Method for predicting full cycle life of power battery

Abstract

The application discloses a kind of power battery full cycle life prediction methods, the predicted capacity attenuation ratio of every interval a cycle is obtained by calculation to predict capacity attenuation ratio accurately predict the cycle life of the battery to be measured, it is proved by experiment, using the life prediction method provided in the application, the error of the prediction result of cycle life obtained and the real cycle test result is small, the method of the application can greatly shorten the time of battery cycle test, shorten the cycle of battery development, and reduce artificial and research and development cost.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of battery, in particular to a power battery full cycle life prediction method. BACKGROUND

[0002] With the increasing shortage of global traditional energy and the increasing emphasis on environmental protection, electric vehicles usher in a rapid development period. Power batteries are the main power source of modern electric vehicles, and the research and development of power batteries are the current hotspots. As a main performance indicator of power batteries, cycle life is increasingly becoming a key technology in the design and development of electric vehicles. However, actual cycle testing of power batteries is a time-consuming, labor-intensive and expensive process, which is far behind the product development cycle.

[0003] Lithium iron phosphate battery has the advantages of high energy density, long service life, low self-discharge rate and strong temperature adaptability, and is the main type of power battery. The mechanism of lithium iron phosphate battery cycle attenuation is that during the normal operation of the battery, due to the charge and discharge cycle, the solvent molecules in the electrolyte react with lithium ions, and an SEI film is formed on the negative electrode graphite, resulting in the loss of active lithium ions in the electrolyte. In the actual research and development process, due to the long service life of lithium iron phosphate battery, actual cycle testing is too time-consuming and labor-intensive, and the current cycle life prediction method is generally used to predict the service life of lithium iron phosphate battery.

[0004] At present, there are many studies on lithium iron phosphate battery cycle prediction. With the gradual deepening of the understanding of the cycle attenuation process of the battery, the theory of cycle prediction mechanism tends to be mature. However, when using the current battery cycle attenuation and prediction model to predict the service life, there are problems such as large error and low reliability. SUMMARY

[0005] In order to overcome the shortcomings and deficiencies of the prior art, the purpose of the present application is to provide a power battery full cycle life prediction method with small error and high reliability.

[0006] In order to achieve the above application purpose, the technical scheme adopted by the present application is as follows:

[0007] A power battery full cycle life prediction method, comprising the following steps:

[0008] S1: providing a battery to be tested, measuring the initial capacity Q of the battery to be tested, the cycle number corresponding to the initial capacity Q is recorded as the initial value N0, and the capacity retention rate corresponding to the initial capacity Q is 100%;

[0009] S2: performing cycle charge and discharge test on the battery to be tested;

[0010] S3: Taking the initial value N0 as the starting point, the capacity retention rate of each interval a times of cyclic charge-discharge test is calculated, and is recorded as A1, A2, A3, …, A n ;

[0011] S4: The capacity attenuation ratio of each interval a times of cycle is A1-100%, A2-A1, …, A n -A n-1 recorded as α1, α2, α3, …, α n , when α n , α n-1 , α n-2 , the average value of α n , α n-1 , α n-2 is taken as the predicted capacity attenuation ratio of each interval a times of cycle

[0012] S5: According to the predicted capacity attenuation ratio The predicted cycle life of the battery to be tested can be derived.

[0013] Further, the environmental temperature range is 23℃-47℃, and the working pressure range is 300±20kgf.

[0014] Further, in the S1 step, the battery to be tested is subjected to charge-discharge test, and when the numerical range of the discharge capacity is less than 3% of the rated capacity for 3 times in succession, the average value of the numerical value of the discharge capacity for 3 times in succession is taken as the initial capacity Q.

[0015] Further, the charge-discharge test in the S1 step is that the battery to be tested is discharged to 2.5V at 1C current, left for 30min, and charged to 3.65V at 1C constant current and constant voltage, with the cutoff current being 0.05C.

[0016] Further, the cyclic charge-discharge test in the S2 step adopts step charging, and the step charging is that the battery to be tested is subjected to constant current charging in multiple stages, and the charging current of the multiple stages is gradually reduced.

