Lithium ion battery capacity fading analysis method based on reaction kinetics theory

Abstract

The invention discloses a lithium ion battery capacity attenuation analysis method based on a reaction kinetics theory, and belongs to the field of lithium ion battery degradation attenuation analysis. The method comprises the following steps: describing a lithium ion battery performance degradation process based on a reaction kinetics theory, and discriminating key influence factors of a battery capacity fading link; establishing a lithium ion battery degradation model according to the screened key influence factors of the battery capacity fading link, and realizing differential characterization of the battery degradation process under the action of different influence factors; and carrying out simulation analysis on the attenuation process of the lithium ion battery under the action of different influence factors so as to verify the effectiveness of the lithium ion battery degradation model. The model provided by the invention can differentially represent the influence of different degradation factors on battery attenuation, and provides theoretical support for subsequent battery state evaluation and life prediction.

Description

Technical Field

[0001] The invention relates to a lithium ion battery capacity attenuation analysis method based on reaction kinetics theory, and belongs to the field of lithium ion battery degradation analysis. Background Art

[0002] Lithium-ion batteries have been widely used in electric vehicles, portable electronic devices, and new energy storage devices due to their advantages such as high specific energy, high specific power, and low self-discharge rate. Its working principle is to achieve the charging and discharging process by controlling the directional movement of electrons between the positive and negative electrodes. The battery capacity is directly related to the number of free electrons inside. However, due to the chemical reaction characteristics between the electrodes and the electrolyte, the battery performance will gradually decay with the increase of the number of charge and discharge cycles. Under the background of the national "dual carbon" strategy, the large-scale application of lithium-ion batteries makes it of great significance to conduct in-depth research on their attenuation characteristics.

[0003] At present, the battery capacity attenuation modeling and analysis mainly include actual measurement analysis method and simulation analysis method. The actual measurement analysis method studies the battery attenuation process by repeatedly charging and discharging the sample and recording the capacity data. However, this method only records the attenuation phenomenon under different conditions, lacks in-depth analysis of the capacity change trend, and the test results are overly dependent on the sample characteristics and lack generalization ability. At the same time, its time-consuming and high-cost testing characteristics also limit the promotion and application of the method. The use of mathematical models for battery loss assessment is another important means, which can effectively overcome the time and cost disadvantages of the actual measurement analysis method. However, although this type of model can accurately reflect the internal process of battery loss, it has many parameters and a complex structure, which brings greater calculation pressure and difficulty in solving in the modeling process. Summary of the invention

[0004] The present invention provides a lithium-ion battery capacity decay analysis method based on reaction kinetics theory. Based on the reaction kinetics theory, the performance degradation process of lithium-ion batteries is described, the key influencing factors of battery capacity decay are identified, and a lithium-ion battery degradation model is constructed to achieve differentiated characterization of lithium-ion battery loss, and simulation verification is carried out. The results show that the proposed model can differentiate the effects of different degradation factors on battery decay, providing theoretical support for subsequent battery status evaluation and life prediction.

[0005] The technical solution of the present invention is:

[0006] According to a first aspect of the present invention, a method for analyzing capacity decay of a lithium-ion battery based on reaction kinetics theory is provided, comprising the following steps:

[0007] Describe the performance degradation process of lithium-ion batteries based on reaction kinetics theory and identify the key influencing factors of battery capacity attenuation;

[0008] Based on the identified key influencing factors of battery capacity attenuation, a lithium-ion battery degradation model is established to achieve differentiated characterization of the battery degradation process under different influencing factors;

[0009] A simulation analysis is carried out on the attenuation process of lithium-ion batteries under different influencing factors to verify the effectiveness of the proposed lithium-ion battery degradation model.

[0010] Furthermore, based on the reaction kinetics theory, the performance degradation process of lithium-ion batteries is described, and the key influencing factors of battery capacity attenuation are identified, including: temperature, discharge rate, and discharge depth.

