Calendar life evaluation method for lithium ion battery

Abstract

The invention discloses a lithium ion battery calendar life evaluation method, which comprises the following steps of: firstly, obtaining test data based on a calendar life test design of an attenuation factor: setting a plurality of temperature stress gradients and SOC stress gradients to carry out a standing test on a battery, and keeping the battery in a set SOC and temperature state in a constant-temperature environment; regularly taking out in a test period to carry out a recoverable capacity test; then constructing a temperature stress attenuation model and an SOC stress attenuation model: according to temperature stress test data, establishing a temperature attenuation rate function based on an Arrhenius formula to obtain the temperature stress attenuation model; establishing an SOC attenuation rate function based on an inverse power law formula according to the SOC stress test data to obtain an SOC stress attenuation model; and finally, model compounding and life evaluation: compounding the temperature stress attenuation model and the SOC stress attenuation model to obtain a battery calendar life evaluation formula, and substituting the battery calendar life evaluation formula into the temperature, SOC and time of the target working condition to calculate the calendar life attenuation rate of the battery under the working condition.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of new energy power battery, in particular to a lithium ion battery calendar life evaluation method. BACKGROUND

[0002] Lithium ion batteries are widely used in new energy electric vehicles due to their high energy density, long cycle life and good environmental protection. As the core power component of the vehicle, its durability directly determines the vehicle's range and service life. However, during the long-term service of the battery, irreversible lithium loss occurs, leading to gradual capacity degradation of the battery, resulting in a decrease in the vehicle's range, and further causing user complaints about the battery's reliability and use experience. Therefore, during the battery design and verification stage, how to accurately predict and evaluate the battery life has become the focus of the industry.

[0003] In the prior art, the research and evaluation of battery life mainly rely on cycle performance testing, that is, by observing the capacity retention rate and decay trend through continuous charge and discharge cycles. However, relying solely on cycle performance to characterize life has certain limitations. In actual application conditions, electric vehicles are not always in frequent charge and discharge state, and a large amount of time is spent in static or low-load running stage. At this time, the calendar decay of the battery cannot be ignored. The so-called calendar decay refers to the performance decline of the battery due to the passage of storage time under non-cycling conditions, and its decay degree is closely related to environmental temperature, state of charge (SOC) under static state, static time and other factors.

[0004] However, the existing research on the quantitative method of calendar decay is not perfect, and it is difficult to accurately reflect the real evolution process of battery life under different conditions. The present application proposes a lithium battery calendar life quantitative analysis method based on experimental design, which can systematically evaluate the influence of key factors such as temperature, SOC and static time on battery decay behavior, thereby providing a reliable theoretical basis and experimental guidance for lithium battery life prediction and evaluation. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides a lithium ion battery calendar life evaluation method, which overcomes the shortcomings of existing methods that rely solely on cycle testing and ignore calendar decay by establishing a composite model based on multi-gradient stress test design based on decay factors and combining Arrhenius formula and inverse power law formula, accurately reflecting the decay law of the battery under actual working conditions, making the life evaluation more consistent with the real use scenario of electric vehicles and energy storage applications.

[0006] To achieve the above purpose, the technical scheme adopted by the present application is as follows: A lithium ion battery calendar life evaluation method, comprising the following steps: S1, calendar life test design based on decay factors.

[0007] Use accelerated test protocol for test design. For temperature, use 3 or more stress gradients, usually three gradients stress T1=25℃, T2=45℃, T3 is the temperature not more than the upper limit of electrolyte window, set 2 or more parallel samples at each temperature stress. Adjust the battery to the same SOC state, usually 100% SOC, with clamp, the clamp force can refer to the initial pre-tightening force of the monomer in the module, put into the temperature test box corresponding to the temperature for testing, take out every interval for battery recoverable capacity test, adjust to test SOC after test is completed, continue to test until the specified number of days of test is completed.

[0008] For SOC, use 3 or more stress gradients, and one of them is the same as the SOC set in the temperature accelerated test, set 2 or more parallel samples at each SOC stress. Adjust the battery to the same temperature state, with clamp, the clamp force can refer to the initial pre-tightening force of the monomer in the module, put into the temperature test box corresponding to the temperature for testing, take out every interval for battery recoverable capacity test, adjust to test SOC after test is completed, continue to test until the specified number of days of test is completed.

[0009] S2, parameter evaluation of attenuation model.

