Electric vehicle power battery thermal runaway fault detection method, system, equipment and medium

Abstract

The invention provides an electric vehicle power battery thermal runaway fault detection method, system and device and a medium, and belongs to the technical field of battery detection. The method comprises the following steps: acquiring an original current time sequence generated by operation of a power battery and preprocessing the original current time sequence to obtain a current time sequence; sampling and analyzing the current time sequence 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 thermal runaway fault preliminary detection result of the power battery; when it is preliminarily detected that the power battery may have a thermal runaway fault, Fourier transform is performed on the current time sequence to obtain a current frequency domain sequence; sampling and analyzing the current frequency domain sequence to obtain a plurality of second current amplitude standard deviations; and evaluating the plurality of second current amplitude standard deviations according to an evaluation standard to obtain a final detection result of the thermal runaway fault of the power battery. Whether the power battery has a thermal runaway fault can be accurately detected.

Description

Technical Field

[0001] The present application relates to the field of battery detection technology, and in particular to a method, system, equipment and medium for detecting thermal runaway faults of power batteries for electric vehicles. Background Art

[0002] Under high temperature, short circuit or abnormal discharge, the chemical substances in the power battery of new energy vehicles react faster, releasing a lot of heat, which can easily cause thermal runaway failure. In the prior art, thermal runaway fault detection is usually achieved by monitoring the current of the power battery and directly judging the threshold. However, the step load change and disconnection operation of the inverter on which the power battery depends during operation will interfere with the current of the power battery, so the prior art cannot accurately achieve thermal runaway fault detection. Summary of the invention

[0003] The main purpose of this application is to propose a method, system, equipment and medium for detecting thermal runaway faults of electric vehicle power batteries, and to achieve more accurate detection of thermal runaway faults occurring in power batteries by combining time domain analysis and frequency domain analysis.

[0004] To achieve the above objectives, one aspect of the present application provides a method for detecting thermal runaway faults of a power battery of an electric vehicle, the method comprising: 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; The plurality of second current amplitude standard deviations are evaluated according to a preset evaluation standard to obtain a final detection result of the thermal runaway fault of the power battery.

[0005] Furthermore, the preprocessing of the original current time series to obtain the current time series includes: Extracting the AC component of 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.

[0006] Furthermore, 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.

[0007] Further, the 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: Determining a first average value and a first standard deviation according to the plurality of first current amplitude standard deviations; adjusting the standard deviation threshold according to the first average value and the first standard deviation; 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.

[0008] Furthermore, 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.

[0009] Further, the 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.

[0010] Furthermore, 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.

[0011] To achieve the above objectives, another aspect of the present application provides a thermal runaway fault detection system for a power battery of an electric vehicle, the system comprising: 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; The second evaluation module is used to evaluate 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.

[0012] To achieve the above objective, another aspect of the present application provides an electronic device, the electronic device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the above method when executing the computer program.

[0013] To achieve the above objective, another aspect of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program implements the above method when executed by a processor.

[0014] The present application includes at least the following beneficial effects: by sampling and analyzing the current sequence in the time domain, when using several first current amplitude standard deviations obtained by analysis to evaluate to preliminarily determine that a power battery may have a thermal runaway fault, considering that the step load changes and disconnection operations of the inverter on which the power battery relies during operation will interfere with the evaluation results in the time domain, the current sequence in the time domain is converted to the frequency domain for sampling and analysis, and finally, several second current amplitude standard deviations obtained by analysis are used to evaluate to determine whether the power battery has a thermal runaway fault. This dual evaluation method can improve the accuracy and reliability of the final thermal runaway fault detection result. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a flow chart of a method for detecting thermal runaway fault of a power battery of an electric vehicle provided in an embodiment of the present application; Figure 2 It is a structural schematic diagram of a thermal runaway fault detection system for a power battery of an electric vehicle provided in an embodiment of the present application; Figure 3 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments 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 as detailed in the attached claims.

[0017] It is understood that the terms "first", "second", etc. used in this application can be used to describe various concepts in this article, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another concept. For example, without departing from the scope of the embodiment of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein can be interpreted as "at the time of" or "when" or "in response to determination".

