A battery prediction early warning method and device

Abstract

The application provides a battery prediction and early warning method and device, which can obtain a measured expansion force curve of a lithium iron phosphate battery during charging, determine an expansion force maximum value of the measured expansion force curve at SOC=30% and an expansion force maximum value of the measured expansion force curve at SOC=100%, and perform capacity loss prediction and / or rapid degradation judgment on the lithium iron phosphate battery according to the actual pressure difference between the two expansion forces and a pre-constructed capacity loss model. In this way, capacity loss prediction and / or rapid degradation early warning can be achieved based on the charging and discharging platform characteristics of the lithium iron phosphate battery, by using the size relationship and pressure difference between the two expansion force peaks during charging, so that the accuracy of prediction and early warning can be improved.

Description

Technical Field

[0001] This application relates to the field of battery technology, and in particular to a battery prediction and early warning method and device. Background Technology

[0002] Lithium-ion batteries boast advantages such as high energy density and long cycle life, and are currently widely used in various electronic products and new energy vehicles. Among various types of lithium-ion batteries, lithium iron phosphate batteries occupy a mainstream position in power batteries due to their high safety, high specific energy, high specific power, and long cycle life. However, due to the unique charge and discharge platform characteristics of lithium iron phosphate batteries, current technologies struggle to accurately predict and provide early warnings regarding their performance. Summary of the Invention

[0003] The purpose of this application is to address at least one of the aforementioned technical deficiencies, particularly the low accuracy of prediction and early warning in the prior art.

[0004] In a first aspect, embodiments of this application provide a battery prediction and early warning method, including:

[0005] Obtain the measured expansion force curve of the lithium iron phosphate battery during the charging process; wherein the measured expansion force curve is used to reflect the change of the expansion force of the lithium iron phosphate battery with SOC during the charging process.

[0006] The maximum expansion force value of the measured expansion force curve in the first SOC interval is determined, and a first pressure value is obtained; wherein, the upper limit of the first SOC interval is greater than 30%, and the lower limit is less than 30%;

[0007] The maximum value of the expansion force in the second SOC interval of the measured expansion force curve is determined, and the second pressure value is obtained; wherein, the upper limit of the second SOC interval is 100%, and the lower limit is greater than or equal to the SOC corresponding to the minimum value of the expansion force in the measured expansion force curve;

[0008] Calculate the actual pressure difference based on the first pressure value and the second pressure value;

[0009] Based on the actual pressure difference and the pre-built capacity loss model, the capacity loss of the lithium iron phosphate battery is predicted and / or rapid degradation is judged; wherein, the capacity loss model is used to describe the relationship between the capacity loss rate of the lithium iron phosphate battery and the expansion pressure difference during the charging process.

[0010] In some embodiments, the lithium iron phosphate battery is subjected to rapid degradation assessment based on the actual pressure difference and a pre-built capacity loss model, including:

[0011] Based on the actual pressure difference, determine whether the lithium iron phosphate battery needs to undergo a rapid deterioration assessment process.

[0012] If necessary, the lithium iron phosphate battery is subjected to a capacity loss test to obtain the actual capacity loss value and the latest actual pressure difference;

[0013] The actual capacity loss value is substituted into the capacity loss model for calculation, and the predicted pressure difference is obtained.

[0014] Based on the difference between the latest actual pressure difference and the predicted pressure difference, it is determined whether the lithium iron phosphate battery has experienced rapid deterioration.

[0015] In some embodiments, determining whether the lithium iron phosphate battery has experienced rapid degradation based on the difference between the latest actual pressure difference and the predicted pressure difference includes:

[0016] If the difference between the latest actual pressure difference and the predicted pressure difference is less than a first preset threshold, then it is determined that the lithium iron phosphate battery has experienced rapid deterioration, and the cause of the rapid deterioration is gas production in the battery; wherein, the first preset threshold is less than zero.

[0017] In some embodiments, determining whether the lithium iron phosphate battery has experienced rapid degradation based on the difference between the latest actual pressure difference and the predicted pressure difference includes:

[0018] If the difference between the latest actual pressure difference and the predicted pressure difference is greater than the second preset threshold, it is determined that the lithium iron phosphate battery has experienced rapid deterioration, and the cause of the rapid deterioration is other side reactions.

[0019] Wherein, the second preset threshold is greater than zero, and the other side reactions refer to other side reactions besides battery gas production.

[0020] In some embodiments, determining whether a rapid degradation assessment process needs to be performed on the lithium iron phosphate battery based on the actual pressure difference includes:

[0021] Based on the actual pressure difference of the lithium iron phosphate battery during multiple charging processes, determine whether the actual pressure difference of the lithium iron phosphate battery undergoes a sudden change;

[0022] If so, a rapid degradation judgment process needs to be performed on the lithium iron phosphate battery; otherwise, a rapid degradation judgment process does not need to be performed on the lithium iron phosphate battery.

[0023] In some embodiments, determining whether a rapid degradation assessment process needs to be performed on the lithium iron phosphate battery based on the actual pressure difference includes:

[0024] If the absolute difference between the actual pressure difference and the predicted pressure difference is greater than a third preset threshold, then the lithium iron phosphate battery needs to undergo a rapid degradation judgment process; otherwise, the lithium iron phosphate battery does not need to undergo a rapid degradation judgment process.

[0025] In some embodiments, predicting the capacity loss of the lithium iron phosphate battery based on the actual pressure difference and a pre-built capacity loss model includes:

[0026] The actual pressure difference is substituted into the capacity loss model for calculation, and the predicted capacity loss value of the lithium iron phosphate battery is obtained.

[0027] In some embodiments, the construction steps of the capacity loss model include:

[0028] Obtain the charging expansion force curves of sample lithium iron phosphate batteries under different charge-discharge cycles;

[0029] Obtain the capacity loss curve of the sample lithium iron phosphate battery; the capacity loss curve is used to describe the relationship between the actual capacity loss value of the sample lithium iron phosphate battery and the number of charge-discharge cycles;

[0030] The capacity loss model is obtained by fitting data to the capacity loss curve and each of the charging expansion force curves.

[0031] In some embodiments, when the lithium iron phosphate battery is disposed within a battery pack or battery module, obtaining the measured expansion force curve of the lithium iron phosphate battery during charging includes:

[0032] Charge the battery pack or battery module;

[0033] During the charging process, the expansion force of the battery pack or battery module is collected by a pressure sensor located at the target position, and the measured expansion force curve is obtained; wherein, the target position is the center position of the highest temperature region in the battery pack or battery module.

