Failure detection method and device for battery pack bolt, storage medium and program product

Abstract

The invention discloses a failure detection method and device for a battery pack bolt, a storage medium and a program product, and the method comprises the steps: carrying out the multi-parameter coupling analysis of the axial force and transverse shear component force of a beam unit and a bolt assembly through combining the axial force and transverse shear component force of the beam unit obtained through random vibration simulation; the residual pre-tightening force and the anti-sliding capacity of the bolt assembly are quantitatively evaluated, the failure risk of the bolt assembly is further determined according to the residual pre-tightening force and the anti-sliding capacity of the bolt assembly, the advantages of a frequency domain linear random vibration simulation method are reserved, and the purpose of effectively checking the anti-loosening performance of the bolt can be achieved. The problems that a traditional test is low in efficiency, a simulation model is excessively simplified and failure criteria are incomplete are effectively solved, and the method has the advantages that the detection accuracy is improved, the test cost is reduced, the calculation efficiency is improved, and potential failure points are comprehensively covered.

Description

TECHNICAL FIELD

[0001] The present disclosure generally relates to the field of new energy technology, and particularly relates to a battery pack bolt failure detection method and device, a storage medium and a program product. BACKGROUND

[0002] With the development of new energy vehicles, the mechanical safety and reliability of power batteries as the core components of new energy vehicles are important design indicators for battery system research and development. Generally, random vibration tests are used to verify whether the battery system has vibration fatigue failure. However, in the random vibration test, the loosening of the battery pack bolt often occurs. The loosening of the battery pack bolt can cause sealing failure, connection failure and other problems, which can further lead to the risk of fracture failure. Therefore, how to avoid the loosening of the battery pack bolt during the random vibration process is an important research content for battery manufacturers.

[0003] In the prior art, simulation means is used to predict the bolts that may be loosened in the random vibration test, so as to optimize the bolt specifications. However, the existing simulation for predicting the random vibration test cannot consider the nonlinear factors such as friction force and pre-tightening force attenuation in the bolt connection, so it cannot evaluate the bolt connection failure. Moreover, the calculation is very time-consuming and has problems such as convergence difficulty, which makes it difficult to apply in actual engineering. SUMMARY

[0004] In view of the above defects or deficiencies in the prior art, it is desirable to provide a battery pack bolt failure detection method that can more quickly and accurately detect whether the bolts in the battery pack have a failure risk.

[0005] In a first aspect, a battery pack bolt failure detection method is provided, the method comprising: obtaining a simulation model of a target battery pack, parameters of a bolt assembly in the target battery pack, and parameters of a connecting piece, the connecting piece of the bolt assembly comprising a first connected piece and a second connected piece, the parameters of the connecting piece comprising at least one of the parameters of the first connected piece and / or the parameters of the second connected piece; the simulation model comprising a beam element, inputting the parameters of the bolt assembly into the simulation model for random vibration simulation to obtain an axial force and a transverse shear component force of the beam element, wherein the beam element is used to simulate the tensile or shear behavior of the bolt assembly; determining a residual pre-tightening force of the bolt assembly based on the axial force, the parameters of the bolt assembly and the parameters of the connecting piece, and determining a anti-slip ability coefficient of the bolt assembly based on the transverse shear component force and the parameters of the bolt assembly; determining a failure risk of the bolt assembly based on the residual pre-tightening force and the anti-slip ability coefficient.

[0006] The application provides a battery pack bolt failure detection method. Considering that the current simulation prediction random vibration test cannot consider the friction, pre-tightening force attenuation and other nonlinear factors in the bolt connection, the bolt connection failure cannot be evaluated, and the calculation is very time-consuming, and there are problems such as calculation convergence difficulty. The application provides a battery pack bolt failure detection method. The method combines the axial force and transverse shear force of the beam element obtained by random vibration simulation, analyzes the coupling of the axial force and transverse shear force of the beam element and the multi-parameter of the bolt assembly, quantitatively evaluates the residual pre-tightening force and anti-slippage ability of the bolt assembly, further determines the failure risk of the bolt assembly according to the residual pre-tightening force and anti-slippage ability of the bolt assembly, realizes the advantages of the frequency domain linear random vibration simulation method, and effectively checks the bolt anti-loose performance. The problems of low efficiency, excessive simplification of the simulation model and incomplete failure criterion in the traditional test are effectively solved, and the advantages of improving the detection accuracy, reducing the test cost, improving the calculation efficiency and fully covering the potential failure points are achieved.

[0007] In a second aspect, a battery pack bolt failure detection device is provided, and the device comprises: An acquisition module is configured to acquire a simulation model of a target battery pack, parameters of a bolt assembly in the target battery pack, and parameters of a connecting piece, wherein the connecting piece of the bolt assembly comprises a first connected piece and a second connected piece, and the parameters of the connecting piece comprise at least one of the parameters of the first connected piece and / or the parameters of the second connected piece. The simulation model comprises a beam element, and an input acquisition module is configured to input the parameters of the bolt assembly into the simulation model for random vibration simulation to obtain an axial force and a transverse shear force of the beam element, wherein the beam element is used to simulate the tensile or shear behavior of the bolt assembly. A first determination module is configured to determine a residual pre-tightening force of the bolt assembly based on the axial force, the parameters of the bolt assembly and the parameters of the connecting piece, and determine an anti-slippage ability coefficient of the bolt assembly based on the transverse shear force and the parameters of the bolt assembly. A second determination module is configured to determine a failure risk of the bolt connection assembly based on the residual pre-tightening force and the anti-slippage ability coefficient.

[0008] In a third aspect, a computer readable storage medium is provided, and a computer program is stored on the computer readable storage medium. When the computer program is executed by a processor, the steps of the method of the first aspect are implemented.

