Temperature control method of lithium iron phosphate battery, electronic equipment and program product

Abstract

The embodiment of the invention provides a temperature control method of a lithium iron phosphate battery, electronic equipment and a program product. The method comprises the following steps: acquiring temperature structure data of a to-be-controlled battery, and acquiring real-time working data of the to-be-controlled battery; the temperature structure data comprises position data of a temperature monitoring point of the to-be-controlled battery; wherein the temperature monitoring point is a pre-calibrated monitoring point used for performing temperature control on the battery to be controlled; based on a preset temperature simulation model, performing thermal simulation processing according to the temperature structure data and the real-time working data to obtain a predicted temperature of the temperature monitoring point; and determining a temperature control parameter of the to-be-controlled battery according to the predicted temperature of the temperature monitoring point, and performing temperature control processing on the to-be-controlled battery based on the determined temperature control parameter. The method is used for achieving the effect of improving the operation safety of the battery.

Description

Technical Field

[0001] The present application relates to the technical field of batteries, and particularly to a temperature control method, an electronic device, and a program product for a lithium iron phosphate battery. Background Art

[0002] Lithium iron phosphate batteries (LiFePO4 batteries) are widely used in fields such as electric vehicles, energy storage systems, and portable electronic devices due to their high safety, long cycle life, and environmental protection characteristics. However, with the continuous increase in battery capacity and power requirements, the heat generated by the battery during charging and discharging has gradually become one of the important factors affecting battery performance and life. The temperature change of the battery not only directly affects the charging and discharging efficiency of the battery, but also affects the service life and safety of the battery. Therefore, it is particularly important to perform timely and effective temperature control on the battery.

[0003] In the prior art, a temperature sensor is used to monitor the temperature of the battery in real time, and the temperature of the battery is controlled based on the monitoring results to ensure the safe operation of the battery.

[0004] However, the method in the prior art may lead to problems of inaccurate and untimely temperature control, resulting in poor operational safety of the battery. Summary of the Invention

[0005] Embodiments of the present application provide a temperature control method, an electronic device, and a program product for a lithium iron phosphate battery, so as to achieve the effect of improving the operational safety of the battery.

[0006] In a first aspect, an embodiment of the present application provides a temperature control method for a lithium iron phosphate battery, including:

[0007] Obtain the temperature structure data of the battery to be controlled, and obtain the real-time working data of the battery to be controlled; wherein, the temperature structure data includes the position data of the temperature monitoring points of the battery to be controlled; wherein, the temperature monitoring points are pre-calibrated monitoring points for temperature control of the battery to be controlled;

[0008] Based on a preset temperature simulation model, perform thermal simulation processing according to the temperature structure data and the real-time working data to obtain the predicted temperature of the temperature monitoring points;

[0009] Determine the temperature control parameters of the battery to be controlled according to the predicted temperature of the temperature monitoring points, and perform temperature control processing on the battery to be controlled based on the determined temperature control parameters.

[0010] In a possible implementation, the temperature structure data includes position data of at least one heat source reference center point of the battery to be controlled; wherein, the heat source reference center point is a pre-calibrated center point that generates heat during the operation of the battery to be controlled; based on a preset temperature simulation model, thermal simulation processing is performed according to the temperature structure data and the real-time working data to obtain the predicted temperature of the temperature monitoring point, including: based on the preset temperature simulation model, basis function value generation processing is performed according to the temperature structure data and the real-time working data to obtain the basis function value corresponding to the heat source reference center point; based on the preset temperature simulation model, calculation processing is performed on the basis function values corresponding to each heat source reference center point to obtain the predicted temperature of the temperature monitoring point.

[0011] In a possible implementation, the temperature structure data further includes the size data of the battery; the real-time working data includes working current data and ambient temperature data; based on the preset temperature simulation model, basis function value generation processing is performed according to the temperature structure data and the real-time working data to obtain the basis function value corresponding to the heat source reference center point, including: based on the preset temperature simulation model, calculation processing is performed on the position data of the temperature monitoring point and the position data of the heat source reference center point to obtain a heat diffusion parameter; based on the preset temperature simulation model, processing is performed on the size data of the battery to obtain a heat distribution parameter; based on the preset temperature simulation model, calculation processing is performed on the working current data and the ambient temperature data to obtain a heat fluctuation parameter; based on the preset temperature simulation model, calculation processing is performed on the heat diffusion parameter, the heat distribution parameter, and the heat fluctuation parameter to obtain the basis function value corresponding to the heat source reference center point.

[0012] In a possible implementation, according to the predicted temperature of the temperature monitoring point, the temperature control parameter of the battery to be controlled is determined, including: determining the temperature control type of the battery to be controlled, and obtaining a parameter adjustment coefficient corresponding to the temperature control type; based on the predicted temperature of the temperature monitoring point and the parameter adjustment coefficient, the temperature control parameter of the battery to be controlled is determined.

[0013] In a possible implementation, the temperature control type includes at least one of a liquid cooling type, an air cooling type, a direct cooling type, and a hot spot cooling type.

[0014] In a possible implementation manner, the method further includes: obtaining predicted temperatures of temperature monitoring points of other batteries included in the battery pack where the battery to be controlled is located based on a preset temperature simulation model; determining a thermal runaway probability of the battery to be controlled based on the predicted temperatures of the temperature monitoring points of the other batteries and the predicted temperature of the temperature monitoring point of the battery to be controlled; and if the thermal runaway probability is greater than a preset thermal runaway probability threshold, performing a thermal runaway temperature control process on the battery to be controlled.

[0015] In a possible implementation manner, performing a thermal runaway temperature control process on the battery to be controlled includes at least one of the following: controlling the battery pack where the battery to be controlled is located to perform a shutdown process; determining a temperature control type of the battery to be controlled, and obtaining a thermal runaway temperature control parameter corresponding to the temperature control type; then performing a temperature control process on the battery pack where the battery to be controlled is located based on the thermal runaway temperature control parameter; generating and presenting a thermal runaway warning prompt message.

[0016] In a second aspect, an embodiment of the present application provides a temperature control device for a lithium iron phosphate battery, including:

[0017] An acquisition module, configured to acquire temperature structure data of a battery to be controlled and acquire real-time working data of the battery to be controlled; wherein, the temperature structure data includes position data of a temperature monitoring point of the battery to be controlled; wherein, the temperature monitoring point is a pre-calibrated monitoring point for performing temperature control on the battery to be controlled;

[0018] A processing module, configured to perform a thermal simulation process based on a preset temperature simulation model according to the temperature structure data and the real-time working data to obtain a predicted temperature of the temperature monitoring point;

[0019] A control module, configured to determine a temperature control parameter of the battery to be controlled according to the predicted temperature of the temperature monitoring point, and perform a temperature control process on the battery to be controlled based on the determined temperature control parameter.

[0020] In a possible implementation manner, the temperature structure data includes position data of at least one heat source reference center point of the battery to be controlled; wherein, the heat source reference center point is a pre-calibrated center point that generates heat during the operation of the battery to be controlled; the processing module is specifically configured to perform a basis function value generation process based on a preset temperature simulation model according to the temperature structure data and the real-time working data to obtain a basis function value corresponding to the heat source reference center point; and perform a calculation process on the basis function values corresponding to each heat source reference center point based on a preset temperature simulation model to obtain a predicted temperature of the temperature monitoring point.

