Reliability detection method, monitoring method, detection device, monitoring device, electronic equipment, detection system, battery pack, electric equipment, medium and program product

Abstract

The invention provides a reliability detection method, a monitoring method, a detection device, a monitoring device, electronic equipment, a detection system, a battery pack, electric equipment, a medium and a program product. The method comprises the following steps: acquiring load data of the battery pack, and detecting the fatigue reliability of the battery pack based on the load data of the battery pack. The fatigue reliability of the overall structure of the battery pack can be detected, and the use safety of the battery pack is improved.

Description

Technical Field

[0001] This application relates to battery detection technology, and in particular to a reliability detection method, a monitoring method, a detection device, a monitoring device, an electronic device, a detection system, a battery pack, an electrical equipment, a medium, and a program product. Background Art

[0002] As a core component of electric vehicles and hybrid electric vehicles, the reliability of the battery pack is directly related to the use safety of the whole vehicle. Traditional battery pack reliability analysis methods usually focus on detecting the electrochemical performance of the battery pack, and evaluate the safety of the battery pack by evaluating the state of charge, state of health, service life, etc. of the battery.

[0003] However, electric vehicles and hybrid electric vehicles need to drive on various different road conditions, and the diverse road environments will impose different mechanical stresses and vibration excitations on the battery pack. Under this driving condition, mechanical stresses and vibration excitations may cause the risk of fatigue damage to the welded joints at multiple parts of the battery pack.

[0004] Therefore, detecting the fatigue reliability of the battery pack during driving on different roads is of great significance for analyzing the reliability of electric vehicles. Summary of the Invention

[0005] This application provides a reliability detection method, a monitoring method, a detection device, a monitoring device, an electronic device, a detection system, a battery pack, an electrical equipment, a medium, and a program product to solve the problem in the prior art that the fatigue reliability of the overall structure of the battery pack cannot be detected.

[0006] In a first aspect, this application provides a reliability detection method, and the method includes:

[0007] Obtain the load data of the battery pack;

[0008] Based on the load data of the battery pack, detect the fatigue reliability of the battery pack.

[0009] Optionally, the detecting the fatigue reliability of the battery pack based on the load data of the battery pack includes:

[0010] Based on the load data of the battery pack, obtain the stress data of the connection part of the battery pack;

[0011] Based on the stress data of the connection part of the battery pack, detect the fatigue reliability of the battery pack.

[0012] Optionally, the load data includes: the acceleration load of the battery pack; the obtaining the stress data of the connection part of the battery pack based on the load data of the battery pack includes:

[0013] Based on the acceleration load, using the finite element simulation model of the overall structure of the battery pack, obtain the stress data of the connection part of the battery pack.

[0014] Optionally, the load data further includes: the physical force load on the first connection part of the battery pack;

[0015] The obtaining of the stress data of the connection part of the battery pack based on the load data of the battery pack includes:

[0016] If, based on the acceleration load, using the finite element simulation model of the overall structure of the battery pack, the stress data of the first connection part of the battery pack is not obtained, then based on the physical force load of the first connection part, using the finite element simulation model of the local structure of the battery pack, obtain the stress data of the first connection part.

[0017] Optionally, the load data further includes: the strain load on the second connection part of the battery pack;

[0018] The obtaining of the stress data of the connection part of the battery pack based on the load data of the battery pack includes:

[0019] If, based on the acceleration load, using the finite element simulation model of the overall structure of the battery pack, the stress data of the second connection part of the battery pack is not obtained, then based on the strain load of the second connection part and the material elastic parameters of the second connection part, obtain the stress data of the second connection part.

[0020] Optionally, the detecting of the fatigue reliability of the battery pack based on the stress data of the connection part of the battery pack includes:

[0021] Based on the stress data of the connection part, determine the cumulative amount of fatigue damage of the connection part;

[0022] Based on the cumulative amount of fatigue damage of the connection part, detect the fatigue reliability of the battery pack.

[0023] Optionally, the determining of the cumulative amount of fatigue damage of the connection part based on the stress data of the connection part includes:

[0024] Based on the stress data of the connection part, determine the current fatigue damage contribution amount of the connection part;

[0025] Based on the sum of the current fatigue damage contribution amount of the connection part and the previous cumulative amount of fatigue damage of the connection part, determine the cumulative amount of fatigue damage of the connection part.

[0026] Optionally, determining the current fatigue damage contribution of the connection part based on the stress data of the connection part includes:

[0027] Based on the stress data of the connection part and the mapping relationship between the stress data and the life of the battery pack, determining the expected life currently corresponding to the connection part;

[0028] Based on the actual life of the connection part and the expected life currently corresponding thereto, determining the current fatigue damage contribution of the connection part.

[0029] Optionally, determining the current fatigue damage contribution of the connection part based on the actual life of the connection part and the expected life currently corresponding thereto includes:

[0030] Based on the quotient of the actual life of the connection part and the expected life currently corresponding thereto, determining the current fatigue damage contribution of the connection part.

[0031] Optionally, detecting the fatigue reliability of the battery pack based on the cumulative fatigue damage amount of the connection part includes:

[0032] If the cumulative fatigue damage amount of the connection part is less than the first critical value, it is determined that the battery pack has not suffered fatigue damage;

[0033] If the cumulative fatigue damage amount of the connection part is greater than or equal to the first critical value, it is determined that the battery pack has fatigue damage.

[0034] Optionally, the method further includes:

[0035] Based on the fatigue reliability detection result of the battery pack, determining the fatigue reliability warning level of the battery pack;

[0036] Based on the fatigue reliability warning level, performing a warning operation corresponding to the level.

[0037] Optionally, determining the fatigue reliability warning level of the battery pack based on the fatigue reliability detection result of the battery pack includes:

[0038] If the cumulative fatigue damage amount of the connection part is less than the first critical value, it is determined that the fatigue reliability warning level of the battery pack is level one;

[0039] If the cumulative fatigue damage amount of the connection part is greater than or equal to the first critical value and less than the second critical value, it is determined that the fatigue reliability warning level of the battery pack is level two;

[0040] If the cumulative fatigue damage amount of the connection part is greater than or equal to the second critical value, it is determined that the fatigue reliability warning level of the battery pack is level three.

[0041] Optionally, performing an early warning operation corresponding to the fatigue reliability early warning level, including:

[0042] In the case that there is a connection part with a fatigue reliability early warning level of level two, and / or there is a connection part with a fatigue reliability early warning level of level three, output a reminder message, where the reminder message is used to indicate the connection part with fatigue damage and the degree of fatigue damage; the degree of fatigue damage is positively correlated with the cumulative amount of fatigue loss.

[0043] Optionally, the method further includes:

[0044] If the fatigue reliability detection result of the battery pack indicates that the battery pack has not suffered fatigue damage, then predict the remaining life of the battery pack based on the actual life of the connection part and the current corresponding expected life;

[0045] Output the predicted remaining life of the battery pack.

[0046] Optionally, predicting the remaining life of the battery based on the actual life of the connection part and the current corresponding expected life includes:

[0047] Based on the actual life of the connection part and the current corresponding expected life, obtain the initial remaining life of the battery pack corresponding to the connection part;

[0048] Based on the initial remaining life of the battery pack corresponding to each connection part, obtain the remaining life of the battery pack.

[0049] Optionally, the method is applied to a server, and obtaining the load data of the battery pack includes:

[0050] Obtain the reported abnormal load data.

[0051] Optionally, the abnormal load data includes: at least one load data greater than or equal to the corresponding threshold.

[0052] In a second aspect, the present application provides a method for monitoring the reliability of a battery pack, the method including:

[0053] Obtain the load data of the battery pack;

[0054] Report the load data of the battery pack to the server so that the server uses the method according to any one of the first aspect to detect the fatigue reliability of the battery pack.

[0055] Optionally, reporting the load data of the battery pack to the server includes:

[0056] In the case of abnormal load data, report the abnormal load data of the battery pack to the server.

