A method for judging the health status of a nickel-rich lithium battery based on the incremental capacity analysis method

Abstract

The present invention discloses a method for determining the health of nickel-rich lithium batteries based on incremental capacity analysis. The method comprises the following steps: obtaining constant current charge and discharge data of a ternary lithium-ion battery in a fully charged and discharged state; obtaining an IC curve based on the constant current charge and discharge data, and extracting key features from the IC curve; constructing a fitting function, inputting the key features into the fitting function, and obtaining a fitting curve; fitting the IC curve to the fitting curve to obtain a goodness of fit, and determining the battery health status based on the goodness of fit. The present invention can accurately capture the dynamic reactions of a battery during charging, particularly when polarization significantly affects it, providing more refined battery performance analysis with higher accuracy than traditional methods.

Description

Technical Field

[0001] The present invention belongs to the technical field of nickel-rich lithium batteries for automobiles, and in particular relates to a method for judging the health status of nickel-rich lithium batteries based on an incremental capacity analysis method. Background Art

[0002] In today's society, with the continued rise in demand for renewable energy and the rapid development of electric transportation, nickel-rich lithium batteries, in particular, are becoming an increasingly important part of the global energy transition. Nickel-rich lithium batteries have shown excellent application potential in electric vehicles, smart devices, and energy storage systems due to their high energy density and ideal cycle performance. Battery state of health (SOH) assessment has become one of the key factors in promoting the widespread application of this technology. When evaluating the SOH of nickel-rich lithium batteries, there are still deficiencies, especially in terms of battery polarization issues. It is particularly important to develop an effective battery SOH estimation method.

[0003] Battery polarization refers to the voltage drop caused by current flow during the battery's charge and discharge processes. This phenomenon can be categorized into several different types, the most prominent of which include electrochemical polarization, concentration polarization, and ohmic polarization. These polarization phenomena directly impact the battery's energy efficiency and safety, particularly during high-power discharge or rapid charging. Polarization renders traditional methods that rely solely on potential or current inaccurate for determining the battery's state of health (SOH) and incapable of fully assessing the true performance of nickel-rich lithium batteries. Therefore, there is an urgent need for methods that can deeply analyze battery performance, particularly under the significant influence of polarization. Battery state of health (SOH) is a crucial indicator for evaluating battery performance and lifespan. Accurate SOH assessment enables users to understand the battery's health status promptly, enabling them to make informed decisions about battery usage and replacement, thereby improving battery efficiency and safety. However, traditional SOH assessment methods, which primarily rely on simple voltage and current measurements, struggle to maintain high accuracy under complex polarization conditions. Summary of the Invention

[0004] The present invention proposes a method for determining the health status of nickel-rich lithium batteries based on incremental capacity analysis to solve the problems existing in the above-mentioned prior art.

[0005] To achieve the above objectives, the present invention provides a method for determining the health status of nickel-rich lithium batteries based on incremental capacity analysis, comprising the following steps:

[0006] Obtain constant current charge and discharge data of ternary lithium-ion batteries in full charge and discharge state;

[0007] Obtaining an IC curve based on the constant current charge and discharge data, and extracting key features from the IC curve;

[0008] Constructing a fitting function, inputting the key features into the fitting function, and obtaining a fitting curve;

[0009] The IC curve is fitted with a fitting curve to obtain a goodness of fit, and the battery health state is determined based on the goodness of fit.

[0010] Preferably, the key features include the area enclosed by the first peak and the abscissa axis, the maximum half-peak width of the first peak and the symmetry center of the peak.

[0011] Preferably, the fitting function expression is:

[0012]

[0013] Where, is the dependent variable, A is the area enclosed by the first peak and the abscissa axis, ω is the maximum half-peak width of the first peak, V0 is the symmetric center of the peak, and V is the voltage.

[0014] Preferably, judging the battery health state according to the goodness of fit includes:

[0015] When the goodness of fit R 2 When the goodness of fit R is within the range of [0.9, 1.0], the battery health status is qualified; when the goodness of fit R is within the range of [0.9, 1.0], the battery health status is qualified. 2 When the value is in the range of [0,0.9), the battery health status is unqualified.

