrochemical-thermal coupling model of the energy storage battery to be tested according to the battery electrochemical model and the battery thermal model.

[0101] Specifically, after obtaining the battery electrochemical model and the battery thermal model, the electrochemical-thermal coupling model of the energy storage battery to be tested can be determined based on the battery electrochemical model and the battery thermal model, so as to comprehensively simulate the electrochemical behavior and thermal effects of the energy storage battery to be tested during the charging and discharging process through the electrochemical-thermal coupling model, thereby laying the foundation for subsequently obtaining the simulated temperature and test thermal conductivity coefficient at each test position on the surface of the energy storage battery to be tested under each set operating condition based on the electrochemical-thermal coupling model.

[0102] Optionally, a closed-loop model consisting of a battery electrochemical model and a battery thermal model is determined as an electrochemical-thermal coupling model of the energy storage battery to be tested.

[0103] Specifically, the electrochemical-thermal coupling model of the energy storage battery to be tested can be determined by forming a closed-loop model with the battery electrochemical model and the battery thermal model. For example, each set operating condition, such as a discharge rate of 0.25C, 0.5C or 1C, can be loaded into the electrochemical-thermal coupling model so that the battery electrochemical model can calculate the electrochemical heat generation rate of the energy storage battery to be tested under specific operating conditions. The electrochemical heat generation rate can be determined by the polarization voltage and current in the simulation results of the electrochemical model. After calculating the electrochemical heat generation rate, the electrochemical heat generation rate can be allocated as a heat source to the three-dimensional digital-analog domain corresponding to the energy storage battery to be tested in the battery thermal model to drive the simulation of the temperature field in the battery thermal model. In the battery thermal model, the three-dimensional temperature distribution of the energy storage battery to be tested can be simulated by the solid heat transfer physical field, and the average temperature of the entire domain of the energy storage battery to be tested can be calculated using an integral operator, such as the aveop operator. The average temperature reflects the overall thermal state inside the energy storage battery to be tested. Thus, the average temperature data can be fed back to the battery electrochemical model in real time as an input parameter of the battery electrochemical model. It can be understood that temperature feedback affects the kinetic parameters of the electrochemical reaction, such as the reaction rate constant and the diffusion coefficient, through the reaction activation energy parameters, so that the heat generation rate of the battery electrochemical model can be dynamically adjusted, thereby forming a closed-loop coupling model, and the closed-loop coupling model can be determined as the electrochemical-thermal coupling model of the energy storage battery to be tested.

[0104] Optionally, after obtaining the electrochemical-thermal coupling model of the energy storage battery to be tested, the method further includes: obtaining a surface temperature distribution curve of the energy storage battery to be tested under each test condition; determining the test temperature at each test position on the surface of the energy storage battery to be tested according to the surface temperature distribution curve; when the thermal conductivity in the electrochemical-thermal coupling model is set to a preset coefficient value, obtaining the simulated temperature at each test position on the surface of the energy storage battery to be tested under each test condition based on the electrochemical-thermal coupling model; and correcting the electrochemical-thermal coupling model according to the test temperature and the simulated temperature at each test position.

[0105] Specifically, after determining the electrochemical-thermal coupling model of the energy storage battery to be tested, the electrochemical-thermal coupling model can also be corrected by measuring the surface temperature distribution curve of the energy storage battery to be tested under various test conditions, such as a discharge rate of 0.25C, 0.5C or 1C, to ensure that the electrochemical-thermal coupling model can accurately reflect the temperature distribution and heat conduction behavior of the energy storage battery to be tested during the charge and discharge process. Each test condition can be the same as or different from each set condition. The present invention does not make specific restrictions on this to ensure the universality of the electrochemical-thermal coupling model. For example, the energy storage battery to be tested, such as a lithium iron phosphate battery cell with a battery capacity of 314Ah, can be controlled to discharge at a constant current of 1C, and at the same time, the test temperature at each test position on the surface of the energy storage battery to be tested can be obtained and recorded through a temperature sensing line to obtain the surface temperature distribution curve of the energy storage battery to be tested under the test condition.

