Method and system for early identification and early warning of internal short circuit in full life cycle of lithium ion battery

Abstract

The invention relates to the field of safety monitoring of lithium ion batteries, in particular to an early identification and early warning method and system for internal short circuit in the whole life cycle of a lithium ion battery. Comprising the steps of performing internal short circuit simulation on a to-be-tested battery module; passively balancing the to-be-tested battery module based on the battery management system; estimating the SOC of each battery cell in the battery module to be tested in real time based on the first-order RC equivalent circuit model in combination with an extended Kalman filtering algorithm; calculating an SOC difference value between the average SOC of the target battery cell and the average SOC of other battery cells in the battery module to be detected; according to the method, the change of the safety performance of the battery can be monitored in real time by simulating the internal short circuit, monitoring the equalization frequency of the battery core in real time and combining SOC estimation of the first-order RC equivalent circuit model, so that internal short circuit safety detection of the battery in the whole life cycle is realized, and safety accidents caused by the internal short circuit are effectively prevented.

Description

Technical Field

[0001] The present invention relates to the field of lithium-ion battery safety monitoring, and in particular to a method and system for early identification and warning of internal short circuits in the entire life cycle of lithium-ion batteries. Background Art

[0002] In the current technological context, lithium-ion batteries are widely used in electric vehicles and electrochemical energy storage systems due to their excellent energy density and cycle life, becoming one of the key technologies to promote energy transformation.

[0003] However, as lithium-ion batteries develop towards higher energy density, their safety issues are becoming increasingly prominent, especially the internal short circuit phenomenon, which not only reduces the overall performance of the battery, but may also cause serious thermal runaway events, posing a major threat to personnel and equipment.

[0004] Existing lithium-ion battery management systems (BMS) primarily focus on monitoring the battery pack's voltage, current, and temperature, as well as estimating the state of charge (SOC). Despite this, detecting and providing early warning of internal short circuits throughout the battery's lifecycle, especially in the early stages, remains a significant technical challenge. This is primarily due to the following reasons: 1. Early internal short circuits are difficult to identify: They occur in the early stages of the battery life. Because the discharge effect they cause is mild, they are usually not easily detected by the standard monitoring procedures of the BMS. This makes it difficult for the battery management system to have an effective response strategy in the early stages of internal short circuits and to take preventive measures in advance.

[0005] 2. Lack of unified internal short-circuit detection standards: Despite the industry's increasing emphasis on battery safety, there is no universally recognized and effective standard for internal short-circuit detection and assessment. This makes it difficult for battery manufacturers and users to find consistent detection criteria and treatment methods when faced with internal short-circuit issues.

[0006] 3. Insufficient SOC estimation accuracy: In existing technologies, battery SOC estimation often relies on relatively simple equivalent circuit models and algorithms. However, these models and algorithms may not accurately reflect the dynamic characteristics of lithium-ion batteries under internal short-circuit conditions, resulting in large errors in SOC estimation, which in turn affects battery balancing and thermal safety management. Summary of the Invention

[0007] In view of the problems mentioned in the prior art, the present application provides a lithium ion battery full life cycle internal short circuit early identification and warning method and system, which can monitor the change of battery safety performance in real time by designing different degrees of internal short circuit simulation through parallel resistance, and combining SOC difference and power comparison methods, to solve the problems in the background art.

[0008] In order to achieve the above-mentioned purpose, the present application adopts the following technical solutions: The present application is a lithium ion battery full life cycle internal short circuit early identification and warning method, comprising the following steps: S1, internal short circuit simulation is performed on the battery module to be tested, which includes connecting resistors with different resistance values in parallel to the battery module to be tested; S2, passive balancing of the battery module to be tested is performed based on the battery management system, taking the voltage of the first fully charged cell in the battery module to be tested as the charging cutoff threshold, balancing each cell in the charging and discharging cycle, and recording the balancing frequency of each cell in real time from empty to full state; S3, based on the first-order RC equivalent circuit model combined with the extended Kalman filter algorithm, the SOC of each cell in the battery module to be tested is estimated in real time, and for the target cell with abnormal balancing frequency, the SOC difference between the target cell and the average SOC of other cells in the battery module to be tested is calculated; S4, when the balancing frequency of the target cell is lower than that of other cells in the battery module to be tested, and the SOC difference is not less than the threshold, it is determined that the target cell has internal short circuit, so as to realize early warning.

