Short circuit detection method and system based on electrochemical impedance detection and computer equipment

Abstract

The embodiment of the invention provides a short circuit detection method and system based on electrochemical impedance detection and computer equipment, and belongs to the technical field of electrochemical detection. The method comprises the following steps: receiving test steps and impedance parameters sent by an upper computer, and obtaining a plurality of test groups; performing electrochemical impedance spectroscopy detection on all the test objects based on the test steps to obtain a Nyquist curve; performing fitting analysis on all the Nyquist curves to obtain a fitted curve, and performing similarity analysis on all the Nyquist curves according to the fitted curve to obtain a similarity value; when the similarity value is smaller than a preset threshold value, determining a target Nyquist curve corresponding to the similarity value, and performing outlier analysis on the target Nyquist curve according to the impedance parameter to obtain an outlier analysis value; and when the outlier analysis value is greater than or equal to the parameter outlier threshold value, determining that the target test object corresponding to the target Nyquist curve is short-circuited. According to the embodiment of the invention, the detection of the short-circuit condition is realized, and the detection efficiency and reliability are improved.

Description

Technical Field

[0001] The present application relates to the field of electrochemical detection technology, and in particular to a short circuit detection method, system, computer equipment and storage medium based on electrochemical impedance detection. Background Art

[0002] With the development of science and technology, batteries are gradually being used in many technical fields, so battery performance testing has become particularly important. Current battery testing methods mainly include open circuit voltage detection method and DC internal resistance test method. The open circuit voltage detection method disconnects the battery and then measures the open circuit voltage of the battery. Based on the measurement results, it evaluates whether the open circuit voltage of the battery is within the normal range to determine the battery's status and performance. The DC internal resistance test method measures the internal resistance of the battery by applying a DC current. During the test, a small DC current is applied between the positive and negative poles of the battery, and the corresponding voltage drop is measured. The battery's internal resistance data is used to evaluate the battery's status.

[0003] However, the open circuit voltage detection method and the DC internal resistance test method cannot directly detect the short circuit problem inside the battery, which leads to a blind spot when detecting battery performance. The detection of internal short circuits also requires additional, specific, and high-cost detection equipment, which not only increases production costs, but may also lead to the complexity and inefficiency of the detection process, thereby affecting the efficiency and reliability of the entire battery production and quality control process. Summary of the invention

[0004] The main purpose of the embodiments of the present application is to propose a short circuit detection method, system, computer equipment and storage medium based on electrochemical impedance detection, so as to realize the detection of short circuit conditions and improve the detection efficiency and reliability.

[0005] To achieve the above-mentioned purpose, a first aspect of an embodiment of the present application proposes a short circuit detection method based on electrochemical impedance spectroscopy, the method comprising: Receive the test steps and impedance parameters sent by the host computer, and obtain multiple test groups, wherein each of the test groups includes multiple test objects, and the test steps include parameter outlier thresholds; Based on the test step, electrochemical impedance spectroscopy is performed on all test objects in the test group to obtain a Nyquist curve corresponding to the test object; Performing fitting analysis on all the Nyquist curves to obtain fitting curves, and performing similarity analysis on all the Nyquist curves according to the fitting curves to obtain similarity values; When the similarity value is less than a preset threshold, determining a target Nyquist curve corresponding to the similarity value, and performing an outlier analysis on the target Nyquist curve according to the impedance parameter to obtain an outlier analysis value; When the outlier analysis value is greater than or equal to the parameter outlier threshold, it is determined that the target test object corresponding to the target Nyquist curve is short-circuited.

[0006] In some embodiments, the test step includes a first step, a second step and a third step, wherein the operating frequencies of the first step, the second step and the third step are increased in sequence; performing electrochemical impedance spectroscopy detection on all test objects in the test group based on the test step to obtain a Nyquist curve corresponding to the test object includes: Sending the first process step to a lower computer, so that the lower computer performs solution diffusion on the test object based on the first process step to obtain a diffusion coefficient; Sending the second process step to a subordinate computer, so that the subordinate computer performs a charge transfer operation on the test object based on the second process step to obtain a charge transfer rate; Sending the third step to a lower computer, so that the lower computer performs a double-layer generation operation on the test object based on the third step to form a solid electrolyte interface film on the surface of the test object to obtain high-frequency parameters; The diffusion coefficient, the charge transfer rate and the high-frequency parameter sent by the lower computer are received to generate a Nyquist curve corresponding to the test object through the diffusion coefficient, the charge transfer rate and the high-frequency parameter.

[0007] In some embodiments, performing fitting analysis on all the Nyquist curves to obtain a fitting curve includes: For each of the Nyquist curves, data analysis is performed on the Nyquist curve to obtain curve data; Inputting the curve data into a preset fitting model, so that the fitting model performs feature analysis on the Nyquist curve based on the curve data and outputs fitting features; Curve fitting is performed on all the fitting features and all the Nyquist curves using a preset fitting algorithm to obtain a fitting curve.

[0008] In some embodiments, performing similarity analysis on all the Nyquist curves according to the fitting curve to obtain a similarity value includes: For each of the Nyquist curves, feature extraction is performed on the Nyquist curve to obtain curve features; Calculating the similarity between the curve feature and the fitting curve based on a preset Euclidean distance to obtain a feature distance value; A similarity matrix is ​​constructed according to the characteristic distance values, and cluster analysis is performed on the similarity matrix according to a preset clustering algorithm to obtain similarity values.

[0009] In some embodiments, the impedance parameters include a target ohmic impedance value, a target SEI film impedance value, and a target charge transfer impedance value; performing an outlier analysis on the target Nyquist curve according to the impedance parameters to obtain an outlier analysis value includes: In response to the calculation instruction of the lower computer, the target Nyquist curve is analyzed to obtain a test ohmic impedance value, a test SEI film impedance value and a test charge transfer impedance value; Comparing the target ohmic impedance value with the test ohmic impedance value to obtain a first deviation value; Comparing the target SEI film impedance value with the test SEI film impedance value to obtain a second deviation value; Comparing the target charge transfer impedance value with the test charge transfer impedance value to obtain a third deviation value; An outlier analysis value is obtained according to the first deviation value, the second deviation value, and the third deviation value.

[0010] In some embodiments, before performing electrochemical impedance spectroscopy detection on all test objects in the test group based on the test step to obtain a Nyquist curve corresponding to the test object, the method further includes: Recording the channel information of the channel where the test object is located; After determining that the target test object corresponding to the target Nyquist curve is short-circuited, the method further includes: Determine the target channel information corresponding to the target test object, and determine the target channel where the target test object is located according to the target channel information; A protection instruction is sent to the target channel to stop the target channel from working.

[0011] In some embodiments, after determining the target channel information corresponding to the target test object and determining the target channel where the target test object is located according to the target channel information, the method further includes: The target channel is marked, and production information of the marked target channel is recorded.

