Test system, evaluation method, device, equipment and medium
By combining a pressure regulating mechanism and sensors, it is adapted to different battery specifications, solving the problem of needing to change the sensor layout, and realizing efficient measurement and evaluation of battery expansion force.
Patent Information
- Application Number
- CN202511547088.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-27
- Publication Date
- 2026-02-06
AI Technical Summary
In existing technologies for measuring battery expansion force, the sensor layout needs to be changed according to the battery type or specifications, resulting in cumbersome design and low efficiency.
It employs a pressure regulating mechanism and a movable platform, combined with sensors on a fixed platform, to accommodate batteries of different specifications. The pressure regulating mechanism controls the position of the movable platform, applies or removes pressure, collects pressure detection data, and conducts testing in an environmental simulation chamber.
It enables efficient measurement of expansion force characteristics for different battery specifications, avoids sensor interference with normal battery operation, and provides accurate pressure detection data and evaluation results.
Smart Images
Figure CN121475477A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of battery testing, in particular to a testing system, an evaluation method, a device, equipment and a medium. BACKGROUND
[0002] When testing a battery, it is usually necessary to detect its swelling force characteristics.
[0003] The prior art generally deploys multiple sensors in close proximity to the surface of the battery, but this solution has obvious limitations: once the battery type or specification is changed, the layout and installation of the sensors need to be redesigned, which is tedious and inefficient.
[0004] Therefore, an improved battery swelling force measurement scheme is needed. SUMMARY
[0005] Therefore, the embodiments of the present application provide a testing system, an evaluation method, a device, equipment and a medium to test the swelling force characteristics of different types of batteries.
[0006] In a first aspect, the embodiments of the present application provide a testing system, comprising: a detection module; The detection module comprises: a pressure adjusting mechanism; a movable platform connected to the pressure adjusting mechanism, configured to apply pressure or remove pressure from the first surface of the battery based on the driving of the pressure adjusting mechanism; a fixed platform configured to apply pressure to the second surface of the battery; the first surface and the second surface are different; The surfaces of the movable platform and the fixed platform are each provided with a plurality of pressure sensors configured to collect pressure on the first surface and / or the second surface when contacting the battery, to obtain pressure detection data.
[0007] In a feasible implementation, the system further comprises: an environment simulation box for placing the detection module; The environment simulation box is provided with an environment adjusting submodule configured to adjust the environmental parameters in the environment simulation box, so that the detection module performs detection operations under different environmental parameters; the environmental parameters include at least one of the following: temperature, humidity, air pressure.
[0008] In a second aspect, the embodiments of the present application further provide an evaluation method, comprising: obtaining detection data of a target battery; the detection data at least includes pressure detection data detected by the testing system according to the first aspect; transmit the detection data to a pre-trained performance evaluation model to obtain an evaluation result output by the performance evaluation model; the evaluation result is used to indicate the swelling force characteristic of the battery.
[0009] In an implementable embodiment, the test system comprises an environment simulation box. The detection data further comprises an environmental parameter and a mapping relationship between the environmental parameter and the pressure detection data. The performance evaluation model is obtained by the following method: A plurality of sets of training data are obtained in advance; each set of the training data comprises pressure detection data of a battery under different environmental parameters. The performance evaluation model is trained based on the plurality of sets of training data.
[0010] In an implementable embodiment, the performance evaluation model is trained based on the plurality of sets of training data, comprising: The training data are preprocessed to obtain target data. An initial model is driven to dynamically adjust its model parameters based on the target data by using a preset algorithm to obtain a target model; the preset algorithm is used to reduce the prediction error of the initial model.
[0011] If the target model satisfies a preset evaluation accuracy by a ten-fold cross-validation method, the target model is determined as a final performance evaluation model.
[0012] In an implementable embodiment, the preset algorithm comprises: A least square method or a back propagation algorithm. The initial model comprises: A multiple linear regression model, a support vector machine model or a neural network model.
[0013] In an implementable embodiment, the method further comprises: Obtaining a specification parameter of a target battery to be detected; Determining a driving signal matched to the specification parameter; Sending the driving signal to the pressure adjusting mechanism to drive the movable platform to apply a pressure matched to the target battery.
