Battery temperature prediction method, prediction device, electronic device and storage medium

Abstract

The present application discloses a battery temperature prediction method, prediction device, electronic device, and storage medium. The battery temperature prediction method includes: performing a charge and discharge test on a target battery to obtain test data of the target battery, wherein the test data includes the voltage and current of the target battery during the charge and discharge test; based on the voltage and current of the test data, obtaining the ratio of the discharge energy to the charge energy of the charge and discharge test to obtain the current energy efficiency of the target battery; obtaining the current temperature of the target battery based on the current energy efficiency and a preset correspondence; the preset correspondence includes at least a first correspondence between the energy efficiency of the target battery and the surface temperature of the target battery. The battery temperature prediction method does not require an EIS test on the battery, has low requirements for test equipment, and greatly expands the applicable scenarios of battery temperature prediction technology.

Description

Technical Field

[0001] The present application relates to the field of battery technology, and in particular to a battery temperature prediction method, prediction device, electronic device, and storage medium. Background Art

[0002] Batteries, particularly lithium-ion batteries, play a vital role in portable devices, electric vehicles, and renewable energy storage. However, batteries generate heat during charging and discharging. If not properly managed, this heat can lead to performance degradation, shortened service life, and even pose safety risks. Therefore, battery temperature prediction is crucial to improving the performance, safety, and lifespan of battery systems.

[0003] In related technologies, the solution used for battery temperature prediction is to estimate the battery cell temperature through impedance test data and a pre-constructed function between low-frequency impedance and temperature. This requires an EIS (Electrochemical Impedance Spectroscopy, EIS for short) test on the battery, which places high demands on the test equipment and limits its applicable scenarios.

[0004] The above statements are only used to provide background information related to the present application and do not necessarily constitute prior art. Summary of the Invention

[0005] In view of the problem that the above-mentioned related technologies have high requirements for testing equipment, resulting in limited applicable scenarios, the present application provides a battery temperature prediction method, prediction device, electronic device and storage medium to at least partially solve the problem that the related technologies have high requirements for testing equipment, resulting in limited applicable scenarios.

[0006] A first aspect of an embodiment of the present application provides a battery temperature prediction method, comprising:

[0007] Performing a charge and discharge test on a target battery to obtain test data of the target battery, wherein the test data includes a voltage and a current of the target battery during the charge and discharge test;

[0008] Based on the voltage and current of the test data, obtaining a ratio of discharge energy to charge energy of the charge-discharge test to obtain a current energy efficiency of the target battery;

[0009] The current temperature of the target battery is acquired according to the current energy efficiency and a preset corresponding relationship; the preset corresponding relationship includes at least a first corresponding relationship between the energy efficiency of the target battery and the surface temperature of the target battery.

[0010] The battery temperature prediction method provided in the embodiment of the present application is different from the technical solution in the related art that estimates the battery cell temperature through impedance test data and a pre-constructed function between low-frequency impedance and temperature. It does not require EIS testing of the battery and has low requirements for test equipment, which greatly expands the applicable scenarios of battery temperature prediction technology.

[0011] In some embodiments of the present application, the voltage and current of the test data include the real-time discharge voltage, real-time discharge current, real-time charge voltage, and real-time charge current of the target battery during the charge and discharge test;

[0012] The step of obtaining a ratio of discharge energy to charge energy of the charge-discharge test based on the voltage and current of the test data to obtain a current energy efficiency of the target battery includes:

[0013] Based on the voltage and current of the test data, a first discharge energy and a first charge energy of the charge-discharge test are obtained; the first discharge energy is the cumulative discharge energy generated by the real-time discharge voltage and the real-time discharge current during a time interval of the charging process of the charge-discharge test; and the first charge energy is the cumulative charge energy generated by the real-time charge voltage and the real-time charge current during a time interval of the discharging process of the charge-discharge test;

[0014] A first ratio of the first discharge energy to the first charge energy is obtained, where the first ratio is a current energy efficiency of the target battery.

[0015] Energy efficiency is sensitive to test temperature and test rate, and has low sensitivity to battery aging status. Using energy efficiency as a temperature monitoring indicator can eliminate the influence of battery cell aging status factors. When the test rate remains unchanged, the battery cell temperature can be approximately obtained, which simplifies the battery temperature acquisition steps and improves the battery temperature acquisition efficiency.

[0016] In some embodiments of the present application, obtaining the current temperature of the target battery according to the current energy efficiency and a preset correspondence includes:

[0017] Substituting the current energy efficiency into a function expression representing the first correspondence relationship to calculate the current target battery surface temperature, the function expression being a univariate multivariate function with the target battery surface temperature as a dependent variable and the target battery energy efficiency as an independent variable. This allows for more efficient acquisition of the target battery surface temperature.

[0018] In some embodiments of the present application, the preset correspondence further includes a second correspondence between the target battery internal temperature, the target battery surface temperature, and the target battery ambient temperature; and obtaining the current temperature of the target battery according to the current energy efficiency and the preset correspondence includes:

[0019] Obtaining a current target battery surface temperature based on the first corresponding relationship;

[0020] The current internal temperature of the target battery is obtained based on the current target battery surface temperature, the current target battery ambient temperature, and the second corresponding relationship. This allows for more efficient acquisition of the internal temperature of the battery, helping to further reflect the overall temperature of the battery.

[0021] In some embodiments of the present application, obtaining the current internal battery temperature of the target battery according to the current target battery surface temperature, the current ambient temperature of the target battery, and the second corresponding relationship includes:

[0022] Substituting the current target battery surface temperature and the current target battery ambient temperature into the function expression representing the second correspondence relationship, the current internal battery temperature of the target battery is calculated. This allows for more efficient acquisition of the internal battery temperature, helping to further reflect the overall battery temperature.