[0012] A second aspect of an embodiment of the present application provides a short circuit detection system based on electrochemical impedance detection, the system comprising: A parameter receiving module, used for receiving the test steps and impedance parameters sent by the host computer, and obtaining a plurality of test groups, wherein each of the test groups includes a plurality of test objects, and the test steps include a parameter outlier threshold; An electrochemical impedance spectroscopy detection module, used to perform electrochemical impedance spectroscopy detection on all test objects in the test group based on the test step to obtain a Nyquist curve corresponding to the test object; A similarity calculation module, used for performing fitting analysis on all the Nyquist curves to obtain fitting curves, and performing similarity analysis on all the Nyquist curves according to the fitting curves to obtain similarity values; an outlier analysis module, configured to determine a target Nyquist curve corresponding to the similarity value when the similarity value is less than a preset threshold, and perform an outlier analysis on the target Nyquist curve according to the impedance parameter to obtain an outlier analysis value; The short circuit determination module is used to determine that the target test object corresponding to the target Nyquist curve is short-circuited when the outlier analysis value is greater than or equal to the parameter outlier threshold.

[0013] A third aspect of an embodiment of the present application proposes a computer device, comprising a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor is used to execute the short circuit detection method based on electrochemical impedance detection as described in the first aspect.

[0014] The fourth aspect of the embodiments of the present application proposes a storage medium, which is a computer-readable storage medium, and the computer-readable storage medium stores a computer program. When the computer program is executed by a computer, the computer is used to execute the short circuit detection method based on electrochemical impedance detection as described in any one of the embodiments of the first aspect of the present application.

[0015] The short circuit detection method, system, computer equipment and medium based on electrochemical impedance detection proposed in the embodiments of the present application have the following beneficial effects: first, the test steps and impedance parameters sent by the host computer are received, and multiple test groups are obtained, each test group includes multiple test objects, so as to facilitate the subsequent testing of the test objects according to the test steps sent by the host computer, and the impedance parameters can be used as parameters for subsequent impedance comparison, and then electrochemical impedance spectrum detection is performed on all test objects in the test group based on the test steps, so as to realize real-time monitoring of the test objects, timely understand the status and performance changes of the test objects in different steps, and obtain the Nyquist curve corresponding to the test objects, so as to intuitively display the performance changes of the test objects. Since the Nyquist curves corresponding to the normal test objects of the same batch have a certain degree of fit under the same environment, the embodiment of the present application performs fitting analysis on all Nyquist curves to obtain a fitting curve, so that it is possible to judge whether the test object has an abnormality through the fitting curve, and to achieve an evaluation of the overall performance of the test object. Based on the fitting curve, a similarity analysis is performed on all Nyquist curves to obtain a similarity value. By analyzing the similarity value, it is possible to judge whether the test object has similar electrochemical characteristics, and to promptly discover and handle test objects with abnormalities. When the similarity value is less than a preset threshold, it indicates that the difference between the Nyquist curve of the test object and the fitting curve is large. , it is necessary to determine the target Nyquist curve corresponding to the similarity value, realize the preliminary screening of abnormal test objects, and perform outlier analysis on the target Nyquist curve according to the impedance parameter to realize in-depth analysis of the target Nyquist curve. The impedance parameter sent by the host computer is used to determine whether the target Nyquist curve has outliers, and the outlier analysis value is obtained to realize accurate analysis of the target Nyquist curve and improve the detection accuracy. When the outlier analysis value is greater than or equal to the parameter outlier threshold, it means that the target Nyquist curve has obvious deviation. At this time, it is determined that the target test object corresponding to the target Nyquist curve is short-circuited, thereby realizing accurate detection of short-circuit conditions and improving detection efficiency and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flowchart of a specific method of the short circuit detection method based on electrochemical impedance detection provided in an embodiment of the present application; Figure 2 is a specific flow chart of step S102 provided in an embodiment of the present application; Figure 3 is a specific flow chart for fitting and analyzing all Nyquist curves provided in an embodiment of the present application; Figure 4 It is a specific flow chart of performing similarity analysis on all Nyquist curves according to the fitting curve provided in the embodiment of the present application; Figure 5It is a specific flow chart of performing outlier analysis on a target Nyquist curve according to impedance parameters provided in an embodiment of the present application; Figure 6 is a specific flow chart of a short circuit detection method based on electrochemical impedance detection provided by another embodiment of the present application; Figure 7 is a specific flow chart of a short circuit detection method based on electrochemical impedance detection provided by another embodiment of the present application; Figure 8 is a specific flow chart of a short circuit detection method based on electrochemical impedance detection provided by another embodiment of the present application; Fig. 9 Schematic diagram of the structure of a short circuit detection system based on electrochemical impedance spectroscopy provided in an embodiment of the present application; Fig.10 is a schematic diagram of the Nyquist curve provided by the example of this application; Fig.11 It is a schematic diagram of the hardware structure of the computer device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0018] It should be noted that, although the functional modules are divided in the system schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the system or the order in the flowchart. The terms "first", "second", etc. in the specification, claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0020] The short circuit detection method based on electrochemical impedance detection provided in the embodiment of the present application can be applied to the terminal, can also be applied to the server side, and can also be software running in the terminal or the server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer or a smart watch, etc.; the server side can be configured as an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN) and big data and artificial intelligence platforms; the software can be an application that implements the above method, etc., but is not limited to the above forms.

[0021] Embodiments of the present application can be used in numerous general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer computer devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0022] With the development of science and technology, batteries are gradually being used in many technical fields, so battery performance testing has become particularly important. Current battery testing methods mainly include open circuit voltage detection method and DC internal resistance test method. The open circuit voltage detection method disconnects the battery and then measures the open circuit voltage of the battery. Based on the measurement results, it evaluates whether the open circuit voltage of the battery is within the normal range to determine the battery's status and performance. The DC internal resistance test method measures the internal resistance of the battery by applying a DC current. During the test, a small DC current is applied between the positive and negative poles of the battery, and the corresponding voltage drop is measured. The battery's internal resistance data is used to evaluate the battery's status.

[0023] However, the open circuit voltage detection method and the DC internal resistance test method cannot directly detect the short circuit problem inside the battery, which leads to a blind spot when detecting battery performance. The detection of internal short circuits also requires additional, specific, and high-cost detection equipment, which not only increases production costs, but may also lead to the complexity and inefficiency of the detection process, thereby affecting the efficiency and reliability of the entire battery production and quality control process.

