Power supply thermal management method, system and intelligent power supply

Abstract

The present application discloses a power supply thermal management method, system, and intelligent power supply. The method includes: collecting m reference temperature data sets of m battery cells within a first preset time period; performing preprocessing operations on the m reference temperature data sets to obtain m temperature data sets; determining a first temperature value of a target power supply based on the m temperature data sets; predicting a predicted temperature value of the target power supply at a target time based on the m temperature data sets and the first temperature value; determining a target operating state of the target power supply based on the first temperature value and the predicted temperature value; and controlling a thermal management module to perform thermal management on the target power supply within a second preset time period based on the first temperature value, the predicted temperature value, and the target operating state, so as to return the temperature of the target power supply to a preset temperature range. The embodiments of the present application can improve the thermal management effect of the power supply.

Description

Technical Field

[0001] The present application relates to the field of power management technology, and in particular to a power supply thermal management method and system, and an intelligent power supply. Background Art

[0002] With the continuous development of electronic devices, power supply, as a key component, has received more and more attention for its performance and reliability.

[0003] At present, traditional thermal management control algorithms usually only choose whether to perform thermal management on the power supply based on its current temperature. For example, if the power supply temperature is too high, it will be cooled. It is difficult to adjust the cooling strategy in real time and accurately according to changes in actual applications. This can easily lead to unstable temperature control and large temperature fluctuations, resulting in poor thermal management effect. Therefore, how to improve the thermal management effect of the power supply has become an urgent problem to be solved. Summary of the Invention

[0004] The embodiments of the present application provide a power supply thermal management method, system, and intelligent power supply, which can improve the thermal management effect of the power supply.

[0005] In a first aspect, an embodiment of the present application provides a power supply thermal management method, which is applied to a power supply thermal management device, wherein the power supply thermal management device includes: a target power supply and a thermal management module, wherein the target power supply includes m battery cells, where m is a positive integer, and the method includes:

[0006] Within a first preset time period, collecting a temperature data set of each of the m battery cells to obtain m reference temperature data sets;

[0007] Performing a preprocessing operation on the m reference temperature data sets to obtain m temperature data sets; the preprocessing operation includes at least one of the following: a data cleaning operation, a data conversion operation, and a data smoothing operation;

[0008] determining a first temperature value of the target power supply according to the m temperature data sets;

[0009] Predicting a predicted temperature value of the target power supply at a target time based on the m temperature data sets and the first temperature value; the target time is a time within a second preset time period; the start time of the second preset time period is later than the end time of the first preset time period;

[0010] Determining a target operating state of the target power supply according to the first temperature value and the predicted temperature value; the target operating state includes one of the following: a normal operating state, an overheated operating state, and an overcooled operating state;

[0011] During the second preset time period, the thermal management module is controlled to perform thermal management on the target power supply based on the first temperature value, the predicted temperature value, and the target operating state, so that the temperature of the target power supply returns to a preset temperature range.

[0012] In a second aspect, an embodiment of the present application provides a power supply thermal management system, which is applied to a power supply thermal management device. The power supply thermal management device includes: a target power supply and a thermal management module. The target power supply includes m battery cells, where m is a positive integer. The system includes: an acquisition unit, a control unit, and a thermal management unit, wherein:

[0013] The acquisition unit is configured to acquire a temperature data set of each of the m battery cells within a first preset time period to obtain m reference temperature data sets;

[0014] The control unit is configured to perform a preprocessing operation on the m reference temperature data sets to obtain m temperature data sets; the preprocessing operation includes at least one of the following: a data cleaning operation, a data conversion operation, and a data smoothing operation; determine a first temperature value of the target power supply based on the m temperature data sets; predict a predicted temperature value of the target power supply at a target time based on the m temperature data sets and the first temperature value; the target time is a time within a second preset time period; the start time of the second preset time period is later than the end time of the first preset time period; determine a target operating state of the target power supply based on the first temperature value and the predicted temperature value; the target operating state includes one of the following: a normal operating state, an overheated operating state, and an overcooled operating state;

[0015] The thermal management unit is configured to control the thermal management module to perform thermal management on the target power supply based on the first temperature value, the predicted temperature value, and the target operating state within the second preset time period, so as to return the temperature of the target power supply to a preset temperature range.

[0016] In a third aspect, the present application provides an intelligent power supply, comprising: a processor and a memory, wherein the memory is used to store one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the first aspect of the present application.

[0017] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute some or all of the steps described in the first aspect of the present application.

[0018] In a fifth aspect, the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, wherein the computer program is operable to cause a computer to perform some or all of the steps described in the first aspect of the present application. The computer program product may be a software installation package.

[0019] The implementation of this application has the following beneficial effects:

[0020] It can be seen that the thermal management method of the power supply described in the present application is applied to a power supply thermal management device, which includes: a target power supply, a thermal management module, and the target power supply includes m battery cells. The method includes: within a first preset time period, collecting a temperature data set of each of the m battery cells to obtain m reference temperature data sets; performing a preprocessing operation on the m reference temperature data sets to obtain m temperature data sets; determining a first temperature value of the target power supply based on the m temperature data sets; predicting a predicted temperature value of the target power supply at a target time based on the m temperature data sets and the first temperature value; determining a target operating state of the target power supply based on the first temperature value and the predicted temperature value; within a second preset time period, based on the first temperature value , predicted temperature value and target working state control thermal management module to perform thermal management on the target power supply so that the temperature of the target power supply returns to the preset temperature range. In this way, by adjusting the working mode and parameters of the thermal management module accordingly according to the first temperature value of the target power supply, the predicted temperature value and the temperature data sets of each of the m battery cells, a set of appropriate thermal management strategies are matched for different thermal states of the target power supply. Performing thermal management operations on the target power supply in this way can ensure the safety of the power supply, avoid dangerous situations such as thermal runaway caused by overheating, or battery performance degradation and shortened life due to overcooling, thereby improving the thermal management effect of the power supply thermal management device on the target power supply, and ensuring that the target power supply can operate stably and efficiently for a long time. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the background technology, the drawings required for use in the embodiments of the present application or the background technology will be described below.

[0022] Figure 1 This is a schematic structural diagram of a power supply thermal management device provided in an embodiment of the present application;

[0023] Figure 2 This is a flow chart of a thermal management method for a power supply provided in an embodiment of the present application;

[0024] Figure 3 This is a block diagram of the functional units of a thermal management system for a power supply provided in an embodiment of the present application;

[0025] Figure 4This is a schematic diagram of the structure of an intelligent power supply provided in an embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0027] The terms "first," "second," and the like in the specification and claims of this application and the accompanying drawings are used to distinguish between different objects, not to describe a particular order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0028] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0029] The following is an explanation of some professional terms involved in this application:

[0030] Battery Management System (BMS): A system that monitors the status of energy storage batteries (or power sources) and is used to manage and monitor the battery charging and discharging process. Its main function is to intelligently manage and maintain the battery, ensuring that the battery can provide stable and reliable performance throughout its life cycle, while maximizing the battery's service life.

