Energy storage battery pack temperature data processing method, device and equipment and storage medium

Abstract

The invention discloses an energy storage battery pack temperature data processing method and device, equipment and a storage medium. The method comprises the steps that current information of energy storage batteries in an energy storage battery pack to be tested and temperature information of temperature sampling points in the energy storage battery pack are acquired, and the temperature information comprises temperature values of at least two preset sampling points in the energy storage battery pack to be tested; inputting the obtained current information of the energy storage battery into a pre-trained temperature rise analysis model to obtain a predicted temperature change value; and judging whether the temperature rise of the energy storage battery pack to be detected is abnormal or not according to the temperature value at the sampling point and the predicted temperature change value. According to the exemplary embodiment, the storage management and fault early warning level of the temperature information of the energy storage battery pack is improved.

Description

Technical Field

[0001] The present application relates to the technical field of energy storage, and in particular, to a method, device, equipment, and storage medium for processing temperature data of an energy storage battery pack. Background Art

[0002] In energy storage technology, battery packs in the form of air cooling are mostly arranged in a central axisymmetric form, or are equipped with a single or double fan to ensure uniform temperature. The temperature acquisition module of the battery management system acquires the battery temperature therein, and makes a judgment process of high or low temperature thresholds to form a warning message.

[0003] In related technologies, the detection and processing method of the acquired temperature data has certain management defects only relying on the determination of high or low temperature thresholds, cannot be coupled with the temperature field characteristics, and the form of fault determination is single and the accuracy is poor.

[0004] It should be noted that the statements here only provide background information related to the present application, and do not necessarily constitute prior art. Summary of the Invention

[0005] In view of the above problems, the present application proposes a method, device, equipment, and storage medium for processing temperature data of an energy storage battery pack that overcomes the above problems or at least partially solves the above problems.

[0006] The embodiments of the present application adopt the following technical solutions:

[0007] In a first aspect, the embodiments of the present application provide a method for processing temperature data of an energy storage battery pack, the method including: acquiring current information of the energy storage battery in the energy storage battery pack to be measured and temperature information of temperature sampling points in the energy storage battery pack, where the temperature information includes temperature values at at least two preset sampling points in the energy storage battery pack to be measured; inputting the acquired current information of the energy storage battery into a pre-trained temperature rise analysis model to obtain a predicted temperature change value; and judging whether the temperature rise of the energy storage battery pack to be measured is abnormal according to the temperature value at the sampling point and the predicted temperature change value.

[0008] Preferably, the inputting the acquired current information of the energy storage battery into a pre-trained temperature rise analysis model to obtain a predicted temperature change value includes: inputting the current information of the energy storage battery in the energy storage battery pack to be measured at different times into the temperature rise analysis model according to a time series to obtain a predicted temperature change range.

[0009] Preferably, the judging whether the temperature rise of the energy storage battery pack to be measured is abnormal according to the temperature value at the sampling point and the predicted temperature change value includes: triggering a temperature rise abnormal alarm when the predicted temperature change value of the energy storage battery in the energy storage battery pack to be measured exceeds the predicted temperature change range.

[0010] Preferably, determining whether the temperature rise of the energy storage battery pack to be measured is abnormal according to the temperature value at the sampling point and the predicted temperature change value further includes: managing the temperature values at the preset sampling points separately; at the same sampling moment, when the sampling temperature difference between different sampling points is greater than a preset threshold, triggering a temperature rise abnormal alarm. The preset sampling points include the axially symmetric positions of the energy storage battery pack to be measured.

[0011] In a second aspect, an embodiment of the present application further provides a temperature data processing device, including: a first unit that acquires current information of the energy storage battery in the energy storage battery pack to be measured and temperature information of the temperature sampling points in the energy storage battery pack, where the temperature information includes temperature values at at least two preset sampling points in the energy storage battery pack to be measured; a second unit that inputs the acquired current information of the energy storage battery into a pre-trained temperature rise analysis model to obtain a predicted temperature change value; and a third unit that determines whether the temperature rise of the energy storage battery pack to be measured is abnormal according to the temperature value at the sampling point and the predicted temperature change value.

