Methods, devices, and systems for determining torsional operating conditions

Abstract

This application provides a method, apparatus, and system for determining torsional conditions. The method acquires first and second strain data during the driving process under the test condition. Then, based on the first strain data and target calibration data, the actual rotation angle data of the test object is determined. Finally, based on the correlation between the actual rotation angle data and the second strain data, it is determined whether the test condition is a torsional condition. This allows the derivation of the actual rotation angle data corresponding to the test condition from the pre-calibrated target calibration data and the first strain data corresponding to the calibration device during driving, thus solving the problem of difficulty in obtaining torsional condition data during actual driving. By using the correlation between the actual rotation angle data and the second strain data, it is possible to objectively assess whether the strain of the test object is mainly caused by torsion, thereby determining whether the test condition is a torsional condition and solving the problem of difficulty in accurately defining torsional conditions.

Description

Technical Field

[0001] This application relates to the field of battery technology, and in particular to a method, apparatus and system for determining torsional operating conditions. Background Technology

[0002] With the continuous iteration and upgrading of battery technology, its application areas have been further expanded. Especially in the field of new energy vehicles, as the core power source component of the vehicle, the performance stability and operational safety of the power battery affect the driving safety level of the entire vehicle, and is also one of the key elements supporting the high-quality development of the new energy vehicle industry.

[0003] During the operation of new energy vehicles, the battery pack is prone to torsional deformation due to factors such as road bumps, turning and lane changes, extreme driving postures, and the structural design characteristics of the vehicle. When the torsional deformation reaches a certain level, it may cause safety hazards such as structural strength failure of the battery pack and airtightness damage, thereby threatening the operational safety of the entire vehicle.

[0004] However, there is a practical problem that it is difficult to obtain torsional operating data during actual vehicle operation. This makes it impossible to accurately define the torsional operating conditions of the battery pack, which in turn makes it impossible to conduct a quantitative assessment of the structural reliability of the battery pack under torsional conditions. As a result, it is difficult to formulate targeted optimization solutions, which restricts the further improvement of the overall performance of the battery pack.

[0005] The above statements are for the purpose of providing background information in relation to this application only and do not necessarily constitute prior art. Summary of the Invention

[0006] In view of the above problems, embodiments of this application provide a method, apparatus and system for determining torsional working conditions.

[0007] In a first aspect, embodiments of this application provide a method for determining a torsional condition. The method includes: acquiring first strain data and second strain data, wherein the first strain data is the detection value of a first strain gauge of a calibration device fixedly connected to the object under test during the driving process under the test condition, and the second strain data is the detection value of a second strain gauge at a preset position of the object under test during the driving process under the test condition; acquiring target calibration data corresponding to the object under test, wherein the target calibration data includes a mapping relationship between calibration angle data and calibration strain data; determining the actual angle data of the object under test based on the first strain data and the target calibration data; and determining whether the test condition is a torsional condition based on the correlation between the actual angle data and the second strain data.

[0008] In the above embodiments, first strain data and second strain data of the test object during its driving process under the test condition can be obtained. Then, based on the first strain data and target calibration data, the actual turning angle data of the test object is determined. Finally, based on the correlation between the actual turning angle data and the second strain data, it is determined whether the test condition is a torsional condition. According to the solution provided in this application, when determining whether the test condition is a torsional condition, the actual turning angle data corresponding to the test condition can be derived based on the pre-calibrated target calibration data and the first strain data corresponding to the calibration device during driving, thereby solving the problem of difficulty in obtaining torsional condition data during actual driving. Through the correlation between the actual turning angle data and the second strain data, it is possible to objectively assess whether the strain of the test object is mainly caused by torsion, thereby determining whether the test condition is a torsional condition and solving the problem of difficulty in accurately defining torsional conditions.

[0009] In some optional embodiments, the target calibration data is a mapping relationship between calibration angle data and calibration strain data obtained in advance by applying different rotational loads to the calibration device, wherein the calibration angle data is the detection value of the rotation angle sensor of the calibration device, and the calibration strain data is the detection value of the first strain gauge.

[0010] In the above embodiments, unlike the whole vehicle testing phase, which is limited by factors such as installation space, complex driving conditions (such as vibration and bumps), and dense component layout, it is difficult to install angle sensors to detect angle data. In the calibration bench testing phase, the environment is controllable and space is ample, allowing for convenient installation of angle sensors. Therefore, relying on the precise detection capabilities of the angle sensors and the first strain gauge in the calibration bench testing, high-quality target calibration data can be pre-constructed, providing a reliable foundation for subsequent derivation of actual angle data.

[0011] In some optional embodiments, obtaining target calibration data corresponding to the object under test includes: obtaining target calibration data corresponding to the object under test from multiple sets of calibration data, wherein the multiple sets of calibration data include calibration data corresponding to different objects under test.

[0012] In the above embodiments, matching calibration data that is suitable for different test objects can solve the problem of large errors in actual rotation angle data caused by mismatch between calibration data and test objects, and provide a reliable guarantee for the accurate back-calculation of subsequent actual rotation angle data and the accurate determination of torsional working conditions.

[0013] In some optional embodiments, obtaining target calibration data corresponding to the object under test from multiple sets of calibration data includes: obtaining the actual size of the object under test; obtaining target calibration data corresponding to the actual size of the object under test from multiple sets of calibration data, wherein the multiple sets of calibration data include calibration data corresponding to objects under test of different sizes respectively.

[0014] In the above embodiments, considering that the distribution of the torsion center and stress concentration area of ​​test objects of different sizes under torsional loads in a vehicle is closely related to their own size, selecting corresponding target calibration data for test objects of different sizes can enable the calculation of actual rotation angle data, which can more realistically and accurately reflect the torsional characteristics of the test object under the test conditions.

[0015] In some optional embodiments, multiple sets of calibration data are mapping relationships between calibration angle data and calibration strain data obtained in advance by applying different rotational loads to calibration devices of different sizes. The calibration angle data is the detection value of the rotation angle sensor of the calibration device, and the calibration strain data is the detection value of the first strain gauge.

[0016] In some optional embodiments, the preset location is located in the stress concentration area of ​​the object under test.

[0017] In the above embodiments, under torsional load, the stress in the stress concentration region is higher than that in the non-stress concentration region. The effective signal in the non-stress concentration region is easily drowned out by noise, making it difficult to extract valuable features. Therefore, the strain signal acquired in the stress concentration region has an effective signal amplitude much larger than the noise amplitude, allowing for clear identification of signal variation patterns without complex filtering algorithms.

[0018] In some optional embodiments, determining whether the test condition is a torsional condition based on the correlation between the actual rotation angle data and the second strain data includes: determining the correlation coefficient between the actual rotation angle data and the second strain data in the target frequency range using the actual rotation angle data as the independent variable and the second strain data as the dependent variable; and determining whether the test condition is a torsional condition based on the correlation coefficient and the correlation coefficient threshold.

