Battery risk diagnosis method and device, electronic equipment, storage medium and carrier

Abstract

The invention discloses a battery risk diagnosis method and device, electronic equipment, a storage medium and a carrier, and belongs to the technical field of batteries. The battery risk diagnosis method comprises the following steps: acquiring first frequency domain data of a vibration signal of a target battery in a target time period; determining whether a risk exists in the target battery or not based on the difference of wave crests in the target frequency range in the first frequency domain data and the second frequency domain data; the second frequency domain data is the frequency domain data of the vibration signal of the target battery in the previous time period of the target time period; the first frequency range does not include noise. According to the battery risk diagnosis method and device, the electronic equipment, the storage medium and the carrier provided by the invention, the target frequency domain data of the vibration signal of the target battery in the target time period is de-noised and then analyzed to determine whether the target battery has a risk, so that noise, normal working conditions and environment signals can be filtered more effectively, and the risk diagnosis accuracy is improved. The effectiveness of vibration signal analysis can be improved, and the risk of the battery can be found more timely.

Description

Technical Field

[0001] The present application belongs to the field of battery technology, and in particular relates to a battery risk diagnosis method, device, electronic device, storage medium and carrier. Background Art

[0002] Batteries used in new energy vehicles, energy storage systems, base stations, consumer electronics or medical devices are prone to risks during use. In order to warn of battery risks, it is generally possible to monitor at least one of the battery's voltage, current, temperature and state of charge (SOC), and then determine whether the value obtained by monitoring exceeds the threshold. However, existing battery risk diagnosis methods have a certain lag, making it difficult to detect risks in a timely manner. Summary of the invention

[0003] The present application aims to solve at least one of the technical problems existing in the prior art. To this end, the present application proposes a battery risk diagnosis method, device, electronic device, storage medium and carrier, which can detect battery risks more timely.

[0004] In a first aspect, the present application provides a battery risk diagnosis method, the method comprising:

[0005] Acquire first frequency domain data of a vibration signal of a target battery during a target time period;

[0006] Based on the difference between the peaks in the target frequency range in the first frequency domain data and the second frequency domain data, determine whether the target battery is at risk; the second frequency domain data is the frequency domain data of the vibration signal of the target battery in the previous time period of the target time period; the target frequency range does not contain noise.

[0007] According to the battery risk diagnosis method of the present application, by denoising the first frequency domain data of the vibration signal of the target battery in the target time period and then analyzing it, based on the difference between the peaks in the target frequency range in the first frequency domain data and the second frequency domain data, it is determined whether the target battery has risks, which can more effectively filter noise, normal operating conditions and environmental signals, improve the effectiveness of vibration signal analysis, and detect battery risks more timely. In addition, windowing the time domain data and performing battery risk diagnosis in units of time periods can improve the analyzability of the data.

[0008] According to one embodiment of the present application, the target frequency range includes a first frequency range;

[0009] The determining whether the target battery has a risk based on the difference between the peaks in the target frequency range in the first frequency domain data and the second frequency domain data includes:

[0010] Based on the difference in the number and position of the peaks within the first frequency range between the first frequency domain data and the second frequency domain data, it is determined whether the target battery has a risk of connection failure.

[0011] According to one embodiment of the present application, the target frequency range includes a second frequency range;

[0012] The determining whether the target battery has a risk based on the difference between the peaks in the target frequency range in the first frequency domain data and the second frequency domain data includes:

[0013] Based on the difference in the number and position of the peaks in the second frequency range between the first frequency domain data and the second frequency domain data, it is determined whether the target battery has a risk of collision.

[0014] According to an embodiment of the present application, determining whether the target battery has a risk of connection failure based on the difference in the number and position of peaks within the first frequency range between the first frequency domain data and the second frequency domain data includes:

[0015] When the difference between the number of peaks within the first frequency range in the first frequency domain data and the second frequency domain data is greater than or equal to a first threshold, and the extra peaks in the first frequency domain data satisfy that the difference in frequency between adjacent peaks in at least three consecutive peaks is less than or equal to a second threshold, a first alarm signal is triggered; the first alarm signal is used to indicate that the target battery is at risk of connection failure and the risk level is a first level.

[0016] According to an embodiment of the present application, determining whether the target battery has a risk of connection failure based on the difference in the number and position of peaks in the first frequency range between the first frequency domain data and the second frequency domain data, further includes:

[0017] When the difference between the number of peaks within the first frequency range in the first frequency domain data and the second frequency domain data is greater than or equal to the first threshold, and the extra peaks in the first frequency domain data do not satisfy the condition that the difference in frequency between adjacent peaks in at least three consecutive peaks is less than or equal to the second threshold, a second alarm signal is triggered; the second alarm signal is used to indicate that the target battery has a risk of connection failure and the risk level is the second level; the severity of the risk indicated by the second level is lower than the severity of the risk indicated by the first level.

[0018] According to an embodiment of the present application, determining whether the target battery has a risk of collision based on the difference in the number and position of peaks in the second frequency range between the first frequency domain data and the second frequency domain data includes:

[0019] When the difference between the number of peaks in the second frequency range in the first frequency domain data and the second frequency domain data is greater than or equal to a third threshold, a third alarm signal is triggered; the third alarm signal is used to indicate that there is a risk of collision with the target battery.

[0020] According to an embodiment of the present application, determining whether the target battery has a risk of collision based on the difference in the number and position of peaks in the second frequency range between the first frequency domain data and the second frequency domain data includes:

[0021] The third alarm signal is triggered when the difference between the number of peaks in the second frequency range in the first frequency domain data and the second frequency domain data is less than the third threshold, and the difference between the frequencies of peaks in the second frequency range in the first frequency domain data and the second frequency domain data is greater than the fourth threshold.

[0022] In a second aspect, the present application provides a battery risk diagnosis device, the device comprising:

[0023] An acquisition module, used to acquire first frequency domain data of a vibration signal of a target battery during a target time period;

[0024] A determination module is used to determine whether the target battery has a risk based on the difference between the peaks in the target frequency range in the first frequency domain data and the second frequency domain data; the second frequency domain data is the frequency domain data of the vibration signal of the target battery in the previous time period of the target time period; the target frequency range does not contain noise.

[0025] According to the battery risk diagnosis device of the present application, by denoising the first frequency domain data of the vibration signal of the target battery in the target time period and then analyzing it, based on the difference between the peaks in the first frequency range in the first frequency domain data and the second frequency domain data, it is determined whether the target battery has risks, which can more effectively filter noise, normal operating conditions and environmental signals, improve the effectiveness of vibration signal analysis, and detect battery risks more timely. In addition, windowing the time domain data and performing battery risk diagnosis in units of time periods can improve the analyzability of the data.

[0026] In a third aspect, the present application provides a vehicle comprising a battery and a battery risk diagnosis device as described in the second aspect.

