CN117347868A - Battery thermal runaway early warning evaluation method, system, electronic equipment and storage medium - Google Patents
Battery thermal runaway early warning evaluation method, system, electronic equipment and storage medium Download PDFInfo
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- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
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- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
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- G01R31/385—Arrangements for measuring battery or accumulator variables
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- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/392—Determining battery ageing or deterioration, e.g. state of health
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- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
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Abstract
The application provides a battery thermal runaway early warning evaluation method, a system, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring a first parameter, wherein the first parameter comprises a plurality of temperature indexes, and the plurality of temperature indexes are used for representing temperatures corresponding to different stages of thermal runaway of the battery; the first parameter is selected from a target database which is established based on characteristic parameters obtained by a battery thermal runaway experiment and a battery aging experiment; receiving a second parameter sent by a cloud server, wherein the second parameter is used for evaluating the thermal runaway risk of the battery; establishing an early warning system based on the first parameter and the second parameter, wherein the early warning system is used for representing corresponding early warning indexes and early warning behaviors at different levels; and carrying out early warning grade division on the single batteries based on the early warning system. The method provided by the application is beneficial to better realizing the thermal runaway risk assessment of the battery.
Description
Technical Field
The application relates to the technical field of electrochemical energy storage batteries, in particular to a battery thermal runaway early warning evaluation method, a system, electronic equipment and a storage medium.
Background
With the application of large-scale energy storage systems, the safety of energy storage batteries is getting more and more important. Particularly, the battery thermal runaway fault caused by conditions such as high temperature, overcharge, overdischarge and overcurrent is one of the main reasons for the fault of the energy storage battery. Meanwhile, as the scale of the energy storage system increases, the battery data volume is multiplied, however, the problem that the processing speed is low and the evaluation result is inaccurate due to overlarge data volume and incapability of performing complex algorithm calculation by local calculation exists in the prior art in the implementation of thermal runaway risk evaluation by means of local calculation, so that a battery thermal runaway early warning evaluation method is needed, and the thermal runaway risk evaluation can be rapidly and accurately realized.
Disclosure of Invention
The application provides a battery thermal runaway early warning evaluation method, a system, electronic equipment and a storage medium, which are beneficial to solving the problems of low battery thermal runaway risk evaluation processing speed and inaccurate evaluation results.
In a first aspect, the present application provides a battery thermal runaway early warning evaluation method, including:
acquiring a first parameter, wherein the first parameter comprises a plurality of temperature indexes, and the plurality of temperature indexes are used for representing temperatures corresponding to different stages of thermal runaway of the battery; the first parameter is selected from a target database which is established based on characteristic parameters obtained by a battery thermal runaway experiment and a battery aging experiment;
receiving a second parameter sent by a cloud server, wherein the second parameter is used for evaluating the thermal runaway risk of the battery;
establishing an early warning system based on the first parameter and the second parameter, wherein the early warning system is used for representing corresponding early warning indexes and early warning behaviors at different levels;
and carrying out early warning grade division on the single batteries based on the early warning system.
In the method, the battery is subjected to thermal runaway risk assessment by combining cloud and local calculation results according to the big data processing capacity of the cloud, so that the accuracy of the thermal runaway risk assessment of the battery is improved, and the data calculation processing time is effectively shortened.
In a second aspect, the present application provides a battery thermal runaway warning evaluation device, comprising:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring a first parameter, the first parameter comprises a plurality of temperature indexes, and the plurality of temperature indexes are used for representing temperatures corresponding to different phases of thermal runaway of a battery; the first parameter is selected from a target database which is established based on characteristic parameters obtained by a battery thermal runaway experiment and a battery aging experiment;
the receiving module is used for receiving a second parameter sent by the cloud server, wherein the second parameter is used for evaluating the thermal runaway risk of the battery
The building module is used for building an early warning system based on the first parameter and the second parameter, and the early warning system is used for representing corresponding early warning indexes and early warning behaviors at different levels;
and the dividing module is used for dividing the early warning grades of the single batteries based on the early warning system.
In a third aspect, the present application provides an electronic device, including: a processor and a memory for storing a computer program; the processor is used for running the computer program to realize the battery thermal runaway early warning and evaluating method according to the first aspect.
