Method, System, Device and Medium for Detecting Thermal Runaway Fault of Electric Vehicle Power Battery

Abstract

The present application provides a method, a system, a device and a medium for detecting a thermal runaway fault of an electric vehicle power battery, belonging to the technical field of battery detection. The method includes: obtaining an original current time series generated by the operation of the power battery and performing preprocessing to obtain a current time series; performing sampling analysis on the current time series to obtain a plurality of first current amplitude standard deviations; evaluating the plurality of first current amplitude standard deviations according to a standard deviation threshold to obtain a preliminary detection result of the thermal runaway fault of the power battery; when it is preliminarily detected that the power battery may have a thermal runaway fault, performing Fourier transform on the current time series to obtain a current frequency domain series; performing sampling analysis on the current frequency domain series to obtain a plurality of second current amplitude standard deviations; evaluating the plurality of second current amplitude standard deviations according to an evaluation criterion to obtain a final detection result of the thermal runaway fault of the power battery. The present application can accurately detect whether the power battery has a thermal runaway fault.

Description

Technical Field

[0001] This application relates to the technical field of battery detection, and particularly to a method, system, device and medium for detecting thermal runaway faults of power batteries for electric vehicles. Background Art

[0002] In new energy vehicles, the chemical substances inside the power battery react more rapidly under conditions such as high temperature, short circuit or abnormal discharge, releasing a large amount of heat, which is likely to cause thermal runaway faults. In the prior art, thermal runaway fault detection is usually achieved by monitoring the current of the power battery and directly judging the threshold value. However, due to the step load change and switching operation of the inverter on which the power battery depends during operation, it will interfere with the current of the power battery, making it impossible for the prior art to accurately detect thermal runaway faults. Summary of the Invention

[0003] The main purpose of this application is to propose a method, system, device and medium for detecting thermal runaway faults of power batteries for electric vehicles, and to more accurately detect the thermal runaway faults that occur in the power battery by combining time-domain analysis and frequency-domain analysis.

[0004] To achieve the above object, on the one hand, this application proposes a method for detecting thermal runaway faults of power batteries for electric vehicles, and the method includes:

[0005] When the power battery is in an operating state, obtain the original current time series of the power battery;

[0006] Preprocess the original current time series to obtain a current time series;

[0007] Perform sampling analysis on the current time series to obtain a number of first current amplitude standard deviations;

[0008] Evaluate the number of first current amplitude standard deviations according to a preset standard deviation threshold to obtain a preliminary detection result of the thermal runaway fault of the power battery;

[0009] When the preliminary detection result of the thermal runaway fault indicates that there is a possibility that the power battery has a thermal runaway fault, perform Fourier transform on the current time series to obtain a current frequency domain series;

[0010] Perform sampling analysis on the current frequency domain series to obtain a number of second current amplitude standard deviations;

[0011] Evaluate the number of second current amplitude standard deviations according to a preset evaluation criterion to obtain a final detection result of the thermal runaway fault of the power battery.

[0012] Further, the preprocessing of the original current time series to obtain the current time series includes:

[0013] Extract the AC component from the original current time series to obtain the first current time series;

[0014] Filter the noise from the first current time series to obtain the current time series.

[0015] Further, the sampling analysis of the current time series to obtain several first current amplitude standard deviations includes:

[0016] Perform sliding time-domain sampling on the current time series according to a preset first moving window and a preset first moving step size to obtain several current time sampling sequences;

[0017] Determine the first current amplitude standard deviation corresponding to each current time sampling sequence according to all the current amplitudes included in each current time sampling sequence.

[0018] Further, the evaluation of the several first current amplitude standard deviations according to a preset standard deviation threshold to obtain a preliminary detection result of the thermal runaway fault of the power battery includes:

[0019] Determine the first average value and the first standard deviation according to the several first current amplitude standard deviations;

[0020] Adjust the standard deviation threshold according to the first average value and the first standard deviation;

[0021] Determine a preliminary detection result of the thermal runaway fault of the power battery according to the relationship between the several first current amplitude standard deviations and the adjusted standard deviation threshold.