[0014] In a third aspect, the embodiments of the present application further provide an evaluation device, comprising: An obtaining module is configured to obtain detection data of a target battery; the detection data at least comprises pressure detection data detected by the test system according to the first aspect. An evaluation module is configured to transmit the detection data to a pre-trained performance evaluation model to obtain an evaluation result output by the performance evaluation model, wherein the evaluation result is used to indicate the swelling force characteristic of the battery.
[0015] In an embodiment, the test system comprises an environment simulation box. The detection data further comprises an environmental parameter and a mapping relationship between the environmental parameter and the pressure detection data. The performance evaluation model is trained by the training module in the following manner: A plurality of sets of training data are obtained in advance, wherein each set of training data comprises pressure detection data of a battery under different environmental parameters. The performance evaluation model is trained based on the plurality of sets of training data.
[0016] In an embodiment, the training module is configured to train the performance evaluation model based on the plurality of sets of training data, and the performance evaluation model is configured to: Preprocess the training data to obtain target data. Based on the target data, an initial model is driven to dynamically adjust its model parameters using a preset algorithm to obtain a target model, wherein the preset algorithm is used to reduce the prediction error of the initial model.
[0017] If the target model satisfies a preset evaluation accuracy through a ten-fold cross-validation method, the target model is determined as the final performance evaluation model.
[0018] In an embodiment, the preset algorithm comprises: A least square method or a back propagation algorithm. The initial model comprises: A multiple linear regression model, a support vector machine model, or a neural network model.
[0019] In an embodiment, the device further comprises: A specification determination module configured to obtain a specification parameter of a target battery to be detected. A matching module configured to determine a driving signal matched to the specification parameter. A sending module configured to send the driving signal to the pressure adjusting mechanism, so that the pressure adjusting mechanism drives the movable platform to apply a pressure matched to the target battery.
[0020] In a fourth aspect, the embodiments of the present application further provide an electronic device, comprising a processor, a storage medium and a bus, the storage medium storing machine readable instructions executable by the processor, when the electronic device is running, the processor and the storage medium communicate through the bus, and the processor executes the machine readable instructions to perform the steps of the method according to any one of the second aspect.
[0021] In a fifth aspect, the embodiments of the present application further provide a computer readable storage medium, the computer readable storage medium storing a computer program, when the computer program is run by a processor, the steps of the method according to any one of the second aspect are performed.
[0022] The embodiments of the present application provide a test system, an evaluation method, a device and a medium. The test system is used to test the pressure of one surface of the battery by a fixed platform and the pressure of the other surface of the battery by a movable platform. The test system provided by the present application is provided with a pressure adjusting mechanism connected with the movable platform. On the one hand, the position of the movable platform can be controlled by the pressure adjusting mechanism, so as to adapt to the test of batteries of different specifications.
[0023] On the other hand, different pressures can be applied to the surface of the battery in different test stages, so as to avoid the problem that the sensor interferes with the normal work of the battery and causes inaccurate test results.
[0024] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the following preferred embodiments are described in detail below, and the accompanying drawings are described as follows. BRIEF DESCRIPTION OF DRAWINGS
[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.
[0026] Figure 1 The structure schematic diagram of the detection module of the test system provided by the embodiments of the present application is shown.
[0027] Figure 2 The moving direction schematic diagram of the movable platform in the detection module provided by the embodiments of the present application is shown.
[0028] Figure 3 The structure schematic diagram of a test system provided by the embodiments of the present application is shown.
[0029] Figure 4 The flow schematic diagram of an evaluation method provided by the embodiments of the present application is shown.
[0030] Figure 5 A structural schematic diagram of an evaluation device provided by an embodiment of the present application is shown.
[0031] Figure 6 A structural schematic diagram of an electronic device provided by an embodiment of the present application is shown. DETAILED DESCRIPTION
[0032] To make the objectives, technical solutions, and superiorities of the embodiments of the present application clearer, the following will be a clear and complete description of the technical solutions in the embodiments of the present application with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the accompanying drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.