[0010] Process the test data. Under temperature stress test, the initial recoverable capacity is recorded as C T0 , the time and recoverable capacity of the i-th observation is recorded as (D i , C Ti ), the decay rate F i =1-C Ti / C T0 , and the data record of k observations is: [0, D1, D2, …, D k ; 0, F1, F2, …, F k ] Fit the observed decay rate at different temperatures using the following formula, and the fitting formula is: F(T, D)=f(E, T)xD x In the formula, f(E, T) is a temperature decay rate function containing Arrhenius formula, E is the activation energy, T is the test temperature, D is the time, and x is the time index. Use the data under different temperature stress to solve the fitting parameters in the formula.

[0011] Under SOC stress test, the initial recoverable capacity is recorded as C S0 , the time and recoverable capacity of the i-th observation is recorded as (D i , C Si ), the decay rate F i =1-C Si / C S0 The data record of k observations is: [0, D1, D2, …, D k ;0, F1, F2, …, F k ] The observed decay rates at different SOCs are fitted using the following formula, and the decay rate coefficients at different SOCs are normalized: the decay rate coefficient at the SOC stress set during the temperature acceleration test (denoted as SOC_0) is dimensionless, and the decay rate coefficients at the remaining SOC stresses are the ratio of the actual decay rate to the SOC_0 actual decay rate.

[0012] The fitting formula is: F(S, D) = g(S, n) x D x In the formula, g(S, n) is a SOC decay rate function containing an inverse power law formula, S is the tested SOC, n is the power index, D is the time, and x is the time index. Using data at different SOC stresses, the fitting parameters in the formula are solved.

[0013] S3, model combination and calendar life evaluation The Arrhenius formula related to temperature stress and the inverse power law formula related to SOC stress are combined to form a calendar life evaluation formula: F(T, S, D) = f(E, T) x g(S, n) x D x The temperature factor, SOC factor and time required for evaluation are substituted into the above formula, and the calendar life decay rate under the condition can be obtained.

[0014] Advantages of the present application: 1. The method of the present application simultaneously introduces multi-gradient test design of temperature stress and SOC stress, which can systematically analyze the influence of environmental temperature, state of charge and standing time on battery calendar decay, and avoid the deviation caused by the traditional method of only using cycle life to infer.

[0015] 2. By combining the temperature decay rate function (Arrhenius formula) and the SOC decay rate function (inverse power law formula), a unified calendar life prediction model is constructed, which realizes the quantitative characterization of battery decay rate and improves the scientificity and accuracy of life evaluation.

[0016] 3. The error between the calendar life evaluation value and the measured value of the 160Ah lithium iron phosphate battery is within 1.2% after the improvement, and the long-period calendar life can be predicted, and the calendar life under various working conditions can be accurately evaluated.

[0017] 4. The experimental design and model formulas of this method are universal and applicable to different types of lithium-ion batteries (including lithium iron phosphate batteries, ternary batteries, etc.), providing a generalized tool for the design and life prediction of power batteries, energy storage batteries, and consumer batteries. The life prediction results obtained through this method can provide battery manufacturers with a reliable basis for design selection, verification testing, thermal management strategy optimization, and after-sales life management, thereby improving the overall performance and user experience of electric vehicles and energy storage systems.

[0018] 5. By introducing clamping force constraints into the experiment, the stress state of the individual battery cells is made closer to the actual working conditions of the module, thereby ensuring the correlation and reliability of the test data with the actual application environment. Attached Figure Description

[0019] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 This is the lifespan assessment curve plotted based on test data in this invention; Figure 2 This is the life prediction curve plotted based on the model calculation in this invention. Detailed Implementation

[0021] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0022] Example 1

[0023] The specific implementation of this invention aims to elaborate on the implementation process of a lithium-ion battery calendar life assessment method. This method comprehensively considers the influence of temperature, SOC (state of charge), and resting time on the degradation of battery calendar life through multi-dimensional stress test design and composite model construction, and finally forms a scientific life assessment model.

[0024] First, the implementation steps of this invention start with multi-dimensional stress test design, and gradually progress to data acquisition, model fitting, and the application of the final calendar life assessment formula.