[0011] Furthermore, based on the identified key influencing factors of battery capacity attenuation, a lithium-ion battery degradation model is established, specifically:

[0012] First, the temperature loss characterization model

[0013]

[0014] In the formula, Q loss,T Indicates the effect of temperature on battery capacity loss; T indicates ambient temperature; A indicates pre-exponential factor; E a represents activation energy, i.e., the threshold for chemical reaction to occur; R represents the ideal gas constant; z represents the power law factor; t represents the cycle time;

[0015] Second, the discharge rate loss characterization model

[0016] Q loss,c-rate =I×k1×t z

[0017] In the formula, Q loss,c-rate Indicates the effect of discharge rate on battery capacity loss; I indicates the maximum discharge current; k1 indicates the linear correlation coefficient; Third, the discharge depth loss characterization model

[0018]

[0019] n=kT h (k=1,2,3,...∞);

[0020] In the formula, Q loss,DOD (n) represents the effect of discharge depth on battery capacity loss; T h is the half cycle time; Q BOL represents the initial capacity; Q EOL represents the battery capacity at the end of life; ε(n) represents the battery degradation caused by the depth of discharge.

[0021] According to a second aspect of the present invention, a lithium-ion battery capacity decay analysis system based on reaction kinetics theory is provided, comprising a module of any one of the lithium-ion battery capacity decay analysis methods based on reaction kinetics theory described above.

[0022] According to a third aspect of the present invention, a processor is provided, the processor being used to run a program, wherein when the program is run, any one of the above-mentioned lithium-ion battery capacity decay analysis methods based on reaction kinetics theory is executed.

[0023] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the above-mentioned lithium-ion battery capacity decay analysis methods based on reaction kinetics theory.

[0024] The beneficial effects of the present invention are as follows: the present invention combines the battery capacity decay mechanism with the reaction kinetics theory to evaluate the degradation mechanism of lithium-ion batteries; by establishing a corresponding degradation model, it realizes the accurate characterization of the effects of different aging factors such as temperature, discharge rate, and discharge depth on battery life; the model reveals the relationship between battery capacity decay and changes in electrochemical characteristics, and provides a theoretical basis for predicting and extending battery life. The simulation results show that temperature, discharge rate, and discharge depth will accelerate the reaction process inside the battery, causing the loss of lithium ions and active materials, and accelerating the aging rate of the battery. And under the same conditions for the selected battery, the effects of discharge rate, temperature, and discharge depth on battery capacity gradually weaken. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is the overall flow chart of the present invention;

[0026] Figure 2 This is a framework diagram for analyzing capacity degradation of lithium-ion batteries;

[0027] Figure 3 This is a graph showing the effect of different temperatures on lithium-ion battery degradation;

[0028] Figure 4 This is a graph showing the effect of different discharge rates on lithium-ion battery degradation;

[0029] Figure 5 This is a graph showing the effect of different discharge depths on lithium-ion battery degradation. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. It should be noted that the embodiments in this application and the features in the embodiments can be combined with each other arbitrarily without conflict.

[0031] Example 1: Figure 1-5 As shown, according to a first aspect of an embodiment of the present invention, a method for analyzing capacity decay of a lithium-ion battery based on reaction kinetics theory is provided, comprising the following steps:

[0032] Step 1: Describe the performance degradation process of lithium-ion batteries based on reaction kinetics theory and identify the key influencing factors of battery capacity attenuation;

[0033] Step 2: Based on the identified key influencing factors of battery capacity attenuation, a lithium-ion battery degradation model is established to achieve differentiated characterization of the battery degradation process under different influencing factors;

[0034] Step 3: Carry out simulation analysis on the lithium-ion battery attenuation process under different influencing factors to verify the effectiveness of the proposed lithium-ion battery degradation model.