[0012] In a third aspect, an embodiment of the present application further provides a computer storage medium, on which instructions are stored, and when the instructions are executed alone or jointly by at least one processor of a computing device, the computing device is caused to execute the method according to any one of the first aspect.

[0013] In a fourth aspect, an embodiment of the present application further provides a computer program product, including instructions, and when the instructions are executed alone or jointly by at least one processor of a computing device, the computing device is caused to execute the method according to any one of the first aspect.

[0014] In a fifth aspect, an embodiment of the present application further provides an electronic device, including: a processor; and a memory arranged to store computer-executable instructions, and when the executable instructions are executed, the processor is caused to execute the method according to any one of the first aspect.

[0015] At least one of the technical solutions adopted in the embodiments of the present application can achieve the following beneficial effects:

[0016] The present disclosure confirms the abnormal temperature condition of the battery in the energy storage battery pack by independently managing the battery temperature rise information in the energy storage battery pack and comparing the temperatures of multiple sampling points in the battery pack. It improves the coupling of the temperature data collected by the battery management system and the temperature field space association, and improves the storage management and fault warning level of temperature information.

[0017] The above description of the technical solution of this application is only an overview of the technical solution of this application. In order to be able to understand the technical means of this application more clearly, it can be implemented in accordance with the content of the specification. And in order to make the above and other purposes, features and advantages of this application more obvious and understandable, the following specifically illustrates the specific implementation manners of this application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of this application. Moreover, throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0019] Figure 1 It is a schematic flowchart of the method for processing temperature data of the energy storage battery pack in the embodiment of this application;

[0020] Figure 2 It is a schematic diagram of the device for processing temperature data of the energy storage battery pack in the embodiment of this application;

[0021] Figure 3 It is a second schematic flowchart of the method for processing temperature data of the energy storage battery pack in the embodiment of this application;

[0022] Figure 4 It is a schematic diagram of the device for processing temperature data of the energy storage battery pack in the embodiment of this application;

[0023] Figure 5 It is a schematic diagram of the structure of an electronic device in the embodiment of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] To make the objectives, technical solutions and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with the specific embodiments of this application and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts shall fall within the scope of protection of this application.

[0025] The concept of this application is to design an automated and highly universal method for processing temperature data of an energy storage battery pack in view of the current situation that the processing of temperature data of the energy storage battery pack in the prior art cannot be coupled with the temperature field characteristics and the form of temperature fault determination is single. This method manages the battery data in the battery pack by column, comprehensively considers the temperatures at different sampling points, and confirms the abnormal conditions of the battery, improving the storage management of battery pack information and the level of fault warning.

[0026] The following will describe in detail the technical solutions provided by each embodiment of this application in conjunction with the drawings.

[0027] The embodiments of the present application provide a method, device and system for processing temperature data of an energy storage battery pack, as Figure 1 shown, a schematic flowchart of the method 100 for processing temperature data of an energy storage battery pack in the embodiments of the present application is provided. The method 100 at least includes the following steps S110 to S130:

[0028] Step S110, obtaining the current information of the energy storage batteries in the energy storage battery pack to be measured and the temperature information of the temperature sampling points in the energy storage battery pack, where the temperature information includes the temperature values at at least two preset sampling points in the energy storage battery pack to be measured

[0029] As Figure 2 shown, the battery pack temperature data processing device includes a detection unit, a processor, a memory and a communication bus. Among them, the communication bus is used to realize the connection and communication between the detection unit, the memory and the processor. The detection unit is a common NTC (negative temperature coefficient) probe or other current sensors, which can realize the acquisition of raw data. The processor includes a communication interface and a data processing program for realizing data processing. The memory includes an operating system, a communication interface and a user interface. Optionally, it may further include external modules such as wireless or wired network interfaces. Among them, the user interface may include a display screen, an input unit such as a keyboard, etc. The memory may be a high-speed random access memory or a stable non-volatile memory such as a disk memory. Optionally, the memory may be a storage device independent of the aforementioned processor.