[0034] Secondly, embodiments of this application provide a battery prediction and early warning device, comprising:

[0035] The first curve acquisition module is used to acquire the measured expansion force curve of the lithium iron phosphate battery during the charging process; wherein, the measured expansion force curve is used to reflect the change of the expansion force of the lithium iron phosphate battery with SOC during the charging process.

[0036] The first pressure value determination module is used to determine the maximum expansion force value of the measured expansion force curve in the first SOC interval and obtain the first pressure value; wherein, the upper limit of the first SOC interval is greater than 30% and the lower limit is less than 30%;

[0037] The second pressure value determination module is used to determine the maximum expansion force value of the measured expansion force curve in the second SOC interval and obtain the second pressure value; wherein, the upper limit value of the second SOC interval is 100%, and the lower limit value is greater than or equal to the SOC corresponding to the minimum expansion force value in the measured expansion force curve;

[0038] The actual pressure difference calculation module is used to calculate the actual pressure difference based on the first pressure value and the second pressure value;

[0039] The prediction and early warning module is used to predict the capacity loss and / or determine the rapid deterioration of the lithium iron phosphate battery based on the actual pressure difference and a pre-built capacity loss model; wherein, the capacity loss model is used to describe the relationship between the capacity loss rate of the lithium iron phosphate battery and the expansion pressure difference during the charging process.

[0040] Thirdly, embodiments of this application provide a storage medium storing computer-readable instructions, which, when executed by one or more processors, cause the one or more processors to perform the steps of the battery prediction and early warning method described in any of the above embodiments.

[0041] Fourthly, embodiments of this application provide a computer device, which includes: one or more processors, and a memory;

[0042] The memory stores computer-readable instructions, which, when executed by the one or more processors, perform the steps of the battery prediction and early warning method described in any of the above embodiments.

[0043] In the battery prediction and early warning method and apparatus provided in some embodiments of this application, the measured expansion force curve of a lithium iron phosphate battery during the charging process can be obtained. The maximum expansion force value at approximately 30% SOC and the maximum expansion force value at approximately 100% SOC are determined. Based on the actual pressure difference between the two expansion forces and a pre-built capacity loss model, capacity loss prediction and / or rapid degradation judgment of the lithium iron phosphate battery can be performed. Thus, based on the charge / discharge platform characteristics of the lithium iron phosphate battery, the relationship between the two expansion force peaks during the charging process and the pressure difference can be used to achieve capacity loss prediction and / or rapid degradation early warning, thereby improving the accuracy of prediction and early warning. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is a flowchart illustrating the battery prediction and early warning method in some embodiments;

[0046] Figure 2 This is a flowchart illustrating the steps involved in constructing the capacity loss model in some embodiments;

[0047] Figure 3 This is a schematic diagram of the charging expansion force curve of the sample lithium iron phosphate battery throughout its entire life cycle in some embodiments;

[0048] Figure 4 This is a schematic diagram of the capacity loss curve of a sample lithium iron phosphate battery in some embodiments;

[0049] Figure 5 In some embodiments, the correspondence between the actual capacity loss and the actual pressure difference of the sample lithium iron phosphate battery at different cycle numbers is shown.

[0050] Figure 6 This is a schematic diagram of the capacity loss model in some embodiments;

[0051] Figure 7 This is a flowchart illustrating the rapid degradation judgment steps for lithium iron phosphate batteries in some embodiments.

[0052] Figure 8 A comparison chart showing the predictions of existing technologies and those of this application;

[0053] Figure 9 This is one of the schematic diagrams illustrating the change of the first pressure value of a lithium iron phosphate battery with the number of charge-discharge cycles in some embodiments;

[0054] Figure 10 This is one of the schematic diagrams illustrating the change of the second pressure value of a lithium iron phosphate battery with the number of charge-discharge cycles in some embodiments;

[0055] Figure 11 This is one of the schematic diagrams illustrating how the actual pressure difference of a lithium iron phosphate battery changes with the number of charge-discharge cycles in some embodiments;

[0056] Figure 12 This is a second schematic diagram illustrating the change of the first pressure value of a lithium iron phosphate battery with the number of charge-discharge cycles in some embodiments.

[0057] Figure 13 This is a second schematic diagram illustrating the change of the second pressure value of a lithium iron phosphate battery with the number of charge-discharge cycles in some embodiments;

[0058] Figure 14 This is the second schematic diagram illustrating how the actual pressure difference of a lithium iron phosphate battery changes with the number of charge-discharge cycles in some embodiments.

[0059] Figure 15 This is a schematic diagram of the battery prediction and early warning device in some embodiments;

[0060] Figure 16 This is a diagram of the internal structure of a computer device in some embodiments. Detailed Implementation

[0061] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0062] In some embodiments, this application provides a battery prediction and early warning method. The following embodiments illustrate this method applied to a computer device. It is understood that the computer device described in this application can be an electronic device with data acquisition and data processing functions, and can be, but is not limited to, various personal computers, laptops, tablets, smartphones, etc. Furthermore, the computer device can be a standalone device or integrated into various battery acquisition and analysis devices; this application does not impose specific limitations in this regard.

[0063] like Figure 1 As shown, the battery prediction and early warning method provided in this application may include the following steps:

[0064] S102: Obtain the measured expansion force curve of the lithium iron phosphate battery during the charging process; wherein, the measured expansion force curve is used to reflect the change of the expansion force of the lithium iron phosphate battery with SOC during the charging process.

[0065] S104: Determine the maximum expansion force value of the measured expansion force curve in the first SOC interval and obtain the first pressure value; wherein, the upper limit of the first SOC interval is greater than 30%, and the lower limit is less than 30%;

[0066] S106: Determine the maximum value of the expansion force in the second SOC interval of the measured expansion force curve, and obtain the second pressure value; wherein, the upper limit of the second SOC interval is 100%, and the lower limit is greater than or equal to the SOC corresponding to the minimum value of the expansion force in the measured expansion force curve;

[0067] S108: Calculate the actual pressure difference based on the first pressure value and the second pressure value;

[0068] S110: Based on the actual pressure difference and the pre-built capacity loss model, predict the capacity loss and / or determine the rapid deterioration of the lithium iron phosphate battery; wherein, the capacity loss model is used to describe the relationship between the capacity loss rate of the lithium iron phosphate battery and the expansion pressure difference during the charging process.