[0016] The present invention also discloses a nickel-rich lithium battery health status judgment system based on incremental capacity analysis method, comprising:

[0017] A data acquisition module is used to obtain constant current charge and discharge data of the ternary lithium-ion battery in a fully charged and discharged state;

[0018] a feature extraction module, configured to obtain an IC curve based on the constant current charge and discharge data, and extract key features from the IC curve;

[0019] A curve construction module is used to construct a fitting function, input the key features into the fitting function, and obtain a fitting curve;

[0020] The judgment module is used to fit the IC curve with the fitting curve to obtain the goodness of fit, and judge the battery health state according to the goodness of fit.

[0021] The present invention also discloses a computer device, comprising a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method.

[0022] The present invention also discloses a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the method are implemented.

[0023] The present invention also discloses a computer program product, comprising a computer program, which implements the steps of the method when executed by a processor.

[0024] Compared with the prior art, the present invention has the following advantages and technical effects:

[0025] The present invention discloses a method for determining the health of nickel-rich lithium batteries based on incremental capacity analysis. The method comprises the following steps: obtaining constant current charge and discharge data of a ternary lithium-ion battery in a fully charged and discharged state; obtaining an IC curve based on the constant current charge and discharge data, and extracting key features from the IC curve; constructing a fitting function, inputting the key features into the fitting function, and obtaining a fitting curve; fitting the IC curve to the fitting curve to obtain a goodness of fit, and determining the battery health status based on the goodness of fit. The present invention can accurately capture the dynamic reactions of a battery during charging, particularly when polarization significantly affects it, providing more refined battery performance analysis with higher accuracy than traditional methods.

[0026] The present invention uses an incremental capacity curve to perform health judgment, reduces the probability of battery runaway under high load or abnormal conditions, and improves battery safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of this application. The exemplary embodiments and descriptions of this application are intended to explain this application and do not constitute an improper limitation on this application. In the accompanying drawings:

[0028] Figure 1 is a flow chart of a method according to an embodiment of the present invention;

[0029] Figure 2 Graph showing coulombic efficiency of two batteries according to an embodiment of the present invention versus cycle number;

[0030] Figure 3 This is a fitting effect diagram of the battery under test in Experiment 1 of an embodiment of the present invention;

[0031] Figure 4 This is a fitting effect diagram of the battery under test in Experiment 2 of an embodiment of the present invention. DETAILED DESCRIPTION

[0032] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0033] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0034] Incremental Capacity Analysis (ICA) based on constant-current charging data is a common data-driven approach for battery SOH estimation, providing a relatively intuitive and effective state-of-health assessment. The ICA method, which converts voltage plateaus into observable peaks, is more commonly used in practical applications. The peaks and valleys of the IC curve are used to analyze various aging mechanisms, such as lithium inventory loss and active material loss.

[0035] The present invention proposes a model-based method for estimating the state of health (SOH) of nickel-rich lithium batteries. This method analyzes and fits the IC curve and establishes a voltage-capacity model based on the Lorentzian function to simulate the dynamic reaction of the battery during the charging process. This model can accurately capture the voltage characteristics of nickel-rich lithium batteries that reflect material-level phase change phenomena, providing a new approach for estimating SOH. According to this method, the IC curve is first analyzed from the voltage and capacity data collected during the constant current charging process to obtain representative features (FOI). These FOIs include the curve of battery voltage change over time, the capacity change trend, and the kinetic parameters of the electrochemical reaction. This information can not only be used to analyze the health status of the battery, but also reveal the performance of the battery under different operating conditions. This process reveals the relationship between the various features through statistical methods to ensure that the extracted features can indeed provide meaningful information for SOH estimation.

[0036] In addition, inside the nickel-rich ternary lithium battery, Ni 2+ Easily oxidized to Ni 3+, which is the primary source of the battery's charge capacity. When fitting the model, it is crucial to pay special attention to the first peak of the function, as this reflects the actual redox state of the battery's transition metals, allowing for a more accurate assessment of the battery's operating health. The proposed health assessment method based on the Lorentzian function not only demonstrates excellent accuracy but also excellent adaptability to diverse battery operating conditions. Even under initial aging conditions and complex cycling conditions, the method effectively captures the battery's operating characteristics. This highly accurate health assessment can help battery management systems optimize charging strategies, improve charging efficiency, and reduce energy loss. This has significant practical significance for the development of fields such as electric vehicles and energy storage systems, particularly in scenarios where batteries are frequently used, ensuring their safety and economic efficiency. The ICA-based polarization determination method for nickel-rich lithium batteries provides important support for the safe, economical, and efficient use of nickel-rich lithium batteries. This innovative method significantly enhances the intelligence of battery management systems and promotes the advancement of related technologies.