[0017] Further, the step charging includes the following steps:

[0018] S100: Charging at 1C constant current to a capacity of 80%Q;

[0019] S200: Charging at 0.8C constant current to 3.5V;

[0020] S300: Charging at 0.5C constant current to 3.6V;

[0021] S400: Charging at 0.1C constant current to 3.65V;

[0022] S500: resting for 30 min in open circuit state, discharging to 2.5V at 1C current, resting for 30 min;

[0023] S600: repeating S100-S500 steps.

[0024] Further, the capacity retention rate of the battery to be tested is attenuated by 5% each time, and the charging current value A of each stage of S100-S400 is adjusted to A x (1-c x 5%), wherein c is equal to any one of 1, 2, 3, 4, …, c.

[0025] Further, the value of a in the S3 step is 50-200, and preferably, the value of a is 100.

[0026] Further, when α n , α n-1 , α n-2 , the value range of α n , α n-1 , α n-2 is less than or equal to 0.05%, the average value of α n , α n-1 , α n-2 is taken.

[0027] Compared with the prior art, the present application has the following advantages:

[0028] 1. By obtaining the predicted capacity attenuation ratio The cycle life of the battery to be tested can be accurately predicted. Experimental results show that the error between the predicted results of the cycle life and the true cycle test results is small. The application of the method of the present application can greatly shorten the cycle test time of the battery, shorten the development cycle of the battery, and reduce the labor and research and development costs.

[0029] 2. The data analysis and prediction method can analyze the fluctuation points of the battery cycle curve, determine the cycle interval where the cycle attenuation slows down or intensifies, and help the researchers fully master the attenuation performance of the battery to be tested. BRIEF DESCRIPTION OF DRAWINGS

[0030] Figure 1 is the measured / predicted cycle life curve of the battery at 25℃;

[0031] Figure 2 is the measured / predicted cycle life curve of the battery at 45℃. DETAILED DESCRIPTION

[0032] The application will be described in further detail below with specific embodiments and examples, but the embodiments of the application are not limited thereto. Unless otherwise specified, all raw materials and reagents in the application are commercially available conventional raw materials and reagents. The amount of each component in the examples is calculated in mass volume parts, mg, mL.

[0033] Implementation 1: 25°C cycle life prediction

[0034] S1: Provide EVE-54174207 specification battery, install fixture on the battery at ambient temperature 25°C±2°C, 300kgf±20kgf, discharge the battery at 1C current to 2.5V, stand for 30min, charge the battery at 1C constant current and constant voltage to 3.65V, cutoff current 0.05C, when the result difference of three consecutive tests is less than 3% of the rated capacity, the test can be ended in advance, take the average value of the results of three consecutive tests as the initial capacity Q, N0 is 20 times in this embodiment;

[0035] S2: Cycle charge and discharge test of the battery at ambient temperature 25°C±2°C, 300kgf±20kgf, which includes the following steps:

[0036] S100: Charge at 1C constant current to 80%Q capacity;

[0037] S200: Charge at 0.8C constant current to 3.5V;

[0038] S300: Charge at 0.5C constant current to 3.6V;

[0039] S400: Charge at 0.1C constant current to 3.65V;

[0040] S500: Stand for 30min in open circuit state, discharge to 2.5V at 1C current, stand for 30min;

[0041] S600: Repeat S100-S500 steps, the capacity retention rate of the battery is attenuated by 5% each time, the charge current value A of S100 to S400 at each stage is adjusted to A×(1-c×5%), where c=1, 2, 3, 4, …, c, so that the charge time of each charge and discharge cycle can be kept consistent; see Table 1 for the corresponding charge and discharge current table;

[0042] Table 1 Test process charge and discharge current table

[0043]

[0044] S3: Take the initial value of 20 cycles as the starting point, calculate the capacity retention rate every 100 cycles, respectively recorded as A1, A2, A3, …, A n , see Table 2 for specific results;

[0045] S4: Calculate the capacity fade ratio A1-100%, A2-A1, A3-A2, …, A n -A n-1 denoted as α1, α2, α3, …, α n When α n , α n-1 , α n-2 The average value of α n , α n-1 , α n-2 is taken when the numerical range is less than or equal to 0.05% Predicted capacity fade ratio Continue to calculate the subsequent charge and discharge.

