Method and device for determining heat production power of lithium battery and readable storage medium

Abstract

The invention discloses a lithium battery heat production power determination method and device and a readable storage medium, and the method comprises the steps: obtaining the charge state of a target lithium battery at the current moment, matching the charge state of the target lithium battery with target corresponding relation information, and obtaining the real heat production power of the target lithium battery at the current moment; the target corresponding relation information is obtained according to the surface heat production power and the heat dissipation power of the target lithium battery in the stage of simultaneous heat production and heat dissipation of the target lithium battery, and the heat production power in the target corresponding relation information is obtained by distinguishing heat production of the battery and environment heat dissipation; therefore, the real heat production power of the target lithium battery can be accurately reflected by obtaining the heat production power based on target corresponding relation information matching, and the method has the advantages of distinguishing the real heat production characteristics and improving the heat production power determination accuracy.

Description

Technical Field

[0001] This disclosure generally relates to the field of new energy technology, and specifically to a method, apparatus and readable storage medium for determining the heat generation power of a lithium battery. Background Technology

[0002] With the widespread application of lithium batteries in electric vehicles, energy storage systems, and other fields, thermal safety has become a core factor restricting battery performance and lifespan. Accurately obtaining the true heat generation power of lithium batteries under specific charge and discharge conditions is a crucial fundamental parameter for thermal management design, thermal runaway early warning, and battery system optimization. Currently, the industry relies on calorimetry techniques under non-adiabatic conditions to measure the heat generation power of lithium batteries; however, this method has significant errors. Summary of the Invention

[0003] In view of the above-mentioned defects or deficiencies in the prior art, it is desirable to provide a method, device and storage medium for determining the heat generation power of a lithium battery, which has the advantages of improving the accuracy of heat generation power measurement, establishing a precise correspondence between heat generation power and state of charge, and distinguishing the actual heat generation characteristics under dynamic operating conditions.

[0004] In a first aspect, a method for determining the heat generation power of a lithium battery is provided, the method comprising: Obtain the current state of charge of the target lithium battery; The target lithium battery's state of charge is matched with the target correspondence information to obtain the target lithium battery's actual heat generation power at the current moment. The target correspondence information includes multiple heat generation powers and the state of charge corresponding to each heat generation power. The target correspondence information is obtained based on the target lithium battery's surface heat generation power and heat dissipation power in the first stage.

[0005] This application provides a method for determining the heat generation power of a lithium battery. Considering that current industry measurements of lithium battery heat generation power rely on calorimetry under non-adiabatic conditions, which suffers from significant errors, this application offers a method for determining the heat generation power of a lithium battery. This method obtains the current state of charge (SOC) of the target lithium battery and matches it with target correspondence information to obtain the true heat generation power of the target lithium battery at that moment. Since the target correspondence information is obtained based on the surface heat generation and heat dissipation power of the target lithium battery during the simultaneous heat generation and dissipation phase, and the heat generation power in the target correspondence information distinguishes between the battery's own heat generation and environmental heat dissipation, the heat generation power obtained based on the target correspondence information can accurately reflect the true heat generation power of the target lithium battery. This method has the advantages of distinguishing true heat generation characteristics and improving the accuracy of heat generation power determination.

[0006] Secondly, a device for determining the heat generation power of a lithium battery is provided, the device comprising: The acquisition module is used to acquire the current state of charge of the target lithium battery. The matching module is used to match the state of charge of the target lithium battery with the target correspondence information to obtain the actual heat generation power of the target lithium battery at the current moment. The target correspondence information includes multiple heat generation powers and the state of charge corresponding to each heat generation power. The target correspondence information is obtained based on the surface heat generation power and heat dissipation power of the target lithium battery in the first stage.

[0007] Thirdly, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the method of the first aspect. Attached Figure Description

[0008] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 An application scenario diagram for the method for determining the heat generation power of a lithium battery provided in this application; Figure 2 A flowchart illustrating a method for determining the heat generation power of a lithium battery provided in this application; Figure 3 A flowchart illustrating the steps of a method for determining the heat generation power of a lithium battery provided in this application; Figure 4 A flowchart illustrating the steps of a method for determining the heat generation power of a lithium battery provided in this application; Figure 5 A flowchart illustrating the steps of a method for determining the heat generation power of a lithium battery provided in this application; Figure 6 A structural block diagram of a device for determining the heat generation power of a lithium battery provided in this application. Detailed Implementation

[0009] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings.