[0009] As a further improvement of the present application, the resistors with different resistance values in S1 include 1000Ω resistance value simulating micro-short circuit, 100Ω resistance value simulating soft short circuit and 1Ω resistance value simulating hard short circuit.

[0010] As a further improvement of the present application, the passive balancing process in S2 is: When the cell voltage is higher than the charging cutoff threshold and the lowest voltage of the battery module is detected, the cell with high voltage is discharged to return the voltage to normal.

[0011] As a further improvement of the present application, the process from empty to full state in S2 is to use 1C constant current and constant voltage charging and 1C constant current discharging working condition; The charging cutoff condition is that the voltage reaches 4.2V and the current decreases to 1 / 20C; The discharge cutoff condition is that the voltage decreases to 3.3V.

[0012] As a further improvement of the present application, the judgment principle of abnormal balancing frequency in S3 is: Healthy cells participate in the balancing frequency more, and abnormal cells participate in the balancing frequency less or 0, so when the balancing frequency of the target cell is 0 or the balancing frequency is less than that of other cells, it is judged that the target cell has an internal short circuit.

[0013] As a further improvement of the application, the SOC difference in S4 is not less than a threshold, and the threshold is 5%. When the SOC difference is greater than or equal to 5%, a warning is realized.

[0014] As a further improvement of the application, the threshold is determined according to the standard of 5% monthly self-discharge of the battery.

[0015] The application provides an early identification and warning system for internal short circuit in the whole life cycle of a lithium ion battery, comprising: An internal short circuit simulation module is configured to simulate internal short circuit of a battery module to be tested, wherein the internal short circuit simulation comprises connecting resistors with different resistances in parallel to the battery module to be tested; A passive balancing judgment module is configured to balance the battery module to be tested based on a battery management system, to take the voltage of the cell that is first fully charged in the battery module to be tested as a charging cutoff threshold, to balance each cell in a charge-discharge cycle, and to record the balancing frequency of each cell in real time from empty to full state. An SOC judgment module is configured to estimate the SOC of each cell in the battery module to be tested in real time based on a first-order RC equivalent circuit model combined with an extended Kalman filter algorithm, to calculate the SOC difference between the target cell and the average SOC of other cells in the battery module to be tested for a target cell with abnormal balancing frequency. A warning module is configured to determine that the target cell has an internal short circuit when the balancing frequency of the target cell is lower than that of other cells in the battery module to be tested, and the SOC difference is not less than a threshold, so as to realize early warning.

[0016] The application provides an early identification and warning device for internal short circuit in the whole life cycle of a lithium ion battery, characterized by comprising a processor and a memory, wherein the processor executes a computer program stored in the memory to realize the early identification and warning method for internal short circuit in the whole life cycle of a lithium ion battery.

[0017] The application provides a computer readable storage medium, characterized by storing a computer program, wherein the computer program is executed by a processor to realize the early identification and warning method for internal short circuit in the whole life cycle of a lithium ion battery.

[0018] Compared with the prior art, the application has the following technical effects: The present invention simulates internal short circuits of varying degrees, monitors the balanced frequency of the battery cells in real time, and combines SOC estimation based on a first-order RC equivalent circuit model. The combination of two different detection methods can monitor changes in battery safety performance in real time, further reducing the occurrence of misjudgments. The synergy of these two methods can significantly improve the accuracy of internal short circuit identification, thereby achieving internal short circuit safety detection of the battery throughout its life cycle and effectively preventing safety accidents caused by internal short circuits.