In a fourth aspect, the present application provides a battery thermal runaway warning evaluation system, comprising: an electronic device and a cloud server as shown in the third aspect.
In a fifth aspect, the present application provides a computer-readable storage medium having stored therein a computer program which, when run on a computer, causes the computer to implement the battery thermal runaway warning evaluation method according to the first aspect.
Drawings
Fig. 1 is an application scenario architecture diagram provided in an embodiment of the present application;
fig. 2 is a flow chart of a battery thermal runaway early warning evaluation method according to an embodiment of the present disclosure;
fig. 3 is a schematic flow chart of establishing a target database according to an embodiment of the present application;
FIG. 4 is a schematic flow chart of calculating thermal runaway evaluation parameters according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a battery thermal runaway warning and evaluating device according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In the embodiment of the present application, unless otherwise specified, the character "/" indicates that the front-rear association object is one or a relationship. For example, A/B may represent A or B. "and/or" describes an association relationship of an association object, meaning that three relationships may exist. For example, a and/or B may represent: a exists alone, A and B exist together, and B exists alone.
It should be noted that the terms "first," "second," and the like in the embodiments of the present application are used for distinguishing between description and not necessarily for indicating or implying a relative importance or number of features or characteristics that are indicated, nor does it imply a sequential order.
In the embodiments of the present application, "at least one" means one or more, and "a plurality" means two or more. Furthermore, "at least one item(s)" below, or the like, refers to any combination of these items, and may include any combination of single item(s) or plural items(s). For example, at least one (one) of A, B or C may represent: a, B, C, a and B, a and C, B and C, or A, B and C. Wherein each of A, B, C may itself be an element or a collection comprising one or more elements.
In this application embodiments, "exemplary," "in some embodiments," "in another embodiment," etc. are used to indicate an example, instance, or illustration. Any embodiment or design described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, the term use of an example is intended to present concepts in a concrete fashion.
"of", "corresponding" and "corresponding" in the embodiments of the present application may be sometimes used in combination, and it should be noted that the meaning to be expressed is consistent when the distinction is not emphasized. In the embodiments of the present application, communications and transmissions may sometimes be mixed, and it should be noted that, when the distinction is not emphasized, the meaning expressed is consistent. For example, a transmission may include sending and/or receiving, either nouns or verbs.
The equal to that relates to in this application embodiment can be with being greater than even using, is applicable to the technical scheme that adopts when being greater than, also can be with being less than even using, is applicable to the technical scheme that adopts when being less than. It should be noted that when the number is equal to or greater than the sum, the number cannot be smaller than the sum; when the value is equal to or smaller than that used together, the value is not larger than that used together.
The current thermal runaway risk assessment of the battery is based on the result of local calculation, but the thermal runaway risk assessment based on the local calculation has the problems of insufficient calculation power, low calculation speed and the like due to large data volume, and a local battery management system (Battery Management System, BMS for short) cannot perform complex algorithm calculation, so that more accurate and rapid thermal runaway risk assessment cannot be realized, and a better solution to the safety problem caused by thermal runaway and expansion of the energy storage battery cannot be provided.
Based on the above problems, the embodiment of the application provides a battery thermal runaway early warning evaluation method, which is characterized in that battery data is uploaded to a cloud by means of cloud big data processing capability, and thermal runaway risk evaluation is performed on a battery by combining cloud and local calculation results, so that on one hand, the accuracy of the battery thermal runaway risk evaluation is improved, and on the other hand, the data calculation processing time is effectively reduced.
The battery thermal runaway warning evaluation method provided in the embodiment of the present application will now be described with reference to fig. 1 to 6.
Fig. 1 is an application scenario architecture diagram provided in an embodiment of the present application. As shown in fig. 1, the application scenario includes a cloud server and an electronic device, where the electronic device and the cloud server may perform real-time data interaction. And the electronic equipment uploads battery data acquired by the local BMS to the cloud server, receives a thermal runaway early warning evaluation result calculated and returned by the cloud server, and establishes a thermal runaway early warning system by combining the early warning evaluation result calculated by the local BMS. Based on the early warning system, the early warning grades of the single batteries can be divided, the risk assessment and early warning of the thermal runaway of the batteries are better realized, and when the thermal runaway fault occurs, relevant technicians can implement corresponding early warning behaviors according to the early warning grades of the single batteries so as to remove the fault. The embodiment of the application does not limit the type of the electronic device, and the electronic device may be a desktop computer, a tablet computer, a notebook computer, a palm computer, an ultra-mobile personal computer (UMPC), a netbook, or the like.