[0010] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0011] In existing technologies, the measurement of heat generation power of lithium batteries typically employs calorimetry techniques under non-adiabatic conditions. Because lithium batteries undergo dynamic heat dissipation in practical applications, these methods struggle to accurately distinguish the combined effect of surface heat generation and heat dissipation, leading to discrepancies between the measured results and the actual heat generation power. This is particularly problematic in electric vehicle fast-charging or high-rate-discharging scenarios, where internal battery heat generation and external heat dissipation occur simultaneously. Current technologies cannot effectively separate these two processes, resulting in a lack of accurate data support for the design of thermal management systems.

[0012] To address the aforementioned issues, the core contradiction in existing technologies lies in their inability to simultaneously quantify the heat generation and dissipation processes. Analysis reveals that during the charging and discharging process of lithium batteries, surface temperature changes are influenced by both internal heat generation and external heat dissipation. If heat generation power is inferred solely from temperature data, interference errors in heat dissipation power will inevitably be introduced. Therefore, a new method is needed to accurately determine the true heat generation power of lithium batteries.

[0013] Therefore, this application proposes a technical solution to directly obtain the actual heat generation power by acquiring the current state of charge of the target lithium battery and matching it with pre-established target correspondence information. This target correspondence information is constructed based on a comprehensive analysis of the surface heat generation power and heat dissipation power of the target lithium battery during the coexistence of heat generation and dissipation, and can reflect the variation law of the actual heat generation power under different states of charge.

[0014] Please refer to Figure 1 , Figure 1 This diagram illustrates an application scenario for a method to determine the heat generation power of a lithium battery, as provided in this application. The scenario includes a terminal device 100 and a service device 200. The terminal device 100 acquires the state of charge (SOC) of the lithium battery. The terminal device 100 is communicatively connected to the service device 200. The service device 200 acquires the SOC of the source lithium battery from the terminal device 100 and matches it with stored target correspondence information to obtain the actual heat generation power of the target lithium battery at the current moment. The terminal device 100 may be, for example, a combination of a voltage acquisition device and a processing chip, or a combination of a current acquisition circuit and a microcontroller. The service device 200 may be, for example, a single server or a server cluster.

[0015] Below, in conjunction with Figure 2 The method for determining the heat generation power of this lithium battery is applied to Figure 1 Taking the service equipment 200 as an example, the method for determining the heat generation power of the lithium battery provided in this application is described. The method includes the following steps: Step S20: Obtain the current state of charge of the target lithium battery; The state of charge (SOC) refers to the ratio of the current remaining capacity of the target lithium battery to its rated capacity. This can be calculated in real-time using voltage measurement or ampere-hour integration methods, and is used to characterize the battery's real-time energy state. For example, the open-circuit voltage across the target lithium battery can be measured using a voltage meter, and the current SOC can be obtained by comparing it to the OCV-SOC curve.

[0016] Step S30: Match the state of charge of the target lithium battery with the target correspondence information to obtain the actual heat generation power of the target lithium battery at the current moment. The target correspondence information includes multiple actual heat generation powers and the state of charge corresponding to each actual heat generation power. The actual heat generation power is the heat generation power after heat dissipation power compensation of the heat generation power on the surface of the lithium battery.

[0017] The target correspondence information refers to a mapping table between actual heat generation power and state of charge (SOC) established through experimental data. It includes multiple actual heat generation powers and their corresponding SOCs. Actual heat generation power is used to distinguish between measured values ​​and actual values ​​on the lithium battery surface. Specifically, it refers to the heat generated by the electrochemical reactions and ohmic impedance within the target lithium battery, which needs to be eliminated by removing the heat dissipation power component from the surface heat generation power; that is, the heat generation power after heat dissipation compensation. This target correspondence information can be obtained through testing of any battery of the same model as the target lithium battery.

[0018] Target correspondence information can be obtained, for example, by obtaining the surface heat generation power and heat dissipation power of a lithium battery during the coexistence of heat generation and heat dissipation, and then constructing the heat generation and heat dissipation components by separating them through a thermodynamic model; it can also be obtained by experimentally measuring the heat generation characteristics of the battery under different SOCs, etc.

[0019] For example, the target correspondence information is as follows:

[0020] If the current state of charge of the target lithium battery is A4, then by matching it with the target correspondence information, the actual heat generation power of the target lithium battery at the current moment is obtained as B4.

[0021] Compared to existing technologies, traditional methods only infer the actual heat generation power from surface temperature, ignoring the dynamic impact of heat dissipation power. This scheme achieves effective separation of heat generation and heat dissipation components by constructing target-correspondence information. Simultaneously, by converting the time dimension to a state of charge dimension, the online matching process can directly correlate with the battery's energy state parameters, avoiding the impact of accumulated time errors on measurement accuracy.