[0046] Table 2: Cycle life test data and life prediction data of the battery cell

[0047]

[0048]

[0049] In this embodiment, the capacity of the battery cell climbs during the cycle test, and the capacity reaches a maximum value at the 20th cycle, denoted as the initial capacity of the battery cell; wherein the capacity retention rate = current discharge capacity / initial capacity; the capacity fade ratio = last cycle capacity retention rate-current cycle capacity retention rate.

[0050] As can be seen from the data in Table 2, the capacity fade ratio of the battery cell gradually tends to a stable value at the 1220th cycle, and the average value of the capacity fade ratios at the 1220th, 1320th and 1420th cycles is taken, with two decimal places, to obtain the predicted capacity fade ratio 0.36%, and the capacity retention rate decay ratio per 100 cycles is predicted as 0.36%, i.e. a data table of cycle number and capacity retention rate is obtained, Figure 1 is the actual / predicted cycle life curve of the battery cell fitted according to the data in Table 2, and it can be seen that the actual curve and the predicted curve have the same trend and little deviation.

[0051] As can be seen from this embodiment, the actual cycle life of the battery cell at 25°C is 5020 times @ 80.68%, and the predicted life is 5020 times @ 79.67%. Using this prediction method, the error of the cycle life of the battery cell at 25°C is only 1.01%, and the life prediction method is accurate. That is, by applying this method to the cycle life prediction of the battery, at least 3500 times of charge and discharge cycles can be saved.

[0052] Cycle life prediction at 45°C in Example 2

[0053] S1: provide EVE-54174207 specification battery, install fixture on the battery at ambient temperature 45℃±2℃, 300kgf±20kgf, discharge the battery at 1C current to 2.5V, rest for 30min, charge the battery at 1C constant current and constant voltage to 3.65V, cut-off current 0.05C, when the result difference of 3 consecutive tests is less than 3% of the rated capacity, the test can be ended in advance, take the average value of the results of 3 consecutive tests as the initial capacity Q, in this embodiment, N0 is 20 times;

[0054] S2: cycle charge and discharge test is carried out on the battery at ambient temperature 25℃±2℃, 300kgf±20kgf, which specifically includes the following steps:

[0055] S100: charge at 1C constant current to 80%Q capacity;

[0056] S200: charge at 0.8C constant current to 3.5V;

[0057] S300: charge at 0.5C constant current to 3.6V;

[0058] S400: charge at 0.1C constant current to 3.65V;

[0059] S500: rest for 30min in open circuit state, discharge to 2.5V at 1C current, rest for 30min;

[0060] S600: repeat S100-S500 steps, the capacity retention rate of the battery is attenuated by 5% each time, the charge current value A of S100 to S400 at each stage is adjusted to A×(1-c×5%), wherein c=1, 2, 3, 4, …, c, so that the charge time of each charge and discharge cycle can be kept consistent; see Table 3 for the corresponding charge and discharge current table;

[0061] Table 3 test process charge and discharge current table

[0062]

[0063]

[0064] In this embodiment, the capacity of the battery climbs during the cycle test process, and reaches the maximum value at the 3rd cycle, which is recorded as the initial capacity of the battery; wherein, the capacity retention rate=current discharge capacity / initial capacity; the capacity attenuation ratio=last cycle capacity retention rate-current cycle capacity retention rate.