[0027] In a fourth aspect, the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the battery risk diagnosis method as described in the first aspect above is implemented.

[0028] In a fifth aspect, the present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the battery risk diagnosis method as described in the first aspect above is implemented.

[0029] In a sixth aspect, the present application provides a chip, comprising a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the battery risk diagnosis method as described in the first aspect.

[0030] In a seventh aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the battery risk diagnosis method as described in the first aspect above.

[0031] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0033] Figure 1 This is one of the flowcharts of the battery risk diagnosis method provided in the embodiment of the present application;

[0034] Figure 2 is a schematic diagram of frequency domain data in the battery risk diagnosis method provided in an embodiment of the present application;

[0035] Figure 3 This is the second flow chart of the battery risk diagnosis method provided in the embodiment of the present application;

[0036] Figure 4 is a schematic diagram of the structure of a battery risk diagnosis device provided in an embodiment of the present application;

[0037] Figure 5 is a schematic diagram of the structure of a carrier provided in an embodiment of the present application;

[0038] Figure 6 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0040] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0041] The battery risk diagnosis method, battery risk diagnosis device, electronic device and readable storage medium provided in the embodiments of the present application are described in detail below with reference to the accompanying drawings through specific embodiments and their application scenarios.

[0042] The battery risk diagnosis method may be applied to a terminal, and may be specifically executed by hardware or software in the terminal.

[0043] The terminal includes, but is not limited to, a portable communication device such as a mobile phone or tablet computer with a touch-sensitive surface (e.g., a touch screen display and / or a touch pad). It should also be understood that in some embodiments, the terminal may not be a portable communication device, but a desktop computer with a touch-sensitive surface (e.g., a touch screen display and / or a touch pad).

[0044] In the following various embodiments, a terminal including a display and a touch-sensitive surface is described. However, it should be understood that the terminal may include one or more other physical user interface devices such as a physical keyboard, a mouse and a joystick.

[0045] The battery risk diagnosis method provided in the embodiment of the present application may be executed by an electronic device or a functional module or functional entity in the electronic device that can implement the battery risk diagnosis method. The electronic devices mentioned in the embodiment of the present application include but are not limited to mobile phones, tablet computers, computers, cameras, and wearable devices. The battery risk diagnosis method provided in the embodiment of the present application is described below using an electronic device as an example of the execution subject.

[0046] like Figure 1 As shown, the battery risk diagnosis method includes: step 110 and step 120.

[0047] Step 110: Acquire first frequency domain data of a vibration signal of a target battery in a target time period.

[0048] In actual implementation, the target battery can be any battery included in new energy vehicles, energy storage systems, base stations, consumer electronic products or medical devices. In some embodiments, the electronic device that serves as the executor of the battery risk diagnosis method can be a battery management system (BMS) or other electronic devices with information processing capabilities. The above-mentioned battery management system and other electronic devices with information processing capabilities can be devices included in the above-mentioned new energy vehicles, energy storage systems, base stations, consumer electronic products or medical devices, etc., or they can be independent of the above-mentioned new energy vehicles, energy storage systems, base stations, consumer electronic products or medical devices, etc., but they are used in conjunction with the above-mentioned new energy vehicles, energy storage systems, base stations, consumer electronic products or medical devices.

[0049] The embodiment of the present application does not limit the type of the target battery. In some embodiments, the target battery can be any lithium polymer battery (such as a ternary polymer lithium battery, etc.), any lithium ion battery (such as a lithium iron phosphate battery or a lithium cobalt oxide battery, etc.), any fuel cell (such as SOFC, RFC or DMFC, etc.) or any graphene battery, etc.

[0050] Generally speaking, the vibration signal is the vibration response of the target battery due to external stimulation during operation. The above external stimulation may include direct stimulation and indirect stimulation. Direct stimulation may include collision between other objects and the battery, and disconnection of hardware connection or electrical connection between the battery and other objects. Indirect stimulation may include resonance, etc.

[0051] In actual implementation, the vibration signal of the target battery can be collected according to a preset collection frequency. The specific value of the collection frequency is not limited in the embodiment of the present application. The vibration signal can be collected by any vibration sensor, etc. The specific type of the vibration sensor is not limited in the embodiment of the present application.

[0052] The specific type of vibration signal is not limited in the embodiments of the present application. In some embodiments, the vibration signal may include any one of the relevant parameters of vibration or a signal of any combination of multiple ones. The above-mentioned relevant parameters may include displacement, velocity, acceleration and other parameters. In the case where the vibration signal is an acceleration signal of vibration or at least includes an acceleration signal of vibration, the detection accuracy of the battery risk diagnosis method provided in the embodiments of the present application is better.

[0053] In actual execution, the data of the time period in the above-collected data can be intercepted in units of each time period, and the time domain data of the vibration signal of the target battery in the time period can be obtained. The target time period can be any time period, so the time domain data of the vibration signal of the target battery in the target time period can be obtained in the above manner. In some embodiments, the target time period can be the current time period.

[0054] In some embodiments, the time domain data of the vibration signal of the target battery in each time period can be obtained by dividing the time window. The length of the time window corresponds to the length of the time period. In the above steps, one time period can be represented as one time window.

[0055] The specific duration of the time period is not limited in the embodiments of the present application. The duration of the time period can be flexibly adjusted according to actual conditions. The increase or decrease of the duration of the time period does not affect the accuracy of the implementation and diagnosis of subsequent steps. The duration of the time period corresponds to the size of the time window, and the duration of the time period can be flexibly adjusted according to actual conditions, so the size of the time window can also be reduced and increased according to actual conditions, without affecting subsequent analysis steps.

[0056] In some embodiments, the length of the time period can be determined according to the hardware and software conditions of the execution subject of the battery risk diagnosis method and the requirements of risk diagnosis. For example, the length of the time period, the amount of data in the time window, or the length of the time window can be determined according to the acquisition capability, storage capability, and data processing capability of the chip and / or vibration sensor of the execution subject and the requirements of risk diagnosis.

[0057] It can be understood that the time window division principle can be determined according to the software and hardware conditions of the execution subject of the aforementioned battery risk diagnosis method and the requirements of risk diagnosis.

[0058] It is understandable that, when the vibration signal of the target battery is collected at a preset collection frequency, the length of the time window can be determined by determining the amount of data in the time window. Since the length of the time window corresponds to the length of the time period, determining the length of the time window can correspond to determining the length of the time period.

[0059] In actual implementation, any time domain-frequency domain data conversion method can be used to convert the frequency domain data of the vibration signal of the target battery in each time period to obtain the frequency domain data of the vibration signal of the target battery in that time period. Therefore, the frequency domain data of the vibration signal of the target battery in the target time period can be obtained in the above manner and recorded as the first frequency domain data.

