Air tightness detection method and device of battery pack, electronic equipment and storage medium

Abstract

The invention provides an airtightness detection method and device for a battery pack, electronic equipment and a storage medium. The airtightness detection method comprises the following steps: acquiring a sensor sampling interval of each monitoring parameter in a plurality of monitoring parameters of the battery pack; averaging the acquired sampling intervals of all the sensors, and determining the average value as the sampling interval of each monitoring parameter; for each monitoring parameter, based on two initial sampling moments of the monitoring parameter with the minimum time difference with the current sampling moment, determining an estimated monitoring value corresponding to the monitoring parameter at the current sampling moment; determining a standardized monitoring value corresponding to the monitoring parameter at the current sampling moment based on the estimated monitoring value; based on the standardized monitoring value corresponding to each monitoring parameter at the current sampling moment, determining a leakage score of the battery pack; and determining the airtight state of the battery pack based on the leakage score. By adopting the technical scheme provided by the invention, multi-dimensional monitoring of the leakage of the battery pack is realized, and the reliability of the monitoring system is improved.

Description

Technical Field

[0001] This application relates to the field of battery technology, and in particular to a method, apparatus, electronic device, and storage medium for airtightness testing of a battery pack. Background Technology

[0002] With the continuous development of new energy battery technology, people have put forward higher requirements for battery safety performance, and the airtightness of battery packs has become a key research object. Existing battery pack airtightness testing technologies are mainly divided into two categories: production-end testing and user-end monitoring. Currently, the main technologies used at the production end include differential pressure leak detection, helium mass spectrometry leak detection, and water immersion / bubble testing, while the main technologies used at the user end include basic monitoring of battery management systems (BMS), external infrared thermal imaging, and acoustic detection.

[0003] However, for technologies used in production, differential pressure leak detection is limited to the production process and has low sensitivity, making it difficult to meet the needs of real-time monitoring and accurate diagnosis of micro-leakage in battery packs. Helium mass spectrometry leak detection is expensive, complex, and time-consuming, limiting its application to laboratories or high-end manufacturing and hindering its widespread use and dynamic monitoring capabilities, thus making it unsuitable for addressing sealing failures in operating battery packs. Water immersion / bubble detection may cause corrosion of internal battery pack components and relies heavily on manual observation of bubbles, resulting in a high false alarm rate. For technologies used at the user end, basic BMS monitoring relies on indirect inference, which can easily lead to false alarms and cannot distinguish between sealing failures and cell malfunctions, providing only alarms and failing to effectively guide maintenance. External infrared thermal imaging relies on manual inspections, cannot achieve automated real-time monitoring, can only detect abnormal surface temperatures, is highly susceptible to environmental interference, and struggles to detect minute internal leaks. Acoustic detection is easily affected by noise, especially when the vehicle is in motion, as vibration and wind noise can mask the leak sound signal, and requires sensors to be in close contact with the battery pack casing, making integration into vehicle systems difficult. In summary, existing airtightness detection technologies have limitations, resulting in unsatisfactory airtightness detection performance for battery packs. Summary of the Invention

[0004] In view of this, embodiments of this application provide a method, apparatus, electronic device, and storage medium for detecting the airtightness of a battery pack. By combining multiple sensors, multi-dimensional monitoring of battery pack leakage is achieved, improving the reliability of the monitoring system. Furthermore, it can provide early warning of battery pack leakage, thereby enhancing the safety of the battery pack.

[0005] This application mainly includes the following aspects: In a first aspect, embodiments of this application provide a method for airtightness testing of a battery pack, the method comprising: Obtain the sensor sampling interval for each of the multiple monitoring parameters of the battery pack; The average value of all sensor sampling intervals is taken, and the average value is used to determine the sampling interval for each monitoring parameter; For each monitoring parameter, based on the two initial sampling times of the monitoring parameter with the smallest time difference from the current sampling time, the estimated monitoring value corresponding to the monitoring parameter at the current sampling time is determined; wherein, the current sampling time is determined based on the sampling interval; and the initial sampling time is determined based on the sensor sampling interval of the monitoring parameter. Based on the estimated monitoring value, determine the standardized monitoring value of the monitoring parameter at the current sampling time; Based on the standardized monitoring value of each monitoring parameter at the current sampling time, the leakage score of the battery pack is determined; Based on the leakage score, the airtightness of the battery pack is determined.