[0033] During the charging and discharging process of the battery, due to the embedding and extraction of lithium ions, the volume of the electrode material changes, resulting in the "breathing effect" of the entire battery cell, which expands outward. This expansion will generate pressure on the battery shell and the module fixing structure. Therefore, when testing the battery, it is usually necessary to detect its swelling force characteristics.
[0034] The prior art generally deploys multiple sensors close to the surface of the battery, but this solution has obvious limitations: once the battery type or specification is changed, the layout and installation of the sensors need to be redesigned, which is tedious and inefficient.
[0035] Therefore, an improved battery swelling force measurement scheme is needed.
[0036] Based on this, the embodiments of the present application provide a test system, an evaluation method, an apparatus, a device and a medium, which are described below through embodiments.
[0037] Figure 1 A structural schematic diagram of a detection module of a test system provided by an embodiment of the present application is shown, as shown in Figure 1 The detection module includes: A pressure adjusting mechanism 101.
[0038] An active platform 102 connected with the pressure adjusting mechanism, configured to apply pressure or remove pressure on the first surface of the battery 100 based on the driving of the pressure adjusting mechanism 101.
[0039] A fixed platform 103 is arranged to apply pressure to the second face of the battery 100, which is different from the first face.
[0040] The surfaces of the movable platform 102 and the fixed platform 103 are provided with a plurality of pressure sensors (such as Figure 1 The sensors 104 and 105 are arranged to collect the pressure of the first face and / or the second face when contacting the battery 100, and obtain pressure detection data.
[0041] For example, Figure 2 The movement direction of the movable platform in the detection module is shown in the schematic diagram. Figure 2 As shown, the pressure adjusting mechanism 101 can control the movable platform 102 to move up and down along the arrow direction, so as to apply or release pressure to the first face of the battery 100. It can be seen that when the movable platform 102 moves downward along the arrow direction (towards the battery 100), pressure is applied to the first face (the upper contact surface) of the battery 100. The closer the movable platform 102 is to the battery 100, the greater the pressure applied to the battery 100.
[0042] Before testing, each sensor is calibrated to ensure the accuracy of pressure data collection. Then, the battery 100 is placed on the fixed platform 103. Then, according to the specifications of the battery 100, the pressure adjusting mechanism 101 controls the movable platform 102 to apply pressure to the battery 100, so that the first face of the battery 100 is tightly attached to the movable platform 102, and the second face of the battery 100 is tightly attached to the fixed platform 103. At this time, the data collected by the sensor is the pressure detection data of the battery 100.
[0043] It should be noted that in order to test the expansion force performance of the battery 100 in the running state, the battery 100 can be subjected to charging and discharging operation. Optionally, the pressure adjusting mechanism 101 is further provided with a control center, which can generate control instructions to control the pressure adjusting mechanism 101 to drive the movable platform 102 to move. For example, after obtaining the specifications of the battery, the control center can generate control instructions suitable for the specifications of the battery according to the specifications of the battery or the detected position of the battery, so that the movable platform 102 moves to a specific position.
[0044] For another example, the control center can control the movable platform 102 to apply different sizes of pressure in different test stages. For example, a pre-tightening force of 10N is applied to the battery at first, and during the charging and discharging process, in order to avoid excessive pressure interfering with the operation of the battery, the pre-tightening force of 10N can be modified to 8N. Or, in order to improve the measurement accuracy, it is modified to 20N.
[0045] In a feasible implementation, Figure 3A structural schematic diagram of a test system provided by an embodiment of the present application is shown, and the test system further comprises: An environment simulation box 301 for placing the detection module.
[0046] The environment simulation box 301 is provided with an environment adjusting submodule for adjusting the environment parameters in the environment simulation box, so that the detection module performs detection operation under different environment parameters; the environment parameters include at least one of the following: temperature, humidity, air pressure.
[0047] It can be seen that, Figure 1 The detection module is shown to be located in the environment simulation box 301. When detecting the battery, in order to ensure that the environment in the environment simulation box 301 is not affected by the external environment, the environment simulation box 301 is closed.
[0048] For example, according to the specifications of the battery 100, the pressure adjusting mechanism 101 controls the movable platform 102 to apply pressure (assuming pressure one) to the battery 100, so that the first surface of the battery 100 closely adheres to the movable platform 102, and the second surface of the battery 100 closely adheres to the fixed platform 103.