[0009] In a fourth aspect, a computer program product is provided, and the computer program product comprises a computer program. When the computer program is executed by a processor, the steps of the method of the first aspect are implemented. BRIEF DESCRIPTION OF DRAWINGS

[0010] Other features, objects, and advantages of the application will become more apparent from the following detailed description when read in connection with the following drawings: Figure 1 An application scenario diagram of a failure detection method for a battery pack bolt provided by the application; Figure 2 An application scenario diagram of a failure detection method for a battery pack bolt provided by the application; Figure 3 A flowchart of a failure detection method for a battery pack bolt provided by the application; Figure 4 A flowchart of a failure detection method for a battery pack bolt provided by the application; Figure 5 A flowchart of a failure detection method for a battery pack bolt provided by the application; Figure 6 A flowchart of a failure detection method for a battery pack bolt provided by the application; Figure 7 A structural diagram of a failure detection device for a battery pack bolt provided by the application. DETAILED DESCRIPTION

[0011] The application will be further described below in conjunction with the drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the related application, and not to limit the application. In addition, it should be noted that only parts related to the application are shown in the drawings for ease of description.

[0012] It should be noted that the embodiments in the application and the features in the embodiments can be combined with each other without conflict. The application will be described in detail below with reference to the drawings and in conjunction with the embodiments.

[0013] In the prior art, power batteries, as the core components of new energy vehicles, directly affect the performance of the whole vehicle in terms of mechanical safety and reliability. The industry generally uses random vibration tests to verify the fatigue resistance of battery systems, but during the test, the phenomenon of battery pack bolt loosening often occurs, leading to sealing failure, connection failure, and even the risk of rupture. Although traditional simulation methods are used to predict bolt loosening, they are limited by linear assumptions and cannot accurately simulate the changes in friction force, pre-tightening force decay, and other nonlinear factors in bolt connection, resulting in a deviation of the prediction results from the actual working conditions. In addition, the existing simulation model has low calculation efficiency and is often difficult to apply to engineering practice due to convergence difficulties, which cannot meet the demand for rapid evaluation of bolt connection reliability.

[0014] To solve the above problems, the inventors found that the core defect of the traditional simulation method lies in the oversimplification of the bolted joint structure. By analyzing the actual stress characteristics of the bolted joint assembly, it is realized that the contact stiffness between the bolt flange and the receiving surface, the coupling effect of the axial load and the transverse shear force have a decisive influence on the pre-tightening force decay. Therefore, a composite simulation model containing rigid elements and beam elements is proposed, which simulates the mechanical response in different directions by separating the axial stiffness and shear stiffness. As shown in Figure 1 The bolted joint assembly in the target battery pack is simulated using the combination of "first rigid element + beam element + second rigid element". In order to better explain the beam element, we define the contact area between the bolt and the first connected part as the first receiving surface, which is coupled to the geometric center by the first rigid element, and the geometric center point is defined as the first main node. The contact area between the nut and the second connected part is defined as the second receiving surface, which is coupled to the geometric center by the second rigid element, and the geometric center point is defined as the second main node. Then the beam element used to connect the first main node and the second main node is used to simulate the bolt shank, i.e. the tensile or shear behavior of the bolt assembly, and its cross-sectional geometry is defined as a circle with a diameter equal to the nominal diameter of the bolt.

[0015] Further considering the statistical characteristics of dynamic load under random vibration conditions, the simulation data is processed using the Rama-Dada criterion to establish a quantitative evaluation index of residual pre-tightening force and anti-slip ability, and a complete bolt connection failure judgment logic is formed.

[0016] Please refer to Figure 2 , Figure 2 An application scenario diagram of a battery pack bolt failure detection method provided by the present application is provided, which includes a terminal device 100 and a service device 200. The terminal device 100 stores data such as bolt parameters of a target battery pack and parameters of a bolted joint assembly in the target battery pack. The service device 200 stores simulation models for different types of battery packs. When it is determined that the target battery pack needs to be detected for failure, the corresponding simulation model is obtained from the memory address of the service device 200 according to the type of the target battery pack, and the data such as the bolt parameters of the target battery pack and the parameters of the bolted joint assembly in the target battery pack are obtained from the terminal device 100. The corresponding data is input into the corresponding simulation model, and the failure detection of the target battery pack is performed according to the result output by the simulation model. The terminal device 100 is, for example, a notebook computer, a desktop computer, a tablet computer, a wearable device, etc. The service device 200 is, for example, a single server or a server cluster.

[0017] Next, combined with Figure 3 The battery pack bolt failure detection method is applied to Figure 2The service device 200 in the battery pack bolt failure detection method provided by the application is taken as an example to illustrate the battery pack bolt failure detection method provided by the application, and the method comprises the following steps: In step S20, the simulation model of the target battery pack, the parameters of the bolt assembly in the target battery pack, and the parameters of the connecting piece are obtained, the connecting piece of the bolt assembly comprises a first connected piece and a second connected piece, and the parameters of the connecting piece comprise at least one of the parameters of the first connected piece and / or the parameters of the second connected piece. It should be noted that before the failure detection of the target battery pack, a corresponding simulation model can be established for each type of battery pack, and when the failure detection of the target battery pack is needed, the simulation model corresponding to the type of the target battery pack can be obtained from the memory address of the server.

[0018] Since the simulation model is used to detect the failure of the bolt assembly in the battery pack, in order to reduce the simulation calculation amount and improve the calculation efficiency, when the simulation model is established, as shown in the figure, Figure 1 The bolt assembly in the battery pack is simulated by the form of "first rigid unit + beam unit + second rigid unit". The first rigid unit is used to simulate the axial stiffness of the contact surface (i.e. the first bearing surface) between the bolt in the bolt assembly and the first connected piece. The second rigid unit is used to simulate the axial stiffness of the contact surface (i.e. the second bearing surface) between the nut in the bolt assembly and the second connected piece. The first connected piece is a connecting piece having a connection relationship with the bolt assembly, specifically a connecting piece having a connection relationship with the bolt in the bolt assembly; the second connected piece is a connecting piece having a connection relationship with the nut in the bolt assembly. The beam unit is used to simulate the bolt shank in the bolt assembly, that is, the tensile or shear behavior of the bolt assembly, and its cross-sectional geometry is defined as a circle with a diameter of the nominal diameter of the bolt.