Fig. 2 is a flow chart of a battery thermal runaway early warning evaluation method according to an embodiment of the present application, which specifically includes the following steps:
step S21, acquiring a first parameter, wherein the first parameter comprises a plurality of temperature indexes, and the temperature indexes are used for representing temperatures corresponding to different phases of thermal runaway of the battery; the first parameter is selected from a target database established based on characteristic parameters obtained from a thermal runaway test and a battery aging test.
Specifically, a first parameter is selected from a target database, the first parameter including a plurality of temperature indicators for characterizing temperatures corresponding to different phases of thermal runaway of the battery. Fig. 3 is a schematic flow chart of establishing the target database according to the embodiment of the present application, where the thermal runaway characteristic parameters including a temperature index, a temperature rise rate, a voltage drop rate, and the like are obtained through a thermal runaway experiment of the battery, where the temperature index is used to represent temperatures corresponding to different phases of thermal runaway of the battery, for example, the temperature index may be T1, T2, and T3, T1 represents an abnormal heating temperature, T2 represents a thermal runaway trigger temperature, and T3 represents a thermal runaway maximum temperature. The temperature indexes T1, T2 and T3 are merely exemplary, and those skilled in the art may divide temperatures corresponding to different phases of thermal runaway of the battery according to actual needs, which is not limited in this application. Test characteristic parameters under different SOH (State of Health) and SOC (State of Charge) conditions of the battery, including Charge and discharge terminal voltage, self-discharge rate and the like, are obtained through a battery aging experiment. And a full life cycle thermal runaway characteristic parameter database, i.e. a target database, is established based on the thermal runaway characteristic parameter and the test characteristic parameter with SOH greater than a threshold value (e.g. 70%).
Step S22, receiving a second parameter sent by the cloud server, wherein the second parameter is used for evaluating the thermal runaway risk of the battery.
Specifically, the local BMS collects battery data of all the single batteries, wherein the battery data at least comprises voltage, temperature, current, charge state, battery charge and discharge state, battery serial number and collection time of the single batteries.
Optionally, in order to improve the reliability of the data and the accuracy of the evaluation result, the collected data may be cleaned to remove abnormal data in the battery data. Because various abnormal conditions exist under the actual operation working condition, such as feedback current abnormality, single voltage drop and the like, corresponding cleaning strategies need to be specified for different abnormal data. The abnormal data comprise dislocation data, overflow data, jump data, missing data, single voltage drop data, temperature abnormal data, unsynchronized data and the like.
The electronic equipment uploads the battery data collected by the local BMS to the cloud server, and can select a wired communication connection mode or a wireless data network communication connection mode to upload the data, wherein the wired communication connection mode can be one or more of RS485 wired communication, RS232 wired communication and modbusTCP, IEC61850, and the wireless data network communication connection mode can be one or more of low-frequency wireless communication, zigBee communication, WIFI, bluetooth, 3G network communication, 4G network communication and 5G network communication. In order to ensure data security, in wireless data network communication, the battery data is uploaded through a message queue telemetry transmission (Message Queuing Telemetry Transport, MQTT) protocol, authentication user names and passwords are required when equipment logs in the MQTT, and meanwhile, an advanced encryption standard (Advanced Encryption Standard, AES) algorithm is used for encrypting a message containing the battery data.
And the cloud server receives and stores all the battery data, screens the data and selects partial data as a calculation basis for subsequent algorithm evaluation. Specifically, the characteristic segments are selected from the charge-discharge curves of the individual single batteries in proportion, for example, the battery data of the charge end or the discharge end is selected as the calculation basis of the subsequent algorithm evaluation. And the cloud server carries out thermal runaway evaluation calculation by adopting an intelligent analysis algorithm based on the battery data to obtain a second parameter, namely the parameter for evaluating the thermal runaway risk.