[0049] Then, the detection module is placed in Figure 3 The environment simulation box 301 is shown, and then the temperature is set to 25℃, the humidity is set to 50%, and the air pressure is set to 1 standard atmosphere by the environment adjusting submodule.
[0050] Then, the battery 100 is subjected to a charge-discharge operation. For example, the charge-discharge operation can be performed in the following manner: the charge-discharge operation adopts 0.5C, 1C, and 1.5C three charge-discharge rates for cycle test, and 5 charge-discharge cycles are performed under each charge-discharge rate.
[0051] Alternatively, the temperature of the environment simulation box 301 is set to 30℃, the humidity is set to 60%, and the air pressure is set to 1.1 standard atmosphere. The charge-discharge operation adopts 0.3C, 1.2C, and 1.8C three charge-discharge rates for cycle test, and 8 charge-discharge cycles are performed under each charge-discharge rate.
[0052] During this period, the pressure data of the battery 100 in the charge-discharge process is detected by the sensors on the movable platform 102 and the fixed platform 103, and the pressure detection data is obtained.
[0053] When the battery is charged and discharged, the charge-discharge parameters of the battery are recorded. Including but not limited to: charge-discharge current, charge-discharge voltage and charge-discharge time.
[0054] Based on the same technical concept, the present application further provides an evaluation method, and the method is applied to a control center, Figure 4A flowchart of an evaluation method provided by an embodiment of the application is shown, and the method comprises the following steps: In step 401, detection data of a target battery is obtained; the detection data at least comprises pressure detection data detected by the test system in the foregoing embodiment.
[0055] The target battery is placed in the test system in the foregoing embodiment for detection, and detection data of the target battery can be obtained. The detection data at least comprises pressure detection data detected by the sensors on the movable platform and the fixed platform.
[0056] Exemplarily, the charge and discharge parameters of the battery can also be included, including but not limited to: charge and discharge current, charge and discharge voltage, and charge and discharge time.
[0057] In step 402, the detection data is transmitted to a pre-trained performance evaluation model, and an evaluation result output by the performance evaluation model is obtained; the evaluation result is used to indicate the swelling force characteristics of the battery.
[0058] The performance evaluation is pre-trained, and can analyze the swelling force characteristics of the target battery according to the input detection data, and evaluate the performance and safety of the target battery.
[0059] According to the scheme, the swelling force performance of the battery and / or other performance of the battery can be evaluated according to the detection data of the target battery provided by the test system, which helps to understand the life and characteristics of the battery, and provides direction and data support for battery optimization.
[0060] It should be noted that the control center applied in the scheme can be a control center in the test system, or can be independent of the test system, and interacts with the test system through other ways (for example, obtains data of the test system, or sends control instructions to the pressure adjusting mechanism of the test system, etc.).
[0061] In a feasible embodiment, the test system comprises an environment simulation box. The detection data further comprises environmental parameters and a mapping relationship between the environmental parameters and the pressure detection data.
[0062] At this time, the performance evaluation model is obtained by the following way: A plurality of sets of training data are obtained in advance; each set of training data comprises pressure detection data of a battery under different environmental parameters; and a performance evaluation model is trained based on the plurality of sets of training data.
[0063] The training data at least comprises pressure detection data of the battery, and can further comprise charge and discharge parameters of the battery and environmental parameters (temperature, humidity, atmospheric pressure, etc.).
[0064] After obtaining the performance evaluation model, since the performance evaluation model considers the stress data of the battery under different environmental parameters during training, the expansion force characteristics and performance of the battery under different working conditions can be analyzed.
[0065] The following gives several examples: Case one, analyze the expansion force of the target battery under different combinations of temperature (such as 0°C, 40°C, 60°C), humidity (such as 30%, 70%), air pressure (such as 0.8 standard atmosphere, 1.2 standard atmosphere) and charge-discharge rate (such as 0.2C, 2C, 3C). For example, take temperature 40°C, humidity 70%, air pressure 1.2 standard atmosphere, and charge-discharge rate 2C as input, and the performance evaluation model will output the following evaluation results: the expansion force of the battery is 3000N.