[0023] In some embodiments of the present application, obtaining the first correspondence includes:

[0024] Performing multiple first calibration tests on a first battery and obtaining a battery surface temperature, a second discharge energy, and a second charge energy for each first calibration test; the model of the first battery is the same as the model of the target battery; the second discharge energy is the cumulative charge energy generated by the real-time discharge voltage and real-time discharge current of the first calibration test during a discharge time interval of the first calibration test; and the second charge energy is the cumulative charge energy generated by the real-time charge voltage and real-time charge current of the first calibration test during a charge time interval of the first calibration test;

[0025] For each of the first calibration tests, obtaining a second ratio of the second discharge energy to the second charge energy in the first calibration test, where the second ratio is the energy efficiency of the first calibration test;

[0026] The first corresponding relationship is obtained by fitting based on the energy efficiency and battery surface temperature of the multiple first calibration tests. In this way, the corresponding relationship between the battery energy efficiency and the battery surface temperature can be obtained more accurately, which helps to improve the accuracy of predicting the battery temperature based on the battery energy efficiency.

[0027] In some embodiments of the present application, obtaining the battery surface temperature of each first calibration test includes:

[0028] For each of the first calibration tests, during the first calibration test, the ambient temperature of the battery is detected multiple times to obtain multiple temperature detection values;

[0029] The average value of the plurality of temperature detection values ​​is calculated to obtain the battery surface temperature of the first calibration test. In this way, a relatively accurate battery surface temperature can be obtained.

[0030] In some embodiments of the present application, the method further comprises:

[0031] During the process of performing multiple first calibration tests on the first battery, the internal temperature of the battery and the ambient temperature of the battery are obtained during each first calibration test;

[0032] Based on the battery surface temperature, the battery internal temperature, and the battery ambient temperature during the multiple first calibration tests, a second corresponding relationship is obtained by fitting; the second corresponding relationship is a corresponding relationship between the battery internal temperature, the battery surface temperature, and the battery ambient temperature. The second corresponding relationship obtained in this way is relatively accurate.

[0033] According to a second aspect of an embodiment of the present application, a battery temperature prediction device is provided, comprising:

[0034] a charge and discharge test module, configured to perform a charge and discharge test on a target battery and obtain test data of the target battery, wherein the test data includes a voltage and a current of the target battery during the charge and discharge test;

[0035] an energy efficiency determination module, configured to obtain a ratio of discharge energy to charge energy of the charge-discharge test based on the voltage and current of the test data, and obtain a current energy efficiency of the target battery;

[0036] The battery temperature acquisition module is used to acquire the current temperature of the target battery according to the current energy efficiency and a preset corresponding relationship; the preset corresponding relationship at least includes a first corresponding relationship between the energy efficiency of the target battery and the target battery surface temperature.

[0037] The battery temperature prediction device of the second aspect of the embodiment of the present application can achieve the same beneficial technical effects as the battery temperature prediction method of the first aspect of the embodiment of the present application.

[0038] According to a third aspect of an embodiment of the present application, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the battery temperature prediction method described in any embodiment of the present application.

[0039] The electronic device of the third aspect of the embodiment of the present application can achieve the same beneficial technical effects as the battery temperature prediction method of the first aspect of the embodiment of the present application.

[0040] According to a fourth aspect of the embodiments of the present application, a computer-readable storage medium is provided, on which a computer program is stored. The computer program is executed by a processor to implement the battery temperature prediction method described in any embodiment of the present application.

[0041] The computer-readable storage medium of the fourth aspect of the embodiment of the present application can achieve the same beneficial technical effects as the battery temperature prediction method of the first aspect of the embodiment of the present application.

[0042] The above description is only an overview of the technical solutions of the embodiments of the present application. In order to more clearly understand the technical means of the embodiments of the present application, they can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the embodiments of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the embodiments below. The accompanying drawings are only for the purpose of illustrating the embodiments of the present application and are not to be considered as limiting the present application. The same reference numerals are used throughout the drawings to represent the same components.

[0044] Figure 1 FIG. 4 is a flow chart of a battery temperature prediction method according to one or more embodiments.

[0045] Figure 2 A flowchart of determining the current energy efficiency of a target battery based on test data according to one or more embodiments is provided.

[0046] Figure 3 The present invention is a flowchart of obtaining the current temperature of a target battery according to the current energy efficiency and a preset correspondence relationship according to one or more embodiments.

[0047] Figure 4 A graph showing the relationship between battery energy efficiency and battery surface temperature constructed based on test data from a calibration test according to one or more embodiments.

[0048] Figure 5The figure is a data graph showing the measured and predicted temperatures of the cell surfaces of a battery under actual operating conditions according to one or more embodiments.

[0049] Figure 6 FIG. 4 is a structural block diagram of a battery temperature prediction device according to one or more embodiments.

[0050] Figure 7 FIG. 4 is a structural block diagram of an electronic device according to one or more embodiments.

[0051] Figure 8 is a schematic diagram of a computer-readable storage medium according to one or more embodiments. DETAILED DESCRIPTION

[0052] The following embodiments of the technical solution of the present application will be described in detail with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present application and are therefore only examples and are not intended to limit the scope of protection of the present application.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned figure descriptions are intended to cover non-exclusive inclusions.

[0054] In the description of the embodiments of this application, technical terms such as "first" and "second" are used solely to distinguish between different objects and should not be understood to indicate or imply relative importance, or to implicitly specify the quantity, specific order, or primary and secondary relationship of the technical features indicated. In the description of the embodiments of this application, "plurality" means two or more (including two), unless otherwise specifically defined.

[0055] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0056] In the description of the embodiments of this application, the term "and / or" is simply a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent the following three situations: A exists, A and B exist at the same time, and B exists. In addition, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0057] The solution used in related technologies to predict battery temperature is to estimate the cell temperature through impedance test data and a pre-constructed function between low-frequency impedance and temperature. This requires EIS testing of the battery, so the solution in related technologies has high requirements for test equipment, resulting in limited applicable scenarios.