[0060] In some embodiments, any one of the methods such as discrete Fourier transform, continuous Fourier transform, short-time Fourier transform, adaptive linear frequency modulation mode decomposition, synchronous compression transform, continuous wavelet transform and discrete wavelet transform can be used to convert the frequency domain data of the vibration signal of the target battery in the target time period into the first frequency domain data.

[0061] Step 120: determine whether the target battery is at risk based on the difference between the peaks in the target frequency range in the first frequency domain data and the second frequency domain data; the second frequency domain data is the frequency domain data of the vibration signal of the target battery in the previous time period of the target time period; the target frequency range does not contain noise.

[0062] In actual execution, the frequency domain data of the vibration signal of the target battery in the previous time period of the target time period can be recorded as the second frequency domain data. The first frequency domain data can be the frequency domain data in the current time window, and correspondingly, the second frequency domain data can be the frequency domain data in the historical time window.

[0063] After acquiring the first frequency domain data, the peaks within the first frequency range in the first frequency domain data and the peaks within the target frequency range in the second frequency domain data can be compared, and based on the difference between the peaks within the first frequency range in the first frequency domain data and the peaks within the target frequency range in the second frequency domain data, it is determined whether the target battery is at risk.

[0064] In some embodiments, the difference between the peaks in the target frequency range in the first frequency domain data and the peaks in the target frequency range in the second frequency domain data may include at least one difference in the number and position of the peaks, etc. The position of the peak may be the frequency corresponding to the highest point of the peak.

[0065] In some embodiments, the difference between the peak within the target frequency range in the first frequency domain data and the peak within the target frequency range in the second frequency domain data is within an error range, indicating that the peak within the target frequency range in the first frequency domain data is the same as or similar to the peak within the target frequency range in the second frequency domain data. Therefore, when the difference between the peak within the target frequency range in the first frequency domain data and the peak within the target frequency range in the second frequency domain data is within the error range, it can be determined that there is no risk to the target battery.

[0066] In some embodiments, when there is a large difference between a peak within the target frequency range in the first frequency domain data and a peak within the target frequency range in the second frequency domain data, it can be determined that the target battery is at risk.

[0067] It should be noted that when the target battery is operating normally, the peaks in the target frequency range in the frequency domain data of the target battery vibration signal in each time period basically do not change. However, when there is a risk in the target battery, the peaks in the target frequency range in the frequency domain data of the target battery vibration signal in a time period are significantly different from the peaks in the target frequency range in the frequency domain data of the target battery vibration signal in a time period when the target battery is operating normally. Therefore, based on the difference in the peaks in the target frequency range in the first frequency domain data and the second frequency domain data, it is possible to diagnose whether the target battery has a risk.

[0068] It should be noted that the target frequency range may be the frequency range where the peak appears in the frequency domain data of the vibration signal of the target battery due to the existence of the class risk. The target frequency range may be a continuous range in the frequency domain, or multiple discontinuous frequency ranges, or may also be the entire frequency range.

[0069] It should be noted that within the time domain range of the vibration signal of the target battery, the characteristics of noise, normal working conditions and environmental signals are ultra-high frequency and ultra-low frequency. By converting the time domain data of the vibration signal into frequency domain data, the ultra-high frequency and ultra-low frequency signals can be conveniently and easily removed, thereby improving the analysis efficiency of the vibration signal and the accuracy of feature extraction. Therefore, the frequency domain data within the target frequency range is the data after noise removal.

[0070] According to the battery risk diagnosis method provided in the embodiment of the present application, by denoising the first frequency domain data of the vibration signal of the target battery in the target time period and then analyzing it, based on the difference between the peaks in the target frequency range in the first frequency domain data and the second frequency domain data, it is determined whether the target battery has risks, which can more effectively filter noise, normal operating conditions and environmental signals, improve the effectiveness of vibration signal analysis, and discover battery risks more timely. In addition, windowing the time domain data and performing battery risk diagnosis in units of time periods can improve the analyzability of the data.

[0071] In some embodiments, the target frequency range includes a first frequency range.

[0072] In actual implementation, according to different types of risks existing in the target battery, the target frequency range may include one or more types of frequency ranges, and each type of frequency range may correspond to a type of risk of the target battery.

[0073] The target frequency range can be divided into different frequency ranges, and based on the changes in the peaks in different frequency ranges, it is possible to diagnose and evaluate whether the target has a certain type of risk.

[0074] In some embodiments, the first frequency range may be a frequency range where a peak appears in the frequency domain data of the vibration signal of the target battery due to the existence of the first type of risk. The first frequency range may be a continuous range in the frequency domain, or multiple discontinuous frequency ranges, or the entire frequency range. The embodiments of the present application do not limit which type of risk the first type of risk is.

[0075] Determine whether a target battery has a risk based on a difference in peaks within a target frequency range between the first frequency domain data and the second frequency domain data, including: determine whether the target battery has a risk of connection failure based on a difference in the number and position of peaks within a first frequency range between the first frequency domain data and the second frequency domain data.

[0076] In actual implementation, the first type of risk may be a risk of connection failure. The difference in the number of peaks and the difference in the positions of the peaks in the first frequency range between the first frequency domain data and the second frequency domain data may be analyzed to diagnose whether the target battery has a risk of connection failure.

[0077] According to the battery risk diagnosis method provided in the embodiment of the present application, by analyzing the differences in the number and positions of peaks within the first frequency range in the first frequency domain data and the second frequency domain data, it is determined whether the target battery has a risk of connection failure, and the risk of connection failure can be discovered more promptly.

[0078] According to one embodiment of the present application, the target frequency range includes a second frequency range.

[0079] In actual implementation, the second frequency range may be the frequency range where the peak appears in the frequency domain data of the vibration signal of the target battery due to the existence of the first type of risk. The second frequency range may be a continuous range in the frequency domain, or multiple discontinuous frequency ranges, or the entire frequency range. The embodiment of the present application does not limit which type of risk the second type of risk is.

[0080] It should be noted that the second frequency range does not completely overlap with the first frequency range.

[0081] Determine whether a target battery is at risk based on a difference in the number and position of peaks within a target frequency range between the first frequency domain data and the second frequency domain data, including: determine whether the target battery is at risk of collision based on a difference in the number and position of peaks within a second frequency range between the first frequency domain data and the second frequency domain data.

[0082] In actual implementation, the second type of risk may be a collision risk. The difference in the number of peaks and the difference in the positions of the peaks in the second frequency range between the first frequency domain data and the second frequency domain data may be analyzed to diagnose whether the target battery has a collision risk.

[0083] According to the battery risk diagnosis method provided in the embodiment of the present application, by analyzing the difference in the number and position of peaks in the second frequency range between the first frequency domain data and the second frequency domain data, it is determined whether the target battery has the risk of connection failure, and the risk of collision can be discovered more promptly.