[0019] The method of the present invention is not only applicable to vehicle BMS, but can also be widely used in various electrochemical energy storage management systems. Whether it is a household energy storage device or a large-scale industrial energy storage system, by implementing the technical solution provided by the present invention, the monitoring of the internal condition of the battery can be strengthened, thereby improving the overall safety and reliability of the energy storage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a schematic diagram of the framework of the present invention; Figure 2 Schematic diagram of the first-order RC model of the present invention; Figure 3 This is a single cell voltage curve diagram of the internal short-circuit battery equalization system of the present invention; Figure 4 This is a graph showing the frequency of short-circuited cells in the battery participating in equalization; Figure 5 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0021] The present invention will be further described in detail below with reference to the accompanying drawings and examples. It will be understood that the specific embodiments described herein are intended only to illustrate the present invention and are not intended to limit the present invention. It should also be noted that, for ease of description, the accompanying drawings only illustrate portions relevant to the present invention, not all structures.

[0022] See also Figure 1 and Figure 5 The present invention proposes a method for early identification and warning of internal short circuit in the entire life cycle of a lithium-ion battery, comprising the following steps: S1. Performing an internal short-circuit simulation on the battery module to be tested, wherein the internal short-circuit simulation includes connecting resistors of different resistance values ​​in parallel to the battery module to be tested; S2. The battery management system passively balances the battery module under test, using the voltage of the first fully charged cell in the battery module under test as the charge cutoff threshold. Each cell is balanced during the charge and discharge cycle, and the balancing frequency of each cell from empty to fully charged is recorded in real time. S3, based on the first-order RC equivalent circuit model combined with the extended Kalman filter algorithm, the SOC of each battery cell in the battery module to be measured is estimated in real time, and for the target battery cell with abnormal balancing times, the SOC difference between the target battery cell and the average SOC of other battery cells in the battery module to be measured is calculated; S4, when the balancing times of the target battery cell are lower than those of other battery cells in the battery module to be measured, and the SOC difference is not less than the threshold value, it is determined that the target battery cell has internal short circuit, so as to realize early warning.

[0023] The application will be further explained in combination with the drawings and specific embodiments: In this embodiment, resistors with different resistance values are connected in parallel to simulate internal short circuit of the battery, and specific simulation is made from micro short circuit, soft short circuit and hard short circuit, so that various internal short circuit conditions that the battery may encounter in the whole life cycle can be comprehensively detected.

[0024] In this embodiment, a certain degree of energy leakage is artificially introduced into the battery by connecting resistors in parallel to simulate the short circuit phenomenon occurring in the battery, and then whether there is internal short circuit is judged by observing the response of the battery. In terms of effect, the technology in this embodiment can accurately simulate different severity of internal short circuit of the battery, so that early accurate identification and early warning of internal short circuit of the battery are realized.

[0025] The application comprises resistors with resistance values of 1000Ω, 100Ω and 1Ω connected in parallel, which are used to simulate micro short circuit, soft short circuit and hard short circuit respectively, so as to comprehensively cover the internal short circuit conditions of lithium ion battery in different life cycle stages. By setting three resistors with different resistance values, different stages of internal short circuit of the battery can be simulated more carefully, and the detection accuracy and range of the system are improved.

[0026] In this embodiment, the battery management system is used to passively balance the battery module to be measured, and the voltage of the battery cell that is first charged to full in the battery module to be measured is used as the charging cutoff threshold. In the charging and discharging cycle, each battery cell is balanced, and the balancing frequency of each battery cell from empty to full is recorded in real time.

[0027] In this embodiment, based on the first-order RC equivalent circuit model combined with the extended Kalman filter algorithm, the SOC of each battery cell in the battery module to be measured is estimated in real time, and for the target battery cell with abnormal balancing times, the SOC difference between the target battery cell and the average SOC of other battery cells in the battery module to be measured is calculated.