[0057] Optionally, the abnormal load data includes:

[0058] At least one load data greater than or equal to the corresponding threshold.

[0059] Optionally, the method further includes:

[0060] If a reminder message sent by the server based on the fatigue reliability detection result of the battery pack is received, output the reminder message, where the reminder message is used to indicate the connection part with fatigue damage and the degree of fatigue damage; the degree of fatigue damage is positively correlated with the cumulative amount of fatigue loss.

[0061] Optionally, the method further includes:

[0062] If the remaining life of the battery predicted by the server when the fatigue reliability detection result of the battery pack indicates that the battery pack has not suffered fatigue damage is received;

[0063] Output the predicted remaining life of the battery pack.

[0064] In a third aspect, the present application provides a reliability detection device, where the reliability detection device includes:

[0065] An acquisition module, configured to acquire the load data of the battery pack;

[0066] A processing module, configured to detect the fatigue reliability of the battery pack based on the load data of the battery pack.

[0067] In a fourth aspect, the present application provides a reliability monitoring device, characterized in that the reliability detection device includes:

[0068] An acquisition module, which acquires the load data of the battery pack.

[0069] A transceiver module, which reports the load data of the battery pack to the server, so that the server detects the fatigue reliability of the battery pack by using the method according to any item of the first aspect.

[0070] In a fifth aspect, the present application provides a reliability detection system, characterized in that the reliability detection system includes: a data analysis device and a collection device; the data analysis device is communicatively connected to the collection device;

[0071] The collection device is disposed on the battery pack and is configured to acquire the load data of the battery pack;

[0072] The data analysis device is used to execute the methods described in any one of the first aspect and any one of the second aspect.

[0073] Optionally, the acquisition device includes: an acceleration acquisition device for acquiring the acceleration load of the battery pack.

[0074] Optionally, the acceleration acquisition device is arranged at the side beam of the battery pack tray.

[0075] Optionally, the acquisition device further includes: a physical force acquisition device arranged at the first connection part of the battery pack for acquiring the physical force load of the first connection part of the battery pack.

[0076] Optionally, the first connection part includes at least one of the following: the position where the bolt is located, the liquid cooling plate support structure, and the battery cell shell support structure.

[0077] Optionally, the acquisition device further includes: a strain acquisition device arranged at the second connection part of the battery pack for acquiring the strain load of the second connection part of the battery pack.

[0078] Optionally, the second connection part includes at least one of the following: the welding joint of the tray side beam, the welding joint of the battery cell shell, the welding joint of the liquid cooling plate, and the weld at the lifting lug.

[0079] In a sixth aspect, the present application provides a battery pack, which includes: a reliability detection system as described in any one of the fifth aspect.

[0080] Optionally, the reliability detection system is a battery management system.

[0081] In a seventh aspect, the present application provides an electrical equipment, which includes: a battery pack as described in any one of the sixth aspect.

[0082] In an eighth aspect, the present application provides an electronic device, which includes: a processor and a memory communicatively connected to the processor;

[0083] The memory stores computer-executable instructions;

[0084] The processor executes the computer-executable instructions stored in the memory to implement the methods described in any one of the first aspect or any one of the second aspect.

[0085] In a ninth aspect, the present application provides a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, they are used to implement the methods described in any one of the first aspect or any one of the second aspect.

[0086] In a tenth aspect, the present application provides a computer program product, including a computer program which, when executed by a processor, implements the method according to any one of the first aspect or any one of the second aspect.

[0087] The reliability detection method, monitoring method, detection device, monitoring device, electronic device, detection system, battery pack, electrical equipment, medium and program product provided by the present application can detect the fatigue reliability of the battery pack by obtaining the load data of the battery pack, and further based on the load data reflecting the structural stress of the battery pack, thus solving the problem in the prior art that the fatigue reliability of the overall structure of the battery pack cannot be detected, and improving the safety of the battery pack in use. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] The drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0089] Figure 1 FIG. is a schematic structural diagram of a reliability detection system provided by an embodiment of the present application;

[0090] Figure 2 FIG. is a schematic diagram of a possible installation position of a collection device provided by an embodiment of the present application;

[0091] Figure 3 FIG. is a schematic flow chart of a reliability detection method provided by an embodiment of the present application;

[0092] Figure 4 FIG. is a schematic flow chart of a method for detecting the fatigue reliability of a battery pack based on the load data of the battery pack provided by an embodiment of the present application;

[0093] Figure 5 FIG. is a schematic flow chart of a method for realizing the reliability detection of a battery pack provided by an embodiment of the present application;

[0094] Figure 6 FIG. is a schematic structural diagram of a reliability detection device provided by an embodiment of the present application;

[0095] Figure 7 FIG. is a schematic structural diagram of a reliability monitoring device provided by an embodiment of the present application;

[0096] Figure 8 FIG. is a schematic structural diagram of an electronic device provided by an embodiment of the present application.

[0097] Reference Signs:

[0098] 21 - acceleration acquisition device; 22 - strain acquisition device.

[0099] Through the above-mentioned drawings, specific embodiments of the present application have been shown, and more detailed descriptions will be provided hereinafter. These drawings and written descriptions are not intended to limit the scope of the concept of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. Detailed Description of the Embodiments

[0100] Here, exemplary embodiments will be described in detail, and examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0101] As a core component of electric vehicles and hybrid vehicles, the reliability of the battery pack is directly related to the use safety of the entire vehicle. The reliability of the battery pack refers to the ability of the battery pack to continuously and stably provide the expected performance and safety guarantee under specific environmental and operating conditions. It involves the durability, stability, and safety of the battery pack under various environments and working conditions, especially the damage resistance when affected by adverse factors such as physical damage, overcharging, over-discharging, and extreme temperatures.

[0102] The reliability of the battery pack is affected by various factors such as the electrochemical performance, structure, internal and external temperatures, and charge and discharge conditions of the battery pack. Traditional battery pack reliability analysis methods usually focus on detecting the electrochemical performance of the battery pack and evaluating the reliability of the battery pack by assessing conditions such as the state of charge, state of health, and service life of the battery.

[0103] However, during the actual operation of electric vehicles and hybrid vehicles, the battery pack will face mechanical stresses and vibration excitations brought about by various road conditions. Especially in the case of collision, extrusion, and deformation, pressure and impact loads may cause fatigue damage to the welded connection parts of key components such as battery cells, liquid cooling plates, and tray side beam lugs in the battery pack. These fatigue damages may lead to local stress concentration, further causing the formation and expansion of cracks, and ultimately reducing the reliability of the overall structure of the battery pack.

[0104] Traditional battery pack reliability analysis methods cannot detect the fatigue reliability that the battery pack may occur during the actual operation of electric vehicles and hybrid vehicles. Therefore, detecting the fatigue reliability of the battery pack during driving on different roads is of great significance for analyzing the reliability of electric vehicles.

[0105] In view of this, an embodiment of the present application provides a reliability detection method, which performs fatigue reliability detection on a battery pack through the load data of the battery pack, and solves the problem in the prior art that the fatigue reliability of the overall structure of the battery pack cannot be detected.

[0106] Figure 1 It is a schematic structural diagram of a reliability detection system provided by an embodiment of the present application, as Figure 1 shown, the reliability detection system includes: a collection device and a data analysis device.

[0107] The collection device is used to collect the load data of the battery pack. The load data is used to characterize the force acting on the structure of the battery pack. The embodiment of the present application does not limit the type of the load data. For example, it can be one or more types of load data that can characterize the force-bearing situation of the structure of the battery pack. For example, acceleration load, physical force load, vibration load, strain load, etc.

[0108] The structure of the battery pack has multiple connection parts. The connection parts are mechanical connection areas between battery cells, between battery cells and the battery management system, and between the battery pack and external devices. When an external force acts on the structure of the battery pack, unstable deformation or damage will occur first at its connection parts, resulting in fatigue loss. Therefore, in the embodiment of the present application, the collection device can be set at one or more connection parts of the structure of the battery pack, specifically related to the type of load data required by the battery pack.

