Automobile battery pack health state detection method, device and system and storage medium

Abstract

The invention discloses an automobile battery pack health state detection method, device and system and a storage medium in the technical field of new energy automobiles. The automobile battery pack health state detection method, device and system is composed of an acceleration sensor, an exciting force hammer, an acceleration signal acquisition module, a signal processing unit and a detection result display module which are arranged on a battery pack bottom plate. In combination with an advanced algorithm analysis technology of the device, a maintainer or a driver can simply and regularly carry out accurate diagnosis on the health state of the battery pack after mechanical impact and collision, and potential fault early warning information is sent out according to a detection result to remind a vehicle owner to carry out maintenance treatment in time; the excitation force hammer knocks a fixed position of a vehicle body, and vibration data of the vehicle sensor is acquired by the signal acquisition module and transmitted to the signal processing module. The processing unit calculates key modal frequency information of the current bottom plate by using a built-in algorithm, and compares the key modal frequency information with a preset threshold value; according to the comparison result, if any abnormity is found, fault early warning information is sent out, and a driver or a vehicle management system is reminded to take corresponding measures.

Description

Technical Field

[0001] The present invention relates to a method, device, system and storage medium for detecting the health status of an automobile battery pack, and belongs to the technical field of new energy automobiles. Background Art

[0002] With the rapid development of the new energy vehicle industry, the safety and reliability of battery packs as core components are increasingly valued. However, in actual use, battery packs are often subjected to external forces such as mechanical shocks or collisions, which may be caused by various factors such as traffic accidents, uneven road surfaces or human operational errors. Even though the current battery management system (BMS) can monitor the battery's electrical properties and temperature, there are still technical blind spots in the identification and monitoring of mechanical damage.

[0003] Mechanical damage may directly affect the battery pack's casing, modules and cells, resulting in failure of sealing, damage to the supporting structure and even damage to the cells. These problems will not only shorten the battery life, but may also cause safety hazards such as battery leakage, short circuit or fire. Therefore, how to monitor the health status of the battery pack in real time without affecting the normal operation of the battery pack, especially detecting mechanical damage caused by external forces, has become a technical problem that needs to be solved urgently.

[0004] Some existing battery monitoring methods usually rely on information such as voltage and temperature collected by the battery management system, and it is difficult to identify microstructural changes caused by mechanical damage. At the same time, many mechanical damage detection technologies require complex equipment or time-consuming detection processes, which are difficult to use during vehicle driving. Therefore, developing a simple and efficient battery pack health status monitoring method that can accurately determine whether the battery pack is damaged in real time and provide early warning when damage occurs will greatly improve the safety of new energy vehicles and the reliability of battery packs. Summary of the invention

[0005] The purpose of the present invention is to overcome the deficiencies in the prior art. The existing electric vehicle mechanical damage detection technology requires complex equipment and a time-consuming detection process, making it difficult to monitor the vehicle in real time while driving.

[0006] In order to solve the above technical problems, the present invention is implemented by adopting the following technical solutions:

[0007] In a first aspect, a method for detecting the health status of a vehicle battery pack is provided, comprising:

[0008] Obtaining vibration response data measured at a preset striking point;

[0009] Determine the frequency data corresponding to the vibration response data, and extract the key modal frequency in the frequency curve composed of the frequency data;

[0010] The critical mode frequency is compared with the preset fault threshold to determine the fault detection result.

[0011] Furthermore, the method for measuring vibration response data at the preset tapping point includes:

[0012] The battery pack bottom plate is struck by an excitation hammer according to a preset rule;

[0013] Real-time monitoring of the vibration response data of the battery pack bottom plate by an acceleration sensor;

[0014] Wherein, the acceleration sensor is arranged on the surface of the battery pack bottom plate according to a preset rule; the preset rule is determined by the structural characteristics and force of the battery pack itself.

[0015] Furthermore, the preset tapping points include:

[0016] Select the four corner points on the surface of the battery pack bottom plate and the midpoints of the lines connecting three sets of adjacent corner points.

[0017] Furthermore, the obtaining of vibration response data measured at a preset tapping point includes:

[0018] Select two of the preset tapping points to tap;

[0019] One of the tapping points is one of the four corner points, and the other tapping point is one of the three midpoints.