[0028] When the balancing times of the target battery cell are lower than those of other battery cells in the battery module to be measured, and the SOC difference is not less than the threshold value, it is determined that the target battery cell has internal short circuit, so as to realize early warning.

[0029] This embodiment specifically proposes a process for early identification and warning of internal short circuits in the entire life cycle of a lithium-ion battery to illustrate the above method.

[0030] First, a lithium-ion battery module consisting of 6 cells (such as a ternary lithium battery) is selected and the initial state is set: the cell state of charge (SOC) follows a normal distribution with a mean of 60% and a variance of 1%; the cell capacity has a mean of 102 Ah and a variance of 0.02 Ah.

[0031] The battery management system (BMS) is equipped with voltage and current sensors (accuracy ±0.1%).

[0032] External resistors of different resistance values, including 1Ω, 100Ω, and 1000Ω, are used to simulate internal short circuits.

[0033] A first-order RC equivalent circuit model is established, which includes a voltage source OCV, a resistor R0, a resistor R1 and a capacitor C1, and the initial parameters of the first-order RC equivalent circuit model are optimized using a genetic algorithm.

[0034] like Figure 2 As shown, in the first-order RC equivalent circuit model of this embodiment, the voltage source OCV provides power to the entire circuit, wherein the resistor R0 is located to the right of the voltage source OCV and is connected in series with the voltage source. To the right of the resistor R0, the circuit is divided into two branches: the capacitor C1 branch, which includes a capacitor C1, and the voltage across it is marked as U1. The resistor R1 branch, which includes a resistor R1, is marked on the right side of the circuit, indicating the output voltage of the entire circuit.

[0035] In an internal short circuit simulation experiment, a target cell (such as Cell 1) is selected, and external resistors are connected in parallel to simulate three types of internal short circuits: 1Ω resistor, 100Ω resistor, and 1000Ω resistor. In this embodiment, a 100Ω resistor is preferably used for simulation.

[0036] like Figure 3 and Figure 4 As shown, the charge and discharge cycle is performed: in the charging stage: 1C constant current charging to 4.2V, then switching to constant voltage charging until the current is ≤0.05C; discharge stage: 1C constant current discharge to 3.3V cut off; number of cycles: ≥3 complete cycles to activate the balancing system and stabilize the data.

[0037] The battery management system compares the voltages of all cells in the battery module in real time. When the voltage of a cell is higher than the minimum voltage of the battery module + the charge cut-off threshold, passive balancing is triggered; the high-voltage cell is discharged ("clipped") through a parallel resistor until the voltage returns to the normal range.

[0038] The embodiment counts the equalization start times of each battery cell in a single cycle and calculates the equalization frequency in the whole life cycle, because the healthy battery cell needs to participate in equalization frequently to discharge; and the battery cell with internal short circuit triggers equalization rarely because the voltage of the battery cell with internal short circuit is continuously low due to self-discharge, so the equalization frequency tends to 0 or is obviously smaller than that of other battery cells.

[0039] SOC real-time estimation: input data: real-time collection of voltage, current, temperature and other data of the battery cell; the SOC state of the battery cell is estimated based on a first-order RC equivalent circuit model through Kalman filtering iteration, and the SOC estimation value is output, which can ensure that the engineering error is less than or equal to 1%.

[0040] The SOC difference value ΔSOC between the target battery cell SOC and the average SOC of the battery module is calculated, that is: ΔSOC = SOC 目标 -SOC 平均 And the threshold value ΔSOC is set to be greater than or equal to 5%. The threshold value 5% of the embodiment is set according to the standard of the national standard monthly self-discharge rate 5%.

[0041] The embodiment adopts a double verification method to judge, first identifies the target battery cell whose equalization frequency is significantly lower than that of other battery cells (such as the frequency is 0); and second, calculates the ΔSOC of the target battery cell to verify, if the ΔSOC is greater than or equal to 5%, the target battery cell is determined to be an internal short circuit.