[0022] Further, the sampling analysis of the current frequency domain sequence to obtain several second current amplitude standard deviations includes:

[0023] Perform sliding frequency-domain sampling on the current frequency domain sequence according to a preset second moving window and a preset second moving step size to obtain several current frequency domain sampling sequences;

[0024] Determine the second current amplitude standard deviation corresponding to each current frequency domain sampling sequence according to all the current amplitudes included in each current frequency domain sampling sequence.

[0025] Further, the evaluation of the several second current amplitude standard deviations according to a preset evaluation criterion to obtain a final detection result of the thermal runaway fault of the power battery includes:

[0026] Obtain a plurality of predetermined standard deviations of reference current amplitudes, the number of the plurality of standard deviations of reference current amplitudes being the same as the number of the plurality of standard deviations of second current amplitudes, the plurality of standard deviations of reference current amplitudes being obtained by performing frequency-domain analysis on a reference original current time series of the power battery, and the reference original current time series being generated by the power battery during operation without a thermal runaway fault;

[0027] Determine a final detection result of the thermal runaway fault of the power battery according to the relationship between the plurality of standard deviations of second current amplitudes and the plurality of standard deviations of reference current amplitudes.

[0028] Further, the plurality of standard deviations of reference current amplitudes are obtained through the following steps:

[0029] Preprocess the reference original current time series to obtain a reference current time series;

[0030] Perform Fourier transform on the reference current time series to obtain a reference current frequency-domain series;

[0031] According to the second moving window and the second moving step, perform sampling analysis on the reference current frequency-domain series to obtain the plurality of standard deviations of reference current amplitudes.

[0032] To achieve the above object, another aspect of the present application proposes a thermal runaway fault detection system for an electric vehicle power battery, the system including:

[0033] An acquisition module, configured to acquire the original current time series of the power battery when the power battery is in an operating state;

[0034] A first processing module, configured to preprocess the original current time series to obtain a current time series;

[0035] A first analysis module, configured to perform sampling analysis on the current time series to obtain a plurality of first standard deviations of current amplitudes;

[0036] A first evaluation module, configured to evaluate the plurality of first standard deviations of current amplitudes according to a preset standard deviation threshold to obtain a preliminary detection result of the thermal runaway fault of the power battery;

[0037] A second processing module, configured to perform Fourier transform on the current time series to obtain a current frequency-domain series when the preliminary detection result of the thermal runaway fault indicates that there is a possibility of the power battery having a thermal runaway fault;

[0038] A second analysis module, configured to perform sampling analysis on the current frequency-domain series to obtain a plurality of second standard deviations of current amplitudes;

[0039] A second evaluation module, configured to evaluate the plurality of second current amplitude standard deviations according to a preset evaluation criterion, so as to obtain a final detection result of the thermal runaway fault of the power battery.

[0040] To achieve the above object, another aspect of the present application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the above method is implemented.

[0041] To achieve the above object, another aspect of the present application provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the above method is implemented.

[0042] The present application at least includes the following beneficial effects: By sampling and analyzing the current sequence in the time domain, when using the plurality of first current amplitude standard deviations obtained from the analysis to evaluate and preliminarily judge that the power battery may have a thermal runaway fault, considering that the step load change and switching operation of the inverter on which the power battery depends during operation will interfere with the evaluation result in the time domain, the current sequence in the time domain is converted to the frequency domain and then sampled and analyzed. Finally, the plurality of second current amplitude standard deviations obtained from the analysis are used for evaluation to determine whether the power battery has a thermal runaway fault. Through this dual evaluation method, the accuracy and reliability of the final thermal runaway fault detection result can be improved. Description of the Drawings

[0043] Figure 1 It is a schematic flowchart of a method for detecting a thermal runaway fault of an electric vehicle power battery provided by an embodiment of the present application;

[0044] Figure 2 It is a schematic structural diagram of a system for detecting a thermal runaway fault of an electric vehicle power battery provided by an embodiment of the present application;

[0045] Figure 3 It is a schematic hardware structure diagram of an electronic device provided by an embodiment of the present application. Detailed Embodiments

[0046] In order to make the objectives, technical solutions and advantages of the present application more clear and understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the embodiments of the present application. They are only examples of systems and methods consistent with some aspects of the embodiments of the present application detailed in the appended claims.