[0019] After the simulation model is established, the random vibration simulation working condition such as the constraint condition, the modal analysis load step, the frequency response analysis load step, the random vibration load step, and the unit force output mode is set, and then the simulation model can be tested under the set random vibration simulation working condition, and the required data can be obtained during the random vibration test. For example, the output mode of the unit force is in the form of root mean square.

[0020] The parameters of the bolt assembly are used to define the specifications of the bolt assembly, which are different from the bolt assemblies on different battery packs of different models. The parameters of the bolt assembly include, for example, parameters of the bolt, parameters of the screw rod, parameters of the nut, parameters of the abutting surface connected with the bolt assembly, and the like. The parameters of the bolt assembly include, for example, nominal diameter of the bolt, pitch of the bolt, minor diameter of the external thread of the bolt, basic major diameter of the external thread of the bolt, thread angle of the bolt, strength grade of the bolt, tightening torque of the bolt, outer diameter of the first abutting surface, outer diameter of the second abutting surface, inner diameter of the first abutting surface, inner diameter of the second abutting surface, and the like. Optionally, the outer diameter of the first abutting surface is the same as the outer diameter of the second abutting surface, and the inner diameter of the first abutting surface is the same as the inner diameter of the second abutting surface. The parameters of the bolt assembly can be obtained by measurement, for example.

[0021] The parameters of the connecting piece include at least one of the parameters of the first connected piece and / or the parameters of the second connected piece described above. The parameters of the first connected piece include, for example, stiffness parameters, diameter parameters, thickness parameters, and the like of the first connected piece, and the parameters of the second connected piece include, for example, stiffness parameters, diameter parameters, thickness parameters, and the like of the second connected piece. The parameters of the connecting piece can be obtained by measurement, for example.

[0022] In step S30, the simulation model includes a beam element, the parameters of the bolt assembly are input into the simulation model for random vibration simulation, and axial force and transverse shear force of the beam element are obtained, wherein the beam element is used to simulate the tensile or shear behavior of the bolt assembly. According to the simulation model described above, the beam element is used to reflect the combined action of the axial tension and the transverse shear force. Next, the bolt parameters in the bolt assembly of the target battery pack can be directly obtained from, for example, a terminal device, input into the simulation model, and subjected to random vibration simulation test under the set random vibration simulation conditions, and the axial force and the transverse shear force of the beam element are obtained during the random vibration test.

[0023] The present application separates the axial and transverse directions by obtaining the axial force and the transverse shear force of the beam element, respectively, so as to facilitate the evaluation of the failure risk of the bolt from two different directions of the axial and transverse directions.

[0024] In step S40, the residual pre-tightening force of the bolt assembly is determined based on the axial force of the bolt assembly, the parameters of the bolt assembly, and the parameters of the connecting piece, and the anti-slippage coefficient of the bolt assembly is determined based on the transverse shear force and the parameters of the bolt assembly. The axial force and the transverse shear force are obtained by random vibration simulation test of the simulation model described above, and the parameters of the bolt assembly can be obtained by measurement of the bolt assembly, for example. Exemplarily, the parameters of the bolt assembly include, for example, bolt stiffness, nominal diameter of the bolt, equivalent friction diameter of the abutting surface, initial torque of the bolt assembly, initial pre-tightening force of the bolt assembly, and the like.

[0025] The parameters of the connecting member can be obtained by simulation or experimental methods, which are relatively mature methods and will not be described herein. In addition, the parameters of the connecting member can also be obtained by experience, which is not limited.

[0026] The residual preload refers to the actual effective preload of the bolt connection under the action of the vibration load, which can be obtained by the relative stiffness coefficient and the axial force, for example, and is used to determine whether the bolt connection fails due to insufficient preload. The anti-slippage coefficient refers to the safety margin of the bolt connection against transverse slip, which can be obtained by the ratio of the residual friction force to the transverse shear force, for example, and is used to evaluate the shear failure resistance of the bolt.

[0027] In step S50, the failure risk of the bolt assembly is determined based on the residual preload and the anti-slippage coefficient.

[0028] The residual preload can be used to determine whether the bolt connection fails due to insufficient preload. The anti-slippage coefficient can be used to evaluate the safety margin of the bolt connection against transverse slip. The present application can separately evaluate the preload attenuation and the anti-slippage capability by separating the axial and shear processing methods, which can overcome the defects of the traditional method that cannot quantitatively evaluate the multi-factor coupling failure, and can provide more comprehensive evaluation indexes for the reliability of the bolt connection.

[0029] For example, the present application can compare the residual preload with the material yield strength, and combine the anti-slippage coefficient threshold to form a failure determination standard.

[0030] The present application can achieve efficient simulation calculation by simplifying the model, can quickly identify high-risk bolt positions in the simulation model design stage, and can guide the bolt specification selection and preload optimization. The dual criteria of residual preload and anti-slippage coefficient can significantly improve the accuracy of failure prediction and avoid the risk of misjudgment caused by a single criterion. The method can provide reliable technical support for the bolt connection design of the battery pack, reduce the cost of experimental verification, and shorten the product development cycle.

[0031] In an optional embodiment, if the parameters of the bolt assembly include the stiffness parameter of the bolt assembly and the initial preload of the bolt assembly, and the parameters of the connecting member include the stiffness parameter of the connecting member, as shown in Figure 4 , the method for determining the residual preload of the bolt assembly provided by the present application can include the following steps: Figure 4 The optional method embodiment for determining the residual preload of the bolt assembly provided by the present application includes the following steps: In step S401, the axial working load of the bolt assembly is determined based on the Tresca criterion according to the axial force. The axial force of the beam element is obtained through random vibration simulation test of the simulation model. The Rida criterion is an algorithm for identifying and removing outliers in simulation data through statistical methods. Specifically, data points exceeding three times the standard deviation can be removed after calculating the standard deviation of the axial force data, to eliminate the interference of extreme loads in vibration simulation on the calculation of the residual pretension. The axial working load refers to the dynamic axial force actually borne by the bolt in the vibration environment. Specifically, the maximum value or root mean square value of the axial force output by the beam element in random vibration simulation after Rida criterion screening can be taken to represent the maximum stress state of the bolt under vibration conditions.