[0021] In a possible implementation manner, the temperature structure data further includes the size data of the battery; the real-time working data includes the working current data and the ambient temperature data; the processing module is further specifically configured to perform calculation processing on the position data of the temperature monitoring points and the position data of the heat source reference center point based on a preset temperature simulation model to obtain a heat diffusion parameter; perform processing on the size data of the battery based on a preset temperature simulation model to obtain a heat distribution parameter; perform calculation processing on the working current data and the ambient temperature data based on a preset temperature simulation model to obtain a heat fluctuation parameter; perform calculation processing on the heat diffusion parameter, the heat distribution parameter, and the heat fluctuation parameter based on a preset temperature simulation model to obtain the basis function value corresponding to the heat source reference center point.

[0022] In a possible implementation manner, the control module is specifically configured to determine the temperature control type of the battery to be controlled and obtain a parameter adjustment coefficient corresponding to the temperature control type; determine the temperature control parameter of the battery to be controlled based on the predicted temperature of the temperature monitoring point and the parameter adjustment coefficient.

[0023] In a possible implementation manner, the temperature control type includes at least one of a liquid cooling type, an air cooling type, a direct cooling type, and a hot spot cooling type.

[0024] In a possible implementation manner, the control module is further configured to obtain the predicted temperatures of the temperature monitoring points of the other batteries included in the battery pack where the battery to be controlled is located based on a preset temperature simulation model; determine the thermal runaway probability of the battery to be controlled based on the predicted temperatures of the temperature monitoring points of the other batteries and the predicted temperature of the temperature monitoring point of the battery to be controlled; if the thermal runaway probability is greater than a preset thermal runaway probability threshold, perform thermal runaway temperature control processing on the battery to be controlled.

[0025] In a possible implementation manner, the control module is further specifically configured to perform at least one of the following: control the battery pack where the battery to be controlled is located to perform a work shutdown process; determine the temperature control type of the battery to be controlled and obtain the thermal runaway temperature control parameter corresponding to the temperature control type; then perform temperature control processing on the battery pack where the battery to be controlled is located based on the thermal runaway temperature control parameter; generate and present a thermal runaway warning prompt message.

[0026] In a third aspect, an embodiment of the present application provides an electronic device, including: a memory, a processor;

[0027] The memory stores computer execution instructions;

[0028] The processor executes the computer-executable instructions stored in the memory, such that the processor executes the first aspect and / or various possible implementation manners of the first aspect as described above.

[0029] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing computer-executable instructions, which are used to implement the first aspect and / or various possible implementation manners of the first aspect as described above when being executed by a processor.

[0030] In a fifth aspect, an embodiment of the present application provides a computer program product including a computer program, which implements the first aspect and / or various possible implementation manners of the first aspect as described above when being executed by a processor.

[0031] The temperature control method, electronic device and program product of the lithium iron phosphate battery provided by the embodiments of the present application obtain the temperature structure data of the battery to be controlled and the real-time working data of the battery to be controlled, perform thermal simulation processing based on the preset temperature simulation model according to the temperature structure data and the real-time working data to obtain the predicted temperature of the temperature monitoring point, determine the temperature control parameter of the battery to be controlled according to the predicted temperature of the temperature monitoring point, and perform temperature control processing on the battery to be controlled based on the determined temperature control parameter. Among them, predicting the battery temperature based on the preset temperature simulation model and performing temperature control based on the predicted temperature improves the accuracy and efficiency of temperature control, thereby improving the operating safety of the battery. Among them, during the process of predicting the battery temperature, predicting the temperature of the pre-calibrated temperature monitoring point improves the efficiency and accuracy of temperature prediction, thereby improving the accuracy and efficiency of temperature control and further improving the operating safety of the battery. Based on the above description, the temperature control method of the lithium iron phosphate battery provided by the embodiments of the present application improves the operating safety of the battery. Description of the Drawings

[0032] The drawings here are incorporated into the specification and form a part of this specification, showing the embodiments consistent with the present application and used to explain the principles of the present application together with the specification.

[0033] Figure 1 Schematic flow of the temperature control method of the lithium iron phosphate battery provided by the present application Figure 1 ;

[0034] Figure 2 Schematic flow of the temperature control method of the lithium iron phosphate battery provided by the present application Figure 2 ;

[0035] Figure 3 Schematic flow of the temperature control method of the lithium iron phosphate battery provided by the present application Figure 3 ;

[0036] Figure 4 Schematic structural diagram of the temperature control device for the lithium iron phosphate battery provided by this application;

[0037] Figure 5 Schematic structural diagram of the electronic device provided by this application.

[0038] Through the above-mentioned drawings, specific embodiments of this application have been shown, and there will be more detailed descriptions hereinafter. These drawings and textual descriptions are not intended to limit the scope of the concept of this application in any way, but to illustrate the concept of this application to those skilled in the art by referring to specific embodiments. Specific Embodiments

[0039] Here, exemplary embodiments will be described in detail, and examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numerals in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. On the contrary, they are merely examples of devices and methods consistent with some aspects of this application as detailed in the appended claims.

[0040] In the prior art, a temperature sensor is used to monitor the temperature of the battery in real time, and the temperature of the battery is controlled based on the monitoring results to ensure the safe operation of the battery. However, the method in the prior art may cause problems of inaccurate and untimely temperature control, resulting in poor operational safety of the battery.

[0041] The temperature control method for the lithium iron phosphate battery provided by this application includes obtaining the temperature structure data of the battery to be controlled, obtaining the real-time working data of the battery to be controlled, performing thermal simulation processing based on a preset temperature simulation model according to the temperature structure data and the real-time working data to obtain the predicted temperature of the temperature monitoring point, determining the temperature control parameters of the battery to be controlled according to the predicted temperature of the temperature monitoring point, and performing temperature control processing on the battery to be controlled based on the determined temperature control parameters. Among them, predicting the battery temperature based on a preset temperature simulation model and performing temperature control based on the predicted temperature improves the accuracy and efficiency of temperature control, thereby improving the operational safety of the battery. Among them, during the process of predicting the battery temperature, predicting the temperature of the pre-calibrated temperature monitoring point improves the efficiency and accuracy of temperature prediction, thereby improving the accuracy and efficiency of temperature control and further improving the operational safety of the battery. Based on the above description, the temperature control method for the lithium iron phosphate battery provided by the embodiments of this application improves the operational safety of the battery.

[0042] The following uses specific embodiments to elaborate in detail on the technical solution of the present application and how the technical solution of the present application solves the above technical problems. The following several specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0043] Figure 1 Flow schematic of the temperature control method for the lithium iron phosphate battery provided by the present application Figure 1 As Figure 1 shown, the method includes:

[0044] Step S101, obtain the temperature structure data of the battery to be controlled, and obtain the real-time working data of the battery to be controlled.

[0045] Specifically, the temperature structure data of the battery to be controlled can be obtained, where the temperature structure data is pre-calibrated structure data related to the temperature of the battery to be controlled. The temperature structure data includes the position data of the temperature monitoring points of the battery to be controlled. Among them, the temperature monitoring point is a pre-calibrated monitoring point for temperature control of the battery to be controlled.

[0046] Specifically, the present application does not limit the temperature monitoring points. Optionally, the position point on the battery to be controlled that is most effective for monitoring the working temperature of the battery, that is, the position point with the highest temperature during the working process of the battery to be controlled, can be determined as the temperature monitoring point of the battery to be controlled.