[0047] It can be understood that the terms "first", "second", etc. used in the present application may be used herein to describe various concepts, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of the present application, the first information may also be referred to as the second information. Similarly, the second information may also be referred to as the first information. Depending on the context, the words "if", "when" as used herein may be interpreted as "when...", "while...", or "in response to determining".

[0048] The terms "at least one", "a plurality of", "each", "any one", etc. used in the present application, at least one includes one, two or more than two, a plurality includes two or more than two, each refers to each of the corresponding plurality, and any one refers to any one of the plurality.

[0049] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

[0050] The power battery in a new energy vehicle may cause a fire or explosion under specific conditions. The specific conditions include internal short circuits caused by production defects or mechanical damage, battery short circuits caused by external impacts or damage, or the charging range or discharge range exceeding the battery design range, etc. The main principle is that the internal chemical reactions of the power battery accelerate under high temperature, short circuit or abnormal discharge conditions, releasing a large amount of heat, which easily causes a thermal runaway failure.

[0051] In the prior art, some scholars have proposed to use temperature monitoring or gas monitoring methods to achieve thermal runaway fault detection. The temperature monitoring method refers to real-time monitoring of the temperature of the power battery during operation, and when the temperature is abnormal, it can prompt the risk of thermal runaway. The gas monitoring method refers to real-time monitoring of the gases released by the power battery during operation, and when it is found that gases such as hydrogen and carbon dioxide are released, it can prompt the risk of thermal runaway. However, these two methods cannot accurately determine thermal runaway faults. Other scholars have proposed to use current monitoring to achieve thermal runaway fault detection, that is, monitoring the current generated by the power battery during operation and directly judging based on a threshold. However, since an inverter is needed in an electric vehicle to convert the direct current provided by the power battery into alternating current to drive the motor, the step load change and switching operation of the inverter will cause certain interference to the current of the power battery, making it impossible for this current monitoring method to accurately achieve thermal runaway fault detection.

[0052] In view of this, the embodiments of the present application provide a method, system, device and medium for detecting thermal runaway faults of electric vehicle power batteries. This solution samples and analyzes the current sequence in the time domain. When using several standard deviations of the first current amplitude obtained from the analysis to evaluate and preliminarily judge that the power battery may have a thermal runaway fault, considering that the step load change and switching operation of the inverter on which the power battery depends during operation will interfere with the evaluation result in the time domain, the current sequence in the time domain is converted to the frequency domain and then sampled and analyzed. Finally, several standard deviations of the second current amplitude obtained from the analysis are used for evaluation to determine whether the power battery has a thermal runaway fault. Through this dual evaluation method, the accuracy and reliability of the final thermal runaway fault detection result can be improved.

[0053] A method for detecting thermal runaway faults of electric vehicle power batteries provided by the embodiments of the present application relates to the technical field of battery detection and can be applied to a terminal, a server, or software running on a terminal or a server. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, a vehicle-mounted terminal, etc., but is not limited thereto; the server can be configured as an independent physical server, or as a server cluster or distributed system composed of multiple physical servers, or as a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network; the software can be an application that implements the above-mentioned method for detecting thermal runaway faults of electric vehicle power batteries, etc., but is not limited to the above forms.

[0054] This application can be used in numerous general or specific computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and so on. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0055] Figure 1 is an alternative flowchart of a method for detecting thermal runaway faults in an electric vehicle's power battery provided by an embodiment of this application. Figure 1 The method in may but is not limited to include steps S101 to S107:

[0056] Step S101, when the power battery is in an operating state, obtain the original current time series of the power battery;

[0057] Step S102, preprocess the original current time series to obtain the current time series;

[0058] Step S103, perform sampling analysis on the current time series to obtain a number of first current amplitude standard deviations;

[0059] Step S104, evaluate the number of first current amplitude standard deviations according to a preset standard deviation threshold to obtain a preliminary detection result of the thermal runaway fault of the power battery;

[0060] Step S105, when the preliminary detection result of the thermal runaway fault indicates that there is a possibility of the power battery having a thermal runaway fault, perform Fourier transform on the current time series to obtain the current frequency domain series;

[0061] Step S106, perform sampling analysis on the current frequency domain series to obtain a number of second current amplitude standard deviations;

[0062] Step S107, evaluate the number of second current amplitude standard deviations according to a preset evaluation criterion to obtain the final detection result of the thermal runaway fault of the power battery.