[0006] Furthermore, for each monitoring parameter, determining the estimated monitoring value corresponding to the monitoring parameter at the current sampling time based on the two initial sampling times of the monitoring parameter with the smallest time difference from the current sampling time includes: For each monitoring parameter, the monitoring values ​​corresponding to the two initial sampling times of the monitoring parameter with the smallest time difference from the current sampling time are interpolated to obtain the initial estimated monitoring value of the monitoring parameter at the current sampling time. The average value between the initial estimated monitoring value and the first preset number of historical estimated monitoring values ​​corresponding to the monitoring parameter is determined as the estimated monitoring value of the monitoring parameter at the current sampling time.

[0007] Furthermore, determining the standardized monitoring value of the monitoring parameter at the current sampling time based on the estimated monitoring value includes: The largest and smallest historical estimated monitoring values ​​are selected from the second preset number of historical estimated monitoring values ​​corresponding to the monitoring parameter. Based on the estimated monitoring value, the largest historical estimated monitoring value, and the smallest historical estimated monitoring value, the estimated monitoring value is normalized, and the normalized estimated monitoring value is determined as the standardized monitoring value corresponding to the monitoring parameter at the current sampling time.

[0008] Furthermore, determining the battery pack leakage score based on the standardized monitoring value corresponding to each monitoring parameter at the current sampling time includes: The average value between the standardized monitoring value and the first preset number of historical standardized monitoring values ​​corresponding to the monitoring parameter is determined as the average standardized monitoring value of the monitoring parameter at the current sampling time. Based on the average standardized monitoring value, determine the weight of the monitoring parameter at the current sampling time; The leakage score of the battery pack is determined by adding the standardized monitoring value of each monitoring parameter at the current sampling time to the product of the corresponding weight.

[0009] Furthermore, determining the weight of the monitoring parameter at the current sampling time based on the average standardized monitoring value includes: Based on the average standardized monitoring value and the first preset number of historical standardized monitoring values ​​corresponding to the monitoring parameter, the standard deviation of the monitoring parameter at the current sampling time is determined. The sum of the standard deviations of all monitored parameters at the current sampling time is determined as the total standard deviation; The quotient of the standard deviation of the monitoring parameter at the current sampling time and the total standard deviation is determined as the weight of the monitoring parameter at the current sampling time.

[0010] Furthermore, determining the airtightness of the battery pack based on the leakage score includes: If the leakage score is within the first preset score range, then the battery pack is determined to be airtight. If the leakage score is in the second preset score range, it is determined that the battery pack has leaked, and the alarm device is controlled to sound an alarm. If the leakage score is within the third preset score range, it is determined that the battery pack has leaked, the power supply to the battery pack is cut off, and the alarm device is controlled to sound an alarm. The upper limit of the first preset score range is not greater than the lower limit of the second preset score range, and the upper limit of the second preset score range is not greater than the lower limit of the third preset score range.

[0011] Secondly, embodiments of this application also provide an airtightness detection device for a battery pack, the airtightness detection device comprising: The acquisition module is used to acquire the sensor sampling interval for each of the multiple monitoring parameters of the battery pack; The averaging module is used to average the sampling intervals of all acquired sensors and determine the average value as the sampling interval for each monitoring parameter; The estimated monitoring value determination module is used to determine the estimated monitoring value of each monitoring parameter at the current sampling time based on the two initial sampling times of the monitoring parameter with the smallest time difference from the current sampling time; wherein, the current sampling time is determined based on the sampling interval; and the initial sampling time is determined based on the sensor sampling interval of the monitoring parameter. The standardized monitoring value determination module is used to determine the standardized monitoring value of the monitoring parameter at the current sampling time based on the estimated monitoring value; The leakage score determination module is used to determine the leakage score of the battery pack based on the standardized monitoring value corresponding to each monitoring parameter at the current sampling time. An airtightness determination module is used to determine the airtightness of the battery pack based on the leakage score.

[0012] Furthermore, the estimated monitoring value determination module is specifically used for: For each monitoring parameter, the monitoring values ​​corresponding to the two initial sampling times of the monitoring parameter with the smallest time difference from the current sampling time are interpolated to obtain the initial estimated monitoring value of the monitoring parameter at the current sampling time. The average value between the initial estimated monitoring value and the first preset number of historical estimated monitoring values ​​corresponding to the monitoring parameter is determined as the estimated monitoring value of the monitoring parameter at the current sampling time.

[0013] Thirdly, embodiments of this application also provide an electronic device, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory through the bus. The machine-readable instructions are executed by the processor to perform the steps of the airtightness detection method for the battery pack described in the first aspect or any possible implementation of the first aspect.