[0047] Specifically, the present application does not limit the pre-calibration process of the temperature structure data. Optionally, the pre-calibration process of the temperature structure data provided by the present application may include the following steps:

[0048] First, clarify the calibration purpose and requirements. Specifically, before starting the pre-calibration, it is first necessary to clarify the calibration purpose and requirements. This includes determining the specific parameters to be calibrated during the process of the temperature structure data (that is, temperature parameters, such as the internal temperature and surface temperature of the battery, etc.), as well as the accuracy and range required for calibration. At the same time, it is also necessary to understand the type, specifications, and usage environment of the battery to provide guidance for subsequent calibration work.

[0049] Second, prepare the calibration equipment and tools. Among them, the present application does not limit the calibration equipment and tools provided by the present application. Optionally, it includes but is not limited to: a constant temperature chamber for simulating the working environment of the battery at different ambient temperatures; a temperature sensor for measuring the internal temperature and surface temperature of the battery; a data recording device for recording the temperature data and other relevant parameters during the calibration process; and calibration software for data processing and analysis, as well as output and storage of the calibration results.

[0050] Then, design the calibration experiment. Determine the calibration environmental temperature range: Based on the battery's usage environment and performance requirements, determine the range of the calibration environmental temperature. Set the environmental temperature step: Within the calibration environmental temperature range, adjust the temperature of the thermostat according to the set step. Standing time: At each environmental temperature, let the battery stand for a certain period (e.g., 4 hours) to ensure that the internal temperature and surface temperature of the battery reach an equilibrium state.

[0051] Next, perform the calibration experiment. Place the battery: Place the battery to be calibrated in the thermostat. Adjust the environmental temperature: Adjust the environmental temperature of the thermostat according to the set step and let it stand for a certain period at each environmental temperature. Measure the battery temperature: At each environmental temperature, use a temperature sensor to measure the internal temperature and surface temperature of the battery under different working conditions and record the data. Repeat the experiment: To improve the accuracy of calibration, the experiment can be repeated multiple times at each environmental temperature and each working condition, and the average value can be taken as the final result.

[0052] Subsequently, process and analyze the data. Plot the temperature curve: Use the calibration software to plot the measured battery temperature data into a temperature curve to visually observe the variation law of the battery temperature with the environmental temperature. Analyze the temperature difference: Compare the internal temperature and surface temperature of the battery and analyze the differences and variation trends between them. Determine the optimal working parameters, i.e., the temperature structure data of the battery, such as the temperature monitoring points: According to the calibration results, determine the position points with the highest temperature of the battery to be calibrated at each environmental temperature and each disclosure.

[0053] Furthermore, verify the calibration results. Simulate the actual usage scenario: Through simulating the actual usage scenario, conduct a long-term running test on the battery and observe whether its temperature performance is stable, i.e., whether the temperature of the calibrated temperature monitoring point is always the highest position of the battery temperature. Collect user feedback: Collect user feedback in actual applications, understand the temperature performance of the battery in different environments, and optimize the calibration parameters according to the feedback.

[0054] Finally, record and store the calibration results. Record the calibration data: Record all the data obtained during the calibration process, including temperature data, time data, battery status data, etc. Store the calibration results: Store the calibration results in a safe and reliable storage medium for subsequent reference and use.

[0055] Optionally, during the calibration process of the temperature monitoring point, attention should be paid to the safety, accuracy, and repeatability of the calibration process. Among them, safety means that during the entire calibration process, it is necessary to ensure the safety of operations and avoid dangerous situations such as battery overheating and short circuits; accuracy means that in order to improve the accuracy of calibration, it is necessary to strictly control experimental conditions, such as the accuracy of the constant temperature box and the accuracy of the temperature sensor, etc.; repeatability means that the calibration experiment should be repeatable for verification and comparison at different times and different locations.

[0056] Specifically, this application does not limit the process of obtaining the temperature structure data of the battery to be controlled. Optionally, the model of the battery to be controlled can be obtained first; then, according to the model of the battery to be controlled, the temperature structure data corresponding to the model of the battery to be controlled can be extracted from the pre-stored mapping table of the battery model and temperature structure data. Optionally, the mapping table of the battery model and temperature structure data can be obtained through the pre-calibration process described above.

[0057] Specifically, the real-time working data of the battery to be controlled can be obtained. Among them, the real-time working data of the battery refers to the working-related data obtained in real time during the operation of the battery. Specifically, this application does not limit the real-time working data of the battery to be controlled. Optionally, it includes but is not limited to: basic power parameters, voltage and current parameters, internal resistance and temperature parameters, and other key parameters.

[0058] Among them, the basic power parameters include but are not limited to: the remaining power percentage, which reflects the current state of the battery and is usually expressed as a percentage. For example, when the battery is fully charged, the displayed value is 100%; as the power is consumed, the value gradually decreases until it drops to 0% when the power is exhausted; the charging state, which indicates whether the battery is charging or fully charged. This is usually displayed through a charging icon or text prompt.

[0059] Among them, the voltage and current parameters include but are not limited to: the open-circuit voltage, which is the potential difference of the battery in the non-working state and is of great significance for battery state estimation and performance evaluation; the terminal voltage, which reflects the instantaneous state of the battery during operation and is one of the key parameters for battery performance evaluation; the charge and discharge current, which represents the magnitude of the current during the charging or discharging process of the battery. For lithium batteries, too large a charge and discharge current may damage the battery.

[0060] Among them, the internal resistance and temperature parameters include but are not limited to: the internal resistance, including the ohmic internal resistance and the polarization internal resistance, which reflects the resistance of the battery during charge and discharge. The size of the internal resistance directly affects the charging efficiency and discharge power of the battery; the temperature, the ambient temperature of the battery has an important impact on its performance. Too high or too low a temperature may lead to a decline in battery performance and even cause safety problems.

[0061] Among them, other key parameters include but are not limited to: discharge rate, defined as the current value required to discharge its rated capacity within a specified time, which is directly related to the acceleration performance and charging time of the battery; rated capacity and actual capacity, where the rated capacity is the maximum discharge power of the battery under standard conditions, while the actual capacity is affected by various factors such as temperature, discharge rate, and battery aging; cut-off voltage, which defines the voltage range of the battery during charging or discharging, and strictly controlling the battery to operate within this range is a key measure to ensure battery safety; self-discharge rate, which describes the rate of power loss of the battery when not in use, and this has a certain impact on maintaining the performance of the battery during long-term storage; cycle life and calendar life, which respectively reflect the durability of the battery during repeated charging and discharging and during use. These two indicators are crucial for evaluating the economy and service life of the battery.

[0062] Specifically, this application does not limit the method of obtaining the real-time working data of the battery to be controlled. Optionally, according to the specific type of the working data, the acquisition method of each type of working data can be determined respectively. For example, if the type of the working data is the type obtained by direct measurement, the working data can be obtained in real time by measurement, such as data of charge and discharge current, open-circuit voltage, terminal voltage, internal resistance, and temperature. For example, if the type of the working data is not the type obtained by direct measurement, the initial data of the working data can be obtained in real time by measurement first, and then the working data can be calculated in real time according to a preset calculation method, such as data of remaining power percentage, rated capacity and actual capacity, and self-discharge rate.

[0063] Step S102: Based on a preset temperature simulation model, perform thermal simulation processing according to the temperature structure data and the real-time working data to obtain the predicted temperature of the temperature monitoring point.