[0031] See also Figure 1 , Figure 1This is a schematic diagram of the structure of a power supply thermal management device provided in an embodiment of the present application. It can be seen that the power supply thermal management device includes, in addition to: a target power supply and a thermal management module, a control module. The thermal management module may include at least one of the following: a fin assembly, an air cooling assembly, a liquid cooling assembly, a heating assembly, etc., which are not limited here; the control module may include one of the following: a battery management system, a programmable logic controller, a digital signal processor, etc., which are not limited here; wherein:

[0032] The target power supply provides power to the power thermal management device. Specifically, the target power supply can be a battery pack consisting of m cells, which provides power to external devices. Its performance and status directly impact the operation of the entire system. Different power sources (such as lithium-ion batteries and lead-acid batteries) have different characteristics, including energy density, charge and discharge efficiency, and operating temperature range. These characteristics determine the suitability of the power supply in different application scenarios.

[0033] The thermal management module regulates the target power supply's temperature to keep it within an appropriate range. This temperature regulation can be achieved in a variety of ways. For example, cooling can be achieved through air cooling (using a fan to move air over the power supply to remove heat) or liquid cooling (using a circulating coolant to absorb heat). Heating can be achieved through heating elements such as heating wires, heating plates, or heat exchangers.

[0034] The control module monitors various parameters of the target power supply, including but not limited to each cell's voltage, current, temperature, remaining charge, and health status. This monitoring data provides a precise understanding of the power supply's internal conditions. For example, by monitoring cell voltage changes, it can be determined whether the cell is overcharged, over-discharged, or has imbalances between individual cells. Temperature monitoring can promptly detect abnormalities such as local overheating.

[0035] See also Figure 2 , Figure 2 This is a flow chart of a power supply thermal management method provided in an embodiment of the present application. The method can be applied to a power supply thermal management device, the power supply thermal management device comprising: a target power supply and a thermal management module. The target power supply comprises m battery cells, where m is a positive integer. The method may comprise the following steps:

[0036] S201 . Within a first preset time period, collect a temperature data set of each of the m battery cells to obtain m reference temperature data sets.

[0037] In the embodiment of the present application, the first preset time period can be preset in advance or defaulted; the temperature acquisition device for obtaining the battery cell temperature can include at least one of the following: a temperature sensor, a thermistor, an infrared sensor, etc., which is not limited here.

[0038] In a specific embodiment, the above-mentioned power supply thermal management device may include a BMS, and the BMS may collect a temperature data set of each of the m battery cells to obtain m reference temperature data sets. Specifically, the temperature collection device may be a temperature sensor. By installing a temperature sensor in each battery cell, the temperature of the battery cell is directly measured using the temperature sensor. The BMS may read all output data of each temperature sensor within a first preset time period, classify these output data according to the data source, and obtain m reference temperature data sets.

[0039] S202 . Perform a preprocessing operation on the m reference temperature data sets to obtain m temperature data sets; the preprocessing operation includes at least one of the following: a data cleaning operation, a data conversion operation, and a data smoothing operation.

[0040] In an embodiment of the present application, a preprocessing operation can be performed on m reference temperature data sets to obtain m temperature data sets. Specifically, the preprocessing operation may include three operations: data cleaning operation, data conversion operation, and data smoothing operation. The data cleaning operation can be performed on the m reference temperature data sets first. Statistical methods can be used to calculate the mean and standard deviation of each reference temperature data set, and data points that exceed the mean ±n times the standard deviation (for example, n=3) are regarded as outliers and removed. Then, data conversion operations can be performed according to usage needs. For example, the m reference temperature data sets can be normalized or standardized. Finally, a data smoothing operation can be performed. The moving average method or exponential smoothing method can be used to smooth the m reference temperature data sets to obtain m temperature data sets.

[0041] S203 : Determine a first temperature value of the target power supply according to the m temperature data sets.

[0042] In the embodiment of the present application, the m temperature data sets may be analyzed and integrated to determine the overall temperature value of the target power supply, that is, the first temperature value.

[0043] Optionally, step S203, determining the first temperature value of the target power supply according to the m temperature data sets, may include the following steps:

[0044] A1. Determine a reference temperature value corresponding to each temperature data set in the m temperature data sets to obtain m reference temperature values;

[0045] A2. Obtain the shell type of each of the m battery cells to obtain m shell types;

[0046] A3. Determine a first thermal conductivity corresponding to each of the m shell types to obtain m first thermal conductivities;

[0047] A4. Determine a weight corresponding to each of the m first thermal conductivities to obtain m weights;

[0048] A5. Determine the first temperature value according to the m reference temperature values and the m weights.

[0049] In the embodiment of the present application, the shell type may include one of the following: steel shell, aluminum shell, aluminum-plastic film, etc., which is not limited here.

[0050] In a specific embodiment, a reference temperature value corresponding to each temperature data set in the m temperature data sets may be first determined to obtain m reference temperature values. Then, a shell type of each of the m battery cells may be obtained to obtain m shell types. Specifically, the shell type of each of the m battery cells may be directly queried from a preset database of the power supply thermal management device, thereby obtaining m shell types. Then, a first thermal conductivity corresponding to each of the m shell types may be determined to obtain m first thermal conductivities. For example, a preset mapping relationship between shell types and thermal conductivities may be pre-stored, and the m first thermal conductivities corresponding to the m shell types may be determined based on the mapping relationship. Furthermore, a weight corresponding to each of the m first thermal conductivities may be determined to obtain m weights. Similarly, a preset mapping relationship between the first thermal conductivities and weights may be pre-stored, and the m weights corresponding to the m first thermal conductivities may be determined based on the mapping relationship. The larger the first thermal conductivity, the smaller the corresponding weight. Finally, a weighted operation may be performed based on the m reference temperature values and the m weights to obtain the first temperature value.

[0051] By determining corresponding weights (m weights) based on different first thermal conductivities, personalized weight assignment is achieved for different cell temperature data, ensuring that the final first temperature value more accurately reflects the target power supply's temperature. This personalized assessment approach can provide more precise temperature control strategies for different cell types in the battery management system. For example, for cells with high weights (high thermal conductivity), their temperature changes can be more closely monitored to ensure safe and stable operation of the power supply.