[0032] The axial working load can be calculated by the following formula: SF1 where F A is the axial working load, and SF1 is the axial force of the beam element.

[0033] In step S402, the relative stiffness coefficient of the bolt assembly and the connecting piece is determined according to the stiffness parameter of the bolt assembly and the stiffness parameter of the connecting piece. The stiffness parameter of the bolt refers to the elastic response characteristic of the bolt under axial load, which reflects the elongation change law of the bolt under the action of pretension. For example, it can be calculated by the elastic modulus and effective bearing area of the bolt material, or obtained by simulation, test, or taking an empirical value. The stiffness parameter of the connecting piece refers to the ability of the connecting piece (first connected piece and / or second connected piece) to resist deformation under the action of axial force, which is used to represent the deformation characteristic when it is stressed. For example, it can be calculated by the material elastic modulus and geometric size of the connecting piece, or obtained by simulation, test, or taking an empirical value, which is not limited in the present application.

[0034] The relative stiffness coefficient refers to the ratio of the stiffness of the connecting piece (first connected piece and / or second connected piece) to the stiffness of the bolt. For example, it can be calculated by the ratio of the compression stiffness of the connecting piece to the tensile stiffness of the bolt, which is used to quantify the deformation coordination relationship between the connecting piece and the bolt when stressed.

[0035] The relative stiffness coefficient can be calculated by the following formula:

[0036] where λ is the relative stiffness coefficient, C m is the stiffness of the connecting piece, and C B is the stiffness of the bolt.

[0037] In step S403, the residual pretension is determined based on the axial working load, the relative stiffness coefficient, and the initial pretension.

[0038] The initial pretightening force of the bolt assembly refers to the axial pretightening load applied by the bolt during assembly by tightening torque, and the value can be obtained by a torque-pretightening force conversion formula or experimental measurement as a reference value for evaluating the residual pretightening force. For example, it can be obtained by, for example, ultrasonic method, pressure sensor acquisition method, etc. It can also be calculated according to the initial torque of the bolt assembly, which is not limited in the present application.

[0039] For example, the initial pretightening force of the bolt assembly can be calculated by the following formula:

[0040] Wherein, The initial pretightening force of the bolt assembly refers to the axial pretightening load applied by the bolt during assembly by tightening torque, and the value can be obtained by a torque-pretightening force conversion formula or experimental measurement as a reference value for evaluating the residual pretightening force. For example, it can be obtained by, for example, ultrasonic method, pressure sensor acquisition method, etc. It can also be calculated according to the initial torque of the bolt assembly, which is not limited in the present application. The nominal diameter of the bolt.

[0041] For example, in random vibration simulation, the relative deformation of the beam element and the bolt assembly under vibration load can be calculated by extracting the axial force data of the beam element, combining the stiffness parameters of the connector and the stiffness parameters of the bolt assembly, and then the attenuation degree of the bolt pretightening force can be deduced. For example, the relative stiffness coefficient is used to quantify the proportional relationship between the stiffness parameters of the connector and the stiffness parameters of the bolt assembly, and the dynamic changes of the initial pretightening force and the axial working load are combined to establish an attenuation model of the residual pretightening force.

[0042] For example, the residual pretightening force considering the effect of vibration load can be obtained by multiplying the axial working load by the relative stiffness coefficient and superimposing the initial pretightening force. The calculation process introduces the stiffness matching relationship and the dynamic load screening mechanism, so that the evaluation result of the residual pretightening force is closer to the actual working condition. The present scheme introduces the relative stiffness coefficient and the Lyapunov criterion, which not only considers the influence of the stiffness characteristics of the connecting structure on the pretightening force distribution, but also eliminates the influence of abnormal fluctuations in the simulation data on the calculation result, so that the prediction accuracy of the residual pretightening force is significantly improved.

[0043] Through the above technical scheme, the present application can accurately quantify the dynamic attenuation process of the bolt pretightening force in the vibration environment, provide a reliable basis for judging whether the bolt is loose and fails due to insufficient pretightening force, and solve the technical defects that the existing simulation method cannot effectively evaluate the nonlinear attenuation of the pretightening force.

[0044] Optionally, the residual pretightening force is determined based on the axial working load, the relative stiffness coefficient and the initial pretightening force, comprising: Based on the axial working load and the relative stiffness coefficient, the released pretightening force of the bolt assembly in the axial direction is determined; The initial pretightening force minus the released pretightening force to obtain the residual pretightening force.

[0045] The relative stiffness coefficient is used to represent the deformation coordination relationship of the connected member (the first connected member or the second connected member) and the bolt under stress. The axial working load is used to reflect the maximum axial stress of the bolt in the actual working condition. The initial pretightening force is used to provide the initial connection strength and anti-slippage capability. The residual pretightening force is used to evaluate whether the bolt connection fails due to insufficient pretightening force.

[0046] For example, the residual pretightening force can be calculated by the following formula: F'0=F0-(1-λ)·F A wherein, F'0 is the residual pretightening force, F0 is the initial pretightening force, λ is the relative stiffness coefficient, F A F is the axial working load.

[0047] Through the above technical solution, the application can quickly and accurately quantify the attenuation degree of the bolt pretightening force in the vibration environment, and solves the technical bottleneck that the traditional simulation method cannot effectively evaluate the dynamic change of the pretightening force. The method provides a direct calculation basis for judging whether the bolt leads to sealing failure or connection loosening due to insufficient pretightening force, and the calculation process does not need complex iteration, which significantly improves the efficiency and reliability of the battery pack bolt failure risk evaluation.