[0109] The connection parts of the structure of the battery pack may include, for example, a first connection part and / or a second connection part. Among them, the first connection part may be a part using a detachable connection method such as a bolt or a buckle. Exemplarily, the first connection part may include, for example, the position where the bolt of the battery pack structure is located, the liquid cooling plate support structure, and the battery cell shell support structure.

[0110] The second connection part may be a part using a welded connection. Exemplarily, the second connection part may include, for example, connection parts such as the side beam of the battery pack tray, the battery cell shell, and the welded joint part of the liquid cooling plate.

[0111] It should be understood that in addition to the first connection part and the second connection part, it is not limited whether there are other connection parts on the structure of the battery pack.

[0112] In addition, the above division of the connection parts is only for illustration. Specifically, according to the structural design of the battery pack and the requirements of fatigue reliability detection, the connection parts using different connection methods can be divided, and this is not limited.

[0113] Figure 2 It is a schematic diagram of a possible installation position of the collection device provided by an embodiment of the present application.

[0114] Exemplarily, the load data includes acceleration loads. The acquisition device may include, for example: an acceleration acquisition device 21, which may be, for example, an acceleration sensor or any device capable of acquiring acceleration loads, and is used to detect the acceleration loads of the entire battery pack and each connection part. The acceleration load refers to the force generated on the battery pack structure due to the acceleration change caused during the actual use of the battery pack.

[0115] Exemplarily, taking the acceleration sensor as an example, the acceleration sensor can acquire acceleration signals during the operation of the battery pack, convert the acceleration signals into acceleration waveform signals, and then transform them into acceleration loads.

[0116] The entire battery pack refers to the dynamic response of the entire battery pack as a complete structure, including the responses of all its components such as its housing, internal modules, and battery cells to external loads. Each connection part of the battery pack (at least including the above-mentioned first connection part and second connection part) focuses on the acceleration response of the connection parts between various parts inside the battery pack and those connected to the external structure under the action of loads. By detecting the acceleration loads of the entire battery pack and each connection part, the fatigue reliability of the battery pack can be detected more comprehensively.

[0117] As Figure 2 shown, the acceleration acquisition device 21 can be installed at any position of the battery pack. For example, it can be installed at the side beams on one or both sides of the battery pack tray.

[0118] Exemplarily, when the load data includes physical force loads, the acquisition device may include, for example, a physical force acquisition device installed at the first connection part, and the physical force acquisition device is used to detect the physical force loads at the first connection part of the battery pack. Among them, the physical force load refers to the direct physical force received by the battery pack during actual use, such as impact force, tensile force, or pressure, etc.

[0119] A possible implementation manner is that the physical force acquisition devices provided on the battery pack can all be the same type of physical force sensor, or corresponding types of sensors can be set according to the connection method of the connection part and the structure of the connection part. For example, a ring load washer force sensor can be installed at the lug part of the battery pack tray to detect the physical force loads at the lug part. Micro pressure sensors and / or thin film pressure sensors can be installed at parts such as the liquid cooling plate support and the battery cell shell support of the battery pack to detect the physical force loads at the parts of the battery pack prone to fatigue failure.

[0120] Installing different types of physical force sensors at different connection parts of the battery pack can achieve comprehensive and high-precision detection of the force conditions at the key connection parts of the battery pack, which helps to identify the weak links at the connection parts of the battery pack.

[0121] Exemplarily, taking a physical force sensor as an example, the physical force sensor can collect physical force signals during the operation of the battery pack, convert the physical force signals into the magnitude of the force, and then convert it into a physical force load.

[0122] Exemplarily, the load data includes strain loads. The acquisition device can, for example, include a strain acquisition device 22 installed at the second connection part to detect the strain load of the second connection part of the battery pack. Among them, the strain load refers to the internal stress generated by the deformation of the material of the connection part of the battery pack due to external stress during the use of the battery pack.

[0123] Figure 2 FIG. is a schematic diagram of the strain acquisition device 22 installed in the lug weld area of the side beams on both sides of the battery pack tray.

[0124] The strain acquisition device 22 can, for example, include any device such as a strain gauge that can detect strain loads.

[0125] Exemplarily, taking a strain gauge as an example, the strain gauge can collect voltage signals during the operation of the battery pack, convert the voltage signals into strain signals, and then convert them into strain loads.

[0126] The acquisition devices in the embodiments of the present application are all communicatively connected to the data analysis device for sending the load data collected by them to the data analysis device.

[0127] The data analysis device is used to detect the fatigue reliability of the battery pack based on the load data of the battery pack collected by the acquisition device.

[0128] Alternatively, the data analysis device reports the load data of the battery pack collected to the data analysis device of the electrical device so that the data analysis device of the electrical device detects the fatigue reliability of the battery pack.

[0129] Alternatively, the data analysis device reports the load data of the battery pack collected to the server on the cloud side so that the server detects the fatigue reliability of the battery pack. The reporting mentioned here can be directly reported by itself, and the other is to report to the cloud through the data analysis device of the electrical device, which is specifically related to the product implementation.

[0130] In some embodiments, in the scenario where the data analysis device detects the fatigue reliability of the battery pack with the help of other devices, the data analysis device can directly send the obtained load data to other devices, or can first perform a preliminary analysis on the load data. When it is determined that the load data is abnormal and may cause fatigue loss, the abnormal load data is then sent to other devices for fatigue reliability detection.

[0131] In a data analysis device, there is, for example, a memory for storing data required for a reliability detection system to detect the reliability of a battery pack. Exemplarily, acceleration load thresholds, physical stress load thresholds, and strain load thresholds can be stored, etc.

[0132] In a specific implementation, the above-mentioned reliability detection system can be a Battery Management System (BMS). In this implementation mode, the data analysis device can be, for example, the Microcontroller Unit (MCU) of the BMS. That is, in this implementation mode, by adding a collection device as described above in the BMS, the BMS can implement the method of the embodiments of the present application.

[0133] First, an explanation will be given on how to perform fatigue reliability detection based on the load data of the battery pack. Figure 3 It is a schematic flowchart of a reliability detection method provided by an embodiment of the present application. As Figure 3 shown, the method may include the following steps:

[0134] S301. Obtain the load data of the battery pack.

[0135] As described above, the load data refers to the forces acting on each connection part of the battery pack. The load data here can be the load data collected by the aforementioned collection device, or the load data with anomalies in the load data collected by the collection device.

[0136] Among them, the abnormal load data can be the load data that significantly deviates from the normal load range. When such load data is detected, it indicates that the structure of the battery pack has suffered greater stress and may cause fatigue damage.

[0137] Exemplarily, the load data can be determined whether it is abnormal by comparing it with the corresponding threshold data.

[0138] S302. Detect the fatigue reliability of the battery pack based on the load data of the battery pack.

[0139] Fatigue reliability refers to the ability of the battery pack not to suffer fatigue damage after multiple load cycles under cyclic loads. It reflects the durability of the battery pack and is a key indicator for measuring how many cyclic loads the battery pack can withstand without failure during actual use. Cyclic loads refer to the load data acting on the connection part of the battery pack that periodically repeats over time.

[0140] For example, the load data of the battery pack can be input into a pre-trained neural network fatigue reliability detection model, and it is determined whether the battery pack has fatigue damage based on the result output by the neural network model. Among them, the neural network fatigue reliability detection model can be, for example, pre-trained according to historical load data.

[0141] Again, for example, the load data of the battery pack can be input into a fatigue reliability detection simulation model of the battery pack built in advance, and it is determined whether the battery pack has fatigue damage based on the result output by the simulation model.

[0142] Again, for example, based on the load data of the battery pack, the stress data of the connection part of the battery pack can be obtained. Based on the stress data of the connection part of the battery pack, the fatigue reliability of the battery pack is detected to determine whether the battery pack has fatigue damage.

[0143] Among them, the stress data can help understand the stress condition of the connection part of the battery pack under different load data conditions and detect the fatigue reliability of the battery pack structure. The embodiments of the present application do not limit the specific form of the stress data. The stress data can include, for example, the stress value of the connection part of the battery pack.