Optionally, the cloud server calculates the thermal runaway evaluation parameter L by using a battery voltage anomaly analysis algorithm based on the battery voltage jump property, as shown in fig. 4, and fig. 4 is a schematic flow chart of calculating the thermal runaway evaluation parameter according to an embodiment of the present application, which specifically includes the following steps:
step S41, recording the voltage information of all the single batteries in a certain time to obtain a battery time-voltage matrix. Specifically, the battery time-voltage matrix is M T-V ，
M T-V
＝{(V 11 ,V 12 ,V 13 ,…,V 1T ),(V 21 ,V 22 ,V 23 ,…,V 2T ),(V 31 ,V 32 ,V 33 ,…,V 3T ),…,(V N1 ,V N2 ,V N3 ,…,V NT )}
Wherein T represents a time number, N represents a number of the battery, and V represents a battery voltage, e.g., V 32 The voltage value of the battery with the battery number 3 at the time of the time number 2 is shown.
Step S42, calculating the average voltage value of all the single batteries in a certain time sequence number based on the battery time-voltage matrix to obtain a battery time-average voltage matrix.
Specifically, the formulas for calculating the average voltage values of all the unit cells are shown as formulas 1-1, 1-2, 1-3, 1-4,
…
wherein,indicating the average voltage value of all the cells at time number 1, < >>The average voltage value of all the single cells at time number T is shown.
Thus, the resulting battery time-average voltage matrixIs that
Step S43, calculating the voltage standard deviation of all the single batteries with a certain time sequence number as an evaluation parameter K1 based on the battery time-average voltage matrix.
Specifically, formulas for calculating the standard deviation of the voltages of all the single batteries at a certain moment are shown as formulas 2-1, 2-2, 2-3 and 2-4,
...
wherein S is t＝1 Represents the standard deviation of the voltages of all the single batteries when the time sequence number is 1, S t＝T The standard deviation of the voltages of all the single cells at time number T is shown.
Step S44, calculating the standard deviation of the voltage of a certain single battery in a certain period of time as the evaluation parameter K2 based on the battery time-average voltage matrix.
Specifically, the formulas for calculating the standard deviation of the voltages of a certain single battery in a certain period of time are shown as formulas 3-1, 3-2, 3-3 and 3-4,
...
wherein S is n＝1 Represents the standard deviation of the voltage of the battery number 1 in a certain period of time, S n＝N The standard deviation of the voltage of the battery number N in a certain period of time is shown.
In step S45, weights are assigned to the parameter K1 and the parameter K2, and a weighted average method is used to calculate the thermal runaway risk evaluation parameter L.
Specifically, a hierarchical analysis method or an entropy weight method can be adopted to distribute parameter weights, and as an example, the weight of the parameter K1 is a1, the weight of the parameter K2 is a2, the calculation formula of the thermal runaway risk assessment parameter L is shown as a formula 4-1,
L＝a1×K1+a2×K2 (4-1)
it can be understood that the parameter K1 or the parameter K2 may be directly used as the thermal runaway risk evaluation parameter L, or a plurality of parameters (more than the parameters K1 and K2) may be adopted to allocate weights, and a weighted average method is adopted to calculate the thermal runaway risk evaluation parameter L, for the latter, adding the evaluation parameter to the evaluation parameter may improve the accuracy of the thermal runaway risk evaluation. Because a plurality of evaluation parameters are fused to evaluate the thermal runaway risk, the influence caused by deviation of a single evaluation parameter is avoided, and the robustness of the algorithm is improved.
It should be noted that other intelligent analysis algorithms may be used to calculate the thermal runaway evaluation parameter L, such as the voltage sharp algorithm, the mean normalization algorithm, etc., which is not limited in this application.
Step S23, an early warning system is established based on the first parameter and the second parameter, and the early warning system is used for representing corresponding early warning indexes and early warning behaviors at different levels.
