Lithium iron phosphate battery insulation detection system

Abstract

The invention provides a lithium iron phosphate battery insulation detection system, which is applied to the technical field of new energy batteries, and can provide accurate insulation resistance readings by using a high-precision current detection device and a fine resistance measurement module, thereby improving the evaluation precision of the battery insulation performance. The software algorithm module analyzes the measurement data of the insulation resistance by using a time sequence analysis and statistical model, so that the abnormal change of the insulation performance of the battery can be recognized in an early stage, and the possibility is provided for timely maintenance and fault prevention; by setting a threshold parameter and a detection window, a software algorithm can identify and mark intermittent insulation problems which may be neglected in a conventional test, so that the reliability and the safety of the system are improved; a built-in historical database of the system provides data support for long-term trend analysis and performance monitoring, more accurate maintenance decision making based on data is facilitated, the service life of the battery is prolonged, and the performance of the battery is improved.

Description

Technical Field

[0001] The present application relates to the technical field of new energy batteries, and in particular to an insulation detection system for lithium iron phosphate batteries. Background Art

[0002] Lithium iron phosphate battery is a lithium-ion battery that uses lithium iron phosphate (LiFePO4) as the positive electrode material and carbon as the negative electrode material. The single cell rated voltage is 3.2V and the charging cut-off voltage is 3.6V~3.65V;

[0003] During the charging process, some lithium ions in the lithium iron phosphate are released, transferred to the negative electrode through the electrolyte, and embedded in the negative electrode carbon material; at the same time, electrons are released from the positive electrode and reach the negative electrode through the external circuit to maintain the balance of the chemical reaction. During the discharge process, lithium ions are released from the negative electrode and reach the positive electrode through the electrolyte. At the same time, the negative electrode releases electrons and reaches the positive electrode through the external circuit to provide energy to the outside world.

[0004] Lithium iron phosphate batteries have the advantages of high operating voltage, high energy density, long cycle life, good safety performance, low self-discharge rate and no memory effect;

[0005] Insulation testing usually needs to be performed under specific environmental conditions, such as temperature and humidity control. Changes in environmental factors may affect the accuracy of test results. In addition, the test process may be affected by external electromagnetic interference, especially when testing at high voltages. This may lead to errors or false positive / false negative results. Insulation testing systems may find it difficult to detect intermittent insulation problems because these problems may only occur under specific conditions and not in routine tests. Summary of the Invention

[0006] This application aims to solve the problem that insulation testing usually needs to be carried out under specific environmental conditions, such as temperature and humidity control. Changes in environmental factors may affect the accuracy of the test results, and the test process may be subject to external electromagnetic interference, especially during high voltage testing, which may lead to errors or false positive / false negative results. The insulation detection system may have difficulty detecting intermittent insulation problems because these problems may only occur under specific conditions rather than in routine tests. A lithium iron phosphate battery insulation detection system is provided.

[0007] This application adopts the following technical means to solve the technical problem: a lithium iron phosphate battery insulation detection system,

[0008] A lithium iron phosphate battery insulation detection system, the system comprising:

[0009] A test unit, equipped with a voltage applying device and an insulation resistance measuring device for testing the insulation performance of the battery;

[0010] Environmental control unit, used to control the temperature and humidity conditions in the test area to maintain it within the preset test environment range;

[0011] Electromagnetic interference shielding unit, used to reduce the impact of external electromagnetic interference on insulation test results;

[0012] a data processing unit configured with software algorithms for analyzing measurement data and identifying intermittent insulation problems;

[0013] A user interface is used to display test results and environmental parameters and allow the user to input test parameters and environmental control setting values; a data processing unit is used to operate the control logic of the test unit in continuous or periodic test mode to capture intermittent insulation characteristics under different environmental conditions and time points.

