Method for judging health degree of nickel-rich lithium battery based on incremental capacity analysis method

Abstract

The invention discloses a method for judging the health degree of a nickel-rich lithium battery based on an incremental capacity analysis method. The method comprises the following steps: acquiring constant-current charging and discharging data of a ternary lithium ion battery in a complete charging and discharging state; obtaining an IC curve based on the constant-current charging and discharging data, and extracting key features from the IC curve; constructing a fitting function, and inputting the key features into the fitting function to obtain a fitting curve; and fitting the IC curve and the fitting curve to obtain the goodness of fit, and judging the health state of the battery according to the goodness of fit. According to the method, the dynamic reaction of the battery in the charging process can be accurately captured, particularly under the condition of obvious influence of a polarization phenomenon, finer battery performance analysis is provided, and compared with a traditional method, the method has higher accuracy.

Description

Technical Field

[0001] The 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 increase 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 transformation. 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 to promote 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 the passage of current during the battery charge and discharge process. This phenomenon can be divided into several different types, the most important of which include electrochemical polarization, concentration polarization, and ohmic polarization. These polarization phenomena directly affect the energy saving and safety performance of the battery, especially in the case of high-power discharge or fast charging. The existence of polarization makes the traditional method of relying solely on potential or current in judging the health state of the battery less accurate and unable to fully evaluate the true performance of nickel-rich lithium batteries. Therefore, there is an urgent need for a method that can deeply analyze battery performance, especially performance evaluation under the significant influence of polarization phenomena. The state of health (SOH) of the battery is an important indicator for evaluating battery performance and life. Accurate SOH evaluation enables users to understand the health status of the battery in a timely manner, so as to make reasonable use and replacement decisions and improve the efficiency and safety of the battery. However, traditional SOH evaluation methods mainly rely on simple voltage and current measurements, which are difficult to maintain high accuracy in the face of complex polarization conditions. Summary of the invention

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

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

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

[0007] Acquire an IC curve based on the constant current charge and discharge data, and extract 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 the fitting curve to obtain the goodness of fit, and the battery health state is judged according to 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] In the formula, 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; 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 a ternary lithium-ion battery in a fully charged and discharged state;

[0018] A feature extraction module, used 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 judging the health of a nickel-rich lithium battery based on an incremental capacity analysis method, comprising 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 with the fitting curve, obtaining the goodness of fit, and judging the battery health state according to the goodness of fit. The present invention 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 sophisticated battery performance analysis, which has higher accuracy than traditional methods.

[0026] The present invention uses an incremental capacity curve to make health judgments, thereby reducing the probability of battery runaway under high load or abnormal conditions and improving battery safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

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

[0029] Figure 2 The coulombic efficiency of two batteries according to the embodiment of the present invention varies with the number of cycles;

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

[0031] Figure 4 This is a fitting effect diagram of the battery to be tested 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 in the embodiments of the present 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] The incremental capacity analysis (ICA) method based on constant current charging data is a commonly used data-driven method for battery SOH estimation, which can provide a more intuitive and effective health status assessment. The ICA method that converts the voltage platform into an observable peak 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 SOH of nickel-rich lithium batteries. The 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 idea for estimating SOH. According to this method, first, an IC curve analysis is performed 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 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 main source of battery charging capacity. When fitting the model, it is crucial to pay special attention to the first peak of the function, because this can reflect the actual redox state of the transition metal of the battery, thereby more accurately evaluating the working health of the battery. The proposed health status assessment method based on the Lorentzian function not only performs well in accuracy, but also shows excellent adaptability to different battery operating conditions. Even in the initial aging state and complex cycle conditions, this method can effectively capture the operating characteristics of the battery. This high-precision health status assessment can help the battery management system optimize the charging strategy, improve charging efficiency and reduce energy loss. It has great practical significance for the development of electric vehicles and energy storage systems, especially in scenarios where batteries are frequently used, it can ensure the safety and economy of batteries. The polarization judgment method of nickel-rich lithium batteries based on ICA provides important support for the safe, economical and efficient use of nickel-rich lithium batteries. This innovative method significantly improves the intelligence level of battery management systems and promotes the advancement of related technologies.

[0037] In summary, nickel-rich lithium batteries have broad application prospects in the fields of electric transportation and renewable energy, and accurate evaluation of SOH during battery operation is the key to realizing its potential. By using the newly developed SOH estimation method based on the Lorentzian function, we can deeply understand the working mechanism of the battery, overcome the limitations of traditional methods, and promote changes in battery management technology. This will not only promote the technological progress of electric vehicles and energy storage systems, help achieve safer and more efficient energy management, but also make important contributions to achieving a sustainable green future. With the continuous advancement of technology, future electric vehicles and energy storage systems will reach new heights in efficiency, safety and overall economy.