[0014] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the airtightness detection method for a battery pack as described in the first aspect or any possible implementation of the first aspect.

[0015] This application provides a method, apparatus, electronic device, and storage medium for airtightness detection of a battery pack. The airtightness detection method includes: acquiring the sensor sampling interval for each of a plurality of monitoring parameters of the battery pack; averaging all acquired sensor sampling intervals and determining the average value as the sampling interval for each monitoring parameter; for each monitoring parameter, determining an estimated monitoring value corresponding to the monitoring parameter at the current sampling time based on the two initial sampling times with the smallest time difference from the current sampling time; determining a standardized monitoring value corresponding to the monitoring parameter at the current sampling time based on the estimated monitoring value; determining a leakage score for the battery pack based on the standardized monitoring value corresponding to each monitoring parameter at the current sampling time; and determining the airtightness status of the battery pack based on the leakage score. Using the technical solution provided in this application, multi-dimensional monitoring of battery pack leakage is achieved, improving the reliability of the monitoring system.

[0016] In this way, by combining multiple sensors, multi-dimensional monitoring of battery pack leaks is achieved, improving the reliability of the monitoring system. Furthermore, it can provide early warnings of battery pack leaks, thereby enhancing battery pack safety.

[0017] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 One of the flowcharts of a battery pack airtightness testing method provided in an embodiment of this application is shown; Figure 2 A second flowchart of a battery pack airtightness testing method provided in an embodiment of this application is shown; Figure 3 The third flowchart illustrates a battery pack airtightness testing method provided in an embodiment of this application; Figure 4 The fourth flowchart illustrates a battery pack airtightness testing method provided in an embodiment of this application; Figure 5 The fifth flowchart illustrates a battery pack airtightness testing method provided in an embodiment of this application; Figure 6 This illustration shows a schematic diagram of the structure of a battery pack airtightness detection device provided in an embodiment of this application; Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of this application is shown. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0021] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0022] The methods, apparatus, electronic devices, or computer-readable storage media described in this application can be applied to any scenario requiring airtightness testing of battery packs. This application does not limit specific application scenarios, and any scheme using the airtightness testing method and apparatus for battery packs provided in this application is within the protection scope of this application.

[0023] It is worth noting that with the continuous development of new energy battery technology, people have put forward higher requirements for battery safety performance, and the airtightness of battery packs has become a key research object. Existing battery pack airtightness testing technologies are mainly divided into two categories: production-end testing and user-end monitoring. Currently, the main technologies used at the production end include differential pressure leak detection, helium mass spectrometry leak detection, and water immersion / bubble testing, while the main technologies used at the user end include basic monitoring of battery management systems (BMS), external infrared thermal imaging, and acoustic detection. However, for the technologies used at the production end, differential pressure leak detection is limited to the production process and has low sensitivity, thus making it difficult to meet the needs of real-time monitoring and accurate diagnosis of micro-leakage in battery packs; helium mass spectrometry leak detection is expensive, complex to operate, and time-consuming, and is only suitable for laboratories or high-end manufacturing, making it unsuitable for widespread use and dynamic monitoring, and therefore unsuitable for dealing with sealing failures in operating battery packs; water immersion / bubble testing may cause corrosion of internal components of the battery pack and mainly relies on manual observation of bubbles, resulting in a high failure rate. Regarding the technologies used at the user end, basic BMS monitoring relies on indirect inference, which is prone to false alarms and cannot distinguish between seal failure and cell malfunction. It can only issue an alarm and is not effective in guiding maintenance. External infrared thermal imaging depends on manual inspection and cannot achieve automated real-time monitoring. It can only detect abnormal surface temperatures, is greatly affected by environmental interference, and is difficult to detect minute internal leaks. Acoustic detection is easily affected by noise, especially when the vehicle is in motion, as vibration and wind noise can mask the sound signal of leakage. Furthermore, it requires the sensor to be in close contact with the battery pack casing, making it difficult to integrate into the vehicle system. In summary, existing airtightness detection technologies have limitations, and the airtightness detection effect of battery packs is unsatisfactory.

[0024] To address the aforementioned issues, this application proposes a method, apparatus, electronic device, and storage medium for detecting the airtightness of a battery pack. By combining multiple sensors, multi-dimensional monitoring of battery pack leaks is achieved, improving the reliability of the monitoring system. Furthermore, it can provide early warnings of battery pack leaks, thereby enhancing battery pack safety.