[0022] Through the above technical solution, this application can accurately obtain the real heat generation power of lithium battery under dynamic operating conditions, effectively solve the problem of difficulty in distinguishing between heat generation and heat dissipation components in traditional calorimetry, and significantly improve the accuracy of real heat generation power measurement.

[0023] In one alternative method embodiment, such as Figure 2 As shown, Figure 2 An optional method embodiment for obtaining target correspondence information provided in this application includes the following steps: Step S201: Under the target operating conditions, collect the first temperature data of the sample lithium battery in the first stage and the first temperature data of the sample lithium battery in the second stage. The second stage is the stage where the sample lithium battery is purely dissipating heat. The target operating condition refers to the pre-set charge and discharge test conditions used to ensure that the sample lithium battery completes the heat generation and dissipation process under controllable conditions, including charging or discharging conditions. The sample lithium battery is any lithium battery of the same model as the target lithium battery, used to construct the initial target correspondence information.

[0024] The first stage refers to the process in which the sample lithium battery simultaneously generates heat through internal chemical reactions and dissipates heat from its surface; that is, the stage where heat generation and dissipation coexist. This can be achieved by applying charging and discharging current to the battery while simultaneously monitoring temperature changes. The second stage refers to the process in which the battery cools down only through natural heat dissipation after charging and discharging have stopped; that is, the pure heat dissipation stage of the sample lithium battery. This can be achieved by disconnecting the charging and discharging circuit and continuously recording temperature data.

[0025] The first temperature data is obtained in the first stage by collecting temperature data through temperature sensing points arranged at the center of the sample lithium battery according to a preset collection rule, such as collecting temperature data once every 0.5 seconds.

[0026] The second temperature data is obtained in the second stage by collecting temperature data through, for example, temperature sensing points placed at the center of the sample lithium battery according to a preset collection rule, wherein the preset collection rule is, for example, to collect temperature data once every 5 seconds.

[0027] Optionally, if the target operating condition is a discharge condition, the first stage is the stage of discharging the sample lithium battery from the upper limit voltage to the lower limit voltage, and the second stage is the stage of letting the sample lithium battery, discharged to the lower limit voltage, rest for a preset time. If the target operating condition is a charging condition, the first stage is the stage of charging the sample lithium battery to the upper limit voltage using a standard constant current and constant voltage charging mode, and the second stage is the stage of letting the sample lithium battery, charged to the upper limit voltage, rest for a preset time. The preset time may be, for example, 2 hours, 3 hours, etc.

[0028] Step S202: Construct a first model based on the first temperature data and the first time data, and construct a second model based on the second temperature data and the second time data, wherein the first time data is the time data for collecting the first temperature data, and the second time data is the time data for collecting the second temperature data; The first model refers to a function that describes the temperature change of the sample lithium battery under the combined effects of heat generation and heat dissipation. For example, it can be implemented by fitting the temperature change curve over time using a polynomial, and is used to derive the surface heat generation power of the sample lithium battery.

[0029] The second model refers to a function that describes the temperature change pattern of the battery during the pure heat dissipation phase. For example, it can be implemented by fitting the temperature data through an exponential function or linear regression, and is used to calculate the heat dissipation power.

[0030] For example, during the charging and discharging operation of the sample lithium battery under target operating conditions, the first temperature data and corresponding timestamps (i.e., first time data) of the sample lithium battery surface temperature change over time are simultaneously recorded in the first stage. When the sample lithium battery enters the second stage of heat dissipation only, the second temperature data and corresponding timestamps (i.e., second time data) are collected and recorded. The first stage data is input into a polynomial fitting function to generate a first model. At the same time, the second model constructed using the second stage data can quantify the relationship between heat dissipation power and temperature.

[0031] Step S203: Based on the first time data, the first model, and the second model, obtain the surface heat generation power array and the heat dissipation power array; The surface heat generation power array refers to the set of heat generation power derived from the first model without deducting the heat dissipation effect. It includes surface heat generation power data corresponding to multiple time points, which can be calculated, for example, by differentiating the rate of temperature change and combining it with heat capacity parameters. This is used to subsequently correct the actual heat generation power. The heat dissipation power array refers to the set of heat dissipation capacity data of the sample lithium battery at different temperatures derived from the second model. It includes heat dissipation power data corresponding to multiple time points, which can be calculated, for example, by the correlation between the rate of temperature change and the heat dissipation coefficient. This is used to offset the heat dissipation loss in the surface heat generation power.