[0069] Specifically, the inventors discovered that during the charging process of lithium iron phosphate (LFP) batteries, the expansion force exhibits a trend of increasing-decreasing-increasing. This is because, during charging, the lithium iron phosphate (LiFePO4) phase in the cathode shifts towards the iron phosphate (FePO4) phase. While lithium iron phosphate has a similar structure to iron phosphate, iron phosphate is approximately 6.81% smaller in volume, resulting in a continuous decrease in the thickness of the cathode electrode during charging. Conversely, the graphite anode has a layered structure, and the thickness continuously increases after lithium is intercalated between the layers, thus gradually increasing the thickness of the anode electrode during charging.

[0070] In the early stages of charging, the LiFePO4 at the cathode contracts minimally, while the graphite at the anode expands, resulting in an increasing expansion force in the lithium iron phosphate battery. In the middle stages of charging, the LiFePO4 at the cathode contracts, partially offsetting the pressure changes caused by the expansion of the graphite at the anode, thus decreasing the battery's expansion force. In the later stages of charging, the LiFePO4 at the cathode stops contracting, but the graphite at the anode continues to expand, causing the battery's expansion force to increase again. Based on this analysis, the expansion force of the lithium iron phosphate battery exhibits an increasing-decreasing-increasing trend during charging, while the trend during discharging is opposite to that during charging.

[0071] The inventors discovered that when the State of Charge (SOC) is around 30%, the expansion rate of the anode graphite is greater than the contraction rate of the cathode LiFePO4, causing the cell to expand and the battery's expansion force to increase. When the SOC is between 30% and 65%, the expansion rate of the anode graphite is less than the contraction rate of the cathode FePO4, causing the cell to contract and the battery's expansion force to decrease. When the SOC is between 65% and 100%, the expansion rate of the anode graphite is greater than the contraction rate of the cathode FePO4, causing the cell to expand and the expansion force to increase.

[0072] Based on the above findings, the battery early warning and prediction scheme provided in this application first obtains the measured expansion force curve of the lithium iron phosphate battery during the charging process. This measured expansion force curve can show how the expansion force of the lithium iron phosphate battery changes with the state of charge (SOC) during charging. For example, the horizontal axis of the measured expansion force curve can be SOC, and the vertical axis can be the battery expansion force. Alternatively, the horizontal axis of the measured expansion force curve can be the battery expansion force, and the vertical axis can be SOC. It should be noted that the expansion force mentioned in this application can be the pressure on the large surface of the lithium iron phosphate battery casing. Since the expansion force changes most significantly at this point, the change in expansion force can be more clearly reflected, improving the detection accuracy.

[0073] Given the measured expansion force curve, this application can determine the maximum expansion force value in the first SOC range and obtain the first pressure value. Since the upper limit of the first SOC range is greater than 30% and the lower limit of the first SOC range is less than 30%, the first pressure value can be understood as the peak expansion force of the lithium iron phosphate battery in the early to mid-stages of charging.

[0074] Furthermore, this application can determine the maximum expansion force value of the measured expansion force curve within the second SOC range and obtain the second pressure value. Since the upper limit of the second SOC range is 100%, and the lower limit of the second SOC range is greater than or equal to the SOC corresponding to the expansion force in the measured expansion force curve, the second pressure value can be understood as the peak expansion force of the lithium iron phosphate battery in the later stages of charging. That is, the first pressure value and the second pressure value are two peak expansion forces of the lithium iron phosphate battery during the charging process.

[0075] Given a first pressure value and a second pressure value, this application can calculate the numerical difference between the two pressure values ​​to obtain the actual pressure difference. It is understood that the specific formula for calculating the actual pressure difference can be determined based on actual circumstances, and this application does not impose specific limitations on this, as long as the actual pressure difference can reflect the numerical difference between the first and second pressure values. For example, a computer device can use the difference between the first and second pressure values ​​as the actual pressure difference. For ease of explanation and description, some embodiments of this application use the difference between the second and first pressure values ​​as the actual pressure difference.

[0076] Once the actual pressure difference is calculated, the computer equipment can predict capacity loss and / or provide early warning of rapid degradation for lithium iron phosphate batteries based on the actual pressure difference and a capacity loss model that describes the relationship between capacity loss rate and expansion pressure difference, thus achieving battery early warning and prediction. Capacity loss prediction refers to predicting the capacity loss rate of the lithium iron phosphate battery, while rapid degradation early warning refers to determining whether the performance of the lithium iron phosphate battery will decline sharply in a short period of time.

[0077] Compared to schemes that rely on the peak expansion force itself for prediction and early warning, this application utilizes the magnitude relationship and pressure difference between two peak expansion forces during charging to predict capacity loss and / or provide early warning of rapid degradation, thereby improving the accuracy of prediction and early warning. This will be described in detail below.

[0078] The capacity loss model is explained in detail below:

[0079] In some embodiments, such as Figure 2 As shown, the steps for constructing the capacity loss model include:

[0080] S202: Obtain the charging expansion force curves of sample lithium iron phosphate batteries under different charge-discharge cycles;

[0081] S204: Obtain the capacity loss curve of the sample lithium iron phosphate battery; the capacity loss curve is used to describe the relationship between the actual capacity loss value of the sample lithium iron phosphate battery and the number of charge-discharge cycles.

[0082] S206: Based on the capacity loss curve and each charging expansion force curve, data fitting is performed to obtain the capacity loss model.

[0083] Specifically, in the process of constructing the capacity loss model, the charging expansion force curve of the sample lithium iron phosphate battery throughout its entire life cycle can be obtained. The entire life cycle mentioned in this application may include charge-discharge cycle conditions and storage conditions. Figure 3 As shown, Figure 3 The diagram shows the charging expansion force curve of the sample lithium iron phosphate battery throughout its entire life cycle. Since this curve records the expansion force change trend of the sample lithium iron phosphate battery under different charge and discharge cycles (i.e. different number of cycles), the peak pressure difference of the expansion force of the sample lithium iron phosphate battery throughout its entire life cycle can be collected, and the pressure difference under different number of cycles can be obtained.

[0084] It can be understood that the pressure difference ΔF of the sample lithium iron phosphate battery at the target number of cycles is determined based on the maximum expansion force F1 in the first SOC range and the maximum expansion force F2 in the second SOC range of the target expansion force curve. For example, ΔF can be the value of (F2-F1). Here, the target expansion force curve refers to the charging expansion force curve corresponding to the target number of cycles, and the target number of cycles refers to the number of cycles per cycle.