[0037] In summary, nickel-rich lithium batteries hold broad application prospects in electric transportation and renewable energy. Accurately assessing the battery's SOH during operation is crucial to realizing this potential. By applying a newly developed SOH estimation method based on the Lorentzian function, we can gain a deeper understanding of battery operating mechanisms, overcome the limitations of traditional methods, and drive innovation in battery management technology. This will not only promote technological advancements in electric vehicles and energy storage systems, enabling safer and more efficient energy management, but also make a significant contribution to achieving a sustainable, green future. With continued technological advancements, future electric vehicles and energy storage systems will reach new heights in efficiency, safety, and overall affordability.

[0038] Example 1

[0039] like Figure 1 As shown, this embodiment provides a method for determining the health status of a nickel-rich lithium battery based on an incremental capacity analysis method, comprising the following steps:

[0040] Obtain constant current charge and discharge data of ternary lithium-ion batteries in full charge and discharge state;

[0041] Obtaining an IC curve based on the constant current charge and discharge data, and extracting key features from the IC curve;

[0042] Constructing a fitting function, inputting the key features into the fitting function, and obtaining a fitting curve;

[0043] The IC curve is fitted with a fitting curve to obtain a goodness of fit, and the battery health state is determined based on the goodness of fit.

[0044] The fitting function expression is:

[0045]

[0046] Where, is the dependent variable, A is the area enclosed by the first peak and the abscissa axis, ω is the maximum half-peak width of the first peak, V0 is the symmetric center of the peak, and V is the voltage.

[0047] This study collected a large amount of constant-current charge-discharge data from ternary lithium-ion batteries under full charge and discharge conditions to verify that the fitted function closely matches the battery's SOH. The function is defined as follows: dQ / dV is the dependent variable, A is the area enclosed by the first peak and the abscissa, ω is the maximum half-maximum width of the first peak, and V0 is the symmetric center of the peak. The IC curves obtained from actual measurements were then compared with the fitted function.

[0048] Furthermore, set the range of fitting degree:

[0049] Definition: When the function fitting equation is brought in, the goodness of fit range is R 2 =[0.9,1.0], the battery health status is qualified. When the function fitting equation is put into it, the goodness of fit range is R 2 =[0,0.9) The battery health status is unqualified.

[0050] This embodiment carried out the following two experiments:

[0051] Experiment 1:

[0052] Step 1: Prepare a Xinwei charge and discharge instrument, model CT-4008Tn-5v50Ma-HWX. Take a CR2032 button-type nickel-rich lithium-ion battery to be tested as the experimental material; Step 2: Connect the nickel-rich lithium-ion battery to be tested to the charge and discharge instrument, set the charge cut-off voltage to 4.3V (the relative potential of lithium), and the discharge cut-off voltage to 2.8V; Step 3: Perform 20 cycles of constant current charge and discharge on the lithium battery to be tested, and record and organize the IC curve; Step 4: Substitute the area enclosed by the first oxidation peak in the IC curve A = 0.09402, the maximum half-peak width ω = 0.13964, and the peak symmetry center V0 = 3.6995 into the function expression Step 5: In the software Origin, enter the nonlinear function to draw a graph and fit it with the IC curve. Draw the images before and after fitting on a table to judge the fitting effect. Step 6: According to the set health status fitting effect range, if the range of goodness of fit with this function is R 2 =[0.9,1.0], the battery is safe, otherwise, the battery under test is in a dangerous state; Step 7, the fitting effect of the battery under test in this example is as follows Figure 3 As shown, the goodness of fit is 0.6577, which is outside the safety range. Therefore, the conclusion is given: at the ninth cycle, the health status of the lithium battery is unqualified.