[0058] In response to the problems existing in the related art, the embodiment of the present application provides a battery temperature prediction method, which performs charge and discharge tests on the target battery to obtain test data of the target battery, wherein the test data includes the voltage and current of the target battery in the charge and discharge test. Then, based on the voltage and current of the test data, the ratio of the discharge energy to the charge energy of the charge and discharge test is obtained to obtain the current energy efficiency of the target battery. Then, based on the current energy efficiency and a preset correspondence, the current temperature of the target battery is obtained. The preset correspondence includes at least a first correspondence between the energy efficiency of the target battery and the surface temperature of the target battery. Different from the technical solution in the related art that estimates the battery cell temperature by impedance test data and a pre-constructed function between low-frequency impedance and temperature, there is no need to perform EIS (Electrochemical Impedance Electrochemical impedance spectroscopy (EIS) is a key technology in the field of electrochemical testing. It applies a small-amplitude sinusoidal potential or current disturbance to the electrochemical system, measures the corresponding current or potential response generated by the system, and then plots an impedance spectrum. The impedance spectrum depicts the changing relationship between the impedance of the electrochemical system and frequency. This test has low requirements for test equipment and greatly expands the applicable scenarios of battery temperature prediction technology.

[0059] The battery temperature prediction method of the embodiment of the present application can be applied to application scenarios such as battery temperature detection, for example, in application scenarios such as power battery temperature detection of power vehicles and temperature detection of energy storage batteries. The battery in the embodiment of the present application may be, but is not limited to, a battery cell, a single battery, a battery module or a battery pack. The battery may be a battery of any chemical type, such as a lithium iron phosphate battery, a lithium-ion battery, a nickel-cadmium battery, a nickel-hydrogen battery, a lead-acid battery, etc. The battery may be a battery of any shape and structure, such as a cylindrical battery, a flat battery, a soft-pack battery, a square battery, etc. The battery can be applied to any application scenario that requires the use of a battery, and the battery can be used as a consumer electronic battery, such as for mobile phones, laptop computers, etc. The battery can also be used as an energy storage battery, and the battery can also be used as a power battery, such as for electric vehicles, electric bicycles, electric aircraft, electric ships, etc.

[0060] The following describes a battery temperature prediction method, a battery temperature prediction device, an electronic device, and a computer-readable storage medium according to embodiments of the present application in conjunction with the accompanying drawings.

[0061] refer to Figure 1 As shown, an embodiment of the present application provides a battery temperature prediction method, which may include steps S10-S30:

[0062] S10 . Perform a charge and discharge test on the target battery to obtain test data of the target battery, where the test data includes the voltage and current of the target battery during the charge and discharge test.

[0063] The charge and discharge test can include one discharge process and one charge process. The target battery is discharged and charged once by the charge and discharge equipment, and the real-time current and real-time voltage of the target battery are recorded during the charge and discharge test.

[0064] S20 . Based on the voltage and current of the test data, obtain the ratio of the discharge energy to the charge energy of the charge and discharge test to obtain the current energy efficiency of the target battery.

[0065] In some embodiments, the voltage and current of the test data may include the real-time discharge voltage, real-time discharge current, real-time charge voltage, and real-time charge current of the target battery during the charge and discharge test. Figure 2 As shown, based on the voltage and current of the test data, obtaining the ratio of the discharge energy to the charge energy of the charge and discharge test to obtain the current energy efficiency of the target battery may include:

[0066] S201 : Acquire a first discharge energy and a first charge energy of a charge-discharge test based on the voltage and current of the test data.

[0067] The first discharge energy is the accumulated discharge energy generated by the real-time discharge voltage and the real-time discharge current during the time interval of the charging process of the charge-discharge test; specifically, the first discharge energy can be the integrated value of the product of the real-time discharge voltage and the real-time discharge current during the time interval of the charging process, or sampling can be performed during the charging process of the charge-discharge test to obtain multiple sampling points, each sampling point including the real-time discharge voltage and the real-time discharge current at the sampling moment, and the power corresponding to each sampling point is calculated, and the power corresponding to each sampling point is equal to the product of the real-time discharge voltage and the real-time discharge current at the sampling point, and the power point is depicted in a pre-set rectangular coordinate system, and each power point includes the power corresponding to each sampling point and the corresponding sampling current. At the sampling moment, the horizontal coordinate axis of the preset rectangular coordinate system is the sampling moment coordinate axis, and the vertical coordinate axis is the power. Then, all power points are connected in sequence according to the sampling moments to obtain a broken line, and a straight line perpendicular to the horizontal coordinate axis is drawn at the end time of the charging process of the charge-discharge test. The vertical coordinate axis is perpendicular to the vertical coordinate axis with the earliest power point at the sampling moment as the endpoint, and the straight line is perpendicular to the vertical coordinate axis with the latest power point at the sampling moment as the endpoint, thereby obtaining a closed first polygon, dividing the first polygon using a geometric method, calculating the area of ​​each divided part, and then summarizing and calculating the area of ​​the first polygon, and the area of ​​the first polygon is used as the first discharge energy.

[0068] The first charging energy is the cumulative charging energy generated by the real-time charging voltage and the real-time charging current during the time interval of the discharge process of the charge and discharge test. Specifically, the first charging energy can be the integrated value of the product of the real-time charging voltage and the real-time charging current during the time interval of the discharge process. Alternatively, the first charging energy can be obtained by plotting charging power sampling points on a pre-set rectangular coordinate system, then connecting each charging power sampling point in sequence according to the sampling time to obtain a broken line, using the broken line and the coordinate axes to form a closed second polygon, calculating the area of ​​the second polygon, and using the area of ​​the second polygon as the first charging energy.

[0069] S202 : Obtain a first ratio of the first discharge energy to the first charge energy, where the first ratio is the current energy efficiency of the target battery.

[0070] The current energy efficiency of the target battery is calculated as η=DE / CE*100%.

[0071] Wherein, DE represents the first discharge energy, and CE represents the first charge energy.

[0072] A battery's energy efficiency (EE) refers to the ratio of energy output to energy input during the charge and discharge process, typically expressed as a percentage. It is a core metric for measuring a battery's energy conversion performance. Energy efficiency is sensitive to test temperature and test rate, but less sensitive to battery aging. Using energy efficiency as a temperature monitoring metric eliminates the influence of cell aging. While maintaining a constant test rate, it can approximate the cell's temperature, simplifying the battery temperature acquisition process and improving its efficiency.