Specifically, an early warning system is established based on a first parameter (the first parameter includes T1, T2 and T3) acquired from the full life cycle thermal runaway characteristic parameter database and a second parameter (i.e., thermal runaway risk evaluation parameter L) transmitted by the cloud server, and the early warning system may be a hierarchical early warning system. Specifically, the early warning system comprises a first-stage early warning, a second-stage early warning and a third-stage early warning, wherein the reference index, the statistical basis, the early warning time and the early warning behavior corresponding to different early warning grades are shown in the table 1,
table 1 hierarchical table of early warning system
Wherein, the reference index represents the basis for dividing the early warning level; the statistical basis represents the scene of the statistical data, namely, corresponding data are counted under the scene; the early warning time represents the time of early warning in advance of different early warning grades, the lower the grade is, the longer the early warning time is, and the higher the grade is, the shorter the early warning time is; the early warning behavior represents operation and maintenance advice, when an early warning is sent out, the equipment end or the owner end needs to perform corresponding actions or operations, and the lower the early warning level is, the lighter the early warning behavior is needed.
The thermal runaway risk evaluation parameter L and a plurality of temperature indexes are used as grading standards of different dangerous degrees, so that the thermal runaway risk of the energy storage battery can be effectively evaluated, and then safety early warning can be carried out.
And step S24, carrying out early warning grade division on the single batteries based on the early warning system.
The early warning system is used for classifying the single batteries, so that the single batteries are managed in a classified mode and early warning is facilitated, and the thermal runaway risk of the single batteries can be well estimated.
Fig. 5 is a schematic structural diagram of a battery thermal runaway warning and evaluating device according to an embodiment of the present application, as shown in fig. 5, the battery thermal runaway warning and evaluating device 50 may include:
an acquisition module 51 for acquiring a first parameter including a plurality of temperature indicators for characterizing temperatures corresponding to different phases of thermal runaway of the battery; the first parameter is selected from a target database which is established based on characteristic parameters obtained by a battery thermal runaway experiment and a battery aging experiment;
a receiving module 52, configured to receive a second parameter sent by the cloud server, where the second parameter is used to evaluate a thermal runaway risk of the battery;
the establishing module 53 is configured to establish an early warning system based on the first parameter and the second parameter, where the early warning system is used to characterize early warning indicators and early warning behaviors corresponding to different levels;
the dividing module 54 is configured to divide the unit batteries into early-warning grades based on the early-warning system.
In one possible implementation, the apparatus 50 further includes an acquisition module configured to acquire battery data;
in one possible implementation manner, the apparatus 50 further includes a cleaning module, configured to clean the collected battery data to remove abnormal data;
in one possible implementation manner, the apparatus 50 further includes an uploading module, configured to upload the battery data to the cloud server;
in one possible implementation manner, the uploading module further comprises a data security module, which is used for guaranteeing the security of data uploading, and is specifically characterized in that a wireless data network is adopted to upload the battery data through a message queue telemetry transmission protocol, and an advanced encryption standard algorithm is adopted to encrypt a message containing the battery data.
The battery thermal runaway warning and evaluating device 50 provided in the embodiment shown in fig. 5 may be used to implement the technical solution of the method embodiment shown in the application, and the implementation principle and technical effects may be further described with reference to the related description in the method embodiment.
It should be understood that the above division of the respective modules of the battery thermal runaway warning and evaluating device 50 shown in fig. 5 is merely a division of logic functions, and may be fully or partially integrated into one physical entity or may be physically separated. And these modules may all be implemented in software in the form of calls by the processing element; or can be realized in hardware; it is also possible that part of the modules are implemented in the form of software called by the processing element and part of the modules are implemented in the form of hardware. For example, the detection module may be a separately established processing element or may be implemented integrated in a certain chip of the electronic device. The implementation of the other modules is similar. In addition, all or part of the modules can be integrated together or can be independently implemented. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in a software form.
For example, the modules above may be one or more integrated circuits configured to implement the methods above, such as: one or more specific integrated circuits (Application Specific Integrated Circuit; hereinafter ASIC), or one or more microprocessors (Digital Signal Processor; hereinafter DSP), or one or more field programmable gate arrays (Field Programmable Gate Array; hereinafter FPGA), etc. For another example, the modules may be integrated together and implemented in the form of a System-On-a-Chip (SOC).