[0052] Optionally, step A1, determining a reference temperature value corresponding to each of the m temperature data sets to obtain m reference temperature values, may include the following steps:

[0053] B1. Obtain a first temperature data set; the first temperature data set is any temperature data set among the m temperature data sets; the first temperature data set includes n temperature values; n is an integer greater than 1;

[0054] B2. Determine the target average temperature value corresponding to the n temperature values;

[0055] B3. When the target average temperature value is greater than a first preset temperature value, determining a reference temperature value corresponding to the first temperature data set according to the target average temperature value;

[0056] B4. When the target average temperature value is not greater than the first preset temperature value, obtaining a collection time of each of the n temperature values to obtain n collection times;

[0057] B5. Obtaining the difference between each of the n acquisition moments and the end moment of the first preset time period to obtain n differences;

[0058] B6. Determine the average difference corresponding to the n differences;

[0059] B7. Divide the first preset time period into k intervals according to the average difference, where k is an integer greater than 1;

[0060] B8. Based on the n acquisition moments, the n temperature values are classified into the k intervals;

[0061] B9. Determine a temperature value set in each of the k intervals to obtain k temperature value sets;

[0062] B10. Determine the average temperature value corresponding to each temperature value set in the k temperature value sets to obtain k average temperature values;

[0063] B11. Obtain a weight corresponding to each of the k intervals to obtain k weights, where the sum of the k weights is 1, and the weight of an interval closer to the start time of the first preset time period is smaller;

[0064] B12. Determine a reference temperature value corresponding to the first temperature data set according to the k weights and the k average temperature values.

[0065] In the embodiment of the present application, the first preset temperature value can be preset in advance or defaulted.

[0066] In a specific embodiment, a first temperature data set can be obtained first; then, the average value of these n temperature values, that is, the target average temperature value, is calculated; when the target average temperature value is greater than the first preset temperature value, the target average temperature value can be directly determined as the reference temperature value corresponding to the first temperature data set.

[0067] When the target average temperature value is not greater than the first preset temperature value, the collection time of each temperature value in the n temperature values can be obtained to obtain n collection times. Specifically, the BMS will automatically add a timestamp to each data point when collecting data, which records the exact time when the data is collected. Then, the n timestamps corresponding to the n temperature values can be obtained from the BMS database, that is, n collection times. Then, the difference between each collection time in these n collection times and the end time of the first preset time period can be calculated to obtain n differences. Then, the average difference of these n differences can be calculated. Furthermore, the first preset time period can be divided into k intervals of equal length according to the average difference. , k intervals are obtained. For example, assuming that the first preset time period is 12:00~12:05 and the average difference is 60 seconds, then the first preset time period can be divided into 5 segments (i.e. k=5), i.e. 5 intervals; then, the n temperature values can be placed into k intervals based on the n collection moments. Specifically, the above n collection moments can be placed into k intervals first, and then the temperature values corresponding to these n collection moments can be placed into k intervals. For example, assuming that a certain collection moment t1=12:03, t1 falls into the interval 12:02~12:03, then the temperature value corresponding to t1 also falls into the interval. In this way, after n cycles, the n temperature values can all fall into k intervals.

[0068] Next, the temperature value set in each of the k intervals can be determined to obtain k temperature value sets. Specifically, the temperature value falling in each of the k intervals can be obtained, and the temperature values in the same interval can be merged together to obtain k temperature value sets; then, the average temperature value corresponding to each temperature value set in the k temperature value sets can be calculated to obtain k average temperature values; further, the weight corresponding to each of the k intervals can be obtained to obtain k weights. Specifically, the mapping relationship between the preset intervals and the weights can be pre-stored, and the k weights corresponding to the k intervals can be determined based on the mapping relationship; finally, a weighted operation can be performed based on the k weights and the k average temperature values to obtain a reference temperature value corresponding to the first temperature data set.

[0069] Thus, the target average temperature value is first determined, which is a preliminary summary of the first temperature data set. When the target average temperature value is greater than the first preset temperature value, the reference temperature value is directly determined based on this value. In the case of high temperature, the focus is on the overall average temperature, because the high temperature has already suggested that the power supply and other equipment are in some special state (for example, overheating). At this time, the overall average temperature is sufficient to reflect its temperature characteristics. When the target average temperature value is not greater than the first preset temperature value, the first preset time period is divided into k intervals, and the temperature conditions of the power supply are analyzed in different time intervals to make the temperature assessment more refined, so as to discover potential temperature rise or fall trends in advance, and provide a basis for preventive measures, such as adjusting the working mode of the power supply in advance to avoid excessive temperature.

[0070] S204. Predicting a predicted temperature value of the target power supply at a target time based on the m temperature data sets and the first temperature value; the target time is a time within a second preset time period; the start time of the second preset time period is later than the end time of the first preset time period.

[0071] In the embodiment of the present application, the second preset time period can be preset in advance or defaulted.

[0072] In a specific embodiment, the predicted temperature value of the target power source at the target time is determined based on analysis and prediction of the m temperature data sets and the first temperature value.

[0073] Optionally, step S204, predicting the predicted temperature value of the target power source at the target time according to the m temperature data sets and the first temperature value, may include the following steps:

[0074] S41, fitting each of the m temperature data sets to obtain m temperature straight lines, wherein the abscissa is time and the ordinate is temperature value;

[0075] S42, determining m reference predicted temperature values corresponding to the target time according to the m temperature straight lines;

[0076] S43, determining a second temperature value according to the m reference predicted temperature values;

[0077] S44, obtaining a target internal resistance and a target operating current of the target power supply;

[0078] S45. Determine the amount of heat generated by the target power supply within a target duration based on the target internal resistance and the target operating current, to obtain a target amount of heat; the target duration is the duration from the end of the first preset time period to the target time;

[0079] S46, estimating a first temperature change value of the target power supply according to the target heat;

[0080] S47. Determine a third temperature value according to the first temperature change value and the first temperature value;

[0081] S48. Determine a target deviation between the second temperature value and the third temperature value;

[0082] S49. When the target deviation is not greater than a preset deviation, obtaining a first weight corresponding to the second temperature value and a second weight corresponding to the third temperature value; and determining the predicted temperature value based on the second temperature value, the third temperature value, the first weight, and the second weight.

[0083] S410, when the target deviation is greater than the preset deviation, obtaining the slope of each of the m temperature straight lines to obtain m slopes;

[0084] S411, determining a target slope corresponding to the m slopes;

[0085] S412, determining a second temperature change value according to the target slope and the target duration;

[0086] S413: Determine the predicted temperature value according to the second temperature change value and the first temperature value.

[0087] In the embodiment of the present application, the preset deviation can be preset in advance or defaulted.

[0088] In a specific embodiment, a preset fitting method can be used to fit each of the m temperature data sets to obtain m temperature lines. The preset fitting method can include one of the following: least squares method, polynomial fitting, Lagrange interpolation method, etc., which are not limited here. Then, m reference predicted temperature values corresponding to the target time can be determined based on the m temperature lines. Specifically, m straight line equations corresponding to the m temperature lines can be obtained. Then, the target time can be substituted into the m straight line equations to obtain m reference predicted temperature values. Then, a second temperature value can be determined based on the m reference predicted temperature values. Specifically, an average of the m reference predicted temperature values can be calculated and used as the second temperature value. Alternatively, the method for obtaining the second temperature value can be the same as the method for obtaining the first temperature value described above. Furthermore, a target internal resistance and a target operating current of the target power supply can be obtained. Specifically, the target internal resistance and the target operating current of the target power supply can be detected by a BMS. For example, a small-amplitude AC signal can be injected into the target power supply, and the target internal resistance can be calculated by measuring the voltage and current responses of the target power supply to the AC signal. Alternatively, the operating current can be directly measured by a current sensor connected in series with the target power supply to obtain the target operating current.