[0063] Steps S101 to S107 illustrated in the embodiments of the present application can, by combining time-domain analysis and frequency-domain analysis, more accurately detect the thermal runaway faults that occur in the power battery, and overcome the adverse effects of the step load changes and switching operations of the inverter on which the power battery depends during operation on the detection results of thermal runaway faults.

[0064] In some embodiments, the above step S102 may but is not limited to include steps S201 to S202:

[0065] Step S201: Extract the AC component from the original current time series to obtain the first current time series; in the present application, the extraction of the current AC component can be achieved by using the difference method, window function method, wavelet transform, etc., and the present application does not make any limitations in this regard;

[0066] Step S202: Filter out the noise from the first current time series to obtain the current time series; in the present application, it is preferably to use a low-pass filter to filter out the switching noise from the inverter on which the power battery depends during operation carried by the first current time series.

[0067] Steps S201 to S202 illustrated in the embodiments of the present application can provide reliable data support for the subsequent thermal runaway fault detection process by extracting the AC component and filtering out the noise from the original current time series generated during the operation of the power battery.

[0068] In some embodiments, the above step S103 may but is not limited to include steps S301 to S302:

[0069] Step S301: Perform sliding time-domain sampling on the current time series according to a preset first moving step size and a preset first moving window to obtain a plurality of current time sampling sequences;

[0070] Specifically, denote the current time series as , is the current amplitude corresponding to the th moment, is the number of all current amplitudes included in the current time series, which can be understood as the current time series contains current amplitudes corresponding to moments. When the width of the first moving window is and the first moving step size is , and are both positive integers and , starting from the first current amplitude Start by using the first moving window to perform the first time-domain sampling to obtain , then use the first moving step size to slide the first moving window along the time axis, and use the slid first moving window to perform the second time-domain sampling to obtain , subsequently use the first moving step size to slide the first moving window along the time axis again, and use the slid first moving window to perform the third time-domain sampling to obtain , and so on until a number of current-time sampling sequences are obtained.

[0071] Step S302: According to all the current amplitudes included in each current-time sampling sequence, determine the first current amplitude standard deviation corresponding to each current-time sampling sequence through the following expression:

[0072]

[0073] In the formula, is the first current amplitude standard deviation corresponding to the th current-time sampling sequence sampled through the above step S301, can also be understood as the number of all current amplitudes included in the th current-time sampling sequence, is the th current amplitude included in the th current-time sampling sequence, is the average value of all current amplitudes included in the th current-time sampling sequence.

[0074] Steps S301 to S302 shown in the embodiments of the present application, by using the first moving window to perform sliding time-domain sampling on the current-time sequence and calculating the current amplitude standard deviation for each sampled current-time sampling sequence, can provide specific data support for the subsequent preliminary thermal runaway fault detection steps.

[0075] In some embodiments, the above step S104 may but is not limited to include steps S401 to S403:

[0076] Step S401: According to a number of first current amplitude standard deviations, determine the first average value and the first standard deviation through the following expression:

[0077]

[0078] In the formula, is the first average value, is the number of a number of current-time sampling sequences sampled through the above step S301, This is the first standard deviation.

[0079] Step S402: According to the first average value and the first standard deviation, adjust the preset standard deviation threshold through the following expression:

[0080]

[0081] In the formula, is the preset standard deviation threshold, is the adjusted standard deviation threshold.

[0082] Step S403: Determine the preliminary detection result of the thermal runaway fault of the power battery according to the relationship between several first current amplitude standard deviations and the adjusted standard deviation threshold;

[0083] Specifically, judge whether several first current amplitude standard deviations are all less than or equal to the adjusted standard deviation threshold; if so, generate a first preliminary detection result of the thermal runaway fault of the power battery, and this first preliminary detection result of the thermal runaway fault is used to characterize that the power battery is unlikely to have a thermal runaway fault. At this time, directly end this round of thermal runaway fault detection, and you can return to execute the above step S101 to start a new round of thermal runaway fault detection until the power battery is in an end-of-operation state; if not, that is, at least one first current amplitude standard deviation is identified as greater than the adjusted standard deviation threshold, then generate a second preliminary detection result of the thermal runaway fault of the power battery, and this second preliminary detection result of the thermal runaway fault is used to characterize that the power battery may have a thermal runaway fault.