[0066] Case two, by analyzing the regression coefficients of each variable (temperature, humidity, air pressure, charge-discharge rate, etc.) in the performance evaluation model, the influence degree of each influencing factor on the expansion force of the battery is determined. In one embodiment, it can be analyzed that the charge-discharge rate has the most significant influence on the expansion force of the battery, followed by temperature, and the influence of humidity and air pressure is relatively small.
[0067] Case three, study the change rule of the expansion force of the battery with the number of charge-discharge cycles, and by analyzing the pressure data under different charge-discharge cycle numbers, it is found that the expansion force of the battery gradually increases with the increase of the number of charge-discharge cycles, and when the number of charge-discharge cycles reaches 2000 times, the growth rate of the expansion force of the battery obviously accelerates, indicating that the battery begins to show aging phenomenon, and the life expectancy of the battery is estimated to be around 2500 charge-discharge cycles.
[0068] Case four, through the analysis of the performance evaluation model, it is found that the influence degree of temperature on the expansion force of the battery has increased, and is similar to the influence degree of the charge-discharge rate.
[0069] For example, the performance evaluation model can also evaluate the safety of the battery. The following methods can be used: Compare the evaluated expansion force of the battery with the preset safety threshold, for example, the safety threshold can be set to 30000N, if the expansion force exceeds the safety threshold, it is judged that the battery has safety risk. For example, when the expansion force of the battery under a certain working condition is predicted to be 35000N, it is judged that the battery has safety risk under this condition.
[0070] Further, the performance evaluation model can also provide suggestions for optimizing battery design and usage strategies based on the battery swelling force characteristics and safety evaluation results. For example, since the charge-discharge rate has a significant impact on the battery swelling force, it is recommended to avoid using excessively high charge-discharge rates during battery use. To address battery aging issues, it is recommended to improve battery materials and increase the stability of battery materials to extend battery life.
[0071] Alternatively, when the battery is working at a high temperature and high humidity environment with a high charge-discharge rate, the swelling force increases rapidly, and the safety risk is greater, therefore it is recommended to strengthen the heat management and moisture-proof measures in the battery design, and at the same time optimize the battery management system, and adjust the charge-discharge strategy in real time according to the working environment of the battery.
[0072] In one possible implementation, the performance evaluation model is trained based on the plurality of sets of training data, including: The training data is preprocessed to obtain target data, and based on the target data, an initial model is driven to dynamically adjust its model parameters using a preset algorithm to obtain a target model. The preset algorithm is used to reduce the prediction error of the initial model. If the target model satisfies the preset evaluation accuracy by ten-fold cross-validation method, the target model is determined as the final performance evaluation model.
[0073] Preprocessing is to clean up data. For example, the following preprocessing can be performed: The data cleaning algorithm is used to remove obviously incorrect and abnormal data points, then the wavelet denoising algorithm is used for denoising, and finally the data is normalized to the interval [0, 1] by a normalization formula to eliminate the influence of different data dimensions.
[0074] After preprocessing, target data is obtained, and the initial model is trained to obtain a target model. Then, the accuracy of the target model is verified by ten-fold cross-validation method (whether it reaches the preset evaluation accuracy). If it reaches the preset evaluation accuracy, the target model is taken as the final performance evaluation model.
[0075] In this way, a performance evaluation model with accurate evaluation results can be obtained.
[0076] For example, the preset algorithm includes least squares method or back propagation algorithm, and the initial model includes multivariate linear regression model, support vector machine model or neural network model.
[0077] For example, a neural network model is selected as the initial model, and the neural network model is trained by several sets of training data, and the neural network model is trained by using a back propagation algorithm, and the connection weights and thresholds between neurons are adjusted to minimize the error between the evaluation results of the performance evaluation model and the actual data. Alternatively, a multiple linear regression model is selected as the initial model because the multiple linear regression model can better handle the linear relationship between multiple independent variables and dependent variables, and the calculation is relatively simple, easy to understand and interpret.