[0030] In the data processing device, the current sensor can obtain the current information of the energy storage batteries in the battery pack. Among them, the current information may include the current information of all the energy storage batteries in the energy storage battery pack or the current information of some (preset positions) energy storage batteries. The collected current information is stored separately in the memory according to the energy storage battery numbers. When needed, it is transmitted to the processor for data processing through data calling.

[0031] The temperature information includes the temperature values at at least two preset sampling points in the energy storage battery pack to be measured. The sampling points are set in the battery pack, and the setting positions are set according to needs. In one example, since the batteries in the battery pack are symmetrically distributed in space, the battery temperatures at the same flow positions in the cooling air flow direction have similar characteristics, and this feature also applies to systems equipped with symmetric double fans. Therefore, the positions of the sampling points can be set at symmetric positions inside the battery pack to make the obtained temperature information more reasonable and accurate.

[0032] It can be understood that the detection unit in this embodiment can be any device with similar functions. For example, in the case of contact temperature measurement, a thermometer is used to measure the battery temperature, or it can be a non-contact temperature measurement method to obtain the battery temperature using infrared temperature measurement technology. The same applies to the current sensor, and this example does not limit it.

[0033] Step S120: Input the obtained current information of the energy storage battery into a pre-trained temperature rise analysis model to obtain a predicted temperature change value;

[0034] The temperature rise of the battery satisfies the basic heat transfer law. The change in the magnitude of the current affects the heat generation, and the change characteristics of the temperature rise rate satisfy the exponential power form. The temperature measured in the temperature rise analysis model also has the characteristics of the solution of a first-order ordinary differential equation, which is in the exponential power form. Specifically, the battery generates heat during operation, and its heat transfer process mainly includes heat conduction, heat convection, and heat radiation. Heat conduction refers to the heat transfer caused by the temperature gradient inside the battery, such as the heat transfer between the electrode materials and electrolytes inside the battery. Heat convection is the heat exchange between the battery surface and the surrounding environment (such as air), which is closely related to the heat dissipation environment where the battery is located. Heat radiation is relatively weak, but it will also have a certain impact on heat dissipation in special cases such as high temperatures. When current passes through the battery internal resistance, heat is generated, and its heat generation in the battery can be expressed as Q = I 2 R int t, where I is the current, R int is the battery internal resistance, and t is the time. When the magnitude of the current changes, the heat generation will change accordingly. For example, when the current increases, according to the above formula, the heat generation will increase by a multiple of the square of the current. This causes the heat generated inside the battery to increase, resulting in an accelerated temperature rise rate.

[0035] When the difference between the battery temperature and the ambient temperature is small, the temperature rise rate is relatively slow; as the difference increases, the temperature rise rate will accelerate. The temperature rise rate equation can be expressed as: dT / dt = k(T - T 0 ) n . T is the current temperature, and T 0 is the ambient temperature. By using the experimental measurement data obtained during the test, the temperature rise rate equation is optimized to obtain a temperature rise analysis model that conforms to the temperature rise characteristics of the battery pack. After obtaining the basic temperature rise analysis model, the subsequent sampled data can be corrected and compared, and the iteration of the corresponding parameters makes the temperature rise prediction value within a certain tolerance range, conforming to the temperature rise change law of the basic charge and discharge process of the battery. Input the obtained current information of the energy storage battery into a pre-trained temperature rise analysis model to obtain a predicted temperature change value.

[0036] Such as Figure 3As shown, in some embodiments, inputting the obtained current information of the energy storage battery into a pre-trained temperature rise analysis model to obtain a predicted temperature change value includes: inputting the current information of the energy storage batteries in the energy storage battery pack to be measured at different times into the temperature rise analysis model according to a time series to obtain a predicted temperature change range.

[0037] Perform time series management on the obtained current information data and temperature information data. The time series management targets the accumulation of data collected at the same measurement point on the time scale. In one example, since the temperature data of different batteries in the battery pack have different change mechanisms and correspond to different parameters when using the temperature rise model, there are differences, and the data at different measurement points need to be stored and managed separately.