[0048] In an optional embodiment, the parameters of the bolt assembly include the initial pretightening force of the bolt assembly, the specification parameters of the bolt assembly, and the inner and outer diameter sizes of the receiving surface of the bolt assembly. As Figure 5 shown, Figure 5 The method embodiment provided by the application for determining the anti-slippage capability coefficient of the bolt assembly includes the following steps: Step S501, determining the lateral working load of the bolt according to the lateral shear component force based on the Tresca criterion; Wherein, the lateral shear component force of the beam element is obtained by random vibration simulation test of the simulation model. The lateral working load is the lateral dynamic load borne by the bolt during vibration, and is used to represent the extreme load condition in the vibration environment. For example, the maximum lateral load value can be extracted by the three times standard deviation method.

[0049] The Tresca criterion has been described above and will not be repeated here. The lateral working load of the bolt can be calculated by the following formula:

[0050] Wherein, R is the lateral working load, SF2 and SF3 are the lateral shear component forces.

[0051] Step S502, determining the equivalent friction diameter of the receiving surface according to the inner and outer diameter sizes of the receiving surface; wherein the equivalent friction diameter refers to an equivalent acting diameter for calculating the friction force, and the equivalent friction diameter of the receiving surface can be the equivalent friction diameter of the first receiving surface or the equivalent friction diameter of the second receiving surface, and of course both can be considered the same. The equivalent friction diameter of the receiving surface can be calculated according to the outer diameter of the first receiving surface or the second receiving surface, the inner diameter of the first receiving surface or the second receiving surface, according to the following formula:

[0052] wherein, is the outer diameter of the first receiving surface or the second receiving surface; is the inner diameter of the first receiving surface or the second receiving surface.

[0053] Step S503, determining the friction coefficient of the receiving surface according to the specification parameters of the bolt assembly, the initial pretightening force and the equivalent friction diameter of the receiving surface; wherein the specification parameters of the bolt assembly are, for example, the initial pretightening torque, the pitch of the bolt in the bolt assembly, the basic pitch diameter of the external thread in the bolt assembly and the thread angle of the bolt in the bolt assembly. The initial torque of the bolt assembly can be obtained, for example, by a digital display torque wrench. The pitch of the bolt, the basic pitch diameter of the external thread of the bolt, the thread angle of the bolt, the outer diameter of the receiving surface and the inner diameter of the receiving surface can all be obtained by measurement. The basic pitch diameter of the external thread and the thread angle can be combined to calculate the friction coefficient of the threaded pair, which can be used to evaluate the relationship between the pretightening torque and the residual friction.

[0054] Alternatively, the application can be to determine the friction coefficient of the receiving surface according to the initial pretightening torque, the initial pretightening force, the pitch, the basic pitch diameter of the external thread, the thread angle of the bolt and the friction coefficient of the receiving surface.

[0055] Assuming that the friction coefficient of the thread and the friction coefficient of the receiving surface are the same, the friction coefficient of the receiving surface can be calculated according to the following formula:

[0056] wherein T is the initial torque; is the initial pretightening force; P is the pitch of the bolt; is the basic pitch diameter of the external thread in the bolt assembly; is the thread angle of the bolt; is the equivalent friction diameter of the receiving surface.

[0057] Step S504, determining the residual friction of the receiving surface according to the friction coefficient of the receiving surface and the residual pretightening force; Wherein, the residual friction force refers to the friction resistance still existing after the bolt pretightening force decays, which can be derived by an associated formula of initial torque and thread parameters, friction diameter, for example, and is comprehensively calculated by combining thread lead angle, friction coefficient and contact area.

[0058] For example, the residual friction force can be calculated by the following formula

[0059] Wherein, F is the residual friction force, F is the friction coefficient of the receiving surface.

[0060] Step S505, the actual anti-slippage safety margin of the bolt assembly under random vibration simulation is obtained according to the product of the preset safety factor and the residual friction force of the receiving surface; Wherein, the preset safety factor can be obtained by experiment, empirical value or industry standard, for example, 1.3. Then the actual anti-slippage safety margin can be obtained according to the following formula for example: F B =1.3·F μ F is the residual friction force, and 1.3 is the preset safety factor.

[0061] Step S506, the anti-slippage capacity coefficient is determined according to the difference between the lateral working load and the actual anti-slippage safety margin.

[0062] Wherein, the anti-slippage capacity coefficient can be calculated by the following formula: A=R-F B Wherein, A is the anti-slippage capacity coefficient, R is the lateral working load, and F B is the actual anti-slippage safety margin.

[0063] For the calculation of the anti-slippage capacity coefficient, the lateral shear component, the residual friction force generated by the initial torque and the geometric parameters of the contact surface need to be comprehensively considered, for example, the initial torque is converted into the normal pressure of the receiving surface by the equivalent friction diameter, and then the friction characteristics of the thread pair are combined to evaluate the critical condition of the bolt resisting lateral slippage during vibration.

[0064] Compared with the prior art, the existing simulation method usually only considers the linear stiffness characteristics of the bolt, does not introduce the influence of the connected piece stiffness on the pre-tightening force attenuation, and causes a large error in the evaluation of the residual pre-tightening force. At the same time, the prior art lacks quantitative analysis of the geometric parameters of the receiving surface. The present application solves the influence of the nonlinear factors on the evaluation of the bolt connection state by introducing the stiffness coupling analysis and the calculation of the geometric parameters of the receiving surface. Through the above technical solution, the present application can accurately quantify the dynamic attenuation law of the bolt pre-tightening force in the random vibration process, and establish a multi-parameter evaluation model of the anti-slippage capability. The pre-tightening force evaluation deviation caused by ignoring the nonlinear friction effect in the traditional simulation is avoided, and the accuracy of the residual pre-tightening force prediction is improved through the stiffness coupling calculation, thereby providing a reliable basis for the failure risk judgment of the bolt connection.