[0014] Furthermore, in the step of configuring a voltage applying device and an insulation resistance measuring device for testing the insulation performance of the battery,

[0015] The test unit also includes a test unit, which includes: a high-voltage source for applying a predetermined DC voltage to the battery; a current detection device for measuring the leakage current of the battery when the high voltage is applied; and a resistance measurement module for calculating the insulation resistance value of the battery based on the leakage current and the applied voltage.

[0016] Furthermore, the high voltage source is a programmable direct current power supply.

[0017] Furthermore, in the step of reducing the influence of external electromagnetic interference on the insulation test result,

[0018] The EMI shielding unit includes a metal shielding layer and / or an electromagnetic interference filter.

[0019] Further, in the step of configuring a software algorithm for analyzing the measurement data and identifying intermittent insulation problems,

[0020] The data were pre-processed and then time series analysis techniques were used, using an autoregressive moving average model, to identify abnormal patterns in the data by comparing the statistical properties, mean and standard deviation of continuous measurements with historical data.

[0021] Furthermore, a set of preset threshold parameters for intermittent fault detection is included, including a fault detection threshold and a fault confirmation time window.

[0022] Furthermore, the data analysis step of the software algorithm module includes applying the following formula to identify intermittent insulation problems:

[0023] R_t=μ+σ*ε_t

[0024] Where: R_t represents the insulation resistance measurement value at time point t; μ represents the mean of the historical insulation resistance measurement values; σ represents the standard deviation of the historical insulation resistance measurement values; ε_t represents the random error at time point t, which is assumed to be normally distributed; when the value of R_t continuously exceeds μ±n*σ (where n is a preset threshold multiple), the system will mark it as a potential intermittent insulation problem.

[0025] Furthermore, the software algorithm module further includes a history database for recording and storing the insulation resistance value of each test.

[0026] Furthermore, an automatic calibration unit is included for regularly calibrating the voltage applying device and the insulation resistance measuring device in the test unit.

[0027] This application provides a lithium iron phosphate battery insulation detection system, which has the following beneficial effects:

[0028] By using a high-precision current detection device and a sophisticated resistance measurement module, the system can provide accurate insulation resistance readings, thereby improving the accuracy of battery insulation performance assessment;

[0029] The software algorithm module uses time series analysis and statistical models to analyze insulation resistance measurement data, which helps to identify abnormal changes in battery insulation performance at an early stage, thereby making it possible to provide timely maintenance and fault prevention.

[0030] By setting threshold parameters and detection windows, software algorithms can identify and flag intermittent insulation problems that may go unnoticed during routine testing, thereby improving system reliability and safety.

[0031] The system's built-in historical database provides data support for long-term trend analysis and performance monitoring, helping to make more accurate maintenance decisions based on data and improve battery life and performance;

[0032] The entire insulation testing process is automatically executed by a microprocessor and software algorithms, reducing dependence on operators while enhancing the user experience through an intuitive interface and report output;

[0033] Because the programmable DC power supply and software algorithm parameters in the system are adjustable, the detection system can adapt to batteries of different types and specifications, and has strong adaptability and flexibility.

[0034] Through accurate fault detection and early warning, the system helps avoid serious consequences of battery failure, reducing potential maintenance costs and economic losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1This is a flow chart of an embodiment of the lithium iron phosphate battery insulation detection system of the present application.

[0036] The implementation, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0037] It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application.

[0038] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0039] It should be noted that the terms "include", "comprising" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings 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 limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices. In the claims, specification and drawings of this application, relational terms such as "first" and "second" are merely used to distinguish one entity / operation / object from another entity / operation / object, and do not necessarily require or imply any actual relationship or order between these entities / operations / objects.