[0035] The specific description of step 1 is as follows:

[0036] The charge and discharge cycle of lithium-ion batteries is essentially a directional migration process of lithium ions between the positive electrode and the negative electrode. During the charging process, the external power source causes the lithium ions in the positive electrode material (LiCoO2) to escape, migrate through the electrolyte and embed into the interlayer of the negative electrode material graphite (C6). During discharge, the battery is connected to the circuit, and the lithium ions in the negative electrode material migrate back to the positive electrode through the electrolyte, releasing the stored chemical energy and converting it into electrical energy. Given the chemical reaction characteristics between the electrodes and the electrolyte of lithium-ion batteries, during repeated charge and discharge processes, the electrode materials and the electrolyte undergo side reactions, and the electrode structure gradually changes. These factors together cause the battery capacity to decay as the number of cycles increases.

[0037] Based on existing research, it is shown that the capacity of lithium-ion batteries depends on the amount of internal circulatory lithium ions and active materials. As the number of battery charge and discharge cycles increases, the loss of circulatory lithium ions (LLI) and the loss of active materials (LAM) jointly lead to a decrease in battery capacity, which can be described specifically as:

[0038] Q loss =Q LAM +Q LLI ;

[0039] Among them, Qloss Indicates capacity loss. In the battery working process, negative electrode graphite peeling, metal dissolution and active material corrosion will cause LAM, while LLI is caused by the formation and continuous thickening of the solid electrolyte interface SEI (solid electrolyte interface) film and lithium deposition. Among them, SEI growth is considered to be the main aging mechanism in most cases. Specifically, the SEI film is a thin film produced by the interaction between lithium ions and electrolytes on the surface of the electrode material during the first charge and discharge of the battery. It can effectively prevent direct contact between the electrode and the electrolyte and reduce the occurrence of side reactions. However, the increase in the thickness of the SEI film will cause a decrease in the number of lithium ions, resulting in battery capacity decay. At the same time, due to the instability of the SEI film, it will break and then reform, further consuming the lithium ions in the battery, thereby accelerating the degradation of the battery capacity, which can be described as:

[0040]

[0041] Among them, Q SEIform and Q SEIre-form They represent the capacity loss caused by SEI formation and SEI damage and regeneration process respectively; F represents the Faraday constant; L neg Indicates the thickness of the negative electrode; ε s,neg represents the volume fraction of the negative electrode solid phase; c SEIform and c SEIre-form Respectively represent the lithium ions consumed in the SEI formation and SEI damage regeneration process; dA neg Represents the unit cross-sectional area of ​​the negative electrode. In summary, the capacity decay of the battery can be described as:

[0042] Q loss =Q LAM +Q SEIform +Q SEIre-form ;

[0043] The growth of SEI film is significantly dependent on temperature. The increase in temperature will accelerate the movement of ions and the rate of chemical reactions inside the battery, resulting in rapid thickening of the SEI film. At the same time, the SEI film will be decomposed into loose particles, weakening its protective effect and exacerbating lithium ion loss. In addition, high temperature environment will also cause electrode material damage and loss of active substances, further accelerating capacity decay. At the same time, the increase in discharge rate will also affect the stability of the SEI film. The increase in discharge rate not only increases the local current density and electrochemical reaction rate at the anode-electrolyte interface, but also generates greater mechanical stress on the surface of the electrode particles, resulting in SEI film damage and loss of active substances. In addition, the increase in temperature during high-rate discharge will further aggravate this effect. As another key factor, the increase in discharge depth will significantly increase the internal stress and chemical reaction intensity of the battery. Excessive discharge depth will cause drastic changes in the structure of the electrode material, resulting in loss of active substances, and ultimately leading to rapid capacity decay.

[0044] In summary, external factors such as temperature, discharge rate and discharge depth jointly determine the capacity decay process of the battery by affecting the stability of the SEI film, the integrity of the electrode structure and the kinetics of the electrochemical reaction.