[0019] In the above embodiments, by establishing a causal relationship between the torsional angle and the strain change, a correlation coefficient is calculated. This correlation coefficient can characterize the correlation between the actual angle data and the second strain data, thereby enabling an objective and quantitative assessment of whether the test condition is a torsional condition. Furthermore, by limiting the correlation analysis to a target frequency range, the frequency band corresponding to the torsional effect can be precisely focused, effectively filtering signal noise caused by non-torsional interference and avoiding misjudgments caused by interference signals.

[0020] In some optional embodiments, using actual rotation angle data as the independent variable and second strain data as the dependent variable, the correlation coefficient between the actual rotation angle data and the second strain data in the target frequency range is determined, including: converting the actual rotation angle data into first frequency domain data; converting the second strain data into second frequency domain data; determining the first power spectrum corresponding to the first frequency domain data; determining the second power spectrum corresponding to the second frequency domain data; determining the complex conjugate cross power spectrum of the first frequency domain data and the second frequency domain data; and determining the correlation coefficient between the first frequency domain data and the second frequency domain data in the target frequency range based on the first power spectrum, the second power spectrum, and the cross power spectrum.

[0021] In some optional embodiments, the method further includes: if the test condition is determined to be a torsion condition, determining the actual rotation angle data as the input data for the torsion condition bench test.

[0022] In the above embodiments, the torsional condition is simulated based on the actual rotation angle data corresponding to the test condition, and the performance of the test object under the simulated torsional condition is tested. Based on the performance test results, targeted structural optimization, safety protection strategies and other solutions can be formulated to further improve the performance of the test object.

[0023] In some optional embodiments, the method further includes: when the test condition is determined to be a torsional condition, converting the actual rotation angle data into displacement data; and determining the displacement data as the input data for the torsional condition bench test.

[0024] In the above embodiments, by converting actual rotation angle data into displacement data, the bench loading mode can be switched to linear displacement control mode during torsion bench testing. By controlling the movement distance of the loading end of the bench, the required angular torsional deformation of the test object can be equivalently reproduced. In this way, torsion bench testing can directly use a conventional loading device with linear displacement loading function, without the need for dedicated angle control equipment, thereby effectively reducing the hardware configuration requirements for torsion bench testing.

[0025] Secondly, embodiments of this application provide a device for determining a torsional working condition. The device includes: a first acquisition component for acquiring first strain data and second strain data, wherein the first strain data is the detection value of a first strain gauge of a calibration device fixedly connected to the object under test during travel under the working condition, and the second strain data is the detection value of a second strain gauge at a preset position on the object under test during travel under the working condition; a second acquisition component for acquiring target calibration data corresponding to the object under test, wherein the target calibration data includes a mapping relationship between calibration angle data and calibration strain data; a first determination component for determining the actual angle data of the object under test based on the first strain data and the target calibration data; and a second determination component for determining whether the working condition under test is a torsional working condition based on the correlation between the actual angle data and the second strain data.

[0026] Thirdly, embodiments of this application provide a battery management system, including: a sampling unit, configured to acquire first strain data and second strain data, wherein the first strain data is the detection value of a first strain gauge of a calibration device fixedly connected to the object under test during driving under the test condition, and the second strain data is the detection value of a second strain gauge at a preset position of the object under test during driving under the test condition; a processing unit, configured to acquire target calibration data corresponding to the object under test, wherein the target calibration data includes a mapping relationship between calibration angle data and calibration strain data; configured to determine the actual angle data of the object under test based on the first strain data and the target calibration data; and configured to determine whether the test condition is a torsional condition based on the correlation between the actual angle data and the second strain data.

[0027] Fourthly, embodiments of this application provide a battery system, including the battery management system of the third aspect.

[0028] Fifthly, embodiments of this application provide an electrical device, including the battery system of the fourth aspect.

[0029] In a sixth aspect, embodiments of this application provide a torsional condition determination system, the system including a controller for performing the method of the first aspect.

[0030] In a seventh aspect, embodiments of this application provide an electronic device including a processor and a memory, the processor being configured to execute a computer program stored in the memory to cause the electronic device to perform the method of the first aspect.

[0031] Eighthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method of the first aspect.

[0032] In the technical solution provided in this application embodiment, first strain data and second strain data of the test object during its driving process under the test condition can be obtained. Then, based on the first strain data and target calibration data, the actual turning angle data of the test object is determined. Finally, based on the correlation between the actual turning angle data and the second strain data, it is determined whether the test condition is a torsional condition. According to the solution provided in this application embodiment, when determining whether the test condition is a torsional condition, the actual turning angle data corresponding to the test condition can be derived based on the pre-calibrated target calibration data and the first strain data corresponding to the calibration device during driving, thereby solving the problem of difficulty in obtaining torsional condition data during actual driving. Through the correlation between the actual turning angle data and the second strain data, it is possible to objectively assess whether the strain of the test object is mainly caused by torsion, thereby determining whether the test condition is a torsional condition and solving the problem of difficulty in accurately defining torsional conditions. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 This is a schematic diagram of a multi-stage test architecture for a torsion test system according to one or more embodiments;

[0035] Figure 2 A schematic diagram of the system architecture for determining torsional conditions according to one or more embodiments;

[0036] Figure 3 A schematic diagram of the architecture for the calibration bench testing phase according to one or more embodiments;

[0037] Figure 4 This is a flowchart illustrating a method for determining a torsional working condition according to one or more embodiments;

[0038] Figure 5 Example diagram of target calibration data according to one or more embodiments;

[0039] Figure 6 This is an example diagram showing the conversion of actual rotation angle data into displacement data according to one or more embodiments;

[0040] Figure 7 This is a flowchart illustrating a method for determining a torsional working condition according to one or more embodiments;

[0041] Figure 8This is a structural block diagram of a device for determining torsional conditions according to one or more embodiments. Detailed Implementation

[0042] The embodiments of the technical solution of this application are described below with reference to the accompanying drawings. These embodiments are only used to more clearly illustrate the technical solution of this application and are therefore merely examples, and should not be used to limit the scope of protection of this application.

[0043] It should be noted that the term "embodiment" as used in this application means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. Those skilled in the art will explicitly and implicitly understand that the embodiments described in this application can be combined with other embodiments.

[0044] Unless otherwise defined, the technical and scientific terms used in the embodiments of this application have the same meaning as understood by one of ordinary skill in the art to which this application belongs. The terminology used in the embodiments of this application is for the purpose of describing the embodiments only and is not intended to limit the application.

[0045] In the description of the embodiments in this application, the term "exemplary" means "serving as an example, embodiment, or illustration." Any embodiment illustrated as "exemplary" is not necessarily to be construed as superior to or better than other embodiments. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless specifically indicated otherwise.

[0046] The terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion. The terms “first,” “second,” “third,” etc., are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, particular order, or primary or secondary relationship of the indicated technical features. The term “multiple” means two or more (including two), unless otherwise expressly and specifically defined.

[0047] The term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. Additionally, the character " / " in this text generally indicates that the preceding and following related objects are in an "or" relationship.