[0025] To facilitate understanding of this application, the technical solutions provided in this application will be described in detail below with reference to specific embodiments.

[0026] Please see Figure 1 , Figure 1 This is one of the flowcharts for a battery pack airtightness testing method provided in an embodiment of this application.

[0027] like Figure 1 As shown in the figure, the airtightness detection method for a battery pack provided in this application includes the following steps: Step S101: Obtain the sensor sampling interval for each of the multiple monitoring parameters of the battery pack.

[0028] Here, the sensor sampling interval refers to the time interval between data acquisitions by the sensor, i.e., the length of time between two consecutive acquisitions. Monitored parameters include: internal battery pack pressure, internal battery pack humidity, components of volatile gases emitted from the battery pack, deformation state of the battery pack casing, and internal battery pack temperature. Each monitoring parameter corresponds to a type of sensor, and the sampling intervals differ between different sensors. For the aforementioned internal battery pack pressure, pressure sensors installed in the electrolyte storage area and between battery modules are used to obtain the data; for the aforementioned internal battery pack humidity, humidity sensors installed near the electrolyte storage area and battery terminals are used to obtain the data; for the aforementioned volatile gases emitted from the battery pack, gas sensors installed in the battery pack vents and areas with weak airtightness are used to obtain the data; for the aforementioned battery pack casing deformation state, deformation sensors installed inside the battery pack casing are used, where the deformation sensors can be flexible circuits or strain gauges; for the aforementioned internal battery pack temperature, temperature sensors installed between each battery module are used to obtain the data.

[0029] Step S102: Take the average value of all the sensor sampling intervals obtained, and determine the average value as the sampling interval for each monitoring parameter.

[0030] Here, since the sensor sampling intervals for different monitoring parameters are different, the average sensor sampling interval is calculated using all sensor sampling intervals to unify the time axis. As an example, the sampling interval for each monitoring parameter can be calculated using formula (1).

[0031] (1).

[0032] in, The sampling interval for each monitored parameter, The sensor sampling interval for the internal pressure of the battery pack. The sampling interval for the humidity sensor inside the battery pack. The sensor sampling interval for the gaseous components volatilized from the battery pack. The sensor sampling interval for the deformation state of the battery pack casing. The sampling interval for the sensor measuring the internal temperature of the battery pack.

[0033] Step S103: For each monitoring parameter, based on the two initial sampling times of the monitoring parameter with the smallest time difference from the current sampling time, determine the estimated monitoring value corresponding to the monitoring parameter at the current sampling time.

[0034] Here, the current sampling time is determined based on the sampling interval; that is, the current sampling time is a specific point in time determined according to the sampling interval. The initial sampling time is determined based on the sensor sampling interval of this monitoring parameter. As an example, if a sensor sampling interval is set to 10 seconds, then from the start of operation, there is an initial sampling time every 10 seconds, such as 0 seconds, 10 seconds, 20 seconds, etc. The current sampling time is the current sampling time when the data is collected according to the sampling interval.

[0035] The following is combined Figure 2 This section explains in detail how, for each monitoring parameter, the estimated monitoring value at the current sampling time is determined based on the two initial sampling times of the monitoring parameter that have the smallest time difference with the current sampling time.

[0036] Please see Figure 2 , Figure 2 This is a second flowchart of a battery pack airtightness testing method provided in an embodiment of this application.

[0037] like Figure 2 As shown, regarding step S103, in a specific implementation, as an example, the following steps may be included: Step S1031: For each monitoring parameter, interpolate the monitoring values ​​corresponding to the two initial sampling times of the monitoring parameter with the smallest time difference from the current sampling time to obtain the initial estimated monitoring value of the monitoring parameter at the current sampling time.

[0038] Here, as an example, the initial estimated monitoring value can be calculated using formula (2).

[0039] (2).

[0040] in, This is the initial estimated monitoring value of the monitoring parameter at the current sampling time. and These are the two initial sampling times for the monitoring parameter that have the smallest time difference with the current sampling time. and These are the monitoring values ​​corresponding to the two initial sampling times of the monitoring parameter that have the smallest time difference with the current sampling time, where, As an example, suppose the temperature sensor measures the internal temperature of the battery pack to be 22°C at the 10th second of the initial sampling time, and assumes that the temperature sensor measures the internal temperature of the battery pack to be 23°C at the 15th second of the initial sampling time. The current sampling time of the internal temperature of the battery pack is the 13th second. Then the initial estimated monitoring value of the internal temperature of the battery pack at the current sampling time is 22°C + (3 / 5) × 1°C = 22.6°C.