[0064] Specifically, after obtaining the temperature structure data of the battery to be controlled and the real-time working data of the battery to be controlled, based on a preset temperature simulation model, thermal simulation processing can be performed according to the temperature structure data and the real-time working data to obtain the predicted temperature of the temperature monitoring point.

[0065] Among them, the preset temperature simulation model is a pre-trained deep neural network model for predicting the temperature of the temperature monitoring point of each battery under different working conditions. Among them, this application does not limit the training process of the preset temperature simulation model. Optionally, the historical working data of the battery and the historical temperature of the temperature monitoring point can be obtained first; then at least one preprocessing such as cleaning, normalizing, and denoising is performed on the obtained historical data; then training is performed based on the preprocessed historical data to obtain the preset temperature simulation model.

[0066] Specifically, this application does not limit the process of performing thermal simulation processing on the predicted temperature of the temperature monitoring points based on a preset temperature simulation model according to temperature structure data and real-time working data. Optionally, based on the preset temperature simulation model, basis function value generation processing can be performed according to temperature structure data and real-time working data to obtain the basis function value corresponding to the heat source reference center point; based on the preset temperature simulation model, calculation processing is performed on the basis function values corresponding to each heat source reference center point to obtain the predicted temperature of the temperature monitoring points.

[0067] Step S103: Determine the temperature control parameter of the battery to be controlled according to the predicted temperature of the temperature monitoring point, and perform temperature control processing on the battery to be controlled based on the determined temperature control parameter.

[0068] Specifically, after obtaining the predicted temperature of the temperature monitoring point, the temperature control parameter of the battery to be controlled can be determined according to the predicted temperature of the temperature monitoring point.

[0069] Among them, the temperature control parameter refers to the parameter for performing temperature control processing on the battery to be controlled. Optionally, the temperature control parameter characterizes the working intensity of performing temperature control processing on the battery to be controlled. For example, the larger the temperature control parameter, the greater the working intensity of performing temperature control processing on the battery to be controlled, and the smaller the temperature control parameter, the smaller the working intensity of performing temperature control processing on the battery to be controlled.

[0070] Specifically, this application does not limit the process of determining the temperature control parameter of the battery to be controlled according to the predicted temperature of the temperature monitoring point. Optionally, the temperature control type of the battery to be controlled can be determined, and the parameter adjustment coefficient corresponding to the temperature control type can be obtained; based on the predicted temperature of the temperature monitoring point and the parameter adjustment coefficient, the temperature control parameter of the battery to be controlled is determined.

[0071] Specifically, after determining the temperature control parameter of the battery to be controlled according to the predicted temperature of the temperature monitoring point, temperature control processing can be performed on the battery to be controlled based on the determined temperature control parameter. Optionally, if the process of determining the temperature control parameter of the battery to be controlled according to the predicted temperature of the temperature monitoring point is as shown above, then performing temperature control processing on the battery to be controlled based on the determined temperature control parameter can be to perform temperature control processing of the corresponding temperature control type on the battery to be controlled based on the determined temperature control parameter to ensure the safety of the operation of the battery to be controlled.

[0072] The temperature control method for lithium iron phosphate batteries provided by the embodiments of the present application obtains the temperature structure data of the battery to be controlled and the real-time working data of the battery to be controlled. Based on a preset temperature simulation model, thermal simulation processing is performed according to the temperature structure data and the real-time working data to obtain the predicted temperature of the temperature monitoring points. According to the predicted temperature of the temperature monitoring points, the temperature control parameters of the battery to be controlled are determined, and temperature control processing is performed on the battery to be controlled based on the determined temperature control parameters. Among them, predicting the battery temperature based on a preset temperature simulation model and performing temperature control based on the predicted temperature improves the accuracy and efficiency of temperature control, thereby improving the operating safety of the battery. Among them, during the process of predicting the battery temperature, predicting the temperature of the pre-calibrated temperature monitoring points improves the efficiency and accuracy of temperature prediction, thereby improving the accuracy and efficiency of temperature control and further improving the operating safety of the battery. Based on the above description, the temperature control method for lithium iron phosphate batteries provided by the embodiments of the present application improves the operating safety of the battery.

[0073] Figure 2 Schematic flow of the temperature control method for lithium iron phosphate batteries provided by the present application Figure 2 , such as Figure 2 shown. On the basis of the Figure 1 embodiment, a detailed description is given of performing thermal simulation processing based on a preset temperature simulation model according to temperature structure data and real-time working data to obtain the predicted temperature of the temperature monitoring points. The method includes:

[0074] Step S201: Based on a preset temperature simulation model, perform basis function value generation processing according to temperature structure data and real-time working data to obtain the basis function value corresponding to the heat source reference center point.

[0075] Specifically, based on a preset temperature simulation model, basis function value generation processing can be performed according to temperature structure data and real-time working data to obtain the basis function value corresponding to the heat source reference center point.

[0076] Among them, the description of the temperature result data can refer to the description in step S101 and will not be elaborated here. Optionally, the temperature structure data includes the position data of at least one heat source reference center point of the battery to be controlled.

[0077] Among them, the heat source reference center point is a pre-calibrated center point that generates heat during the operation of the battery to be controlled. Specifically, the heat source reference center is a virtual point or area used to describe the internal heat source distribution and heat transfer in the battery. In battery thermal management, understanding the location and characteristics of the heat source reference center is of great significance for optimizing the battery heat dissipation design and improving battery performance and safety. Among them, the location of the heat source reference center is usually determined according to the internal heat distribution and transfer conditions of the battery. It may be located in the core area of the battery or may be offset due to the influence of structures such as the positive and negative electrode tabs. Among them, the core heat source is the main heat source inside the battery, which mainly comes from the chemical reactions inside the battery. During the battery discharge process, the positive and negative active materials undergo oxidation-reduction reactions, releasing energy and generating heat. In addition, the electrolyte also generates a certain amount of heat during the process of conducting ions. Among them, for the heat source of the positive and negative electrode tabs, the positive and negative electrode tabs are metal sheet structures connecting the internal and external circuits of the battery. Although they are affected by the current collection effect and have a large current flowing through them, compared with the core heat source, the heat generated by them is relatively small. However, in battery design and thermal management, the heat source of the positive and negative electrode tabs cannot be ignored because they may directly affect the heat dissipation effect and temperature distribution of the battery.

[0078] Among them, this application does not limit the pre-calibration process of the heat source reference center. Optionally, the position of the heat source reference center can be accurately determined through pre-calibration processes such as experimental measurement and simulation analysis.

[0079] Among them, the basis function is an important concept in mathematics, especially playing a key role in function spaces, numerical analysis, and approximation theory. The following is a detailed explanation of the concept of the basis function:

[0080] Among them, the definition of the basis function is: The basis function is a set of special basis elements in the function space. In the function space, each continuous function can be expressed as a linear combination of basis functions, just as in the vector space, each vector can be expressed as a linear combination of basic vectors.

[0081] Among them, the characteristics of the basis function are: Linear combination: Continuous functions in the function space can be expressed as linear combinations of basis functions, which is the basic characteristic of the basis function. Interpolation application: In numerical analysis and approximation theory, basis functions are usually applied in interpolation and are therefore also called blending functions. By combining basis functions, an interpolation function can be constructed to approximate or fit given data points. Diversity: The forms of basis functions are diverse and can be polynomial functions, trigonometric functions, exponential functions, logarithmic functions, etc., depending on the nature of the function space and the type of function to be approximated.