[0048] Unless otherwise explicitly specified and limited, the terms "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can be a mechanical connection or an electrical connection; they can be a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0049] Furthermore, the terms "upper," "lower," "inner," "outer," "front," "back," "left," "right," "top," and "bottom," etc., indicate the orientation or positional relationship based on the working state of the embodiments of this application. They are only used to facilitate the description of the embodiments of this application and to simplify the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0050] In the description of the embodiments of this application, unless otherwise expressly specified and limited, "above" or "below" the second feature can mean that the first feature and the second feature are in direct contact, or that the first feature and the second feature are in indirect contact through an intermediate medium. Furthermore, "above," "over," and "on top" of the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0051] In the description of the embodiments of this application, "parallel" includes not only the case of absolute parallelism, but also the case of approximate parallelism as commonly understood in engineering; at the same time, "perpendicular" also includes not only the case of absolute perpendicularity, but also the case of approximate perpendicularity as commonly understood in engineering.

[0052] In the description of the embodiments of this application, the same reference numerals denote the same components, and for the sake of brevity, detailed descriptions of the same components are omitted in different embodiments. It should be understood that the thickness, length, and other dimensions of various components in the embodiments of this application shown in the drawings, as well as the overall thickness, length, and other dimensions of the integrated device, are merely illustrative and should not constitute any limitation on this application.

[0053] To facilitate understanding of the technical solutions of this application, the application scenarios of the technical solutions provided in the embodiments of this application will be described by way of example below.

[0054] With the continuous iteration and upgrading of battery technology, its application areas have been further expanded. Especially in the field of new energy vehicles, as the core power source component of the vehicle, the performance stability and operational safety of the power battery affect the driving safety level of the entire vehicle, and is also one of the key elements supporting the high-quality development of the new energy vehicle industry.

[0055] During the operation of new energy vehicles, the battery pack is prone to torsional deformation due to factors such as road bumps, turning and lane changes, extreme driving postures, and the structural design characteristics of the vehicle. When the torsional deformation reaches a certain level, it may cause safety hazards such as structural strength failure of the battery pack and airtightness damage, thereby threatening the operational safety of the entire vehicle.

[0056] However, there is a practical problem that it is difficult to obtain torsional operating data during actual vehicle operation. This makes it impossible to accurately define the torsional operating conditions of the battery pack, which in turn makes it impossible to conduct a quantitative assessment of the structural reliability of the battery pack under torsional conditions. As a result, it is difficult to formulate targeted optimization solutions, which restricts the further improvement of the overall performance of the battery pack.

[0057] Based on this, to address the difficulty in accurately defining torsional conditions during actual driving, this application provides a method for determining torsional conditions. This method involves acquiring first strain data and second strain data. The first strain data is the detection value of the first strain gauge of a calibration device fixedly connected to the object under test during driving under the test condition. The second strain data is the detection value of the second strain gauge at a preset position on the object under test during driving under the test condition. Target calibration data corresponding to the object under test is also acquired, including a mapping relationship between calibration angle data and calibration strain data. Then, based on the first strain data and the target calibration data, the actual angle data of the object under test is determined. Based on the correlation between the actual angle data and the second strain data, it is determined whether the test condition is a torsional condition. According to the solution provided in this application, when determining whether the test condition is a torsional condition, the actual angle data corresponding to the test condition can be derived based on the pre-calibrated target calibration data and the first strain data corresponding to the calibration device during driving, thereby solving the problem of difficulty in obtaining torsional condition data during actual driving. By comparing the actual rotation angle data with the second strain data, we can objectively assess whether the strain of the object under test is mainly caused by torsion, thereby determining whether the working condition under test is a torsion condition and solving the problem of the difficulty in accurately defining torsion conditions.

[0058] It should be understood that the torsional condition determination method provided in the embodiments of this application can be applied to any application scenario in the vehicle field that requires the determination of torsional conditions. For example, it can be applied to the torsional condition determination scenario of a battery pack, as well as to the torsional condition determination scenarios of other vehicle components, such as chassis frames, fuel tank assemblies, suspension control arms, and motor and electronic control integrated housings. Other scenarios will not be listed here.

[0059] The system architecture of the embodiments of this application will be described by way of example below.

[0060] See Figure 1 , Figure 1 This is a schematic diagram of a multi-stage test architecture for a torsion test system according to one or more embodiments.

[0061] like Figure 1 As shown, the torsion test may include a calibration bench test phase, a vehicle test phase, and a torsion condition bench test phase.

[0062] The calibration bench testing phase refers to the testing phase conducted on a pre-built calibration bench, detached from the actual operating environment of the vehicle. For example, in the calibration bench testing phase, different rotational loads are applied to a calibration device equipped with an angle sensor to obtain the mapping relationship between calibration angle data and calibration strain data. This mapping relationship can then be used as the target calibration data.

[0063] The vehicle testing phase refers to the stage where the test object is assembled onto a complete vehicle and tested in a real road environment. For example, during the vehicle testing phase, the vehicle can be driven under conditions such as tortuous road surfaces, bumpy road surfaces, and extreme cornering. Torsional data during driving is detected using calibration devices and a second strain gauge mounted on the vehicle. Examples include first strain data and second strain data.

[0064] Subsequently, the target calibration data corresponding to the test object obtained during the calibration bench test phase, as well as the first strain data and second strain data obtained during the whole vehicle test phase, can be used to determine the torsional condition and obtain the torsional condition data under that torsional condition, such as the actual rotation angle data.

[0065] The torsion test bench phase refers to simulating torsion conditions on a test bench, away from the actual operating environment of the vehicle, to test the performance of the test object under these simulated torsion conditions. For example, in the torsion test bench phase, torsion conditions are simulated based on torsion data obtained from the vehicle testing phase, a torsion test is performed on the test object, and the performance of the test object is then evaluated after the torsion test.

[0066] Through the above design, the torsional condition used in the torsional bench test is a targeted simulation constructed based on real torsional condition data obtained during the vehicle testing phase. This simulated torsional condition closely resembles the actual torsional characteristics of a vehicle during real-world driving. Bench tests conducted under this condition accurately reproduce the performance response of the test vehicle under actual torsional conditions, providing R&D personnel with a reliable basis for performance evaluation. R&D personnel can then use this information to implement targeted optimization of the test vehicle's weak points, thereby significantly improving the overall performance of the test vehicle under torsional conditions.

[0067] This application provides a torsion condition determination system for the above-mentioned vehicle testing phase. The architecture of the torsion condition determination system in this application is described below as an example.

[0068] See Figure 2 , Figure 2 This is a schematic diagram of the architecture of a torsional condition determination system according to one or more embodiments. The torsional condition determination method provided in this application embodiment can be applied to this torsional condition determination system.

[0069] like Figure 2 As shown, the torsional condition determination system may include: a calibration device, a first strain gauge located on the calibration device, a second strain gauge located on the object under test, and a controller (not shown in the figure). It should be understood that the torsional condition determination system may also include more or fewer devices than shown in the figure, and this application does not impose any limitations on this.

[0070] The calibration device can be used in the vehicle testing phase or in the calibration bench testing phase.

[0071] For example, such as Figure 2 As shown, the calibration device used in the vehicle testing phase may include a rotating shaft and a first strain gauge fixed on the rotating shaft. Thus, during vehicle operation, the first strain gauge can be used to collect first strain data.