[0085] Furthermore, this application can also obtain the capacity loss curve of the sample lithium iron phosphate battery, which can be shown as follows: Figure 4As shown. Since the capacity loss curve describes the relationship between the actual capacity loss value Qloss of the sample lithium iron phosphate battery and the number of charge-discharge cycles, that is, it describes the actual capacity loss value of the sample lithium iron phosphate battery under different cycle numbers. Step S202 obtains the charging expansion force curves of the sample lithium iron phosphate battery under different cycle numbers. Therefore, this application can use the number of cycle numbers as an intermediate parameter for data fitting to fit the capacity loss curve and each charging expansion force curve, thereby obtaining the capacity loss model of this application. Since the number of cycle numbers is itself the cumulative amount of capacity decay and also the cumulative beam of expansion force change, the two originally independent curves can be fitted through the common independent variable of "number of cycle numbers," without considering the time dimension, avoiding the complexity of high-dimensional curve fitting, while retaining the characteristic value of expansion force pressure difference, which is most relevant to capacity decay. Thus, the capacity loss model can more accurately describe the relationship between the capacity loss rate and expansion force pressure difference of the lithium iron phosphate battery.

[0086] For example, during the data fitting process, this application can obtain the actual capacity loss value and actual pressure difference for multiple cycle counts, and use the actual capacity loss value and actual pressure difference for the same cycle count as a coordinate point on a coordinate system, thereby obtaining multiple coordinate points. For instance, this application can use the actual capacity loss value as the x-coordinate and the actual pressure difference as the y-coordinate, then based on... Figure 5 The data shown yields coordinate points (0, 78.2), (2.78%, 50.00), (5.28%, 42.50), (7.95%, 16.50), (10.4%, 3.80), and (13.90%, 9.70). With multiple coordinate points obtained, this application can perform curve fitting on these points to establish a curve relationship between the capacity loss rate and the expansion pressure difference. This curve relationship can be expressed as follows: Figure 6 As shown.

[0087] Furthermore, in some examples, in practical applications, this application can determine the current number of cycles of the lithium iron phosphate battery, and when the lithium iron phosphate battery cycles to a preset number of cycles, execute step S110 to determine the actual capacity loss value of the lithium iron phosphate battery and determine whether the battery has experienced rapid degradation.

[0088] In some embodiments, such as Figure 7 As shown, based on the actual pressure difference and the pre-built capacity loss model, the rapid degradation judgment of lithium iron phosphate batteries is performed, including:

[0089] S302: Determine whether the rapid degradation judgment process needs to be performed on the lithium iron phosphate battery based on the actual pressure difference;

[0090] S304: If necessary, perform capacity loss testing on the lithium iron phosphate battery and obtain the actual capacity loss value and the latest actual pressure difference;

[0091] S306: Substitute the actual capacity loss value into the capacity loss model for calculation and obtain the predicted pressure difference;

[0092] S308: Determine whether the lithium iron phosphate battery has experienced rapid deterioration based on the difference between the latest actual pressure difference and the predicted pressure difference.

[0093] The inventors discovered that if a lithium iron phosphate battery experiences rapid degradation, its capacity will decrease sharply, and its swelling force will increase dramatically. This application can preliminarily determine whether a lithium iron phosphate battery is at risk of rapid degradation based on its swelling force, and thus determine whether a more in-depth rapid degradation assessment process is needed.

[0094] Specifically, in the process of assessing the rapid degradation of lithium iron phosphate (LFP) batteries, firstly, computer equipment can make a preliminary judgment on whether the LFP battery is at risk of rapid degradation based on the actual pressure difference. If it is preliminarily determined that the LFP battery is at risk of rapid degradation, a rapid degradation assessment procedure can be executed to further analyze whether the problem of rapid degradation exists. Furthermore, if it is preliminarily determined that the LFP battery is not at risk of rapid degradation, the rapid degradation assessment procedure can be omitted. In this way, online detection can be achieved with a relatively small computational load, saving resources.

[0095] It is understood that step S302 can be implemented in various ways in this application. The specific implementation method can be determined based on actual conditions such as the calculation formula of the actual pressure difference, calculation speed requirements, and accuracy requirements. This application does not impose specific limitations on this. For example, if the actual pressure difference is less than a preset pressure difference threshold, the computer device can determine that the rapid deterioration judgment process needs to be executed. Conversely, if the actual pressure difference is greater than or equal to the preset pressure difference threshold, the computer device can determine that the rapid deterioration judgment process does not need to be executed.

[0096] If it is determined that a rapid degradation assessment process needs to be performed on the lithium iron phosphate battery, a capacity loss test can be conducted to determine the actual capacity loss of the battery. The pressure difference between the two expansion force peaks during charging can also be tested again to obtain the actual capacity loss value and the latest actual pressure difference. In some examples, this application can perform a complete charge-discharge test on the lithium iron phosphate battery to obtain the actual capacity loss value and the latest actual pressure difference.

[0097] Since the capacity loss model is used to describe the relationship between the capacity loss rate of lithium iron phosphate batteries and the expansion pressure difference during charging, this application can substitute the actual capacity loss value into the capacity loss model for calculation to obtain the predicted pressure difference predicted by the capacity loss model. It can be understood that this predicted pressure difference is the expansion pressure difference corresponding to the actual capacity loss value of the lithium iron phosphate battery when there is no rapid degradation problem.

[0098] Given the predicted pressure difference, the computer device can compare the predicted pressure difference with the latest actual pressure difference and issue an early warning of rapid battery degradation based on the deviation between the two. This enables accurate early warning of rapid degradation. Furthermore, this application makes a preliminary judgment based on the actual pressure difference, which can improve the efficiency of early warning of rapid degradation and eliminate most healthy batteries with minimal computational cost, thus saving overall resources.

[0099] Compared to existing technologies, this application can amplify the problem of rapid capacity decay caused by battery gas production or other side reactions, and thereby determine whether lithium iron phosphate batteries are experiencing rapid degradation, thus achieving more accurate battery early warning. For example, Figure 8 The predictions and actual results of existing technologies were compared, as well as the predictions and actual results of this application. From... Figure 8 It can be seen that even when lithium iron phosphate batteries have experienced rapid degradation, the difference between the predicted and measured values ​​in existing technologies is relatively small, making it impossible to determine whether the battery has experienced rapid degradation based on the difference between the predicted and measured values. However, the method provided in this application differs from existing technologies. When the battery exhibits rapid degradation, the measured values ​​deviate significantly from the predicted values, thus allowing for the determination of whether the battery has experienced rapid degradation based on the difference between the predicted and measured values.

[0100] It should be noted that the solution adopted in this application does not require manual differentiation between cell hard expansion (core expansion) and cell gas expansion (expansion caused by gas production). This application can automatically determine whether the lithium iron phosphate battery is rapidly deteriorating due to gas expansion or other side reactions.