[0025] In the experimental design stage, at least three temperature gradients T1, T2, T3 are selected, uniformly distributed from room temperature to no more than the upper limit of the electrolyte window. For example, T1 = 25°C, T2 = 45°C, and T3 is set to a high temperature condition not exceeding the upper limit of the electrolyte window, usually 60°C or higher, to ensure that significant capacity degradation phenomena can be observed in accelerated testing. At the same time, at least three SOC gradients S1, S2, S3 are set to cover the state of charge interval of the battery in actual use. One of the SOC gradients needs to be consistent with the SOC setting during the temperature test to ensure the consistency of the test conditions and the comparability of the data. For example, S1 = 50%, S2 = 80%, and S3 = 100% can be selected as the SOC gradient range, which can cover the common state of charge interval of the battery in actual use.

[0026] During the test, the battery needs to be fixed in the clamp, and the clamp force is set to the initial pre-tightening force of the single cell in the module. This design simulates the stress state of the battery in actual working conditions, thereby ensuring the consistency of the test environment and the actual application environment. The clamp design should meet the following requirements: the pre-tightening force applied by the clamp should be uniformly distributed on the surface of the battery to avoid damage to the internal structure of the battery due to excessive local pressure. In addition, the recoverable capacity test method is used in the capacity test link, that is, after each capacity measurement, the battery is fully charged and discharged, only the transient irreversible loss generated during the test is eliminated, and the calendar aging trend is not affected, thereby improving the accuracy and reliability of the test data.

[0027] Next, enter the data collection phase. Place the battery in different temperature gradients and SOC gradients in the accelerated test environment, and record its capacity degradation data within a certain time period. Specifically, for each temperature gradient and SOC gradient combination, select multiple standing time points to cover the required time scale, which can be flexibly set according to the actual test period, for example, D1 = 7 days, D2 = 14 days, D3 = 30 days, etc., to obtain the capacity degradation under different time scales. In this way, the comprehensive influence of temperature, SOC and standing time on the calendar life degradation of the battery can be fully captured. During the test, the capacity measurement uses high-precision charge and discharge equipment, and the current and voltage resolution needs to reach the level of milliamperes and millivolts to ensure the accuracy of the data.

[0028] Based on the above test data, the capacity degradation rate under temperature stress and SOC stress is fitted respectively. In the temperature stress test, the capacity degradation rate fitting formula is F(T, D) = f(E, T) x D x where f(E, T) is the temperature degradation rate function, which is in the form of the Arrhenius formula f(E, T) = A x e -E / RT, wherein E is the activation energy, J / mol; R is the gas constant, J / (mol·K); T is the absolute temperature, K; A is the frequency factor; D is the time, days; and x is the time index. The parameters A, E and x are solved by non-linear regression analysis of the test data at different temperatures. For example, at T1=25℃, T2=45℃ and T3=60℃, the corresponding f(E,T) values are obtained, and the relationship curve of temperature and capacity attenuation rate is drawn. As the temperature increases, the capacity attenuation rate of the battery increases significantly, which is consistent with the theoretical prediction of the Arrhenius formula.

[0029] In the SOC stress test, the capacity attenuation rate fitting formula is F(S,D)=g(S,n)×D x , wherein g(S,n) is the SOC attenuation rate function, which is in the form of the inverse power law formula g(S,n)=B×S n . In the formula, S is the state of charge, n is the power index, B is the proportional coefficient, D is the time, and x is the time index. To unify the dimensions, the g(S,n) is normalized, taking the actual attenuation rate of the SOC point (denoted as S0) set in the temperature test as the benchmark, and the attenuation rate coefficients of other SOC points as the ratio of their actual values to the benchmark value. For example, assuming S0=80%, the normalized attenuation rates of S1=50% and S3=100% are g(S1,n) / g(S0,n) and g(S3,n) / g(S0,n) respectively. By fitting the test data at different SOC gradients, the parameters B and n are solved, and the relationship curve of SOC and capacity attenuation rate is drawn. The influence of SOC on the capacity attenuation rate shows a nonlinear characteristic, and the attenuation rate increases significantly in the high SOC region.

[0030] The attenuation rate functions of temperature stress and SOC stress are combined to form the calendar life evaluation formula F(T,S,D)=f(E,T)×g(S,n)×D x . This formula can accurately reflect the calendar life attenuation rate of the battery under specific working conditions, and is suitable for different types of lithium ion batteries. For example, in actual application, if the target working condition is T=35℃, S=60%, and D=90 days, the calendar life attenuation rate under this condition can be calculated by substituting the corresponding parameter values. The specific calculation process is as follows: first, calculate the value of f(E,T) according to the Arrhenius formula, then calculate the normalized value of g(S,n) according to the inverse power law formula, and finally multiply the two with the time index D x to obtain the final calendar life attenuation rate. It has been verified that this method can control the prediction error within 1.2% in the calendar life evaluation of lithium iron phosphate batteries, and can accurately predict the long-term calendar life.