[0072] For example, such as Figure 3 As shown, the calibration device used in the calibration bench testing phase can include a rotating shaft, a first strain gauge fixed on the rotating shaft, and an angle sensor. In other words, compared to the whole vehicle testing phase, the calibration device used in the calibration bench testing phase adds an angle sensor. This allows for the application of different rotational loads to the calibration device, with angle data collected by the angle sensor and strain data collected by the first strain gauge. Subsequently, based on the angle and strain data collected at the same time, a mapping relationship between the angle and strain data can be established, thus obtaining the target calibration data corresponding to the object under test.

[0073] It should be noted that, for the same test object, the calibration equipment used in the whole vehicle testing phase is the same as that used in the calibration bench testing phase, except that it does not include the angle sensor. For example, the dimensions of the rotating shaft and the position of the first strain gauge on the rotating shaft are the same.

[0074] In some optional embodiments, during the calibration bench testing phase, different calibration devices can be configured for different test objects to obtain different calibration data. Furthermore, during the vehicle testing phase, the same calibration devices as those used in the calibration bench testing phase can be employed for different test objects.

[0075] For example, a calibration device with a corresponding sized rotating shaft can be selected for test objects of different sizes. Taking a battery pack as an example, see [link to relevant documentation]. Figure 2 The total length of the calibration device's shaft is the same as the length L of the battery pack. For battery packs of different lengths, a calibration device with a shaft of corresponding length can be selected.

[0076] In the above embodiments, when test objects of different sizes are subjected to torsional loads in a vehicle, the distribution of their torsional center and stress concentration areas is size-dependent. Configuring calibration devices of corresponding specifications for different test objects allows for a high degree of matching between the calibration device and the torsional stiffness distribution and deformation transmission path of the test object. When both undergo torsional deformation simultaneously, the strain response of the calibration device can more accurately reproduce the deformation characteristics of the test object.

[0077] Optionally, to better adapt the calibration device to test objects of different sizes, such as Figure 3 As shown, the rotating shaft may include a first connecting shaft and a second connecting shaft, which are connected by a coupling. A first strain gauge is mounted on the first connecting shaft. This allows for the replacement of different lengths (…). Figure 3 The second connecting axis of the X-axis is matched with test objects of different sizes.

[0078] In this way, by replacing the second connecting shaft, the calibration device of the corresponding specification can be flexibly configured for different sizes of test objects without the need for large-scale modification of the basic structure of the calibration device. This can greatly improve the compatibility and reusability of the calibration device and adapt to the R&D needs of multi-size iteration of new energy vehicle battery packs.

[0079] Correspondingly, during the bench testing phase, calibration data for each size of test object can be collected using the corresponding calibration device.

[0080] like Figure 2As shown, during the vehicle testing phase, the test object is mounted on the vehicle, and the calibration device is fixedly connected to the test object on the vehicle. A second strain gauge is installed at a preset position on the test object. The controller can communicate with the first and second strain gauges on the calibration device to obtain their detection values.

[0081] A strain gauge is a sensing element used to measure the minute deformation of a component caused by torsion, tension, compression, etc. The first strain gauge can be used to detect the strain data generated by the calibration device, and the second strain gauge can be used to detect the strain data generated by the object under test.

[0082] In some alternative embodiments, the first and second strain gauges can be adhesive strain gauges, embedded strain gauges, clamp-on strain gauges, etc. Adhesive strain gauges can be sheet-like strain gauges, fixed to the surface of the test piece (e.g., the object under test or a calibration device) by adhesive bonding. Embedded strain gauges can be pre-embedded inside the test piece. Clamp-on strain gauges can be fixed to the test piece using a special clamp.

[0083] In the above embodiments, the first strain gauge and the second strain gauge are attached to the surface of the tested part, embedded in the interior, or fixed by a clamp, and will not interfere with the arrangement and operation of other parts of the vehicle.

[0084] The function or role of each device in the system determined by the torsional condition can be found in the following embodiments, and will not be described in detail here.

[0085] The method for determining torsional conditions provided in the embodiments of this application will be described below by way of example.

[0086] See Figure 4 , Figure 4 This is a flowchart illustrating a method for determining a torsional operating condition according to one or more embodiments. This method can be applied to a controller or other devices with processor capabilities, and this application does not limit its application. The following description uses a controller as an example to illustrate embodiments of this application. Figure 4 As shown, the method may include the following steps:

[0087] Step S101: Obtain the first strain data and the second strain data.

[0088] The first strain data is the detection value of the first strain gauge of the calibration device fixedly connected to the object under test during the driving process under the test condition, and the second strain data is the detection value of the second strain gauge at the preset position of the object under test during the driving process under the test condition.

[0089] The object under test is the object whose performance needs to be tested under torsional conditions. For example, the object under test can be a battery pack, chassis frame, fuel tank assembly, suspension control arm, motor and electronic control integrated housing, etc.

[0090] The test condition can be any of a variety of test conditions. For example, the test condition may include vibrating pavement, tortuous pavement, Belgian pavement, etc.

[0091] See Figure 2 During the vehicle testing phase, the test object is mounted on the vehicle, and the test object on the vehicle is fixedly connected to a calibration device equipped with a first strain gauge. A second strain gauge is installed at a preset position on the test object. During the vehicle's operation under the test conditions, the first strain gauge on the vehicle can collect first strain data reflecting the deformation of the calibration device, and the second strain gauge on the vehicle can collect second strain data reflecting the actual deformation of the test object.

[0092] For example, the first strain data may include strain data at multiple moments during the driving process under the test condition. Similarly, the second strain data may include strain data at the aforementioned multiple moments during the driving process under the test condition.

[0093] Optionally, the controller can actively send data requests to the first strain gauge and the second strain gauge and obtain the corresponding strain data.

[0094] Optionally, the first and second strain gauges can actively push the acquired strain data to the controller.

[0095] Step S102: Obtain the target calibration data corresponding to the object to be tested.

[0096] Among them, the target calibration data is the calibration data that matches the object to be tested. The target calibration data includes the mapping relationship between the calibration rotation data and the calibration strain data corresponding to the object to be tested.

[0097] For example, the target calibration data can be a calibration curve formed by fitting calibration angle data and calibration strain data obtained through calibration bench testing.

[0098] For example, such as Figure 5 As shown, the horizontal axis of the calibration curve represents the calibration angle data of the test object, and the vertical axis represents the calibration strain data of the test object. This calibration curve demonstrates the mapping relationship between the calibration strain data and the calibration angle data of the test object.

[0099] As another example, the target calibration data can be in tabular form, providing calibration strain data corresponding to different calibration angle data, which facilitates quick querying and matching.

[0100] Step S103: Based on the first strain data and the target calibration data, determine the actual rotation angle data of the object to be measured.

[0101] Since the first strain data can reflect the deformation state of the calibration device under the test condition, and the target calibration data has clearly defined the mapping relationship between the calibration angle and the calibration strain corresponding to the calibration device, the first strain data can be substituted into this mapping relationship to solve in reverse and obtain the calibration angle data that matches the first strain data.

[0102] The calibrated rotation angle data obtained by this solution can characterize the actual rotation angle state under the test condition. Therefore, it can be used as the actual rotation angle data under the test condition.