[0038] Step S130, determine whether the temperature rise of the energy storage battery pack to be measured is abnormal according to the temperature value at the sampling point and the predicted temperature change value.

[0039] In some embodiments, determining whether the temperature rise of the energy storage battery pack to be measured is abnormal according to the temperature value at the sampling point and the predicted temperature change value includes: when the predicted temperature change value of the energy storage batteries in the energy storage battery pack to be measured exceeds the predicted temperature change range, trigger a temperature rise abnormal alarm.

[0040] In one example, for an energy storage battery pack, the temperature of the internal energy storage batteries is a key parameter. To ensure the normal, safe, and efficient operation of the battery pack, a temperature change value range is set in advance based on many factors such as the characteristics of the battery, past operation data, environmental conditions, and the heat dissipation design of the battery pack. This range covers the expected temperature fluctuation range of the battery in the normal working state, from the low temperature limit to the high temperature limit.

[0041] At the same time, the predicted temperature change value of the battery obtained through the temperature sensor installed on the energy storage battery and the temperature rise analysis model will "predict" the temperature value of the battery in real time. Once the monitored predicted temperature change value breaks through the pre-set range, whether it is higher than the high temperature limit or lower than the low temperature limit, the system will immediately trigger a "temperature rise abnormal alarm".

[0042] After the alarm is triggered, the alarm information will be transmitted to the control center, enabling the operator to be aware of the situation in a timely manner. Meanwhile, some emergency measures are automatically initiated. In case of abnormal high temperature, the heat dissipation is increased, such as enhancing the intensity of air cooling and water cooling, or reducing the charge and discharge power of the battery, to prevent safety accidents caused by overheating of the battery, such as thermal runaway, combustion, or even explosion. In case of abnormal low temperature, a heating device is activated to raise the battery temperature back to the normal operating range, ensuring that the charge and discharge performance of the battery is not damaged. This mechanism plays a crucial role in ensuring the reliability of the energy storage battery pack, extending its service life, and maintaining the stable operation of the entire energy storage system.

[0043] In some embodiments, determining whether the temperature rise of the energy storage battery pack to be tested is abnormal based on the temperature value at the sampling point and the predicted temperature change value further includes: managing the temperature values at the preset sampling points separately; at the same sampling moment, when the difference between the sampling temperatures at different sampling points is greater than a preset threshold, an alarm for abnormal temperature rise is triggered.

[0044] As Figure 3 shown, in one example, the temperature data of different sampling points are managed separately according to spatial symmetry distribution. The separate management refers to storing them in double arrays or multiple arrays by separating the same positions in the spatial symmetry distribution. The temperature differences at symmetric positions of the separately managed temperature data are compared. It should be noted that the batteries in the battery pack are symmetrically distributed in space, and the battery temperatures at the same process positions in the direction of the cooling air flow have similar characteristics, which also applies to systems equipped with symmetric double fans.

[0045] After data is collected from all sampling points at the same moment, the system immediately calculates the temperature differences between every two sampling points. The comparison of this difference is of great significance as it can directly reflect the temperature balance inside the monitored object. Taking the power battery pack of a new energy vehicle as an example, which consists of multiple energy storage batteries inside, and there are multiple different sampling points set inside the battery pack. Under normal circumstances, the temperatures at symmetric position sampling points should be relatively close, and the heat balance is maintained by the heat dissipation design of the battery management system.

[0046] When the temperature difference between two sampling points at symmetric positions exceeds a preset threshold, it means that there is an abnormal situation of overheating or overcooling locally. At this time, the system immediately triggers a warning of abnormal temperature rise. In one example, if the temperature of a certain sampling point is much higher than the surrounding area, it may indicate that there are fault risks such as blocked heat dissipation and internal short circuit in the energy storage battery pack. The warning can timely remind the operator or the automatic control system to intervene and take actions such as suspending charge and discharge, starting additional heat dissipation measures, and further diagnosing the abnormal energy storage battery, so as to avoid further damage to the battery pack and even causing safety accidents, and ensure the safe and stable operation of the entire system. It can be understood that by comparing the temperatures between any two sampling points in the battery pack, the distribution of the temperature difference inside the battery pack can be obtained, and the coupling of the spatial correlation of the temperature field can be improved.