[0018] The terms "at least one", "multiple", "each", "any", etc. used in this application, at least one includes one, two or more, multiple includes two or more, each refers to each of the corresponding multiple, and any refers to any one of the multiple.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0020] The power batteries in new energy vehicles may cause fire or explosion under certain conditions, including internal short circuits caused by production defects or mechanical damage, battery short circuits caused by external impacts or damage, or charging or discharging ranges beyond the battery design range. The main principle is that under high temperature, short circuit or abnormal discharge, the reaction of internal chemical substances of the power battery is accelerated, releasing a large amount of heat, which can easily cause thermal runaway failures.

[0021] In the prior art, some scholars have proposed to use temperature monitoring or gas monitoring to detect thermal runaway faults. The temperature monitoring method refers to real-time monitoring of the temperature of the power battery during operation and can indicate the risk of thermal runaway when the temperature is abnormal. The gas monitoring method refers to real-time monitoring of the gas released by the power battery during operation and can indicate the risk of thermal runaway when it is found that it releases gases such as hydrogen and carbon dioxide. However, these two methods cannot accurately determine thermal runaway faults. Other scholars have proposed to use current monitoring to detect thermal runaway faults, that is, to monitor the current generated by the power battery during operation and directly judge the threshold. However, since an inverter is needed in electric vehicles to convert the DC power provided by the power battery into AC power to drive the motor, the step load change and disconnection operation of the inverter will cause certain interference to the current of the power battery, so that the current monitoring method cannot accurately detect thermal runaway faults.

[0022] In view of this, the embodiments of the present application provide a method, system, device and medium for detecting thermal runaway faults of power batteries of electric vehicles. The scheme samples and analyzes the current sequence in the time domain. When several first current amplitude standard deviations obtained by analysis are used to evaluate to preliminarily determine that the power battery may have a thermal runaway fault, considering that the step load changes and disconnection operations of the inverter on which the power battery relies during operation will interfere with the evaluation results in the time domain, the current sequence in the time domain is converted to the frequency domain for sampling and analysis. Finally, several second current amplitude standard deviations obtained by analysis are used to evaluate to determine whether the power battery has a thermal runaway fault. This dual evaluation method can improve the accuracy and reliability of the final thermal runaway fault detection result.

[0023] The embodiment of the present application provides a method for detecting thermal runaway faults of electric vehicle power batteries, which relates to the field of battery detection technology, and can be applied to terminals, servers, or software running in terminals or servers. 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, and a vehicle-mounted terminal, etc., but is not limited thereto; the server side can be configured as an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides 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.

[0024] The present application can be used in many general or special 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 electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present 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. The present application can also be practiced in distributed computing environments, in which 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.

[0025] Figure 1 is an optional flow chart of a method for detecting thermal runaway faults of a power battery of an electric vehicle provided in an embodiment of the present application. Figure 1 The method may include but is not limited to steps S101 to S107: Step S101: when the power battery is in operation, obtaining the original current time series of the power battery; Step S102, preprocessing the original current time series to obtain a current time series; Step S103, sampling and analyzing the current time series to obtain a plurality of first current amplitude standard deviations; Step S104, evaluating a plurality of first current amplitude standard deviations according to a preset standard deviation threshold, and obtaining a preliminary detection result of a thermal runaway fault of the power battery; Step S105: When the preliminary detection result of the thermal runaway fault indicates that the power battery has the possibility of a thermal runaway fault, Fourier transform is performed on the current time series to obtain a current frequency domain series; Step S106, sampling and analyzing the current frequency domain sequence to obtain a plurality of second current amplitude standard deviations; Step S107: Evaluate a 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.

[0026] Steps S101 to S107 shown in the embodiment of the present application can achieve more accurate detection of thermal runaway faults occurring in power batteries by combining time domain analysis and frequency domain analysis, and overcome the adverse effects of step load changes and disconnection operations of the inverter on which the power battery relies during operation on the thermal runaway fault detection results.

[0027] In some embodiments, the above step S102 may include but is not limited to steps S201 to S202: Step S201, extracting the AC component of the original current time series to obtain a first current time series; in the present application, the difference method, the window function method, the wavelet transform, etc. can be used to extract the AC component of the current, and the present application does not limit this; Step S202: filtering the first current time series for noise to obtain a current time series; in the present application, a low-pass filter is preferably used to filter out the switching noise carried in the first current time series from the inverter on which the power battery relies during operation.