[0103] S104. Based on the correlation between the actual rotation angle data and the second strain data, determine whether the test condition is a torsional condition.

[0104] The correlation between the actual rotation angle data and the second strain data characterizes the degree to which the second strain data is influenced by the actual rotation angle data. A higher correlation indicates a more significant driving effect of the actual rotation angle change on the second strain data, meaning the deformation of the test object is primarily caused by torsion. Thus, by using the correlation between the actual rotation angle data and the second strain data, it is possible to objectively assess whether the strain of the test object is primarily caused by torsion, thereby determining whether the test condition is a torsion condition and solving the problem of accurately defining torsion conditions.

[0105] For example, the relevance can be 0, 1, or any value between 0 and 1, with a higher value indicating a higher relevance.

[0106] In the above embodiments, first strain data and second strain data of the test object during its driving process under the test condition can be obtained. Then, based on the first strain data and target calibration data, the actual turning angle data of the test object is determined. Finally, based on the correlation between the actual turning angle data and the second strain data, it is determined whether the test condition is a torsional condition. According to the solution provided in this application, when determining whether the test condition is a torsional condition, the actual turning angle data corresponding to the test condition can be derived based on the pre-calibrated target calibration data and the first strain data corresponding to the calibration device during driving, thereby solving the problem of difficulty in obtaining torsional condition data during actual driving. Through the correlation between the actual turning angle data and the second strain data, it is possible to objectively assess whether the strain of the test object is mainly caused by torsion, thereby determining whether the test condition is a torsional condition and solving the problem of difficulty in accurately defining torsional conditions.

[0107] In some optional embodiments, the target calibration data can be a mapping relationship between calibration angle data and calibration strain data obtained in advance by applying different rotational loads to the calibration device, wherein the calibration angle data is the detection value of the angle sensor and the calibration strain data is the detection value of the first strain gauge.

[0108] For example, see Figure 3 Under calibration bench testing conditions, different rotational loads are applied to the calibration device equipped with an angle sensor. For example, different rotational loads can be applied to the shaft in the calibration device using a hydraulic loading device. Correspondingly, the calibration angle data can be detected by the angle sensor on the calibration device, and the calibration strain data can be detected by the first strain gauge on the calibration device. Thus, a mapping relationship between the calibration angle data and the calibration strain data can be established, thereby obtaining the target calibration data.

[0109] In the above embodiments, unlike the whole vehicle testing phase, which is limited by factors such as installation space, complex driving conditions (such as vibration and bumps), and dense component layout, it is difficult to install angle sensors to detect angle data. In the calibration bench testing phase, the environment is controllable and space is ample, allowing for convenient installation of angle sensors. Therefore, relying on the precise detection capabilities of the angle sensors and the first strain gauge in the calibration bench testing, high-quality target calibration data can be constructed, providing a reliable foundation for subsequent derivation of actual angle data.

[0110] In some optional embodiments, the target calibration data corresponding to the object under test can be obtained in the following manner: the target calibration data corresponding to the object under test is obtained from multiple sets of calibration data, wherein the multiple sets of calibration data include calibration data corresponding to different objects under test.

[0111] Among them, multiple sets of calibration data can be calibration data for test objects with different characteristics. For example, multiple sets of calibration data can be calibration data for test objects with different dimensions, different stiffnesses, and other characteristics.

[0112] For example, multiple sets of calibration data can be stored in a database, meaning the target calibration data corresponding to the object under test can be retrieved from the database. This way, when conducting subsequent testing on a specific object under test, the target calibration data matching the current object can be retrieved from the database, eliminating the need to repeat the calibration bench test.

[0113] For example, the calibration data in the database can be continuously expanded to enrich the scope of testing and respond to the testing needs of different models and types of test objects.

[0114] In the above embodiments, matching calibration data that is suitable for different test objects can solve the problem of large errors in actual rotation angle data caused by mismatch between calibration data and test objects, and provide a reliable guarantee for the accurate back-calculation of subsequent actual rotation angle data and the accurate determination of torsional working conditions.

[0115] In some optional embodiments, obtaining target calibration data corresponding to the object under test from multiple sets of calibration data can be achieved as follows: obtaining the actual size of the object under test; obtaining target calibration data corresponding to the actual size of the object under test from multiple sets of calibration data, wherein the multiple sets of calibration data include calibration data corresponding to objects under test of different sizes respectively.

[0116] The actual dimension can be any dimension of the object under test extending in any direction. For example, the actual dimension can be the projected length of the calibration device on the surface connected to the object under test. Taking a battery pack as an example, the actual dimension can be the length, width, or height of the battery pack.

[0117] For example, such as Figure 2 As shown, the actual dimension can be the length L of the battery pack. The calibration device is fixedly connected along the length of the battery pack.

[0118] In the above embodiments, considering that the distribution of the torsion center and stress concentration area of ​​test objects of different sizes under torsional loads in a vehicle is closely related to their own size, selecting corresponding target calibration data for test objects of different sizes can enable the calculation of actual rotation angle data, which can more realistically and accurately reflect the torsional characteristics of the test object under the test conditions.

[0119] In some optional embodiments, obtaining target calibration data corresponding to the object under test from multiple sets of calibration data can be achieved as follows: obtaining target calibration data corresponding to a calibration device fixedly connected to the object under test from multiple sets of calibration data, wherein the multiple sets of calibration data include calibration data corresponding to calibration devices applicable to different objects under test respectively.

[0120] Different objects under test can correspond to different calibration devices, and the calibration data is the calibration data obtained by calibration through the calibration device. Therefore, the target calibration data corresponding to the object under test can be selected based on the calibration device.

[0121] For example, a battery pack with a length of L1 corresponds to a calibration device with a shaft length of L1, and a battery pack with a length of L2 corresponds to a calibration device with a shaft length of L2.

[0122] In some optional embodiments, multiple sets of calibration data are mapping relationships between calibration angle data and calibration strain data obtained in advance by applying different rotational loads to calibration devices of different sizes. The calibration angle data is the detection value of the angle sensor, and the calibration strain data is the detection value of the first strain gauge.

[0123] For example, calibration devices of different sizes can be calibration devices with rotating shafts of different lengths. Each calibration device with a rotating shaft of different lengths includes an angle sensor and a first strain gauge. The angle sensor collects corresponding calibration angle data, and the first strain gauge collects corresponding calibration strain data, thereby establishing calibration data corresponding to calibration devices of different sizes.

[0124] In some optional embodiments, during the vehicle testing phase, the calibration device can be fixedly connected to the side or bottom surface of the object under test. The bottom surface of the object under test refers to the side facing the ground during vehicle operation. The side surface of the object under test refers to the side adjacent to the bottom surface.

[0125] For example, taking a battery pack as the object under test, the calibration device can be fixedly connected to the side mounting point or the bottom surface of the battery pack.