[0084] In some embodiments, based on the difference in the number and position of peaks in the first frequency range between the first frequency domain data and the second frequency domain data, determining whether the target battery has a risk of connection failure includes: triggering a first alarm signal when the difference in the number of peaks in the first frequency range between the first frequency domain data and the second frequency domain data is greater than or equal to a first threshold, and the extra peaks in the first frequency domain data satisfy the condition that the difference in frequency difference between adjacent peaks in at least three consecutive peaks is less than or equal to a second threshold; the first alarm signal is used to indicate that the target battery has a risk of connection failure and the risk level is the first level.

[0085] In actual implementation, for the frequency domain data of the vibration signal of the target battery in each time period, the number of peaks in the first frequency range can be obtained. Therefore, the number of peaks in the first frequency range in the first frequency domain data and the number of peaks in the first frequency range in the second frequency domain data can be obtained, which are recorded as the first number and the second number, respectively.

[0086] After obtaining the first quantity and the second quantity, the second quantity may be subtracted from the first quantity to obtain the difference between the first quantity and the second quantity. After obtaining the difference between the first quantity and the second quantity, the difference may be compared with a first threshold to determine whether the difference is greater than or equal to the first threshold.

[0087] The first threshold value may be a difference threshold value of the number of peaks in the first frequency range in the frequency domain data of each time period and the previous time period of the time period. The first threshold value may correspond to the first frequency range. The specific value of the first threshold value is not limited in the embodiment of the present application.

[0088] The difference is less than the first threshold, indicating that the difference between the peak in the first frequency range in the first frequency domain data and the peak in the first frequency range in the second frequency domain data is within the error range, and the peak in the first frequency range in the first frequency domain data is the same as or similar to the peak in the first frequency range in the second frequency domain data. Therefore, when the difference is less than the first threshold, it can be determined that there is no risk in the target battery.

[0089] The difference is greater than or equal to the first threshold, indicating that there is a large difference between the peak in the first frequency range in the first frequency domain data and the peak in the first frequency range in the second frequency domain data. Therefore, when the difference is greater than or equal to the first threshold, it can be determined that the target battery is at risk.

[0090] In some embodiments, the first type of risk may be a risk of connection failure, and accordingly, the first frequency range may be a frequency range where a peak appears in the frequency domain data of the vibration signal of the target battery due to the risk of connection failure. When the difference is greater than or equal to the first threshold, it can be determined that the target battery has a risk of connection failure.

[0091] In the case where the first type of risk is the risk of connection failure, the first threshold may be greater than or equal to three.

[0092] In some embodiments, when the difference is greater than or equal to the first threshold, the extra peaks in the first frequency domain data may be further analyzed to diagnose the severity of the risk of connection failure.

[0093] It should be noted that when the target battery operates normally, no peaks will appear in the first frequency range, and when the target battery connection fails, multiple peaks will generally appear in the first frequency range, and the above peaks are extra peaks. Moreover, depending on the severity of the connection failure, the multiple peaks appearing in the first frequency range have different characteristics. Therefore, the severity of the risk of connection failure can be diagnosed by analyzing the extra peaks in the first frequency domain data.

[0094] It should be noted that the embodiments of the present application may focus on capturing the time period from the normal operation of the target battery to the risk. In the case where the target battery operates normally in the previous time period of the target time period but the target battery connection fails in the target time period, by comparing whether the aforementioned difference is greater than or equal to the first threshold, it can be determined whether the target battery has a risk of connection failure. In the case where it has been determined that there is a risk of connection failure, the operation of the target battery can be intervened. Since the risk has been found, it is not meaningful to subsequently compare the number of peaks in the first frequency range in the first frequency domain data with the number of peaks in the first frequency range in the second frequency domain data.

[0095] In actual implementation, the positions of the extra peaks in the first frequency domain data may be analyzed to diagnose the severity of the risk of connection failure.

[0096] In some embodiments, the frequency difference between each two adjacent peaks in the extra peaks in the first frequency domain data can be obtained. For two adjacent peaks, the frequency difference between the two adjacent peaks can be obtained by subtracting the larger one of the frequencies of the two peaks from the smaller one. The frequency of the peak refers to the frequency corresponding to the highest point of the peak. After obtaining the frequency difference between each two adjacent peaks, it can be determined whether the difference between two consecutive frequency differences is less than or equal to the second threshold.

[0097] The second threshold is a very small value. The second threshold can be set according to actual conditions. The specific value of the second threshold is not limited in the embodiment of the present application.

[0098] If the difference between two consecutive frequency differences is less than or equal to the second threshold, it means that the two frequency differences are equal or close; conversely, if the difference between two consecutive frequency differences is greater than the second threshold, it means that the two frequency differences are not close. The difference between two consecutive frequency differences is less than or equal to the second threshold, that is, the difference between the frequency differences of adjacent peaks in three consecutive peaks is less than or equal to the second threshold. In the case where the extra peaks in the first frequency domain data satisfy the condition that the difference between the frequency differences of adjacent peaks in at least three consecutive peaks is less than or equal to the second threshold, it means that the severity of the risk of connection failure is very high, and a first alarm signal indicating that the target battery has a risk of connection failure and the risk level is the first level can be triggered to prompt the user that the target battery has a risk of connection failure and the risk level is very high.

[0099] It should be noted that the extra peaks in the first frequency domain data satisfy the condition that the frequency difference between adjacent peaks in at least three consecutive peaks is less than or equal to the second threshold, indicating that at least one connection inside the target battery has failed, and that resonance exists during the operation of the target battery and continues to occur at multiple frequencies, seriously affecting the safety of the target battery and even causing thermal runaway of the target battery.

[0100] Figure 2 It is a comparison diagram of a normal connection and an abnormal connection (ie, a connection failure) in the frequency domain and an explanation of the situation where the peak position difference in the spectrum diagram is similar, shown in an exemplary embodiment. Figure 2 The frequency spectrum of the vibration acceleration signal conversion of the battery with normal connection and the battery with failed connection is shown. For the battery with normal connection, its frequency spectrum curve is relatively smooth in the first frequency range, and no characteristic peak appears; while for the battery with failed connection, its frequency spectrum curve has characteristic peaks (i.e., the extra peaks mentioned above) in the first frequency range, and the frequencies of the peaks are f1, f2, and f3, etc. In addition, for the battery with failed connection, the peak spacing Δf1 (Δf1 = f2-f1) and Δf2 (Δf2 = f3-f2) between the characteristic peaks are approximately equal, indicating that a connection inside the battery has failed, and compared with the normal operation of the battery, a resonant frequency appears in the first frequency range, and the vibration energy at the resonant frequency is high. Continuous vibration can aggravate the connection failure and further lead to battery failure and thermal runaway events.