In the above embodiments, the processor may include, for example, a CPU, a DSP, a microcontroller, or a digital signal processor, and may further include a GPU, an embedded Neural Network Processor (NPU) and an image signal processor (Image Signal Processing; ISP), where the processor may further include a necessary hardware accelerator or a logic processing hardware circuit, such as an ASIC, or one or more integrated circuits for controlling the execution of the program in the technical solution of the present application, and so on. Further, the processor may have a function of operating one or more software programs, which may be stored in a storage medium.
Embodiments of the present application also provide a computer-readable storage medium having a computer program stored therein, which when run on a computer, causes the computer to perform the methods provided by the embodiments shown in the present application.
Embodiments of the present application also provide a computer program product comprising a computer program which, when run on a computer, causes the computer to perform the methods provided by the embodiments shown in the present application.
An exemplary electronic device provided in an embodiment of the present application is further described below in conjunction with fig. 6. Fig. 6 shows a schematic structural diagram of an electronic device 6000.
The electronic device 6000 may include: at least one processor; and at least one memory communicatively coupled to the processor, wherein: the memory stores program instructions executable by the processor, and the processor can execute the battery thermal runaway early warning and evaluating method provided by the embodiment of the application when the processor calls the program instructions.
Fig. 6 illustrates a block diagram of an exemplary electronic device 6000 suitable for use in implementing embodiments of the present application. The electronic device 6000 shown in fig. 6 is only an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present application.
As shown in fig. 6, the electronic device 6000 is in the form of a general purpose computing device. Components of electronic device 6000 may include, but are not limited to: one or more processors 6010, a memory 6020, a communication bus 6040 that connects the various system components (including the memory 6020 and the processor 6010), and a communication interface 6030.
Communication bus 6040 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include industry Standard architecture (Industry Standard Architecture; hereinafter ISA) bus, micro channel architecture (Micro Channel Architecture; hereinafter MAC) bus, enhanced ISA bus, video electronics standards Association (Video Electronics Standards Association; hereinafter VESA) local bus, and peripheral component interconnect (Peripheral Component Interconnection; hereinafter PCI) bus.
Electronic device 6000 typically includes a variety of computer system readable media. Such media can be any available media that can be accessed by the electronic device and includes both volatile and nonvolatile media, removable and non-removable media.
Memory 6020 may include computer system-readable media in the form of volatile memory, such as random access memory (Random Access Memory; hereinafter: RAM) and/or cache memory. The electronic device may further include other removable/non-removable, volatile/nonvolatile computer system storage media. Although not shown in fig. 6, a magnetic disk drive for reading from and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable non-volatile optical disk (e.g., a compact disk read only memory (Compact Disc Read Only Memory; hereinafter CD-ROM), digital versatile read only optical disk (Digital Video Disc Read Only Memory; hereinafter DVD-ROM), or other optical media) may be provided. In these cases, each drive may be connected to communication bus 6040 by one or more data medium interfaces. Memory 6020 may comprise at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of the embodiments of the application.
A program/utility having a set (at least one) of program modules can be stored in the memory 6020, including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules generally perform the functions and/or methods in the embodiments described herein.
The electronic device 6000 may also communicate with one or more external devices (e.g., keyboard, pointing device, display, etc.), with one or more devices which enable a user to interact with the electronic device, and/or with any devices which enable the electronic device to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication can occur through a communication interface 6030. Also, the electronic device 6000 may communicate with one or more networks, such as a local area network (Local Area Network; hereinafter: LAN), a wide area network (Wide Area Network; hereinafter: WAN) and/or a public network, such as the Internet, through a network adapter (not shown in FIG. 6) which may communicate with other modules of the electronic device via a communication bus 6040. It should be appreciated that although not shown in fig. 6, other hardware and/or software modules may be used in connection with electronic device 6000, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, disk arrays (Redundant Arrays of Independent Drives; hereinafter RAID) systems, tape drives, data backup storage systems, and the like.
The processor 6010 executes various functional applications and data processing by running programs stored in the memory 6020, for example, implements the methods provided by the embodiments of the present application.
It should be understood that the connection relationship between the modules illustrated in the embodiments of the present application is only illustrative, and does not limit the structure of the electronic device 6000. In other embodiments of the present application, the electronic device 6000 may also use different interfacing manners or a combination of multiple interfacing manners in the foregoing embodiments.