[0073] S30 : Acquire the current temperature of the target battery according to the current energy efficiency and a preset corresponding relationship.

[0074] The preset correspondence includes at least a first correspondence between the energy efficiency of the target battery and the target battery surface temperature. The current temperature of the target battery may include the target battery surface temperature and / or the target battery internal temperature. The battery surface temperature refers to the temperature of the outer surface of the battery. For example, the average temperature of multiple points on the outer surface of the battery may be used as the battery surface temperature. The battery internal temperature refers to the temperature within a preset size range inside the battery with the center point of the battery as a reference point. For example, the average temperature within a spherical shape with the center point of the battery as the center and the length from the center point as a preset value inside the battery may be used as the battery internal temperature. Alternatively, the average temperature of a geometric body with the center point of the battery as the center and similar to the overall shape of the battery may be used as the battery internal temperature. Estimating the operating temperature of the battery cell based on the test energy efficiency does not require additional arrangement of temperature sensors, simplifies the test system structure, improves test efficiency, and reduces the test cost during the battery life cycle.

[0075] In some embodiments, obtaining the current target battery temperature based on the current energy efficiency and the preset correspondence relationship may include substituting the current energy efficiency into a function expression representing the first correspondence relationship to calculate the current target battery surface temperature. This allows for more efficient acquisition of the target battery surface temperature.

[0076] The function expression representing the first correspondence is a univariate multinomial function with the target battery surface temperature as a dependent variable and the target battery energy efficiency as an independent variable. Function expressions representing the first correspondence include, but are not limited to, a univariate n-order function, where n is an integer greater than 1, and the univariate n-order function is a univariate n-order function with the battery surface temperature as a dependent variable and the energy efficiency as an independent variable; a univariate n-order function is also a univariate multinomial function.

[0077] For example, the function expression representing the first corresponding relationship may be a quadratic function with the battery surface temperature as the dependent variable and the energy efficiency as the independent variable, for example:

[0078] ;

[0079] in, T e Represents the surface temperature of the target battery; stands for energy efficiency; a 、 b and c are preset constants. a 、 b and c The values ​​of are obtained by pre-fitting. For example, in a specific example, a=9545.9, b=-16927, and c=7522.9.

[0080] In some embodiments, the preset correspondence relationship further includes a second correspondence relationship between the target battery internal temperature, the target battery surface temperature, and the target battery ambient temperature; Figure 3 As shown, obtaining the current temperature of the target battery according to the current energy efficiency and the preset corresponding relationship may include steps S301-S302:

[0081] S301 : Obtain a current target battery surface temperature based on a first corresponding relationship.

[0082] Specifically, the current energy efficiency is substituted into the function expression representing the first correspondence relationship to calculate the current target battery surface temperature. The function expression representing the first correspondence relationship is a univariate multivariate function with the target battery surface temperature as the dependent variable and the target battery energy efficiency as the independent variable.

[0083] S302: Obtain the current internal temperature of the target battery based on the current target battery surface temperature, the current target battery ambient temperature, and the second corresponding relationship. This allows for more efficient acquisition of the internal temperature of the battery, helping to further reflect the overall temperature of the battery.

[0084] In some embodiments, obtaining the current internal temperature of the target battery based on the current target battery surface temperature, the current target battery ambient temperature, and the second corresponding relationship may include substituting the current target battery surface temperature and the current target battery ambient temperature into a function expression representing the second corresponding relationship to calculate the current internal temperature of the target battery. This allows for more efficient acquisition of the internal temperature of the battery, helping to further reflect the overall temperature of the battery.

[0085] For example, the function expression representing the second corresponding relationship is:

[0086]

[0087] Where f(T0) and g(T e ) can be a function related to battery design parameters (such as battery cell material and shape).

[0088] In one example, the function expression representing the second corresponding relationship is a binary linear function with the battery surface temperature and the battery environment temperature as independent variables and the battery internal temperature as the dependent variable. For example,

[0089]

[0090] in, Represents the internal temperature of the battery, Represents the ambient temperature of the battery. represents the battery surface temperature, and m and n are constants obtained in advance through fitting operations.

[0091] The battery temperature prediction method of the embodiment of the present application estimates the operating temperature of the battery cell based on the test energy efficiency. It does not require additional temperature sensors, simplifies product design, quickly responds to system configuration, and controls life cycle costs. The calculation process is simple and the amount of calculation is small. The battery cell temperature can be obtained by combining the energy efficiency data of the battery cell, and can be compared with historical test temperatures to analyze the battery cell temperature change trend.

[0092] In some implementations, obtaining the first correspondence may include steps 101 to 103:

[0093] Step 101: Perform a first calibration test on a first battery multiple times, and obtain the battery surface temperature, second discharge energy, and second charge energy of each first calibration test.

[0094] The first calibration test refers to a test process in which standard measuring instruments are used to test various parameters of the first battery to obtain test values ​​for comparison with standard values. The various parameters of the first battery include but are not limited to the battery surface temperature, the second discharge energy, and the second charge energy. The model of the first battery is the same as that of the target battery. The first battery can be the target battery, that is, the first calibration test is directly performed multiple times on the target battery. The second discharge energy is the cumulative charge energy generated by the real-time discharge voltage and real-time discharge current of the first calibration test during the discharge process time interval of the first calibration test; the second charge energy is the cumulative charge energy generated by the real-time charge voltage and real-time charge current of the first calibration test during the charging process time interval of the first calibration test. The second discharge energy can be obtained in the same way as the first discharge energy, and the second charge energy can be obtained in the same way as the first charge energy.

[0095] In some embodiments, obtaining the battery surface temperature for each first calibration test may include: for each first calibration test, during the process of the first calibration test, performing multiple detections on the ambient temperature of the battery to obtain multiple temperature detection values; and calculating an average of the multiple temperature detection values ​​to obtain the battery surface temperature for the first calibration test.

[0096] Step 102: For each first calibration test, obtain a second ratio of the second discharge energy to the second charge energy in the first calibration test, where the second ratio is the energy efficiency of the first calibration test.