[0089] Furthermore, the heat generated by the target power supply within the target duration can be determined based on the target internal resistance and target operating current to obtain the target heat. Specifically, the target internal resistance, target operating current and target duration can be substituted into the heat calculation formula of Joule's law (Q=I 2 Rt, where Q is heat, I is operating current, R is resistance, and t is duration), to obtain the target heat. Then, the first temperature change value of the target power supply can be estimated based on the target heat. Specifically, the heat capacity of the target voltage can be first obtained, and the target heat can be divided by the heat capacity to obtain the first temperature change value. Then, the first temperature change value and the first temperature value can be added together to obtain the third temperature value. Then, the target deviation between the second temperature value and the third temperature value can be calculated. The specific calculation formula is as follows:

[0090] Target deviation = |second temperature value - third temperature value| / third temperature value × 100%;

[0091] The target deviation can be obtained according to the above formula. When the target deviation is not greater than the preset deviation, the first weight corresponding to the second temperature value and the second weight corresponding to the third temperature value can be obtained. Specifically, the target acquisition accuracy of the temperature acquisition device can be obtained first, and then the target inspection accuracy of the target internal resistance detected by the BMS can be obtained. Then, the first weight and the second weight are calculated according to the following formula:

[0092] Target acquisition accuracy / target inspection accuracy = first weight / second weight;

[0093] 1=first weight + second weight;

[0094] The first weight and the second weight can be calculated according to the above two formulas. Then, the predicted temperature value can be determined according to the second temperature value, the third temperature value, the first weight and the second weight. The specific calculation formula is as follows:

[0095] Predicted temperature value = second temperature value × first weight + third temperature value × second weight;

[0096] The predicted temperature value can be obtained according to the above formula.

[0097] When the target deviation is greater than the preset deviation, the slope of each of the m temperature lines can be obtained to obtain m slopes. Then, the average of these m slopes can be calculated, which is the target slope. Then, the second temperature change value can be determined based on the target slope and the target duration. The specific calculation formula is as follows:

[0098] Second temperature change value = target slope × target duration;

[0099] The second temperature change value can be obtained according to the above formula; finally, the second temperature change value and the first temperature value can be added together to obtain the predicted temperature value.

[0100] In this way, the second temperature value is predicted using m temperature data sets. The target internal resistance and target operating current of the target power supply are then taken into account to calculate the heat generated within the target duration (target heat). This results in a predicted third temperature value. A weighted calculation is then performed based on the second and third temperature values to obtain the final predicted temperature value. This comprehensive approach avoids the limitations of relying on a single method for temperature prediction. For example, relying solely on historical temperature data may not accurately reflect temperature fluctuations caused by changes in the power supply's internal state (such as varying heat generation due to changes in internal resistance), while considering only power supply heat generation may overlook the influence of the external environment or previous temperature trends. Combining these two methods can make the predicted temperature closer to reality, improving the accuracy of temperature prediction.

[0101] S205 . Determine a target operating state of the target power supply according to the first temperature value and the predicted temperature value; the target operating state includes one of the following: a normal operating state, an overheated operating state, and an overcooled operating state.

[0102] In the embodiment of the present application, the temperature change trend of the target power supply can be determined based on the first temperature value and the predicted temperature value, and then the target operating state can be determined based on the temperature change trend.

[0103] Optionally, step S205, determining the target operating state of the target power supply according to the first temperature value and the predicted temperature value, may include the following steps:

[0104] When the first temperature value is greater than the second preset temperature value, it indicates that the temperature of the target power supply is too high and needs to be cooled down. Therefore, it can be determined that the target working state is an overheating working state; the second preset temperature value is greater than the first preset temperature value;

[0105] When the first temperature value is less than the third preset temperature value, it indicates that the temperature of the target power supply is too low and needs to be heated. Therefore, it can be determined that the target working state is an overcooling working state; the third preset temperature value is less than the first preset temperature value;

[0106] When the first temperature value is not greater than the second preset temperature value, a first difference between the predicted temperature value and the first temperature value may be calculated; if the first difference is greater than the first preset difference, it means that the temperature of the target power supply will have a significant upward trend in the future. Even if the current temperature has not reached the overheating standard, it is very likely that the target power supply will soon enter an overheating state. Therefore, the target operating state may be determined to be an overheating operating state.

[0107] If the first difference is less than the second preset difference, it means that the temperature of the target power supply will have a significant downward trend in the future. Even if the current temperature has not reached the overcooling standard, it is very likely to enter the overcooling state. Therefore, it can be determined that the target operating state is the overcooling operating state; the second preset difference is less than the first preset difference;

[0108] If the first temperature value is within the preset temperature range (i.e., greater than or equal to the third preset temperature value and less than or equal to the second preset temperature value), and the first difference is within the preset difference range (i.e., greater than or equal to the second preset difference and less than or equal to the first preset difference), the target working state is determined to be the normal working state.

[0109] It should be explained that the second preset temperature value, the third preset temperature value, the first preset difference, the second preset difference, the preset temperature range and the preset difference range can all be preset or defaulted.

[0110] S206 : Within the second preset time period, control the thermal management module to perform thermal management on the target power supply based on the first temperature value, the predicted temperature value, and the target operating state, so that the temperature of the target power supply returns to a preset temperature range.

[0111] In an embodiment of the present application, within the second preset time period, the thermal management module can be controlled to cool down or heat up the target power supply based on the first temperature value, the predicted temperature value and the target working state, so that the temperature of the target power supply returns to the preset temperature range.

[0112] Optionally, step S206, controlling the thermal management module to perform thermal management on the target power supply based on the first temperature value, the predicted temperature value, and the target operating state, may include the following steps:

[0113] C1. Determine the thermal management components corresponding to the target operating state in the thermal management module to obtain a thermal management components, where a is a natural number; each thermal management component includes one of the following: a heating component and a cooling component;

[0114] C2. determining a difference between the first temperature value and the predicted temperature value to obtain a second difference;

[0115] C3. Determine a first operating power according to the second difference;

[0116] C4. Obtaining the distance between each of the a thermal management components and the target power supply to obtain a distances;

[0117] C5. Determine an adjustment factor corresponding to each of the a distances to obtain a adjustment factors;

[0118] C6. Adjust the first operating power according to the a adjustment factors to obtain a second operating power;

[0119] C7. Determine the amount of heat generated by the target power supply during a preset time period based on the target internal resistance and the target operating current, to obtain a first amount of heat;

[0120] C8. Obtaining a target thermal conductivity corresponding to the target power supply;

[0121] C9. Determine a first optimization factor corresponding to the target thermal conductivity;

[0122] C10. Adjusting the first amount of heat according to the first optimization factor to obtain a second amount of heat;

[0123] C11. Determine a second optimization factor corresponding to the second amount of heat;

[0124] C12. Adjust the a second operating powers according to the second optimization factor to obtain a third operating powers;

[0125] C13. Control the a thermal management components to operate at a corresponding third operating power among the a third operating powers to perform thermal management on the target power supply.