[0053] Experiment 2:

[0054] Step 1: Prepare a Xinwei charge and discharge instrument, model CT-4008Tn-5v50Ma-HWX. Take a CR2032 nickel-rich button-type lithium-ion battery to be tested as the experimental object; Step 2: Connect the nickel-rich lithium-ion battery to be tested to the charge and discharge instrument, set the charge cut-off voltage to 4.3V (the relative potential of lithium) and the discharge cut-off voltage to 2.8V; Step 3: Perform 20 cycles of constant current charge and discharge on the lithium battery to be tested, and record and organize the IC curve; Step 4: Substitute the area enclosed by the first oxidation peak in the IC curve A = 0.06548, the maximum half-peak width ω = 0.0423, and the peak's symmetric center V0 = 3.8264 into the function expression Step 5: In the software Origin, enter the nonlinear function to draw a graph and fit it with the IC curve. Draw the images before and after fitting on a table to judge the fitting effect. Step 6: According to the set health status fitting effect range, if the range of goodness of fit with this function is R 2 =[0.9,1.0], the battery under test is safe, otherwise, the battery under test is in a dangerous state; Step 7, the fitting effect of the battery under test in this example is as follows Figure 4 As shown, the goodness of fit is 0.94047, which is outside the safety range. Therefore, it is concluded that the health status of the lithium battery is qualified at the ninth cycle.

[0055] It is known that Experiment 1 is the ninth cycle condition of lithium battery A under full charge and discharge conditions, and Experiment 2 is the ninth cycle condition of lithium battery B under full charge and discharge conditions. After multiple function fittings, we get the function fitting effect diagram, as shown in the figure below: Figure 3 、 Figure 4 As shown. By goodness of fit R 2 To judge the quality of the fitting effect, Figure 3 At this time, the goodness of fit R 2 It is 0.6577. Figure 4 At this time, the goodness of fit R 2 The value is 0.94047. Therefore, we can conclude that the battery health in Experiment 1 is unqualified, while the battery health in Experiment 2 is qualified. This method improves the accuracy of identification and reduces the possibility of misjudgment.

[0056] Feasibility verification:

[0057] The coulombic efficiency of a lithium battery refers to the ratio of the battery's charging capacity to its actual discharge capacity. In the past, the coulombic efficiency of a battery was used to roughly judge the health of the battery. Although this method cannot accurately judge the health of the battery under complex conditions, it can also be used to verify the feasibility of this patented method. It is known that Experiment 1 is the ninth cycle condition of lithium battery A, and Experiment 2 is the ninth cycle condition of lithium battery B. Figure 2 As shown, the Coulombic efficiency in Experiment 1 was 96.86%, and the Coulombic efficiency in Experiment 2 was 97.76%. It is obvious that the Coulombic efficiency in Experiment 2 was greater than that in Experiment 1, and the health condition was also better than that in Experiment 1. This is consistent with the conclusions drawn from the method of this patent and confirms the feasibility of this patent.

[0058] Example 2

[0059] This embodiment also provides a nickel-rich lithium battery health status judgment system based on incremental capacity analysis method, including:

[0060] A data acquisition module is used to obtain constant current charge and discharge data of the ternary lithium-ion battery in a fully charged and discharged state;

[0061] a feature extraction module, configured to obtain an IC curve based on the constant current charge and discharge data, and extract key features from the IC curve;

[0062] A curve construction module is used to construct a fitting function, input the key features into the fitting function, and obtain a fitting curve;

[0063] The judgment module is used to fit the IC curve with the fitting curve to obtain the goodness of fit, and judge the battery health state according to the goodness of fit.

[0064] Example 3

[0065] This embodiment further provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method.

[0066] Example 4

[0067] This embodiment further provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when executed by a processor.

[0068] Example 5

[0069] This embodiment also provides a computer program product, including a computer program, which implements the steps of the method when executed by a processor.

[0070] Compared with the existing technology, this technical solution has the following significant advantages:

[0071] The present invention adopts a voltage-capacity model based on the Lorentzian function for SOH estimation, which can accurately capture the dynamic response of the battery during the charging process, especially when the polarization phenomenon has a significant impact, and provide a more detailed battery performance analysis, which has higher accuracy than traditional methods.

[0072] The present invention can maintain good performance and high accuracy even under different charging and discharging conditions (such as rapid charging and high-load discharge). This feature makes it suitable for a variety of operating environments and helps to better manage battery life and performance in practical applications.

[0073] The model of the present invention can adapt to different types and brands of nickel-rich ternary lithium batteries and has strong versatility. This flexibility makes the method easy to apply to multiple battery types.

