CN114252795B - Method for predicting cycle life of lithium ion battery - Google Patents
Method for predicting cycle life of lithium ion battery Download PDFInfo
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- CN114252795B CN114252795B CN202111448690.3A CN202111448690A CN114252795B CN 114252795 B CN114252795 B CN 114252795B CN 202111448690 A CN202111448690 A CN 202111448690A CN 114252795 B CN114252795 B CN 114252795B
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- 238000000034 method Methods 0.000 title claims abstract description 42
- 229910001416 lithium ion Inorganic materials 0.000 title claims abstract description 31
- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 title claims abstract description 30
- 230000014759 maintenance of location Effects 0.000 claims abstract description 64
- 238000012360 testing method Methods 0.000 claims abstract description 55
- 230000001133 acceleration Effects 0.000 claims abstract description 25
- 238000010586 diagram Methods 0.000 claims description 31
- 238000012886 linear function Methods 0.000 claims description 18
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 claims description 14
- 229910052744 lithium Inorganic materials 0.000 claims description 14
- GELKBWJHTRAYNV-UHFFFAOYSA-K lithium iron phosphate Chemical group [Li+].[Fe+2].[O-]P([O-])([O-])=O GELKBWJHTRAYNV-UHFFFAOYSA-K 0.000 claims description 8
- 238000004364 calculation method Methods 0.000 claims description 5
- QHGJSLXSVXVKHZ-UHFFFAOYSA-N dilithium;dioxido(dioxo)manganese Chemical compound [Li+].[Li+].[O-][Mn]([O-])(=O)=O QHGJSLXSVXVKHZ-UHFFFAOYSA-N 0.000 claims description 2
- BDKWOJYFHXPPPT-UHFFFAOYSA-N lithium dioxido(dioxo)manganese nickel(2+) Chemical compound [Mn](=O)(=O)([O-])[O-].[Ni+2].[Li+] BDKWOJYFHXPPPT-UHFFFAOYSA-N 0.000 claims description 2
- 125000004122 cyclic group Chemical group 0.000 abstract description 8
- 238000005259 measurement Methods 0.000 abstract description 2
- 230000032683 aging Effects 0.000 description 2
- 238000004146 energy storage Methods 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 238000005087 graphitization Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- NCZYUKGXRHBAHE-UHFFFAOYSA-K [Li+].P(=O)([O-])([O-])[O-].[Fe+2].[Li+] Chemical compound [Li+].P(=O)([O-])([O-])[O-].[Fe+2].[Li+] NCZYUKGXRHBAHE-UHFFFAOYSA-K 0.000 description 1
- 239000003153 chemical reaction reagent Substances 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 238000013075 data extraction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000004880 explosion Methods 0.000 description 1
- 238000001125 extrusion Methods 0.000 description 1
- 239000007770 graphite material Substances 0.000 description 1
- 238000010813 internal standard method Methods 0.000 description 1
- 238000011056 performance test Methods 0.000 description 1
- 239000007774 positive electrode material Substances 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000004904 shortening Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/392—Determining battery ageing or deterioration, e.g. state of health
Abstract
The invention discloses a method for predicting the cycle life of a lithium ion battery. According to the method, the target working condition and the acceleration working condition are adopted to alternately perform the cyclic acceleration test, the test period is shortened, the fitting is performed in real time, the number of inflection points and the corresponding functional relation are adjusted according to the requirement, and the prediction and the actual measurement are combined, so that the accuracy of a test result is ensured, and the purpose of rapidly testing the cyclic life of the battery cell is achieved. The prediction method is suitable for different types of lithium ion batteries, data except the cyclic capacity retention rate are not required to be processed in the process, the accuracy is high, the reproducibility is good, and the operation is simple and convenient.
Description
Technical Field
The invention relates to a method for predicting the cycle life of a lithium ion battery.