[0126] In an embodiment of the present application, the heating component may include at least one of the following: a heating plate, a Peltier module, a hot air circulation system, etc., which are not limited here; the cooling component may include at least one of the following: a fan, a heat sink, a liquid cooling system, a heat pipe, etc., which are not limited here; the preset time length can be preset in advance or defaulted.

[0127] In a specific embodiment, the thermal management component corresponding to the target operating state in the thermal management module can be determined to obtain a thermal management components. Specifically, a mapping relationship between a preset operating state and a thermal management component can be pre-stored, and the a thermal management components corresponding to the target operating state can be determined based on the mapping relationship. Then, the difference between the first temperature value and the predicted temperature value can be calculated to obtain a second difference. Then, the first operating power can be determined based on the second difference. For example, a mapping relationship between the preset difference and the operating power can be pre-stored, and the first operating power corresponding to the second difference can be determined based on the mapping relationship. Then, the distance between each of the a thermal management components and the target power supply can be obtained to obtain a distance. Specifically, a design document of the power supply thermal management device can be obtained, and the position information of the a thermal management components and the target power supply can be obtained from the design document. Then, the a distances can be calculated based on the position information. Alternatively, the a distances can be measured by a distance measuring device (for example, a laser rangefinder).

[0128] Furthermore, an adjustment factor corresponding to each of the a distances can be determined to obtain a adjustment factor. Specifically, a mapping relationship between preset distances and adjustment factors can be pre-stored, and a adjustment factor corresponding to the a distances can be determined based on the mapping relationship. The value range of the adjustment factor can be -0.2 to 0.2. Then, the first operating power can be adjusted according to the a adjustment factors. The specific calculation formula is as follows:

[0129] Target second operating power = first operating power × (1 + first adjustment factor);

[0130] Among them, the first adjustment factor is any one of the a adjustment factors, and the target second working power is the second working power corresponding to the first adjustment factor in the a second working powers; according to the above formula, a times of calculation can be performed to obtain a second working power; then, the heat generated by the target power supply in the preset time can be determined according to the target internal resistance and the target working current to obtain the first heat. Specifically, the method for obtaining the first heat can be the same as the method for obtaining the target heat; then, the target thermal conductivity corresponding to the target power supply can be obtained. Specifically, the target shell type of the target power supply can be obtained, and the target thermal conductivity corresponding to the target shell type can be determined according to the mapping relationship between the above shell type and thermal conductivity; then, the first optimization factor corresponding to the target thermal conductivity can be determined. For example, the mapping relationship between the preset thermal conductivity and the optimization factor can be pre-stored, and the first optimization factor corresponding to the target thermal conductivity can be determined based on the mapping relationship; then, the first heat can be adjusted according to the first optimization factor. The specific calculation formula is as follows:

[0131] Second heat = first heat × (1 + first optimization factor);

[0132] According to the above formula, the second heat amount can be obtained; then, the second optimization factor corresponding to the second heat amount can be determined. For example, a mapping relationship between a preset heat amount and the optimization factor can be pre-stored, and the second optimization factor corresponding to the second heat amount can be determined based on the mapping relationship, wherein the value range of the first optimization factor and the second optimization factor can both be -0.12 to 0.12; further, the a second working power can be adjusted according to the second optimization factor. The specific calculation formula is as follows:

[0133] Reference third operating power = reference second operating power × (1 + second adjustment factor);

[0134] Among them, the reference second working power is any one of the a second working powers, and the reference third working power is the third working power corresponding to the reference second working power among the a third working powers; according to the above formula, a calculation a times can be obtained to obtain a third working power; finally, a thermal management components can be controlled to operate at the corresponding third working power among the a third working powers to perform thermal management on the target power supply.

[0135] By adjusting power based on the temperature fluctuation (the second difference), more precise temperature control can be achieved. This avoids over-regulation (e.g., using maximum cooling power at the slightest temperature increase) or under-regulation (e.g., using too little cooling power at a rapid temperature increase). This dynamic power regulation helps stabilize the power supply temperature within an appropriate range, improving the stability and safety of the power supply.

[0136] Optionally, the method may further include the following steps:

[0137] D1. Obtaining a target thermal management component and its corresponding target third operating power; the target thermal management component is any one of the a thermal management components;

[0138] D2. Obtaining a target usage time of the target thermal management component;

[0139] D3. Determine the initial power attenuation coefficient corresponding to the target usage duration;

[0140] D4. Obtaining target environment data of the thermal management component;

[0141] D5. Determine the target impact factor corresponding to the target environmental data;

[0142] D6. Adjusting the initial power attenuation coefficient according to the target impact factor to obtain a target power attenuation coefficient;

[0143] D7. Adjusting the target third operating power according to the target power attenuation coefficient to obtain a target fourth operating power;

[0144] D8. Control the target thermal management component to operate at the target fourth operating power.

[0145] In the embodiment of the present application, the target environment data may include at least one of the following: temperature data, humidity data, wind data, dust concentration, etc., which are not limited here.

[0146] In a specific embodiment, the target thermal management component and the third working power corresponding to the target thermal management component in a third working power, that is, the target third working power, can be obtained; then, the target usage time of the target thermal management component can be obtained. Specifically, the usage record of the target thermal management component can be obtained. The usage record can record the start time and shutdown time of each use of the target thermal management component. The usage time of each time can be obtained by subtracting the start time from the shutdown time. Then, the usage time of each time can be superimposed to obtain the target usage time. Then, the initial power attenuation coefficient corresponding to the target usage time can be determined. Specifically, the mapping relationship between the preset usage time and the power attenuation coefficient can be pre-stored, and the initial power attenuation coefficient corresponding to the target usage time is determined based on the mapping relationship. The value range of the power attenuation coefficient can be -0.3~0.3.

[0147] Next, the target environment data of the thermal management component can be obtained. Specifically, the target environment data can be humidity data, which can be detected by a humidity sensor. Then, the target impact factor corresponding to the target environment data can be determined. Specifically, a mapping relationship between preset environment data and impact factors can be pre-stored, and the target impact factor corresponding to the target environment data can be determined based on the mapping relationship. The value range of the target impact factor can be -0.25~0; then, the initial power attenuation coefficient can be adjusted according to the target impact factor. The specific calculation formula is as follows:

[0148] Target power attenuation coefficient = initial power attenuation coefficient × (1 + target impact factor);

[0149] The target power attenuation coefficient can be obtained according to the above formula. Then, the target third operating power can be adjusted according to the target power attenuation coefficient. The specific calculation formula is as follows:

[0150] Target fourth operating power = target third operating power × (1 + target power attenuation coefficient);

[0151] The target fourth operating power can be obtained according to the above formula; finally, the target thermal management component can be controlled to operate at the target fourth operating power.

[0152] By adjusting power based on component age, this helps extend the lifespan of thermal management components. Ignoring this degradation and consistently operating components at a fixed power level can lead to premature failure due to excessive wear and tear. By appropriately reducing power, component aging can be mitigated to a certain extent, reducing the frequency of repairs and replacements and lowering costs. This also ensures that even if component performance degrades, thermal management of the target power supply remains as effective as possible.