[0126] In the above embodiments, the side mounting point and the bottom fixed connection point are the core connection points between the test object and the vehicle body, and also the main stress points and deformation transmission reference points of the test object under torsional conditions. Fixing the calibration device here makes the calibration device and the test object a rigidly linked whole. When the test object is subjected to torsional load and deforms, the calibration device will synchronously generate torsional deformation, so that the strain data collected by the calibration device can more accurately reflect the actual torsional condition of the test object.

[0127] In some optional embodiments, the preset position can be any position on the surface of the object to be tested. For example, the preset position can be located in the stress concentration area of ​​the object to be tested.

[0128] The stress concentration region of the object under test can be obtained through simulation experiments, and the preset position can be located at any position in the stress concentration region of the object under test.

[0129] For example, the stress concentration area can be a region where the stress value is greater than a preset stress threshold, and the preset location can be the location with the highest stress value in the stress concentration area.

[0130] In the above embodiments, under torsional load, the stress in the stress concentration region is higher than that in the non-stress concentration region. The effective signal in the non-stress concentration region is easily drowned out by noise, making it difficult to extract valuable features. Therefore, the strain signal acquired in the stress concentration region has an effective signal amplitude much larger than the noise amplitude, allowing for clear identification of signal variation patterns without complex filtering algorithms.

[0131] In some optional embodiments, determining whether the test condition is a torsional condition based on the correlation between the actual rotation angle data and the second strain data can be achieved as follows: using the actual rotation angle data as the independent variable and the second strain data as the dependent variable, determine the correlation coefficient between the actual rotation angle data and the second strain data in the target frequency range; based on the correlation coefficient and the correlation coefficient threshold, determine whether the test condition is a torsional condition.

[0132] Using the actual rotation angle data as the independent variable and the second strain data as the dependent variable, the obtained correlation coefficient can characterize the correlation between the actual rotation angle data and the second strain data, that is, the degree to which the second strain data is affected by the actual rotation angle data. The higher the correlation coefficient, the more significant the driving effect of the actual rotation angle change on the second strain data, that is, the deformation of the test object is mainly caused by torsion.

[0133] For example, if the correlation coefficient is greater than or equal to the correlation coefficient threshold, the test condition can be determined to be a torsional condition. If the correlation coefficient is less than the correlation coefficient threshold, the test condition can be determined not to be a torsional condition.

[0134] During vehicle operation, the strain data of the test object is easily affected by non-torsional factors such as vertical road vibration, engine vibration, and wind resistance impact, and these interference signals are mostly distributed in specific frequency ranges. Therefore, correlation analysis can be performed focusing on the target frequency range corresponding to torsional action to filter out signal noise caused by non-torsional interference.

[0135] The target frequency range can be the frequency band corresponding to the focusing torsional effect, and this target frequency range can be obtained through simulation or experience.

[0136] In the above embodiments, by establishing the causal relationship between the torsional angle and the strain change, the calculated correlation coefficient can objectively and quantitatively assess whether the test condition is a torsional condition. Furthermore, by limiting the correlation analysis to a target frequency range, the frequency band corresponding to the torsional effect can be precisely focused, effectively filtering signal noise caused by non-torsional interference and avoiding misjudgments caused by interference signals.

[0137] In some optional embodiments, using actual rotation angle data as the independent variable and second strain data as the dependent variable, the correlation coefficient between the actual rotation angle data and the second strain data in the target frequency range can be determined as follows: convert the actual rotation angle data into first frequency domain data; convert the second strain data into second frequency domain data; determine the first power spectrum corresponding to the first frequency domain data; determine the second power spectrum corresponding to the second frequency domain data; determine the complex conjugate cross power spectrum of the first frequency domain data and the second frequency domain data; and determine the correlation coefficient between the first frequency domain data and the second frequency domain data in the target frequency range based on the first power spectrum, the second power spectrum, and the cross power spectrum.

[0138] Both the actual rotation angle data and the second strain data are time-domain data. For example, the actual rotation angle data is X(t), and the second strain data is Y(t).

[0139] For example, the first frequency domain data X(f) can be obtained by performing a Fourier transform on the actual rotation angle data X(t); and the second frequency domain data Y(f) can be obtained by performing a Fourier transform on the second strain data Y(t).

[0140] For example, the first power spectrum can be calculated using the following relationship (1):

[0141] G XX (f)=|X(f)| 2 Relation (1)

[0142] The second power spectrum can be calculated using the following relationship (2):

[0143] G YY (f)=|X(f)| 2 Relation (2)

[0144] The cross power spectrum can be calculated using the following relationship (3):

[0145] G XY (f)=X(f)Y * (f) Relation (3)

[0146] Among them, Y * (f) is the complex conjugate of Y(f).

[0147] The correlation coefficient can be calculated using the following formula (4):

[0148] Relation (4)

[0149] The correlation coefficient N ranges from [0,1]. The larger the value of N, the higher the correlation between the actual rotation angle data and the second strain data. For example, when N=1, it means that the second strain data is completely caused by the actual rotation angle data, and the signals at that frequency are highly correlated.

[0150] For example, taking a correlation coefficient threshold of 0.7 as an example, if the correlation coefficient is greater than or equal to 0.7, the test condition is determined to be a torsional condition. If the correlation coefficient is less than 0.7, the test condition is determined not to be a torsional condition.

[0151] In some optional embodiments, the method may further include: determining the actual rotation angle data as the input data for the torsion test bench test when the test condition is determined to be a torsion condition.

[0152] For example, in a torsion bench test, a torsion test is performed on the test object based on actual rotation angle data, simulating the torsion condition. Performance testing is then conducted on the test object after the torsion test. For instance, the test object is inspected for structural abnormalities, insulation withstand voltage / air tightness, etc., after the torsion test. The structural durability test results of the test object can then be determined based on these test results.

[0153] In the above embodiments, the torsional condition is simulated based on the actual rotation angle data corresponding to the test condition, and the performance of the test object under the simulated torsional condition is tested. Based on the performance test results, targeted structural optimization, safety protection strategies and other solutions can be formulated to further improve the performance of the test object.

[0154] In some optional embodiments, the method may further include: when the test condition is determined to be a torsional condition, converting the actual rotation angle data into displacement data; and determining the displacement data as the input data for the torsional condition bench test.

[0155] For example, see Figure 2 Taking the battery pack as the object to be tested, the product of the sine value of the actual rotation angle data and the width W of the battery pack can be used as the displacement data corresponding to the actual rotation angle data.

[0156] See Figure 6 , Figure 6 In the middle (a), the actual turning angle data is represented. Figure 6 (b) indicates based on Figure 6 The displacement data is obtained by converting the actual rotation angle data in (a).

[0157] For example, taking a battery pack as the object under test, and the actual displacement corresponding to the rotation angle as 1mm, different displacements can be applied to different mounting points of the battery pack to simulate and reproduce the torsional angle. For example, applying an upward displacement of 0.5mm to the left mounting point of the battery pack and a downward displacement of 0.5mm to the right mounting point of the battery pack will achieve an overall displacement of 1mm.

[0158] In the above embodiments, by converting actual rotation angle data into displacement data, the bench loading mode can be switched to linear displacement control mode during torsion bench testing. By controlling the movement distance of the loading end of the bench, the required angular torsional deformation of the test object can be equivalently reproduced. In this way, torsion bench testing can directly use a conventional loading device with linear displacement loading function, without the need for dedicated angle control equipment, thereby effectively reducing the hardware configuration requirements for torsion bench testing.