[0038] Embodiment 1

[0039] like Figure 1 As shown, this embodiment provides a method for judging 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] Acquire an IC curve based on the constant current charge and discharge data, and extract 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 the fitting curve to obtain the goodness of fit, and the battery health state is judged according to the goodness of fit.

[0044] The fitting function expression is:

[0045]

[0046] In the formula, 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] The present invention verifies that the fitting function has a high degree of fit with the battery's SOH by collecting a large amount of constant current charge and discharge data of ternary lithium-ion batteries in a fully charged and discharged state. The function is defined as follows: dQ / dV 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, and V0 is the symmetric center of the peak. The IC curve obtained by actual measurement is used to optimize and compare with the fitting function relationship.

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

[0049] Definition: When the function is inserted into the fitting equation, the goodness of fit range is R 2 =[0.9,1.0], the battery health status is qualified. When the function fitting equation is substituted, 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 (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 sort out the IC curve; Step 4: Substitute the area A=0,09402, the maximum half-peak width ω=0,13964, and the symmetry center V0=3.6995 of the first oxidation peak in the IC curve into the function expression Step 5: In the software Origin, enter the nonlinear function formula 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, it is concluded that the health status of the lithium battery is unqualified at the ninth cycle.

[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 (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 sort out the IC curve; Step 4: Substitute the area A=0,06548, the maximum half-peak width ω=0,0423, and the symmetry center V0=3.8264 of the first oxidation peak in the IC curve into the function expression Step 5: In the software Origin, enter the nonlinear function formula 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 at the ninth cycle, the health status of the lithium battery is qualified.

[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, such as 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 is 0.94047. Therefore, it can be judged that the health of the battery in Experiment 1 is unqualified, while the health of the battery 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 the 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 is 96.86%, and the coulombic efficiency in experiment 2 is 97.76%. It is obvious that the coulombic efficiency of experiment 2 is greater than that of experiment 1, and the health condition is also better than that of experiment 1. This is consistent with the conclusion drawn by the method of this patent, confirming the feasibility of this patent.

[0058] Embodiment 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 a ternary lithium-ion battery in a fully charged and discharged state;

[0061] A feature extraction module, used 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] Embodiment 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] Embodiment 4

[0067] This embodiment also provides 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.

[0068] Embodiment 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 prior art, this technical solution has the following significant advantages:

[0071] The present invention adopts a voltage-capacity model based on the Lorentzian function to estimate SOH, 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 show high accuracy even under different charging and discharging conditions (such as fast 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 enables the method to be conveniently applied to a variety of battery types.

[0074] The present invention uses an incremental capacity curve to make health judgments, thereby reducing the probability of battery runaway under high load or abnormal conditions and improving battery safety.

[0075] The present invention can help users or management systems adjust charging current and charging time in real time by analyzing the polarization characteristics of the battery, thereby optimizing the charging and discharging efficiency of the battery and improving the overall performance of the battery.

[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 the battery management efficiency and user experience.

[0077] The present invention quantifies the polarization degree and uses a mathematical model for judgment. Compared with the previous complex testing methods based on ICA, this method can significantly simplify the battery status monitoring process, improve detection efficiency, reduce maintenance costs, and make online monitoring of batteries more convenient.

[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, provide accurate health status monitoring for battery manufacturers, optimize design and production processes, and improve product quality.

[0080] 2. Improvement of electric vehicle performance: By applying this method in the battery management system of electric vehicles, the health of the battery can be monitored in real time, so as to adjust the charging strategy in a targeted manner and improve the overall performance, driving range and service life of the battery.

[0081] 3. Energy storage system optimization: During the operation of the 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 service life of the system, and improve energy utilization efficiency.

[0082] Through the implementation of the present invention, the development of lithium-ion battery technology can be significantly promoted to meet the market demand for battery health management. The method is based on the incremental capacity analysis method, and the accuracy of the conclusion is greatly improved, which is conducive to large-scale battery polarization state monitoring and processing, thereby improving the economic benefits and sustainable development of lithium-ion batteries and related industries. With the continuous development of electric vehicles and energy storage technology, the market application prospects of this method will be broader, bringing significant social and economic benefits.

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

Claims

1. A method for judging the health of a nickel-rich lithium battery 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; Acquire an IC curve based on the constant current charge and discharge data, and extract key features from the IC curve; Constructing a fitting function, inputting the key features into the fitting function, and obtaining a fitting curve; The IC curve is fitted with the fitting curve to obtain the goodness of fit, and the battery health state is judged according to the goodness of fit.

2. The method according to claim 1, characterized in that 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.

3. The method according to claim 1, characterized in that The fitting function expression is: In the formula, 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.

4. 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.

5. 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 a ternary lithium-ion battery in a fully charged and discharged state; A feature extraction module, used to obtain an IC curve based on the constant current charge and discharge data, and extract key features from the IC curve; 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 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.

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

7. 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 4 are implemented.

8. 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 4 are implemented.

Images