[0097] Step 103: Based on the energy efficiency and battery surface temperature of the multiple first calibration tests, a first corresponding relationship is obtained by fitting. In this way, the corresponding relationship between the battery energy efficiency and the battery surface temperature can be obtained more accurately, which helps to improve the accuracy of predicting the battery temperature based on the battery energy efficiency.

[0098] In a specific example, the first battery is placed in an incubator and allowed to stand for 1-5 hours until the battery temperature is equal to the ambient temperature T1. The temperature range of T1 is generally: -20-60°C; the first battery is discharged with a C1 current (here it can be a specific current or a specific power) to obtain a fully discharged battery. The discharge current range is generally: 0-5C; after the discharge process is completed, the first battery is allowed to stand for 0.1-2 hours; the first battery is charged with a C1 current, and the charging energy CE1 is recorded. After the charging process is completed, the first battery is allowed to stand for 0.1-2 hours; the first battery is discharged with a C1 current, and the discharge energy DE1 is recorded. In the process of discharging the first battery with a C1 current to discharging the first battery with a C1 current, the battery is placed in a cooling system, thereby reducing the impact of temperature changes caused by heat generation of the battery cell on the test data. Calculate the energy efficiency η under the current test scenario T1 =DE1 / CE1*100%; then calculate the average temperature under the current test scenario: ; Where n represents the total number of temperature sampling times in the charge and discharge test, n includes but is not limited to 3, 4, 5, etc., and can be set according to actual application needs; Ti represents the temperature sampling value. At temperature T1, the highest temperature during the charge and discharge process is T 11 =max(Ti).

[0099] Raise the temperature in the incubator to T2, perform the operation of obtaining energy efficiency and temperature average value in the charge and discharge test, and obtain the energy efficiency η at T2 temperature. T2 and the average temperature ; Raise the temperature in the incubator to T3, perform the operation of obtaining energy efficiency and temperature average value in the charge and discharge test, and obtain the energy efficiency η at T3 temperature T3 and the average temperature , 3-5 temperature values ​​can be tested in each charge and discharge test, and then the corresponding temperature average value is calculated; according to the needs of actual application, the energy efficiency and temperature average value at multiple different temperatures are tested; then, the energy efficiency and temperature average value obtained at the above multiple different temperatures are used to fit and obtain the first corresponding relationship. The specific fitting process includes depicting multiple points corresponding to different temperatures on a plane coordinate system with energy efficiency and temperature average value as coordinate values, with the horizontal and vertical coordinates of each point being the energy efficiency and temperature average value, and then connecting the multiple points on the plane with a smooth curve to obtain the first corresponding relationship. The fitting method includes but is not limited to algorithms such as the least squares curve fitting method.

[0100] The functional expression of the first correspondence can be, for example,

[0101] ;

[0102] in, T e Represents the surface temperature of the target battery; Represents energy efficiency; the values ​​of a, b, and c are obtained by fitting. For example, in a specific example, a=9545.9, b=-16927, and c=7522.9, and the corresponding formula is . refer to Figure 4 As shown, Figure 4 A graph showing the relationship between battery energy efficiency and battery surface temperature constructed based on test data of a calibration test in a specific example is shown. Figure 5 As shown, Figure 5 The data graph shows the measured surface temperature and predicted temperature of the battery cell under actual operating conditions. The overall fluctuation trend of the predicted temperature is consistent with that of the measured temperature. The average error of 20 predictions is 0.15°C, and the maximum prediction error does not exceed 0.4°C. The battery temperature prediction method of this embodiment achieves a high prediction accuracy.

[0103] In some embodiments, the method may further include: during multiple first calibration tests on the battery, obtaining the battery internal temperature and the battery ambient temperature during each first calibration test; and fitting a second corresponding relationship based on the battery surface temperature, the battery internal temperature, and the battery ambient temperature during the multiple first calibration tests; the second corresponding relationship being a corresponding relationship between the battery internal temperature, the battery surface temperature, and the battery ambient temperature. The second corresponding relationship obtained in this manner is relatively accurate.

[0104] The function expression representing the second correspondence can be

[0105]

[0106] Where f(T0) and g(T e ) can be a function related to battery design parameters (such as battery cell material and shape).

[0107] Specifically, the function expression representing the second corresponding relationship is a binary linear function with the battery surface temperature and the battery environment temperature as independent variables and the battery internal temperature as the dependent variable. For example,

[0108]

[0109] in, Represents the internal temperature of the battery, Represents the ambient temperature of the battery. Represents the battery surface temperature. Based on the battery surface temperature, battery internal temperature and battery ambient temperature of multiple first calibration tests, m and n are fitted and are both constants.

[0110] In some implementations, obtaining the second correspondence includes:

[0111] Performing multiple second calibration tests on the battery and obtaining the battery surface temperature, battery internal temperature, and battery ambient temperature during each second calibration test; each second calibration test includes one charging process and one discharging process;

[0112] Based on the battery surface temperature, battery internal temperature and battery environment temperature obtained from multiple second calibration tests, a second corresponding relationship is obtained by fitting. The second corresponding relationship obtained in this way is relatively accurate.

[0113] In some embodiments, obtaining the internal temperature of the battery for each second calibration test includes:

[0114] For each second calibration test, during the second calibration test, the temperature of the preset built-in temperature sensing wire of the battery is detected to obtain the internal temperature of the battery for the second calibration test. This helps to improve the accuracy of the obtained second correspondence.

[0115] The above description of the various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced with each other and will not be repeated herein for the sake of brevity.