[0024] In order to solve the above problems, the present embodiment provides a short circuit detection method, system, computer equipment and medium based on electrochemical impedance detection. First, the test steps and impedance parameters sent by the host computer are received, and multiple test groups are obtained. Each test group includes multiple test objects, which is convenient for subsequent testing of the test objects according to the test steps sent by the host computer, and the impedance parameters can be used as parameters for subsequent impedance comparison. Then, based on the test steps, electrochemical impedance spectrum detection is performed on all test objects in the test group to achieve real-time monitoring of the test objects, and the state and performance changes of the test objects under different steps can be understood in time, and the Nyquist curve corresponding to the test object can be obtained, so that the performance changes of the test objects can be intuitively displayed. Since the Nyquist curves corresponding to the normal test objects of the same batch have a certain degree of fit under the same environment, the embodiment of the present application performs fitting analysis on all Nyquist curves to obtain a fitting curve, so that it is possible to judge whether the test object has an abnormality through the fitting curve, and to achieve an evaluation of the overall performance of the test object. Based on the fitting curve, a similarity analysis is performed on all Nyquist curves to obtain a similarity value. By analyzing the similarity value, it is possible to judge whether the test object has similar electrochemical characteristics, and to promptly discover and handle test objects with abnormalities. When the similarity value is less than a preset threshold, it indicates that the difference between the Nyquist curve of the test object and the fitting curve is large. , it is necessary to determine the target Nyquist curve corresponding to the similarity value, realize the preliminary screening of abnormal test objects, and perform outlier analysis on the target Nyquist curve according to the impedance parameter to realize in-depth analysis of the target Nyquist curve. The impedance parameter sent by the host computer is used to determine whether the target Nyquist curve has outliers, and the outlier analysis value is obtained to realize accurate analysis of the target Nyquist curve and improve the detection accuracy. When the outlier analysis value is greater than or equal to the parameter outlier threshold, it means that the target Nyquist curve has obvious deviation. At this time, it is determined that the target test object corresponding to the target Nyquist curve is short-circuited, thereby realizing accurate detection of short-circuit conditions and improving detection efficiency and reliability.

[0025] Please refer to Figure 1 , Figure 1 1 is a flowchart of a specific method of a short circuit detection method based on electrochemical impedance spectroscopy provided in an embodiment of the present application. In some embodiments, the method includes but is not limited to steps S101 to S105.

[0026] Step S101, receiving the test steps and impedance parameters sent by the host computer, and obtaining multiple test groups, wherein each test group includes multiple test objects, and the test steps include parameter outlier thresholds.

[0027] It is understandable that the test object in this embodiment can be an electrochemical interface, a battery, an electrochemical energy storage system, a biosensor, an electrochemical catalyst, etc., and this embodiment does not make specific restrictions. Specifically, the embodiment of the present application is described by taking the test object as a battery as an example, wherein the test object can be a lithium-ion battery, a lead-acid battery, a fuel cell, a nickel-hydrogen battery, etc., and this embodiment does not make specific restrictions.

[0028] In step S101 of some embodiments, the test steps and impedance parameters sent by the host computer are received to facilitate subsequent electrochemical testing based on the test steps sent by the host computer, and provide data reference for subsequent testing through impedance parameters, thereby improving the accuracy and repeatability of the test results, and obtaining multiple test groups to facilitate subsequent testing of the test groups based on the test steps and impedance parameters.

[0029] It is understandable that the host computer can adjust the test steps and parameters as needed, making the test more flexible and able to quickly adapt to different test requirements and condition changes.

[0030] Step S102 : performing electrochemical impedance spectroscopy detection on all test objects in the test group based on the test process to obtain a Nyquist curve corresponding to the test object.

[0031] It is understandable that electrochemical impedance spectroscopy (EIS) can be used to analyze the surface properties of materials, the stability of electrolyte systems, and the energy efficiency of electrical equipment, etc. In this embodiment, it is used to analyze the performance parameters of the battery, that is, when the electrochemical cell is in a balanced state (open circuit state) or under a certain stable DC polarization condition, a small AC excitation signal is applied according to the sine law to measure the change relationship between the electrochemical AC impedance and the frequency. The frequency can also be fixed to measure the change of the AC impedance of the electrochemical cell over time. Frequency domain impedance analysis methods are more commonly used in basic research on lithium-ion batteries. Since EIS records the impedance of electrochemical cells at different response frequencies, and the general measurement covers a wide frequency range, it can analyze different electrode processes with different reaction time constants.

[0032] In step S102 of some embodiments, electrochemical impedance spectroscopy is performed on all test objects in the test group based on the test step. By detecting the test objects at different frequencies, the electrochemical characteristics of the test objects at different frequencies can be fully reflected, and the Nyquist curve corresponding to the test object can be obtained, which is convenient for subsequent identification of the charge transfer impedance, diffusion process and other dynamic behaviors of the test object through the Nyquist curve, thereby providing in-depth performance analysis and fault diagnosis, and improving the use efficiency and safety of the test objects.

[0033] In this embodiment, by performing electrochemical impedance spectroscopy on the test object, detailed information on the internal characteristics of the battery can be obtained. By measuring the impedance spectrum of the battery, the electrochemical reaction kinetics, ion transport process, interface characteristics, surface state of the electrode material, etc. of the battery can be understood. By analyzing the impedance spectrum, important parameters such as the internal resistance of the battery, the electrochemical reaction rate of the electrode, the concentration of the electrolyte, and the electrode interface characteristics can be obtained. This is convenient for subsequent judgment of the performance level, capacity attenuation, and charge and discharge efficiency of the battery.

[0034] Step S103, performing fitting analysis on all Nyquist curves to obtain fitting curves, and performing similarity analysis on all Nyquist curves according to the fitting curves to obtain similarity values.

[0035] In step S103 of some embodiments, a fitting analysis is performed on all Nyquist curves to minimize the deviation between the fitting curve and the actual data, ensuring that the fitting curve fits the data as closely as possible to obtain a fitting curve. Similarity analysis is performed on all Nyquist curves based on the fitting curve to calculate the similarity between the Nyquist curve and the fitting curve. This can more intuitively display the relationship between the two curves and obtain a similarity value, which is convenient for subsequent judgment of whether the Nyquist curve is offset.

[0036] Step S104: when the similarity value is less than a preset threshold, a target Nyquist curve corresponding to the similarity value is determined, and an outlier analysis is performed on the target Nyquist curve according to the impedance parameter to obtain an outlier analysis value.

[0037] In step S104 of some embodiments, when the similarity value is less than a preset threshold value, it indicates that the Nyquist curve is significantly different from the fitting curve, and it is preliminarily determined that the Nyquist curve is offset. At this time, a target Nyquist curve corresponding to the similarity value is determined, and an outlier analysis is performed on the target Nyquist curve according to the impedance parameters. The impedance parameters are used to accurately detect the offset degree of the target Nyquist curve, obtain the outlier analysis value, and improve the detection accuracy of the test object.