[0031] Effect comparison before and after improvement: By comparing the calendar life evaluation value and the measured value of the 160Ah lithium iron phosphate battery cell, the error is within 1.2%. Compared with the cycle test method, the prediction error is significantly reduced, and the long-term calendar decay can be covered. And it can predict the long-term calendar life, and more accurately evaluate the calendar life under various working conditions.

[0032]

[0033] The test design and model formula of the present application are universal and suitable for different types of lithium ion batteries. For example, in the calendar life evaluation of ternary lithium batteries and lithium cobalt oxide batteries, the relevant parameters can also be adjusted to adapt to different chemical systems. Especially in electric vehicles and energy storage systems, this method can provide a universal tool for the design and life prediction of power batteries and energy storage batteries. For example, in the application scenario of electric vehicles, the calendar life decay of the battery under different use conditions can be predicted according to the temperature change and SOC fluctuation of the vehicle operating environment combined with the method of the present application, so as to optimize the control strategy of the battery management system (BMS) and prolong the service life of the battery. In the energy storage system, this method can help designers evaluate the performance decay of the battery under long-term static state, so as to develop a reasonable maintenance and replacement plan and improve the overall performance and user experience of the system.

[0034] The above shows and describes the basic principles, main features and advantages of the present application. Those skilled in the art should understand that the present application is not limited to the above examples, and the above examples and descriptions in the specification are only the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the claimed present application.

Claims

1. A method for evaluating calendar life of a lithium-ion battery, characterized by, The method comprises the following steps: S1, obtaining test data based on calendar life test design of attenuation factor: A plurality of temperature stress gradients and SOC stress gradients are set, and the battery is subjected to static test, the battery is kept at a set SOC and temperature state in a constant temperature environment, and is periodically taken out for recoverable capacity test within a test period; S2, constructing temperature stress attenuation model and SOC stress attenuation model: According to the temperature stress test data, a temperature attenuation rate function based on Arrhenius formula is established, and the temperature stress attenuation model is obtained; According to the SOC stress test data, an SOC attenuation rate function based on inverse power formula is established, and the SOC stress attenuation model is obtained; S3, model composition and life evaluation: The temperature stress attenuation model and the SOC stress attenuation model are composed, a battery calendar life evaluation formula is obtained, and the temperature, SOC and time of a target working condition are substituted into the formula to calculate the calendar life attenuation rate of the battery under the working condition.

2. The method of claim 1, wherein, The temperature stress test comprises at least three temperature gradients, and the three temperature gradients are distributed at intervals from normal temperature to a temperature not exceeding the upper limit of the electrolyte window.

3. The method for evaluating the calendar life of a lithium-ion battery according to claim 1, characterized in that, The SOC stress test comprises at least three SOC gradients, and one of the SOC stress points is the same as the SOC set in the temperature stress test.

4. The method of claim 1, wherein, The capacity attenuation rate fitting formula under the temperature stress test is: F(T,D) = f(E,T) x D x Wherein, f(E,T) is the temperature attenuation rate function, E is the activation energy, T is the temperature, D is the time, and x is the time index.

5. The method for evaluating the calendar life of a lithium-ion battery according to claim 1, characterized in that, The capacity attenuation rate fitting formula under the SOC stress test is: F(S,D) = g(S,n) x D x Wherein, g(S,n) is the SOC attenuation rate function, S is the SOC, n is the power index, D is the time, and x is the time index.

6. The method of claim 1, wherein, The SOC attenuation rate coefficient is normalized, and the SOC stress point set in the temperature stress test is dimension 1, and the attenuation rate coefficient of other SOC stress points is the ratio of the actual attenuation rate to the actual attenuation rate of the SOC stress point.

7. The method for evaluating the calendar life of a lithium-ion battery according to claim 1, characterized in that, The calendar life evaluation formula is: F(T,S,D) = f(E,T) x g(S,n) x D x .

8. The method of claim 1, wherein, The battery capacity test is a recoverable capacity test.

9. The method of claim 1, wherein, The battery is fixed by a clamp during the test, and the clamp force is set to the initial pre-tightening force of the single body in the module.

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