[0078] In a feasible implementation, the method further comprises: Obtaining the specification parameters of the target battery to be detected. Determining the driving signal matched to the specification parameters. Sending the driving signal to the pressure adjusting mechanism to drive the pressure adjusting mechanism to drive the movable platform to apply pressure matched to the target battery.
[0079] By this method, the pressure adjusting mechanism can apply different pressures to batteries of different specifications, so that it can be applied to measure the performance of all batteries, so as to obtain more accurate pressure detection data through testing, and then help to obtain more accurate evaluation results.
[0080] In an alternative, a sensor can be installed on the movable platform and / or the fixed platform to detect the specification of the battery to be tested, so as to automatically control the pressure adjusting mechanism to move the movable platform to a position suitable for the specification of the battery according to the detected specification of the battery. Alternatively, the specification parameters of the battery can also be input into the test system, and then the control center of the test system (which can be a separate control center or the control center of the pressure adjusting mechanism) issues a control instruction to control the pressure adjusting mechanism to move the movable platform to a position suitable for the specification of the battery.
[0081] In a feasible implementation, the battery evaluated as qualified by the above evaluation method is applied to a vehicle.
[0082] For example, a correlation model of the battery swelling force and the environmental parameters and the charging and discharging parameters can also be constructed to realize quantitative analysis and prediction of the swelling force. And / or, the influence degree of factors such as temperature, humidity, air pressure, and charging and discharging rate on the battery swelling force is analyzed based on the performance evaluation model to distinguish the primary and secondary factors related to the battery swelling force.
[0083] Based on the same technical concept, the embodiments of the present application also provide an evaluation device, as shown in Figure 5 The device comprises: The acquisition module 501 is configured to acquire detection data of a target battery, and the detection data at least comprises pressure detection data detected by the test system according to the first aspect.
[0084] The evaluation module 502 is configured to transmit the detection data to a pre-trained performance evaluation model to obtain an evaluation result output by the performance evaluation model, and the evaluation result is used to indicate the swelling force characteristic of the battery.
[0085] In an embodiment, the test system comprises an environment simulation box.
[0086] The detection data further comprises an environmental parameter and a mapping relationship between the environmental parameter and the pressure detection data.
[0087] The performance evaluation model is trained by the training module in the following manner: A plurality of sets of training data are obtained in advance, and each set of training data comprises pressure detection data of a battery under different environmental parameters.
[0088] The performance evaluation model is trained based on the plurality of sets of training data.
[0089] In an embodiment, the training module is configured to train the performance evaluation model based on the plurality of sets of training data, so as to: The training data are preprocessed to obtain target data.
[0090] Based on the target data, an initial model is driven by a preset algorithm to dynamically adjust model parameters of the initial model to obtain a target model, and the preset algorithm is used to reduce a prediction error of the initial model.
[0091] If the target model satisfies a preset evaluation accuracy by a ten-fold cross-validation method, the target model is determined as a final performance evaluation model.
[0092] In an embodiment, the preset algorithm comprises a least square method or a back propagation algorithm.
[0093] The initial model comprises a multiple linear regression model, a support vector machine model or a neural network model.
[0094] In an embodiment, the device further comprises: A specification determination module is configured to obtain a specification parameter of a target battery to be detected.
[0095] A matching module is configured to determine a driving signal matched to the specification parameter.
[0096] A sending module is configured to send the driving signal to the pressure adjusting mechanism, so that the pressure adjusting mechanism drives the movable platform to apply a pressure matched to the target battery.
[0097] Figure 6A structural schematic diagram of an electronic device provided in the embodiment of the present application is shown, which comprises a processor 601, a storage medium 602 and a bus 603, the storage medium 602 stores machine readable instructions executable by the processor 601, when the electronic device runs the evaluation method as in the embodiment, the processor 601 and the storage medium 602 communicate through the bus 603, the processor 601 executes the machine readable instructions to perform the steps as in the embodiment.
[0098] In the embodiment, the storage medium 602 can also execute other machine readable instructions to perform the methods as in the embodiment, for the specific method steps and principles executed, refer to the description of the embodiment, which will not be described in detail here.
[0099] The embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to perform the steps as in the embodiment.
[0100] In the embodiment of the present application, the computer program executed by the processor can also execute other machine readable instructions to perform the methods as in the embodiment, for the specific method steps and principles executed, refer to the description of the embodiment, which will not be described in detail here.