[0020] Further, the determining of frequency data corresponding to the vibration response data and extracting key modal frequencies in a frequency curve composed of the frequency data includes:

[0021] Calculate the corresponding frequency data in the frequency domain space according to the multiple vibration response data, and obtain the extreme frequency of each order of the frequency domain curve in the frequency domain space;

[0022] The frequency domain curve is composed of frequency domain data, the key modal frequency is the first n-order extreme frequency of the frequency domain curve, and the value of n is 1, 2 or 3.

[0023] Furthermore, the method for measuring vibration response data at the preset knocking point further includes: improving the accuracy of the acceleration sensor data by averaging;

[0024] The excitation hammer excites each striking point m times, and the determined frequency data is the average value of the m acceleration sensor data, where m is one of the values ​​2-6.

[0025] Furthermore, comparing the critical modal frequency with a preset fault threshold to determine the fault detection result includes:

[0026] The critical modal frequency is compared with the modal threshold, and when it is less than the modal threshold, a potential fault warning message is issued.

[0027] In a second aspect, a new energy vehicle battery pack health status detection device is provided, comprising:

[0028] Data acquisition module, used to obtain vibration response data measured at preset tapping points

[0029] A determination and extraction module, used to determine the frequency data corresponding to the vibration response data, and extract the key modal frequency in the frequency curve composed of the frequency data;

[0030] The detection result determination module is used to compare the key modal frequency with the preset fault threshold to determine the fault detection result.

[0031] In a third aspect, a new energy vehicle battery pack health status detection system includes a processor and a memory connected to the processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the steps of any one of the above methods are performed.

[0032] In a fourth aspect, a computer-readable storage medium stores a computer program, which implements the steps of any of the above methods when executed by a processor.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] 1. The present invention converts vibration response data into modal frequency information in real time and compares it with a preset threshold. When the key modal frequency exceeds the threshold, the system will issue a warning signal to remind the user or the vehicle management system to take measures to avoid more serious damage. The detection process is simplified by selecting preset knocking points and extracting key modal frequencies. No complex external equipment is required, which facilitates high-precision and rapid fault detection and meets the needs of new energy vehicle battery pack status monitoring.

[0035] 2. The present invention arranges acceleration sensors on the bottom plate of the battery pack and combines them with advanced algorithm analysis technology to achieve accurate diagnosis of the health status of the battery pack after vibration impact, and can provide timely warnings when potential faults are detected. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 Shown is a module diagram of a monitoring system according to an embodiment of the present invention;

[0037] Figure 2 It is a schematic diagram showing the arrangement position of the acceleration and the arrangement of the hammer excitation points according to an embodiment of the present invention;

[0038] Figure 3Shown is a flow chart of a monitoring system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0039] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of the present invention.

[0040] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood by specific circumstances.

[0041] Embodiment 1:

[0042] This embodiment provides a method for detecting the health status of a vehicle battery pack, comprising the following steps:

[0043] Step 1, obtaining vibration response data measured at a preset tapping point;

[0044] Step 2, determining the frequency data corresponding to the vibration response data, and extracting the key modal frequency in the frequency curve composed of the frequency data;

[0045] Step 3: Compare the key modal frequency with the preset fault threshold and perform fault detection.

[0046] The method for measuring vibration response data at the preset tapping point includes:

[0047] The battery pack bottom plate is struck by an excitation hammer according to a preset rule;

[0048] Real-time monitoring of the vibration response data of the battery pack bottom plate by an acceleration sensor;

[0049] Wherein, the acceleration sensor is arranged on the surface of the battery pack bottom plate according to a preset rule; the preset rule is determined by the structural characteristics and force of the battery pack itself.

[0050] The preset tapping points include:

[0051] Select the four corner points on the surface of the battery pack bottom plate and the midpoints of the lines connecting three sets of adjacent corner points.

[0052] The step of obtaining vibration response data measured at a preset striking point includes:

[0053] Select two of the preset tapping points to tap;

[0054] One of the tapping points is one of the four corner points, and the other tapping point is one of the three midpoints.