[0116] For example, in an exemplary battery temperature prediction method, the target battery is a lithium iron phosphate battery. First, a calibration test is performed on the lithium iron phosphate battery. The steps include:

[0117] 1.1. Adjust the battery temperature to 20℃;

[0118] 1.2. Let it stand for 120 minutes;

[0119] 1.3, 1C constant current discharge to 2.5V;

[0120] 1.4. Let it stand for 30 minutes;

[0121] 1.5, 1C constant current charge to 3.65V;

[0122] 1.6. Let it stand for 30 minutes;

[0123] 1.7, 1C constant current discharge to 2.5V;

[0124] 1.8. Let it stand for 30 minutes;

[0125] 1.9. Loop through steps 1.5 to 1.8 three times and calculate the energy efficiency using the data from the last cycle. η 1;

[0126] 1.10. Adjust the battery temperature to 25℃;

[0127] 1.11. Let stand for 120 minutes;

[0128] 1.12. Loop through steps 1.5 to 1.8 three times and calculate the energy efficiency using the data from the last cycle. η 2;

[0129] 1.13. Adjust the battery temperature to 35℃;

[0130] 1.14, let it stand for 120 minutes;

[0131] 1.15. Loop through steps 1.5 to 1.8 three times, and calculate the energy efficiency using the data from the last cycle. η 3;

[0132] 1.16. Adjust the battery temperature to 45°C;

[0133] 1.17, let it stand for 120 minutes;

[0134] 1.18. Loop through steps 1.5 to 1.8 three times, and calculate the energy efficiency using the data from the last cycle. η 4.

[0135] 1.19. According to η 1. η 2. η 3. η 4 and the corresponding target battery surface temperature, the fitting formula is obtained .

[0136] Then, the temperature of the lithium iron phosphate battery is predicted, including:

[0137] 2.1. Charge to 3.65V with 1C constant current;

[0138] 2.2, let it stand for 120 minutes;

[0139] 2.3. Use 1C constant current to discharge to 2.5V;

[0140] 2.4. Let it stand for 120 minutes.

[0141] 2.5. Repeat steps 2.1 to 2.4 2500 times.

[0142] By adjusting the ambient temperature to simulate different cell surface temperatures, the energy efficiency data of the lithium iron phosphate battery is obtained every 30 days. According to the formula , calculate the target battery surface temperature corresponding to each energy efficiency, and substitute the target battery surface temperature and the target battery ambient temperature into , the battery internal temperature Ti of the target battery is calculated.

[0143] In a specific example of a battery temperature prediction method, a charge and discharge test is first performed on a target battery to obtain test data for the target battery. The test data includes the voltage and current of the target battery during the charge and discharge test. The charge and discharge test may include one discharge process and one charge process. A charge and discharge device is used to perform one discharge operation and one charge operation on the target battery, and the corresponding real-time current and real-time voltage of the target battery during the charge and discharge test are recorded. The voltage and current of the test data may include the discharge voltage, discharge current, charge voltage, and charge current of the target battery during the charge and discharge test.

[0144] Then, based on the voltage and current of the test data, a first discharge energy and a first charge energy of the charge-discharge test are obtained, wherein the first discharge energy is the integral value of the product of the real-time discharge voltage and the real-time discharge current over the time interval of the charging process, and the first charge energy is the integral value of the product of the real-time charge voltage and the real-time charge current over the time interval of the discharge process. A first ratio of the first discharge energy to the first charge energy is obtained, and the first ratio is the current energy efficiency of the target battery.

[0145] The preset correspondence relationship includes at least a first correspondence relationship between the energy efficiency of the target battery and the target battery surface temperature. Substitute the current energy efficiency into the function expression representing the first correspondence relationship to calculate the current target battery surface temperature. The function expression is the target battery surface temperature. , Represents the current energy efficiency. Finally, according to the current target battery surface temperature, the current target battery ambient temperature and the second corresponding relationship, the current internal temperature of the target battery is obtained. Among them, the function expression representing the second corresponding relationship is a binary linear function with the battery surface temperature and the battery ambient temperature as independent variables and the battery internal temperature as the dependent variable, which is:

[0146]

[0147] in, Represents the internal temperature of the battery, Represents the ambient temperature of the battery. represents the battery surface temperature, and m and n are constants obtained in advance through fitting operations.

[0148] Battery cell temperature fluctuations can also affect battery testing performance and the test results of electrical performance parameters. Furthermore, the pattern of battery cell temperature fluctuations can also reflect the aging pattern of the battery cells. Therefore, establishing an accurate online battery temperature estimation model is crucial for battery thermal state estimation and thermal management system development. Related technologies require a temperature sensor built into the battery module to obtain battery cell temperature, which increases product production and maintenance costs.

[0149] The battery temperature prediction method in this embodiment differs from related art solutions that estimate cell temperature using impedance test data and a pre-constructed function between low-frequency impedance and temperature. It does not require EIS testing of the battery, and has lower requirements for testing equipment, significantly expanding the application scenarios of battery temperature prediction technology. By predicting battery temperature based on test energy efficiency, the prediction results are highly accurate and eliminate the need for additional temperature sensors, simplifying product design, enabling rapid response to system configuration, and reducing battery production and maintenance costs.

[0150] The above description of the various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced with each other and will not be repeated herein for the sake of brevity.

[0151] refer to Figure 6 As shown, another embodiment of the present application provides a battery temperature prediction device, which may include:

[0152] A charge and discharge test module is used to perform charge and discharge tests on a target battery and obtain test data of the target battery, the test data including the voltage and current of the target battery during the charge and discharge tests;

[0153] An energy efficiency determination module is used to obtain the ratio of discharge energy to charge energy in the charge and discharge test based on the voltage and current of the test data to obtain the current energy efficiency of the target battery;

[0154] The battery temperature acquisition module is used to acquire the current temperature of the target battery according to the current energy efficiency and a preset corresponding relationship; the preset corresponding relationship includes at least a first corresponding relationship between the energy efficiency of the target battery and the surface temperature of the target battery.

[0155] In some embodiments, the voltage and current of the test data include the real-time discharge voltage, real-time discharge current, real-time charge voltage, and real-time charge current of the target battery during the charge and discharge test;

[0156] Energy efficiency determination module, including:

[0157] a charge-discharge energy acquisition unit, configured to acquire a first discharge energy and a first charge energy of the charge-discharge test based on the voltage and current of the test data; the first discharge energy may be the accumulated discharge energy generated by the real-time discharge voltage and the real-time discharge current during a time interval of the charge process of the charge-discharge test; the first charge energy may be the accumulated charge energy generated by the real-time charge voltage and the real-time charge current during a time interval of the discharge process of the charge-discharge test; for example, the first discharge energy may be the integral value of the product of the real-time discharge voltage and the real-time discharge current during a time interval of the charge process; the first charge energy may be the integral value of the product of the real-time charge voltage and the real-time charge current during a time interval of the discharge process;

[0158] The energy efficiency acquisition unit is configured to acquire a first ratio of the first discharge energy to the first charge energy, where the first ratio is the current energy efficiency of the target battery.