[0082] Among them, examples of basis functions are as follows: Polynomial basis: For example, {1, t, t^2} is the basis of the set of real - coefficient quadratic polynomials. Every quadratic polynomial of the form a + bt + ct^2 can be written as a linear combination composed of the basis functions 1, t, and t^2. In addition, {(t - 1)(t - 2) / 2, -t(t - 2), t(t - 1) / 2} is another set of bases for quadratic polynomials, called the Lagrange basis; Fourier basis: Cosine functions form an (orthogonal) Schauder basis for square - integrable functions. In the field of signal processing, the Fourier transform gives a set of bases, and it is required to find the combination coefficients for linearly combining each basis to form this signal (function), or in other words, the coordinates in this set of bases; Radial basis function: Radial basis functions are functions used for surface fitting (approximation) in high - dimensional spaces. They provide a method for accurate interpolation and can generate smooth surfaces based on a large number of data points.

[0083] Among them, basis functions have extensive applications in many fields such as mathematics, physics, engineering, and economics. In the field of mathematics, they can be used to study the properties of functions, construct, and represent other more complex functions. In physics and engineering, basis functions can be used to describe the variation laws of basic physical quantities, analyze the responses and variation trends of physical systems. In the field of economics, basis functions can also be used to study the variation laws and interrelationships of economic variables.

[0084] In summary, basis functions are a set of basic elements in function spaces. Through their linear combinations, continuous functions in function spaces can be represented. Basis functions have important applications in numerical analysis and approximation theory and are key tools for problems such as interpolation, function approximation, and surface fitting.

[0085] Among them, the basis functions provided in the embodiments of this application are used to represent the influence of temperature structure data and implementation work data on the battery temperature. Among them, the basis function value corresponding to the heat source reference center point is used to represent the influence of temperature structure data and implementation work data corresponding to one of the at least one heat source reference center in the battery on the battery temperature.

[0086] Therefore, in the process of generating basis function values based on a preset temperature simulation model according to temperature structure data and real - time work data, and obtaining the basis function values corresponding to the heat source reference center points, the number of obtained basis function values corresponds to the number of heat source reference center lines.

[0087] Specifically, this application does not limit the process of generating basis function values based on a preset temperature simulation model according to temperature structure data and real - time work data to obtain the basis function values corresponding to the heat source reference center points.

[0088] Optionally, the temperature structure data further includes the size data of the battery. The real-time working data includes the working current data and the ambient temperature data.

[0089] Based on a preset temperature simulation model, the process of generating the basis function value according to the temperature structure data and the real-time working data to obtain the basis function value corresponding to the heat source reference center point may include:

[0090] Based on a preset temperature simulation model, calculate and process the position data of the temperature monitoring point and the position data of the heat source reference center point to obtain the heat diffusion parameter.

[0091] Based on a preset temperature simulation model, process the size data of the battery to obtain the heat distribution parameter.

[0092] Based on a preset temperature simulation model, calculate and process the working current data and the ambient temperature data to obtain the heat fluctuation parameter.

[0093] Based on a preset temperature simulation model, calculate and process the heat diffusion parameter, the heat distribution parameter and the heat fluctuation parameter to obtain the basis function value corresponding to the heat source reference center point.

[0094] Specifically, the size data of the battery is a series of parameters used to describe the physical size of the battery. Optionally, if the battery is a cylindrical battery, the size data of the battery includes, but is not limited to, parameters such as diameter (D) and height (H). Optionally, if the battery is a non-cylindrical battery, the size data of the battery includes, but is not limited to, parameters such as length (L), width (W) and thickness (T).

[0095] Specifically, the working current data of the battery refers to the charging and discharging current of the battery, and the ambient temperature data of the battery refers to the temperature of the environment where the battery is located during operation. Among them, the description of the charging and discharging current and the ambient temperature of the battery can refer to the description in step S101, which will not be elaborated here.

[0096] Optionally, the formula for generating the basis function value provided in the embodiment of the present application is as follows:

[0097]

[0098] Among them, f i (x,t) represents the basis function value corresponding to the i-th heat source reference center point, x represents the position of the temperature monitoring point of the battery to be controlled, t represents the current time, and x i represents the position of the i-th heat source reference center point.

[0099] Among them, x - x iDenote the heat diffusion parameter. Specifically, the heat diffusion parameter is characterized by the distance between the position of the temperature monitoring point of the battery to be controlled and the position of the reference center point of the i-th heat source.

[0100] Among them, the standard deviation σ represents the heat distribution parameter. Among them, the smaller the working area of the battery, the smaller the heat distribution range. At this time, the heat distribution parameter, that is, the standard deviation, will be smaller.

[0101] Among them, Denote the heat fluctuation parameter, which is a sine function, indicating that during the operation of the battery, such as during the charging or discharging process, the heat will fluctuate with time. Specifically, w i Denote the frequency of heat fluctuation caused by the current change during the charging and discharging process of the battery. Among them, w i = w0·(1 + K I ·|I(t)|), where w0 is the initial frequency, K I is the influence coefficient of the current on the frequency, and I(t) is the charging and discharging current at time t. Specifically, Denote the frequency of heat fluctuation caused by the ambient temperature during the charging and discharging process of the battery. Among them, Among them, T i is the ambient temperature at time t, T0 is the initial ambient temperature, and k T denotes the influence coefficient of the temperature on the phase.

[0102] Among them, formula (1) represents the process of calculating and processing the heat diffusion parameter, the heat distribution parameter, and the heat fluctuation parameter based on a preset temperature simulation model to obtain the basis function value corresponding to the reference center point of the heat source.

[0103] Among them, in the process of generating the basis function value corresponding to the reference center point of the heat source based on a preset temperature simulation model according to the temperature structure data and the real-time working data, in addition to considering the influence of the heat diffusion of the reference center of the heat source on the temperature monitoring point, it also focuses on considering the influence of the heat distribution corresponding to the battery size data in the working data on the temperature monitoring point, and the influence of the heat fluctuation corresponding to the working current data and the ambient temperature data in the working data on the temperature monitoring point, improving the accuracy and efficiency of determining the basis function value, thereby improving the accuracy of the predicted temperature of the temperature monitoring point and further improving the operating safety of the battery.

[0104] Step S202: Based on a preset temperature simulation model, calculate and process the basis function values corresponding to each reference center point of the heat source to obtain the predicted temperature of the temperature monitoring point.

[0105] Specifically, based on a preset temperature simulation model, the basis function values corresponding to the reference center points of each heat source calculated in step S201 can be calculated and processed to obtain the predicted temperature of the temperature monitoring point.

[0106] Among them, the formula for calculating and processing the basis function values corresponding to the reference center points of each heat source to obtain the predicted temperature of the temperature monitoring point provided by the embodiment of the present application is as follows:

[0107]

[0108] Among them, T pred represents the predicted temperature of the temperature monitoring point of the battery to be controlled, and f i (x,t) represents the basis function value corresponding to the i-th heat source reference center point, and its specific description can refer to the description in step S201 and will not be elaborated here. Among them, N represents the number of basis function values, that is, the number of basis function values corresponding to the heat source reference center point, ∈ is the error term, representing the prediction error of the model, and α i represents the weight coefficient associated with the basis function value corresponding to the heat source reference center point.