[0028] Steps S201 to S202 shown in the embodiment of the present application can provide reliable data support for the subsequent thermal runaway fault detection process by extracting the AC component and filtering the noise of the original current time series generated by the operation of the power battery.

[0029] In some embodiments, the above step S103 may include but is not limited to steps S301 to S302: Step S301: performing sliding time domain sampling on the current time series according to a preset first moving step length and a preset first moving window to obtain a plurality of current time sampling sequences; Specifically, the current time series is recorded as , For the The current amplitude corresponding to the time is is the number of all current amplitudes contained in the current time series, which can be understood as the current time series contained in The corresponding moment The current amplitude is, when the width of the first moving window is The first moving step length is hour, and are all positive integers and , from the first current amplitude contained in the current time series At the beginning, the first moving window is used to perform the first time domain sampling to obtain Then, the first moving window is slid along the time axis using the first moving step, and the sliding first moving window is used for a second time domain sampling to obtain , then the first moving window is slid along the time axis again using the first moving step length, and the sliding first moving window is used to perform a third time domain sampling to obtain , and so on, until several current time sampling sequences are obtained.

[0030] Step S302: According to all current amplitudes included in each current time sampling sequence, determine the first current amplitude standard deviation corresponding to each current time sampling sequence by the following expression:

[0031] In the formula, is the first sample obtained by the above step S301. The standard deviation of the first current amplitude corresponding to the current time sampling sequence, It can also be understood as the The number of all current amplitudes contained in a current time sampling sequence, For this The current time sampling sequence contains the The current amplitude, For this The average value of all current amplitudes contained in a current time sampling sequence.

[0032] Steps S301 to S302 shown in the embodiment of the present application, by using the first moving window to perform sliding time domain sampling on the current time series, and calculating the current amplitude standard deviation of each current time sampling sequence obtained by sampling, can provide specific data support for the subsequent preliminary detection step of thermal runaway faults.

[0033] In some embodiments, the above step S104 may include but is not limited to steps S401 to S403: Step S401: Determine a first average value and a first standard deviation according to a plurality of first current amplitude standard deviations by using the following expression:

[0034] In the formula, is the first average value, is the number of the current time sampling sequences obtained by sampling in step S301 above, is the first standard deviation.

[0035] Step S402: According to the first average value and the first standard deviation, the preset standard deviation threshold is adjusted by the following expression:

[0036] In the formula, is the preset standard deviation threshold, is the adjusted standard deviation threshold.

[0037] Step S403, determining a preliminary detection result of a thermal runaway fault of the power battery according to a relationship between a plurality of first current amplitude standard deviations and the adjusted standard deviation threshold; Specifically, it is determined whether several first current amplitude standard deviations are all less than or equal to the adjusted standard deviation threshold; if so, a first preliminary thermal runaway fault detection result for the power battery is generated, and the first preliminary thermal runaway fault detection result is used to characterize that the power battery is unlikely to have a thermal runaway fault. At this time, the current round of thermal runaway fault detection is directly terminated, and the above step S101 can be returned 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, it is identified that at least one first current amplitude standard deviation is greater than the adjusted standard deviation threshold, a second preliminary thermal runaway fault detection result for the power battery is generated, and the second preliminary thermal runaway fault detection result is used to characterize that the power battery may have a thermal runaway fault.

[0038] In steps S401 to S403 shown in the embodiment of the present application, considering that a thermal runaway fault of a power battery under light load conditions will only cause a slight current change, in order to adapt to thermal runaway fault detection under different current change amplitudes, by using several first current amplitude standard deviations corresponding to several current time sampling sequences to adjust the preset standard deviation threshold and then perform threshold comparison, abnormal changes in the power battery current can be effectively identified, thereby improving the accuracy and reliability of the preliminary detection results of the thermal runaway fault.

[0039] In step S105 of some embodiments, the sampling frequency is preferably set to 250 kHz, and the corresponding frequency resolution is the quotient of the sampling frequency and the number of all current amplitudes contained in the current time series. The current time series is converted from the time domain to the frequency domain for representation by the following expression:

[0040] In the formula, is the current frequency domain sequence, is the current time series, is a complex exponential, which is used to convert the time domain signal into the frequency domain signal. is the frequency domain index.