[0159] In some embodiments, the battery temperature acquisition module is further configured to substitute the current energy efficiency into a function expression representing the first corresponding relationship to calculate and obtain the current target battery surface temperature.

[0160] In some embodiments, the preset correspondence further includes a second correspondence between the target battery internal temperature, the target battery surface temperature, and the target battery ambient temperature; and the battery temperature acquisition module includes:

[0161] a battery surface temperature obtaining unit, configured to obtain a current target battery surface temperature based on the first corresponding relationship;

[0162] The battery internal temperature acquisition unit is used to acquire the current battery internal temperature of the target battery according to the current target battery surface temperature, the current target battery environment temperature and the second corresponding relationship.

[0163] Illustratively, the battery internal temperature acquiring unit is further configured to substitute the current target battery surface temperature and the current target battery ambient temperature into a function expression representing the second corresponding relationship to calculate the current battery internal temperature of the target battery.

[0164] In some embodiments, the battery temperature prediction device further includes a first correspondence relationship acquisition module, and the first correspondence relationship acquisition module includes:

[0165] a testing unit, configured to perform multiple first calibration tests on a first battery and obtain a battery surface temperature, a second discharge energy, and a second charge energy for each first calibration test; the model of the first battery is the same as the model of the target battery; the second discharge energy is the cumulative charge energy generated by the real-time discharge voltage and the real-time discharge current of the first calibration test during the discharge process time interval of the first calibration test; and the second charge energy is the cumulative charge energy generated by the real-time charge voltage and the real-time charge current of the first calibration test during the charging process time interval of the first calibration test;

[0166] an energy efficiency acquisition unit, configured to acquire, for each first calibration test, a second ratio of the second discharge energy to the second charge energy in the first calibration test, wherein the second ratio is the energy efficiency of the first calibration test;

[0167] The fitting unit is used to obtain a first corresponding relationship by fitting based on the energy efficiency and the battery surface temperature of multiple first calibration tests.

[0168] In some embodiments, the test unit is further specifically configured to:

[0169] For each first calibration test, during the first calibration test, the ambient temperature of the battery is detected multiple times to obtain multiple temperature detection values;

[0170] Calculate the average value of the multiple temperature detection values ​​to obtain the battery surface temperature of the first calibration test.

[0171] In some embodiments, the battery temperature prediction device further includes a second corresponding relationship acquisition module, which is configured to:

[0172] During the process of performing multiple first calibration tests on the battery, the internal temperature of the battery and the ambient temperature of the battery are also obtained during each first calibration test;

[0173] Based on the battery surface temperature, battery internal temperature and battery ambient temperature of multiple first calibration tests, a second corresponding relationship is obtained by fitting; the second corresponding relationship is the corresponding relationship between the battery internal temperature, battery surface temperature and battery ambient temperature.

[0174] The battery temperature prediction device of the embodiment of the present application can perform charge and discharge tests on a target battery, obtain test data of the target battery, obtain the ratio of discharge energy to charging energy of the charge and discharge test based on the voltage and current of the test data, obtain the current energy efficiency of the target battery, and obtain the current temperature of the target battery based on the current energy efficiency and a preset correspondence. This is different from the technical solution in the related art that estimates the battery cell temperature through impedance test data and a pre-constructed function between low-frequency impedance and temperature. It does not require EIS testing of the battery, has low requirements for test equipment, and greatly expands the applicable scenarios of battery temperature prediction technology.

[0175] The above description of the various embodiments tends to emphasize the differences between the various embodiments. The same or similar aspects can be referenced with each other and will not be repeated herein for the sake of brevity.

[0176] Another embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method of any of the above embodiments.

[0177] refer to Figure 7 As shown, the electronic device 10 may include: a processor 100, a memory 101, a bus 102 and a communication interface 103, and the processor 100, the communication interface 103 and the memory 101 are connected through the bus 102; the memory 101 stores a computer program that can be run on the processor 100, and when the processor 100 runs the computer program, it executes the method provided in any of the aforementioned embodiments of the present application.

[0178] Memory 101 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Communication between the device network element and at least one other network element is achieved through at least one communication interface 103 (which may be wired or wireless), and may utilize the Internet, a wide area network, a local area network, a metropolitan area network, or the like.

[0179] Bus 102 may be an ISA bus, a PCI bus, or an EISA bus. Buses may be classified as address buses, data buses, and control buses. Memory 101 is used to store programs, and processor 100 executes the programs upon receiving execution instructions. The methods disclosed in any of the aforementioned embodiments of the present application may be applied to or implemented by processor 100.

[0180] The processor 100 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits in the processor 100 or by software instructions. The above processor 100 may be a general-purpose processor, which may include a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The various methods, steps, and logic block diagrams disclosed in the embodiments of this application can be implemented or executed. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of this application can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium mature in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory 101 , and the processor 100 reads the information in the memory 101 and completes the steps of the above method in combination with its hardware.

[0181] The electronic device provided in the embodiments of the present application and the method provided in the embodiments of the present application are based on the same inventive concept and have the same beneficial effects as the methods adopted, operated or implemented by them.

[0182] Another embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement the method of any of the above embodiments. Figure 8 As shown, the computer-readable storage medium is a CD 20 on which a computer program (ie, a program product) is stored. When the computer program is run by a processor, the method provided by any of the aforementioned embodiments is executed.

[0183] It should be noted that examples of computer-readable storage media may also include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical or magnetic storage media, which are not listed here one by one.

[0184] The computer-readable storage medium provided in the above-mentioned embodiments of the present application and the method provided in the embodiments of the present application are based on the same inventive concept and have the same beneficial effects as the method adopted, run or implemented by the application program stored therein.