[0040] References to "embodiments" herein mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0041] Reference Attachment Figure 1 , is a flow chart of a lithium iron phosphate battery insulation detection system in one embodiment of the present application;

[0042] Example 1: A lithium iron phosphate battery insulation detection system, the system comprising:

[0043] A test unit, equipped with a voltage applying device and an insulation resistance measuring device for testing the insulation performance of the battery;

[0044] Environmental control unit, used to control the temperature and humidity conditions in the test area to maintain it within the preset test environment range;

[0045] Electromagnetic interference shielding unit, used to reduce the impact of external electromagnetic interference on insulation test results;

[0046] a data processing unit configured with software algorithms for analyzing measurement data and identifying intermittent insulation problems;

[0047] A user interface is used to display test results and environmental parameters and allow the user to input test parameters and environmental control setting values; a data processing unit is used to operate the control logic of the test unit in continuous or periodic test mode to capture intermittent insulation characteristics under different environmental conditions and time points.

[0048] In this embodiment, in the step of configuring a voltage applying device and an insulation resistance measuring device for testing the insulation performance of the battery,

[0049] The test unit also includes a test unit, which includes: a high-voltage source for applying a predetermined DC voltage to the battery; a current detection device for measuring the leakage current of the battery when the high voltage is applied; and a resistance measurement module for calculating the insulation resistance value of the battery based on the leakage current and the applied voltage.

[0050] Specifically, the high voltage source is a programmable direct current power supply.

[0051] High voltage source applies voltage: The high voltage source is configured to apply a predetermined DC voltage, such as 500 volts, to the battery pack, which is usually higher than the normal operating voltage of the battery pack to test its insulation performance under extreme conditions;

[0052] Measuring leakage current: The current detection device measures the leakage current of the battery pack when a high voltage of 500 volts is applied. Assume that during the test, the leakage current detected is 1 milliampere (mA);

[0053] Calculate insulation resistance: The resistance measurement module calculates the insulation resistance value of the battery pack according to Ohm's law (V = IR), where V is the applied voltage, I is the measured leakage current, and R is the insulation resistance;

[0054] Using the formula R = V / I, we can calculate the insulation resistance R = 500V / 0.001A = 500,000 ohms or 500 kilo-ohms (kΩ);

[0055] Data analysis: The measured insulation resistance values are sent to the data processing unit, where the software algorithm module analyzes the data to determine whether there is an intermittent insulation problem;

[0056] For example, the software might compare statistical properties of current measurements with historical measurements, such as mean and standard deviation;

[0057] Identifying intermittent problems: Assume that historical data shows that the normal insulation resistance of a battery pack has a mean of 600 kΩ and a standard deviation of 50 kΩ. If the software algorithm sets the detection threshold to twice the standard deviation of the mean, that is, 700 kΩ (600 kΩ + 2 * 50 kΩ);

[0058] The current measurement of 500 kilo-ohms is below this threshold. If such low resistance values occur continuously within a certain time window, the software algorithm may flag this situation as a potential intermittent insulation problem.

[0059] In this embodiment, in the step of reducing the influence of external electromagnetic interference on the insulation test result,

[0060] The EMI shielding unit includes a metal shielding layer and / or an electromagnetic interference filter.

[0061] In this embodiment, during the step of configuring a software algorithm for analyzing measurement data and identifying intermittent insulation problems,

[0062] The data were pre-processed and then time series analysis techniques were used, using an autoregressive moving average model, to identify abnormal patterns in the data by comparing the statistical properties, mean and standard deviation of continuous measurements with historical data.

[0063] Specifically, data preprocessing: Before conducting insulation testing, historical measurement data needs to be preprocessed to clean the data, fill missing values, remove noise, etc.

[0064] Measuring insulation resistance: Use test equipment to apply a predetermined DC high voltage to the transformer, such as 15kV, and measure the leakage current. Assume that in a specific test, the measured leakage current is 0.5mA.

[0065] Calculate the insulation resistance value based on the measured leakage current and the applied voltage. Using the formula R = V / I, we get R = 15kV / 0.0005A = 30,000,000 ohms or 30MΩ.