Background
In recent years, the lithium ion battery industry rapidly develops, and the lithium ion battery is not only embodied in the electric automobile industry, but also particularly rapidly developed in the energy storage industry. Currently, the mainstream lithium ion batteries are generally classified into ternary lithium ion batteries and lithium iron phosphate lithium ion batteries according to the distinction of positive electrode materials. Due to the problems of the structure and thermodynamic stability of the material, the safety of the ternary lithium ion battery is much worse than that of lithium iron phosphate, once the conditions of strong destructiveness such as extrusion, overcharging and short circuit occur, the possibility of the ternary lithium battery to fire and explode is higher, and most of electric automobile fire and explosion cases reported on the market are carried ternary lithium batteries. Based on the safety aspect, a plurality of vehicle enterprises begin to try to carry lithium iron phosphate batteries, lithium iron phosphate is increasingly accepted by the market, the application range is wider, and currently, the lithium iron phosphate batteries with better safety are generally selected in the energy storage industry.
The normal temperature cycle life of the lithium battery can generally reach 2000-6000 times, and according to the conventional room temperature 1C charge-discharge cycle test conditions, the test is carried out for about 8 months continuously for 2000 cycles, and for the lithium battery with the cycle life reaching 6000 times, the test is carried out for more than 2 years continuously for the whole life cycle, so that the time cost, the equipment depreciation cost, the electricity consumption cost and the like are all very large. Therefore, a method for performing accelerated testing on lithium batteries needs to be found, so that a great deal of cost can be saved, and the project development period can be shortened.
At present, the lithium ion battery cycle life is rapidly estimated in more patents, and typical patents are as follows:
for example, patent document CN107356877a discloses a method capable of realizing rapid prediction of cycle life of a lithium ion battery, which performs short-term performance test of different cycle times on a lithium battery to be evaluated, disassembles empty state batteries with different cycle times, tests graphitization degree of a graphite material on a negative electrode plate by using an XRD internal standard method, and performs fitting calculation according to three test data of cycle times, capacity retention rate and graphitization degree, thereby predicting cycle life of the battery. However, the method needs to disassemble the battery core and perform XRD test, is complicated in flow and complex in method, is limited by the influences of the difference of the pole piece sampling positions and XRD test precision, has poor result reproducibility, and has the result that predicted data is not actually measured data, and the accuracy of prediction cannot be guaranteed.
For another example, patent document CN107728072a discloses a method for rapidly predicting the cycle life of a lithium ion battery, which tests the charge and discharge performance of the lithium ion battery to be evaluated with different cycle numbers, calculates the change of the capacity of the battery in the interval of increasing the voltage from 3.95V to 4.15V in the charging process of the battery with different cycle numbers according to the charge and discharge data, and performs fitting calculation according to the capacity change value and the test data of the cycle numbers to predict the cycle life of the battery. However, the method is only suitable for testing the charge-discharge voltage reaching above 4.15V, and is not suitable for testing the limited charge-discharge voltage interval and the low-voltage lithium iron phosphate battery.
For another example, patent document CN109061478A discloses a method for qualitatively predicting the lifetime of a lithium ion battery by using EIS test, which comprises the steps of placing a lithium battery to be evaluated at a temperature of 45-60 ℃ for accelerated aging, then adopting a specific circulation system for charge-discharge circulation, then placing the battery in a constant temperature box at 35-42 ℃ for standing for 2-10 hours, then performing EIS test on a battery core, collecting EIS data, fitting the EIS data by Zview software, making a curve of the Rct growth rate with the number of circulation, and predicting the lithium battery according to the curve. However, the method needs to perform aging treatment on the battery core and then performs EIS test, the flow is complicated, the method is complex, rct of some lithium batteries is not increased in the cycle process, universality is poor, and the result is prediction data which is not measured data, so that the accuracy of prediction cannot be ensured.
According to the method, the cycle life of the lithium battery is predicted by processing data except the cycle capacity retention rate, and as factors influencing the cycle life of the lithium battery are more, if the cycle life is predicted by only data except the cycle capacity retention rate, the accuracy of a prediction result is difficult to ensure.