[0038] It should be noted that the preset threshold in the embodiment of the present application can be obtained according to the user's needs or historical test parameters, and the embodiment of the present application does not impose any specific limitations.

[0039] It is understandable that under the same environment, the curves generated by the normal test objects of the same batch have a certain degree of fit, and the fitting of the curve can be used to determine whether the battery has an abnormality, thereby achieving preliminary screening of abnormal Nyquist curves.

[0040] Step S105 , when the outlier analysis value is greater than or equal to the parameter outlier threshold, it is determined that the target test object corresponding to the target Nyquist curve is short-circuited.

[0041] In step S105 of some embodiments, when the outlier analysis value is greater than or equal to the parameter outlier threshold, it indicates that the target Nyquist curve deviates greatly from the fitting curve, and it can be determined that the target test object corresponding to the target Nyquist curve is short-circuited, thereby enabling screening of test objects with short circuits, preventing short-circuited target test objects from flowing into subsequent production lines, and reducing waste of resources.

[0042] It should be noted that the parameter outlier threshold in the embodiment of the present application is obtained by being sent by the host computer, wherein the parameter outlier threshold may be an outlier percentage, an outlier value, etc., and the embodiment of the present application does not impose any specific limitation.

[0043] It is worth noting that, taking the test object as a battery, for example, an internal short circuit in the battery causes the internal resistance of the battery to be smaller than that of a normal battery. The curve displayed on the Nyquist curve of the internal short circuit battery will have an obvious left shift compared to the Nyquist curve of the normal battery, and the resistance value will be less affected by the frequency, and the curve will be similar to a curve perpendicular to the real axis. The embodiment of the present application performs a secondary judgment on the Nyquist curve of the battery, so as to accurately determine whether the Nyquist curve is outlier, and further determine whether the battery has an internal short circuit problem.

[0044] Please refer to Figure 2 , Figure 2 1 is a specific flow chart of step S102 provided in an embodiment of the present application. In some embodiments, step S102 specifically includes but is not limited to steps S201 to S204.

[0045] It should be noted that the test steps include a first step, a second step and a third step, wherein the operating frequencies of the first step, the second step and the third step increase sequentially, that is, the operating frequency of the first step in the embodiment of the present application is low frequency, the operating frequency of the second step is medium frequency, and the operating frequency of the third step is high frequency.

[0046] Step S201 : sending the first process step to the lower computer, so that the lower computer performs solution diffusion on the test object based on the first process step to obtain the diffusion coefficient.

[0047] It can be understood that the lower computer in the embodiment of the present application is an EIS lower computer.

[0048] In step S201 of some embodiments, the first process step is sent to the lower computer so that the lower computer performs solution diffusion on the test object based on the first process step. In a low-frequency working scenario, the diffusion rate of ions in the solution is slow, and the accumulation or consumption of ions on the electrode surface of the test object will limit the reaction rate. This process is called a diffusion process. During this process, the lower computer records the parameter changes of the diffusion process and obtains the diffusion coefficient. By understanding the accumulation or consumption rate of ions on the electrode surface, the electrode material and structure can be optimized, the ion diffusion efficiency can be improved, and it is helpful to predict the life of the test object.

[0049] Step S202: sending the second process step to the lower computer, so that the lower computer performs a charge transfer operation on the test object based on the second process step to obtain a charge transfer rate.

[0050] In step S202 of some embodiments, the second process step is sent to the lower computer so that the lower computer performs a charge transfer operation on the test object based on the second process step. In the medium frequency working scenario, the diffusion speed of particles in the solution is fast enough, but the charge transfer speed may become the main factor limiting the battery reaction rate. This process involves the transmission process of potential difference, electrons or ions. During this process, the lower computer records the parameter changes of the process and obtains the charge transfer rate, thereby realizing the recording of the charge and discharge efficiency of the test object.

[0051] Step S203, sending the third process step to the lower computer, so that the lower computer performs a double-layer generation operation on the test object based on the third process step to form a solid electrolyte interface film on the surface of the test object to obtain high-frequency parameters.

[0052] In step S203 of some embodiments, the third process step is sent to the lower computer so that the lower computer performs a double-layer generation operation on the test object based on the third process step. In a high-frequency working scenario, the ion diffusion rate and charge transfer rate of the solution are very fast, but the electrochemical double layer becomes the main factor limiting the reaction rate. This process involves the charge distribution and capacitance effect between the electrode surface and the solution, that is, the formation process of the SEI (Solid Electrolyte Interphase) film. During this process, the lower computer records the parameter changes of the process, obtains high-frequency parameters, and realizes the recording of the capacitance performance of the test object, which is convenient for subsequent optimization of the interface between the electrode and the electrolyte.

[0053] Step S204, receiving the diffusion coefficient, charge transfer rate and high-frequency parameters sent by the lower computer, so as to generate a Nyquist curve corresponding to the test object through the diffusion coefficient, charge transfer rate and high-frequency parameters.

[0054] In step S204 of some embodiments, the diffusion coefficient, charge transfer rate and high-frequency parameters sent by the lower computer are received, so that the performance changes of the test object are monitored in real time through the diffusion coefficient, charge transfer rate and high-frequency parameters, and the parameter changes of the test object at different frequencies are collected, so as to generate a Nyquist curve corresponding to the test object through the diffusion coefficient, charge transfer rate and high-frequency parameters. Specifically, the embodiment of the present application analyzes the real and imaginary values ​​of the test object at different frequencies collected to draw the Nyquist curve of the battery, so as to fully reflect the electrochemical characteristics of the test object at different frequencies, and can identify the charge transfer impedance, diffusion process and other dynamic behaviors of the test object, so as to provide in-depth performance analysis and fault diagnosis, and improve the use efficiency and safety of the test object.

[0055] It is understandable that by analyzing the diffusion process, charge transfer process and electrochemical double layer process of the test object solution, we can have a deeper understanding of the electrochemical behavior of the battery at different frequencies, including the accumulation or consumption of ions on the electrode surface, the charge transfer rate and the formation and change of the electrochemical double layer. We can achieve an accurate evaluation of the performance of the test object, and by detecting these processes in real time, we can understand the status of the test object in a timely manner.

[0056] Please refer to Figure 3 , Figure 3 It is a specific flow chart of fitting and analyzing all Nyquist curves provided by the embodiment of the present application. The method includes but is not limited to steps S301 to S303.

[0057] Step S301: for each Nyquist curve, data analysis is performed on the Nyquist curve to obtain curve data.

[0058] Step S302: input the curve data into a preset fitting model, so that the fitting model performs feature analysis on the Nyquist curve based on the curve data and outputs fitting features.

[0059] Step S303: performing curve fitting on all fitting features and all Nyquist curves by using a preset fitting algorithm to obtain a fitting curve.