[0047] It should be noted that after multiple data samplings and model calculations, the temperature prediction value through the temperature rise model will gradually stabilize within the error range. If the temperature change exceeds this range, it is an abnormal phenomenon.

[0048] The embodiment of the present application also provides a temperature data processing device 400 for an energy storage battery pack, as Figure 4 shown, which provides a schematic structural diagram of the temperature data processing device for the energy storage battery pack in the embodiment of the present application. The device 400 at least includes: a first unit 410, a second unit 420, and a third unit 430, where:

[0049] In an embodiment of the present application, the first unit 410 is specifically configured to: obtain the current information of the energy storage battery in the energy storage battery pack to be measured and the temperature information of the temperature sampling points in the energy storage battery pack, where the temperature information includes the temperature values at at least two preset sampling points in the energy storage battery pack to be measured.

[0050] In an embodiment of the present application, the second unit 420 is specifically configured to: input the obtained current information of the energy storage battery into a pre-trained temperature rise analysis model to obtain a predicted temperature change value.

[0051] In an embodiment of the present application, the third unit 430 is specifically configured to: determine whether the temperature rise of the energy storage battery pack to be measured is abnormal according to the temperature value at the sampling point and the predicted temperature change value.

[0052] It can be understood that the above temperature data processing device for the energy storage battery pack can implement each step of the temperature data processing method for the energy storage battery pack provided in the foregoing embodiment. The relevant explanations about the temperature data processing method for the energy storage battery pack are applicable to the temperature data processing device for the energy storage battery pack, and will not be elaborated here.

[0053] Figure 5 is a schematic structural diagram of an electronic device in an embodiment of the present application. Please refer to Figure 5, at the hardware level, the electronic device includes a processor, and optionally also includes an internal bus, a network interface, and a memory. Among them, the memory may include a memory, such as a high-speed random access memory (Random-Access Memory, RAM), and may also include a non-volatile memory, such as at least one disk memory, etc. Of course, the electronic device may also include other hardware required for other services.

[0054] The processor, network interface, and memory can be interconnected through the internal bus, and the internal bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, Figure 5 only a bidirectional arrow is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0055] The memory is used to store programs. Specifically, the program may include program code, and the program code includes computer operation instructions. The memory can include a memory and a non-volatile memory, and provide instructions and data to the processor.

[0056] The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it, forming a temperature data processing device for the energy storage battery pack at the logical level. The processor executes the program stored in the memory and is specifically used to perform the following operations:

[0057] Obtain the current information of the energy storage battery in the energy storage battery pack to be measured and the temperature information of the temperature sampling points in the energy storage battery pack. Among them, the temperature information includes the temperature values at at least two preset sampling points in the energy storage battery pack to be measured; input the obtained current information of the energy storage battery into a pre-trained temperature rise analysis model to obtain a predicted temperature change value; and judge whether the temperature rise of the energy storage battery pack to be measured is abnormal according to the temperature values at the sampling points and the predicted temperature change value.

[0058] The above is as described in this application Figure 1The method executed by the energy storage battery pack temperature data processing device disclosed in the illustrated embodiment can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, the steps of the above method can be completed through the integrated logic circuit of the hardware in the processor or instructions in the form of software. The above-mentioned processor can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as being executed and completed by the hardware decoding processor, or executed and completed by a combination of the hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. This storage medium is located in the memory, and the processor reads the information in the memory and combines its hardware to complete the steps of the above method.