[0106] After determining the surface temperature distribution curve, the thermal conductivity in the electrochemical-thermal coupling model can be initially set to a preset coefficient value based on experience or material library data, and the electrochemical-thermal coupling model can be loaded with test conditions, so that the battery electrochemical model can calculate the heat generation rate, and the battery thermal model can simulate the three-dimensional temperature field based on the preset thermal conductivity, so that the simulated temperature at each test location can be obtained through the electrochemical-thermal coupling model. The deviation between the test temperature and the simulated temperature in the surface temperature distribution curve corresponding to the same test location can be compared to see if it is within a preset error range. When the deviation between the test temperature and the simulated temperature is large and exceeds the preset error range, it is necessary to optimize the physical parameters of the battery thermal model, such as the thermal conductivity of the electrode group of the battery to be tested. For example, when the test temperature is higher than the simulation temperature, the thermal conductivity of the electrode group can be increased; when the test temperature is lower than the simulation temperature, the thermal conductivity of the electrode group can be decreased. By adjusting the physical parameters individually or jointly and re-running the electrochemical-thermal coupling model after each adjustment, the adjusted simulated temperature at each test location is obtained until the deviation between the test temperature and the simulated temperature at each test location is within the preset error range, completing the optimization of the battery thermal model. By comparing with the measured surface temperature distribution curve to optimize the physical parameters in the battery thermal model, the deviation between the temperature distribution and heat conduction behavior of the battery thermal model and the energy storage battery under test during the charge and discharge process is reduced. This ensures that the electrochemical-thermal coupling model can accurately simulate the electrochemical behavior and thermal effects of the energy storage battery under test during the charge and discharge process, and improves the accuracy of thermal conductivity measurements.

[0107] S305 , based on the electrochemical-thermal coupling model, obtaining the simulated temperature and test thermal conductivity at each test position on the surface of the energy storage battery to be tested under each set working condition.

[0108] S306 , respectively obtaining the actual temperature at each test position on the surface of the energy storage battery to be tested under each set working condition.

[0109] S307 , determining the actual thermal conductivity of the energy storage battery to be tested according to the simulated temperature, the actual temperature, and the tested thermal conductivity under each set working condition.

[0110] In this embodiment, by obtaining the electrochemical parameters and physical parameters of the energy storage battery to be tested, a battery electrochemical model can be established based on the electrochemical parameters of the energy storage battery to be tested, and a battery thermal model can be established based on the physical parameters of the energy storage battery to be tested. After the battery electrochemical model is established, the battery electrochemical model is corrected according to the charge and discharge voltage curves of the energy storage battery to be tested under different operating conditions to ensure that the battery electrochemical model can accurately reflect the electrochemical behavior of the energy storage battery to be tested under different operating conditions. By determining the closed-loop model composed of the battery electrochemical model and the battery thermal model as the electrochemical-thermal coupling model of the energy storage battery to be tested, the electrochemical behavior and thermal effects of the energy storage battery to be tested during the charge and discharge process can be fully simulated through the electrochemical-thermal coupling model. After obtaining the electrochemical-thermal coupling model of the energy storage battery to be tested, the test temperature at each test position is determined according to the surface temperature distribution curve of the energy storage battery to be tested under each test condition, and the simulated temperature at each test position under each test condition obtained based on the electrochemical-thermal coupling model. The electrochemical-thermal coupling model is then corrected, thereby reducing the deviation between the battery thermal model and the temperature distribution and heat conduction behavior of the energy storage battery to be tested during the charging and discharging process, and improving the accuracy of thermal conductivity measurement.

[0111] Example 4

[0112] Figure 6 This is a flow chart of a method for measuring the thermal conductivity of an energy storage battery provided by the fourth embodiment of the present invention. Based on the above embodiments, this embodiment describes in detail the method for determining the actual thermal conductivity of the energy storage battery to be measured. Figure 6 As shown, the method for measuring the thermal conductivity of the energy storage battery of this embodiment may include:

[0113] S401. Obtain an electrochemical-thermal coupling model of the energy storage battery to be tested.

[0114] S402 : Based on the electrochemical-thermal coupling model, the simulated temperature and the test thermal conductivity at each test position on the surface of the energy storage battery to be tested under each set working condition are obtained.

[0115] S403 , respectively obtaining the actual temperature at each test position on the surface of the energy storage battery to be tested under each set working condition.

[0116] S404: Calculate the sum of squares of the errors between the actual temperature and the simulated temperature at each test position under the same set working condition.

[0117] Specifically, after obtaining the actual temperature and simulated temperature at each test position on the surface of the energy storage battery to be tested, the difference between the actual temperature and the simulated temperature at each test position under the same set working condition can be calculated one by one, and the sum of the squares of the differences between the actual temperature and the simulated temperature at each test position can be calculated, so as to provide a data basis for subsequently determining the actual thermal conductivity of the energy storage battery to be tested based on the set working condition corresponding to the minimum value of the sum of squares of the errors.