[0101] According to the battery risk diagnosis method provided in the embodiment of the present application, by evaluating the level of the target battery connection failure risk based on the relationship between the number of peaks in the first frequency range in the first frequency domain data and the second frequency domain data and the first threshold, and triggering a corresponding alarm, the risk of battery connection failure can be diagnosed more promptly in advance or more promptly and the level of connection failure risk can be determined, which helps to deal with the risk of battery connection failure more promptly and avoid the occurrence of more serious safety incidents.

[0102] In some embodiments, determining whether the target battery has a risk of connection failure based on the difference in the number and position of peaks in the first frequency range between the first frequency domain data and the second frequency domain data also includes: triggering a second alarm signal when the difference in the number of peaks in the first frequency range between the first frequency domain data and the second frequency domain data is greater than or equal to a first threshold, and the extra peaks in the first frequency domain data do not satisfy the condition that the difference in frequency difference between adjacent peaks in at least three consecutive peaks is less than or equal to a second threshold; the second alarm signal is used to indicate that the target battery has a risk of connection failure and the risk level is the second level; the severity of the risk indicated by the second level is lower than the severity of the risk indicated by the first level.

[0103] In actual implementation, when the difference between the number of peaks in the first frequency range in the first frequency domain data and the second frequency domain data is greater than or equal to the first threshold, the positions of the extra peaks in the first frequency domain data are analyzed to obtain the frequency difference between each two adjacent peaks in the extra peaks in the first frequency domain data. After obtaining the frequency difference between each two adjacent peaks, it can be determined whether the difference between two consecutive frequency differences is less than or equal to the second threshold.

[0104] In the absence of a situation where the difference between two consecutive frequency differences is less than or equal to the second threshold, that is, in the absence of a situation where the difference between the frequency differences of adjacent peaks in three consecutive peaks is less than or equal to the second threshold, it indicates that the severity of the risk of connection failure is high but not very high, and a second alarm signal indicating that the target battery has a risk of connection failure and the risk level is the second level can be triggered to remind the user that the target battery has a risk of connection failure and the risk level is high.

[0105] It should be noted that the risk of connection failure is at the second level, which means that the vibration energy at the resonant frequency is still relatively low and has not yet reached the level that will further cause battery failure and thermal runaway events.

[0106] According to the battery risk diagnosis method provided in the embodiment of the present application, by evaluating the level of the target battery connection failure risk based on the relationship between the number of peaks in the first frequency range in the first frequency domain data and the second frequency domain data and the first threshold and the positional relationship between the peaks, and triggering a corresponding alarm, the risk of battery connection failure can be diagnosed more promptly in advance or more promptly and the level of connection failure risk can be determined, which helps to deal with the risk of battery connection failure more promptly and avoid the occurrence of more serious safety incidents.

[0107] In some embodiments, based on the difference in the number and position of peaks in the second frequency range between the first frequency domain data and the second frequency domain data, determining whether the target battery is at risk of connection failure includes: triggering a third alarm signal when the difference in the number of peaks in the second frequency range between the first frequency domain data and the second frequency domain data is greater than or equal to a third threshold; the third alarm signal is used to indicate that the target battery is at risk of collision.

[0108] In actual implementation, for the frequency domain data of the vibration signal of the target battery in each time period, the number of peaks in the second frequency range can be obtained. Therefore, the number of peaks in the first frequency range in the first frequency domain data and the number of peaks in the second frequency range in the second frequency domain data can be obtained, which are recorded as the third number and the fourth number, respectively.

[0109] After obtaining the third number and the fourth number, the fourth number can be subtracted from the third number to obtain the difference between the third number and the fourth number. After obtaining the difference between the third number and the fourth number, the difference can be compared with a third threshold to determine whether the difference is greater than or equal to the third threshold.

[0110] The third threshold value may be a difference threshold value of the number of peaks in the second frequency range in the frequency domain data of each time period and the previous time period of the time period. The third threshold value may correspond to the second frequency range. The specific value of the third threshold value is not limited in the embodiment of the present application.

[0111] The difference is greater than or equal to the third threshold, indicating that the difference between the peak in the second frequency range in the first frequency domain data and the peak in the second frequency range in the second frequency domain data is large. Therefore, when the difference is greater than or equal to the third threshold, it can be determined that the target battery is at risk.

[0112] In some embodiments, the aforementioned second type of risk may be a risk of collision, and accordingly, the second frequency range may be a frequency range where a peak appears in the frequency domain data of the vibration signal of the target battery due to the risk of collision. When the difference is greater than or equal to the first threshold, it can be determined that the target battery has a risk of collision.

[0113] When the second type of risk is a collision risk, the third threshold may be greater than or equal to 1. In some embodiments, the third threshold is equal to 1. It should be noted that a collision of the battery generally causes an isolated peak to appear in the second frequency range of the frequency domain data of the vibration signal, and thus the third threshold may be equal to 1. In order to improve the reliability of risk diagnosis, the third threshold may also be equal to 2, but it should not be too large.

[0114] After determining that the target battery has a risk of collision, a third alarm signal for indicating that the target battery has a risk of collision may be triggered to prompt a user that the target battery has a risk of collision.

[0115] According to the battery risk diagnosis method provided in the embodiment of the present application, by evaluating whether a target battery has collided based on the relationship between the number of peaks in the second frequency range in the first frequency domain data and the second frequency domain data and the third threshold, and triggering a corresponding alarm, the risk of battery collision can be diagnosed more promptly in advance or more promptly, which helps to deal with the risk of battery collision more promptly and avoid the occurrence of more serious safety incidents.

[0116] In some embodiments, based on the difference in the number and position of peaks in the second frequency range between the first frequency domain data and the second frequency domain data, determining whether the target battery is at risk of connection failure includes: triggering a third alarm signal when the difference in the number of peaks in the second frequency range between the first frequency domain data and the second frequency domain data is less than a third threshold, and the difference between the frequencies of peaks in the second frequency range between the first frequency domain data and the second frequency domain data is greater than a fourth threshold.

[0117] In actual execution, after obtaining the difference between the third number and the fourth number, the difference may be compared with a third threshold to determine whether the difference is greater than or equal to the third threshold.

[0118] When the difference is smaller than the third threshold, the peaks in the second frequency range in the first frequency domain data and the second frequency domain data may be further analyzed to determine whether there is a risk of collision.