[0060] In steps S301 to S303 of some embodiments, in the process of fitting and analyzing all Nyquist curves, for each Nyquist curve, data preprocessing is performed on the Nyquist curve, the data is cleaned and normalized, and the outliers in the Nyquist curve are removed to obtain curve data, improve data quality, reduce the impact of noise on the fitting results, and improve the accuracy of fitting. The curve data is then input into a preset fitting model so that the fitting model performs feature analysis on the Nyquist curve based on the curve data, analyzes the linear characteristics, nonlinear characteristics or periodic characteristics of the Nyquist curve, and outputs fitting features, thereby improving the fitting accuracy. Afterwards, curve fitting is performed on all fitting features and all Nyquist curves through a preset fitting algorithm to obtain a fitting curve, so that the deviation between the fitting curve and the actual data is minimized, ensuring that the fitting curve fits the data as closely as possible.

[0061] It is worth noting that in the process of data analysis of the Nyquist curve, if the data range varies greatly, the curve data can be standardized or normalized to improve the data quality and ensure that different features are on the same scale.

[0062] It can be understood that the fitting model in the embodiments of the present application can be a linear regression model, a quadratic curve fitting model, an exponential function model, etc., and the fitting algorithm can be a least squares method, maximum likelihood estimation, etc., and the embodiments of the present application do not make specific limitations.

[0063] Please refer to Figure 4 , Figure 4 It is a specific flow chart of performing similarity analysis on all Nyquist curves according to the fitting curve provided in the embodiment of the present application. The method includes but is not limited to steps S401 to S403.

[0064] Step S401: for each Nyquist curve, extract the features of the Nyquist curve to obtain the curve features.

[0065] Step S402: Calculate the similarity between the curve feature and the fitting curve based on the preset Euclidean distance to obtain a feature distance value.

[0066] Step S403: construct a similarity matrix according to the feature distance values, and perform cluster analysis on the similarity matrix according to a preset clustering algorithm to obtain similarity values.

[0067] In steps S401 to S403 of some embodiments, in the process of performing similarity analysis on all Nyquist curves according to the fitting curve, for each Nyquist curve, feature extraction is performed on the Nyquist curve, and key feature points are extracted from the Nyquist curve of each object to be measured. These feature points can be extreme points, inflection points of the curve, or impedance values ​​corresponding to a specific frequency, to obtain curve features, thereby achieving accurate extraction of the features of the Nyquist curve, extracting key information points that can represent the characteristics of the object to be measured from the Nyquist curve, and further achieving the capture of the electrochemical behavior characteristics of the object to be measured, and then calculating the similarity of the curve features and the fitting curve based on a preset Euclidean distance. Specifically, the distance between the feature points in the curve features in the multidimensional space is calculated by the Euclidean distance to calculate the distance between the feature points and the fitting curve. The distance between the Nyquist curve and the fitting curve is obtained, so that the distance between the Nyquist curve and the fitting curve can be quantified by mathematical methods. After that, a similarity matrix is ​​constructed according to the characteristic distance value to store the characteristic distance values ​​of all Nyquist curves and the fitting curves. Specifically, according to the result of the characteristic distance value calculation, a matrix is ​​created, in which rows and columns represent different objects to be tested, and each element in the matrix represents the characteristic distance value of the corresponding Nyquist curve and the fitting curve. The similarity matrix is ​​clustered according to a preset clustering algorithm. Specifically, an initial cluster center is randomly selected, and then data points are iteratively assigned to the nearest cluster center, and the cluster center is updated to obtain a similarity value, so as to realize the calculation of the similarity between the Nyquist curve and the fitting curve, which can more intuitively show the relationship between the two curves and improve the efficiency of production and screening.

[0068] It can be understood that the clustering algorithm in the embodiment of the present application can be a k-means clustering algorithm, a hierarchical clustering algorithm, etc., and the embodiment of the present application does not make specific limitations.

[0069] It should be noted that the embodiment of the present application can also calculate the similarity value between the two curves by comparing the changing trends of the real part, imaginary part, impedance modulus, phase angle and other parameters of the Nyquist curve of different test objects and the fitting curve, and the embodiment of the present application does not make specific restrictions.

[0070] Please refer to Figure 5 , Figure 5 This is a specific flow chart of performing outlier analysis on a target Nyquist curve according to impedance parameters provided by an embodiment of the present application. The method includes but is not limited to steps S501 to S505.

[0071] It should be noted that the impedance parameters include a target ohmic impedance value, a target SEI (Solid Electrolyte Interphase) film impedance value, and a target charge transfer impedance value.

[0072] Step S501, in response to the calculation instruction of the lower computer, a curve analysis is performed on the target Nyquist curve to obtain a test ohmic impedance value, a test SEI film impedance value and a test charge transfer impedance value.

[0073] Step S502: Compare the target ohmic impedance value with the test ohmic impedance value to obtain a first deviation value.

[0074] Step S503: Compare the target SEI film impedance value with the test SEI film impedance value to obtain a second deviation value.

[0075] Step S504: Compare the target charge transfer impedance value with the test charge transfer impedance value to obtain a third deviation value.

[0076] Step S505 , obtaining an outlier analysis value according to the first deviation value, the second deviation value, and the third deviation value.

[0077] In steps S501 to S505 of some embodiments, in the process of performing outlier analysis on the target Nyquist curve according to the impedance parameters, in response to the calculation instruction of the lower computer, the target Nyquist curve is subjected to curve analysis. Specifically, at a specific frequency, the Nyquist curve and the real axis of the coordinate axis have an intersection. At this time, the imaginary part of the impedance of the test object is 0, which is expressed as the ohmic impedance value of the test object. If the tested Nyquist curve does not have an intersection with the real axis, the frequency of the test object can be appropriately increased to determine the ohmic impedance value of the test object. The Nyquist curve obtained by the test is generally two semicircles plus an ascending curve. On the target Nyquist curve, the intersection of the target Nyquist curve and the real axis is the ohmic impedance value of the test object. The real part value of the right endpoint of the first semicircle minus the test ohmic impedance value of the test object (the intersection of the target Nyquist curve and the real axis) is the test SEI film impedance value of the test object. The real part value of the right endpoint of the second semicircle minus the left endpoint The real part value is the test charge transfer impedance value of the test object, so as to achieve accurate determination of the impedance value of the test object. Afterwards, the test ohmic impedance value, the test SEI film impedance value and the test charge transfer impedance value are compared with the target ohmic impedance value, the target SEI film impedance value and the target charge transfer impedance value, that is, the target ohmic impedance value is compared with the test ohmic impedance value to obtain a first deviation value, the target SEI film impedance value is compared with the test SEI film impedance value to obtain a second deviation value, and the target charge transfer impedance value is compared with the test charge transfer impedance value to obtain a third deviation value, so as to obtain the degree of deviation between different impedance values ​​of the test object and the set impedance value. Finally, the outlier analysis value is obtained according to the first deviation value, the second deviation value and the third deviation value, so as to determine whether the target Nyquist curve is offset, to achieve accurate detection of the degree of offset of the target Nyquist curve, and further achieve accurate screening of test objects with short circuits.