[0153] The implementation of this application has the following beneficial effects:

[0154] It can be seen that the thermal management method of the power supply described in the present application is applied to a power supply thermal management device, which includes: a target power supply, a thermal management module, and the target power supply includes m battery cells. The method includes: within a first preset time period, collecting a temperature data set of each of the m battery cells to obtain m reference temperature data sets; performing a preprocessing operation on the m reference temperature data sets to obtain m temperature data sets; determining a first temperature value of the target power supply based on the m temperature data sets; predicting a predicted temperature value of the target power supply at a target time based on the m temperature data sets and the first temperature value; determining a target operating state of the target power supply based on the first temperature value and the predicted temperature value; within a second preset time period, based on the first temperature value , predicted temperature value and target working state control thermal management module to perform thermal management on the target power supply so that the temperature of the target power supply returns to the preset temperature range. In this way, by adjusting the working mode and parameters of the thermal management module accordingly according to the first temperature value of the target power supply, the predicted temperature value and the temperature data sets of each of the m battery cells, a set of appropriate thermal management strategies are matched for different thermal states of the target power supply. Performing thermal management operations on the target power supply in this way can ensure the safety of the power supply, avoid dangerous situations such as thermal runaway caused by overheating, or battery performance degradation and shortened life due to overcooling, thereby improving the thermal management effect of the power supply thermal management device on the target power supply, and ensuring that the target power supply can operate stably and efficiently for a long time.

[0155] See also Figure 3 , Figure 3 This is a block diagram of the functional units of a power supply thermal management system 300 provided in an embodiment of the present application, which is applied to a power supply thermal management device. The power supply thermal management device includes: a target power supply and a thermal management module. The target power supply includes m battery cells, where m is a positive integer. The power supply thermal management system 300 includes: an acquisition unit 301, a control unit 302, and a thermal management unit 303, wherein:

[0156] The acquisition unit 301 is configured to acquire a temperature data set of each of the m battery cells within a first preset time period to obtain m reference temperature data sets;

[0157] The control unit 302 is configured to perform a preprocessing operation on the m reference temperature data sets to obtain m temperature data sets; the preprocessing operation includes at least one of the following: a data cleaning operation, a data conversion operation, and a data smoothing operation; determine a first temperature value of the target power supply based on the m temperature data sets; predict a predicted temperature value of the target power supply at a target time based on the m temperature data sets and the first temperature value; the target time is a time within a second preset time period; the start time of the second preset time period is later than the end time of the first preset time period; determine a target operating state of the target power supply based on the first temperature value and the predicted temperature value; the target operating state includes one of the following: a normal operating state, an overheated operating state, and an overcooled operating state;

[0158] The thermal management unit 303 is configured to control the thermal management module to perform thermal management on the target power supply based on the first temperature value, the predicted temperature value, and the target operating state within the second preset time period, so as to return the temperature of the target power supply to a preset temperature range.

[0159] Optionally, in determining the first temperature value of the target power supply according to the m temperature data sets, the control unit 302 is specifically configured to:

[0160] Determine a reference temperature value corresponding to each temperature data set in the m temperature data sets to obtain m reference temperature values;

[0161] Obtaining the shell type of each of the m battery cells to obtain m shell types;

[0162] Determining a first thermal conductivity corresponding to each of the m shell types to obtain m first thermal conductivities;

[0163] Determine a weight corresponding to each of the m first thermal conductivities to obtain m weights;

[0164] The first temperature value is determined according to the m reference temperature values and the m weights.

[0165] Optionally, in determining the reference temperature value corresponding to each of the m temperature data sets to obtain the m reference temperature values, the control unit 302 is specifically configured to:

[0166] Acquire a first temperature data set; the first temperature data set is any temperature data set among the m temperature data sets; the first temperature data set includes n temperature values; n is an integer greater than 1;

[0167] Determining a target average temperature value corresponding to the n temperature values;

[0168] When the target average temperature value is greater than a first preset temperature value, determining a reference temperature value corresponding to the first temperature data set according to the target average temperature value;

[0169] When the target average temperature value is not greater than the first preset temperature value, obtaining a collection time of each of the n temperature values to obtain n collection times;

[0170] Obtaining the difference between each of the n acquisition moments and the end moment of the first preset time period to obtain n differences;

[0171] Determine an average difference value corresponding to the n difference values;

[0172] Dividing the first preset time period into k intervals according to the average difference; k is an integer greater than 1;

[0173] Based on the n acquisition moments, the n temperature values fall into the k intervals;

[0174] Determine a temperature value set in each of the k intervals to obtain k temperature value sets;

[0175] Determine an average temperature value corresponding to each temperature value set in the k temperature value sets to obtain k average temperature values;

[0176] Obtaining a weight corresponding to each of the k intervals to obtain k weights, wherein the sum of the k weights is 1, and the weight of an interval closer to the start time of the first preset time period is smaller;

[0177] A reference temperature value corresponding to the first temperature data set is determined according to the k weights and the k average temperature values.

[0178] Optionally, in predicting the predicted temperature value of the target power source at the target time according to the m temperature data sets and the first temperature value, the control unit 302 is specifically configured to:

[0179] Fitting each of the m temperature data sets to obtain m temperature straight lines, wherein the horizontal axis is time and the vertical axis is temperature value;

[0180] Determine m reference predicted temperature values corresponding to the target time according to the m temperature straight lines;

[0181] Determine a second temperature value according to the m reference predicted temperature values;

[0182] Obtaining a target internal resistance and a target operating current of the target power supply;

[0183] Determining the amount of heat generated by the target power supply within a target duration based on the target internal resistance and the target operating current to obtain a target amount of heat; the target duration is the duration from the end of the first preset time period to the target time;

[0184] estimating a first temperature change value of the target power supply according to the target heat;

[0185] determining a third temperature value according to the first temperature change value and the first temperature value;

[0186] determining a target deviation between the second temperature value and the third temperature value;

[0187] When the target deviation is not greater than a preset deviation, obtaining a first weight corresponding to the second temperature value and a second weight corresponding to the third temperature value; and determining the predicted temperature value based on the second temperature value, the third temperature value, the first weight, and the second weight;

[0188] When the target deviation is greater than the preset deviation, obtaining the slope of each of the m temperature straight lines to obtain m slopes;

[0189] Determining a target slope corresponding to the m slopes;

[0190] determining a second temperature change value according to the target slope and the target duration;

[0191] The predicted temperature value is determined according to the second temperature change value and the first temperature value.