[0042] Finally, the number and short circuit type of the target battery cell are marked to realize early warning.

[0043] Based on the same inventive concept, the embodiment of the present application also provides a lithium ion battery internal short circuit early identification and early warning system in the whole life cycle. Since the principle of solving problems of the lithium ion battery internal short circuit early identification and early warning system in the whole life cycle is similar to the lithium ion battery internal short circuit early identification and early warning method, the implementation of the lithium ion battery internal short circuit early identification and early warning system in the whole life cycle can be referred to the implementation of the lithium ion battery internal short circuit early identification and early warning method, and the repeated parts will not be described here.

[0044] In specific implementation, the lithium ion battery internal short circuit early identification and early warning system in the whole life cycle provided by the embodiment of the present application specifically includes: An internal short circuit simulation module is configured to simulate internal short circuit of a battery module to be tested, and the internal short circuit simulation includes connecting resistors with different resistance values in parallel to the battery module to be tested; A passive equalization judgment module is configured to perform passive equalization on the battery module to be tested based on a battery management system, to take the voltage of the battery cell first charged to full in the battery module to be tested as a charging cutoff threshold, to perform equalization on each battery cell in a charge-discharge cycle, and to record the equalization frequency of each battery cell in real time from the empty state to the full state. The SOC judging module is configured to estimate the SOC of each cell in the battery module to be tested in real time based on a first-order RC equivalent circuit model combined with an extended Kalman filtering algorithm, and calculate the SOC difference between the target cell and the average SOC of other cells in the battery module to be tested for the target cell with abnormal balancing times. The early warning module is configured to determine that the target cell has internal short circuit when the balancing times of the target cell are lower than those of other cells in the battery module to be tested and the SOC difference is not less than a threshold, so as to realize early warning.

[0045] Correspondingly, the embodiment of the present application also provides a lithium ion battery short circuit early identification and warning device in the whole life cycle, comprising a processor and a memory, wherein the processor executes the computer program stored in the memory to realize the lithium ion battery short circuit early identification and warning method provided by the embodiment of the present application.

[0046] The more specific process of the above method can refer to the corresponding content disclosed in the foregoing embodiments, which will not be repeated here.

[0047] Correspondingly, the embodiment of the present application also provides a computer readable storage medium for storing a computer program, wherein the computer program is executed by a processor to realize the above lithium ion battery short circuit early identification and warning method provided by the embodiment of the present application.

[0048] The embodiments in the specification are described in a progressive manner, and each embodiment focuses on the difference from other embodiments. The same or similar parts of each embodiment can be referred to each other. For the system, device and storage medium disclosed by the embodiments, since it corresponds to the method disclosed by the embodiments, the description is relatively simple, and the related parts can be referred to the method part.

[0049] The skilled person can further realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware, computer software or combination of the two. In order to clearly show the interchangeability of hardware and software, the composition and steps of each example have been described in the above description. Whether the functions are realized by hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0050] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0051] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0052] The above is a detailed introduction to the method, system, device and storage medium for early identification and warning of short circuits in the entire life cycle of lithium-ion batteries provided by the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core ideas. At the same time, for those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the contents of this specification should not be understood as limiting the present invention.

Claims

1. A method for early identification and warning of internal short circuit in the whole life cycle of lithium-ion batteries, characterized in that: The following steps are involved: S1. Performing an internal short-circuit simulation on the battery module to be tested, wherein the internal short-circuit simulation includes connecting resistors of different resistance values ​​in parallel to the battery module to be tested; S2. The battery management system passively balances the battery module under test, using the voltage of the first fully charged cell in the battery module under test as the charge cutoff threshold. Each cell is balanced during the charge and discharge cycle, and the balancing frequency of each cell from empty to fully charged is recorded in real time. S3, based on the first-order RC equivalent circuit model combined with the extended Kalman filter algorithm, estimates the SOC of each cell in the battery module to be tested in real time. For target cells with abnormal balancing times, calculate the SOC difference between the target cell and the average SOC of other cells in the battery module to be tested; S4. When the number of balancing times of the target cell is lower than that of other cells in the battery module to be tested, and the SOC difference is not less than the threshold, it is determined that the target cell has an internal short circuit, so as to achieve early warning.