[0109] Among them, formula (2) represents the process of calculating and processing the basis function values corresponding to the reference center points of each heat source to obtain the predicted temperature of the temperature monitoring point.

[0110] The process of obtaining the predicted temperature of the temperature monitoring point by performing thermal simulation processing on the temperature structure data and real-time working data based on the preset temperature simulation model provided by the embodiment of the present application includes generating basis function values corresponding to the heat source reference center points by performing basis function value generation processing on the temperature structure data and real-time working data based on the preset temperature simulation model, and calculating and processing the basis function values corresponding to the reference center points of each heat source based on the preset temperature simulation model to obtain the predicted temperature of the temperature monitoring point. Among them, in the process of obtaining the predicted temperature of the temperature monitoring point based on the preset temperature simulation model, the influence of each heat source reference center of the battery to be controlled on the temperature monitoring point is considered respectively, which can improve the accuracy of the thermal simulation processing, thereby improving the accuracy of the predicted temperature and further improving the safety of the battery operation.

[0111] Figure 3 is the flowchart of the temperature control method for the lithium iron phosphate battery provided by the present application Figure 3 , as Figure 3 shown, on the basis of the Figure 1 or Figure 2 embodiment, the temperature control parameters of the battery to be controlled are determined in detail according to the predicted temperature of the temperature monitoring point. The method includes:

[0112] Step S301: Determine the temperature control type of the battery to be controlled and obtain the parameter adjustment coefficient corresponding to the temperature control type.

[0113] Specifically, it is possible to determine the temperature control type of the battery to be controlled and obtain the parameter adjustment coefficient corresponding to the temperature control type.

[0114] Among them, the temperature control type refers to the type of temperature control for the battery to be controlled. Optionally, the temperature control type includes at least one of a liquid cooling type, an air cooling type, a direct cooling type, and a thermoelectric cooling type.

[0115] Specifically, the liquid cooling type means that the heat of the battery is taken away by using a circulating coolant (usually water or a water-containing mixture) to achieve efficient cooling; the air cooling type means that the heat of the battery is taken away by air flow to achieve cooling; the refrigeration cooling type means that a refrigerant is used to efficiently absorb heat through a phase change process to achieve rapid cooling of the battery; the thermoelectric cooling type means that based on the thermoelectric effect, the heat effect generated by an electric current on a thermocouple is used to achieve refrigeration or heating.

[0116] Among them, by setting multiple temperature control types, the comprehensiveness of the battery temperature control can be improved, thereby improving the operating safety of the battery.

[0117] Among them, the parameter adjustment coefficient is the adjustment coefficient for determining the temperature control parameters of the battery to be controlled. Specifically, when the temperature control types of the battery to be controlled are different, the corresponding temperature control parameters are different, and therefore, the corresponding parameter adjustment coefficients are also different.

[0118] Optionally, after determining the temperature control type of the battery to be controlled, the parameter adjustment coefficient corresponding to the temperature control type can be determined according to a preset mapping relationship. Among them, the preset mapping relationship represents the corresponding relationship between the temperature control type and the parameter adjustment coefficient.

[0119] Step S302: Determine the temperature control parameters of the battery to be controlled based on the predicted temperature of the temperature monitoring point and the parameter adjustment coefficient.

[0120] Specifically, after determining the parameter adjustment coefficient, the temperature control parameters of the battery to be controlled can be determined based on the predicted temperature of the temperature monitoring point and the parameter adjustment coefficient.

[0121] Among them, the temperature control parameter refers to the control parameter in the process of performing temperature control of the corresponding temperature control type on the battery to be controlled. For example, if the temperature control type is a liquid cooling type or an air cooling type, the temperature control parameter can be a control parameter related to the working intensity. For example, if the temperature control type is a thermoelectric cooling type, the temperature control parameter can be a control parameter related to the magnitude of the current.

[0122] Optionally, the temperature control adjustment parameter corresponding to the temperature control type may be determined first based on the predicted temperature of the temperature monitoring point and the parameter adjustment coefficient; then the initial temperature control parameter corresponding to the temperature control type is obtained; and then the sum of the initial temperature control parameter and the temperature control adjustment parameter is determined as the temperature control parameter of the battery to be controlled.

[0123] Optionally, in the process of determining the temperature control parameter of the battery to be controlled above, only the predicted temperature of the temperature monitoring point of the battery to be controlled itself is considered. However, during the use of the battery, a battery pack usually includes at least one battery. Therefore, if a battery pack includes multiple batteries, then in the process of determining the temperature control parameter of the battery to be controlled, the predicted temperatures of the temperature monitoring points of the batteries in the battery pack need to be considered, so as to improve the accuracy of determining the temperature control parameter.

[0124] Among them, the formula for determining the temperature control adjustment parameter corresponding to the temperature control type based on the predicted temperature of the temperature monitoring point and the parameter adjustment coefficient provided in the embodiments of the present application is as follows:

[0125]

[0126] Among them, ΔT represents the temperature control adjustment parameter, β represents the parameter adjustment coefficient, λ represents the attenuation coefficient, t0 and t1 represent the dynamically adjusted time intervals, represents the change rate of the predicted temperature of the temperature monitoring point of the battery to be controlled. Among them, M represents the number of batteries in the battery pack, and j represents the jth battery.

[0127] Among them, if M is 1, the corresponding formula (3) is the formula for determining the temperature control adjustment parameter corresponding to the temperature control type based on the predicted temperature of the temperature monitoring point and the parameter adjustment coefficient when there is one battery in the battery pack.

[0128] In the process of determining the temperature control parameter of the battery to be controlled provided in the embodiments of the present application, by determining the temperature control type of the battery to be controlled and obtaining the parameter adjustment coefficient corresponding to the temperature control type, and based on the predicted temperature of the temperature monitoring point and the parameter adjustment coefficient, the temperature control parameter of the battery to be controlled is determined. Among them, in the process of determining the temperature control parameter of the battery to be controlled, considering the temperature control type of the battery to be controlled can improve the accuracy of determining the temperature control parameter, further improve the accuracy of temperature control based on the temperature control parameter, and thus improve the operation safety of the battery.

[0129] In a possible embodiment, the temperature control method for lithium iron phosphate batteries further includes:

[0130] Based on a preset temperature simulation model, obtain the predicted temperatures of the temperature monitoring points of the other batteries included in the battery pack where the battery to be controlled is located.

[0131] Based on the predicted temperatures of the temperature monitoring points of the other batteries and the predicted temperature of the temperature monitoring point of the battery to be controlled, determine the thermal runaway probability of the battery to be controlled.

[0132] If the thermal runaway probability is greater than a preset thermal runaway probability threshold, perform thermal runaway temperature control processing on the battery to be controlled.

[0133] Specifically, based on a preset temperature simulation model, to obtain the predicted temperatures of the temperature monitoring points of the other batteries included in the battery pack where the battery to be controlled is located, reference can be made to Figure 1 and Figure 2 the description of the process of obtaining the predicted temperature of the temperature monitoring point of the battery to be controlled in the embodiments shown, which will not be elaborated here.

[0134] Among them, the formula for determining the thermal runaway probability of the battery to be controlled based on the predicted temperatures of the temperature monitoring points of the other batteries and the predicted temperature of the temperature monitoring point of the battery to be controlled is as follows:

[0135]

[0136] Among them, P represents the thermal runaway probability of the battery to be controlled, γ is the weight of the temperature monitoring point of the battery to be controlled, and T safe represents the safety temperature threshold of the battery. Among them, this application does not limit the safety temperature threshold of the battery. Optionally, it can be the temperature threshold to ensure the safe operation of the battery, for example, 50 °C.