[0119] It should be noted that a battery collision may also cause a significant shift in the peak position in the frequency domain data of the vibration signal. In some embodiments, analyzing the peaks in the second frequency range in the first frequency domain data and the second frequency domain data may include: for each peak B in the second frequency range in the first frequency domain data, judging whether all the peaks in the second frequency range in the second frequency domain data satisfy the condition that there is a peak whose difference with the frequency of peak B is greater than the fourth threshold and there is no peak whose difference with the frequency of peak B is less than the fifth threshold. If satisfied, it means that the difference between the frequencies of the peaks in the second frequency range in the first frequency domain data and the second frequency domain data is greater than the fourth threshold. If not satisfied, for example, there is a peak whose difference with the frequency of peak B is less than the fifth threshold, or there is a peak whose difference with the frequency of peak B is greater than the fourth threshold, it means that the difference between the frequencies of the peaks in the second frequency range in the first frequency domain data and the second frequency domain data is less than or equal to the fourth threshold.

[0120] The fourth threshold value can be set according to actual conditions. The fourth threshold value is greater than the second threshold value and the fifth threshold value. The specific value of the fourth threshold value is not limited in the embodiment of the present application.

[0121] The fifth threshold is a very small value. The fifth threshold can be set according to actual conditions. The specific value of the fifth threshold is not limited in the embodiment of the present application.

[0122] When the difference between the frequencies of the peaks in the second frequency range in the first frequency domain data and the second frequency domain data is greater than the fourth threshold, it can be determined that the target battery has a risk of collision. After determining that the target battery has a risk of collision, a third alarm signal for indicating that the target battery has a risk of collision can be triggered to prompt a user that the target battery has a risk of collision.

[0123] It should be noted that a battery collision generally causes an isolated peak to appear in the second frequency range of the frequency domain data of the vibration signal. During the normal operation of the battery, interference or other factors may also cause an isolated peak to appear in the second frequency range of the frequency domain data. However, there are detailed differences in the frequencies of the peaks in the second frequency range in the above two cases. Therefore, if the difference between the frequencies of the peaks in the second frequency range in the first frequency domain data and the second frequency domain data is greater than the fourth threshold, it can be indicated that the target battery is at risk of collision.

[0124] It should be noted that the embodiments of the present application may focus on capturing the time period from normal operation to the existence of risk for the target battery. In the case where the target battery operates normally in the previous time period of the target time period and the target battery connection fails in the target time period, by comparing whether the aforementioned difference is greater than or equal to the third threshold, and when the aforementioned difference is less than the third threshold, it is determined that the difference between the frequencies of the peaks in the second frequency range in the first frequency domain data and the second frequency domain data is greater than the fourth threshold, it can be determined whether the target battery has a risk of collision. In the case where it has been determined that there is a risk of connection failure, the operation of the target battery can be intervened. Since the risk has been found, it is not meaningful to subsequently compare the number of peaks in the first frequency range in the first frequency domain data with the peaks in the second frequency range in the second frequency domain data.

[0125] According to the battery risk diagnosis method provided in the embodiment of the present application, by evaluating whether a target battery has collided based on the relationship between the number of peaks in the second frequency range in the first frequency domain data and the second frequency domain data and the third threshold and the positional relationship between the peaks, and triggering a corresponding alarm, the risk of battery collision can be diagnosed more promptly in advance or more promptly, which helps to deal with the risk of battery collision more promptly and avoid the occurrence of more serious safety incidents.

[0126] In order to facilitate the understanding of the above embodiments of the present application, Figure 3 , an implementation process of the battery risk diagnosis method is described. Figure 3 As shown, an implementation process of the battery risk diagnosis method may include the following steps.

[0127] Step 301: During the operation of a target battery, time domain data of a vibration signal of the battery is obtained according to a preset acquisition frequency.

[0128] Step 302: divide the time domain data of the vibration signal into time windows according to a preset time window division principle.

[0129] Step 303: Convert the time domain data of the vibration signal within the time window into frequency domain data.

[0130] Step 304: Record the number and positions of peaks in the frequency domain data of the current time window.

[0131] Step 305 may be performed when the number of peaks in the second frequency range in the frequency domain data of the current time window is different from that of the previous historical window.

[0132] Step 305: Calculate the difference between the number of peaks in the second frequency range in the frequency domain data of the current time window and the number of peaks in the second frequency range in the frequency domain data of the previous historical window.

[0133] Step 306: Determine whether the difference exceeds a third threshold.

[0134] It may be judged whether the difference value obtained in step 305 exceeds the third threshold value to determine whether the target battery collides, that is, whether there is a risk of the target battery colliding.

[0135] When the difference value obtained in step 305 is less than the third threshold value, step 301 is executed and the process repeats.

[0136] When the difference value obtained in step 305 is greater than or equal to the third threshold, step 307 is executed.

[0137] Step 307: triggering a third alarm signal.

[0138] Step 308 may be performed when the number of peaks in the first frequency range in the frequency domain data of the current time window is different from that of the previous historical window.

[0139] Step 308: Calculate the difference between the number of peaks in the first frequency range in the frequency domain data of the current time window and the number of peaks in the first frequency range in the frequency domain data of the previous historical window, as well as the frequency difference between adjacent characteristic peaks in the first frequency range in the frequency domain data of the current time window.

[0140] The characteristic peak is an additional peak in the first frequency range of the frequency domain data of the current time window compared to the frequency domain data of the previous historical window.

[0141] Step 309: Determine whether the difference exceeds a first threshold.

[0142] It may be judged whether the difference value obtained in step 308 exceeds the first threshold value to determine whether the target battery connection fails, that is, whether there is a risk of target battery connection failure.

[0143] When the difference value obtained in step 308 is less than the first threshold, step 301 is executed and the process repeats.

[0144] When the difference value obtained in step 305 is greater than or equal to the first threshold, step 310 is executed.

[0145] Step 310: Determine whether the frequency differences between adjacent characteristic peaks are similar.

[0146] When the frequency differences between adjacent characteristic peaks obtained in step 308 are not similar, step 311 is executed.

[0147] Step 311: trigger a second alarm signal.

[0148] When the frequency differences between adjacent characteristic peaks obtained in step 308 are similar, step 312 is executed.

[0149] Step 312: trigger a first alarm signal.

[0150] During the implementation of the above-mentioned battery risk diagnosis method, the target battery vibration signal in the time domain is first windowed, and then the time domain data in the time window is converted to obtain the frequency domain data of the vibration signal. Based on the frequency domain data of the vibration signal in each time window, the battery is judged whether a collision occurs according to the relationship between the difference between the number of peaks in the second frequency range in the frequency domain data of the current time window and the number of peaks in the second frequency range in the frequency domain data of the previous historical window and the third threshold value; if the difference exceeds the third threshold value, the third alarm signal is triggered to issue a collision alarm. Furthermore, based on the frequency domain data of the vibration signal in each time window, whether the battery connection has failed and the risk level of the connection failure risk are judged according to the difference between the number of peaks in the second frequency range in the frequency domain data of the current time window and the number of peaks in the second frequency range in the frequency domain data of the previous historical window, as well as the frequency difference between adjacent characteristic peaks in the first frequency range in the frequency domain data of the current time window, and trigger an alarm signal (first alarm signal or second alarm signal) of the corresponding risk level. It can also further trigger corresponding compulsory measures to reduce or even prevent battery fire and explosion accidents, which has a positive promoting significance for the development of battery-driven vehicles such as electric vehicles.