[0192] Optionally, in determining the target operating state of the target power supply according to the first temperature value and the predicted temperature value, the control unit 302 is specifically configured to:

[0193] When the first temperature value is greater than a second preset temperature value, determining that the target operating state is the overheating operating state; the second preset temperature value is greater than the first preset temperature value;

[0194] When the first temperature value is less than a third preset temperature value, determining that the target operating state is the supercooling operating state; the third preset temperature value is less than the first preset temperature value;

[0195] When the first temperature value is not greater than the second preset temperature value, determining a first difference between the predicted temperature value and the first temperature value;

[0196] If the first difference is greater than a first preset difference, determining that the target operating state is the overheating operating state;

[0197] If the first difference is smaller than a second preset difference, determining that the target operating state is the supercooling operating state; and the second preset difference is smaller than the first preset difference;

[0198] If the first temperature value is within the preset temperature range, and the first difference is within the preset difference range, the target working state is determined to be the normal working state.

[0199] Optionally, in controlling the thermal management module to perform thermal management on the target power supply based on the first temperature value, the predicted temperature value, and the target operating state, the thermal management unit 303 is specifically configured to:

[0200] Determine the thermal management component corresponding to the target operating state in the thermal management module to obtain a thermal management components; a is a natural number; each thermal management component includes one of the following: a heating component and a cooling component;

[0201] determining a difference between the first temperature value and the predicted temperature value to obtain a second difference;

[0202] determining a first operating power according to the second difference;

[0203] Obtaining a distance between each of the a thermal management components and the target power supply to obtain a distances;

[0204] Determine an adjustment factor corresponding to each of the a distances to obtain a adjustment factors;

[0205] Adjust the first operating power according to the a adjustment factors to obtain a second operating power;

[0206] determining the amount of heat generated by the target power supply in a preset time period according to the target internal resistance and the target operating current to obtain a first amount of heat;

[0207] Obtaining a target thermal conductivity corresponding to the target power supply;

[0208] determining a first optimization factor corresponding to the target thermal conductivity;

[0209] Adjusting the first amount of heat according to the first optimization factor to obtain a second amount of heat;

[0210] determining a second optimization factor corresponding to the second heat amount;

[0211] Adjusting the a second operating powers according to the second optimization factor to obtain a third operating powers;

[0212] The a thermal management components are controlled to operate at corresponding third operating powers among the a third operating powers to perform thermal management on the target power supply.

[0213] Optionally, the thermal management system 300 of the power supply is further configured to:

[0214] Obtaining a target thermal management component and its corresponding target third operating power; the target thermal management component is any one of the a thermal management components;

[0215] Obtaining a target usage time of the target thermal management component;

[0216] Determining an initial power attenuation coefficient corresponding to the target usage duration;

[0217] Acquiring target environment data of the thermal management component;

[0218] Determining a target impact factor corresponding to the target environmental data;

[0219] Adjusting the initial power attenuation coefficient according to the target impact factor to obtain a target power attenuation coefficient;

[0220] Adjusting the target third operating power according to the target power attenuation coefficient to obtain a target fourth operating power;

[0221] The target thermal management component is controlled to operate at the target fourth operating power.

[0222] In a specific implementation, the thermal management system 300 of the power supply described in the embodiment of the present invention may also execute other implementations described in the thermal management method of the power supply provided in the embodiment of the present invention, which will not be described in detail here.

[0223] See also Figure 4 , Figure 4 1 is a schematic diagram of the structure of an intelligent power supply provided in an embodiment of the present application. The intelligent power supply includes a processor, a memory, a communication interface, and one or more programs, wherein the processor, memory, and communication interface are interconnected via a bus. The one or more programs are stored in the memory and configured to be executed by the processor. The programs include some or all of the steps for executing the thermal management method for a power supply provided in an embodiment of the present application.

[0224] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any method described in the above method embodiments, and the above computer may include an intelligent power supply.

[0225] Embodiments of the present application also provide a computer program product, comprising a non-transitory computer-readable storage medium storing a computer program, wherein the computer program is operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments. The computer program product may be a software installation package, and the computer may include a smart power supply.

[0226] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by this application.

[0227] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0228] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the above-mentioned units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0229] The units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0230] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0231] If the above-mentioned integrated unit 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 memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory and includes a number of instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the above-mentioned methods in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store program code.

[0232] The above is a detailed introduction to the embodiments of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of the present application. At the same time, for those skilled in the art, according to the idea of the present application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A thermal management method for a power supply, characterized in that: Applied to a power supply thermal management device, the power supply thermal management device includes: a target power supply and a thermal management module, the target power supply includes m battery cells, where m is a positive integer, and the method includes: Within a first preset time period, collecting a reference temperature data set of each of the m battery cells to obtain m reference temperature data sets; Performing a preprocessing operation on the m reference temperature data sets to obtain m temperature data sets; the preprocessing operation includes at least one of the following: a data cleaning operation, a data conversion operation, and a data smoothing operation; determining a first temperature value of the target power supply according to the m temperature data sets; Predicting a predicted temperature value of the target power supply at a target time based on the m temperature data sets and the first temperature value; the target time is a time within a second preset time period; the start time of the second preset time period is later than the end time of the first preset time period; Determining a target operating state of the target power supply according to the first temperature value and the predicted temperature value; the target operating state includes one of the following: a normal operating state, an overheated operating state, and an overcooled operating state; During the second preset time period, controlling the thermal management module to perform thermal management on the target power supply based on the first temperature value, the predicted temperature value, and the target operating state, so as to return the temperature of the target power supply to a preset temperature range; The step of predicting the predicted temperature value of the target power source at the target time according to the m temperature data sets and the first temperature value includes: Fitting each of the m temperature data sets to obtain m temperature straight lines, wherein the horizontal axis is time and the vertical axis is temperature value; Determine m reference predicted temperature values corresponding to the target time according to the m temperature straight lines; Determine a second temperature value according to the m reference predicted temperature values; Obtaining a target internal resistance and a target operating current of the target power supply; Determining the amount of heat generated by the target power supply within a target duration based on the target internal resistance and the target operating current to obtain a target amount of heat; the target duration is the duration from the end of the first preset time period to the target time; estimating a first temperature change value of the target power supply according to the target heat; determining a third temperature value according to the first temperature change value and the first temperature value; determining a target deviation between the second temperature value and the third temperature value; When the target deviation is not greater than a preset deviation, obtaining a first weight corresponding to the second temperature value and a second weight corresponding to the third temperature value; and determining the predicted temperature value based on the second temperature value, the third temperature value, the first weight, and the second weight; When the target deviation is greater than the preset deviation, the slope of each of the m temperature straight lines is obtained to obtain m slopes, the target slope corresponding to the m slopes is determined, the second temperature change value is determined based on the target slope and the target duration, and the predicted temperature value is determined based on the second temperature change value and the first temperature value.

2. The method according to claim 1, wherein Determining the first temperature value of the target power supply according to the m temperature data sets includes: Determine a reference temperature value corresponding to each temperature data set in the m temperature data sets to obtain m reference temperature values; Obtaining the shell type of each of the m battery cells to obtain m shell types; Determining a first thermal conductivity corresponding to each of the m shell types to obtain m first thermal conductivities; Determine a weight corresponding to each of the m first thermal conductivities to obtain m weights; The first temperature value is determined according to the m reference temperature values and the m weights.