[0144] The reliability detection method provided by the present application solves the problem in the prior art that the fatigue reliability of the overall structure of the battery pack cannot be detected by obtaining the load data of the battery pack and then detecting the fatigue reliability of the battery pack through the load data of the connection part of the battery pack.

[0145] The following takes obtaining the stress data of the connection part of the battery pack based on the load data of the battery pack and detecting the fatigue reliability of the battery pack based on the stress data of the connection part of the battery pack as an example for description:

[0146] Figure 4 It is a schematic flow chart of a method for detecting the fatigue reliability of a battery pack based on the load data of the battery pack provided by an embodiment of the present application. As Figure 4 shown, step S302 includes:

[0147] S401. Based on the load data of the battery pack, obtain the stress data of the connection part of the battery pack.

[0148] Among them, the stress data of the connection part of the battery pack includes at least the stress data of the first connection part and / or the second part. The embodiments of the present application do not limit the form of the stress data, and it can be, for example, a stress value.

[0149] For example, stress data of the connection part of the battery pack can be obtained based on acceleration load data. Or, stress data of the connection part of the battery pack can be obtained based on physical force load. Or, stress data of the connection part of the battery pack can be obtained based on strain load. Or, stress data of the connection part of the battery pack can be obtained by combining the above two or three, which is specifically related to the type of connection part included in the battery pack.

[0150] Exemplarily, the load data of the battery pack can be input into an algorithm for calculating the stress data of the connection part of the battery pack, and the stress data of the connection part of the battery can be obtained through the algorithm.

[0151] For another example, the load data of the battery pack can be input into a pre-trained model for obtaining the stress data of the connection part of the battery pack, and the stress data of the connection part of the battery can be obtained through the model. This model can be pre-trained, for example, with historical load data and stress data of the connection part.

[0152] For another example, based on acceleration load, the stress data of the connection part of the battery pack can be obtained by using a finite element simulation model of the overall structure of the battery pack.

[0153] The finite element simulation model of the overall structure of the battery pack is a data model constructed by using finite element analysis technology. It can simulate the stress distribution of the overall structure of the battery pack and each connection part, so as to obtain the stress data of the connection part of the battery pack. This model can be pre-trained, for example, according to the load data of the overall structure of the battery pack. The embodiments of the present application do not limit the training method of the finite element simulation model of the overall structure of the battery pack.

[0154] Optionally, if stress data of a certain first connection part of the battery pack cannot be obtained by using the finite element simulation model of the overall structure of the battery pack based on acceleration load, then this part is not detected during this fatigue reliability test. Or, stress data of the first connection part can be further obtained by using a finite element simulation model of the local structure of the battery pack based on the physical force load of the first connection part.

[0155] Correspondingly, for the first connection part for which stress data has been obtained by using the finite element simulation model of the overall structure of the battery pack, the stress data can be directly used as the stress data of the first connection part, or stress data of the first connection part can be further obtained by using a finite element simulation model of the local structure of the battery pack based on the physical force load of the first connection part.

[0156] When the stress data of the first connection part obtained by these two methods are different, one of the stress data can be selected as the stress data of the first connection part, or the stress data of both can be statistically analyzed to obtain the stress data of the first connection part by means such as taking the average value. The embodiments of the present application do not limit this.

[0157] Through the above method, the accuracy and comprehensiveness of the obtained stress data of the first connection part can be improved, thereby improving the accuracy of subsequent fatigue reliability detection.

[0158] The above-mentioned finite element simulation model of the local structure of the battery pack refers to the finite element model established for the first connection part in the battery pack, which is used to analyze the performance of the first connection part when subjected to external loads.

[0159] Exemplarily, a finite element simulation model including all parts of the first connection part can be constructed, and the stress data of each part of the first connection part can be calculated through this model, where each part can be marked by a number. Or a finite element simulation model of the local structure can be established separately for each connection part. The embodiments of the present application do not limit this.

[0160] Optionally, if based on the acceleration load, the stress data of a certain second connection part of the battery pack cannot be obtained by using the finite element simulation model of the overall structure of the battery pack, then during this fatigue reliability detection, this part will not be detected. Or, the stress data of the second connection part can be further obtained based on the strain load of the second connection part and the material elastic parameters of the second connection part.

[0161] Correspondingly, for the second connection part for which the stress data has been obtained by using the finite element simulation model of the overall structure of the battery pack, the stress data can be directly used as the stress data of the second connection part, or the stress data of the second connection part can be further obtained based on the strain load of the second connection part and the material elastic parameters of the second connection part.

[0162] When the stress data of the second connection part obtained by these two methods are different, one of the stress data can be selected as the stress data of the second connection part, or the stress data of both can be statistically analyzed to obtain the stress data of the second connection part by means such as taking the average value. The embodiments of the present application do not limit this.

[0163] Among them, the material elastic parameters of the second connection part are the key elastic parameters of the material used at the second connection point of the battery pack. These parameters include elastic modulus, Poisson's ratio, etc. The elastic modulus is used to describe the ability of the material at the second connection point of the battery pack to resist deformation, and Poisson's ratio is used to describe the relative degree of transverse and longitudinal deformation of the material at the second connection point of the battery pack when stressed. These parameters jointly determine the mechanical response of the material at the second connection point of the battery pack when stressed, which is crucial for ensuring the structural stability and functionality of the second connection part.

[0164] Regarding how to obtain the stress data of the second connection part based on the strain load of the second connection part and the material elastic parameters of the second connection part, specifically, it can be based on the existing implementation methods of calculating stress data based on the elastic parameters and strain load of the part material, and this will not be elaborated here.

[0165] Through the above method, the accuracy and comprehensiveness of the obtained stress data of the second connection part can be improved, thereby improving the accuracy of subsequent fatigue reliability detection.

[0166] S402. Detect the fatigue reliability of the battery pack based on the stress data of the connection part of the battery pack.

[0167] For example, based on the stress data of the connection part of the battery pack and the mapping relationship between the stress data and the fatigue reliability of the battery pack, the fatigue reliability detection result of the battery pack can be obtained.

[0168] For another example, input the stress data of the connection part of the battery pack into a pre-trained fatigue reliability detection model, and detect the fatigue reliability of the battery pack based on the model. This model can be pre-trained according to historical data, for example.

[0169] For another example, based on the stress data of the connection part, determine the cumulative fatigue damage amount of the connection part. Based on the cumulative fatigue damage amount of the connection part, detect the fatigue reliability of the battery pack. Among them, the cumulative fatigue damage amount refers to the physical quantity of the material or structure of the connection part of the battery pack that gradually accumulates fatigue damage under cyclic loading until the reliability of the battery pack is finally damaged.

[0170] Exemplarily, based on the mapping relationship between the connection part and the cumulative fatigue damage amount, the fatigue damage amount of the connection part can be determined.

[0171] Exemplarily, based on the stress data of the connection part, the current fatigue damage contribution amount of the connection part can also be determined, and then based on the sum of the current fatigue damage contribution amount of the connection part and the previous cumulative fatigue damage amount of the connection part, the cumulative fatigue damage amount of the connection part can be determined.

[0172] Among them, the fatigue damage contribution amount is the fatigue damage generated by the connection part of the battery pack under cyclic loading.

[0173] For example, the stress data of the connection part is input into an algorithm for calculating the current fatigue damage contribution of the connection part, and the current fatigue damage contribution of the connection part is obtained through algorithm calculation.

[0174] For another example, based on the stress data of the connection part and the mapping relationship between the stress data and the life of the battery pack, the current corresponding expected life of the connection part is determined. Based on the actual life of the connection part and the currently corresponding expected life, the current fatigue damage contribution of the connection part is determined.

[0175] Among them, the expected life can be, for example, the number of cycles that the battery pack can withstand until fatigue damage occurs under the current cyclic load condition, or the duration that the battery pack can still work under the current cyclic condition. The actual life refers to the number of cycles that the battery pack has cycled under the current cyclic load condition, or the duration that the battery pack has worked under the current cyclic condition. The present application does not limit the manifestation forms of the expected life and the actual life.