[0045] The lithium-ion battery degradation model established in step 2 is as follows:

[0046] Based on the relationship between discharge rate, discharge depth, current and state of charge, the present invention uses different temperatures, currents and states of charge as input parameters to establish a mathematical description of the change in battery capacity under different conditions, thereby evaluating the impact of different factors on battery performance.

[0047] First, the temperature loss characterization model

[0048] The effect of temperature on battery loss is mainly reflected in the impact on the diffusion rate of lithium ions inside the battery, which causes changes in the internal chemical reaction rate, consumes the number of lithium ions, and causes capacity decay. The process can be expressed by the Arrhenius formula.

[0049]

[0050] In the formula, Q loss,T represents battery capacity loss; T represents ambient temperature; A represents pre-exponential factor; E a represents activation energy, i.e., the threshold for chemical reaction; R represents the ideal gas constant; z represents the power law factor; and t represents the cycle time. As can be seen from the above formula, an increase in temperature will lead to Increase, thus accelerating the battery consumption.

[0051] Second, the discharge rate loss characterization model

[0052] When lithium-ion batteries are cycled at different rates, the capacity loss rate and cycle time also satisfy the Arrhenius formula. Temperature loss characterization model:

[0053] When studying the discharge rate loss characterization model, the cycle tests are all carried out at the same temperature, that is, T remains unchanged, so the above formula can be written as: Q loss,c-rate =A rate ×t z ;in At the same time, related studies have shown that A rate There is a good linear relationship between it and the current I, which can be written as: A rate =I×k1; where k1 represents A rate The linear correlation coefficient between the current I.

[0054] In summary, the battery loss model of the discharge rate can be written as: Q loss,c-rate =I×k1×t z .

[0055] The loss of the battery due to the discharge rate is reflected through the current. The discharge rate describes the ability of the lithium-ion battery to complete discharge in a unit time, which can usually be expressed as:

[0056] I=M×C m ;

[0057] Where I represents the maximum discharge current; C represents the rated capacity of the battery; m represents the number of hours to discharge the nominal capacity; and M represents a multiple or fraction of C. For example: for a 5A·h battery discharged at C / 10, the C / 10 discharge rate is written as 0.1C5. In this example, the C / 10 discharge rate is equal to 0.5A, or 500mA. It should be noted that the battery capacity gradually decreases as the discharge current increases. A standard 5A·h battery has a working time of 5 hours when discharged at C / 5 (or 1A). If the battery is discharged at a lower rate, such as C / 10 (0.5A), its discharge time may exceed 10 hours. Conversely, at 1C (5A), the discharge time is less than 1 hour, and the output capacity is also less than 5A·h.

[0058] The increase of discharge rate will cause higher current density, accelerate the embedding and extraction process of lithium ions on the positive and negative electrodes, accelerate the reaction rate of internal reactions, and lead to the loss of battery capacity. At the same time, too high discharge rate will cause the loss of internal active materials, leading to faster battery loss rate. Therefore, the attenuation of battery capacity by current rate is measured by Q loss,c-rate =I×k1×t z .

[0059] Third, the discharge depth loss characterization model

[0060] The loss of battery by discharge depth is shown by the state of charge. The discharge depth indicates how much energy stored in the battery is consumed or utilized during the cycle discharge process. It is a basic indicator of battery performance and energy utilization. It is presented as a percentage of the total storage capacity of the battery. The increase in discharge depth will lead to the loss of active materials in the battery, which will have an adverse effect on the capacity of the battery. The degradation of the battery by discharge depth can be described as:

[0061]

[0062] n=kT h (k=1,2,3,...∞);

[0063] In the formula, Q loss,DOD (n) represents the loss of battery capacity due to discharge depth; n represents the number of cycles; T h is the half cycle time; Q BOL represents the initial capacity; Q EOL Indicates the battery capacity at the end of life; ε(n) represents the battery degradation factor. In the above formula, k / 2 is used to distinguish whether it is a complete cycle. If it is a complete cycle (k is an even number), it is calculated according to the attenuation formula. If it is not a complete cycle (k is an odd number), it is equal to the previous value.