3. The method according to claim 2, wherein The determining of the reference temperature value corresponding to each temperature data set in the m temperature data sets to obtain m reference temperature values includes: Acquire a first temperature data set; the first temperature data set is any temperature data set among the m temperature data sets; the first temperature data set includes n temperature values; n is an integer greater than 1; Determining a target average temperature value corresponding to the n temperature values; When the target average temperature value is greater than a first preset temperature value, determining a reference temperature value corresponding to the first temperature data set according to the target average temperature value; When the target average temperature value is not greater than the first preset temperature value, obtaining a collection time of each of the n temperature values to obtain n collection times; Obtaining the difference between each of the n acquisition moments and the end moment of the first preset time period to obtain n differences; Determine an average difference value corresponding to the n difference values; Dividing the first preset time period into k intervals according to the average difference; k is an integer greater than 1; Based on the n acquisition moments, the n temperature values fall into the k intervals; Determine a temperature value set in each of the k intervals to obtain k temperature value sets; Determine an average temperature value corresponding to each temperature value set in the k temperature value sets to obtain k average temperature values; Obtaining a weight corresponding to each of the k intervals to obtain k weights, wherein the sum of the k weights is 1, and the weight of an interval closer to the start time of the first preset time period is smaller; A reference temperature value corresponding to the first temperature data set is determined according to the k weights and the k average temperature values.

4. The method according to any one of claims 1 to 3, wherein The determining the target operating state of the target power supply according to the first temperature value and the predicted temperature value includes: When the first temperature value is greater than a second preset temperature value, determining that the target operating state is the overheating operating state; the second preset temperature value is greater than the first preset temperature value; When the first temperature value is less than a third preset temperature value, determining that the target operating state is the supercooling operating state; the third preset temperature value is less than the first preset temperature value; When the first temperature value is not greater than the second preset temperature value, determining a first difference between the predicted temperature value and the first temperature value; If the first difference is greater than a first preset difference, determining that the target operating state is the overheating operating state; If the first difference is smaller than a second preset difference, determining that the target operating state is the supercooling operating state; and the second preset difference is smaller than the first preset difference; If the first temperature value is within the preset temperature range, and the first difference is within the preset difference range, the target working state is determined to be the normal working state.

5. The method according to claim 1, wherein The controlling the thermal management module to perform thermal management on the target power supply based on the first temperature value, the predicted temperature value, and the target operating state includes: Determine the thermal management component corresponding to the target operating state in the thermal management module to obtain a thermal management components; a is a natural number; each thermal management component includes one of the following: a heating component and a cooling component; determining a difference between the first temperature value and the predicted temperature value to obtain a second difference; determining a first operating power according to the second difference; Obtaining a distance between each of the a thermal management components and the target power supply to obtain a distances; Determine an adjustment factor corresponding to each of the a distances to obtain a adjustment factors; Adjust the first operating power according to the a adjustment factors to obtain a second operating power; determining the amount of heat generated by the target power supply in a preset time period according to the target internal resistance and the target operating current to obtain a first amount of heat; Obtaining a target thermal conductivity corresponding to the target power supply; determining a first optimization factor corresponding to the target thermal conductivity; Adjusting the first amount of heat according to the first optimization factor to obtain a second amount of heat; determining a second optimization factor corresponding to the second heat amount; Adjusting the a second operating powers according to the second optimization factor to obtain a third operating powers; The a thermal management components are controlled to operate at corresponding third operating powers among the a third operating powers to perform thermal management on the target power supply.

6. The method according to claim 5, wherein The method further comprises: Obtaining a target thermal management component and its corresponding target third operating power; the target thermal management component is any one of the a thermal management components; Obtaining a target usage time of the target thermal management component; Determining an initial power attenuation coefficient corresponding to the target usage duration; Acquiring target environment data of the thermal management component; Determining a target impact factor corresponding to the target environmental data; Adjusting the initial power attenuation coefficient according to the target impact factor to obtain a target power attenuation coefficient; Adjusting the target third operating power according to the target power attenuation coefficient to obtain a target fourth operating power; The target thermal management component is controlled to operate at the target fourth operating power.

7. A thermal management system for a power supply, characterized in that: Applicable to a power supply thermal management device, the power supply thermal management device includes: a target power supply, a thermal management module, the target power supply includes m battery cells, m is a positive integer, the system includes: an acquisition unit, a control unit, and a thermal management unit, wherein: The acquisition unit is configured to acquire a reference temperature data set of each of the m battery cells within a first preset time period to obtain m reference temperature data sets; The control unit is configured to perform a preprocessing operation on the m reference temperature data sets to obtain m temperature data sets; the preprocessing operation includes at least one of the following: a data cleaning operation, a data conversion operation, and a data smoothing operation; determine a first temperature value of the target power supply based on the m temperature data sets; predict a predicted temperature value of the target power supply at a target time based on the m temperature data sets and the first temperature value; the target time is a time within a second preset time period; the start time of the second preset time period is later than the end time of the first preset time period; determine a target operating state of the target power supply based on the first temperature value and the predicted temperature value; the target operating state includes one of the following: a normal operating state, an overheated operating state, and an overcooled operating state; the thermal management unit being configured to control the thermal management module to perform thermal management on the target power supply based on the first temperature value, the predicted temperature value, and the target operating state within the second preset time period, so as to return the temperature of the target power supply to a preset temperature range; Wherein, in predicting the predicted temperature value of the target power source at the target time according to the m temperature data sets and the first temperature value, the control unit is specifically configured to: Fitting each of the m temperature data sets to obtain m temperature straight lines, wherein the horizontal axis is time and the vertical axis is temperature value; Determine m reference predicted temperature values corresponding to the target time according to the m temperature straight lines; Determine a second temperature value according to the m reference predicted temperature values; Obtaining a target internal resistance and a target operating current of the target power supply; Determining the amount of heat generated by the target power supply within a target duration based on the target internal resistance and the target operating current to obtain a target amount of heat; the target duration is the duration from the end of the first preset time period to the target time; estimating a first temperature change value of the target power supply according to the target heat; determining a third temperature value according to the first temperature change value and the first temperature value; determining a target deviation between the second temperature value and the third temperature value; When the target deviation is not greater than a preset deviation, obtaining a first weight corresponding to the second temperature value and a second weight corresponding to the third temperature value; and determining the predicted temperature value based on the second temperature value, the third temperature value, the first weight, and the second weight; When the target deviation is greater than the preset deviation, the slope of each of the m temperature straight lines is obtained to obtain m slopes, the target slope corresponding to the m slopes is determined, the second temperature change value is determined based on the target slope and the target duration, and the predicted temperature value is determined based on the second temperature change value and the first temperature value.

8. An intelligent power supply, characterized in that: include: A processor and a memory, wherein the memory is used to store one or more programs and is configured to be executed by the processor, wherein the programs include instructions for executing the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that A computer program for electronic data exchange is stored, wherein the computer program enables a computer to execute the method according to any one of claims 1 to 6.

Images