[0118] S405 : Determine the set operating condition corresponding to the minimum value of the sum of squares of the errors as the first set operating condition.

[0119] Specifically, after calculating the sum of the squares of the differences between the actual temperature and the simulated temperature at each test position, the set operating condition corresponding to the minimum sum of the squares of the errors can be determined by comparison, and this set operating condition is determined as the first set operating condition. The simulated temperature obtained by the electrochemical-thermal coupling model of the test thermal conductivity determined based on the first set operating condition has the highest match with the actual temperature. Therefore, by first determining the first set operating condition, the foundation is laid for the subsequent determination of the actual thermal conductivity of the energy storage battery to be tested.

[0120] S406: Determine the test thermal conductivity determined under the first set working condition as the actual thermal conductivity of the energy storage battery to be tested.

[0121] Specifically, after determining the first set operating condition, the test thermal conductivity determined under the first set operating condition can be determined as the actual thermal conductivity of the energy storage battery to be tested. The simulated temperature obtained by the electrochemical-thermal coupling model based on the test thermal conductivity determined under the first set operating condition has the highest match with the actual temperature. Therefore, the test thermal conductivity determined under the first set operating condition has the highest match with the actual thermal conductivity of the energy storage battery to be tested. By calculating the sum of squared errors and determining the test thermal conductivity when the sum of squared errors is minimized as the actual thermal conductivity, the influence of experimental measurement errors is eliminated, significantly improving the measurement accuracy of the thermal conductivity, and simplifying the measurement process.

[0122] It can also be understood that compared with the traditional method of measuring the thermal conductivity of the energy storage battery to be tested by directly heating it, the use of the electrochemical-thermal coupling model to measure the thermal conductivity avoids the interference of direct heating on the internal heat transfer characteristics of the electrode group of the energy storage battery to be tested, ensuring the authenticity of the tested thermal conductivity. At the same time, the three-dimensional digital model established by the electrochemical-thermal coupling model can accurately simulate the temperature field inside and on the surface of the energy storage battery to be tested, thereby reflecting the difference in heat conduction in the axial and radial directions, and can accurately determine the axial thermal conductivity and radial thermal conductivity of the energy storage battery to be tested, providing support for the precise design of the anisotropic thermal management of the energy storage battery to be tested. In addition, by determining the test thermal conductivity of the energy storage battery to be tested under different operating conditions, it provides a basis for studying the relationship between the thermal conductivity of the energy storage battery to be tested and factors such as discharge rate and ambient temperature, which helps to develop more intelligent thermal management strategies for energy storage batteries.

[0123] In this embodiment, by calculating the sum of squared errors between the actual temperature and the simulated temperature at each test location under the same set operating condition, the set operating condition corresponding to the minimum value of each sum of squared errors can be determined as the first set operating condition, and the test thermal conductivity determined under the first set operating condition can be determined as the actual thermal conductivity of the energy storage battery to be tested. The simulated temperature obtained based on the electrochemical-thermal coupling model of the test thermal conductivity determined under the first set operating condition has the highest degree of match with the actual temperature. Therefore, the test thermal conductivity determined under the first set operating condition has the highest degree of match with the actual thermal conductivity of the energy storage battery to be tested. By calculating the sum of squared errors and determining the test thermal conductivity that minimizes the sum of squared errors as the actual thermal conductivity, the influence of experimental measurement errors is eliminated, the measurement accuracy of the thermal conductivity is significantly improved, and the measurement process is simplified.

[0124] Example 5

[0125] Figure 7 This is a schematic diagram of the structure of a device for measuring thermal conductivity of an energy storage battery provided in the fifth embodiment of the present invention. The device can implement the method for measuring thermal conductivity of an energy storage battery provided in the embodiment of the present invention. The device can be implemented by software and / or hardware and can generally be integrated into the controller of a thermal conductivity measurement system for an energy storage battery. Figure 7 As shown, the device includes: an electrochemical-thermal coupling model module 501, a simulated temperature and test thermal conductivity acquisition module 502, an actual temperature acquisition module 503 and an actual thermal conductivity determination module 504. The specific structure of the device is as follows:

[0126] The electrochemical-thermal coupling model module 501 is used to obtain the electrochemical-thermal coupling model of the energy storage battery to be tested.