[0064]

[0065] The maximum number of cycles N can be expressed as:

[0066]

[0067] Where H is the cycle constant; ξ is the exponential factor of DOD; ψ is the Arrhenius rate constant of the cycle number; I dis-ave Represents the average discharge current in half a cycle; I ch-ave represents the average charging current in half a cycle; γ1 represents the coefficient of the discharge current; γ2 represents the coefficient of the charging current; T ref Indicates standard ambient temperature; T a Indicates the ambient temperature.

[0068] In order to further compare and analyze the effects of the proposed lithium-ion battery capacity degradation method, this paper Figure 2 The system framework diagram shown in the figure uses Simulink to carry out lithium-ion battery degradation simulation verification. The control variable method is used to conduct experiments, and the benchmark conditions are set as follows: ambient temperature 25°C, discharge current rate 0.5C, and discharge depth 100%. Then, one of these benchmark conditions is changed to observe the change in battery capacity. The specific parameters of the battery selected for simulation are shown below.

[0069] Table 1 Battery parameters

[0070] parameter Numeric Nominal voltage 3.6V Rated capacity 2.0Ah Maximum charge cut-off voltage 4.2V Discharge cut-off voltage 2.5V

[0071] like Figure 3 The battery capacity percentage curve at different temperatures is shown. Figure 3 It can be seen that as the battery charge and discharge process proceeds, the battery capacity percentage at different temperatures shows obvious attenuation with the increase in the number of cycles. At the same time, it can be seen from the figure that within 100 cycles, the rate of change of the battery capacity percentage curve increases with the increase in temperature. This is because the increase in temperature causes the internal chemical reaction rate to accelerate, resulting in a decrease in battery capacity; after experiencing the same 200 cycles, the capacity retention rate at 25°C is 92.2%, while at 55°C it is only 83.7%, and after 200 cycles, the rate of change of each curve with the number of cycles becomes larger and larger. This is because the continuous high temperature conditions cause the loss of active materials and lithium ions, exacerbating the loss of capacity.

[0072] like Figure 4 The battery capacity percentage curves at different discharge rates are shown. Figure 4 It can be seen that the capacity percentage curve of the battery at different charging rates shows a significant decrease with the increase in the number of cycles. This is because the high current rate will increase the local current density in the battery and accelerate the reaction rate. At the same time, the slope of the capacity percentage curve of 0.3C, 0.5C, 1C, and 1.5C discharge rates is getting steeper and steeper under the same number of cycles, indicating that the increase in discharge rate will lead to the loss of active materials and damage to electrode materials inside the battery, further aggravating the capacity decay rate of the battery and causing a sharp decay of capacity.

[0073] like Figure 5 Shows the battery capacity percentage at different depths of discharge, Figure 5 It can be seen that with the increase of the number of cycles, the battery capacity percentage at different discharge depths gradually decreases. This is because the increase in discharge rate will cause the loss of active materials inside the battery, resulting in the decline of the battery capacity. At the same time, it can be seen from the figure that: under the same number of 500 cycles, the capacity percentage curve of high discharge rate decreases more, which shows that high discharge depth intensifies the degree of reaction in the battery. At the same time, maintaining a high discharge depth will damage the battery's electrode structure and accelerate the battery aging process.

[0074] Through the above, the precise characterization of the effects of different aging factors such as temperature, discharge rate, and discharge depth on battery life is achieved, providing a theoretical basis for battery life prediction and battery life extension. Simulation also further shows that temperature, discharge rate, and discharge depth will accelerate the reaction process inside the battery, causing the loss of lithium ions and active materials, and accelerating the aging rate of the battery; and under the same conditions for the battery selected by the present invention, the effects of discharge rate, temperature, and discharge depth on battery capacity gradually weaken.