[0032] Step S204: The surface heat generation power in the surface heat generation power array and the heat dissipation power in the heat dissipation power array are summed according to time to obtain the actual heat generation power, and the actual heat generation power is matched with time to obtain the initial correspondence information. Since the surface heat generation power is affected by the heat dissipation power, it cannot be used as the true heat generation power output of the sample lithium battery. After obtaining the surface heat generation power array and the heat dissipation power array based on the above process, the surface heat generation power can be compensated by the heat dissipation power to obtain the true heat generation power of the sample lithium battery at each time point. The method of compensating for the surface heat generation power by heat dissipation power can be achieved by summing the surface heat generation power in the surface heat generation power array and the heat dissipation power in the heat dissipation power array according to time.

[0033] Step S205: Convert the time in the initial correspondence information into the state of charge of the sample lithium battery to obtain the target correspondence information.

[0034] To avoid the impact of accumulated time errors on measurement accuracy, this application converts the time dimension into a state of charge dimension, establishing a direct mapping relationship between heat generation power and state of charge. For example, this application can convert the time variable into the state of charge using the ampere-hour integration method.

[0035] Compared to existing technologies, current non-adiabatic thermal analysis techniques estimate heat generation power based solely on single temperature data, failing to distinguish the dynamic differences between heat generation and dissipation stages, leading to systematic biases in the calculation results. This proposed solution, however, effectively separates heat generation and dissipation effects by collecting data in stages and establishing a dual-model interactive verification mechanism, significantly improving the accuracy of the actual heat generation power calculation.

[0036] Through the above technical solution, this application solves the problem of measurement error in heat generation power caused by the failure to consider the dynamic process of heat dissipation in traditional methods.

[0037] In yet another alternative method embodiment, such as Figure 3 As shown, Figure 3 An optional method embodiment for obtaining a surface heat generation power array and a heat dissipation power array provided in this application includes the following steps: Step S301: Divide the first time data into equal parts to obtain a time array; The time array refers to a discrete time series formed by dividing continuously collected time data into fixed intervals. Specifically, it can be implemented using an equal-interval segmentation algorithm, such as dividing the total duration by a preset step size to generate uniformly distributed time points.

[0038] For example, if the first-time data is according to Average score share( The smaller the model, the more accurate it is, and ≤1s)

[0039] And create a time array .

[0040] Step S302: Input the time array into the first objective function to obtain the temperature array. The first objective function is obtained by performing odd-degree polynomial fitting based on the first temperature data and the first time data. The first objective function is a mathematical expression for the temperature change over time established through polynomial fitting. For example, a cubic polynomial curve can be used to approximate the experimental data and describe the temperature change trend.

[0041] For example, the first objective function is: ,in, Let t be the polynomial parameter and t be the time array. Substituting the obtained time array into the above formula will yield multiple temperature data points. The collection of multiple temperature data points forms a temperature array.

[0042] It should be noted that at the initial moment, many parameters in the first objective function are unknowns, which are referred to here as the first initial function. The t parameter in the first initial function needs to be replaced with the first time data, and T needs to be replaced with the first temperature data for polynomial fitting to obtain the first objective function.

[0043] Step S303: Input the time array into the first model to obtain the surface heat generation power array; The apparent heat generation power array refers to the battery surface heat generation power dataset without considering the effect of heat dissipation. It is generated by calculating the time array through the first model. For example, the first model can be constructed based on the physical relationship between the rate of temperature change and power.

[0044] Step S304: Input the temperature array into the second model to obtain the heat dissipation power array.

[0045] The heat dissipation power array refers to the power dataset of heat exchange between the battery and the environment. It is generated by calculating the temperature array through the second model. For example, the second model can be established based on the relationship between the temperature change rate and the heat dissipation coefficient.

[0046] For example, in the data preprocessing stage, the collected continuous-time data is divided into equally spaced time arrays to improve computational efficiency. This time array is input into a pre-constructed first objective function, which outputs a corresponding temperature array to reflect the change in surface temperature of the sample lithium battery over time. Subsequently, the time array is input into a first model, which outputs the surface heat generation power at each time point, forming an array-based dataset. Simultaneously, the temperature array is input into a second model, which outputs the heat dissipation power at each time point, forming another set of array data. By processing the time and temperature data step-by-step, independent calculation of heat generation and heat dissipation power is achieved.