2. The method for early identification and warning of internal short circuit in the entire life cycle of a lithium-ion battery according to claim 1, characterized in that: The resistors of different resistance values ​​in S1 include a 1000Ω resistance value for simulating a micro short circuit, a 100Ω resistance value for simulating a soft short circuit, and a 1Ω resistance value for simulating a hard short circuit.

3. The method for early identification and warning of internal short circuit in the whole life cycle of lithium-ion batteries according to claim 1, characterized in that: The process of passive balancing in S2 is: When it is detected that the cell voltage is higher than the charge cut-off threshold and the lowest cell voltage in the battery module, the cell with high voltage is discharged to return the voltage to normal.

4. The method for early identification and warning of internal short circuit in the entire life cycle of a lithium-ion battery according to claim 1, characterized in that: The process from empty to full charge in S2 adopts 1C constant current constant voltage charging and 1C constant current discharge conditions; The charging cut-off condition is when the voltage reaches 4.2V and the current drops to 1 / 20C; The discharge cut-off condition is when the voltage drops to 3.3V.

5. The method for early identification and warning of internal short circuit in the entire life cycle of a lithium-ion battery according to claim 1, characterized in that: The judgment principle of the abnormal equalization frequency in S3 is: Healthy cells participate in balancing at a high frequency, while abnormal cells participate in balancing at a low frequency or 0. Therefore, when the balancing frequency of a target cell is 0 or is lower than that of other cells, it is determined that the target cell has an internal short circuit.

6. The method for early identification and warning of internal short circuit in the entire life cycle of a lithium-ion battery according to claim 1, characterized in that: The SOC difference in S4 is not less than a threshold value, and the threshold value is 5%; When the SOC difference is ≥5%, an early warning will be implemented.

7. The method for early identification and warning of internal short circuit in the entire life cycle of a lithium-ion battery according to claim 6, characterized in that: The threshold value is determined based on a standard of 5% monthly self-discharge of the battery.

8. A lithium-ion battery internal short circuit early warning system during its entire life cycle, characterized in that: include: An internal short-circuit simulation module is used to perform an internal short-circuit simulation on the battery module to be tested, wherein the internal short-circuit simulation includes connecting resistors of different resistance values ​​in parallel to the battery module to be tested; The passive balancing judgment module is used to passively balance the battery module under test based on the battery management system. The voltage of the first fully charged cell in the battery module under test is used as the charging cutoff threshold. Each cell is balanced during the charge and discharge cycle, and the balancing frequency of each cell from empty to fully charged is recorded in real time. The SOC judgment module is used to estimate the SOC of each battery cell in the battery module to be tested in real time based on the first-order RC equivalent circuit model combined with the extended Kalman filter algorithm. For target batteries with abnormal balancing times, the SOC difference between the target battery cell and the average SOC of other batteries in the battery module to be tested is calculated; The early warning module is used to determine that the target cell has an internal short circuit when the target cell's balancing times are lower than those of other cells in the battery module to be tested and the SOC difference is not less than a threshold, so as to achieve early warning.

9. A short circuit early warning device for lithium-ion batteries during their entire life cycle, characterized in that: The method comprises a processor and a memory, wherein when the processor executes the computer program stored in the memory, the method for early identification and warning of internal short circuit in the whole life cycle of a lithium-ion battery as claimed in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that Used to store a computer program, wherein when the computer program is executed by a processor, it implements the method for early identification and warning of internal short circuit in the whole life cycle of a lithium-ion battery as claimed in any one of claims 1 to 7.

Images