[0176] The mapping relationship between the stress data and the life of the battery pack can be obtained, for example, through simulation analysis by a simulation model, or can be described based on the stress-life curve of the material of the connection part of the battery pack. The stress-life curve is a chart used to describe the fatigue performance of the connection part of the battery pack under cyclic load. This curve takes the stress data as the abscissa and the expected life as the ordinate, and shows the number of cycles that the material of the connection part of the battery pack can withstand under different stress levels until fatigue damage occurs.

[0177] Optionally, when the mapping relationship between the stress data and the life of the battery pack is described based on the stress-life curve of the material of the connection part of the battery pack, in this implementation manner, the expected life corresponding to the current connection part can be obtained through the stress-life curve of the material of the connection part of the battery pack and the current stress data. Subsequently, through the calculation method corresponding to the linear fatigue cumulative damage theory, based on the quotient of the expected life of the connection part and the currently corresponding expected life, the current fatigue damage contribution of the connection part is determined.

[0178] Among them, the linear fatigue cumulative damage theory is a theoretical model used to predict the fatigue life of the material of the connection part of the battery pack under different cyclic loads. The core assumption of this theory is that fatigue damage can be linearly accumulated, that is, the fatigue damage under different cyclic loads is independent of each other, and the total fatigue damage can be obtained by accumulating the fatigue damage under each cyclic load.

[0179] For example, it can be expressed by the following formula (1):

[0180]

[0181] Among them, D is the fatigue damage contribution, n is the expected life, and N is the expected life.

[0182] The damage contribution D under the current cyclic load is added to the cumulative fatigue damage of the connection part before, to obtain the cumulative fatigue damage of the battery pack connection part under the current cyclic load.

[0183] The above method for obtaining the cumulative fatigue damage of the battery pack through the fatigue damage contribution can calculate the fatigue damage amount of the battery pack connection part based on the fatigue life of the battery pack under different cyclic load conditions, thereby making the calculation of the cumulative fatigue damage of the battery pack more accurate, and further improving the accuracy of detecting fatigue reliability.

[0184] Exemplarily, based on the cumulative fatigue damage of the battery pack connection part under the current cyclic load, the fatigue reliability of the battery pack is detected.

[0185] For example, if the cumulative fatigue damage of the connection part is less than the first critical value, it is determined that the battery pack has no fatigue damage. If the cumulative fatigue damage of the connection part is greater than or equal to the first critical value, it is determined that the battery pack has fatigue damage.

[0186] Among them, the first critical value is a pre-determined threshold, and the first critical value is used to judge whether the connection part of the battery pack begins to show fatigue damage. Since there are different connection parts of the battery pack and the fatigue characteristics of the structures of each connection part are different, therefore, the fatigue characteristics of the part with the weakest fatigue characteristics among the connection parts of the battery pack can be used as the standard for setting the first critical value. It is usually set as the maximum bearing capacity of the connection part with the weakest fatigue characteristics of the battery pack under normal working conditions.

[0187] Optionally, in some embodiments, respective corresponding critical values can also be set for each connection part, so that the corresponding fatigue damage of each connection part can be determined, and thus more refined detection results can be obtained.

[0188] Optionally, in some embodiments, for example, the fatigue reliability warning level of the battery pack can also be determined based on the fatigue reliability detection result of the battery pack, and then corresponding warning operations of the corresponding level are executed based on the fatigue reliability warning level.

[0189] The division of the fatigue reliability warning level is specifically related to the warning requirements of the user. For example, the warning level can be divided into two categories, low level and high level, or the warning can be divided into three categories, low level, medium level, high level, or level one, level two, level three, etc.

[0190] Taking the classification of early warning levels into three categories as an example, exemplarily, if the cumulative amount of fatigue damage at the connection part is less than the first critical value, the fatigue reliability early warning level of the battery pack is determined to be level one. If the cumulative amount of fatigue loss at the connection part is greater than or equal to the first critical value and less than the second critical value, the fatigue reliability early warning level of the battery pack is determined to be level two. If the cumulative amount of fatigue loss at the connection part is greater than or equal to the second critical value, the fatigue reliability early warning level of the battery pack is determined to be level three.

[0191] Among them, the second critical value is a pre-determined safety threshold, and the second critical value is used to judge whether there is serious fatigue damage to the material or structure of the connection part of the battery pack. Since there are different connection parts in the battery pack and the fatigue characteristics of the structures of each connection part are different, therefore, the fatigue characteristics of the part with the strongest fatigue characteristics among the connection parts of the battery pack are used as the standard for setting the second critical value. It is usually set to the maximum bearing capacity of the connection part with the strongest fatigue characteristics of the battery pack under normal working conditions. Exceeding this value may cause the material or structure of the connection part of the battery pack to fail and the battery pack to be damaged.

[0192] Optionally, in some embodiments, a corresponding second critical value can also be set for each connection part, so that the corresponding early warning level can be determined for each connection part, and thus a more refined early warning result can be obtained.

[0193] Exemplarily, if there is a connection part with a fatigue reliability early warning level of level two, and / or, in the case of a connection part with a fatigue reliability early warning level of level three, a reminder message is output, and the reminder message is used to indicate the connection part with fatigue damage and the degree of fatigue damage. The degree of fatigue damage is positively correlated with the cumulative amount of fatigue loss.

[0194] The reminder message can be used to remind to take necessary measures for the battery pack in time to avoid the further deterioration of the fatigue damage problem of the battery pack or cause other serious consequences.

[0195] For example, the reminder message can be broadcast by voice, or, the reminder message can also be fed back through the color, or brightness, or indicator light displayed by the sound and light device, or, the reminder message can also be output. The embodiments of the present application do not limit the form of the reminder message.

[0196] In this example, for the connection part with a warning level of level one, it can be indicated through the reminder message that there is no fatigue loss in this connection part, or, no treatment is performed on these parts.

[0197] By providing the fatigue reliability early warning level of the battery pack, when the battery pack suffers from fatigue damage, a reminder message can be sent in time to prevent the accidental failure of the battery pack.

[0198] Optionally, when the fatigue reliability detection result of the battery pack indicates that no fatigue damage has occurred to the battery pack, the remaining life of the battery can also be predicted based on the actual life of the connection part and the current corresponding expected life, and the predicted remaining life of the battery pack can be output.

[0199] The remaining life can be, for example, the length of time and / or the number of cycles that the battery pack can still operate under the current cyclic load. The embodiments of the present application do not limit the remaining life.

[0200] In a specific implementation manner, based on the actual life of the connection part and the current corresponding expected life, the initial remaining life of the battery pack corresponding to the connection part is obtained. Exemplarily, the initial remaining life of the battery pack can be obtained by subtracting the actual life of the connection part from the expected life of the connection part. Then, based on the initial remaining life of the battery pack corresponding to each connection part, the remaining life of the battery pack is obtained. Exemplarily, the initial remaining life of any one connection part can be selected as the remaining life of the battery pack, or the shortest initial remaining life can be selected as the remaining life of the battery pack. The embodiments of the present application do not limit this.

[0201] Through the method for predicting the remaining life of the battery pack, accurate fatigue life prediction is provided, which helps to take preventive measures in a timely manner, extend the service life of the battery pack, and thus improve the overall safety of the battery pack during use.

[0202] The reliability detection method provided by the present application obtains the stress data of the connection part of the battery pack through the load data of the battery pack, and detects the fatigue reliability of the battery pack based on the stress data of the connection part of the battery pack. This method obtains the stress data of the connection part of the battery pack in various ways and detects its fatigue reliability, and can more accurately detect the fatigue damage state of the battery pack. By providing the fatigue reliability warning level of the battery pack and the method for predicting the remaining life of the battery pack, the fatigue reliability of the battery pack can be effectively monitored, and the safety of the battery pack during use is improved.