[0127] The simulated temperature and test thermal conductivity acquisition module 502 is used to obtain the simulated temperature and test thermal conductivity at each test position on the surface of the energy storage battery to be tested under each set working condition based on the electrochemical-thermal coupling model.

[0128] The actual temperature acquisition module 503 is used to respectively acquire the actual temperature at each test position on the surface of the energy storage battery to be tested under each set working condition.

[0129] The actual thermal conductivity determination module 504 is used to determine the actual thermal conductivity of the energy storage battery to be tested according to the simulated temperature, the actual temperature and the test thermal conductivity under each set working condition.

[0130] In an optional embodiment of the present invention, the simulated temperature and test thermal conductivity acquisition module 502 may also be used to: adjust the test thermal conductivity in the electrochemical-thermal coupling model under each set operating condition according to the simulated temperature and actual temperature at each test position on the surface of the energy storage battery to be tested under each set operating condition; and obtain the temperature at each test position on the surface of the energy storage battery to be tested under each set operating condition as a corrected simulated temperature based on the electrochemical-thermal coupling model after adjusting the test thermal conductivity.

[0131] In an optional embodiment of the present invention, the electrochemical-thermal coupling model module 501 can also be used to: obtain electrochemical parameters and physical parameters of the energy storage battery to be tested; establish a battery electrochemical model based on the electrochemical parameters of the energy storage battery to be tested; establish a battery thermal model based on the physical parameters of the energy storage battery to be tested; and determine the electrochemical-thermal coupling model of the energy storage battery to be tested based on the battery electrochemical model and the battery thermal model.

[0132] In an optional embodiment of the present invention, the electrochemical-thermal coupling model module 501 can also be used to: after establishing a battery electrochemical model based on the electrochemical parameters of the energy storage battery to be tested, obtain the charge and discharge voltage curves of the energy storage battery to be tested under different operating conditions; and correct the battery electrochemical model based on the charge and discharge voltage curves.

[0133] In an optional embodiment of the present invention, the electrochemical-thermal coupling model module 501 may also be used to determine a closed-loop model consisting of a battery electrochemical model and a battery thermal model as the electrochemical-thermal coupling model of the energy storage battery to be tested.

[0134] In an optional embodiment of the present invention, the electrochemical-thermal coupling model module 501 may also be used to: after obtaining the electrochemical-thermal coupling model of the energy storage battery to be tested, obtain a surface temperature distribution curve of the energy storage battery to be tested under various test conditions; determine the test temperature at each test position on the surface of the energy storage battery to be tested based on the surface temperature distribution curve; when the thermal conductivity in the electrochemical-thermal coupling model is set to a preset coefficient value, obtain the simulated temperature at each test position on the surface of the energy storage battery to be tested under various test conditions based on the electrochemical-thermal coupling model; and modify the electrochemical-thermal coupling model based on the test temperature and the simulated temperature at each test position.

[0135] In an optional embodiment of the present invention, the tested thermal conductivity includes tested axial thermal conductivity and tested radial thermal conductivity. The simulated temperature and tested thermal conductivity acquisition module 502 may further be configured to: determine whether the difference between the simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested is within an error range under the same set operating condition; if not, adjust the tested axial thermal conductivity under the set operating condition by a first preset step size, and adjust the tested radial thermal conductivity under the set operating condition by a second preset step size; after executing the electrochemical-thermal coupling model based on the adjusted tested thermal conductivity to obtain the temperature at each test position on the surface of the energy storage battery to be tested under the set operating condition as the corrected simulated temperature, return to the step of determining whether the difference between the simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested is within an error range under the same set operating condition, until the difference between the corrected simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested is within the error range under the set operating condition.

[0136] In an optional embodiment of the present invention, the actual thermal conductivity coefficient determination module 504 can also be used to: calculate the sum of squares of the errors between the actual temperature and the simulated temperature at each test position under the same set operating condition; determine the set operating condition corresponding to the minimum value of each sum of squares of the errors as the first set operating condition; and determine the test thermal conductivity coefficient determined under the first set operating condition as the actual thermal conductivity coefficient of the energy storage battery to be tested.

[0137] The above-described device for measuring the thermal conductivity of an energy storage battery can implement the method for measuring the thermal conductivity of an energy storage battery provided in any embodiment of the present invention, and possesses the corresponding functional modules and beneficial effects of the method. For technical details not fully described in this embodiment, please refer to the method for measuring the thermal conductivity of an energy storage battery provided in any embodiment of the present invention.