[0137] Specifically, if the calculated thermal runaway probability of the battery to be controlled is greater than the preset thermal runaway probability threshold, it is determined that the battery to be controlled has a risk of thermal runaway. At this time, if the temperature control processing described in the above embodiments is continued, the risk of thermal runaway of the battery to be controlled may not be effectively reduced to ensure the safe operation of the battery. Therefore, thermal runaway temperature control processing needs to be performed on the battery to be controlled to ensure that the battery to be controlled no longer has a risk of thermal runaway.

[0138] Specifically, if the calculated thermal runaway probability of the battery to be controlled is less than or equal to the preset thermal runaway probability threshold, it is determined that the battery to be controlled has no risk of thermal runaway, and then continue the temperature control processing described in the above embodiments.

[0139] Among them, during the temperature control process of the lithium iron phosphate battery, it is determined whether the battery to be controlled has a risk of thermal runaway by calculating the thermal runaway probability of the battery to be controlled. When it is determined that the battery to be controlled has a risk of thermal runaway, thermal runaway temperature control treatment is performed on the battery to be controlled to improve the safety of the battery operation. Among them, during the process of determining the thermal runaway probability of the battery to be controlled, the influence of each battery in the battery pack is considered, which improves the efficiency and accuracy of determining the thermal runaway probability of the battery to be controlled, and further improves the safety of the battery operation.

[0140] In a possible embodiment, performing thermal runaway temperature control treatment on the battery to be controlled includes at least one of the following:

[0141] Controlling the battery pack where the battery to be controlled is located to perform a work shutdown process.

[0142] Determine the temperature control type of the battery to be controlled, and obtain the thermal runaway temperature control parameters corresponding to the temperature control type. Then, based on the thermal runaway temperature control parameters, perform temperature control treatment on the battery pack where the battery to be controlled is located.

[0143] Generate and present a thermal runaway warning prompt message.

[0144] Specifically, controlling the battery pack where the battery to be controlled is located to perform a work shutdown process can avoid the continuous temperature rise of the battery to be controlled caused by the continuous operation of the battery, and reduce the risk of thermal runaway.

[0145] Among them, the description of the temperature control type can refer to the description in the above embodiment and will not be elaborated here. Specifically, the thermal runaway temperature control parameters refer to the parameters for controlling the temperature of the battery to be controlled in the case of thermal runaway. Among them, the process of obtaining the thermal runaway temperature control parameters corresponding to the temperature control type in this application is not limited. Optionally, the corresponding thermal runaway temperature control parameters can be determined according to the temperature control type, the predicted temperature of the temperature monitoring point, and the preset mapping relationship. Here, the preset mapping relationship represents the corresponding relationship between the temperature control type and the predicted temperature of the temperature monitoring point and the thermal runaway temperature control parameters. Generally, when the temperature control type and the predicted temperature of the temperature monitoring point are the same, the determined thermal runaway temperature control parameters will be greater than the determined temperature control parameters to achieve the effect of reducing the risk of thermal runaway.

[0146] Specifically, the thermal runaway warning prompt message is used to prompt the maintenance personnel to check the battery to be controlled to reduce the risk of thermal runaway of the battery to be controlled.

[0147] Among them, during the process of performing thermal runaway temperature control treatment on the battery to be controlled, through at least one method, the efficiency and accuracy of the thermal runaway temperature control treatment can be improved, thereby improving the safety of the battery operation.

[0148] Figure 4 The structural schematic diagram of the temperature control device for the lithium iron phosphate battery provided by this application is as follows Figure 4 shown. The temperature control device 40 for the lithium iron phosphate battery provided in this embodiment includes:

[0149] An acquisition module 401, configured to acquire the temperature structure data of the battery to be controlled and acquire the real-time working data of the battery to be controlled; wherein, the temperature structure data includes the position data of the temperature monitoring points of the battery to be controlled; wherein, the temperature monitoring points are pre-calibrated monitoring points for temperature control of the battery to be controlled;

[0150] A processing module 402, configured to perform thermal simulation processing based on a preset temperature simulation model according to the temperature structure data and the real-time working data to obtain the predicted temperature of the temperature monitoring points;

[0151] A control module 403, configured to determine the temperature control parameters of the battery to be controlled according to the predicted temperature of the temperature monitoring points, and perform temperature control processing on the battery to be controlled based on the determined temperature control parameters.

[0152] In a possible embodiment, the temperature structure data includes the position data of at least one heat source reference center point of the battery to be controlled; wherein, the heat source reference center point is a pre-calibrated center point that generates heat during the operation of the battery to be controlled; the processing module 402 is specifically configured to perform basis function value generation processing based on a preset temperature simulation model according to the temperature structure data and the real-time working data to obtain the basis function value corresponding to the heat source reference center point; based on the preset temperature simulation model, perform calculation processing on the basis function values corresponding to each heat source reference center point to obtain the predicted temperature of the temperature monitoring points.

[0153] In a possible embodiment, the temperature structure data further includes the size data of the battery; the real-time working data includes the working current data and the ambient temperature data; the processing module 402 is further specifically configured to perform calculation processing on the position data of the temperature monitoring points and the position data of the heat source reference center point based on a preset temperature simulation model to obtain a heat diffusion parameter; perform processing on the size data of the battery based on the preset temperature simulation model to obtain a heat distribution parameter; perform calculation processing on the working current data and the ambient temperature data based on the preset temperature simulation model to obtain a heat fluctuation parameter; perform calculation processing on the heat diffusion parameter, the heat distribution parameter, and the heat fluctuation parameter based on the preset temperature simulation model to obtain the basis function value corresponding to the heat source reference center point.

[0154] In a possible embodiment, the control module 403 is specifically configured to determine the temperature control type of the battery to be controlled and obtain the parameter adjustment coefficient corresponding to the temperature control type; and determine the temperature control parameter of the battery to be controlled based on the predicted temperature of the temperature monitoring point and the parameter adjustment coefficient.

[0155] In a possible embodiment, the temperature control type includes at least one of: liquid cooling type, air cooling type, direct cooling type, and hot spot cooling type.

[0156] In a possible embodiment, the control module 403 is further configured to obtain the predicted temperatures of the temperature monitoring points of the other batteries included in the battery pack where the battery to be controlled is located based on a preset temperature simulation model; determine the thermal runaway probability of the battery to be controlled based on the predicted temperatures of the temperature monitoring points of the other batteries and the predicted temperature of the temperature monitoring point of the battery to be controlled; and if the thermal runaway probability is greater than a preset thermal runaway probability threshold, perform thermal runaway temperature control processing on the battery to be controlled.

[0157] In a possible embodiment, the control module 403 is further specifically configured to perform at least one of the following: control the battery pack where the battery to be controlled is located to perform a shutdown process; determine the temperature control type of the battery to be controlled and obtain the thermal runaway temperature control parameter corresponding to the temperature control type; then perform temperature control processing on the battery pack where the battery to be controlled is located based on the thermal runaway temperature control parameter; generate and present a thermal runaway warning prompt message.

[0158] The temperature control device for the lithium iron phosphate battery provided in this embodiment can execute the method provided in the above method embodiment, and its implementation principle and technical effect are similar, which will not be elaborated here in this embodiment.