[0078] It is worth noting that, taking the battery as an example, for batteries with internal short circuit, the internal resistance of the battery is reduced due to the slight internal short circuit, and the performance on the Nyquist curve will be manifested as an obvious left shift compared with the normal curve. The software can be used to test the entire tray of batteries and analyze the battery curves corresponding to each channel to preliminarily screen whether the battery has an internal short circuit. The correlation between the Nyquist curve of the battery with internal short circuit and the frequency is not very high, which causes the Nyquist curve of the battery to be approximately a straight line perpendicular to the real axis, and there is an obvious outlier phenomenon compared with the Nyquist curve of the normal battery.

[0079] In some embodiments, the calculation instructions of the lower computer can be triggered according to the number of frequency points collected by the lower computer, that is, the frequency of data collection on the test object. Specifically, when the number of frequency points collected by the lower computer meets the number of sampling points issued, the median starts to calculate the test ohmic impedance value, test SEI film impedance value and test charge transfer impedance value corresponding to each test object.

[0080] Please refer to Figure 6 , Figure 6 It is a specific flow chart of a short circuit detection method based on electrochemical impedance detection provided by another embodiment of the present application. In some embodiments, it includes but is not limited to step S601.

[0081] It should be noted that step S601 occurs before performing electrochemical impedance spectroscopy detection on all test objects in the test group based on the test process to obtain the Nyquist curve corresponding to the test object.

[0082] Step S601, recording the channel information of the channel where the test object is located.

[0083] In step S601 of some embodiments, before performing electrochemical impedance spectroscopy detection on the test object, the embodiments of the present application will place the test object in different channels for testing, that is, each test object corresponds to a channel, and record the channel information of the channel where the test object is located, so as to achieve independent testing of the test object, avoid mutual interference between multiple test objects, and ensure that the test signal of each object is clear and accurate, thereby improving the reliability of the test data, further improving the test accuracy, and avoiding repeated testing.

[0084] It should be noted that, since each test object in the embodiment of the present application corresponds to a channel, you can choose to view the Nyquist curve diagram of the test object of a single channel, a specific channel or all channels according to different needs, and the embodiment of the present application does not make specific restrictions.

[0085] Please refer to Figure 7 , Figure 7It is a specific flow chart of a short circuit detection method based on electrochemical impedance detection provided by another embodiment of the present application. The method includes but is not limited to steps S701 to S702.

[0086] It should be noted that step S701 to step S702 occur after it is determined that the target test object corresponding to the target Nyquist curve is short-circuited.

[0087] Step S701, determining target channel information corresponding to a target test object, and determining the target channel where the target test object is located according to the target channel information.

[0088] Step S702: Send a protection instruction to the target channel to stop the target channel from working.

[0089] In steps S701 to S702 of some embodiments, after determining that the target test object corresponding to the target Nyquist curve is short-circuited, the embodiments of the present application will determine the target channel information corresponding to the target test object, and determine the target channel where the target test object is located based on the target channel information, thereby determining the channel where the target test object is located, and then turning on the protection function for the specific target channel, sending a protection instruction to the target channel to stop the target channel from working, that is, stopping the test of the test object, thereby ensuring the screening of short-circuited test objects, preventing short-circuited test objects from flowing into subsequent production lines, and reducing losses.

[0090] It should be noted that while sending a protection instruction to the target channel, the present application will also record the event information of the target channel and upload the event information to the channel recording event to avoid the same problem from occurring later and to achieve timely troubleshooting of abnormal channels.

[0091] Please refer to Figure 8 , Figure 8 It is a specific flow chart of a short circuit detection method based on electrochemical impedance detection provided by another embodiment of the present application. The method includes but is not limited to step S801.

[0092] It should be noted that step S801 occurs after the target channel information corresponding to the target test object is determined, and the target channel where the target test object is located is determined according to the target channel information.

[0093] Step S801, marking a target channel and recording production information of the marked target channel.

[0094] In step S801 of some embodiments, after determining the target channel where the target test object is located, the embodiments of the present application will also mark the target channel to mark the channel where a short circuit occurs, and record the production information of the target channel after the marking process, thereby being able to mark the abnormal channel without affecting the production process, thereby facilitating the subsequent judgment of whether the test object has a short circuit through production information and improving production efficiency.

[0095] See also Fig. 9 The present application also provides a short circuit detection system based on electrochemical impedance detection, which can implement the above-mentioned short circuit detection method based on electrochemical impedance detection. The system includes: The parameter receiving module 901 is used to receive the test steps and impedance parameters sent by the host computer, and obtain multiple test groups, wherein each test group includes multiple test objects, and the test steps include parameter outlier thresholds; An electrochemical impedance spectroscopy detection module 902 is used to perform electrochemical impedance spectroscopy detection on all test objects in the test group based on the test process step to obtain a Nyquist curve corresponding to the test object; A similarity calculation module 903 is used to perform fitting analysis on all Nyquist curves to obtain fitting curves, and perform similarity analysis on all Nyquist curves according to the fitting curves to obtain similarity values; An outlier analysis module 904 is used to determine a target Nyquist curve corresponding to the similarity value when the similarity value is less than a preset threshold value, and perform an outlier analysis on the target Nyquist curve according to the impedance parameter to obtain an outlier analysis value; The short circuit determination module 905 is used to determine that the target test object corresponding to the target Nyquist curve is short-circuited when the outlier analysis value is greater than or equal to the parameter outlier threshold.

[0096] In some embodiments, the short circuit detection system based on electrochemical impedance detection also includes an information recording module and a marking processing module, wherein the information recording module is used to record the channel information of the channel where the test object is located. The marking processing module is used to determine the target channel information corresponding to the target test object, and determine the target channel where the target test object is located according to the target channel information; send a protection instruction to the target channel to stop the target channel from working. The marking processing module is also used to mark the target channel and record the production information of the target channel after the marking process.

[0097] In order to further explain the short circuit detection method, system and computer device based on electrochemical impedance detection provided by this embodiment, a specific example is given below for detailed description.

[0098] Example 1: Example 1 is described by taking a battery as an example of a test object.