[0084] Steps S401 to S403 shown in the embodiments of the present application take into account that when a thermal runaway fault occurs in a power battery under light load conditions, only a small current change will be caused. To adapt to the detection of thermal runaway faults under different current change amplitudes, after adjusting the preset standard deviation threshold by using several first current amplitude standard deviations corresponding to several current time sampling sequences and then performing threshold comparison, it is possible to effectively identify abnormal changes in the current of the power battery and improve the accuracy and reliability of the preliminary detection result of the thermal runaway fault.

[0085] In step S105 of some embodiments, it is preferably set that the sampling frequency is 250 kHz, and the corresponding frequency resolution is the quotient value between the sampling frequency and the number of all current amplitudes included in the current time series. The current time series is represented in the frequency domain through the following expression:

[0086]

[0087] In the formula, is the current frequency domain sequence, is the current time series, is a complex exponential used to convert a time-domain signal into a frequency-domain signal, is the frequency-domain index.

[0088] In some embodiments, the above step S106 may but is not limited to including steps S501 to S502:

[0089] Step S501: Perform sliding frequency-domain sampling on the current frequency-domain sequence according to a preset second moving step size and a preset second moving window to obtain a plurality of current frequency-domain sampling sequences;

[0090] Specifically, denote the current frequency-domain sequence as , is the current amplitude corresponding to the th frequency component, is the number of all current amplitudes included in the current frequency-domain sequence, which can be understood as the current amplitudes corresponding to the frequency components included in the current frequency-domain sequence. When the width of the second moving step size is and the second moving step size is , and are both positive integers and , starting from the first current amplitude included in the current frequency-domain sequence, perform the first frequency-domain sampling using the second moving window to obtain , then slide the second moving window along the frequency axis using the second moving step size, and perform the second frequency-domain sampling using the slid second moving window to obtain , then slide the second moving window along the frequency axis again using the second moving step size, and perform the third frequency-domain sampling using the slid second moving window to obtain , and so on, until a plurality of current frequency-domain sampling sequences are obtained.

[0091] Step S502: Determine the second current amplitude standard deviation corresponding to each current frequency-domain sampling sequence through the following expression according to all the current amplitudes included in each current frequency-domain sampling sequence:

[0092]

[0093] In the formula, is the second current amplitude standard deviation corresponding to the th current frequency-domain sampling sequence sampled through the above step S501, can also be understood as the number of all current amplitudes included in the th current frequency-domain sampling sequence, For the th current amplitude in the th current frequency-domain sampling sequence, is the average value of all current amplitudes included in the

[0094] Steps S501 to S502 illustrated in the embodiments of the present application can provide specific data support for the subsequent final thermal runaway fault detection step by performing sliding frequency-domain sampling on the current frequency-domain sequence using a second moving window and calculating the standard deviation of the current amplitude for each sampled current frequency-domain sampling sequence.

[0095] In some embodiments, the above step S107 may but is not limited to include steps S601 to S602:

[0096] Step S601, obtain a plurality of predetermined standard deviations of the reference current amplitude, which are obtained by analyzing the reference original current time series of the power battery in the frequency domain. The reference original current time series is generated when the power battery operates without a thermal runaway fault, and the number of the plurality of standard deviations of the reference current amplitude is the same as the number of the plurality of standard deviations of the second current amplitude. Preferably, the length of the reference original current time series is the same as the length of the original current time series;

[0097] Step S602, determine the final detection result of the thermal runaway fault of the power battery according to the relationship between the plurality of standard deviations of the second current amplitude and the plurality of standard deviations of the reference current amplitude;

[0098] Specifically, determine whether each standard deviation of the second current amplitude is less than or equal to the standard deviation of the reference current amplitude at the same arrangement position; if it is recognized that at least one standard deviation of the second current amplitude is greater than the standard deviation of the reference current amplitude at the same arrangement position, then generate a first final detection result of the thermal runaway fault of the power battery, and the first final detection result of the thermal runaway fault is used to characterize that the power battery has a thermal runaway fault during operation; if it is recognized that each standard deviation of the second current amplitude is less than or equal to the standard deviation of the reference current amplitude at the same arrangement position, then generate a second final detection result of the thermal runaway fault of the power battery, and the second final detection result of the thermal runaway fault is used to characterize that the power battery does not have a thermal runaway fault during operation. At this time, end this round of thermal runaway fault detection, and it is possible to return to execute the above step S101 to start a new round of thermal runaway fault detection until the power battery is in an end-of-operation state.