[0041] In some embodiments, the above step S106 may include but is not limited to steps S501 to S502: Step S501: performing sliding frequency domain sampling on the current frequency domain sequence according to a preset second moving step length and a preset second moving window to obtain a plurality of current frequency domain sampling sequences; Specifically, the current frequency domain sequence is recorded as , For the The current amplitude corresponding to the frequency component is: is the number of all current amplitudes contained in the current frequency domain sequence, which can be understood as the current frequency domain sequence contained in The corresponding frequency components The current amplitude is, when the width of the second moving step is The second moving step length is hour, and are all positive integers and , from the first current amplitude contained in the current frequency domain sequence At the beginning, the second moving window is used to perform the first frequency domain sampling to obtain Then, the second moving window is slid along the frequency axis using the second moving step length, and the second moving window after sliding is used to perform a second frequency domain sampling to obtain Then, the second moving window is slid along the frequency axis again using the second moving step length, and the second moving window after sliding is used to perform a third frequency domain sampling to obtain , and so on, until several current frequency domain sampling sequences are obtained.

[0042] Step S502: According to all current amplitudes contained in each current frequency domain sampling sequence, determine the second current amplitude standard deviation corresponding to each current frequency domain sampling sequence by the following expression:

[0043] In the formula, is the first sample obtained by the above step S501. The standard deviation of the second current amplitude corresponding to the current frequency domain sampling sequence, It can also be understood as the The number of all current amplitudes contained in a current frequency domain sampling sequence, For this The current frequency domain sampling sequence contains the The current amplitude, For this The average value of all current amplitudes contained in a current frequency domain sampling sequence.

[0044] In steps S501 to S502 shown in the embodiment of the present application, by using the second moving window to perform sliding frequency domain sampling on the current frequency domain sequence, and calculating the current amplitude standard deviation of each current frequency domain sampling sequence obtained by sampling, specific data support can be provided for the subsequent thermal runaway fault final detection step.

[0045] In some embodiments, the above step S107 may include but is not limited to steps S601 to S602: Step S601, obtaining a plurality of predetermined reference current amplitude standard deviations, wherein the plurality of reference current amplitude standard deviations are obtained by analyzing a reference original current time series of the power battery in the frequency domain, wherein the reference original current time series is generated by the power battery operating without a thermal runaway fault, and the number of the plurality of reference current amplitude standard deviations is the same as the number of the plurality of second current amplitude standard deviations, and the length of the reference original current time series is preferably the same as the length of the original current time series; Step S602: determining a final detection result of a thermal runaway fault of the power battery according to a relationship between a plurality of second current amplitude standard deviations and a plurality of reference current amplitude standard deviations; Specifically, determine whether each second current amplitude standard deviation is less than or equal to the reference current amplitude standard deviation at the same arrangement position; if it is identified that at least one second current amplitude standard deviation is greater than the reference current amplitude standard deviation at the same arrangement position, then generate a first thermal runaway fault final detection result for the power battery, and the first thermal runaway fault final detection result is used to characterize that the power battery has a thermal runaway fault during operation; if it is identified that each second current amplitude standard deviation is less than or equal to the reference current amplitude standard deviation at the same arrangement position, then generate a second thermal runaway fault final detection result for the power battery, and the second thermal runaway fault final detection result is used to characterize that the power battery has not had a thermal runaway fault during operation, and then end this round of thermal runaway fault detection, and return to execute the above step S101 to start a new round of thermal runaway fault detection until the power battery is in a terminated operation state.

[0046] In steps S601 to S602 shown in the embodiment of the present application, since the current time domain analysis method cannot truly detect whether the power battery has a thermal runaway fault or is only affected by the step load change and the interference of the switching operation of the inverter, by using a number of second current amplitude standard deviations corresponding to a number of current frequency domain sampling sequences and performing a current frequency domain analysis when the power battery does not have a thermal runaway fault, a comparison is performed with a number of reference current amplitude standard deviations, thereby improving the accuracy and reliability of the final thermal runaway fault detection result.

[0047] In step S601 of some embodiments, frequency domain analysis is performed 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, which may include but is not limited to steps S701 to S703: Step S701, preprocessing the reference original current time series to obtain a reference current time series, and the corresponding implementation method is: extracting the AC component of the reference original current time series to obtain a first reference current time series, and filtering the noise of the first reference current time series to obtain the reference current time series; Step S702, performing Fourier transform on the reference current time series to obtain a reference current frequency domain series; Step S703, according to the second moving step and the second moving window, the reference current frequency domain sequence is sampled and analyzed to obtain several reference current amplitude standard deviations. The corresponding implementation method is: according to the second moving step and the second moving window, the reference current frequency domain sequence is sampled in the sliding frequency domain to obtain several reference current frequency domain sampling sequences; according to all current amplitudes contained in each reference current frequency domain sampling sequence, the reference current amplitude standard deviation corresponding to each reference current frequency domain sampling sequence is determined.