[0159] Figure 5 It is a schematic structural diagram of an electronic device provided in this application. As Figure 5 shown, the electronic device 50 provided in this embodiment includes: at least one processor 501 and a memory 502. Optionally, the device 50 further includes a communication component 503. Among them, the processor 501, the memory 502, and the communication component 503 are connected through a bus 504.

[0160] In a specific implementation process, at least one processor 501 executes the computer execution instructions stored in the memory 502, so that at least one processor 501 executes the above method.

[0161] The specific implementation process of the processor 501 can refer to the above method embodiment, and its implementation principle and technical effect are similar, which will not be elaborated here in this embodiment.

[0162] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU for short), or may also be other general-purpose processors, digital signal processors (DSP for short), application specific integrated circuits (ASIC for short), etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the method disclosed in combination with the invention can be directly implemented by the execution of the hardware processor, or can be implemented by the combination of the hardware and software modules in the processor.

[0163] The memory may include a random access memory (RAM), and may also include a non-volatile memory (NVM), such as at least one disk memory.

[0164] The bus may be an industry standard architecture (ISA) bus, a peripheral component interconnect (PCI) bus, an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0165] This application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0166] This application also provides a computer-readable storage medium, in which computer-executable instructions are stored, and when the processor executes the computer-executable instructions, the above method is implemented.

[0167] The above-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as a static random access memory (SRAM), an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a programmable read-only memory (PROM), a read-only memory (ROM), a magnetic memory, a flash memory, a magnetic disk or an optical disk. The readable storage medium can be any available medium accessible by a general-purpose or special-purpose computer.

[0168] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an Application Specific Integrated Circuits (ASIC). Of course, the processor and the readable storage medium can also exist as discrete components in a device.

[0169] The division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Additionally, the couplings or direct couplings or communication connections shown or discussed between each other can be indirect couplings or communication connections through some interfaces, devices or units, and can be in electrical, mechanical or other forms.

[0170] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0171] In addition, in each embodiment of the present invention, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0172] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs that can store program codes.

[0173] Those of ordinary skill in the art will understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments; and the aforementioned storage medium includes: various media such as ROM, RAM, magnetic disks, or optical discs that can store program codes.

[0174] Finally, it should be noted that those skilled in the art will readily conceive of other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses, or adaptations of the present invention, which follow the general principles of the present invention and include known common knowledge or conventional technical means in the technical field not disclosed by the present invention. It is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is only limited by the appended claims.

Claims

1. A temperature control method for a lithium iron phosphate battery, characterized in that, Including: Obtain the temperature structure data of the battery to be controlled, and obtain the real-time working data of the battery to be controlled; wherein, the temperature structure data includes the position data of the temperature monitoring points of the battery to be controlled; wherein, the temperature monitoring points are pre-calibrated monitoring points for temperature control of the battery to be controlled; Based on a preset temperature simulation model, perform thermal simulation processing according to the temperature structure data and the real-time working data to obtain the predicted temperature of the temperature monitoring points; According to the predicted temperature of the temperature monitoring points, determine the temperature control parameters of the battery to be controlled, and perform temperature control processing on the battery to be controlled based on the determined temperature control parameters.

2. The method according to claim 1, characterized in that, The temperature structure data includes the position data of at least one heat source reference center point of the battery to be controlled; wherein, the heat source reference center point is a pre-calibrated center point that generates heat during the operation of the battery to be controlled; Based on a preset temperature simulation model, performing thermal simulation processing according to the temperature structure data and the real-time working data to obtain the predicted temperature of the temperature monitoring points includes: Based on a preset temperature simulation model, perform basis function value generation processing according to the temperature structure data and the real-time working data to obtain the basis function values corresponding to the heat source reference center points; Based on a preset temperature simulation model, perform calculation processing on the basis function values corresponding to each heat source reference center point to obtain the predicted temperature of the temperature monitoring points.

3. The method according to claim 2, wherein The temperature structure data further includes the size data of the battery; the real-time working data includes working current data and ambient temperature data; Based on a preset temperature simulation model, performing basis function value generation processing according to the temperature structure data and the real-time working data to obtain the basis function values corresponding to the heat source reference center points includes: Based on a preset temperature simulation model, perform calculation processing on the position data of the temperature monitoring points and the position data of the heat source reference center points to obtain a heat diffusion parameter; Based on a preset temperature simulation model, process the size data of the battery to obtain a heat distribution parameter; Based on a preset temperature simulation model, perform calculation processing on the working current data and the ambient temperature data to obtain a heat fluctuation parameter; Based on a preset temperature simulation model, perform calculation processing on the heat diffusion parameter, the heat distribution parameter, and the heat fluctuation parameter to obtain the basis function values corresponding to the heat source reference center points.

4. The method according to claim 1, wherein According to the predicted temperature of the temperature monitoring points, determining the temperature control parameters of the battery to be controlled includes: Determine the temperature control type of the battery to be controlled, and obtain the parameter adjustment coefficient corresponding to the temperature control type; Based on the predicted temperature of the temperature monitoring points and the parameter adjustment coefficient, determine the temperature control parameters of the battery to be controlled.

5. The method according to claim 4, wherein The temperature control type includes at least one of a liquid cooling type, an air cooling type, a direct cooling type, and a hot spot cooling type.

6. The method according to any one of claims 1-5, characterized in that, The method further includes: Based on a preset temperature simulation model, obtain the predicted temperatures of the temperature monitoring points of the other batteries included in the battery pack where the battery to be controlled is located; Determine the thermal runaway probability of the battery to be controlled based on the predicted temperatures of the temperature monitoring points of the other batteries and the predicted temperature of the temperature monitoring point of the battery to be controlled; If the thermal runaway probability is greater than a preset thermal runaway probability threshold, perform thermal runaway temperature control processing on the battery to be controlled.

7. The method according to claim 6, characterized in that, Performing thermal runaway temperature control processing on the battery to be controlled includes at least one of the following: Control the battery pack where the battery to be controlled is located to perform a shutdown process; Determine the temperature control type of the battery to be controlled, and obtain the thermal runaway temperature control parameters corresponding to the temperature control type; then perform temperature control processing on the battery pack where the battery to be controlled is located based on the thermal runaway temperature control parameters; Generate and present a thermal runaway warning prompt message.

8. A temperature control device for a lithium iron phosphate battery, characterized in that, Including: An acquisition module, configured to acquire the temperature structure data of the battery to be controlled and acquire the real-time working data of the battery to be controlled; wherein, the temperature structure data includes the position data of the temperature monitoring points of the battery to be controlled; wherein, the temperature monitoring points are pre-calibrated monitoring points for temperature control of the battery to be controlled; A processing module, configured to perform thermal simulation processing based on a preset temperature simulation model according to the temperature structure data and the real-time working data to obtain the predicted temperature of the temperature monitoring point; A control module, configured to determine the temperature control parameters of the battery to be controlled according to the predicted temperature of the temperature monitoring point, and perform temperature control processing on the battery to be controlled based on the determined temperature control parameters.

9. An electronic device, characterized in that, Including: A memory, a processor; The memory stores computer execution instructions; The processor executes the computer execution instructions stored in the memory, so that the processor executes the method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer execution instructions, and when the computer execution instructions are executed by a processor, they are used to implement the method according to any one of claims 1-7.

11. A computer program product, characterized in that, Including a computer program, which when executed by a processor implements the method according to any one of claims 1-7.

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