[0159] It should be noted that the embodiments in this application are only used as examples to illustrate whether a certain working condition is a torsional working condition. The solutions provided in the above embodiments can be used to determine whether other working conditions are torsional working conditions, which will not be repeated here.

[0160] The embodiments of this application will be illustrated below using a battery pack as an example.

[0161] See Figure 7 , Figure 7 This is a flowchart illustrating a method for determining a torsional operating condition according to one or more embodiments. This method can be applied to a controller or other devices with processor capabilities, and this application does not limit its application. The following description uses a controller as an example to illustrate embodiments of this application. Figure 7 As shown, the method may include the following steps:

[0162] Step S201: Obtain first strain data and second strain data, wherein the first strain data is the detection value of the first strain gauge of the calibration device fixedly connected to the battery pack during the first operating condition, and the second strain data is the detection value of the second strain gauge at a preset position of the battery pack during the first operating condition.

[0163] Step S202: Obtain target calibration data that matches the current battery pack.

[0164] Step S203: Based on the first strain data and the target calibration data, determine the actual rotation angle data of the battery pack.

[0165] Step S204: Based on the correlation between the actual rotation angle data and the second strain data, determine whether the first working condition is a torsional working condition. If not, proceed to step S205; if yes, proceed to step S206.

[0166] Step S205: Obtain the first strain data and the second strain data during the driving process under the next working condition (e.g., the second working condition), and re-execute step S202 and subsequent steps.

[0167] Step S206: Convert the actual rotation angle data into displacement data.

[0168] Step S207: Determine the displacement data as the input data for simulating torsional conditions when performing performance testing on the battery pack under torsional bench test conditions.

[0169] The implementation methods and beneficial effects of each step in the above embodiments can be referred to the content of the foregoing embodiments, and will not be described in detail here.

[0170] It is understood that the above embodiments are merely examples, and modifications can be made to the above embodiments in actual implementation. Those skilled in the art will understand that any modifications to the above embodiments that do not require creative effort fall within the protection scope of this application, and will not be described in detail in the embodiments.

[0171] Based on the same inventive concept, embodiments of this application also provide a collision detection device for sealing performance detection.

[0172] See Figure 8 , Figure 8 This is a structural block diagram of an apparatus for determining a torsional condition according to one or more embodiments. The apparatus 800 for determining the torsional condition may include: a first acquisition component 801, a second acquisition component 802, a first determination component 803, and a second determination component 804.

[0173] The first acquisition component 801 is used to acquire first strain data and second strain data, wherein the first strain data is the detection value of the first strain gauge of the calibration device fixedly connected to the object under test during the driving process under the test condition, and the second strain data is the detection value of the second strain gauge at a preset position of the object under test during the driving process under the test condition.

[0174] The second acquisition component 802 is used to acquire the target calibration data corresponding to the object under test, wherein the target calibration data includes the mapping relationship between calibration angle data and calibration strain data;

[0175] The first determining component 803 is used to determine the actual rotation angle data of the object under test based on the first strain data and the target calibration data;

[0176] The second determining component 804 is used to determine whether the test condition is a torsional condition based on the correlation between the actual rotation angle data and the second strain data.

[0177] In some optional embodiments, the target calibration data is a mapping relationship between calibration angle data and calibration strain data obtained in advance by applying different rotational loads to the calibration device, wherein the calibration angle data is the detection value of the calibration device and the calibration strain data is the detection value of the first strain gauge.

[0178] In some optional embodiments, the second acquisition component 802 is used to: acquire target calibration data corresponding to the test object from multiple sets of calibration data, wherein the multiple sets of calibration data include calibration data corresponding to different test objects respectively.

[0179] In some optional embodiments, the second acquisition component 802 is used to: acquire the actual size of the object to be measured;

[0180] Target calibration data corresponding to the actual size of the test object is obtained from multiple sets of calibration data, wherein the multiple sets of calibration data include calibration data corresponding to test objects of different sizes.

[0181] In some optional embodiments, multiple sets of calibration data are mapping relationships between calibration angle data and calibration strain data obtained in advance by applying different rotational loads to calibration devices of different sizes. The calibration angle data is the detection value of the rotation angle sensor of the calibration device, and the calibration strain data is the detection value of the first strain gauge.

[0182] In some optional embodiments, the preset location is located in the stress concentration area of ​​the object under test.

[0183] In some optional embodiments, the second determining component 804 is used to: determine the correlation coefficient between the actual rotation angle data and the second strain data in the target frequency range, using the actual rotation angle data as the independent variable and the second strain data as the dependent variable; and determine whether the test condition is a torsional condition based on the correlation coefficient and the correlation coefficient threshold.

[0184] In some optional embodiments, the second determining component 804 is configured to: convert the actual rotation angle data into first frequency domain data; convert the second strain data into second frequency domain data; determine the first power spectrum corresponding to the first frequency domain data; determine the second power spectrum corresponding to the second frequency domain data; determine the complex conjugate cross power spectrum of the first frequency domain data and the second frequency domain data; and determine the correlation coefficient between the first frequency domain data and the second frequency domain data in the target frequency range based on the first power spectrum, the second power spectrum, and the cross power spectrum.

[0185] In some optional embodiments, it further includes: a third determining module, used to determine the actual rotation angle data as the input data for the torsion condition bench test when the test condition is determined to be a torsion condition.

[0186] In some optional embodiments, it further includes: a fourth determining module, used to convert the actual rotation angle data into displacement data when the test condition is determined to be a torsional condition; and to determine the displacement data as the input data for the torsional condition bench test.

[0187] Based on the same inventive concept, this application also provides a battery management system, including: a sampling unit for acquiring first strain data and second strain data, wherein the first strain data is the detection value of a first strain gauge of a calibration device fixedly connected to the test object during driving under the test condition, and the second strain data is the detection value of a second strain gauge at a preset position of the test object during driving under the test condition; a processing unit for acquiring target calibration data corresponding to the test object, wherein the target calibration data includes a mapping relationship between calibration angle data and calibration strain data; for determining the actual angle data of the test object based on the first strain data and the target calibration data; and for determining whether the test condition is a torsional condition based on the correlation between the actual angle data and the second strain data.

[0188] Based on the same inventive concept, embodiments of this application also provide a battery system, including the aforementioned battery management system.

[0189] Based on the same inventive concept, this application provides an electrical device including the battery system described above.

[0190] Based on the same inventive concept, embodiments of this application also provide a torsional condition determination system, which includes a controller that can be used to execute... Figure 4 , Figure 7 The method in any of the method embodiments shown in the figures is illustrated. It should be understood that the torsional condition determination system may also include other devices, such as a calibration device, a first strain gauge, a second strain gauge, etc. Exemplarily, the torsional condition determination system may be... Figure 2 The torsional condition determination system is shown.

[0191] Based on the same inventive concept, embodiments of this application also provide an electronic device, which includes a processor and a memory, wherein the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so as to cause the electronic device to perform... Figure 4 , Figure 7 The method in any of the method embodiments shown in any of the figures.