[0138] Since the thermal conductivity measurement device for an energy storage battery described above is capable of executing the thermal conductivity measurement method for an energy storage battery according to the embodiments of the present invention, those skilled in the art will be able to understand the specific implementation and various variations of the thermal conductivity measurement device for an energy storage battery according to the embodiments of the present invention based on the thermal conductivity measurement method for an energy storage battery described in the embodiments of the present invention. Therefore, how the thermal conductivity measurement device for an energy storage battery implements the thermal conductivity measurement method for an energy storage battery according to the embodiments of the present invention will not be described in detail herein. Any device employed by those skilled in the art to implement the thermal conductivity measurement method for an energy storage battery according to the embodiments of the present invention falls within the scope of protection of this application.

[0139] Example 6

[0140] Figure 8 A schematic diagram of the structure of a controller for a thermal conductivity measurement system for energy storage batteries that can be used to implement an embodiment of the present invention is shown. The controller can take various forms to suit the environment and requirements within the thermal conductivity measurement system for energy storage batteries, such as an industrial control computer, an embedded control system, a data acquisition terminal, a dedicated measurement controller, and a battery management system (BMS) unit. These devices are specifically designed to measure the thermal conductivity of energy storage batteries to ensure the accuracy and safety of thermal conductivity measurements of energy storage batteries. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0141] like Figure 8 As shown, the controller 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 and a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. The RAM 13 can also store various programs and data required for the operation of the controller 10. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0142] Multiple components in the controller 10 are connected to the I / O interface 15, including an input unit 16, such as measurement control buttons and a parameter adjustment panel; an output unit 17, such as a display screen and a data logging system; a storage unit 18, such as a solid-state drive or flash memory; and a communication unit 19, such as an industrial communication module or a local area network device. The communication unit 19 allows the controller 10 to exchange information / data with other devices, such as an internal network and / or a data transmission system.

[0143] The processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any other suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the method for measuring the thermal conductivity of an energy storage battery.

[0144] In some embodiments, the method for measuring the thermal conductivity of an energy storage battery may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit. In some embodiments, part or all of the computer program may be loaded and / or installed onto the thermal conductivity measurement system for the energy storage battery of the above-described embodiment via a ROM and / or a communication unit. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for measuring the thermal conductivity of the energy storage battery described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the method for measuring the thermal conductivity of the energy storage battery in any other appropriate manner (e.g., by means of firmware).

[0145] Optionally, a method for measuring the thermal conductivity of an energy storage battery may include: obtaining an electrochemical-thermal coupling model of the energy storage battery to be tested; obtaining, based on the electrochemical-thermal coupling model, a simulated temperature and a test thermal conductivity at each test position on the surface of the energy storage battery to be tested under each set operating condition; respectively obtaining the actual temperature at each test position on the surface of the energy storage battery to be tested under each set operating condition; and determining the actual thermal conductivity of the energy storage battery to be tested based on the simulated temperature, the actual temperature, and the test thermal conductivity under each set operating condition.

[0146] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0147] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0148] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0149] To provide interaction with a user, the systems and techniques described herein can be implemented on a controller having: an onboard display device (e.g., an industrial LCD screen) for displaying information to the user; and a keyboard and pointing device (e.g., a touch screen or control panel) through which the user can provide input to the controller. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0150] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0151] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0152] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in the present invention can be achieved. This is not limited herein.

[0153] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for measuring the thermal conductivity of an energy storage battery, characterized in that: include: Obtain an electrochemical-thermal coupling model of the energy storage battery to be tested; Based on the electrochemical-thermal coupling model, obtaining the simulated temperature and test thermal conductivity at each test position on the surface of the energy storage battery to be tested under each set working condition; Respectively obtaining the actual temperature at each test position on the surface of the energy storage battery to be tested under each set working condition; The actual thermal conductivity of the energy storage battery to be tested is determined according to the simulated temperature, the actual temperature and the tested thermal conductivity under each of the set working conditions.

2. The method for measuring thermal conductivity of an energy storage battery according to claim 1, wherein: Also includes: Adjusting the test thermal conductivity in the electrochemical-thermal coupling model under each of the set working conditions according to the simulated temperature and the actual temperature at each of the test positions on the surface of the energy storage battery to be tested under each of the set working conditions; Based on the electrochemical-thermal coupling model after adjusting the test thermal conductivity, the temperature at each test position on the surface of the energy storage battery to be tested under each set working condition is obtained as the corrected simulation temperature.