[0101] Specifically, when lithium plating occurs inside the battery, gas production increases, expansion force increases, and battery capacity drops sharply. Under these circumstances, the actual ΔF-Qloss relationship of the lithium iron phosphate battery deviates from the normal correspondence described by the capacity loss model. When gas production inside the cell is severe, the slope of the actual ΔF-Qloss curve will change abruptly. However, cell hardening is related to electrode rebound and does not cause abrupt changes in the curve slope. Therefore, judging rapid deterioration based on the difference between the actual pressure difference and the predicted pressure difference can eliminate the interference of cell hardening and ensure the accuracy of the judgment.

[0102] Furthermore, in some embodiments, the battery early warning prediction method provided in this application can not only detect whether the battery has a rapid degradation problem, but also distinguish whether the rapid degradation is caused by battery gas production or other side reactions.

[0103] In some embodiments, determining whether a lithium iron phosphate battery has experienced rapid degradation based on the difference between the latest actual pressure difference and the predicted pressure difference includes:

[0104] If the difference between the latest actual pressure difference and the predicted pressure difference is greater than the second preset threshold, it is determined that the lithium iron phosphate battery has deteriorated rapidly, and the cause of the rapid deterioration is other side reactions; where the second preset threshold is greater than zero, other side reactions refer to side reactions other than battery gas production.

[0105] Specifically, when the latest actual pressure difference deviates significantly from the predicted pressure difference, and the latest actual pressure difference is greater than the predicted pressure difference, it can be determined that the lithium iron phosphate battery has experienced rapid degradation, and the cause of the rapid degradation is other side reactions, such as lithium plating. For ease of explanation, the following examples use lithium plating as an example for description; the effects of other side reactions besides battery gas generation on the battery expansion force can be understood in the same way.

[0106] Since the first pressure value is the maximum expansion force in the first SOC range, which is approximately SOC = 30%, the first pressure value represents the maximum expansion force of the lithium iron phosphate battery at a low SOC state. Since the second pressure value is the maximum expansion force in the second SOC range, which is approximately SOC = 100%, the second pressure value represents the maximum expansion force of the lithium iron phosphate battery at a high SOC state.

[0107] Under low SOC conditions, lithium (Li) is normally intercalated into graphite, and no lithium is deposited on the anode surface. Therefore, the anode thickness does not increase abnormally, and the battery expansion force increases with the expansion of the anode electrode. Compared with the case where no rapid degradation has occurred, the trend of increasing battery expansion force remains unchanged. Figure 9 The diagram illustrates the variation of the first pressure value of lithium iron phosphate batteries with capacity loss in several examples. Green dots represent predicted first pressure values ​​when the battery does not experience rapid degradation, while red dots represent measured first pressure values ​​when the battery experiences rapid degradation due to other side reactions. Figure 9 As can be seen, the red dots and green dots are very similar, which is consistent with the trend described above.

[0108] If lithium plating occurs in the battery, the amount of Li embedded in the anode decreases under high SOC conditions. Li deposits on the anode surface as elemental or as a byproduct, leading to an abnormal increase in anode thickness. In addition to increasing anode expansion force, the battery expansion force also increases with increasing anode electrode thickness. Due to the abnormal increase in anode electrode thickness caused by lithium plating on the anode surface, the slope of the battery expansion force increases under high SOC conditions. Figure 10 The diagram illustrates the variation of the second pressure value of lithium iron phosphate batteries with capacity loss in several examples. Green dots represent predicted second pressure values ​​when the battery does not experience rapid degradation, while red dots represent measured second pressure values ​​when the battery experiences rapid degradation due to other side reactions. Figure 10 As can be seen, the red and green dots differ significantly, with the red dots being larger than the green dots. This means that the measured values ​​are significantly greater than the predicted values, which aligns with the trend described earlier.

[0109] Based on the changes in the first and second pressure values ​​described above, if lithium plating occurs in the battery, the second pressure value increases, while the first pressure value remains essentially unchanged. Therefore, compared to the case where the battery has not experienced rapid degradation, rapid battery degradation caused by side reactions will increase the difference between the second and first pressure values.

[0110] Thus, in Figure 11 In the curves shown, the green dots represent the predicted pressure difference when the battery does not experience rapid degradation (i.e., the predicted value output by the capacity loss model), while the red dots represent the actual pressure difference when the battery experiences rapid degradation due to other side reactions (i.e., the measured value obtained from testing). Figure 11 As can be seen, when other side reactions occur in the battery, the red dot deviates significantly from the green dot and is located above the green dot. This means that the difference between the measured pressure difference and the predicted pressure difference is large, and the difference between the two is greater than the second preset threshold. Furthermore, the measured pressure difference is greater than the predicted pressure difference. Based on this, it can be determined that other side reactions have occurred in the battery.

[0111] In some embodiments, determining whether a lithium iron phosphate battery has experienced rapid degradation based on the difference between the latest actual pressure difference and the predicted pressure difference includes:

[0112] If the difference between the latest actual pressure difference and the predicted pressure difference is less than the first preset threshold, it is determined that the lithium iron phosphate battery has experienced rapid deterioration, and the cause of the rapid deterioration is gas production in the battery; wherein, the first preset threshold is less than zero.

[0113] Specifically, when the battery produces gas, the amount of gas produced increases with the number of battery cycles, the internal gas pressure gradually increases, and the overall battery pressure increases accordingly. Regardless of whether the battery is at high or low SOC, gas production continues inside the battery, and the battery expansion force increases accordingly.

[0114] For example, Figure 12 The diagram shows how the first pressure value of lithium iron phosphate batteries changes with capacity loss in some examples. The green dots represent the predicted first pressure value when the battery does not have a rapid degradation problem, while the red dots represent the measured first pressure value when the battery has a rapid degradation problem caused by battery gas production. Figure 13 The diagram illustrates the variation of the second pressure value of lithium iron phosphate batteries with charge capacity loss in several examples. Green dots represent predicted second pressure values ​​when the battery does not experience rapid degradation, while red dots represent measured second pressure values ​​when the battery experiences rapid degradation due to gas generation. Figure 12 and Figure 13 It can be seen that the overall pressure value of the battery increases synchronously, and the difference between the predicted and measured first pressure values ​​is small, as is the difference between the second pressure values.

[0115] Therefore, if the latest actual pressure difference deviates significantly from the predicted pressure difference, and the actual pressure difference is less than the predicted pressure difference, it indicates an abnormal increase in the internal pressure of the lithium iron phosphate battery. However, since the electrode thickness increases uniformly and slowly, without a sudden increase, it can be determined that the rapid deterioration is caused by gas production in the battery.