[0055] The step of extracting the key modal frequencies in the frequency curve composed of the frequency data comprises:

[0056] The step of determining the frequency data corresponding to the vibration response data and extracting the key modal frequency in the frequency curve composed of the frequency data includes:

[0057] Calculate the corresponding frequency data in the frequency domain space according to the multiple vibration response data, and obtain the extreme frequency of each order of the frequency domain curve in the frequency domain space;

[0058] The frequency domain curve is composed of frequency domain data, the key modal frequency is the first n-order extreme frequency of the frequency domain curve, and the value of n is 1, 2 or 3.

[0059] Improve the accuracy of acceleration sensor data by averaging;

[0060] The excitation hammer excites each striking point m times, and the determined frequency data is the average value of the m acceleration sensor data, where m is one of the values ​​2-6.

[0061] The method of comparing the key modal frequency with a preset fault threshold and performing fault detection includes:

[0062] The critical modal frequency is compared with the modal threshold, and when it is less than the modal threshold, a potential fault warning message is issued.

[0063] Embodiment 2:

[0064] like Figure 1 As shown, this embodiment provides a vehicle battery pack health status detection device, including:

[0065] A data acquisition module, used to acquire vibration response data measured at a preset knocking point, including an excitation hammer and an acceleration sensor; the excitation hammer is configured on the vehicle and is used to generate an excitation force to knock the battery pack bottom plate according to a preset rule; the acceleration sensor is arranged on the battery pack bottom plate according to a preset rule and is used to monitor the vibration response of the bottom plate;

[0066] A determination and extraction module, used to determine the frequency data corresponding to the vibration response data, and extract the key modal frequency in the frequency curve composed of the frequency data; the determination and extraction module includes a signal acquisition module and a signal processing module, the signal acquisition module is connected to the acceleration sensor, and is used to collect the vibration data of the sensor; the signal processing module receives the data transmitted by the signal acquisition module, calculates the size of the modal frequency after the bottom plate is subjected to multiple hammer impacts through a preset algorithm, and judges whether the battery pack is damaged according to the comparison between the calculation result and the fault threshold, and outputs the detection result;

[0067] The detection result determination module is used to compare the key modal frequency with the preset fault threshold to determine the fault detection result.

[0068] The detection result display module is used to display the fault detection result to inform the user.

[0069] The excitation hammer strikes the battery pack bottom plate according to a preset rule. The excitation position of the bottom plate is determined according to the structural characteristics of the battery pack bottom plate to ensure that the vibration of the key mode of the bottom plate can be excited. According to the structural characteristics of the battery pack and the bottom plate, the excitation hammer strikes the battery pack bottom plate. The four corner points of the two side edges and the rear side edge and the vicinity of the three midpoints are preferably selected.

[0070] The preset rule of the acceleration sensor determines the sensor distribution position according to the structural characteristics of the battery pack and the force analysis, so as to ensure that the vibration information of the key modes of the bottom plate can be accurately reflected; according to the structural characteristics of the battery pack and the bottom plate, the tension-drum mode is the main key mode, so the preset position of the sensor is preferably at the geometric center of the bottom plate and its vicinity;

[0071] The preferred battery pack bottom plate has four corner points on the two sides and the rear side and the vicinity of the three midpoints thereof. Considering the comprehensive detection accuracy, detection convenience and quickness, two knocking points are preferably used for detection during knocking. Specifically, one of the four corner points is selected as a knocking point, and one of the three midpoints is selected as a knocking point.

[0072] According to the principle of reciprocity, the striking point of the excitation hammer and the arrangement position of the acceleration sensor can be used interchangeably without affecting the final result;

[0073] The preset algorithm in the signal processing unit mainly includes an excitation hammer impact signal modal frequency analysis algorithm, which is used to determine the modal frequency information of the battery pack bottom plate according to the sensor data, so as to facilitate comparison and judgment with the fault threshold;

[0074] The modal frequency analysis algorithm of the excitation hammer impact signal is specifically as follows: the sensor data is obtained by calculating the frequency data corresponding to its frequency domain space, and the extreme frequencies of each order of the base plate frequency domain curve are obtained, with a focus on the first n order key modal frequencies, where n=1, 2, 3 are preferably selected;

[0075] The modal frequency analysis algorithm of the excitation hammer impact signal is that the hammer excites m times at each striking point, and the data for frequency space calculation is the average of the m sensor data, where m is preferably 2 to 6;

[0076] The test modal frequency is compared with each modal threshold fi. When it is less than the modal threshold, a potential fault warning message will be issued to remind the owner to repair it in time.