[0047] Compared to existing technologies, traditional methods typically model the original time series as a whole without discretizing the data, resulting in high computational complexity and difficulty in separating heat generation and dissipation effects. This method reduces data dimensionality by evenly distributing the time array and, combined with a strategy of step-by-step input to different models, effectively distinguishes the calculation paths for apparent heat generation and dissipation power, avoiding mutual interference between the two types of parameters.

[0048] Through the above technical solution, this application achieves independent quantitative calculation of heat generation and heat dissipation power, solving the measurement error problem caused by thermal coupling effect in traditional calorimetry. By processing the discrete-time array step by step, the accuracy and computational efficiency of heat generation power calculation are significantly improved.

[0049] In another alternative embodiment, such as Figure 4 As shown, Figure 4 An embodiment of a method for constructing a first model provided in this application includes the following steps: Step S401: Differentiate the first objective function with respect to time to obtain the relationship between the rate of temperature change and time; The purpose of differentiating the first objective function with respect to time is to transform the test data from discrete points into a smooth, continuous function, converting static temperature data into a dynamic process, thus providing a foundation for establishing the first model. The formula for differentiating the first objective function with respect to time is as follows:

[0050] Step S402: Construct the first model based on the relationship between temperature change rate and time and the relationship between power and temperature.

[0051] The relationship between power and temperature refers to the correlation equation between heat production power and temperature change established based on thermodynamic principles. This relationship directly links the rate of temperature change with the heat production power, thereby constructing a complete first model.

[0052] For example, the first model obtained by construction is:

[0053] Compared to existing technologies, traditional methods often use linear fitting or even-degree polynomials for temperature data modeling, which makes it difficult to accurately describe the asymmetric temperature changes during the charging and discharging of lithium batteries. By using odd-degree polynomial fitting, the different rates of temperature change during the rising and falling phases can be captured more accurately, eliminating distortions that may occur near extreme points in the fitted curve, thereby improving the accuracy of the heat generation power calculation model.

[0054] Through the above technical solution, this application can effectively solve the problem of model distortion caused by improper selection of fitting function in the process of temperature data modeling. By the synergistic effect of odd-degree polynomials and thermodynamic equations, a first model that is more in line with actual working conditions is established, providing accurate power data support for lithium battery thermal management.

[0055] In another alternative embodiment, such as Figure 5 As shown, Figure 5 An embodiment of a method for constructing a second model provided in an exemplary embodiment of this application includes the following steps: Step S501: Input the second temperature data and the second time data into the second initial function expression for least squares fitting to obtain the second objective function expression; The second initial function is a mathematical expression used to describe the temperature change over time in the second stage. For example:

[0056] in, , , As a parameter, T x Let be the ambient temperature during the test, t be the second time data, and T be the second temperature data. Substitute the collected second temperature data and second time data into the above equation sequentially to perform least-squares fitting and solve for the unknown parameters, thus obtaining the second objective function.

[0057] Step S502: After differentiating the second objective function with respect to time, obtain the relationship between the rate of temperature change and temperature. The differentiation transformation refers to expressing the rate of temperature change as a function of temperature through algebraic transformation after performing time derivative operations on the second objective function. For example, the correspondence between the rate of temperature change and temperature can be obtained using the following formula: First, take the time derivative of the second objective function:

[0058] Then Moving the middle element to the left yields:

[0059] Finally, substituting the above equation into the differentiated relation, we get:

[0060] Step S503: Construct a second model based on the relationship between temperature change rate and temperature and the relationship between power and temperature.

[0061] The relationship between power and temperature is as follows:

[0062] m is the mass of the sample lithium battery, and c is the specific heat capacity of the sample lithium battery.

[0063] Will Substituting the relationship between power and temperature, we obtain the second model;

[0064] Compared to existing technologies, traditional methods typically use fixed empirical formulas or simplified models to calculate heat dissipation power, such as directly using Newton's law of cooling without considering the nonlinear characteristics of actual heat dissipation conditions. In contrast, this method, through experimental data-driven least-squares fitting and rigorous mathematical derivation, can automatically adapt to changes in heat dissipation characteristics across different temperature ranges. Especially in the transition between high and low temperature regions, it can more accurately characterize the dynamic response of heat dissipation power.

[0065] Through the above technical solution, this application achieves parameter adaptability of the heat dissipation power model, solving the problem of heat dissipation power calculation deviation caused by model simplification in traditional methods. By accurately separating heat dissipation power from apparent heat generation power, it provides high-precision basic data support for subsequent calculation of actual heat generation power, thereby improving the reliability of lithium battery thermal characteristic analysis.