[0041] Step S1032: The average value between the initial estimated monitoring value and the first preset number of historical estimated monitoring values ​​corresponding to the monitoring parameter is determined as the estimated monitoring value corresponding to the monitoring parameter at the current sampling time.

[0042] Here, a moving average filter is used to denoise the initial estimated monitoring values. As an example, the estimated monitoring values ​​can be calculated using formula (3).

[0043] (3).

[0044] in, This is the estimated monitoring value of the parameter at the current sampling time. The number of historically estimated monitoring values, i The first index variable, counting from 0. t This represents the current sampling time. As an example, N The value is 3.

[0045] See again Figure 1 Step S104: Based on the estimated monitoring value, determine the standardized monitoring value corresponding to the monitoring parameter at the current sampling time.

[0046] The following is combined Figure 3 This section will explain in detail how to determine the standardized monitoring value of the monitoring parameter at the current sampling time based on the estimated monitoring value.

[0047] Please see Figure 3 , Figure 3 This is the third flowchart of a battery pack airtightness testing method provided in an embodiment of this application.

[0048] like Figure 3As shown, regarding step S104, in a specific implementation, as an example, the following steps may be included: Step S1041: Select the largest and smallest historical estimated monitoring values ​​from the second preset number of historical estimated monitoring values ​​corresponding to the monitoring parameter.

[0049] As an example, the second preset quantity is 100. As an example, assume that the historical estimated monitoring values ​​corresponding to the internal pressure of 100 battery packs are [102.1, 101.8, 103.0…105.2], then the minimum historical estimated monitoring value is 101.8 and the minimum historical estimated monitoring value is 105.2.

[0050] Step S1042: Based on the estimated monitoring value, the largest historical estimated monitoring value, and the smallest historical estimated monitoring value, the estimated monitoring value is normalized, and the normalized estimated monitoring value is determined as the standardized monitoring value corresponding to the monitoring parameter at the current sampling time.

[0051] Here, since the data units of different monitoring parameters are different, the estimated monitoring values ​​of all monitoring parameters at the current sampling time are unified to the same scale, that is, normalization is performed. As an example, the standardized monitoring values ​​can be calculated by formula (4).

[0052] (4).

[0053] in, The smallest historical estimated monitoring value among the second preset number of historical estimated monitoring values. The largest historical estimated monitoring value among the second preset number of historical estimated monitoring values. This is the standardized monitoring value of the monitored parameter at the current sampling time. The output range is [0, 1].

[0054] See again Figure 1 Step S105: Determine the leakage score of the battery pack based on the standardized monitoring value corresponding to each monitoring parameter at the current sampling time.

[0055] The following is combined Figure 4 This section will explain in detail how to determine the battery pack leakage score based on the standardized monitoring value corresponding to each monitoring parameter at the current sampling time.

[0056] Please see Figure 4 , Figure 4 This is the fourth flowchart of a battery pack airtightness testing method provided in the embodiments of this application.

[0057] like Figure 4As shown, regarding step S105, in a specific implementation, as an example, the following steps may be included: Step S1051: The average value between the standardized monitoring value and the first preset number of historical standardized monitoring values ​​corresponding to the monitoring parameter is determined as the average standardized monitoring value of the monitoring parameter at the current sampling time.

[0058] Step S1052: Based on the average standardized monitoring value, determine the weight of the monitoring parameter at the current sampling time.

[0059] Here, below, in conjunction with Figure 5 This section will explain in detail how to determine the battery pack leakage score based on the standardized monitoring value corresponding to each monitoring parameter at the current sampling time.

[0060] Please see Figure 5 , Figure 5 This is the fifth flowchart of a battery pack airtightness testing method provided in the embodiments of this application.

[0061] like Figure 5 As shown, regarding step S1052, in a specific implementation, as an example, the following steps may be included: Step S10521: Based on the average standardized monitoring value and the first preset number of historical standardized monitoring values ​​corresponding to the monitoring parameter, determine the standard deviation of the monitoring parameter at the current sampling time.

[0062] Here, as an example, the standard deviation can be calculated using formula (5).

[0063] (5).

[0064] in, To monitor the standard deviation of the parameter at the current sampling time, In order to be in k Sampling time number j The standardized monitoring values ​​corresponding to each monitoring parameter For the first j The average standardized monitoring value of each monitoring parameter at the current sampling time.