[0185] It should be noted that:

[0186] The term "module" is not intended to be limited to a specific physical form. Depending on the specific application, a module can be implemented as hardware, firmware, software, and / or a combination thereof. In addition, different modules can share common components or even be implemented by the same components. There may or may not be clear boundaries between different modules.

[0187] The algorithm and display provided herein are not inherently related to any particular computer, virtual device or other equipment. Various general-purpose devices can also be used together with examples based on this. According to the above description, it is obvious that the structure required for constructing this type of device. In addition, the application is not directed to any specific programming language yet. It should be understood that various programming languages ​​can be utilized to realize the content of the application described herein, and the above description of specific languages ​​is for the purpose of disclosing the best mode of implementation of the application.

[0188] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the flowcharts of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0189] The above embodiments merely represent implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A battery temperature prediction method, characterized in that: include: Performing a charge and discharge test on a target battery to obtain test data of the target battery, wherein the test data includes a voltage and a current of the target battery during the charge and discharge test; Based on the voltage and current of the test data, obtaining a ratio of discharge energy to charge energy of the charge-discharge test to obtain a current energy efficiency of the target battery; Acquiring a current temperature of the target battery according to the current energy efficiency and a preset corresponding relationship; The preset correspondence relationship includes at least a first correspondence relationship between the energy efficiency of the target battery and the target battery surface temperature; The functional expression of the first corresponding relationship is a univariate multivariate functional expression with the target battery surface temperature as a dependent variable and the target battery energy efficiency as an independent variable.

2. The method according to claim 1, characterized in that The voltage and current of the test data include the real-time discharge voltage, real-time discharge current, real-time charge voltage and real-time charge current of the target battery during the charge and discharge test; The step of obtaining a ratio of discharge energy to charge energy of the charge-discharge test based on the voltage and current of the test data to obtain a current energy efficiency of the target battery includes: Based on the voltage and current of the test data, a first discharge energy and a first charge energy of the charge-discharge test are obtained; the first discharge energy is the cumulative discharge energy generated by the real-time discharge voltage and the real-time discharge current during a time interval of the charging process of the charge-discharge test; and the first charge energy is the cumulative charge energy generated by the real-time charge voltage and the real-time charge current during a time interval of the discharging process of the charge-discharge test; A first ratio of the first discharge energy to the first charge energy is obtained, where the first ratio is a current energy efficiency of the target battery.

3. The method according to claim 1 or 2, characterized in that The acquiring the current temperature of the target battery according to the current energy efficiency and the preset corresponding relationship includes: The current energy efficiency is substituted into the function expression representing the first corresponding relationship to calculate and obtain the current target battery surface temperature.

4. The method according to claim 1, wherein The preset correspondence relationship further includes a second correspondence relationship between the target battery internal temperature, the target battery surface temperature and the target battery ambient temperature; The acquiring the current temperature of the target battery according to the current energy efficiency and the preset corresponding relationship includes: Obtaining a current target battery surface temperature based on the first corresponding relationship; The current internal battery temperature of the target battery is acquired according to the current target battery surface temperature, the current ambient temperature of the target battery, and the second corresponding relationship.

5. The method according to claim 4, characterized in that The acquiring, according to the current target battery surface temperature, the current target battery ambient temperature, and the second corresponding relationship, the current battery internal temperature of the target battery includes: The current target battery surface temperature and the current target battery ambient temperature are substituted into a function expression representing the second corresponding relationship to calculate the current battery internal temperature of the target battery.

6. The method according to claim 1 or 2, characterized in that The acquiring of the first corresponding relationship includes: Performing multiple first calibration tests on a first battery and obtaining a battery surface temperature, a second discharge energy, and a second charge energy for each first calibration test; the model of the first battery is the same as the model of the target battery; the second discharge energy is the cumulative charge energy generated by the real-time discharge voltage and real-time discharge current of the first calibration test during a discharge time interval of the first calibration test; and the second charge energy is the cumulative charge energy generated by the real-time charge voltage and real-time charge current of the first calibration test during a charge time interval of the first calibration test; For each of the first calibration tests, obtaining a second ratio of the second discharge energy to the second charge energy in the first calibration test, where the second ratio is the energy efficiency of the first calibration test; The first corresponding relationship is obtained by fitting based on the energy efficiency and battery surface temperature of the multiple first calibration tests.

7. The method according to claim 6, characterized in that Obtain the battery surface temperature for each first calibration test, including: For each of the first calibration tests, during the first calibration test, the ambient temperature of the battery is detected multiple times to obtain multiple temperature detection values; An average value of the plurality of temperature detection values ​​is calculated to obtain the battery surface temperature of the first calibration test.

8. The method according to claim 6, characterized in that The method further comprises: During the process of performing multiple first calibration tests on the first battery, the internal temperature of the battery and the ambient temperature of the battery are obtained during each first calibration test; Based on the battery surface temperature, the battery internal temperature and the ambient temperature of the battery during the multiple first calibration tests, a second corresponding relationship is obtained by fitting; the second corresponding relationship is the corresponding relationship between the battery internal temperature, the battery surface temperature and the ambient temperature of the battery.

9. A battery temperature prediction device, characterized in that: include: a charge and discharge test module, configured to perform a charge and discharge test on a target battery and obtain test data of the target battery, wherein the test data includes a voltage and a current of the target battery during the charge and discharge test; an energy efficiency determination module, configured to obtain a ratio of discharge energy to charge energy of the charge-discharge test based on the voltage and current of the test data, and obtain a current energy efficiency of the target battery; a battery temperature acquisition module, configured to acquire the current temperature of the target battery according to the current energy efficiency and a preset corresponding relationship; The preset correspondence relationship includes at least a first correspondence relationship between the energy efficiency of the target battery and the target battery surface temperature; The functional expression of the first corresponding relationship is a univariate multivariate functional expression with the target battery surface temperature as a dependent variable and the target battery energy efficiency as an independent variable.

10. An electronic device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the battery temperature prediction method according to any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: The computer program is executed by a processor to implement the battery temperature prediction method according to any one of claims 1 to 8.

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