[0066] Optionally, this application uses the ampere-hour integration method to convert the time in the initial correspondence information into the state of charge of the sample lithium battery based on the initial state of charge, test current, test time, and rated capacity of the sample lithium battery. The expression is as follows:

[0067] in, For the initial state of charge, t is the test current, and t is the test time. This is the rated capacity.

[0068] Compared to existing technologies, traditional methods often treat time as an independent variable directly related to heat generation power, ignoring the nonlinear relationship between the state of charge (SOC) and time during actual battery operation. For example, under varying current conditions, the change in SOC corresponding to the same time interval may differ significantly, leading to errors in heat generation power assessment. This solution, however, converts the time parameter into SOC using the ampere-hour integration method, eliminating the influence of current fluctuations on the time-SOC correspondence and making the heat generation power matching process more closely reflect the actual operating state of the battery.

[0069] Through the above technical solution, this application achieves a precise correspondence between heat generation power and state of charge, avoiding the deviation in heat generation power evaluation caused by the mismatch between time parameters and the actual state of charge of the battery, and providing an accurate dynamic thermal characteristic data basis for the design of lithium battery thermal management system.

[0070] Optionally, this application will adjust the initial state of the sample lithium battery before collecting data, including the following steps: Before collecting the first temperature data of the sample lithium battery in the first stage under the target operating conditions, the sample lithium battery is charged to the upper limit voltage under the first target ambient temperature using a standard constant current and constant voltage charging mode. Under the second target ambient temperature, the sample lithium battery charged to the upper limit voltage is left to stand for a preset time; Alternatively, at the first target ambient temperature, the sample lithium battery charged to the upper limit voltage is discharged to the lower limit voltage; Under the second target ambient temperature, the sample lithium battery, discharged to the lower limit voltage, is left to stand for a preset time.

[0071] Since the target operating conditions include both charging and discharging conditions, the preprocessing methods will also differ. Simply put, to test the actual heat generation power under charging conditions, the ambient temperature must first be set to the first target ambient temperature (e.g., 25°C). At the first target ambient temperature, the lithium battery is charged to its upper limit voltage using a standard constant current and constant voltage (e.g., 0.33C) charging mode. Then, it is placed in an environment at a second target temperature (e.g., 45°C) and left to stand for a preset time (e.g., 2 hours). Next, it is placed in the second target temperature environment and discharged to its lower limit voltage. Finally, it is placed in the second target temperature environment and left to stand for a preset time (e.g., 2 hours) to complete the initial state adjustment of the sample lithium battery.

[0072] For discharge conditions, the ambient temperature needs to be set to the first target ambient temperature (e.g., 25°C), and the lithium battery needs to be charged to the upper limit voltage using the standard constant current and constant voltage (e.g., 0.33C) charging mode. Then, the sample lithium battery can be placed in the environment of the second target temperature (e.g., 45°C) for a preset time (e.g., 2 hours) to adjust the initial state of the sample lithium battery.

[0073] The purpose of performing the above process is to bring the battery to a defined state baseline through a standardized charge-discharge procedure before collecting heat generation data. During charging condition testing, the battery must first undergo a complete constant current / constant voltage charging process, followed by resting at a specific temperature to eliminate polarization effects. During discharging condition testing, the battery must first be discharged to the cutoff voltage and then rested. This pretreatment method ensures that the battery has a stable initial state of charge and thermodynamic state at the start of the test, thereby avoiding interference from residual charge or temperature gradients in subsequent heat generation power calculations.

[0074] Compared to existing technologies, current thermal analysis techniques often neglect standardized control of the battery's initial state, directly collecting temperature data from batteries with different charge-discharge histories, leading to systematic errors in heat generation power calculations. This proposed solution, by establishing a standardized charge-discharge pretreatment process combined with static operation at specific temperatures, effectively eliminates the impact of internal battery polarization and thermal hysteresis on test results.

[0075] Through the above technical solutions, this application can ensure that the sample lithium batteries reach a uniform thermodynamic equilibrium state before the heat generation power test, thereby improving the accuracy and repeatability of temperature data acquisition. The standardized preprocessing procedure can avoid the deviation in heat generation power calculation caused by differences in the initial state of the batteries, providing a reliable data foundation for subsequently establishing an accurate correspondence between state of charge and heat generation power.

[0076] It should be noted that although the operations of the method of the present invention are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all of the operations shown must be performed to achieve the desired result. On the contrary, the steps depicted in the flowchart may be performed in a different order.