[0203] The above content introduces how to detect the fatigue reliability of the battery pack based on the load data of the battery pack collected once. Therefore, based on the load data continuously collected by the collection device, the above method can be used to continuously monitor the fatigue reliability of the battery pack.

[0204] In addition, the execution entity of the following embodiments can be any device capable of determining the fatigue reliability of a battery pack based on the load data of the battery pack connection part. For example, it can be a data analysis device of the battery pack itself, a device with processing capabilities in the electrical equipment to which the battery pack belongs, or the server corresponding to the battery pack. The server mentioned here can be a system or platform capable of detecting the fatigue reliability of the battery pack, such as a battery pack detection platform, etc. The server can be deployed in the cloud and obtain the load data of the battery pack by means of remote communication with the data analysis device, so as to detect the fatigue reliability of the battery pack and realize the monitoring of the fatigue reliability of the battery pack.

[0205] Taking the example that the data analysis device reports the collected load data of the battery pack to the server located on the cloud side so that the server monitors the fatigue reliability of the battery pack, how to realize the reliability monitoring of the battery pack will be described below. Figure 5 It is a schematic flowchart of a method for realizing the reliability monitoring of a battery pack provided by an embodiment of the present application. As Figure 5 shown, the method may include the following steps, for example:

[0206] S501. The data analysis device obtains the load data of the battery pack.

[0207] S502. The data analysis device determines whether the load data of the battery pack is abnormal load data.

[0208] Exemplarily, the data analysis device determines whether there is load data greater than or equal to the corresponding threshold in the load data. If so, it indicates that the current load data is abnormal load data, and the data analysis device can send the load data to the server.

[0209] Among them, the threshold is the maximum value of the load data that the battery pack connection part can withstand. Exceeding this critical value indicates that the current battery pack may be abnormal, and further judgment of the abnormal load data is required on this basis. The threshold can be, for example, pre-set in the memory of the data analysis device as shown above, or transmitted by the server to the data analysis device.

[0210] If so, execute S503. If not, it is considered that the current load data is normal load data and no response action is generated.

[0211] S503. The data analysis device sends the load data to the server.

[0212] S504. The server obtains the stress data of the connection part of the battery pack based on the load data of the battery pack.

[0213] S505. The server determines the current fatigue damage contribution amount of the connection part based on the stress data of the connection part.

[0214] S506. The server determines the cumulative fatigue damage of the connection part based on the sum of the current fatigue damage contribution of the connection part and the previous cumulative fatigue damage of the connection part.

[0215] S507. The server detects the fatigue reliability of the battery pack based on the cumulative fatigue damage of the connection part.

[0216] Among them, the method for the server to detect the fatigue reliability of the battery pack based on the cumulative fatigue damage of the connection part is as shown above and will not be elaborated here.

[0217] S508. The server determines the fatigue reliability warning level of the battery pack based on the fatigue reliability detection result of the battery pack.

[0218] If the fatigue reliability warning level of the battery pack is level one, then execute S509. If the fatigue reliability warning level of the battery pack is level two or three, then execute S510.

[0219] S509. The server outputs the predicted remaining life of the battery pack.

[0220] For example, the server sends the predicted remaining life of the battery pack to the data analysis device so that the data analysis device displays the remaining life, or the data analysis device sends it to the control device of the electrical equipment where the battery pack is located so that the control device displays the remaining life through the display device. Taking the electrical equipment as an electric vehicle as an example, the in-vehicle terminal of the electric vehicle can display the remaining life through the display screen.

[0221] Or the server sends the predicted remaining life of the battery pack to the control device of the electrical equipment where the battery pack is located so that the control device displays the remaining life through the display device.

[0222] After executing step S509, after receiving the load data reported by the data analysis device again, it can continue to return to execute step S504 to continuously monitor the fatigue reliability of the battery pack.

[0223] S510. The server outputs a reminder message for indicating the connection part with fatigue damage and the degree of fatigue damage.

[0224] The degree of fatigue damage mentioned here can be represented by the corresponding reliability warning level, or can be general or severe.

[0225] For example, the server sends a reliability warning level to the data analysis device so that the data analysis device displays the reliability warning level, or the data analysis device sends it to the control device of the electrical equipment where the battery pack is located so that the control device displays the reliability warning level through a display device. Taking an electric vehicle as an example of the electrical equipment, the on-vehicle terminal of the electric vehicle can display the reliability warning level through a display screen. Or the server sends the reliability warning level of the predicted battery pack to the control device of the electrical equipment where the battery pack is located so that the control device displays the reliability warning level through a display device.

[0226] After step S510 is executed, after receiving the load data reported by the data analysis device again, step S504 can be continued to be executed to continuously monitor the fatigue reliability of the battery pack.

[0227] The reliability monitoring method provided by this application obtains the stress data of the connection part of the battery pack through the load data of the real-time battery pack, and detects the fatigue reliability of the battery pack based on the stress data of the connection part of the battery pack. This method can continuously monitor the fatigue reliability of the battery pack by obtaining the load data of the battery pack in real time, and provide a fatigue reliability warning level of the battery pack and a prediction method for the remaining life of the battery pack based on the fatigue reliability of the battery, thereby improving the use safety of the battery pack.

[0228] Figure 6 It is a schematic structural diagram of a reliability detection device provided by an embodiment of this application, as Figure 6 shown, the device includes: an acquisition module 601 and a processing module 602.

[0229] The acquisition module 601 is used to acquire the load data of the battery pack.

[0230] The processing module 602 is used to detect the fatigue reliability of the battery pack based on the load data of the battery pack.

[0231] Optionally, the processing module 602 is specifically configured to obtain the stress data of the connection part of the battery pack based on the load data of the battery pack. Detect the fatigue reliability of the battery pack based on the stress data of the connection part of the battery pack.

[0232] Optionally, the load data includes: the acceleration load of the battery pack. The processing module 602 is specifically configured to obtain the stress data of the connection part of the battery pack by using the finite element simulation model of the overall structure of the battery pack based on the acceleration load.

[0233] Optionally, the load data further includes: the physical stress load of the first connection part of the battery pack. The processing module 602 is further configured to, if based on the acceleration load, the stress data of the first connection part of the battery pack cannot be obtained by using the finite element simulation model of the overall structure of the battery pack, then based on the physical stress load of the first connection part, use the finite element simulation model of the local structure of the battery pack to obtain the stress data of the first connection part.

[0234] Optionally, the load data further includes: the strain load of the second connection part of the battery pack. The processing module 602 is further configured to, if based on the acceleration load, the stress data of the second connection part of the battery pack cannot be obtained by using the finite element simulation model of the overall structure of the battery pack, then based on the strain load of the second connection part and the material elastic parameters of the second connection part, obtain the stress data of the second connection part.

[0235] Optionally, the processing module 602 is specifically configured to determine the cumulative amount of fatigue damage of the connection part based on the stress data of the connection part. Detect the fatigue reliability of the battery pack based on the cumulative amount of fatigue damage of the connection part.

[0236] For example, the processing module 602 is specifically configured to determine the current fatigue damage contribution amount of the connection part based on the stress data of the connection part. Determine the cumulative amount of fatigue damage of the connection part based on the sum of the current fatigue damage contribution amount of the connection part and the previous cumulative amount of fatigue damage of the connection part.

[0237] A possible implementation, the processing module 602 is specifically configured to determine the expected life corresponding to the connection part currently based on the stress data of the connection part and the mapping relationship between the stress data and the life of the battery pack. Determine the current fatigue damage contribution amount of the connection part based on the actual life of the connection part and the currently corresponding expected life.

[0238] A possible implementation, the processing module 602 is specifically configured to determine the current fatigue damage contribution amount of the connection part based on the quotient of the actual life of the connection part and the currently corresponding expected life.

[0239] For example, the processing module 602 is specifically configured to determine that the battery pack has no fatigue damage if the cumulative amount of fatigue damage of the connection part is less than the first critical value. Determine that the battery pack has fatigue damage if the cumulative amount of fatigue loss of the connection part is greater than or equal to the first critical value.