[0065] In yet another optional embodiment, as shown in Figure 6 , Figure 6 An optional method embodiment for determining the failure risk of a bolt assembly is provided for an exemplary embodiment of the present application, and the method embodiment comprises the following steps: Step S601, determining the axial total tension of the bolt according to the sum of the axial working load and the residual pre-tightening force of the bolt; The axial total tension refers to the total tension generated by the bolt when bearing external load, and is used to reflect the actual stress condition of the bolt in the vibration environment. For example, the sum of the axial working load and the residual pre-tightening force can be used to calculate.

[0066] For example, the axial total tension can be calculated by the following formula:

[0067] Wherein, F t is the axial total tension, is the residual pre-tightening force, and F A is the axial working load.

[0068] Step S602, determining the axial stress of the bolt according to the axial total tension of the bolt and the parameters of the bolt assembly; For example, the parameters of the bolt assembly are the minor diameter of the external thread of the bolt, which refers to the smallest diameter of the bolt thread, and can be obtained by measurement or reference to standard parameters, for example, to accurately calculate the cross-sectional area of the bolt. The axial stress refers to the internal stress generated by the bolt under the action of the axial total tension, and is used to evaluate whether the bolt is plastically deformed or broken. For example, the axial stress can be calculated by dividing the axial total tension by the cross-sectional area corresponding to the minor diameter of the external thread of the bolt.

[0069] For example, the axial stress can be calculated by the following formula:

[0070] wherein, is the axial stress, is the bolt outer thread minor diameter, F t is the total axial tension.

[0071] In step S603, the failure risk of the bolt assembly is determined according to the axial stress of the bolt, the residual pretightening force and the anti-slippage capability coefficient.

[0072] wherein, the failure risk refers to the possibility of loosening or rupture of the bolt assembly in the vibration process, which can be comprehensively judged by whether the residual pretightening force is sufficient, whether the anti-slippage capability coefficient meets the requirements and whether the axial stress exceeds the material yield strength. For example, the present application can determine that the bolt assembly has a failure risk in the case that the residual pretightening force is too low, the anti-slippage capability coefficient is insufficient or the axial stress exceeds the material yield strength. Conversely, the present application can determine that the bolt assembly does not have a failure risk in the case that the residual pretightening force is not lower than a preset threshold, the anti-slippage capability coefficient is higher than a preset threshold and the axial stress does not exceed the material yield strength.

[0073] The present method solves the problem that the prior art cannot accurately evaluate the influence of nonlinear factors by introducing the joint criterion of residual pretightening force and anti-slippage capability coefficient, combined with real-time calculation of the axial stress. At the same time, the method avoids complex nonlinear simulation calculation, directly derives key parameters through a mechanical model, and significantly improves the calculation efficiency and engineering applicability.

[0074] Through the above technical solutions, the present application can effectively identify the potential failure risk of the bolt in the vibration process due to the attenuation of pretightening force, slippage or overload, and solve the technical defects that the traditional simulation method cannot consider the change of friction and the dynamic attenuation of pretightening force. The method improves the accuracy of bolt connection reliability evaluation through multi-dimensional parameter joint determination, and provides a direct basis for optimizing bolt specification and pretightening force design.

[0075] Alternatively, the present application can determine that the bolt assembly has a failure risk when at least one of the following judgment conditions is met, and the judgment conditions include: the residual pretightening force is less than or equal to a preset pretightening force threshold, the anti-slippage capability coefficient is less than or equal to a preset anti-slippage capability threshold, and the axial stress of the bolt is greater than or equal to a preset axial stress threshold.

[0076] The residual pretightening force is used to evaluate whether the bolt is loosened and failed due to insufficient pretightening force. The anti-slippage capability coefficient is used to determine whether there is a risk of slippage. The axial stress is used to evaluate whether the bolt is fractured due to excessive stress. The preset pretightening force threshold and the preset anti-slippage capability threshold can be set according to experiments or experience, for example, 0. The preset axial stress threshold refers to the maximum working stress threshold allowed by the bolt material, which can be determined by dividing the yield strength of the bolt material by a preset safety factor, and is used to define a safe range of the axial stress. The yield strength of the bolt material refers to the critical stress value when the bolt material is plastically deformed, which can be obtained from a material standard according to the strength grade of the bolt, and is used to measure the tensile performance of the bolt. The preset safety factor refers to a safety margin coefficient set for the axial stress of the bolt in engineering applications, and is used to ensure the reliability of the bolt under dynamic load. For example, any value between 1.3 and 1.7 can be taken, and the preset safety factor is taken as 1.5 in this application.

[0077] For example, the preset axial stress threshold is, for example, , wherein, is the preset axial stress threshold; σs is the yield strength of the bolt material, which is determined by the strength grade of the bolt, such as a 8.8 grade bolt, whose yield strength is 640 MPa, and 1.5 is the preset safety factor.

[0078] Specifically, the application can determine that the bolt assembly has a failure risk when the residual pretightening force is less than or equal to 0. The application can also determine that the bolt assembly has a failure risk when the anti-slippage capability coefficient is less than or equal to 0. The application can also determine that the bolt assembly has a failure risk when the axial stress is greater than or equal to .

[0079] The present scheme realizes the simultaneous detection of three failure modes of bolt loosening, slippage and fracture by establishing a joint criterion of residual pretightening force, anti-slippage coefficient and axial stress. For example, the traditional method can only monitor whether the axial stress is excessive, but ignores the sealing failure problem caused by insufficient pretightening force, while the present scheme can early warn such risks through the residual pretightening force criterion.

[0080] Through the above technical solutions, the application can comprehensively identify the potential failure modes of the bolt in a vibration environment, avoiding the missed detection problem caused by a single criterion. For example, when the axial stress is not excessive but the residual pretightening force is insufficient, it can still accurately determine that there is a risk of sealing failure. When the anti-slippage coefficient is low but the pretightening force is sufficient, it can prompt to strengthen the anti-slippage design in time. This multi-dimensional evaluation mechanism significantly improves the accuracy of bolt connection reliability analysis, and provides an effective basis for optimizing bolt selection and connection structure design.