Disclosure of Invention
The invention aims to overcome the defects of poor accuracy, universality and reproducibility of the lithium ion battery cycle life prediction method in the prior art, and provides a method for predicting the lithium ion battery cycle life. The prediction method is suitable for different types of lithium ion batteries, data except the cyclic capacity retention rate are not required to be processed in the process, the accuracy is high, the reproducibility is good, and the operation is simple and convenient.
The invention solves the technical problems through the following technical proposal.
The invention provides a method for predicting the cycle life of a lithium ion battery, which comprises the following steps:
s1, testing the first battery to be tested from the first time to the cycle time t under the acceleration working condition e A capacity retention rate at the target end condition until the capacity retention rate is equal to or lower than the capacity retention rate e of the target end condition; taking the circulation times x as an abscissa and the capacity retention rate y as an ordinate to obtain a first two-dimensional scatter diagram;
by piecewise fitting the data of the first two-dimensional scatter plot with a power function and a linear function, m inflection points (t 1 ，u 1 )、(t 2 ，u 2 ) Up to(t m ，u m ) The value of m represents the m inflection point, and m is more than or equal to 2;
the m inflection points are obtained by the following steps:
s1.1, fitting the data of the first two-dimensional scatter diagram by using a power function, and sequentially calculating until R by taking the cycle number as 1 as a starting point 2 When the total number is less than or equal to 0.95, recording the last meeting R 2 Coordinate value (t) corresponding to > 0.95 1 ，u 1 ) Is a first inflection point;
s1.2, continuing fitting the data of the rest first two-dimensional scatter diagram by using a linear function to obtain the number of loops as t 1 The first point is the starting point, and the calculation is sequentially carried out until R 2 When the temperature is less than or equal to 0.99, or selecting the last 3 or more points of the first two-dimensional scatter diagram to perform linear fitting, R 2 Less than or equal to 0.99, recording the last meeting R 2 Coordinate value (t) corresponding to > 0.99 2 ，u 2 ) Is a second inflection point;
wherein t is 2 And t 1 Not less than 50;
s1.3, repeating the step S1.2 until m inflection points are obtained;
s2, obtaining the relation between the cycle times and the capacity retention rate of the second battery to be tested, wherein the relation comprises the following steps of:
s2.1, testing the second battery to be tested which is the same as the first battery to be tested under the target working condition from the first time to the cycle times X 1 Capacity retention at number of cycles X 1 On the abscissa, capacity retention Y 1 Obtaining a second two-dimensional scatter diagram by taking the ordinate as the ordinate;
fitting the data of the second two-dimensional scatter plot by using a power function to satisfy R 2 > 0.95, resulting in function Y 1 ＝f(X 1 )；
The first inflection point (t 1 ，u 1 ) Corresponding capacity retention u 1 Substituting the function Y 1 ＝f(X 1 ) The method comprises the steps of carrying out a first treatment on the surface of the Obtaining a first predicted cycle number v 1 ；
50≤X 1 ≤t 1 ；
S2.2, the second battery to be tested is subjected to the testUnder the acceleration condition, test slave (X) 1 +1) the capacity retention rate from the beginning when the capacity retention rate is equal to the u 1 Stopping at the time, and keeping the capacity equal to the u 1 The number of cycles of (2) is X 1 ’；
S2.3, testing the second battery to be tested under the target working condition from (X 1 ' +1) to (X) 1 ' number of cycles X 2 ) The capacity retention rate is X 2 And v 1 The sum is the abscissa, the capacity retention Y 2 A third two-dimensional scatter diagram is obtained by taking the ordinate as the ordinate;
fitting the data of the third two-dimensional scatter diagram by using a linear function to satisfy R 2 > 0.99, resulting in function Y 2 ＝f(X 2 +v 1 )；
The second inflection point (t 2 ，u 2 ) Corresponding capacity retention u 2 Substituting the function Y 2 ＝f(X 2 +v 1 ) The method comprises the steps of carrying out a first treatment on the surface of the Obtaining the second predicted cycle number v 2 ；