[0077] The preset modal threshold fi here is the main key modal information of the initial state of the battery pack bottom plate, which is obtained through experimental testing or simulation test methods;

[0078] Furthermore, the processing unit also has a historical data recording function to store data information of each test in order to perform long-term trend analysis and fault warning.

[0079] The present invention arranges acceleration sensors on the bottom plate of the battery pack and combines them with advanced algorithm analysis technology to achieve accurate diagnosis of the health status of the battery pack after vibration impact, and can provide timely warning when potential faults are detected.

[0080] Embodiment three:

[0081] The simple device for detecting the battery health status of the present invention is installed on a certain new energy vehicle. Figure 3 As shown in FIG. 1 , the device consists of an acceleration sensor arranged on the bottom plate of the battery pack, an excitation hammer, an acceleration signal acquisition module, a signal processing unit and a detection result display module. First, an acceleration sensor is installed on the bottom plate of the battery pack according to a preset rule, and the excitation hammer taps the excitation position of the bottom plate in a preset order, such as Figure 2 Combined with the advanced algorithm analysis technology of this device, maintenance personnel or drivers can easily and regularly diagnose the health status of the battery pack after mechanical impact and collision, and issue potential fault warning information based on the detection results to remind the owner to repair it in time.

[0082] The preset rule of the acceleration sensor determines the distribution position of the sensor according to the structural characteristics of the battery pack and the force analysis, so as to ensure that the vibration information of the key modes of the base plate can be accurately reflected; according to the structural characteristics of the battery pack and the base plate, the tension-drum mode is its main key mode, so the preset position of the sensor is preferably at the geometric center of the base plate and its vicinity; in this implementation case, the acceleration sensor position selects the geometric center O of the base plate.

[0083] The excitation hammer strikes the battery pack bottom plate according to a preset rule, where the excitation position of the bottom plate is determined according to the structural characteristics of the battery pack bottom plate to ensure that the vibration of the key mode of the bottom plate can be excited; according to the structural characteristics of the battery pack and the bottom plate, the excitation hammer striking position is preferably the four corner points A1, A2, A3, A4 on the two sides and the rear side of the battery pack bottom plate, and the positions C1, C2, C3 near their three midpoints; considering the comprehensive detection accuracy as well as the detection convenience and speed, when striking, two striking points are preferably used for detection. In this implementation case, a point A3 among A1, A2, A3, A4 is selected as the first striking point, and C1 among the three midpoints C1, C2, C3 is selected as the second striking point; Figure 2 shown.

[0084] When the battery pack bottom plate is subjected to hammer excitation at points A3 and C1 respectively, the acceleration sensor signal is converted by AD and amplified and filtered by the acquisition module to obtain the acceleration response data of the bottom plate {X(1) X(2)…X(j)…X(n)}, where X(j) is the acceleration response of the jth sampling point in period n.

[0085]

[0086]

[0087] in, is the kth amplitude in the amplitude array, is the jth acceleration response data point in a sampling period, is the kth modal frequency, and Δf is the frequency interval.

[0088] According to the impact signal modal frequency analysis algorithm, the specific algorithm formula is as above, a set of frequency arrays can be calculated { } and the corresponding amplitude array { In order to improve the test accuracy and reduce the test error, the excitation hammer excites each striking point m times, and the signal X(j) is averaged. The value of m is preferably 2 to 6. In this implementation case, m=3.

[0089] For array { } Perform gradient calculation to obtain the extreme value of the amplitude in the frequency domain space and the corresponding frequency. The corresponding frequency here is the extreme value frequency. Arrange the obtained extreme value frequencies and the corresponding amplitude extreme values ​​in ascending order to obtain the array { }、{ },in: From the theory, we know that { } is the system modal frequency obtained from the test.

[0090] Focusing on the first three key modes of the battery pack bottom plate, we first proposed the zero Hz rigid body mode, that is, the first three frequencies are { },in .

[0091] The first three modal frequencies calculated at different striking points of C1 and A3 are { }, and perform arithmetic operations on the corresponding frequency values. The arithmetic operations here are specifically the mean calculation, deviation calculation, and maximum value calculation of the data; respectively obtain the { }、{ }、{ }.