[0081] Optionally, the application can also directly determine that the bolt assembly has a failure risk when it is determined that the residual preload is less than or equal to 0, and does not need to go through the calculation and judgment process of the subsequent anti-slip coefficient and axial stress.

[0082] Similarly, if the application determines that the residual preload is greater than 0, it needs to continue to determine whether the bolt assembly has a failure risk according to the anti-slip coefficient. It can be understood that if the anti-slip coefficient is less than or equal to 0, it is directly determined that the bolt assembly has a failure risk, and does not need to go through the calculation and judgment process of the axial stress. If the anti-slip coefficient is greater than 0, it continues to determine whether the bolt assembly has a failure risk according to the axial stress. Therefore, the application can determine whether the bolt assembly has a failure risk through the three parameters at the same time, or can determine it in turn according to the above description. The application does not limit this, and it can be flexibly set according to the application scenario.

[0083] It should be noted that although the operations of the method of the application are described in a specific order in the drawings, this does not require or imply that the operations must be performed in that specific order, or that all of the shown operations must be performed to achieve the desired result. On the contrary, the steps depicted in the flowchart can change the order of execution.

[0084] Further reference is made to Figure 7 which shows an exemplary structural block diagram of a battery pack bolt failure detection device according to an embodiment of the application, which includes an acquisition module 701, an input simulation module 702, a first determination module 703 and a second determination module 704. Wherein, The acquisition module 701 is configured to acquire a simulation model of a target battery pack, parameters of a bolt assembly in the target battery pack, and parameters of a connecting piece, the connecting piece of the bolt assembly including a first connected piece and a second connected piece, and the parameters of the connecting piece including at least one of the parameters of the first connected piece and / or the parameters of the second connected piece; The input simulation module 702 is configured to input the parameters of the bolt assembly into the simulation model for random vibration simulation to obtain an axial force and a transverse shear component of a beam element, wherein the beam element is used to simulate the tensile or shear behavior of the bolt assembly; The first determination module 703 is configured to determine a residual preload of the bolt assembly based on the axial force, the parameters of the bolt assembly and the parameters of the connecting piece, and determine an anti-slip coefficient of the bolt assembly based on the transverse shear component and the parameters of the bolt assembly; The second determination module 704 is configured to determine a failure risk of the bolt assembly based on the residual preload and the anti-slip coefficient.

[0085] In an optional embodiment, the first determining module 703 is specifically configured to determine the axial working load of the bolt assembly according to the axial force based on the Lyapunov criterion; determine the relative stiffness coefficient of the bolt assembly and the connecting piece according to the stiffness parameter of the bolt assembly and the stiffness parameter of the connecting piece; determine the residual pretightening force based on the axial working load, the relative stiffness coefficient and the initial pretightening force.

[0086] In an optional embodiment, the first determining module 703 is specifically configured to determine the release pretightening force of the bolt assembly in the axial direction based on the product of the axial working load and the relative stiffness coefficient. The residual pretightening force is obtained by subtracting the release pretightening force from the initial pretightening force.

[0087] In an optional embodiment, the first determining module 703 is specifically configured to determine the lateral working load of the bolt according to the lateral shear component force based on the Lyapunov criterion. determine the equivalent friction diameter of the receiving surface according to the inner and outer diameter dimensions of the receiving surface; determine the friction coefficient of the receiving surface according to the specification parameter of the bolt assembly, the initial pretightening force and the equivalent friction diameter of the receiving surface; determine the residual friction force of the receiving surface according to the friction coefficient of the receiving surface and the residual pretightening force; obtain the actual anti-slippage safety margin of the bolt assembly under random vibration simulation according to the product of the preset safety coefficient and the residual friction force of the receiving surface; determine the anti-slippage capability coefficient according to the difference between the lateral working load and the actual anti-slippage safety margin.

[0088] In an optional embodiment, the first determining module 703 is specifically configured to determine the friction coefficient of the receiving surface according to the initial pretightening torque, the initial pretightening force, the pitch, the basic pitch diameter of the external thread, the thread angle of the bolt and the friction coefficient of the receiving surface.

[0089] In an optional embodiment, the second determining module 704 is specifically configured to determine the axial total tension of the bolt according to the sum of the axial working load and the residual pretightening force; determine the axial stress of the bolt according to the axial total tension of the bolt and the parameter of the bolt assembly; determine the failure risk of the bolt assembly according to the axial stress of the bolt, the residual pretightening force and the anti-slippage capability coefficient.

[0090] In an optional embodiment, the second determining module 704 is specifically configured to determine that the bolt assembly has a failure risk if at least one of the following judgment conditions is met, the judgment conditions including that the residual pretightening force is less than or equal to a preset pretightening force threshold, the anti-slippage capability coefficient is less than or equal to a preset anti-slippage capability threshold, and the axial stress of the bolt is greater than or equal to a preset axial stress threshold.

[0091] The modules in the battery pack bolt failure detection described above can be implemented by software, hardware, and combinations thereof, in whole or in part. The modules described above can be embedded in or independent of the processor in the computer device in hardware form, or stored in the memory in the computer device in software form, so as to be called and executed by the processor to perform the operations corresponding to the modules.

[0092] As another aspect, the present application also provides a computer readable storage medium, which can be the computer readable storage medium contained in the device described in the above embodiments, or can exist independently and not be assembled into the device. The computer readable storage medium stores one or more programs, which are executed by one or more processors to perform the battery pack bolt failure detection method described in the present application.

[0093] In one embodiment, a computer program product is provided, which includes a computer program that, when executed by a processor, implements the battery pack bolt failure detection method described above.

[0094] The above description is merely preferred embodiments of the present application and a description of the principles of the technology used. Those skilled in the art should understand that the scope of the application disclosed in the present application is not limited to the technical solutions formed by the specific combinations of the above technical features, and should also cover other technical solutions formed by any combinations of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features can be replaced with the technical features disclosed in the present application (but not limited to) having similar functions to form technical solutions.