[0077] Further reference Figure 6 The diagram illustrates an exemplary structural block diagram of a lithium battery heat generation power determination device 600 according to an embodiment of this application. The lithium battery heat generation power determination device 600 includes an acquisition module 601 and a matching acquisition module 602. The acquisition module is used to acquire the current state of charge of the target lithium battery. The matching module is used to match the state of charge of the target lithium battery with the target correspondence information to obtain the actual heat generation power of the target lithium battery at the current moment. The target correspondence information includes multiple actual heat generation powers and the state of charge corresponding to each heat generation power. The actual heat generation power in the target correspondence information is obtained after compensating the heat dissipation power of the surface heat generation power of the sample lithium battery in the first stage. The first stage is the stage in which heat generation and heat dissipation of the sample lithium battery coexist.

[0078] In an optional embodiment, a construction module is further included for collecting first temperature data of the sample lithium battery in the first stage and first temperature data of the sample lithium battery in the second stage under target operating conditions, wherein the second stage is a stage in which the sample lithium battery is purely dissipating heat. A first model is constructed based on the first temperature data and the first time data, and a second model is constructed based on the second temperature data and the second time data, wherein the first time data is the time data for collecting the first temperature data, and the second time data is the time data for collecting the second temperature data; Based on the first time data, the first model, and the second model, a surface heat generation power array and a heat dissipation power array are obtained. The surface heat generation power in the surface heat generation power array and the heat dissipation power in the heat dissipation power array are summed according to time to obtain the true heat generation power, and the true heat generation power is correlated with time to obtain the initial correspondence information; The time in the initial correspondence information is converted into the state of charge of the sample lithium battery to obtain the target correspondence information.

[0079] In an optional embodiment, the construction module is specifically used to divide the first time data into equal parts to obtain a time array; The time array is input into the first objective function to obtain the temperature array. The first objective function is obtained by performing odd-degree polynomial fitting based on the first temperature data and the first time data. Input the time array into the first model to obtain the surface heat generation power array; Input the temperature array into the second model to obtain the heat dissipation power array.

[0080] In an optional embodiment, the construction module is further configured to differentiate the first objective function with respect to time to obtain the correspondence between the rate of temperature change and time. The first model is constructed based on the relationship between the rate of temperature change and time, and the relationship between power and temperature.

[0081] In an optional embodiment, the construction module is further configured to input the second temperature data and the second time data into the second initial function for least squares fitting to obtain the second objective function; The relationship between the rate of temperature change and temperature is obtained by differentiating the second objective function with respect to time. The second model is constructed based on the relationship between the rate of temperature change and temperature, and the relationship between power and temperature.

[0082] In an optional embodiment, the construction module is further configured to convert the time in the initial correspondence information into the state of charge of the sample lithium battery using the ampere-hour integration method based on the initial state of charge, test current, test time, and rated capacity of the sample lithium battery.

[0083] In an optional embodiment, before acquiring the first temperature data of the sample lithium battery in the first stage under the target operating conditions, the sample lithium battery is charged to the upper limit voltage in a standard constant current and constant voltage charging mode at the first target ambient temperature. Under the second target ambient temperature, the sample lithium battery charged to the upper limit voltage is left to stand for a preset time; Alternatively, at the first target ambient temperature, the sample lithium battery, charged to the upper limit voltage, is discharged to the lower limit voltage; Under the second target ambient temperature, the sample lithium battery, discharged to the lower limit voltage, is left to stand for the preset time.

[0084] In an optional embodiment, if the target operating condition is a discharge operating condition, then the first stage is the stage of discharging the sample lithium battery from the upper limit voltage to the lower limit voltage, and the second stage is the stage of letting the sample lithium battery, which has been discharged to the lower limit voltage, stand for the preset time. If the target operating condition is a charging operating condition, then the first stage is the stage of charging the sample lithium battery to the upper limit voltage using the standard constant current and constant voltage charging mode, and the second stage is the stage of letting the sample lithium battery charged to the upper limit voltage rest for the preset time.

[0085] Each module in the aforementioned lithium battery heat generation power determination device 600 can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0086] In another aspect, this application also provides a computer-readable storage medium, which may be a computer-readable storage medium included in the apparatus described in the above embodiments; or it may be a standalone computer-readable storage medium not assembled into the device. The computer-readable storage medium stores one or more programs, which are used by one or more processors to execute the method for determining the heat generation power of a lithium battery described in this application.