[0065] Step S10522: The sum of the standard deviations of all monitoring parameters at the current sampling time is determined as the total standard deviation.

[0066] Step S10523: The quotient of the standard deviation of the monitoring parameter at the current sampling time and the total standard deviation is determined as the weight of the monitoring parameter at the current sampling time.

[0067] Here, as an example, the weight of the monitoring parameter at the current sampling time can be calculated using formula (6).

[0068] (6).

[0069] in, n To monitor the number of parameters, j The second index variable, counting from 1. For the first j The weight of each monitoring parameter at the current sampling time This represents the total standard deviation. The weights of all monitored parameters at the current sampling time are summed to equal 0.

[0070] See again Figure 4 In step S1053, the result obtained by adding the standardized monitoring value corresponding to each monitoring parameter at the current sampling time to the corresponding weight is determined as the leakage score of the battery pack.

[0071] Here, the leakage score of the battery pack is obtained by weighting and fusing the standardized monitoring values ​​corresponding to each monitoring parameter at the current sampling time. As an example, the leakage score of the battery pack can be calculated by formula (7).

[0072] (7).

[0073] in, For the first j The standardized monitoring value of each monitoring parameter at the current sampling time.

[0074] See again Figure 1 Step S106: Based on the leakage score, determine the airtightness of the battery pack.

[0075] Here, if the leakage score is in the first preset score range, the battery pack is determined to be airtight; if the leakage score is in the second preset score range, the battery pack is determined to be leaking, and the alarm device is activated; if the leakage score is in the third preset score range, the battery pack is determined to be leaking, the power supply to the battery pack is cut off, and the alarm device is activated. The upper limit of the first preset score range is not greater than the lower limit of the second preset score range, and the upper limit of the second preset score range is not greater than the lower limit of the third preset score range. Specifically, if the leakage score is in the first preset score range, it indicates that the battery pack is airtight, and the process returns to step S103 to continue monitoring the battery pack; if the leakage score is in the second preset score range, a primary warning is activated, and the vehicle display screen will show "Battery pack status abnormal, it is recommended to contact a 4S store and go to a 4S store for repair," while recording relevant data. If the leakage score is in the third preset score range, an advanced warning is activated, triggering an audible and visual alarm, automatically cutting off the high-voltage power supply, and activating the battery pack isolation mode to ensure vehicle safety.

[0076] This application provides a method for detecting the airtightness of a battery pack. By combining multiple sensors, this method achieves multi-dimensional monitoring of battery pack leaks, improving the reliability of the monitoring system. Furthermore, it can provide early warnings of battery pack leaks, thereby enhancing battery pack safety.

[0077] Based on the same application concept, this application also provides a battery pack airtightness detection device corresponding to the battery pack airtightness detection method provided in the above embodiments. Since the principle of the device in this application is similar to the battery pack airtightness detection method in the above embodiments of this application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0078] Please see Figure 6 As shown, Figure 6 This is a schematic diagram of the structure of a battery pack airtightness detection device provided in an embodiment of this application.

[0079] like Figure 6 As shown in the figure, the airtightness detection device 610 for the battery pack provided in this application embodiment includes: The acquisition module 611 is used to acquire the sensor sampling interval of each of the multiple monitoring parameters of the battery pack; The averaging module 612 is used to average the sampling intervals of all acquired sensors and determine the average value as the sampling interval for each monitoring parameter; The estimated monitoring value determination module 613 is used to determine the estimated monitoring value of each monitoring parameter at the current sampling time based on the two initial sampling times of the monitoring parameter with the smallest time difference from the current sampling time; wherein, the current sampling time is determined based on the sampling interval; and the initial sampling time is determined based on the sensor sampling interval of the monitoring parameter. The standardized monitoring value determination module 614 is used to determine the standardized monitoring value of the monitoring parameter at the current sampling time based on the estimated monitoring value; The leakage score determination module 615 is used to determine the leakage score of the battery pack based on the standardized monitoring value corresponding to each monitoring parameter at the current sampling time. The airtightness determination module 616 is used to determine the airtightness of the battery pack based on the leakage score.

[0080] Furthermore, the estimated monitoring value determination module 613 is specifically used for: For each monitoring parameter, the monitoring values ​​corresponding to the two initial sampling times of the monitoring parameter with the smallest time difference from the current sampling time are interpolated to obtain the initial estimated monitoring value of the monitoring parameter at the current sampling time. The average value between the initial estimated monitoring value and the first preset number of historical estimated monitoring values ​​corresponding to the monitoring parameter is determined as the estimated monitoring value of the monitoring parameter at the current sampling time.