[0099] In the steps S601 to S602 illustrated in the embodiments of the present application, since the method of current time-domain analysis cannot truly detect whether the power battery has a thermal runaway fault or is only affected by the step load change and switching operation of the inverter, by comparing a plurality of second current amplitude standard deviations corresponding to a plurality of current frequency-domain sampling sequences with a plurality of reference current amplitude standard deviations obtained by performing current frequency-domain analysis when the power battery does not have a thermal runaway fault, the accuracy and reliability of the final thermal runaway fault detection result can be improved.

[0100] In step S601 of some embodiments, performing frequency-domain analysis on the reference original current time series generated by the operation of the power battery to obtain a plurality of reference current amplitude standard deviations may include, but is not limited to, steps S701 to S703:

[0101] Step S701: Preprocess the reference original current time series to obtain a reference current time series. The corresponding implementation is: extract the AC component of the reference original current time series to obtain a first reference current time series, and filter the noise of the first reference current time series to obtain the reference current time series;

[0102] Step S702: Perform Fourier transform on the reference current time series to obtain a reference current frequency-domain series;

[0103] Step S703: According to the second moving step and the second moving window, perform sampling analysis on the reference current frequency-domain series to obtain a plurality of reference current amplitude standard deviations. The corresponding implementation is: perform sliding frequency-domain sampling on the reference current frequency-domain series according to the second moving step and the second moving window to obtain a plurality of reference current frequency-domain sampling sequences; determine the reference current amplitude standard deviation corresponding to each reference current frequency-domain sampling sequence according to all the current amplitudes included in each reference current frequency-domain sampling sequence.

[0104] In the steps S701 to S703 illustrated in the embodiments of the present application, by performing a series of frequency-domain analysis means on the reference original current time series generated by the operation of the power battery when it is clearly known that no thermal runaway fault has occurred, the same frequency-domain analysis is performed on the reference original current time series, which can make the final thermal runaway fault detection process more reasonable.

[0105] Please refer to Figure 2 , the embodiments of the present application further provide a thermal runaway fault detection system for an electric vehicle power battery, which can implement the above-mentioned thermal runaway fault detection method for an electric vehicle power battery. The system includes:

[0106] An acquisition module 801, configured to acquire the original current time series of the power battery when the power battery is in an operating state;

[0107] A first processing module 802, configured to preprocess the original current time series to obtain a current time series;

[0108] A first analysis module 803, configured to perform sampling analysis on the current time series to obtain a plurality of first current amplitude standard deviations;

[0109] A first evaluation module 804, configured to evaluate a plurality of first current amplitude standard deviations according to a preset standard deviation threshold to obtain a preliminary detection result of a thermal runaway fault of the power battery;

[0110] A second processing module 805, configured to perform Fourier transform on the current time series to obtain a current frequency domain series when the preliminary detection result of the thermal runaway fault reflects that there is a possibility of a thermal runaway fault in the power battery;

[0111] A second analysis module 806, configured to perform sampling analysis on the current frequency domain series to obtain a plurality of second current amplitude standard deviations;

[0112] A second evaluation module 807, configured to evaluate a plurality of second current amplitude standard deviations according to a preset evaluation criterion to obtain a final detection result of a thermal runaway fault of the power battery.

[0113] It can be understood that the content in the above method embodiments is applicable to the system embodiments of the present application. The functions specifically implemented by the system embodiments of the present application are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0114] An embodiment of the present application further provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the above-mentioned method for detecting a thermal runaway fault of an electric vehicle power battery is implemented. The electronic device may include any intelligent terminal such as a tablet computer or an in-vehicle computer.