[0048] In steps S701 to S703 shown in the embodiment of the present application, a series of frequency domain analysis methods are performed on the original current time series generated by the operation of the power battery. The same frequency domain analysis is performed on the benchmark original current time series generated by the operation of the power battery when it is clear that no thermal runaway fault has occurred. This can make the final thermal runaway fault detection process more reasonable.

[0049] See also Figure 2 The embodiment of the present application also provides an electric vehicle power battery thermal runaway fault detection system, which can implement the above-mentioned electric vehicle power battery thermal runaway fault detection method, and the system includes: The acquisition module 801 is used to acquire the original current time series of the power battery when the power battery is in operation; A first processing module 802 is used to pre-process the original current time series to obtain a current time series; A first analysis module 803 is used to perform sampling analysis on the current time series to obtain a plurality of first current amplitude standard deviations; A first evaluation module 804 is used to evaluate a plurality of first current amplitude standard deviations according to a preset standard deviation threshold value to obtain a preliminary detection result of a thermal runaway fault of the power battery; The second processing module 805 is used 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 the power battery has the possibility of a thermal runaway fault; A second analysis module 806 is used to perform sampling analysis on the current frequency domain sequence to obtain a plurality of second current amplitude standard deviations; The second evaluation module 807 is used to evaluate a 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.

[0050] It can be understood that the contents of the above method embodiments are all applicable to the present system embodiments, the functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0051] The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above-mentioned electric vehicle power battery thermal runaway fault detection method when executing the computer program. The electronic device may include any intelligent terminal such as a tablet computer and a car computer.

[0052] It can be understood that the contents of the above method embodiments are all applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0053] See also Figure 3 , Figure 3 The hardware structure of an electronic device according to another embodiment is shown. The electronic device includes: The processor 901 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application; The memory 902 may 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). The memory 902 may store an operating system and other application programs. When the technical solution provided in the embodiment of the present application is implemented by software or firmware, the relevant program code is stored in the memory 902, and the processor 901 calls and executes the technical solution provided in the embodiment of the present application; Input / output interface 903, used to implement information input and output; Communication interface 904, used to realize communication interaction between the device and other devices, which can be realized through wired mode (such as USB, network cable, etc.) or wireless mode (such as mobile network, WIFI, Bluetooth, etc.); A bus 905 that transmits information between various components of the device (e.g., the processor 901, the memory 902, the input / output interface 903, and the communication interface 904); The processor 901 , the memory 902 , the input / output interface 903 and the communication interface 904 are connected to each other in communication within the device via a bus 905 .

[0054] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned electric vehicle power battery thermal runaway fault detection method is implemented.

[0055] It can be understood that the contents of the above method embodiments are all applicable to the present storage medium embodiments, the functions specifically implemented by the present storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0056] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0057] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0058] Those skilled in the art will appreciate 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 shown in the figures, or a combination of certain steps, or different steps.

[0059] The system embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

[0060] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0061] 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 are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0062] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least 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.

[0063] In the several embodiments provided in the present 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 only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or units, which can be electrical, mechanical or other forms.

[0064] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0065] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0066] If the 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 the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0067] The preferred embodiments of the present application are described above with reference to the accompanying drawings, but the scope of the rights of the present application is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present application should be within the scope of the rights of the present 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; The plurality of second current amplitude standard deviations are evaluated according to a preset evaluation standard to obtain a final detection result of the thermal runaway fault of the power battery.

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 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: Determining a first average value and a first standard deviation according to the plurality of first current amplitude standard deviations; adjusting the standard deviation threshold according to the first average value and the first standard deviation; 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.

5. 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.

6. The electric vehicle power battery thermal runaway fault detection method according to claim 5, 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.

7. The electric vehicle power battery thermal runaway fault detection method according to claim 6, 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.

8. 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; The second evaluation module is used to evaluate 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.

9. 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 7 when executing the computer program.

10. 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 7 is implemented.

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