[0151] The battery risk diagnosis method provided in the embodiment of the present application can be executed by a battery risk diagnosis device. In the embodiment of the present application, the battery risk diagnosis device provided in the embodiment of the present application is described by taking the battery risk diagnosis method executed by the battery risk diagnosis device as an example.

[0152] An embodiment of the present application also provides a battery risk diagnosis device.

[0153] like Figure 4 As shown, the battery risk diagnosis device includes: an acquisition module 410 and a determination module 420.

[0154] An acquisition module 410 is used to acquire first frequency domain data of a vibration signal of a target battery in a target time period;

[0155] Determination module 420 is used to determine whether the target battery has a risk based on the difference between the peaks in the target frequency range in the first frequency domain data and the second frequency domain data; the second frequency domain data is the frequency domain data of the vibration signal of the target battery in the previous time period of the target time period; the target frequency range does not contain noise.

[0156] According to the battery risk diagnosis device provided by the embodiment of the present application, by denoising the first frequency domain data of the vibration signal of the target battery in the target time period and then analyzing it, based on the difference between the peaks in the target frequency range in the first frequency domain data and the second frequency domain data, it is determined whether the target battery has risks, which can more effectively filter noise, normal operating conditions and environmental signals, improve the effectiveness of vibration signal analysis, and discover battery risks more timely. In addition, windowing the time domain data and performing battery risk diagnosis in units of time periods can improve the analyzability of the data.

[0157] In some embodiments, the acquisition module 410 may include a collection unit 411 and a conversion unit 412 .

[0158] The acquisition unit 411 may be used to obtain time domain data of a vibration signal of the target battery according to a preset acquisition frequency during the operation of the target battery.

[0159] The conversion unit 412 may be used to divide the time window according to the collected time domain data, and convert the time domain data in the time window to obtain corresponding frequency domain data.

[0160] In some embodiments, the determination module 420 may include a first determination unit 421 and a second determination unit 422 .

[0161] In some embodiments, the target frequency range includes a first frequency range;

[0162] The first determination unit 421 may be configured to determine whether the target battery has a risk of connection failure based on the difference in the number and position of peaks within the first frequency range between the first frequency domain data and the second frequency domain data.

[0163] The first determination unit 421 can be specifically used to determine whether the battery connection has failed and the risk level of the connection failure risk based on the difference between the number of peaks in the first frequency range in the frequency domain data of the current time window and the number of peaks in the second frequency range in the frequency domain data of the previous historical window, and the frequency difference between adjacent characteristic peaks in the first frequency range in the frequency domain data of the current time window.

[0164] In some embodiments, the first determination unit 421 can be specifically used to trigger a first alarm signal when the difference between the number of peaks in the first frequency range in the first frequency domain data and the second frequency domain data is greater than or equal to a first threshold, and the extra peaks in the first frequency domain data satisfy the condition that the difference in frequency between adjacent peaks in at least three consecutive peaks is less than or equal to a second threshold; the first alarm signal is used to indicate that the target battery is at risk of connection failure and the risk level is the first level.

[0165] In some embodiments, the first determination unit 421 can also be specifically used to trigger a second alarm signal when the difference between the number of peaks in the first frequency range in the first frequency domain data and the second frequency domain data is greater than or equal to a first threshold, and the extra peaks in the first frequency domain data do not satisfy the condition that the difference in frequency between adjacent peaks in at least three consecutive peaks is less than or equal to a second threshold; the second alarm signal is used to indicate that the target battery is at risk of connection failure and the risk level is the second level; the severity of the risk indicated by the second level is lower than the severity of the risk indicated by the first level.

[0166] In some embodiments, the target frequency range includes a second frequency range;

[0167] The second determination unit 422 may be configured to determine whether the target battery has a risk of collision based on the difference in the number and position of peaks within the second frequency range between the first frequency domain data and the second frequency domain data.

[0168] In some embodiments, the second determination unit 422 can be specifically used to trigger a third alarm signal when the difference between the number of peaks in the second frequency range in the first frequency domain data and the second frequency domain data is greater than or equal to a third threshold; the third alarm signal is used to indicate that there is a risk of collision with the target battery.

[0169] In some embodiments, the second determination unit 422 can also be specifically used to trigger a third alarm signal when the difference between the number of peaks in the second frequency range in the first frequency domain data and the second frequency domain data is less than a third threshold, and the difference between the frequencies of the peaks in the second frequency range in the first frequency domain data and the second frequency domain data is greater than a fourth threshold.

[0170] The second determination unit 422 can be specifically used to determine whether the battery has collided based on the relationship between the difference between the number of peaks in the second frequency range in the frequency domain data of the current time window and the number of peaks in the second frequency range in the frequency domain data of the previous historical window and the third threshold.

[0171] like Figure 5 As shown, according to some embodiments of the present application, the present application also provides a vehicle 500 , including a battery 510 and the aforementioned battery risk diagnosis device 520 .

[0172] The vehicle may be, but is not limited to, a car, a ship, an airplane, or other types of vehicles. The car may be an electric vehicle (EV) or a hybrid electric vehicle (HEV).

[0173] In some embodiments, the vehicle may include at least one battery 510. Any battery 510 may be a target battery in the aforementioned battery targeting method embodiments.

[0174] According to the vehicle provided in the embodiment of the present application, by denoising the first frequency domain data of the vibration signal of the target battery in the target time period and then analyzing it, based on the difference between the peaks in the target frequency range in the first frequency domain data and the second frequency domain data, it is determined whether the target battery has risks, which can more effectively filter noise, normal operating conditions and environmental signals, improve the effectiveness of vibration signal analysis, and discover battery risks more timely. In addition, windowing the time domain data and performing battery risk diagnosis in units of time periods can improve the analyzability of the data.

[0175] The battery risk diagnosis device in the embodiment of the present application can be an electronic device, or a component in the electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal, or other devices other than a terminal. Exemplarily, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, a vehicle-mounted electronic device, a mobile Internet device (Mobile Internet Device, MID), an augmented reality (augmented reality, AR) / virtual reality (virtual reality, VR) device, a robot, a wearable device, an ultra-mobile personal computer (ultra-mobile personal computer, UMPC), a netbook or a personal digital assistant (personal digital assistant, PDA), etc. It can also be a server, a network attached storage (Network Attached Storage, NAS), a personal computer (personal computer, PC), a television (television, TV), a teller machine or a self-service machine, etc., and the embodiment of the present application is not specifically limited.