[0115] It can be understood that the content in the above method embodiments is applicable to the device embodiments of the present application. The functions specifically implemented by the device embodiments of the present application are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0116] Please refer to Figure 3 , Figure 3 which shows the hardware structure of an electronic device in another embodiment. The electronic device includes:

[0117] The processor 901 can be implemented in the form of a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, etc., and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0118] The memory 902 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM), etc. The memory 902 can store an operating system and other application programs. When implementing the technical solutions provided in the embodiments of the present application through software or firmware, the relevant program codes are stored in the memory 902 and are called by the processor 901 to execute the technical solutions provided in the embodiments of the present application;

[0119] The input / output interface 903 is used to implement information input and output;

[0120] The communication interface 904 is used to implement communication interaction between this device and other devices, and can implement communication through a wired method (such as USB, network cable, etc.) or through a wireless method (such as mobile network, WIFI, Bluetooth, etc.);

[0121] The bus 905 transmits information between the various components of the device (such as the processor 901, the memory 902, the input / output interface 903, and the communication interface 904);

[0122] Among them, the processor 901, the memory 902, the input / output interface 903, and the communication interface 904 realize communication connections with each other inside the device through the bus 905.

[0123] The embodiments of the present application also provide a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned method for detecting thermal runaway faults in an electric vehicle power battery is realized.

[0124] It can be understood that the content in the above method embodiments is applicable to the present storage medium embodiments. The functions specifically implemented by the present storage medium embodiments are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those in the above method embodiments.

[0125] The memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. In addition, the memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some embodiments, the memory may optionally include a memory remotely located relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the above networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0126] The embodiments described in the embodiments of the present application are for more clearly illustrating the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art will know that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of the present application are equally applicable to similar technical problems.

[0127] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than those shown in the figures, or combine certain steps, or different steps.

[0128] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0129] Those of ordinary skill in the art can understand that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, and appropriate combinations thereof.

[0130] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0131] It should be understood that in this application, "at least one (item)" means one or more, and "a plurality" means two or more. "And / or" is used to describe the association relationship of associated objects and indicates that there can be three relationships. For example, "A and / or B" can mean: only A exists, only B exists, and both A and B exist at the same time. Among them, A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after. "At least one (one) of the following" or its similar expression refers to any combination of these items, including any combination of single item (one) or plural items (ones). For example, at least one (one) of a, b, or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0132] In several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the above division of units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of systems or units can be in electrical, mechanical or other forms.

[0133] The units described above as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or they can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0134] In addition, each functional unit in various embodiments of this application can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0135] When an 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 storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes: various media that can store programs, such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0136] The preferred embodiments of the embodiments of this application have been described above with reference to the accompanying drawings, which does not limit the scope of rights of the embodiments of this application. Any modifications, equivalent replacements, and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of this application shall be within the scope of rights of the embodiments of this application.

Claims

1. A method for detecting thermal runaway faults of electric vehicle power batteries, characterized in that: The method comprises: When the power battery is in a running state, obtaining an original current time series of the power battery; Preprocessing the original current time series to obtain a current time series; Sampling and analyzing the current time series to obtain a plurality of first current amplitude standard deviations; Evaluating the plurality of first current amplitude standard deviations according to a preset standard deviation threshold to obtain a preliminary detection result of a thermal runaway fault of the power battery; When the preliminary detection result of the thermal runaway fault indicates that the power battery has the possibility of a thermal runaway fault, Fourier transforming the current time series to obtain a current frequency domain series; Sampling and analyzing the current frequency domain sequence to obtain a plurality of second current amplitude standard deviations; Evaluate the plurality of second current amplitude standard deviations according to a preset evaluation standard to obtain a final detection result of a thermal runaway fault of the power battery; The step of evaluating the plurality of first current amplitude standard deviations according to a preset standard deviation threshold to obtain a preliminary detection result of the thermal runaway fault of the power battery includes: According to the plurality of first current amplitude standard deviations, the first average value and the first standard deviation are determined by the following expression: In the formula, is the first average value, is the number of standard deviations of the first current amplitudes, is the first standard deviation, is the standard deviation of the rth first current amplitude; According to the first mean value and the first standard deviation, the standard deviation threshold is adjusted by the following expression: In the formula, is the standard deviation threshold, is the adjusted standard deviation threshold; According to the relationship between the plurality of first current amplitude standard deviations and the adjusted standard deviation threshold, a preliminary detection result of the thermal runaway fault of the power battery is determined.