[0116] For example, in Figure 14 In the curves, the green dots represent the pressure difference when the battery does not experience rapid degradation (i.e., the predicted value output by the capacity loss model), while the red dots represent the pressure difference when the battery experiences rapid degradation due to gas generation (i.e., the measured value obtained from testing). Figure 14 As can be seen, when the battery produces gas, the red dot deviates significantly from the green dot, and the red dot is located below the green dot. This means that the difference between the measured pressure difference and the predicted pressure difference is greater than the preset threshold, and the measured pressure difference is less than the predicted pressure difference. Therefore, it can be determined that the rapid deterioration is caused by gas production.

[0117] In some embodiments, determining whether a rapid degradation assessment process needs to be performed on the lithium iron phosphate battery based on the actual pressure difference includes:

[0118] Based on the actual pressure difference of the lithium iron phosphate battery during multiple charging processes, determine whether the actual pressure difference of the lithium iron phosphate battery undergoes a sudden change.

[0119] If so, a rapid degradation assessment procedure needs to be performed on the lithium iron phosphate battery; otherwise, a rapid degradation assessment procedure does not need to be performed on the lithium iron phosphate battery.

[0120] In this embodiment, when the lithium iron phosphate battery does not experience rapid degradation, the pressure difference of the lithium iron phosphate battery gradually decreases from a positive value to 0, and then gradually decreases from 0 to a negative value as the number of charge-discharge cycles increases. However, when the lithium iron phosphate battery experiences rapid degradation, the pressure difference of the lithium iron phosphate battery will change abruptly. Therefore, this application can determine whether the pressure difference of the lithium iron phosphate battery has changed abruptly based on the actual pressure difference during multiple charging processes, thereby making a preliminary judgment on whether the lithium iron phosphate battery needs to undergo rapid degradation assessment, thus improving the accuracy of the preliminary judgment.

[0121] If the actual pressure difference of a lithium iron phosphate battery undergoes a sudden change, it can be preliminarily determined that the battery is at risk of rapid degradation. In this case, a rapid degradation assessment process needs to be implemented for the lithium iron phosphate battery to further analyze whether a rapid degradation problem exists and to determine the type of rapid degradation problem.

[0122] If the actual pressure difference of the lithium iron phosphate battery does not change abruptly, it can be preliminarily determined that the lithium iron phosphate battery does not have a risk of rapid degradation, so the rapid degradation judgment process does not need to be performed on it.

[0123] In some embodiments, determining whether a rapid degradation assessment process needs to be performed on the lithium iron phosphate battery based on the actual pressure difference includes:

[0124] If the absolute difference between the actual pressure difference and the predicted pressure difference is greater than the third preset threshold, then the lithium iron phosphate battery needs to undergo a rapid degradation judgment process; otherwise, it does not need to undergo a rapid degradation judgment process.

[0125] In this embodiment, the relationship between the absolute difference between the actual pressure difference and the predicted pressure difference of the lithium iron phosphate battery during a single charge and the third preset threshold can be used to preliminarily determine whether the lithium iron phosphate battery needs to be given a rapid deterioration warning, thereby improving the efficiency of the preliminary judgment.

[0126] Specifically, if the absolute difference between the actual and predicted pressure differences of a lithium iron phosphate battery during a single charge is greater than a third preset threshold, it can be preliminarily determined that the lithium iron phosphate battery has a risk of rapid degradation. In this case, a rapid degradation judgment process needs to be performed on the lithium iron phosphate battery to further analyze whether there is a rapid degradation problem. Conversely, if the absolute difference between the actual and predicted pressure differences of a lithium iron phosphate battery during a single charge is less than or equal to the third preset threshold, it can be preliminarily determined that the lithium iron phosphate battery does not have a risk of rapid degradation, and the rapid degradation judgment process does not need to be performed on it. The predicted pressure difference can also be determined by using the number of cycles corresponding to the actual pressure difference as an expansion force curve. The third preset threshold can be set as needed.

[0127] In some embodiments, capacity loss prediction for lithium iron phosphate batteries is performed based on the actual pressure difference and a pre-built capacity loss model, including:

[0128] The actual pressure difference is substituted into the capacity loss model for calculation, and the predicted capacity loss value of the lithium iron phosphate battery is obtained.

[0129] In this embodiment, since the capacity loss model is used to describe the relationship between the capacity loss rate of the lithium iron phosphate battery and the expansion pressure difference during the charging process, the capacity loss value of the battery can be accurately predicted based on the capacity loss model when the expansion pressure difference is determined, and the actual SOH (State of Health) of the lithium iron phosphate battery can be corrected accordingly.

[0130] In some examples, since the actual pressure difference can be obtained simply by monitoring the surface pressure of the lithium iron phosphate battery, this embodiment can predict the capacity loss value by monitoring the surface pressure of the battery, thereby improving the convenience of prediction.

[0131] In some embodiments, when the lithium iron phosphate battery is disposed within a battery pack or battery module, the measured expansion force curve of the lithium iron phosphate battery during charging is obtained, including:

[0132] Charge the battery pack or battery module;

[0133] During charging, the expansion force of the battery pack or battery module is collected by a pressure sensor located at a target position, and a measured expansion force curve is obtained; wherein, the target position is the center position of the largest surface of the highest temperature battery in the battery pack or battery module. Specifically, the highest temperature battery in the battery pack or battery module can be determined based on pre-simulated charging and discharging conditions, and this application does not impose any restrictions.

[0134] In this embodiment, by collecting the measured expansion force curve at the center of the highest temperature battery surface of the battery pack or battery module, more reliable expansion force data can be obtained, thereby improving the accuracy and reliability of subsequent prediction and early warning.

[0135] Furthermore, in this embodiment, considering that the battery pack or battery module may include multiple lithium iron phosphate batteries, after obtaining the measured expansion force curve and calculating the actual pressure difference ΔF, ΔF can be multiplied by the battery quantity coefficient a to obtain the final actual pressure difference. This further improves the reliability of subsequent prediction and early warning.

[0136] The battery prediction and early warning device provided in the embodiments of this application is described below. The battery prediction and early warning device described below can be referred to in correspondence with the battery prediction and early warning method described above.

[0137] In some embodiments, such as Figure 15 As shown, this application provides a battery prediction and early warning device 400, comprising:

[0138] The first curve acquisition module 402 is used to acquire the measured expansion force curve of the lithium iron phosphate battery during the charging process; wherein, the measured expansion force curve is used to reflect the change of the expansion force of the lithium iron phosphate battery with SOC during the charging process.