[0099] In some embodiments, the short circuit detection method based on electrochemical impedance detection of the embodiment of the present application can be combined with a lithium battery detection device. The current charging and discharging equipment tests different charging and discharging of the battery to realize the detection of the battery. The charging and discharging are controlled by different process templates and are controlled by the upper computer. The embodiment of the present application realizes the detection of the internal short circuit of the battery based on this detection system, wherein the detection system includes an upper computer, a middle computer and a lower computer, and the lower computer includes a charging and discharging lower computer and an EIS lower computer. The upper computer realizes the sending of parameters, protection settings, EIS data display, and battery Nyquist curve display. The middle computer is the control module of the entire system, which controls the charging and discharging lower computer and the EIS lower computer to realize normal operation, realizes the corresponding parameter forwarding and impedance value calculation, protection mark judgment, outlier judgment, internal short circuit judgment mark and uploads it to the upper computer for display. The charging and discharging lower computer realizes the charging and discharging test function of the battery. The EIS lower computer realizes reading the EIS parameters during the EIS step and uploading them to the middle computer. The short circuit detection method of the embodiment of the present application is applied to the middle computer.

[0100] Specifically, the embodiment of the present application realizes the detection of the battery by setting a specific EIS test step, and changes the frequency within the test step to collect the real and imaginary values ​​of the battery at different frequencies to draw the Nyquist curve of the battery. Each battery corresponds to a channel, and each battery has a corresponding Nyquist curve. The Nyquist curves of the batteries of a single channel, a specific channel, and all channels can be viewed according to the selection.

[0101] It can be understood that at a specific frequency, the Nyquist curve intersects the real axis of the coordinate axis. At this time, the imaginary part of the impedance of the battery is 0, which is expressed as the ohmic impedance value of the battery. If the tested Nyquist curve does not intersect with the real axis, the frequency of the tested battery can be appropriately increased to determine the ohmic impedance value of the battery. The Nyquist curve obtained by the test is generally two semicircles plus a rising curve.

[0102] Under the same environment, the Nyquist curves generated by normal batteries in the same batch have a certain degree of fit, and the fit of the Nyquist curve can be used to determine whether the battery is abnormal. In a whole tray of batteries, if the Nyquist curves of some channels are significantly different from those of other normal batteries, it can be further determined whether the battery has an internal short circuit. The outlier parameters designed by the software can be used to determine whether the curves of each channel have outliers to determine the corresponding battery internal short circuit.

[0103] See also Fig.10 , Fig.10 Schematic diagram of the Nyquist curve provided for the example of this application.

[0104] On the curve, the intersection of the curve and the real axis is the ohmic impedance value of the battery, the real value of the right end point of the first semicircle minus the ohmic impedance of the battery (the intersection of the curve and the real axis) is the SEI film impedance (Rf) of the battery, and the real value of the right end point of the second semicircle minus the real value of the left end point is the battery charge transfer impedance (Rct). According to the Nyquist curve, specifically, the above three impedance values ​​are actually calculated as follows: Ohmic impedance: Rs=a; SEI film impedance: Rf=ba; Charge transfer impedance: Rct=c–b.

[0105] For batteries with internal short circuit, the internal resistance of the battery is reduced due to the slight internal short circuit. The performance on the Nyquist curve will be shown as a significant left shift compared to the normal curve. In the software, the battery curve corresponding to each channel can be analyzed according to the test of the entire tray of batteries to preliminarily screen whether the battery has an internal short circuit. The correlation between the Nyquist curve of the battery with internal short circuit and the frequency is not very high, which leads to the Nyquist curve of the battery being similar to a straight line perpendicular to the real axis, and there is a significant outlier phenomenon compared with the Nyquist curve of the normal battery. The outlier detection percentage can be set on the host computer to preliminarily screen outlier channels, and it can also be determined whether the curve is outlier to the left or right, how large the outlier deviation value is, and the size of the Rs, Rf, and Rct values ​​of each curve can be confirmed. By judging the value of the battery's ohmic impedance, it can also be determined whether the battery has an internal short circuit.

[0106] When the EIS process is running, the corresponding Rs, Rf, and Rct can be set on the upper computer to determine whether there are outliers on the Nyquist curve of the battery. The corresponding parameter outlier percentage can be set. When the number of frequency points collected by the lower computer meets the number of sampling points sent, the middle computer starts to calculate the Rs, Rf, and Rct corresponding to each channel, and determines whether there are outlier channels based on the sent parameters. If there are, confirm whether to turn on the protection or marking function. If the protection is turned on, upload the channel protection. At the same time, it is also necessary to upload the channel record event, and the channel will stop channel production. If the marking function is turned on, the impedance value is determined and the process step record event is uploaded. At this time, the process step will not be triggered to stop, and the process can continue without affecting the battery quality. For the channel that has uploaded the outlier record event, the overall battery data can also be used to further confirm whether there is a problem with the battery.

[0107] The embodiments of the present application can obtain a variety of battery status information and improve test accuracy through multi-dimensional detection in the time domain and frequency domain. The test does not require a long time and a high-temperature environment, which can shorten the aging time and improve the production capacity of the entire line. It can quickly screen out cells with internal short circuits, reduce the flow of abnormal cells into subsequent production lines, and reduce the significant losses caused by internal short-circuited batteries. In addition, when performing the EIS process step, you can choose to implement protection and marking functions for the battery test. When the protection function is selected, the battery stops when the protection is triggered, and the EIS parameters are no longer tested. The remaining channels that have not triggered the protection can continue to produce, saving resources. When the marking function is selected, when the corresponding protection is triggered for the battery, the process will not be stopped, and production will be continued, but the corresponding recorded events will be uploaded to ensure the battery's excellent rate.

[0108] In some embodiments, the embodiments of the present application also provide a computer device, including a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor is used to execute the short circuit detection method based on electrochemical impedance detection in the above embodiments of the present application.

[0109] Reference Fig.11 , Fig.11 It is a schematic diagram of the hardware structure of the computer device provided in the embodiment of the present application.

[0110] Combine the following Fig.11 The hardware structure of the computer device is described in detail. The computer device includes: a processor 910 , a memory 920 , an input / output interface 930 , a communication interface 940 and a bus 950 .

[0111] The processor 910 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application; The memory 920 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 920 can store an operating system and other application programs. When the technical solution provided in the embodiments of this specification is implemented by software or firmware, the relevant program code is stored in the memory 920, and the processor 910 calls and executes the short-circuit detection method based on electrochemical impedance detection in the embodiments of this application; Input / output interface 930, used to implement information input and output; The communication interface 940 is used to realize the communication interaction between the device and other devices, and the communication can be realized by wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.); and the bus 950 is used to transmit information between the various components of the device (such as the processor 910, the memory 920, the input / output interface 930 and the communication interface 940); The processor 910 , the memory 920 , the input / output interface 930 , and the communication interface 940 are connected to each other in communication within the device via a bus 950 .

[0112] An embodiment of the present application also provides a storage medium, which is a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program is executed by a computer, the computer is used to execute the short circuit detection method based on electrochemical impedance detection in the above embodiment of the present application.

[0113] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0114] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0115] It can be understood by those skilled in the art that Figures 1 to 11 The technical solutions shown in the figure do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than those shown in the figure, or a combination of certain steps, or different steps.