[0075] According to the second aspect of an embodiment of the present invention, a lithium-ion battery capacity decay analysis system based on reaction kinetics theory is provided, including a module of any of the above-mentioned lithium-ion battery capacity decay analysis methods based on reaction kinetics theory; specifically including: a first module for executing step 1, describing the performance degradation process of lithium-ion batteries based on reaction kinetics theory, and identifying key influencing factors of battery capacity decay; a second module for executing step 2, establishing a lithium-ion battery degradation model based on the identified key influencing factors of battery capacity decay, and realizing differentiated characterization of the battery degradation process under different influencing factors; a third module for executing step 3, carrying out simulation analysis on the lithium-ion battery decay process under different influencing factors, so as to verify the validity of the proposed lithium-ion battery degradation model. For the parts not described in detail in the above-mentioned modules, please refer to the relevant descriptions of other embodiments.

[0076] According to a third aspect of the present invention, a processor is provided, the processor being used to run a program, wherein when the program is run, any one of the above-mentioned lithium-ion battery capacity decay analysis methods based on reaction kinetics theory is executed.

[0077] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the above-mentioned lithium-ion battery capacity decay analysis methods based on reaction kinetics theory.

[0078] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0079] The specific implementation modes of the present invention are described in detail above in conjunction with the accompanying drawings, but the present invention is not limited to the above implementation modes, and various changes can be made within the knowledge scope of ordinary technicians in this field without departing from the purpose of the present invention.

Claims

1. A lithium-ion battery capacity decay analysis method based on reaction kinetics theory, characterized in that: The following steps are involved: Describe the performance degradation process of lithium-ion batteries based on reaction kinetics theory and identify the key influencing factors of battery capacity attenuation; Based on the identified key influencing factors of battery capacity attenuation, a lithium-ion battery degradation model is established to achieve differentiated characterization of the battery degradation process under different influencing factors; A simulation analysis is carried out on the attenuation process of lithium-ion batteries under different influencing factors to verify the effectiveness of the proposed lithium-ion battery degradation model.

2. The lithium-ion battery capacity decay analysis method based on reaction kinetics theory according to claim 1, characterized in that: Based on the reaction kinetics theory, the performance degradation process of lithium-ion batteries is described, and the key influencing factors of battery capacity attenuation are identified, including: temperature, discharge rate, and discharge depth.

3. The lithium ion battery capacity decay analysis method based on reaction kinetics theory according to claim 1, characterized in that: According to the key influencing factors of the battery capacity attenuation link identified, a lithium-ion battery degradation model is established, specifically: First, the temperature loss characterization model In the formula, Q loss,T Indicates the effect of temperature on battery capacity loss; T indicates ambient temperature; A indicates pre-exponential factor; E a represents activation energy, i.e., the threshold for chemical reaction to occur; R represents the ideal gas constant; z represents the power law factor; t represents the cycle time; Second, the discharge rate loss characterization model Qloss,c-rate=I×k1×tz In the formula, Q loss,c-rate Indicates the effect of discharge rate on battery capacity loss; I indicates the maximum discharge current; k1 indicates the linear correlation coefficient; Third, the discharge depth loss characterization model In the formula, Q loss,DOD (n) represents the effect of discharge depth on battery capacity loss; T h is the half cycle time; Q BOL represents the initial capacity; Q EOL Indicates the battery capacity at the end of life; ε(n) represents the battery degradation caused by the depth of discharge.

4. A lithium-ion battery capacity decay analysis system based on reaction kinetics theory, characterized in that: A module comprising the lithium-ion battery capacity decay analysis method based on reaction kinetics theory as described in any one of claims 1 to 3.

5. A processor, characterized in that: The processor is used to run a program, wherein the program, when running, executes the lithium-ion battery capacity decay analysis method based on reaction kinetics theory as described in any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute the lithium-ion battery capacity decay analysis method based on reaction kinetics theory as described in any one of claims 1 to 3.

Images