[0081] Furthermore, the standardized monitoring value determination module 614 is specifically used for: The largest and smallest historical estimated monitoring values ​​are selected from the second preset number of historical estimated monitoring values ​​corresponding to the monitoring parameter. Based on the estimated monitoring value, the largest historical estimated monitoring value, and the smallest historical estimated monitoring value, the estimated monitoring value is normalized, and the normalized estimated monitoring value is determined as the standardized monitoring value corresponding to the monitoring parameter at the current sampling time.

[0082] Furthermore, the leakage scoring and determination module 615 is specifically used for: The average value between the standardized monitoring value and the first preset number of historical standardized monitoring values ​​corresponding to the monitoring parameter is determined as the average standardized monitoring value of the monitoring parameter at the current sampling time. Based on the average standardized monitoring value, determine the weight of the monitoring parameter at the current sampling time; The leakage score of the battery pack is determined by adding the standardized monitoring value of each monitoring parameter at the current sampling time to the product of the corresponding weight.

[0083] Furthermore, when determining the weight of the monitoring parameter at the current sampling time based on the average standardized monitoring value, the leakage scoring determination module 615 is specifically used for: Based on the average standardized monitoring value and the first preset number of historical standardized monitoring values ​​corresponding to the monitoring parameter, the standard deviation of the monitoring parameter at the current sampling time is determined. The sum of the standard deviations of all monitored parameters at the current sampling time is determined as the total standard deviation; The quotient of the standard deviation of the monitoring parameter at the current sampling time and the total standard deviation is determined as the weight of the monitoring parameter at the current sampling time.

[0084] Furthermore, the airtightness determination module 616 is specifically used for: If the leakage score is within the first preset score range, then the battery pack is determined to be airtight. If the leakage score is in the second preset score range, it is determined that the battery pack has leaked, and the alarm device is controlled to sound an alarm. If the leakage score is within the third preset score range, it is determined that the battery pack has leaked, the power supply to the battery pack is cut off, and the alarm device is controlled to sound an alarm. The upper limit of the first preset score range is not greater than the lower limit of the second preset score range, and the upper limit of the second preset score range is not greater than the lower limit of the third preset score range.

[0085] This application provides an airtightness detection device for a battery pack. By combining multiple sensors, this device achieves multi-dimensional monitoring of battery pack leaks, improving the reliability of the monitoring system. Furthermore, it can provide early warnings of battery pack leaks, thereby enhancing battery pack safety.

[0086] Please see Figure 7 , Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0087] like Figure 7 As shown, the electronic device 700 includes a processor 710, a memory 720, and a bus 730.

[0088] The memory 720 stores machine-readable instructions executable by the processor 710. When the electronic device 700 is running, the processor 710 communicates with the memory 720 via the bus 730. When the machine-readable instructions are executed by the processor 710, they can perform the operations described above. Figure 1 , Figure 2 , Figure 3 , Figure 4 and Figure 5 The steps of the airtightness detection method for the battery pack in the method embodiment shown are described in detail in the method embodiment, and will not be repeated here.

[0089] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, can perform the above-described actions. Figure 1 , Figure 2 , Figure 3 , Figure 4 and Figure 5 The steps of the airtightness detection method for the battery pack in the method embodiment shown are described in detail in the method embodiment, and will not be repeated here.

[0090] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and devices described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division; in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection may be through some communication interfaces; the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms.

[0091] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0092] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0093] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0094] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method of hermetic detection of a battery pack, characterized by, The air tightness detection method comprises: obtaining a sensor sampling interval of each monitoring parameter in a plurality of monitoring parameters of a battery pack; averaging all obtained sensor sampling intervals, and determining the average value as a sampling interval of each monitoring parameter; for each monitoring parameter, determining an estimated monitoring value of the monitoring parameter corresponding to a current sampling time based on two initial sampling times of the monitoring parameter with the smallest time difference from the current sampling time, wherein the current sampling time is determined based on the sampling interval, and the initial sampling time is determined based on the sensor sampling interval of the monitoring parameter; determining a standardized monitoring value of the monitoring parameter corresponding to the current sampling time based on the estimated monitoring value; determining a leakage score of the battery pack based on the standardized monitoring value of each monitoring parameter corresponding to the current sampling time; determining an air tightness state of the battery pack based on the leakage score.