[0116] The above-described embodiment of the short circuit detection system based on electrochemical impedance detection is merely illustrative, wherein the units described as separate components may or may not be physically separated, i.e., may be located in one place, or may be distributed to multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

[0117] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0118] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0119] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0120] In the several embodiments provided in the present application, it should be understood that the disclosed short-circuit detection system and method based on electrochemical impedance detection can be implemented in other ways. For example, the above-described short-circuit detection system embodiment based on electrochemical impedance detection is only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the short-circuit detection system or unit based on electrochemical impedance detection can be electrical, mechanical or other forms.

[0121] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0122] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0123] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of each embodiment method of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0124] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A short circuit detection method based on electrochemical impedance spectroscopy, characterized in that: The method comprises: Receive the test steps and impedance parameters sent by the host computer, and obtain multiple test groups, wherein each of the test groups includes multiple test objects, and the test steps include parameter outlier thresholds; Based on the test step, electrochemical impedance spectroscopy is performed on all test objects in the test group to obtain a Nyquist curve corresponding to the test object; Performing fitting analysis on all the Nyquist curves to obtain fitting curves, and performing similarity analysis on all the Nyquist curves according to the fitting curves to obtain similarity values; When the similarity value is less than a preset threshold, determining a target Nyquist curve corresponding to the similarity value, and performing an outlier analysis on the target Nyquist curve according to the impedance parameter to obtain an outlier analysis value; When the outlier analysis value is greater than or equal to the parameter outlier threshold, it is determined that the target test object corresponding to the target Nyquist curve is short-circuited.

2. The short circuit detection method based on electrochemical impedance spectroscopy according to claim 1, characterized in that: The test process comprises a first process, a second process and a third process, wherein the working frequencies of the first process, the second process and the third process are increased in sequence; the electrochemical impedance spectroscopy detection is performed on all the test objects in the test group based on the test process to obtain the Nyquist curve corresponding to the test object, including: Sending the first process step to a lower computer, so that the lower computer performs solution diffusion on the test object based on the first process step to obtain a diffusion coefficient; Sending the second process step to a subordinate computer, so that the subordinate computer performs a charge transfer operation on the test object based on the second process step to obtain a charge transfer rate; Sending the third step to a lower computer, so that the lower computer performs a double-layer generation operation on the test object based on the third step to form a solid electrolyte interface film on the surface of the test object to obtain high-frequency parameters; The diffusion coefficient, the charge transfer rate and the high-frequency parameter sent by the lower computer are received to generate a Nyquist curve corresponding to the test object through the diffusion coefficient, the charge transfer rate and the high-frequency parameter.

3. The short circuit detection method based on electrochemical impedance spectroscopy according to claim 1, characterized in that: The fitting analysis of all the Nyquist curves to obtain the fitting curves includes: For each of the Nyquist curves, data analysis is performed on the Nyquist curve to obtain curve data; Inputting the curve data into a preset fitting model, so that the fitting model performs feature analysis on the Nyquist curve based on the curve data and outputs fitting features; Curve fitting is performed on all the fitting features and all the Nyquist curves using a preset fitting algorithm to obtain a fitting curve.

4. The short circuit detection method based on electrochemical impedance spectroscopy according to claim 1, characterized in that: The performing similarity analysis on all the Nyquist curves according to the fitting curve to obtain a similarity value includes: For each of the Nyquist curves, feature extraction is performed on the Nyquist curve to obtain curve features; Calculating the similarity between the curve feature and the fitting curve based on a preset Euclidean distance to obtain a feature distance value; A similarity matrix is ​​constructed according to the characteristic distance values, and cluster analysis is performed on the similarity matrix according to a preset clustering algorithm to obtain similarity values.

5. The short circuit detection method based on electrochemical impedance spectroscopy according to claim 1, characterized in that: The impedance parameters include a target ohmic impedance value, a target SEI film impedance value, and a target charge transfer impedance value; The step of performing an outlier analysis on the target Nyquist curve according to the impedance parameter to obtain an outlier analysis value includes: In response to the calculation instruction of the lower computer, the target Nyquist curve is analyzed to obtain a test ohmic impedance value, a test SEI film impedance value and a test charge transfer impedance value; Comparing the target ohmic impedance value with the test ohmic impedance value to obtain a first deviation value; Comparing the target SEI film impedance value with the test SEI film impedance value to obtain a second deviation value; Comparing the target charge transfer impedance value with the test charge transfer impedance value to obtain a third deviation value; An outlier analysis value is obtained according to the first deviation value, the second deviation value, and the third deviation value.

6. The short circuit detection method based on electrochemical impedance spectroscopy according to claim 1, characterized in that: Before performing electrochemical impedance spectroscopy detection on all test objects in the test group based on the test step to obtain a Nyquist curve corresponding to the test object, the method further includes: Recording the channel information of the channel where the test object is located; After determining that the target test object corresponding to the target Nyquist curve is short-circuited, the method further includes: Determine the target channel information corresponding to the target test object, and determine the target channel where the target test object is located according to the target channel information; A protection instruction is sent to the target channel to stop the target channel from working.

7. The short circuit detection method based on electrochemical impedance spectroscopy according to claim 6, characterized in that: After determining the target channel information corresponding to the target test object, and determining the target channel where the target test object is located according to the target channel information, the method further includes: The target channel is marked, and production information of the marked target channel is recorded.

8. A short circuit detection system based on electrochemical impedance spectroscopy, characterized in that: The system comprises: A parameter receiving module, used for receiving the test steps and impedance parameters sent by the host computer, and obtaining a plurality of test groups, wherein each of the test groups includes a plurality of test objects, and the test steps include a parameter outlier threshold; An electrochemical impedance spectroscopy detection module, used to perform electrochemical impedance spectroscopy detection on all test objects in the test group based on the test step to obtain a Nyquist curve corresponding to the test object; A similarity calculation module is used to perform fitting analysis on all the Nyquist curves to obtain fitting curves, and perform similarity analysis on all the Nyquist curves according to the fitting curves to obtain similarity values; an outlier analysis module, configured to determine a target Nyquist curve corresponding to the similarity value when the similarity value is less than a preset threshold, and perform an outlier analysis on the target Nyquist curve according to the impedance parameter to obtain an outlier analysis value; The short circuit determination module is used to determine that the target test object corresponding to the target Nyquist curve is short-circuited when the outlier analysis value is greater than or equal to the parameter outlier threshold.

9. A computer device, characterized in that: The computer device includes a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor is used to execute the short circuit detection method based on electrochemical impedance detection as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium storing a computer program. When the computer program is executed by a computer, the computer is used to execute the short circuit detection method based on electrochemical impedance detection as described in any one of claims 1 to 7.

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