[0176] The battery risk diagnosis device in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0177] The battery risk diagnosis device provided in the embodiment of the present application can achieve Figures 1 to 3 To avoid repetition, the various processes implemented by the method embodiment are not described here.

[0178] Figure 6 FIG. 1 is a block diagram of an electronic device shown in an exemplary embodiment. Figure 6As shown, the electronic device 800 may include: a processor 801 and a memory 802. The electronic device 800 may also include one or more of a multimedia component 803, an input / output (I / O) interface 804, and a communication component 805.

[0179] The processor 801 is used to control the overall operation of the electronic device 800 to complete all or part of the steps in the above-mentioned battery risk diagnosis method. The memory 802 is used to store various types of data to support the operation of the electronic device 800. For example, these data may include instructions for any application or method used to operate on the electronic device 800, and application-related data, such as contact data, sent and received messages, pictures, audio, video, etc. The memory 802 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read Only Memory, referred to as PROM), read-only memory (Read Only Memory, referred to as ROM), magnetic memory, flash memory, magnetic disk or optical disk. The multimedia component 803 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 802 or sent through the communication component 805. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 804 provides an interface between the processor 801 and other interface modules, and the above-mentioned other interface modules may be keyboards, mice, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 805 is used for wired or wireless communication between the electronic device 800 and other devices. Wireless communication, such as Wi Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB IOT, eMTC, or other 5G, etc., or a combination of one or more of them, is not limited here. Therefore, the corresponding communication component 805 may include: Wi Fi module, Bluetooth module, NFC module, etc.

[0180] In an exemplary embodiment, the electronic device 800 may be implemented by one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to perform the above-mentioned battery risk diagnosis method.

[0181] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0182] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the above-mentioned battery risk diagnosis method are implemented. For example, the computer-readable storage medium may be the above-mentioned memory 802 including program instructions, and the above-mentioned program instructions may be executed by the processor 801 of the electronic device 800 to perform the above-mentioned battery risk diagnosis method.

[0183] In another exemplary embodiment, a computer program product is further provided. The computer program product includes a computer program executable by a programmable device, and the computer program has a code portion for executing the above-mentioned battery risk diagnosis method when executed by the programmable device.

[0184] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings; however, the present disclosure is not limited to the specific details in the above embodiments. Within the technical concept of the present disclosure, a variety of simple modifications can be made to the technical solution of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0185] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.

[0186] In addition, various embodiments of the present disclosure may be arbitrarily combined, and as long as they do not violate the concept of the present disclosure, they should also be regarded as the contents disclosed by the present disclosure.

[0187] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0188] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0189] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

[0190] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0191] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

Claims

1. A battery risk diagnosis method, characterized in that: include: Acquire first frequency domain data of a vibration signal of a target battery during a target time period; Based on the difference between the peaks in the target frequency range in the first frequency domain data and the second frequency domain data, determine whether the target battery is at risk; the second frequency domain data is the frequency domain data of the vibration signal of the target battery in the previous time period of the target time period; the target frequency range does not contain noise.

2. The battery risk diagnosis method according to claim 1, characterized in that: The target frequency range includes a first frequency range; The determining whether the target battery has a risk based on the difference between the peaks within the target frequency range in the first frequency domain data and the second frequency domain data includes: determining whether the target battery has a risk of connection failure based on the difference between the number and position of peaks within the first frequency range in the first frequency domain data and the second frequency domain data.

3. The battery risk diagnosis method according to claim 1 or 2, characterized in that: The target frequency range includes a second frequency range; The determining whether the target battery has a risk based on the difference between the peaks in the target frequency range in the first frequency domain data and the second frequency domain data includes: Based on the difference in the number and position of the peaks in the second frequency range between the first frequency domain data and the second frequency domain data, it is determined whether the target battery has a risk of collision.

4. The battery risk diagnosis method according to claim 2, characterized in that: The determining whether the target battery has a risk of connection failure based on the difference in the number and position of peaks within the first frequency range between the first frequency domain data and the second frequency domain data includes: When the difference between the number of peaks within the first frequency range in the first frequency domain data and the second frequency domain data is greater than or equal to a first threshold, and the extra peaks in the first frequency domain data satisfy that the difference in frequency between adjacent peaks in at least three consecutive peaks is less than or equal to a second threshold, a first alarm signal is triggered; the first alarm signal is used to indicate that the target battery is at risk of connection failure and the risk level is a first level.

5. The battery risk diagnosis method according to claim 4, characterized in that: The determining whether the target battery has a risk of connection failure based on the difference in the number and position of peaks within the first frequency range between the first frequency domain data and the second frequency domain data further includes: When the difference between the number of peaks within the first frequency range in the first frequency domain data and the second frequency domain data is greater than or equal to the first threshold, and the extra peaks in the first frequency domain data do not satisfy the condition that the difference in frequency between adjacent peaks in at least three consecutive peaks is less than or equal to the second threshold, a second alarm signal is triggered; the second alarm signal is used to indicate that the target battery has a risk of connection failure and the risk level is the second level; the severity of the risk indicated by the second level is lower than the severity of the risk indicated by the first level.

6. The battery risk diagnosis method according to claim 3, characterized in that: The determining whether the target battery has a risk of collision based on the difference in the number and position of the peaks in the second frequency range between the first frequency domain data and the second frequency domain data includes: When the difference between the number of peaks in the second frequency range in the first frequency domain data and the second frequency domain data is greater than or equal to a third threshold, a third alarm signal is triggered; the third alarm signal is used to indicate that there is a risk of collision with the target battery.

7. The battery risk diagnosis method according to claim 6, characterized in that: The determining whether the target battery has a risk of collision based on the difference in the number and position of the peaks in the second frequency range between the first frequency domain data and the second frequency domain data includes: The third alarm signal is triggered when the difference between the number of peaks in the second frequency range in the first frequency domain data and the second frequency domain data is less than the third threshold, and the difference between the frequencies of peaks in the second frequency range in the first frequency domain data and the second frequency domain data is greater than the fourth threshold.

8. A battery risk diagnosis device, characterized in that: include: An acquisition module, used to acquire first frequency domain data of a vibration signal of a target battery during a target time period; A determination module is used to determine whether the target battery has a risk based on the difference between the peaks in the target frequency range in the first frequency domain data and the second frequency domain data; the second frequency domain data is the frequency domain data of the vibration signal of the target battery in the previous time period of the target time period.

9. A carrier, characterized in that: The invention comprises a battery and the battery risk diagnosis device as claimed in claim 8.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the battery risk diagnosis method according to any one of claims 1 to 7 is implemented.

11. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the battery risk diagnosis method according to any one of claims 1 to 7 is implemented.

12. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the battery risk diagnosis method according to any one of claims 1 to 7 is implemented.

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