2. The electric vehicle power battery thermal runaway fault detection method according to claim 1, characterized in that: The preprocessing of the original current time series to obtain the current time series comprises: Extracting AC components from the original current time series to obtain a first current time series; Noise is filtered out of the first current time series to obtain the current time series.

3. The electric vehicle power battery thermal runaway fault detection method according to claim 1, characterized in that: The sampling and analysis of the current time series to obtain a plurality of first current amplitude standard deviations includes: According to a preset first moving window and a preset first moving step length, sliding time domain sampling is performed on the current time series to obtain a plurality of current time sampling sequences; According to all current amplitudes included in each current time sampling sequence, a first current amplitude standard deviation corresponding to each current time sampling sequence is determined.

4. The electric vehicle power battery thermal runaway fault detection method according to claim 1, characterized in that: The sampling and analysis of the current frequency domain sequence to obtain a plurality of second current amplitude standard deviations includes: According to a preset second moving window and a preset second moving step length, sliding frequency domain sampling is performed on the current frequency domain sequence to obtain a plurality of current frequency domain sampling sequences; According to all current amplitudes included in each current frequency domain sampling sequence, a second current amplitude standard deviation corresponding to each current frequency domain sampling sequence is determined.

5. The electric vehicle power battery thermal runaway fault detection method according to claim 4, characterized in that: The step of evaluating the plurality of second current amplitude standard deviations according to a preset evaluation standard to obtain a final detection result of the thermal runaway fault of the power battery includes: Acquiring a plurality of predetermined reference current amplitude standard deviations, the number of the plurality of reference current amplitude standard deviations being the same as the number of the plurality of second current amplitude standard deviations, the plurality of reference current amplitude standard deviations being obtained by performing frequency domain analysis on a reference original current time series of the power battery, the reference original current time series being generated by the power battery operating without a thermal runaway fault; According to the relationship between the plurality of second current amplitude standard deviations and the plurality of reference current amplitude standard deviations, a final detection result of the thermal runaway fault of the power battery is determined.

6. The electric vehicle power battery thermal runaway fault detection method according to claim 5, characterized in that: The standard deviations of the several reference current amplitudes are obtained in the following manner: Preprocessing the reference original current time series to obtain a reference current time series; Performing Fourier transformation on the reference current time series to obtain a reference current frequency domain series; The reference current frequency domain sequence is sampled and analyzed according to the second moving window and the second moving step size to obtain the plurality of reference current amplitude standard deviations.

7. An electric vehicle power battery thermal runaway fault detection system, characterized in that: The system comprises: An acquisition module, used for acquiring the original current time series of the power battery when the power battery is in a running state; A first processing module, used for preprocessing the original current time series to obtain a current time series; A first analysis module, used for sampling and analyzing the current time series to obtain a plurality of first current amplitude standard deviations; A first evaluation module, configured to evaluate the plurality of first current amplitude standard deviations according to a preset standard deviation threshold value, and obtain a preliminary detection result of a thermal runaway fault of the power battery; A second processing module is configured to perform Fourier transform on the current time series to obtain a current frequency domain series when the preliminary detection result of the thermal runaway fault indicates that the power battery has the possibility of a thermal runaway fault; A second analysis module is used to sample and analyze the current frequency domain sequence to obtain a plurality of second current amplitude standard deviations; A second evaluation module, configured to evaluate the plurality of second current amplitude standard deviations according to a preset evaluation standard to obtain a final detection result of a thermal runaway fault of the power battery; The step of evaluating the plurality of first current amplitude standard deviations according to a preset standard deviation threshold to obtain a preliminary detection result of the thermal runaway fault of the power battery includes: According to the plurality of first current amplitude standard deviations, the first average value and the first standard deviation are determined by the following expression: In the formula, is the first average value, is the number of standard deviations of the first current amplitudes, is the first standard deviation, is the standard deviation of the rth first current amplitude; According to the first mean value and the first standard deviation, the standard deviation threshold is adjusted by the following expression: In the formula, is the standard deviation threshold, is the adjusted standard deviation threshold; According to the relationship between the plurality of first current amplitude standard deviations and the adjusted standard deviation threshold, a preliminary detection result of the thermal runaway fault of the power battery is determined.

8. An electronic device, characterized in that: The electronic device comprises a memory and a processor, the memory stores a computer program, and the processor implements the method according to any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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