[0092] Then, according to each modal threshold value f preset in the processing unit i , the modal frequency { } is compared with it. When it is less than the modal threshold, the output alarm prompt result will be triggered.

[0093] Here the preset modal threshold f i , which is the main key modal information of the initial state of the battery pack bottom plate, obtained through experimental testing or simulation test methods;

[0094] Furthermore, the processing unit also has a historical data recording function to store data information of each test in order to perform long-term trend analysis and fault warning.

[0095] The present invention arranges acceleration sensors on the bottom plate of the battery pack and combines them with advanced algorithm analysis technology to achieve accurate diagnosis of the health status of the battery pack after vibration impact, and can provide timely warning when potential faults are detected.

[0096] Embodiment 4:

[0097] This embodiment provides a new energy vehicle battery pack health status detection system, including a processor and a memory connected to the processor, in which a computer program is stored. When the computer program is executed by the processor, the steps of the method described in the above embodiment 1 are executed.

[0098] Embodiment five:

[0099] This embodiment provides a computer-readable storage medium on which a computer program is stored, characterized in that when the program is executed by a processor, the steps of the method described in the above-mentioned embodiment 1 are implemented.

[0100] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for detecting the health status of an automobile battery pack, characterized in that: include: Obtaining vibration response data measured at a preset striking point; Determine the frequency data corresponding to the vibration response data, and extract the key modal frequency in the frequency curve composed of the frequency data; The critical mode frequency is compared with the preset fault threshold to determine the fault detection result.

2. The method for detecting the health status of a vehicle battery pack according to claim 1, characterized in that: The method for measuring vibration response data at the preset tapping point includes: The battery pack bottom plate is struck by an excitation hammer according to a preset rule; Real-time monitoring of the vibration response data of the battery pack bottom plate by an acceleration sensor; Wherein, the acceleration sensor is arranged on the surface of the battery pack bottom plate according to a preset rule; the preset rule is determined by the structural characteristics and force of the battery pack itself.

3. The method for detecting the health status of a vehicle battery pack according to claim 1, characterized in that: The preset tapping points include: Select the four corner points on the surface of the battery pack bottom plate and the midpoints of the lines connecting three sets of adjacent corner points.

4. The method for detecting the health status of a vehicle battery pack according to claim 3, characterized in that: The step of obtaining vibration response data measured at a preset striking point includes: Select two of the preset tapping points to tap; One of the tapping points is one of the four corner points, and the other tapping point is one of the three midpoints.

5. The method for detecting the health status of a vehicle battery pack according to claim 1, characterized in that: The step of determining the frequency data corresponding to the vibration response data and extracting the key modal frequency in the frequency curve composed of the frequency data includes: Calculate the corresponding frequency data in the frequency domain space according to the multiple vibration response data, and obtain the extreme frequency of each order of the frequency domain curve in the frequency domain space; The frequency domain curve is composed of frequency domain data, the key modal frequency is the first n-order extreme frequency of the frequency domain curve, and the value of n is 1, 2 or 3.

6. The method for detecting the health status of a vehicle battery pack according to claim 2, characterized in that: The method for measuring vibration response data at the preset knocking point further includes: improving the accuracy of the acceleration sensor data by averaging; The excitation hammer excites each striking point m times, and the determined frequency data is the average value of the m acceleration sensor data, where m is one of the values ​​2-6.

7. The method for detecting the health status of a vehicle battery pack according to claim 1, characterized in that: The step of comparing the key modal frequency with a preset fault threshold to determine the fault detection result includes: The critical modal frequency is compared with the modal threshold, and when it is less than the modal threshold, a potential fault warning message is issued.

8. A new energy vehicle battery pack health status detection device, characterized in that: include: Data acquisition module, used to obtain vibration response data measured at preset tapping points A determination and extraction module, used to determine the frequency data corresponding to the vibration response data, and extract the key modal frequency in the frequency curve composed of the frequency data; The detection result determination module is used to compare the key modal frequency with the preset fault threshold to determine the fault detection result.

9. A new energy vehicle battery pack health status detection system, characterized in that: The method comprises a processor and a memory connected to the processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 7 are performed.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method described in any one of claims 1 to 7 are implemented.

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