X 2 Not less than 50, and (X) 1 ’+X 2 )≤t 2 ；
S2.4. Alternately repeating steps S2.2 and S2.3 until the capacity retention in step S2.2 is equal to said u m Stopping at the time, and keeping the capacity equal to the u m The number of cycles of (2) is X m ’；
S2.5, testing the second battery to be tested under the target working condition from (X m ' +1) to (X) m ' number of cycles X m+1 ) The capacity retention rate is X m+1 And v m The sum is the abscissa, the capacity retention Y m+1 Taking the ordinate as the ordinate, obtaining an (m+1) th two-dimensional scatter diagram;
fitting the data of the (m+1) th two-dimensional scatter diagram by using a linear function to satisfy R 2 > 0.99, resulting in function Y m+1 ＝f(X m+1 +v m )；
X m+1 Not less than 50, and (X) m ’+X m+1 )≤t e ；
Substituting the e into the function Y m+1 ＝f(X m+1 +v m ) The method comprises the steps of carrying out a first treatment on the surface of the Obtaining the target termination prediction cycle number v e 。
In the invention, the battery to be detected can be any type of lithium ion battery, such as a lithium iron phosphate battery, a ternary lithium battery, a lithium manganate battery, a lithium nickel manganate battery and the like.
The invention aims to obtain the circulation times corresponding to the capacity retention rate under the set working condition. The set working condition is the target working condition. According to the prediction method of the invention, the target termination prediction cycle times v corresponding to the capacity retention rate e of the target termination condition under the target working condition can be obtained e 。
In the present invention, the target termination condition refers to the target termination prediction cycle number v corresponding to the capacity retention rate e to be predicted e For example, the target termination prediction cycle number v corresponding to when the present invention is used to predict the capacity retention rate e to be 80% e The target termination condition is: the capacity retention e was 80%. Those skilled in the art will recognize that the typical capacity retention threshold is 80%, or may be 60%.
In the invention, the target working condition and the acceleration working condition comprise a test environment temperature, a charge cut-off voltage, a discharge cut-off voltage, a charge current, a charge power, a discharge current, a discharge power, a standing time during charge and discharge and the like. Preferably, in the acceleration condition, the acceleration condition is the same as other conditions (such as a charge cutoff voltage, a discharge cutoff voltage, a charge power level, a discharge power level, and a rest time during charge and discharge) of the target condition except that a test environment temperature of the acceleration condition is higher than a test environment temperature of the target condition, and/or except that a test current (which may be a charge current level and/or a discharge current level) of the acceleration condition is higher than a test current of the target condition.
More preferably, the test temperature of the acceleration working condition is higher than the test current of the target working condition, and the acceleration working condition is the same as other working conditions of the target working condition; the test temperature of the acceleration working condition is 40-60 ℃, and the test temperature of the target working condition is 23-27 ℃.
More preferably, the test conditions of the target working condition include: the test temperature is 23-27 ℃, the constant current charge of 1C is 3.65V, the constant voltage is 0.05C, the constant current discharge of 1C is 2.5V, the full discharge cut-off voltage is 2.0V, and the standing time during the charge and discharge period is 30min.
In the present invention, t 1 Is the number of cycles corresponding to the first inflection point, u 1 Is the capacity retention rate corresponding to the first inflection point until (t m ，u m ) And so on; t is t e The number of cycles corresponding to the capacity retention rate e for the target termination condition under the acceleration condition.
In the present invention, those skilled in the art will recognize that, after understanding the technical solution of the present invention, the inflection point in the step S1 corresponds to a point where the attenuation trend of the capacity retention rate changes. The number of the inflection points is preferably 2 to 3.