[0066] The measured insulation resistance values were incorporated into time series analysis, and an autoregressive moving average (ARMA) model was used to analyze abnormal patterns in the data. The ARMA model can handle the autocorrelation of time series data, thereby identifying potential abnormal changes.

[0067] Assume that historical data analysis shows that the mean insulation resistance of the transformer during normal operation is 35 MΩ and the standard deviation is 3 MΩ. Set the anomaly detection threshold to the mean minus twice the standard deviation, which is 29 MΩ (35 MΩ - 2 * 3 MΩ).

[0068] The current measured value of 30 MΩ is slightly higher than the anomaly detection threshold of 29 MΩ, so the single measurement does not trigger an alarm. However, if the ARMA model shows a trend of insulation resistance values approaching or falling below 29 MΩ in several consecutive measurements,

[0069] Also included is a set of preset threshold parameters for intermittent fault detection, including a fault detection threshold and a fault confirmation time window.

[0070] Specifically, set the preset threshold parameters: assuming that based on the transformer design specifications and historical insulation resistance test data, the fault detection threshold is set to the mean minus two standard deviations, that is, 29MΩ (35MΩ - 2 * 3MΩ);

[0071] Set a time window, such as 7 consecutive days, to confirm whether the fault persists;

[0072] Conduct continuous insulation resistance tests on transformers once a day and record the resistance value of each test;

[0073] Use ARMA models to analyze time series data of continuously measured values to identify unusual patterns in the data;

[0074] The ARMA model combines the autoregressive (AR) and moving average (MA) methods to describe the dynamic characteristics of time series data. The general form of the ARMA model can be expressed as ARMA(p, q), where p represents the autoregressive order and q represents the moving average order. The AR part describes the linear relationship between the current value of the time series and its past values, while the MA part focuses on the linear relationship between the current value of the time series and the error term.

[0075] When the insulation resistance value of a measurement falls below the fault detection threshold (29MΩ), the software algorithm will mark the measurement as a potential fault event;

[0076] If the insulation resistance value is lower than the fault detection threshold multiple times within the fault confirmation time window (7 consecutive days), the software algorithm will confirm that this is a true intermittent fault;

[0077] For example, if the measured value is lower than 29MΩ for 5 out of 7 consecutive days, the system will issue a fault alarm;

[0078] Assume that the insulation resistance values measured over seven consecutive days are: 32MΩ, 28MΩ, 30MΩ, 27MΩ, 29MΩ, 26MΩ, 31MΩ;

[0079] Based on the preset thresholds and time windows, the system detected that the measured values on days 2, 4, 5, and 6 were below the fault detection threshold of 29 MΩ;

[0080] Since there were four measurements below the threshold within the 7-day window, the system confirmed the presence of an intermittent fault and triggered the corresponding fault alarm;

[0081] In this embodiment, the data analysis step of the software algorithm module includes applying the following formula to identify intermittent insulation problems: R_t=μ+σ*ε_t

[0082] Where: R_t represents the insulation resistance measurement value at time point t; μ represents the mean of the historical insulation resistance measurement values; σ represents the standard deviation of the historical insulation resistance measurement values; ε_t represents the random error at time point t, which is assumed to be normally distributed; when the value of R_t continuously exceeds μ±n*σ (where n is a preset threshold multiple), the system will mark it as a potential intermittent insulation problem.

[0083] The software algorithm module further includes a history database for recording and storing the insulation resistance value of each test.

[0084] Specifically, the database is responsible for collecting the results of each insulation test and storing them as historical records. These test results may include insulation resistance value, test date and time, test conditions (such as temperature, humidity), test voltage and leakage current;

[0085] The database provides a search function that allows users to query test data under specific dates, time ranges or other conditions as needed;

[0086] The database supports data analysis and can perform statistical analysis on stored data, such as calculating the mean, standard deviation, maximum and minimum values of long-term trends;

[0087] The database is combined with data visualization tools to graphically display trends and patterns of insulation resistance values, helping users to understand the data more intuitively;

[0088] The database has a data backup function to ensure that data can be restored in the event of system failure or data corruption.