[0139] The first pressure value determination module 404 is used to determine the maximum expansion force value of the measured expansion force curve in the first SOC interval and obtain the first pressure value; wherein, the upper limit of the first SOC interval is greater than 30% and the lower limit is less than 30%;

[0140] The second pressure value determination module 406 is used to determine the maximum value of the expansion force in the second SOC interval of the measured expansion force curve and obtain the second pressure value; wherein, the upper limit of the second SOC interval is 100%, and the lower limit is greater than or equal to the SOC corresponding to the minimum value of the expansion force in the measured expansion force curve;

[0141] The actual pressure difference calculation module 408 is used to calculate the actual pressure difference based on the first pressure value and the second pressure value;

[0142] The prediction and early warning module 410 is used to predict the capacity loss and / or determine the rapid deterioration of the lithium iron phosphate battery based on the actual pressure difference and the pre-built capacity loss model; wherein, the capacity loss model is used to describe the relationship between the capacity loss rate of the lithium iron phosphate battery and the expansion pressure difference during the charging process.

[0143] In some embodiments, the prediction and early warning module 410 of this application includes:

[0144] An execution judgment unit is used to determine, based on the actual pressure difference, whether the lithium iron phosphate battery needs to undergo a rapid deterioration judgment process.

[0145] The capacity loss testing unit is used to perform capacity loss testing on the lithium iron phosphate battery if necessary, and to obtain the actual capacity loss value and the latest actual pressure difference.

[0146] The first calculation unit is used to substitute the actual capacity loss value into the capacity loss model for calculation and obtain the predicted pressure difference;

[0147] The acute degradation early warning unit is used to determine whether the lithium iron phosphate battery has experienced acute degradation based on the difference between the latest actual pressure difference and the predicted pressure difference.

[0148] In some embodiments, the rapid degradation early warning unit of this application includes:

[0149] The first rapid deterioration judgment unit is used to determine that the lithium iron phosphate battery has rapidly deteriorated if the difference between the latest actual pressure difference and the predicted pressure difference is less than a first preset threshold, and the cause of the rapid deterioration is battery gas production; wherein the first preset threshold is less than zero.

[0150] In some embodiments, the rapid degradation early warning unit of this application includes:

[0151] The second rapid deterioration judgment unit is used to determine that the lithium iron phosphate battery has rapidly deteriorated if the difference between the latest actual pressure difference and the predicted pressure difference is greater than a second preset threshold, and the cause of the rapid deterioration is other side reactions; wherein, the second preset threshold is greater than zero, and the other side reactions refer to other side reactions besides battery gas production.

[0152] In some embodiments, the execution determination unit of this application includes:

[0153] The pressure change determination unit is used to determine whether the actual pressure difference of the lithium iron phosphate battery has changed abruptly based on the actual pressure difference of the lithium iron phosphate battery during multiple charging processes.

[0154] The first judgment unit is used to determine whether the lithium iron phosphate battery needs to undergo a rapid degradation judgment process if the condition is met; otherwise, it is not necessary to perform the rapid degradation judgment process on the lithium iron phosphate battery.

[0155] In some embodiments, the execution determination unit of this application includes:

[0156] The second judgment unit is used to perform a rapid degradation judgment process on the lithium iron phosphate battery if the absolute difference between the actual pressure difference and the predicted pressure difference is greater than a third preset threshold; otherwise, it is not necessary to perform a rapid degradation judgment process on the lithium iron phosphate battery.

[0157] In some embodiments, the prediction and early warning module 410 of this application includes:

[0158] The capacity loss prediction unit is used to substitute the actual pressure difference into the capacity loss model for calculation and obtain the predicted capacity loss value of the lithium iron phosphate battery.

[0159] In some embodiments, the battery prediction and early warning device 400 of this application further includes a model building module, which includes:

[0160] The expansion force curve acquisition unit is used to acquire the charging expansion force curve of the sample lithium iron phosphate battery under different charge-discharge cycles.

[0161] The capacity loss curve acquisition unit is used to acquire the capacity loss curve of the sample lithium iron phosphate battery; the capacity loss curve is used to describe the relationship between the actual capacity loss value of the sample lithium iron phosphate battery and the number of charge-discharge cycles.

[0162] The data fitting unit is used to perform data fitting based on the capacity loss curve and each of the charging expansion force curves, and to obtain the capacity loss model.

[0163] In some embodiments, when the lithium iron phosphate battery is disposed within a battery pack or battery module, the expansion force curve acquisition unit of this application includes:

[0164] A charging unit is used to charge the battery pack or battery module;

[0165] An expansion force acquisition unit is used to acquire the expansion force of the battery pack or battery module through a pressure sensor located at a target position during the charging process, and obtain the measured expansion force curve; wherein, the target position is the center position of the highest temperature region in the battery pack or battery module.

[0166] In one embodiment, this application also provides a storage medium storing computer-readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the battery prediction and warning method as described in any embodiment.

[0167] In one embodiment, this application also provides a computer device storing computer-readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the battery prediction and warning method as described in any embodiment.

[0168] Indicatively, Figure 16 This is a schematic diagram of the internal structure of a computer device provided in an embodiment of this application. In one example, the computer device can be a server. (Refer to...) Figure 16 The computer device 900 includes a processing component 902, which further includes one or more processors, and memory resources represented by memory 901 for storing instructions, such as application programs, that can be executed by the processing component 902. The application programs stored in memory 901 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 902 is configured to execute instructions to perform the steps of the battery prediction and warning method described in any of the above embodiments.

[0169] The computer device 900 may also include a power supply component 903 configured to perform power management of the computer device 900, a wired or wireless network interface 904 configured to connect the computer device 900 to a network, and an input / output (I / O) interface 905. The computer device 900 may operate on an operating system stored in memory 901, such as Windows Server™, Mac OS X™, Unix™, Linux™, Free BSD™, or similar.

[0170] Those skilled in the art will understand that the internal structure of the computer device shown in this application is merely a block diagram of a portion of the structure related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0171] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. In this document, "a," "an," "the," "the," and "its" may also include plural forms unless the context clearly indicates otherwise. "Multiple" refers to at least two, such as 2, 3, 5, or 8, etc. "And / or" includes any and all combinations of the related listed items.