Preferably, when the number of inflection points is 2, fitting the data of the first two-dimensional scatter diagram by using a power function, and sequentially calculating until R by taking the cycle number as 1 as a starting point 2 When the total number is less than or equal to 0.95, recording the last meeting R 2 Coordinate value (t) corresponding to > 0.95 1 ，u 1 ) Is a first inflection point; continuing fitting the data of the remaining first two-dimensional scatter diagram by using a linear function, selecting the last 3 or more points of the first two-dimensional scatter diagram to perform linear fitting, R 2 Less than or equal to 0.99, recording the last meeting R 2 Coordinate value (t) corresponding to > 0.99 2 ，u 2 ) Is the second inflection point. V at this time v 2 The number v of predicted cycles corresponding to the capacity retention rate e of the target termination condition e 。
Preferably, when the number of inflection points is 3, fitting the data of the first two-dimensional scatter diagram by using a power function, and sequentially calculating until R by taking the cycle number as 1 as a starting point 2 When the total number is less than or equal to 0.95, recording the last meeting R 2 Coordinate value (t) corresponding to > 0.95 1 ，u 1 ) Is a first inflection point; fitting the remaining data of the first two-dimensional scatter plot with a linear function to a number of loops t 1 First point of the backSequentially calculating as starting point until R 2 When the total number is less than or equal to 0.99, recording the last meeting R 2 Coordinate value (t) corresponding to > 0.99 2 ，u 2 ) Is a second inflection point; continuing fitting the data of the remaining first two-dimensional scatter diagram by using a linear function, selecting the last 3 or more points of the first two-dimensional scatter diagram to perform linear fitting, R 2 Less than or equal to 0.99, recording the last meeting R 2 Coordinate value (t) corresponding to > 0.99 3 ，u 3 ) And is the third inflection point. V at this time v 3 The number v of predicted cycles corresponding to the capacity retention rate e of the target termination condition e 。
In the present invention, preferably, t is 1 ≤30。
In the present invention, the person skilled in the art knows that when repeating step S1.2, the corresponding t m And t m-1 Not less than 50.
In the invention, preferably, in S2.1, the data of the second two-dimensional scatter diagram is fitted by using a power function to satisfy R 2 > 0.99, resulting in function Y 1 ＝f(X 1 )。
On the basis of conforming to the common knowledge in the field, the above preferred conditions can be arbitrarily combined to obtain the preferred examples of the invention.
The reagents and materials used in the present invention are commercially available.
The invention has the positive progress effects that:
(1) The method adopts the target working condition and the acceleration working condition to alternately perform the cyclic acceleration test, thereby shortening the test period. According to the method, fitting is performed in real time according to the actual attenuation trend of the lithium battery, the number of inflection points and the corresponding functional relation are adjusted according to the requirement, and prediction and actual measurement are combined, so that the accuracy of a test result is ensured, and the purpose of rapidly testing the cycle life of the battery cell is achieved.
(2) The method of the invention can be used for adjusting the test conditions without carrying out special treatment on the battery cell alone.
Drawings
FIG. 1 is a first two-dimensional scatter plot of example 1 for a cyclic test under acceleration conditions.
Fig. 2 is a power function fitting result of example 1.
Fig. 3 is a linear function fitting result of example 1.
Fig. 4 is a comparison of the predicted result and the measured result of example 1.
Detailed Description
The invention is further illustrated by means of the following examples, which are not intended to limit the scope of the invention. The experimental methods, in which specific conditions are not noted in the following examples, were selected according to conventional methods and conditions, or according to the commercial specifications.
Example 1
2 identical lithium ion batteries are selected at will, and are respectively marked as a first battery to be tested and a second battery to be tested, and 50Ah square aluminum-shell lithium iron phosphate batteries in a laboratory are taken as research objects.