[0074] The present invention uses an incremental capacity curve to perform health judgment, reduces the probability of battery runaway under high load or abnormal conditions, and improves battery safety.

[0075] By analyzing the polarization characteristics of the battery, the present invention can help users or management systems adjust the charging current and charging time in real time, optimize the battery's charge and discharge efficiency, and improve the battery's overall performance.

[0076] The present invention combines the charging capacity incremental capacity analysis method, and the new polarization degree judgment method can provide accurate data support for the battery management system (BMS), enabling it to manage the battery status more intelligently, achieve dynamic adjustment, and improve battery management efficiency and user experience.

[0077] By quantifying the degree of polarization and using mathematical models to make judgments, the present invention can significantly simplify the battery status monitoring process, improve detection efficiency, reduce maintenance costs, and make online battery monitoring more convenient compared to previous complex testing methods based on ICA.

[0078] From the above advantages, it can be seen that the present invention has broad application prospects in the field of nickel-rich lithium batteries:

[0079] 1. Production quality assessment of lithium-ion batteries: This method can effectively assess the polarization degree of lithium-ion batteries, providing battery manufacturers with accurate health status monitoring, optimizing design and production processes, and improving product quality.

[0080] 2. Improved electric vehicle performance: By applying this method to the battery management system of electric vehicles, the health of the battery can be monitored in real time, thereby adjusting the charging strategy in a targeted manner to improve the overall performance, mileage and service life of the battery.

[0081] 3. Energy storage system optimization: During the operation of an electrochemical energy storage system, this method can effectively determine the health of the battery, help the management system optimize the charging and discharging strategy, extend the system's service life, and improve energy utilization efficiency.

[0082] The implementation of this invention can significantly advance the development of lithium-ion battery technology and meet market demands for battery health management. This method, based on incremental capacity analysis, significantly improves the accuracy of conclusions, facilitating large-scale battery polarization state monitoring and processing, thereby enhancing the economic benefits and sustainable development of lithium-ion batteries and related industries. With the continued development of electric vehicles and energy storage technologies, the market application prospects of this method will be even broader, bringing significant social and economic benefits.

[0083] The above are merely preferred embodiments of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for judging the health of nickel-rich lithium batteries based on incremental capacity analysis, characterized in that: The following steps are involved: Obtain constant current charge and discharge data of ternary lithium-ion batteries in full charge and discharge state; Obtaining an IC curve based on the constant current charge and discharge data, and extracting key features from the IC curve; The key features include the area enclosed by the first peak and the abscissa axis, the maximum half-peak width of the first peak and the symmetric center of the peak; Constructing a fitting function, inputting the key features into the fitting function, and obtaining a fitting curve; The fitting function expression is: Where, is the dependent variable, A is the area enclosed by the first peak and the abscissa axis, ω is the maximum half-peak width of the first peak, V0 is the symmetric center of the peak, and V is the voltage; The IC curve is fitted with a fitting curve to obtain a goodness of fit, and the battery health state is determined based on the goodness of fit.

2. The method according to claim 1, characterized in that Judging the battery health status based on goodness of fit includes: When the goodness of fit range is within [0.9, 1.0], the battery health state is qualified; when the goodness of fit range is within [0, 0.9), the battery health state is unqualified.

3. A nickel-rich lithium battery health status judgment system based on incremental capacity analysis method, characterized in that: include: A data acquisition module is used to obtain constant current charge and discharge data of the ternary lithium-ion battery in a fully charged and discharged state; a feature extraction module, configured to obtain an IC curve based on the constant current charge and discharge data, and extract key features from the IC curve; The key features include the area enclosed by the first peak and the abscissa axis, the maximum half-peak width of the first peak and the symmetric center of the peak; A curve construction module is used to construct a fitting function, input the key features into the fitting function, and obtain a fitting curve; The fitting function expression is: Where, is the dependent variable, A is the area enclosed by the first peak and the abscissa axis, ω is the maximum half-peak width of the first peak, V0 is the symmetric center of the peak, and V is the voltage; The judgment module is used to fit the IC curve with the fitting curve to obtain the goodness of fit, and judge the battery health state according to the goodness of fit.

4. A computer device comprising a memory, a processor, and a computer program stored in the memory, wherein: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 2.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 2 are implemented.

6. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 2 are implemented.

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