[0240] Optionally, the processing module 602 is further configured to determine the fatigue reliability warning level of the battery pack based on the fatigue reliability detection result of the battery pack. Perform the warning operation corresponding to the level based on the fatigue reliability warning level.

[0241] For example, the processing module 602 is specifically configured to determine that the fatigue reliability warning level of the battery pack is level one if the cumulative amount of fatigue damage at the connection part is less than the first critical value. If the cumulative amount of fatigue loss at the connection part is greater than or equal to the first critical value and less than the second critical value, it is determined that the fatigue reliability warning level of the battery pack is level two. If the cumulative amount of fatigue loss at the connection part is greater than or equal to the second critical value, it is determined that the fatigue reliability warning level of the battery pack is level three.

[0242] For another example, the processing module 602 is specifically configured to output a reminder message when there is a connection part with a fatigue reliability warning level of level two and / or a connection part with a fatigue reliability warning level of level three. The reminder message is used to indicate the connection part with fatigue damage and the degree of fatigue damage. The degree of fatigue damage is positively correlated with the cumulative amount of fatigue loss.

[0243] Optionally, the processing module 602 is further configured to predict the remaining life of the battery based on the actual life of the connection part and the current corresponding expected life if the fatigue reliability detection result of the battery pack indicates that the battery pack has not suffered fatigue damage. Output the predicted remaining life of the battery pack.

[0244] For example, the processing module 602 is specifically configured to obtain the initial remaining life of the battery pack corresponding to the connection part based on the actual life of the connection part and the current corresponding expected life. Obtain the remaining life of the battery pack based on the initial remaining life of the battery pack corresponding to each connection part.

[0245] Optionally, the obtaining module 601 is specifically configured to obtain abnormal load data of the battery pack. For example, the abnormal load data includes at least one load data greater than or equal to the corresponding threshold.

[0246] The reliability detection device provided in the embodiments of the present application can be used to execute the foregoing reliability detection method. The implementation principle, process, and beneficial effects can be referred to the foregoing embodiments and will not be elaborated here.

[0247] Figure 7 FIG. is a schematic structural diagram of a reliability monitoring device provided in an embodiment of the present application, as Figure 7 shown. The device includes an obtaining module 701 and a transceiver module 702. Optionally, the device may further include an output module 703, for example.

[0248] The obtaining module 701 is configured to obtain the load data of the battery pack.

[0249] The transceiver module 702 is configured to report the load data of the battery pack to the server so that the server detects the fatigue reliability of the battery pack by using any method in the foregoing embodiments.

[0250] Optionally, the obtaining module 701 is specifically configured to report the abnormal load data of the battery pack to the server when the load data is abnormal. For example, the abnormal load data includes: at least one load data greater than or equal to the corresponding threshold.

[0251] Optionally, the output module 703 is configured to output a reminder message if the transceiver module 702 receives a reminder message sent by the server based on the fatigue reliability detection result of the battery pack. The reminder message is used to indicate the connection part with fatigue damage and the degree of fatigue damage. The degree of fatigue damage is positively correlated with the cumulative amount of fatigue loss.

[0252] Optionally, the output module 703 is further configured to output the predicted remaining life of the battery pack if the transceiver module 702 receives the predicted remaining life of the battery sent by the server when the fatigue reliability detection result of the battery pack indicates that the battery pack has not suffered fatigue damage.

[0253] The reliability monitoring device provided in the embodiments of the present application can be used to execute the foregoing reliability monitoring method. The implementation principle, process, and beneficial effects can be referred to the foregoing embodiments and will not be elaborated here.

[0254] Figure 8 It is a schematic structural diagram of an electronic device provided in an embodiment of the present application. As Figure 8 shown, the electronic device 800 may include: a memory 801 and a processor 802. Optionally, the electronic device may further include a transceiver 803. Among them, the memory 801 and the processor 802 communicate with each other. Exemplarily, the memory 801, the processor 802, and the transceiver 803 may communicate through a communication bus 806. The memory 801 is used to store a computer program, and the processor 802 executes the computer program to implement the method of the foregoing embodiments.

[0255] Optionally, the foregoing processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps in the method embodiments disclosed in combination with the present application may be directly implemented by a hardware processor, or may be implemented by a combination of hardware and software modules in the processor.

[0256] The embodiment of the present application also provides a battery pack, which includes: the reliability detection system mentioned above, and the reliability detection system can be, for example, a battery management system. The method mentioned in the foregoing embodiment can be used to detect the fatigue reliability of the battery pack, and details are not described herein again.

[0257] The embodiment of the present application also provides an electrical equipment, which includes: the battery pack mentioned above. The method mentioned in the foregoing embodiment can be used to detect the fatigue reliability of the battery pack, and details are not described herein again.

[0258] The electrical equipment can be, for example, an automobile. Taking the electrical equipment as an electric vehicle as an example, the above data analysis device can transmit the abnormal load data to the vehicle controller by means of wired data transmission, and the communication protocol of the wired data transmission can be, for example, the Controller Area Network (CAN) bus.

[0259] Among them, the vehicle controller can transmit the load data to the server by means of finite data transmission or wireless signal transmission, and receive the battery pack reliability prompt information fed back after detection by the server. The vehicle controller can, for example, establish a communication connection with the in-vehicle large screen of the electric vehicle, and send the prompt information to the in-vehicle large screen for display according to the fatigue reliability warning level. The in-vehicle terminal of the electric vehicle can display the reliability warning level through the display screen.

[0260] The embodiment of the present application also provides a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, the methods in any of the above method embodiments are implemented.

[0261] The embodiment of the present application also provides a computer program product, including a computer program, and when the computer program is executed by a processor, the methods in any of the above method embodiments are implemented.

[0262] All or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a readable memory. When the program is executed, it executes the steps including the above method embodiments; and the foregoing memory (storage medium) includes: read-only memory (ROM), RAM, flash memory, hard disk, solid-state drive, magnetic tape, floppy disk, optical disc, and any combination thereof.

[0263] Embodiments of the present application are described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processing unit of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processing unit of the computer or other programmable data processing devices generate means for implementing the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0264] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing devices to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means implement the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0265] These computer program instructions can also be loaded onto a computer or other programmable data processing devices, such that a series of operation steps are executed on the computer or other programmable devices to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable devices provide steps for implementing the functions specified in one process Figure 1 one process or multiple processes and / or blocks Figure 1 or means for implementing the functions specified in multiple blocks.

[0266] Obviously, those skilled in the art can make various modifications and variations to the embodiments of the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the embodiments of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application is also intended to include these modifications and variations.

[0267] After considering the specification and practicing the invention disclosed herein, those skilled in the art will readily conceive of other embodiments of the present application. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include known common knowledge or conventional technical means in the technical field not disclosed in the present application. The specification and embodiments are only regarded as exemplary, and the true scope and spirit of the present application are pointed out by the following claims.

[0268] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present application is only limited by the appended claims.

Claims

1. A reliability detection method, characterized in that the method comprises: Get the load data of the battery pack; Based on the load data of the battery pack, fatigue reliability of the battery pack is detected.

2. The method according to claim 1, characterized in that: The detecting the fatigue reliability of the battery pack based on the load data of the battery pack includes: Acquiring stress data of a connection portion of the battery pack based on the load data of the battery pack; The fatigue reliability of the battery pack is detected based on stress data of a connection portion of the battery pack.

3. The method according to claim 2, characterized in that The load data includes: the acceleration load of the battery pack; the step of acquiring stress data of a connection portion of the battery pack based on the load data of the battery pack includes: Based on the acceleration load, the stress data of the connection parts of the battery pack are obtained by utilizing the finite element simulation model of the overall structure of the battery pack.