In the above embodiments, the processor may include, for example, a CPU, a DSP, a microcontroller, or a digital signal processor, and may further include a GPU, an embedded Neural Network Processor (NPU) and an image signal processor (Image Signal Processing; ISP), where the processor may further include a necessary hardware accelerator or a logic processing hardware circuit, such as an ASIC, or one or more integrated circuits for controlling the execution of the program in the technical solution of the present application, and so on. Further, the processor may have a function of operating one or more software programs, which may be stored in a storage medium.
Those of ordinary skill in the art will appreciate that the various elements and algorithm steps described in the embodiments disclosed herein can be implemented as a combination of electronic hardware, computer software, and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In several embodiments provided herein, any of the functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (hereinafter referred to as ROM), a random access Memory (Random Access Memory) and various media capable of storing program codes such as a magnetic disk or an optical disk.
The foregoing is merely specific embodiments of the present application, and any person skilled in the art may easily conceive of changes or substitutions within the technical scope of the present application, which should be covered by the protection scope of the present application. The protection scope of the present application shall be subject to the protection scope of the claims.
Claims (11)
1. A battery thermal runaway warning assessment method, the method comprising:
acquiring a first parameter, wherein the first parameter comprises a plurality of temperature indexes, and the plurality of temperature indexes are used for representing temperatures corresponding to different stages of thermal runaway of the battery; the first parameter is selected from a target database which is established based on characteristic parameters obtained by a battery thermal runaway experiment and a battery aging experiment;
receiving a second parameter sent by a cloud server, wherein the second parameter is used for evaluating the thermal runaway risk of the battery;
establishing an early warning system based on the first parameter and the second parameter, wherein the early warning system is used for representing corresponding early warning indexes and early warning behaviors at different levels;
and carrying out early warning grade division on the single batteries based on the early warning system.
2. The method of claim 1, further comprising,
collecting battery data;
and uploading the battery data to the cloud server.
3. The method of claim 2, wherein the step of determining the position of the substrate comprises,
the battery data includes at least a voltage, a temperature, and a current of the unit battery.
4. The method of claim 2, wherein the step of determining the position of the substrate comprises,
and the second parameter is an evaluation parameter obtained by the cloud server through preset algorithm analysis based on the battery data.
5. The method of claim 4, wherein the step of determining the position of the first electrode is performed,
and if the evaluation parameters comprise a plurality of evaluation parameters, carrying out weight distribution on the plurality of evaluation parameters, and calculating by adopting a weighted average method to obtain the second parameter.
6. The method of claim 1, wherein the step of determining the position of the substrate comprises,
the temperature index comprises T1, T2 and T3, the early warning system comprises a first stage early warning, a second stage early warning and a third stage early warning, wherein,
when the value of the second parameter is more than or equal to 0 and less than 0.1, the temperature of the single battery is more than T1 and less than T2, and the first-stage early warning is performed;
when the value of the second parameter is more than or equal to 0.1 and less than 1, the temperature of the single battery is more than T1 and less than T2, and the second-stage early warning is performed;
and when the value of the second parameter is greater than or equal to 1, the temperature of the single battery is greater than T3, the temperature rise rate of the single battery is greater than 1 ℃/s, and the voltage difference of the single battery is greater than 1V, the third-stage early warning is performed.
7. The method of claim 2, wherein after the collecting the battery data, the method further comprises,
and cleaning the collected battery data to remove abnormal data.
8. The method of claim 2, wherein uploading the battery data to the cloud server comprises,
and uploading the battery data through a message queue telemetry transmission protocol by adopting a wireless data network, and encrypting a message containing the battery data by adopting an advanced encryption standard algorithm.
9. An electronic device, comprising: a processor and a memory for storing a computer program; the processor is configured to run the computer program to implement the battery thermal runaway warning evaluation method according to any one of claims 1 to 8.
10. A battery thermal runaway early warning evaluation system is characterized in that,
comprising the electronic device of claim 9 and a cloud server.
11. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when run on a computer, implements the battery thermal runaway warning evaluation method according to any one of claims 1 to 8.
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