3. The method for measuring thermal conductivity of an energy storage battery according to claim 1, wherein: Obtain the electrochemical-thermal coupling model of the energy storage battery to be tested, including: Obtaining electrochemical parameters and physical parameters of the energy storage battery to be tested; Establishing a battery electrochemical model according to the electrochemical parameters of the energy storage battery to be tested; Establishing a battery thermal model according to the physical parameters of the energy storage battery to be tested; An electrochemical-thermal coupling model of the energy storage battery to be tested is determined according to the battery electrochemical model and the battery thermal model.

4. The method for measuring thermal conductivity of an energy storage battery according to claim 3, wherein: After establishing a battery electrochemical model according to the electrochemical parameters of the energy storage battery to be tested, the method further includes: Obtaining charge and discharge voltage curves of the energy storage battery to be tested under different operating conditions; The battery electrochemical model is modified according to the charge and discharge voltage curve.

5. The method for measuring thermal conductivity of an energy storage battery according to claim 3, wherein: Determining an electrochemical-thermal coupling model of the energy storage battery to be tested according to the battery electrochemical model and the battery thermal model includes: A closed-loop model formed by the battery electrochemical model and the battery thermal model is determined as an electrochemical-thermal coupling model of the energy storage battery to be tested.

6. The method for measuring thermal conductivity of an energy storage battery according to claim 1, wherein: After obtaining the electrochemical-thermal coupling model of the energy storage battery to be tested, it also includes: Obtaining a surface temperature distribution curve of the energy storage battery to be tested under various test conditions; Determining the test temperature at each test position on the surface of the energy storage battery to be tested according to the surface temperature distribution curve; When the thermal conductivity in the electrochemical-thermal coupling model is set to a preset coefficient value, obtaining the simulated temperature at each test position on the surface of the energy storage battery to be tested under each test condition based on the electrochemical-thermal coupling model; The electrochemical-thermal coupling model is modified according to the test temperature at each test position and the simulation temperature.

7. The method for measuring thermal conductivity of an energy storage battery according to claim 2, wherein: The thermal conductivity test includes the axial thermal conductivity test and the radial thermal conductivity test; Adjusting the test thermal conductivity in the electrochemical-thermal coupling model under each of the set working conditions according to the simulated temperature and the actual temperature at each of the test positions on the surface of the energy storage battery to be tested under each of the set working conditions includes: Determining whether the difference between the simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested is within an error range under the same set working conditions; If not, adjusting the tested axial thermal conductivity under the set working condition by a first preset step size, and adjusting the tested radial thermal conductivity under the set working condition by a second preset step size; After executing the electrochemical-thermal coupling model after adjusting the test thermal conductivity to obtain the temperature at each test position on the surface of the energy storage battery to be tested under the set operating condition as the corrected simulated temperature, returning to the step of determining whether the difference between the simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested under the same set operating condition is within an error range, until the difference between the corrected simulated temperature and the actual temperature at each test position on the surface of the energy storage battery to be tested is within the error range under the set operating condition.

8. The method for measuring thermal conductivity of an energy storage battery according to claim 1, wherein: Determining the actual thermal conductivity of the energy storage battery to be tested according to the simulated temperature, the actual temperature, and the tested thermal conductivity under each of the set working conditions includes: Calculating the sum of squares of the errors between the actual temperature and the simulated temperature at each of the test positions under the same set working condition; Determine the set operating condition corresponding to the minimum value of the sum of squared errors as the first set operating condition; The test thermal conductivity determined under the first set working condition is determined as the actual thermal conductivity of the energy storage battery to be tested.

9. A device for measuring thermal conductivity of an energy storage battery, characterized in that: include: Electrochemical-thermal coupling model module, used to obtain the electrochemical-thermal coupling model of the energy storage battery to be tested; A simulated temperature and test thermal conductivity acquisition module, configured to acquire, based on the electrochemical-thermal coupling model, the simulated temperature and test thermal conductivity at each test position on the surface of the energy storage battery to be tested under each set operating condition; An actual temperature acquisition module, used to respectively acquire the actual temperature at each test position on the surface of the energy storage battery to be tested under each set working condition; The actual thermal conductivity determination module is used to determine the actual thermal conductivity of the energy storage battery to be tested according to the simulated temperature, the actual temperature and the test thermal conductivity under each of the set working conditions.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method for measuring the thermal conductivity of an energy storage battery according to any one of claims 1 to 8.

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