[0192] Based on the same inventive concept, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when run on an electronic device, causes the electronic device to perform... Figure 4 , Figure 7 The method in any of the method embodiments shown in any of the figures.

[0193] Based on the same inventive concept, this application also provides a computer program product, which includes a computer program that, when run on an electronic device, causes the electronic device to perform... Figure 4 , Figure 7 The method in any of the method embodiments shown in any of the figures.

[0194] Those skilled in the art will recognize that the various illustrative logical blocks and steps described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0195] If these functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0196] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the torsional working condition determination device, torsional working condition determination system, electronic device, computer-readable storage medium, and computer program product described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0197] In the several embodiments provided in this application, it should be understood that the disclosed apparatus, system, electronic device, and method can be implemented in other ways. For example, the embodiments of the apparatus and electronic device described above are merely illustrative; multiple components may be combined or integrated into another system, or some features may be omitted or not performed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection between devices or units through some interface, and may be electrical, mechanical, or other forms.

[0198] It should be understood that in the various embodiments of this application, the execution order of each step should be determined by its function and internal logic, and the size of each step number does not mean the order of execution, and does not constitute a limitation on the implementation process of the embodiments.

[0199] The various parts of this specification are described in a progressive manner. Similar or identical parts between the various embodiments can be referred to mutually. Each embodiment focuses on the differences from other embodiments. In particular, the embodiments for the torsional condition determination device, torsional condition determination system, electronic device, computer-readable storage medium, and computer program product are basically similar to the method embodiments, so the description is relatively simple; relevant details can be found in the descriptions within the method embodiments.

[0200] In this document, the terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Those skilled in the art will understand the specific meaning of the above terms in this application according to the specific circumstances. It should be noted that, without conflict, the embodiments and features in the embodiments of this application can be combined with each other. This application is not limited to any single aspect, nor to any single embodiment, nor to any combination and / or substitution of these aspects and / or embodiments. Moreover, each aspect and / or embodiment of this application can be used alone or in combination with one or more other aspects and / or embodiments thereof.

[0201] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and not to limit them; although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and they should all be covered within the scope of this application.

Claims

1. A method for determining torsional operating conditions, characterized in that, The method includes: Acquire first strain data and second strain data, wherein the first strain data is the detection value of the first strain gauge of the calibration device fixedly connected to the object under test during the driving process under the test condition, and the second strain data is the detection value of the second strain gauge at a preset position of the object under test during the driving process under the test condition. Obtain the target calibration data corresponding to the object under test, wherein the target calibration data includes the mapping relationship between calibration angle data and calibration strain data; Based on the first strain data and the target calibration data, the actual rotation angle data of the object under test is determined; Based on the correlation between the actual rotation angle data and the second strain data, it is determined whether the test condition is a torsional condition.

2. The method according to claim 1, characterized in that, The target calibration data is a mapping relationship between calibration angle data and calibration strain data obtained in advance by applying different rotational loads to the calibration device. The calibration angle data is the detection value of the angle sensor of the calibration device, and the calibration strain data is the detection value of the first strain gauge.

3. The method according to claim 1, characterized in that, The step of obtaining the target calibration data corresponding to the object under test includes: Target calibration data corresponding to the test object is obtained from multiple sets of calibration data, wherein the multiple sets of calibration data include calibration data corresponding to different test objects respectively.

4. The method according to claim 3, characterized in that, The step of obtaining target calibration data corresponding to the object under test from multiple sets of calibration data includes: Obtain the actual dimensions of the object to be measured; Target calibration data corresponding to the actual size of the test object is obtained from multiple sets of calibration data, wherein the multiple sets of calibration data include calibration data corresponding to test objects of different sizes.

5. The method according to claim 3 or 4, characterized in that, The multiple sets of calibration data are mapping relationships between calibration angle data and calibration strain data obtained in advance by applying different rotational loads to calibration devices of different sizes. The calibration angle data is the detection value of the rotation angle sensor of the calibration device, and the calibration strain data is the detection value of the first strain gauge.

6. The method according to claim 1, characterized in that, The preset position is located in the stress concentration area of ​​the object under test.

7. The method according to claim 1, characterized in that, The step of determining whether the test condition is a torsional condition based on the correlation between the actual rotation angle data and the second strain data includes: Using the actual rotation angle data as the independent variable and the second strain data as the dependent variable, determine the correlation coefficient between the actual rotation angle data and the second strain data within the target frequency range; Based on the correlation coefficient and the correlation coefficient threshold, it is determined whether the test condition is a torsional condition.

8. The method according to claim 7, characterized in that, The step of determining the correlation coefficient between the actual rotation angle data and the second strain data within the target frequency range, using the actual rotation angle data as the independent variable and the second strain data as the dependent variable, includes: Convert the actual rotation angle data into first frequency domain data; Convert the second strain data into second frequency domain data; Determine the first power spectrum corresponding to the first frequency domain data; Determine the second power spectrum corresponding to the second frequency domain data; Determine the complex conjugate cross power spectrum of the first frequency domain data and the second frequency domain data; Based on the first power spectrum, the second power spectrum, and the cross power spectrum, the correlation coefficient between the first frequency domain data and the second frequency domain data in the target frequency range is determined.

9. The method according to claim 1, characterized in that, The method further includes: If the test condition is determined to be a torsional condition, the actual rotation angle data is determined as the input data for the torsional condition bench test.

10. The method according to claim 1, characterized in that, The method further includes: If the test condition is determined to be a torsional condition, the actual rotation angle data is converted into displacement data. The displacement data is used as the input data for the torsional bench test.

11. A device for determining torsional working conditions, characterized in that, The device includes: The first acquisition component is used to acquire first strain data and second strain data, wherein the first strain data is the detection value of the first strain gauge of the calibration device fixedly connected to the object under test during the driving process under the test condition, and the second strain data is the detection value of the second strain gauge at a preset position of the object under test during the driving process under the test condition. The second acquisition component is used to acquire target calibration data corresponding to the object under test, wherein the target calibration data includes the mapping relationship between calibration angle data and calibration strain data; A first determining component is used to determine the actual rotation angle data of the object under test based on the first strain data and the target calibration data; The second determining component is used to determine whether the test condition is a torsional condition based on the correlation between the actual rotation angle data and the second strain data.

12. A battery management system, characterized in that, include: A sampling unit is used to acquire first strain data and second strain data, wherein the first strain data is the detection value of the first strain gauge of the calibration device fixedly connected to the object under test during the driving process under the test condition, and the second strain data is the detection value of the second strain gauge at a preset position of the object under test during the driving process under the test condition. The processing unit is configured to acquire target calibration data corresponding to the object under test, wherein the target calibration data includes a mapping relationship between calibration angle data and calibration strain data; to determine the actual angle data of the object under test based on the first strain data and the target calibration data; and to determine whether the test condition is a torsional condition based on the correlation between the actual angle data and the second strain data.

13. A battery system, characterized in that, Includes the battery management system as described in claim 12.

14. An electrical appliance, characterized in that, Including the battery system as described in claim 13.

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