4. The method according to claim 3, characterized in that The load data also includes: a physical force load of a first connection portion of the battery pack; The acquiring stress data of the connection part of the battery pack based on the load data of the battery pack includes: If the stress data of the first connection part of the battery pack is not obtained based on the acceleration load by using the finite element simulation model of the overall structure of the battery pack, then based on the physical force load of the first connection part, the stress data of the first connection part is obtained by using the finite element simulation model of the local structure of the battery pack.

5. The method according to claim 3, characterized in that: The load data also includes: a strain load of a second connection portion of the battery pack; The acquiring stress data of the connection part of the battery pack based on the load data of the battery pack includes: If the stress data of the second connection part of the battery pack is not obtained based on the acceleration load by using the finite element simulation model of the overall structure of the battery pack, the stress data of the second connection part is obtained based on the strain load of the second connection part and the material elastic parameters of the second connection part.

6. The method according to claim 2, characterized in that The step of detecting the fatigue reliability of the battery pack based on the stress data of the connection parts of the battery pack includes: Determining the cumulative amount of fatigue damage at the connection location based on the stress data at the connection location; The fatigue reliability of the battery pack is detected based on the cumulative amount of fatigue damage of the connection portion.

7. The method according to claim 6, characterized in that The step of determining the cumulative amount of fatigue damage at the connection part based on the stress data at the connection part comprises: Determining a current fatigue damage contribution of the connection part based on the stress data of the connection part; The accumulated amount of fatigue damage of the connection part is determined based on the sum of the current fatigue damage contribution amount of the connection part and the previous accumulated amount of fatigue damage of the connection part.

8. The method according to claim 7, characterized in that The determining, based on the stress data of the connection part, the current fatigue damage contribution of the connection part comprises: Determine the expected life of the connection part based on the stress data of the connection part and the mapping relationship between the stress data and the life of the battery pack; Based on the actual life of the connection part and the currently corresponding expected life, the current fatigue damage contribution of the connection part is determined.

9. The method according to claim 8, characterized in that The determining of the current fatigue damage contribution of the connection part based on the actual life of the connection part and the current corresponding expected life includes: The current fatigue damage contribution of the connection part is determined based on the quotient of the actual life of the connection part and the current corresponding expected life.

10. The method according to claim 6, characterized in that The detecting the fatigue reliability of the battery pack based on the cumulative amount of fatigue damage of the connection part includes: If the cumulative amount of fatigue damage of the connection part is less than a first critical value, it is determined that the battery pack has no fatigue damage; If the cumulative amount of fatigue loss of the connection portion is greater than or equal to a first critical value, it is determined that fatigue damage exists in the battery pack.

11. The method according to claim 10, characterized in that The method further comprises: Determining a fatigue reliability warning level of the battery pack based on a fatigue reliability test result of the battery pack; Based on the fatigue reliability warning level, a warning operation of a corresponding level is performed.

12. The method according to claim 11, characterized in that The determining the fatigue reliability warning level of the battery pack based on the fatigue reliability detection result of the battery pack includes: If the cumulative amount of fatigue damage of the connection part is less than a first critical value, the fatigue reliability warning level of the battery pack is determined to be level one; If the cumulative amount of fatigue loss of the connection part is greater than or equal to the first critical value and less than the second critical value, the fatigue reliability warning level of the battery pack is determined to be level 2; If the accumulated fatigue loss of the connection part is greater than or equal to the second critical value, the fatigue reliability warning level of the battery pack is determined to be level three.

13. The method according to claim 12, characterized in that The performing of a warning operation of a corresponding level based on the fatigue reliability warning level includes: When there is a connection part with a fatigue reliability warning level of level 2, and / or when there is a connection part with a fatigue reliability warning level of level 3, a reminder message is output, wherein the reminder message is used to indicate the connection part with fatigue damage and the degree of fatigue damage; the degree of fatigue damage is positively correlated with the accumulated amount of fatigue loss.

14. The method according to claim 10, characterized in that The method further comprises: If the fatigue reliability test result of the battery pack indicates that the battery pack has not suffered fatigue damage, then based on the actual life of the connection part and the current corresponding expected life, predict the remaining life of the battery pack; Output the predicted remaining life of the battery pack.

15. The method according to claim 14, characterized in that The predicting the remaining life of the battery based on the actual life of the connection part and the current corresponding expected life includes: Based on the actual life of the connection part and the current corresponding expected life, obtaining the initial remaining life of the battery pack corresponding to the connection part; Based on the initial remaining life of the battery pack corresponding to each of the connection locations, the remaining life of the battery pack is obtained.

16. The method according to any one of claims 1 to 15, characterized in that: The method is applied to the server, and the step of obtaining the load data of the battery pack includes: Get the payload data of the reported exception.

17. The method according to claim 16, characterized in that The abnormal load data includes: at least one load data that is greater than or equal to a corresponding threshold.

18. A method for monitoring the reliability of a battery pack, characterized in that: The method comprises: Acquiring load data of the battery pack; Report the load data of the battery pack to the server so that the server can detect the fatigue reliability of the battery pack using the method described in any one of claims 1-17.

19. The method according to claim 18, characterized in that The reporting of the load data of the battery pack to the server includes: In the case where the load data is abnormal, the abnormal load data of the battery pack is reported to the service end.

20. The method according to claim 19, characterized in that The abnormal load data includes: At least one load data is greater than or equal to a corresponding threshold value.

21. The method according to claim 18, characterized in that The method further comprises: If a reminder message is received from the service end based on the fatigue reliability test result of the battery pack, the reminder message is output, wherein the reminder message is used to indicate the connection parts with fatigue damage and the degree of fatigue damage; the degree of fatigue damage is positively correlated with the accumulated amount of fatigue loss.

22. The method according to claim 18, characterized in that The method further comprises: If the service end receives the predicted remaining life of the battery when the fatigue reliability test result of the battery pack indicates that the battery pack has not suffered fatigue damage; Output the predicted remaining life of the battery pack.

23. A reliability detection device, characterized in that the reliability detection device comprises: An acquisition module is used to obtain the load data of the battery pack; A processing module is used to detect the fatigue reliability of the battery pack based on the load data of the battery pack.

24. A reliability monitoring device, characterized in that the reliability detection device comprises: An acquisition module, for acquiring load data of the battery pack; The transceiver module reports the load data of the battery pack to the server, so that the server adopts the method as described in any one of claims 1 to 17 to detect the fatigue reliability of the battery pack.

25. A reliability detection system, characterized in that the reliability detection system comprises: Data analysis device, and,collection device; The data analysis device is in communication connection with the acquisition device; The acquisition device is arranged on the battery pack and is used to obtain the load data of the battery pack; The data analysis device is used to execute the method as described in any one of claims 1-15, and any one of claims 18-22.

26. The system according to claim 25, characterized in that The acquisition device includes: an acceleration acquisition device, which is used to acquire the acceleration load of the battery pack.

27. The system according to claim 26, characterized in that The acceleration acquisition device is arranged at the side beam of the battery pack tray.

28. The system according to claim 25, characterized in that The collection device also includes: a physical force collection device, which is arranged at the first connection part of the battery pack and is used to collect the physical force load of the first connection part of the battery pack.

29. The system according to claim 28, characterized in that The first connection part includes at least one of the following: the location of the bolt, the liquid cooling plate support structure, and the battery core shell support structure.

30. The system according to claim 25, characterized in that The collection device also includes: a strain collection device, which is arranged at the second connection part of the battery pack and is used to collect the strain load of the second connection part of the battery pack.

31. The system according to claim 30, characterized in that The second connection part includes at least one of the following: a tray side beam welding joint, a battery cell shell welding joint, a liquid cooling plate welding joint, and a lifting ear weld.

32. A battery pack, characterized in that: The battery pack includes: a reliability detection system as described in any one of claims 25-31.

33. The battery pack according to claim 32, characterized in that: The reliability detection system is a battery management system.

34. An electrical equipment, characterized in that: The electrical equipment includes: a battery pack as described in claim 32 or 33.

35. An electronic device, characterized in that: The electronic device comprises: a processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 22.

36. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method according to any one of claims 1 to 22.

37. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 22 when being executed by a processor.

Images