[0087] The above description is merely a preferred embodiment of this application and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A method for determining the heat generation power of a lithium battery, characterized in that, The method includes: Obtain the current state of charge of the target lithium battery; The state of charge of the target lithium battery is matched with the target correspondence information to obtain the actual heat generation power of the target lithium battery at the current moment. The target correspondence information includes multiple actual heat generation powers and the state of charge corresponding to each actual heat generation power. The actual heat generation power is the heat generation power after heat dissipation power compensation of the heat generation power on the surface of the lithium battery.

2. The determination method according to claim 1, characterized in that, The steps for obtaining the target correspondence information include: Under target operating conditions, the sample lithium battery is collected at the first temperature in the first stage and at the first temperature in the second stage, where the second stage is a stage of pure heat dissipation for the sample lithium battery. A first model is constructed based on the first temperature data and the first time data, and a second model is constructed based on the second temperature data and the second time data, wherein the first time data is the time data for collecting the first temperature data, and the second time data is the time data for collecting the second temperature data; Based on the first time data, the first model, and the second model, a surface heat generation power array and a heat dissipation power array are obtained. The surface heat generation power in the surface heat generation power array and the heat dissipation power in the heat dissipation power array are summed according to time to obtain the true heat generation power, and the true heat generation power is correlated with time to obtain the initial correspondence information; The time in the initial correspondence information is converted into the state of charge of the sample lithium battery to obtain the target correspondence information.

3. The determination method according to claim 2, characterized in that, The step of obtaining the surface heat generation power array and heat dissipation power array based on the first time data, the first model, and the second model includes: The first time data is divided into equal parts to obtain a time array; The time array is input into the first objective function to obtain the temperature array. The first objective function is obtained by performing odd-degree polynomial fitting based on the first temperature data and the first time data. Input the time array into the first model to obtain the surface heat generation power array; Input the temperature array into the second model to obtain the heat dissipation power array.

4. The determination method according to claim 3, characterized in that, The construction of the first model based on the first temperature data and the first time data includes: Differentiate the first objective function with respect to time to obtain the relationship between the rate of temperature change and time; The first model is constructed based on the relationship between the rate of temperature change and time, and the relationship between power and temperature.

5. The determination method according to claim 2, characterized in that, The construction of the second model based on the second temperature data and the second time data includes: The second temperature data and the second time data are input into the second initial function and least squares fit is performed to obtain the second objective function. The relationship between the rate of temperature change and temperature is obtained by differentiating the second objective function with respect to time. The second model is constructed based on the relationship between the rate of temperature change and temperature, and the relationship between power and temperature.

6. The determination method according to claim 2, characterized in that, The step of converting the time in the initial correspondence information into the state of charge of the sample lithium battery includes: Based on the initial state of charge, test current, test time, and rated capacity of the sample lithium battery, the time in the initial correspondence information is converted into the state of charge of the sample lithium battery using the ampere-hour integration method.

7. The determination method according to claim 2, characterized in that, The method further includes: Before collecting the first temperature data of the sample lithium battery in the first stage under the target operating conditions, the sample lithium battery is charged to the upper limit voltage in a standard constant current and constant voltage charging mode at the first target ambient temperature. Under the second target ambient temperature, the sample lithium battery charged to the upper limit voltage is left to stand for a preset time; Alternatively, at the first target ambient temperature, the sample lithium battery, charged to the upper limit voltage, is discharged to the lower limit voltage; Under the second target ambient temperature, the sample lithium battery, discharged to the lower limit voltage, is left to stand for the preset time.

8. The determination method according to claim 7, characterized in that, If the target operating condition is a discharge operating condition, then the first stage is the stage of discharging the sample lithium battery from the upper limit voltage to the lower limit voltage, and the second stage is the stage of letting the sample lithium battery, which has been discharged to the lower limit voltage, stand for the preset time. If the target operating condition is a charging operating condition, then the first stage is the stage of charging the sample lithium battery to the upper limit voltage using the standard constant current and constant voltage charging mode, and the second stage is the stage of letting the sample lithium battery charged to the upper limit voltage rest for the preset time.

9. A device for determining the heat generation power of a lithium battery, characterized in that, The device includes: The acquisition module is used to acquire the current state of charge of the target lithium battery. The matching module is used to match the state of charge of the target lithium battery with the target correspondence information to obtain the actual heat generation power of the target lithium battery at the current moment. The target correspondence information includes multiple actual heat generation powers and the state of charge corresponding to each heat generation power. The actual heat generation power in the target correspondence information is obtained after compensating the heat dissipation power of the surface heat generation power of the sample lithium battery in the first stage. The first stage is the stage in which heat generation and heat dissipation of the sample lithium battery coexist.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 8.

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