Claims

1. A method for detecting failure of a battery pack bolt, characterized by, The failure detection method comprises: obtaining a simulation model of a target battery pack, parameters of a bolt assembly in the target battery pack, and parameters of a connecting piece, the connecting piece of the bolt assembly comprising a first connected piece and a second connected piece, the parameters of the connecting piece comprising at least one of the parameters of the first connected piece and / or the parameters of the second connected piece; the simulation model comprises a beam element, the parameters of the bolt assembly are input into the simulation model for random vibration simulation, the axial force and the transverse shear component force of the beam element are obtained, wherein the beam element is used to simulate the tensile or shear behavior of the bolt assembly; determining the residual pre-tightening force of the bolt assembly based on the axial force, the parameters of the bolt assembly and the parameters of the connecting piece, and determining the anti-slippage capability coefficient of the bolt assembly based on the transverse shear component force and the parameters of the bolt assembly; determining the failure risk of the bolt assembly based on the residual pre-tightening force and the anti-slippage capability coefficient.

2. The failure detection method according to claim 1, characterized by, The parameters of the bolt assembly comprise the stiffness parameters of the bolt assembly and the initial pre-tightening force of the bolt assembly, and the parameters of the connecting piece comprise the stiffness parameters of the connecting piece; the residual pre-tightening force of the bolt assembly is determined based on the axial force, the parameters of the bolt assembly and the parameters of the connecting piece, comprising: determining the axial working load of the bolt assembly according to the axial force based on the Tresca criterion; determining the relative stiffness coefficient of the bolt assembly and the connecting piece according to the stiffness parameters of the bolt assembly and the stiffness parameters of the connecting piece; determining the residual pre-tightening force based on the axial working load, the relative stiffness coefficient and the initial pre-tightening force.

3. The failure detection method according to claim 2, characterized by, The residual pre-tightening force is determined based on the axial working load, the relative stiffness coefficient and the initial pre-tightening force, comprising: determining the released pre-tightening force of the bolt assembly in the axial direction based on the axial working load and the relative stiffness coefficient; the initial pre-tightening force minus the released pre-tightening force, to obtain the residual pre-tightening force.

4. The failure detection method according to claim 1, characterized by, The parameters of the bolt assembly comprise the initial pre-tightening force of the bolt assembly, the specification parameters of the bolt assembly and the inner and outer diameter dimensions of the receiving surface of the bolt assembly; the anti-slippage capability coefficient of the bolt assembly is determined based on the transverse shear component force and the parameters of the bolt assembly, comprising: determining the transverse working load of the bolt according to the transverse shear component force based on the Tresca criterion; determining the equivalent friction diameter of the receiving surface according to the inner and outer diameter dimensions of the receiving surface; determining the friction coefficient of the receiving surface according to the specification parameters of the bolt assembly, the initial pre-tightening force and the equivalent friction diameter of the receiving surface; determining the residual friction force of the receiving surface according to the friction coefficient of the receiving surface and the residual pre-tightening force; obtaining the actual anti-slippage safety margin of the bolt assembly under random vibration simulation according to the product of the preset safety coefficient and the residual friction force of the receiving surface; determining the anti-slippage capability coefficient according to the difference between the transverse working load and the actual anti-slippage safety margin.

5. The failure detection method according to claim 4, characterized by, The specification parameters of the bolt assembly include an initial pre-tightening torque, a pitch of a bolt in the bolt assembly, a basic major diameter of an external thread in the bolt assembly, and a thread angle of the bolt in the bolt assembly; and the friction coefficient of the bearing surface is determined according to the specification parameters of the bolt assembly, the initial pre-tightening force, and the equivalent friction diameter of the bearing surface, and includes: The friction coefficient of the bearing surface is determined according to the initial pre-tightening torque, the initial pre-tightening force, the pitch, the basic major diameter of the external thread, the thread angle of the bolt, and the friction coefficient of the bearing surface.

6. The failure detection method according to claim 2, characterized by, The failure risk of the bolt assembly is determined based on the residual pre-tightening force and the anti-slippage capability coefficient, and includes: The axial total tension of the bolt is determined according to the sum of the axial working load and the residual pre-tightening force; The axial stress of the bolt is determined according to the axial total tension of the bolt and the parameters of the bolt assembly; The failure risk of the bolt assembly is determined according to the axial stress of the bolt, the residual pre-tightening force, and the anti-slippage capability coefficient.

7. The failure detection method according to claim 6, characterized by, The failure risk of the bolt assembly is determined according to the axial stress of the bolt, the residual pre-tightening force, and the anti-slippage capability coefficient, and includes: If at least one of the following judgment conditions is met, it is determined that the bolt assembly has a failure risk, and the judgment conditions include that the residual pre-tightening force is less than or equal to a preset pre-tightening force threshold, the anti-slippage capability coefficient is less than or equal to a preset anti-slippage capability threshold, and the axial stress of the bolt is greater than or equal to a preset axial stress threshold.

8. A battery pack bolt failure detection apparatus, characterized by, The device includes: An acquisition module is configured to acquire a simulation model of a target battery pack, parameters of a bolt assembly in the target battery pack, and parameters of a connecting piece, the connecting piece of the bolt assembly including a first connected piece and a second connected piece, and the parameters of the connecting piece including at least one of the parameters of the first connected piece and / or the parameters of the second connected piece; The simulation model includes a beam element, an input simulation module is configured to input the parameters of the bolt assembly into the simulation model for random vibration simulation to obtain an axial force and a transverse shear component force of the beam element, wherein the beam element is used to simulate a tensile or shear behavior of the bolt assembly; A first determination module is configured to determine a residual pre-tightening force of the bolt assembly based on the axial force, the parameters of the bolt assembly, and the parameters of the connecting piece, and determine an anti-slippage capability coefficient of the bolt assembly based on the transverse shear component force and the parameters of the bolt assembly; A second determination module is configured to determine a failure risk of the bolt assembly based on the residual pre-tightening force and the anti-slippage capability coefficient.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 7.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 7.

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