[0172] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0173] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A battery prediction and early warning method, characterized in that, include: Obtain the measured expansion force curve of the lithium iron phosphate battery during the charging process; wherein the measured expansion force curve is used to reflect the change of the expansion force of the lithium iron phosphate battery with SOC during the charging process. The maximum expansion force value of the measured expansion force curve in the first SOC interval is determined, and a first pressure value is obtained; wherein, the upper limit of the first SOC interval is greater than 30%, and the lower limit is less than 30%; The maximum value of the expansion force in the second SOC interval of the measured expansion force curve is determined, and the second pressure value is obtained; wherein, the upper limit of the second SOC interval is 100%, and the lower limit is greater than or equal to the SOC corresponding to the minimum value of the expansion force in the measured expansion force curve; Calculate the actual pressure difference based on the first pressure value and the second pressure value; Based on the actual pressure difference and the pre-built capacity loss model, the capacity loss of the lithium iron phosphate battery is predicted and / or rapid degradation is judged: The lithium iron phosphate battery was subjected to a capacity loss test, and the actual capacity loss value and the latest actual pressure difference were obtained. The actual capacity loss value is substituted into the capacity loss model for calculation, and the predicted pressure difference is obtained. Based on the difference between the latest actual pressure difference and the predicted pressure difference, it is determined whether the lithium iron phosphate battery has experienced rapid deterioration. The capacity loss model is used to describe the relationship between the capacity loss rate of lithium iron phosphate batteries and the expansion force pressure difference during charging. The steps for constructing the capacity loss model include: Obtain the charging expansion force curves of sample lithium iron phosphate batteries under different charge-discharge cycles; Obtain the capacity loss curve of the sample lithium iron phosphate battery; the capacity loss curve is used to describe the relationship between the actual capacity loss value of the sample lithium iron phosphate battery and the number of charge-discharge cycles; The capacity loss model is obtained by fitting data to the capacity loss curve and each of the charging expansion force curves.

2. The method according to claim 1, characterized in that, Based on the actual pressure difference and the pre-built capacity loss model, the lithium iron phosphate battery is assessed for rapid degradation, including: Based on the actual pressure difference, determine whether the lithium iron phosphate battery needs to undergo a rapid deterioration assessment process.

3. The method according to claim 2, characterized in that, The step of determining whether the lithium iron phosphate battery has experienced rapid degradation based on the difference between the latest actual pressure difference and the predicted pressure difference includes: If the difference between the latest actual pressure difference and the predicted pressure difference is less than a first preset threshold, then it is determined that the lithium iron phosphate battery has experienced rapid deterioration, and the cause of the rapid deterioration is gas production in the battery; wherein, the first preset threshold is less than zero.

4. The method according to claim 2, characterized in that, The step of determining whether the lithium iron phosphate battery has experienced rapid degradation based on the difference between the latest actual pressure difference and the predicted pressure difference includes: If the difference between the latest actual pressure difference and the predicted pressure difference is greater than the second preset threshold, it is determined that the lithium iron phosphate battery has experienced rapid deterioration, and the cause of the rapid deterioration is other side reactions. Wherein, the second preset threshold is greater than zero, and the other side reactions refer to other side reactions besides battery gas production.

5. The method according to claim 2, characterized in that, The step of determining whether to perform a rapid degradation assessment process on the lithium iron phosphate battery based on the actual pressure difference includes: Based on the actual pressure difference of the lithium iron phosphate battery during multiple charging processes, determine whether the actual pressure difference of the lithium iron phosphate battery undergoes a sudden change; If so, a rapid degradation judgment process needs to be performed on the lithium iron phosphate battery; otherwise, a rapid degradation judgment process does not need to be performed on the lithium iron phosphate battery.

6. The method according to claim 2, characterized in that, The step of determining whether to perform a rapid degradation assessment process on the lithium iron phosphate battery based on the actual pressure difference includes: If the absolute difference between the actual pressure difference and the predicted pressure difference is greater than a third preset threshold, then the lithium iron phosphate battery needs to undergo a rapid degradation judgment process; otherwise, the lithium iron phosphate battery does not need to undergo a rapid degradation judgment process.

7. The method according to claim 1, characterized in that, The process of predicting the capacity loss of the lithium iron phosphate battery based on the actual pressure difference and a pre-built capacity loss model includes: The actual pressure difference is substituted into the capacity loss model for calculation, and the predicted capacity loss value of the lithium iron phosphate battery is obtained.

8. The method according to any one of claims 1 to 6, characterized in that, When the lithium iron phosphate battery is installed in a battery pack or battery module, obtaining the measured expansion force curve of the lithium iron phosphate battery during charging includes: Charge the battery pack or battery module; During the charging process, the expansion force of the battery pack or battery module is collected by a pressure sensor located at the target position, and the measured expansion force curve is obtained; wherein, the target position is the center position of the highest temperature region in the battery pack or battery module.

9. A battery prediction and early warning device, characterized in that, include: The first curve acquisition module is used to acquire the measured expansion force curve of the lithium iron phosphate battery during the charging process; wherein, the measured expansion force curve is used to reflect the change of the expansion force of the lithium iron phosphate battery with SOC during the charging process. The first pressure value determination module is used to determine the maximum expansion force value of the measured expansion force curve in the first SOC interval and obtain the first pressure value; wherein, the upper limit of the first SOC interval is greater than 30% and the lower limit is less than 30%; The second pressure value determination module is used to determine the maximum expansion force value of the measured expansion force curve in the second SOC interval and obtain the second pressure value; wherein, the upper limit value of the second SOC interval is 100%, and the lower limit value is greater than or equal to the SOC corresponding to the minimum expansion force value in the measured expansion force curve; The actual pressure difference calculation module is used to calculate the actual pressure difference based on the first pressure value and the second pressure value; The prediction and early warning module is used to predict the capacity loss and / or determine the rapid degradation of the lithium iron phosphate battery based on the actual pressure difference and a pre-built capacity loss model. The lithium iron phosphate battery was subjected to a capacity loss test, and the actual capacity loss value and the latest actual pressure difference were obtained. The actual capacity loss value is substituted into the capacity loss model for calculation, and the predicted pressure difference is obtained. Based on the difference between the latest actual pressure difference and the predicted pressure difference, it is determined whether the lithium iron phosphate battery has experienced rapid deterioration. The capacity loss model is used to describe the relationship between the capacity loss rate of lithium iron phosphate batteries and the expansion force pressure difference during charging. The steps for constructing the capacity loss model include: Obtain the charging expansion force curves of sample lithium iron phosphate batteries under different charge-discharge cycles; Obtain the capacity loss curve of the sample lithium iron phosphate battery; the capacity loss curve is used to describe the relationship between the actual capacity loss value of the sample lithium iron phosphate battery and the number of charge-discharge cycles; The capacity loss model is obtained by fitting data to the capacity loss curve and each of the charging expansion force curves.

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