[0089] The database implements appropriate security measures, such as access controls, encryption, and audit logs, to protect data from unauthorized access and tampering;

[0090] Database Management System (DBMS):

[0091] A database management system is software used to create, maintain, and manipulate databases. It can be a SQL database like MySQL or PostgreSQL, or a NoSQL database like MongoDB.

[0092] The database contains multiple data tables, each of which stores different types of data. During design, a data model is created to define the structure, relationships, and constraints of the data.

[0093] In one embodiment, the test unit further includes an automatic calibration unit for periodically calibrating the voltage applying device and the insulation resistance measuring device in the test unit.

[0094] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0095] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0096] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0097] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0098] Although the embodiments of the present application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations may be made to these embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A lithium iron phosphate battery insulation detection system, characterized in that: The system comprises: A test unit, equipped with a voltage applying device and an insulation resistance measuring device for testing the insulation performance of the battery; Environmental control unit, used to control the temperature and humidity conditions in the test area to maintain it within the preset test environment range; Electromagnetic interference shielding unit, used to reduce the impact of external electromagnetic interference on insulation test results; a data processing unit configured with software algorithms for analyzing measurement data and identifying intermittent insulation problems; A user interface is used to display test results and environmental parameters and allow the user to input test parameters and environmental control setting values; a data processing unit is used to operate the control logic of the test unit in continuous or periodic test mode to capture intermittent insulation characteristics under different environmental conditions and time points.

2. The lithium iron phosphate battery insulation detection system according to claim 1, characterized in that: In the step of configuring a voltage applying device and an insulation resistance measuring device for testing the insulation performance of the battery, the testing unit further includes a testing unit comprising: a high voltage source for applying a predetermined DC voltage to the battery; a current detecting device for measuring the leakage current of the battery when the high voltage is applied; A resistance measurement module that calculates the insulation resistance value of the battery based on the leakage current and applied voltage.

3. The lithium iron phosphate battery insulation detection system according to claim 2, characterized in that: The high voltage source is a programmable direct current power supply.

4. The lithium iron phosphate battery insulation detection system according to claim 1, characterized in that: In the step of reducing the influence of external electromagnetic interference on the insulation test result, the EMI shielding unit includes a metal shielding layer and / or an electromagnetic interference filter.

5. The lithium iron phosphate battery insulation detection system according to claim 1, characterized in that: In the step of configuring a software algorithm for analyzing the measurement data and identifying intermittent insulation problems, the data is pre-processed and then time series analysis techniques are used, through an autoregressive moving average model, to identify abnormal patterns in the data by comparing the statistical properties, mean and standard deviation of continuous measurements with historical data.

6. The lithium iron phosphate battery insulation detection system according to claim 5, characterized in that: Also included is a set of preset threshold parameters for intermittent fault detection, including a fault detection threshold and a fault confirmation time window.

7. The lithium iron phosphate battery insulation detection system according to claim 6, characterized in that: The data analysis step of the software algorithm module includes applying the following formula to identify intermittent insulation problems: R_t=μ+σ*ε_t, where: R_t represents the insulation resistance measurement value at time point t; μ represents the mean of the historical insulation resistance measurement values; σ represents the standard deviation of the historical insulation resistance measurement values; ε_t represents the random error at time point t, assumed to be normally distributed; when the value of R_t continuously exceeds μ±n*σ (where n is a preset threshold multiple), the system will mark it as a potential intermittent insulation problem detected.

8. The lithium iron phosphate battery insulation detection system according to claim 7, characterized in that: The software algorithm module further includes a history database for recording and storing the insulation resistance value of each test.

9. The lithium iron phosphate battery insulation detection system according to claim 1, characterized in that: An automatic calibration unit is also included for periodically calibrating the voltage applying device and the insulation resistance measuring device in the test unit.

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