[0065] As can be seen from the data in Table 4, the capacity attenuation ratio of the battery gradually tends to a stable value from the 503rd cycle, take the average value of the capacity attenuation ratios of the 503rd, 603rd and 703rd cycles, and round to two decimal places, to obtain the predicted capacity attenuation ratio 0.60%, the capacity retention rate is predicted by the proportion of 0.60% per 100 cycles, that is, the data table of cycle number and capacity retention rate is obtained, Figure 1 is the measured / predicted cycle life curve of the battery cell fitted according to the data in Table 4, and in this embodiment, the measured curve and the predicted curve are highly fitted;

[0066] Therefore, according to the above embodiment, the actual cycle life of the battery cell at 45 DEG C is 2703 times @ 80.58%, and the predicted life is 2703 times @ 80.29%. Using the prediction method, the error of the cycle life of the battery cell at 45 DEG C is only 0.29%, and the life prediction method is accurate. That is, the application of the method to the cycle life prediction of the battery can save at least 2000 times or more of the charge-discharge cycle number.

[0067] Table 4: Cycle life test data and life prediction data of battery cell

[0068]

[0069]

[0070] In summary, the error between the predicted value and the measured value of Example 1 is 1.01%, and the error between the predicted value and the measured value of Example 2 is 0.29%. Compared with the prediction error of more than 5% in the prior art, the battery cycle life provided by the present application has the characteristics of small error and high reliability, and has a good application prospect in actual research and development.

[0071] The above embodiments are the optimal implementation modes explored by the present application, but the implementation modes of the present application are not limited by the above embodiments, and any changes, modifications, substitutions, combinations, simplifications made without departing from the spirit and principles of the present application are equivalent replacement modes, and are all included in the protection scope of the present application.

Claims

1. A method for predicting the full cycle life of a power battery, characterized in that, The method comprises the following steps: S1: providing a battery to be tested, determining an initial capacity Q of the battery to be tested, the cycle number corresponding to the initial capacity Q being recorded as an initial value N0, and the capacity retention rate corresponding to the initial capacity Q being 100%; S2: performing a cycle charge-discharge test on the battery to be tested; S3: taking the initial value N0 as a starting point, calculating the capacity retention rate of every interval a cycle charge-discharge test, and recording them as A1, A2, A3, …, An respectively; S4: recording the capacity attenuation ratios A1-100%, A2-A1, …, An-An-1 of every interval a cycle as α1, α2, α3, …, αn, and taking the average value of αn, αn-1, and αn-2 as the predicted capacity attenuation ratio of every interval a cycle when the values of αn, αn-1, and αn-2 tend to be stable; S5: deriving the predicted cycle life of the battery to be tested according to the predicted capacity attenuation ratio; In the S1 step, the charge-discharge test on the battery to be tested is performed, and when the numerical range of the discharge capacity of three consecutive times is less than 3% of the rated capacity, the average value of the numerical value of the discharge capacity of the three consecutive times is taken as the initial capacity Q; In the S2 step, the cycle charge-discharge test adopts a step charging, and the step charging is to perform constant current charging on the battery to be tested in multiple stages, the charging current of the multiple stages gradually decreases, and the step charging comprises the following steps: S100: charging at 1C constant current to 80%Q; S200: charging at 0.8C constant current to 3.5V; S300: charging at 0.5C constant current to 3.6V; S400: charging at 0.1C constant current to 3.65V; S500: standing for 30 minutes in an open circuit state, discharging at 1C current to 2.5V, and standing for 30 minutes; S600: repeating the steps S100-S500; The charging current value A of each stage of S100 to S400 is adjusted to A×(1-c×5%), where c is equal to 1, 2, 3, 4, …, any numerical value of c.

2. The power battery full cycle life prediction method according to claim 1, characterized in that: The environmental temperature range of the charge-discharge test of the battery to be tested is 23-47℃, and the working pressure range is 300±20kgf.

3. The method of claim 1, wherein: In the S1 step, the charge-discharge test is to discharge the battery to be tested at 1C current to 2.5V every cycle, stand for 30 minutes, charge at 1C constant current and constant voltage to 3.65V, and the cutoff current is 0.05C.

4. The power battery full cycle life prediction method of claim 1, wherein: In the S3 step, the value of a is 50-200.

5. The power battery full cycle life prediction method of claim 4, wherein: In the S3 step, the value of a is 100.

6. The power battery full cycle life prediction method of claim 1, wherein: When the numerical range of αn, αn-1, and αn-2 is less than or equal to 0.05%, the average value of αn, αn-1, and αn-2 is taken.

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