2. The method of claim 1, wherein, The method comprises: for each monitoring parameter, performing interpolation operation on monitoring values corresponding to two initial sampling times of the monitoring parameter with the smallest time difference from the current sampling time to obtain an initial estimated monitoring value of the monitoring parameter corresponding to the current sampling time; determining an average value between the initial estimated monitoring value and a first preset number of historical estimated monitoring values corresponding to the monitoring parameter as the estimated monitoring value of the monitoring parameter corresponding to the current sampling time.

3. The method of claim 1, wherein, The method comprises: selecting a maximum historical estimated monitoring value and a minimum historical estimated monitoring value from a second preset number of historical estimated monitoring values corresponding to the monitoring parameter; performing normalization processing on the estimated monitoring value based on the estimated monitoring value, the maximum historical estimated monitoring value and the minimum historical estimated monitoring value, and determining a normalized monitoring value of the monitoring parameter corresponding to the current sampling time as the normalized monitoring value after the normalization processing.

4. The method of claim 1, wherein, The method comprises: determining an average standardized monitoring value of the monitoring parameter corresponding to the current sampling time as an average value between the standardized monitoring value and a first preset number of historical standardized monitoring values corresponding to the monitoring parameter; determining a weight of the monitoring parameter corresponding to the current sampling time based on the average standardized monitoring value; adding a product of the standardized monitoring value of each monitoring parameter corresponding to the current sampling time and the corresponding weight to obtain a result, and determining the result as the leakage score of the battery pack.

5. The method of claim 4, wherein, The method comprises: determining a standard deviation of the monitoring parameter corresponding to the current sampling time based on the average standardized monitoring value and a first preset number of historical standardized monitoring values corresponding to the monitoring parameter; determining a total standard deviation as a sum of standard deviations of all monitoring parameters corresponding to the current sampling time; A quotient of a standard deviation corresponding to the monitoring parameter at the current sampling time and the total standard deviation is determined as a weight corresponding to the monitoring parameter at the current sampling time.

6. The method of hermetic detection of a battery pack according to claim 1, wherein The method further includes: if the leakage score is in a first preset score interval, determining that the battery pack is airtight normal; if the leakage score is in a second preset score interval, determining that the battery pack has a leak and controlling an alarm device to alarm; if the leakage score is in a third preset score interval, determining that the battery pack has a leak, cutting off a power supply source of the battery pack, and controlling the alarm device to alarm, wherein an upper limit of the first preset score interval is not greater than a lower limit of the second preset score interval, and an upper limit of the second preset score interval is not greater than a lower limit of the third preset score interval.

7. A gas tightness detection device of a battery pack, characterized by, The airtight detection device includes: an acquisition module configured to acquire a sensor sampling interval of each of a plurality of monitoring parameters of the battery pack; an averaging module configured to average all of the acquired sensor sampling intervals and determine an average value as a sampling interval of each of the monitoring parameters; an estimated monitoring value determination module configured to, for each of the monitoring parameters, determine an estimated monitoring value of the monitoring parameter at a current sampling time based on two initial sampling times of the monitoring parameter with the smallest time difference from the current sampling time, wherein the current sampling time is determined based on the sampling interval, and the initial sampling times are determined based on the sensor sampling interval of the monitoring parameter; a standardized monitoring value determination module configured to determine a standardized monitoring value of the monitoring parameter at the current sampling time based on the estimated monitoring value; a leakage score determination module configured to determine a leakage score of the battery pack based on the standardized monitoring value of each of the monitoring parameters at the current sampling time; and an airtight state determination module configured to determine an airtight state of the battery pack based on the leakage score.

8. The gas tightness detection apparatus of the battery pack according to claim 7, characterized by, The estimated monitoring value determination module is specifically configured to: for each of the monitoring parameters, perform interpolation operation on monitoring values corresponding to two initial sampling times of the monitoring parameter with the smallest time difference from the current sampling time to obtain an initial estimated monitoring value of the monitoring parameter at the current sampling time; and determine an average value between the initial estimated monitoring value and a first preset number of historical estimated monitoring values corresponding to the monitoring parameter as the estimated monitoring value of the monitoring parameter at the current sampling time.

9. An electronic device, comprising: The method further includes: a processor, a memory, and a bus, the memory stores machine readable instructions executable by the processor, when the electronic device is running, the processor and the memory communicate through the bus, the machine readable instructions are executed by the processor to perform the steps of the airtight detection method of the battery pack according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, the computer program is executed by the processor to perform the steps of the airtight detection method of the battery pack according to any one of claims 1 to 6.

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