[0059] The electronic device can also execute Figure 1 the method executed by the energy storage battery pack temperature data processing device in Figure 1 the illustrated embodiment, and implement the functions of the energy storage battery pack temperature data processing device in

[0060] Embodiments of the present application also propose a computer-readable storage medium that stores one or more programs. The one or more programs include instructions that, when executed by an electronic device including multiple application programs, can enable the electronic device to execute Figure 1 the method executed by the energy storage battery pack temperature data processing device in the illustrated embodiment, and specifically used to execute:

[0061] Obtain the current information of the energy storage battery in the energy storage battery pack to be measured and the temperature information of the temperature sampling points in the energy storage battery pack, where the temperature information includes the temperature values at at least two preset sampling points in the energy storage battery pack to be measured; input the obtained current information of the energy storage battery into a pre-trained temperature rise analysis model to obtain a predicted temperature change value; determine whether the temperature rise of the energy storage battery pack to be measured is abnormal according to the temperature values at the sampling points and the predicted temperature change value.

[0062] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0063] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for realizing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0064] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device realizes the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0065] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for realizing the functions specified in Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0066] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0067] Memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM), and / or non-volatile memory such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0068] Computer-readable media includes both permanent and non-permanent, removable and non-removable media implemented by any method or technology for storing information. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transitory medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transitory media such as modulated data signals and carrier waves.

[0069] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the statement "comprising a..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0070] Those skilled in the art will appreciate that the embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0071] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A method for processing temperature data of an energy storage battery pack, characterized in that: The method comprises: Acquire current information of energy storage batteries in the energy storage battery pack to be tested and temperature information of temperature sampling points in the energy storage battery pack, wherein the temperature information includes temperature values ​​at at least two preset sampling points in the energy storage battery pack to be tested; Inputting the acquired current information of the energy storage battery into a pre-trained temperature rise analysis model to obtain a predicted temperature change value; Whether the temperature rise of the energy storage battery pack to be tested is abnormal is determined according to the temperature value at the sampling point and the predicted temperature change value.

2. The method according to claim 1, characterized in that: The step of inputting the acquired current information of the energy storage battery into a pre-trained temperature rise analysis model to obtain a predicted temperature change value includes: According to the time series, the current information of the energy storage batteries in the energy storage battery pack to be tested at different times is input into the temperature rise analysis model to obtain the predicted temperature change range.

3. The method according to claim 2, characterized in that: The determining whether the temperature rise of the energy storage battery pack to be tested is abnormal according to the temperature value at the sampling point and the predicted temperature change value includes: When the predicted temperature change value of the energy storage battery in the energy storage battery pack to be tested exceeds the predicted temperature change range, a temperature rise abnormality alarm is triggered.

4. The method according to claim 3, characterized in that: The determining whether the temperature rise of the energy storage battery pack to be tested is abnormal according to the temperature value at the sampling point and the predicted temperature change value further includes: Managing the temperature values ​​at the preset sampling points separately; At the same sampling time, when the difference in sampling temperature at different sampling points is greater than the preset threshold, an abnormal temperature rise alarm is triggered.

5. The method according to any one of claims 1 to 4, characterized in that: The preset sampling points include positions symmetrical about the central axis of the energy storage battery pack to be tested.

6. A temperature data processing device for an energy storage battery pack, characterized in that: The device comprises: The first unit obtains current information of energy storage batteries in the energy storage battery pack to be tested and temperature information of temperature sampling points in the energy storage battery pack, wherein the temperature information includes temperature values ​​at at least two preset sampling points in the energy storage battery pack to be tested; The second unit inputs the acquired current information of the energy storage battery into a pre-trained temperature rise analysis model to obtain a predicted temperature change value; The third unit determines whether the temperature rise of the energy storage battery pack to be tested is abnormal according to the temperature value at the sampling point and the predicted temperature change value.

7. A computer storage medium storing instructions, characterized in that: When the instructions are executed individually or collectively by at least one processor of a computing device, the computing device is caused to perform the method according to any one of claims 1 to 5.

8. A computer program product comprising instructions, characterized in that When the instructions are executed individually or collectively by at least one processor of a computing device, the computing device is caused to perform the method according to any one of claims 1 to 5.

9. An electronic device, comprising: processor; and a memory arranged to store computer executable instructions, which, when executed, cause the processor to perform the method as claimed in any one of claims 1 to 5.

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