[0101] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented by other ways. The device embodiments described above are only schematic, for example, the division of the modules is only a logical function division, and there can be another division way in actual implementation, for example, a plurality of modules or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the shown or discussed mutual elements can be indirect coupling or communication connection through some communication interfaces, devices or modules, which can be electrical, mechanical or other forms.
[0102] The modules described as separate components can or can not be physically separated, and the components shown as modules can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.
[0103] In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit.
[0104] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a nonvolatile computer readable storage medium executable by a processor. Based on this understanding, the technical solutions of the present application essentially or the parts that contribute to the prior art or parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a ROM, a RAM, a magnetic disk or an optical disk, and various media that can store program codes.
[0105] The above merely describes the specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.
Claims
1. A test system, characterized by, The test system comprises: a detection module; the detection module comprises: a pressure adjusting mechanism; a movable platform connected with the pressure adjusting mechanism, configured to apply pressure or remove pressure on a first surface of a battery based on driving of the pressure adjusting mechanism; a fixed platform configured to apply pressure on a second surface of the battery; the first surface is different from the second surface; surfaces of the movable platform and the fixed platform are each provided with a plurality of pressure sensors configured to collect pressure of the first surface and / or the second surface when contacting the battery, to obtain pressure detection data.
2. The test system of claim 1, wherein, The test system further comprises: an environment simulation box for placing the detection module; the environment simulation box is provided with an environment adjusting submodule configured to adjust an environment parameter in the environment simulation box, so that the detection module performs detection operation under different environment parameters; the environment parameter comprises at least one of the following: temperature, humidity, air pressure.
3. An assessment method characterized by, The method comprises: obtaining detection data of a target battery; the detection data at least comprises pressure detection data detected by the test system according to claim 1 or claim 2; transmitting the detection data to a pre-trained performance evaluation model to obtain an evaluation result output by the performance evaluation model; the evaluation result is used to indicate the swelling force characteristic of the battery.
4. The method of claim 3, wherein, The test system comprises: an environment simulation box; the detection data further comprises an environment parameter and a mapping relationship between the environment parameter and the pressure detection data; the performance evaluation model is trained in the following way: a plurality of sets of training data are obtained in advance; each set of training data comprises pressure detection data of a battery under different environment parameters; 5. The method of claim 4, wherein, a performance evaluation model is trained based on the plurality of sets of training data. Training the performance evaluation model based on the plurality of sets of training data comprises: preprocessing the training data to obtain target data; based on the target data, driving an initial model to dynamically adjust its model parameters by using a preset algorithm to obtain a target model; the preset algorithm is used to reduce the prediction error of the initial model; 6. The method of claim 5, wherein, if the target model satisfies the preset evaluation accuracy by ten-fold cross-validation method, the target model is determined as the final performance evaluation model. The preset algorithm comprises: least square method or back propagation algorithm; the initial model comprises:
7. The method of claim 3, wherein, multivariate linear regression model, support vector machine model or neural network model. The method further comprises: obtaining specification parameters of a target battery to be detected; determining a driving signal matched with the specification parameters; 8. An evaluation device, characterized by sending the driving signal to the pressure adjusting mechanism, so that the pressure adjusting mechanism drives the movable platform to apply pressure matched with the target battery. The device comprises: an acquisition module configured to obtain detection data of a target battery; the detection data at least comprises pressure detection data detected by the test system according to claim 1 or claim 2; 9. An electronic device, comprising: an evaluation module configured to transmit the detection data to a pre-trained performance evaluation model to obtain an evaluation result output by the performance evaluation model; the evaluation result is used to indicate the swelling force characteristic of the battery. The test system comprises: A processor, a storage medium storing machine readable instructions executable by the processor, and a bus for communication between the processor and the storage medium when the electronic device is running, the processor executing the machine readable instructions to perform the steps of the evaluation method of any one of claims 3 to 7.
10. A computer-readable storage medium, characterized in that, A computer program stored on the computer readable storage medium, the computer program when executed by a processor performing the steps of the evaluation method of any one of claims 3 to 7.