The target operating conditions are as follows: the test environment temperature is 25+/-2 ℃, the constant current charge of 1C is carried out until the voltage reaches 3.65V, the constant voltage reaches 0.05C, the constant current discharge of 1C reaches 2.5V (the full discharge cut-off voltage is 2.0V), the standing time during the charge and discharge period is 30min, and the cycle termination condition is that the discharge capacity retention rate e is not higher than 80% of the initial capacity;
the acceleration working conditions are the same as the target working conditions except that the test environment temperature is 60 ℃.
The steps for predicting the cycle life of the lithium ion battery of the battery to be measured are as follows,
1) And (3) carrying out a circulation test under the acceleration working condition to obtain an inflection point:
and (3) placing the first battery to be tested in an acceleration working condition to test the capacity retention rate under different cycle times until the capacity retention rate is equal to or lower than 80% of the capacity retention rate e of the target termination condition.
The first two-dimensional scattergram was obtained with the number of cycles x as the abscissa and the capacity retention y as the ordinate, as shown in fig. 1 and table 1.
Fitting the data of the first two-dimensional scatter diagram by using a power function, and sequentially calculating until R by taking the cycle number as 1 as a starting point 2 When the total number is less than or equal to 0.95, recording the last meeting R 2 Corresponding to > 0.95Coordinate value (t) 1 ，u 1 ) Is the first inflection point (u 1 ＝94.5％，t 1 =70), the resulting function y= 1.0045x -0.013 (as shown in FIG. 2), R 2 = 0.9538. Continuing to fit the remaining data of the first two-dimensional scatter plot using a linear function, selecting the last 3 points (600, 620, 630) of the first two-dimensional scatter plot for linear fitting to obtain R 2 = 0.9643 < 0.99, record the last satisfying R 2 Coordinate value (t) corresponding to > 0.99 2 ，u 2 ) Is the second inflection point, i.e. the second inflection point is (t e ，u e )(t e ＝620，u e = 79.70%) and fitting the remaining data of the first two-dimensional scatter plot with a linear function to obtain the function y= -0.0003x+0.9634, r 2 = 0.9996 (as shown in fig. 3).
TABLE 1 cycle data extraction results for 60℃acceleration
2) Placing a second battery to be tested which is the same as the first battery to be tested under a target working condition, and circulating X 1 The number of cycles of the cycle data and the discharge capacity retention rate data were extracted, and as shown in table 2 below, the number of cycles was taken as the abscissa and the discharge capacity retention rate was taken as the ordinate, and data fitting was performed by using a power function to obtain the formula Y 1 ＝f(X 1 )：y＝1.0029x -0.008 ，R 2 = 0.9937, assigning u to y 1 =94.5% and the x first predicted cycle number v is calculated 1 =1691, i.e. the number of cycles of the predicted battery to 94.5% capacity retention was 1691.
TABLE 2 extraction results of 25 ℃ target operating cycle data
| Number of cycles | Capacity retention rate |
| 1 | 100％ |
| 10 | 98.60％ |
| 20 | 98.00％ |
| 30 | 97.60％ |
| 40 | 97.31％ |
| 50 | 97.13％ |
3) Then placing the second battery to be tested under an acceleration working condition, and continuing to circulate for X2 '(the times of X2' are 52 times) until the capacity retention rate reaches 94.5%, and stopping;
4) Then the second battery to be tested is placed under the target working condition, and the cycle X is continued m+1 Number of cycles of extracting the cycle data (number of cycles from v =200 times 1 Start count=1691), discharge capacity retention rate data, as shown in table 3 below, data fitting was performed using a linear function with the number of cycles as the abscissa and the discharge capacity retention rate as the ordinate, to obtain formula Y m+1 ＝f(X m+1 +v m )：y＝-5E-05x+1.0229，R 2 = 0.9954, assigning 80% to y, and finding x=v e 4458 times, under the target condition of 25deg.CThe cycle life from 1C,2.5 to 3.65V to 80% of the discharge capacity retention rate was 4458 times.
TABLE 3 extraction results of 25 ℃ target operating cycle data
| Number of cycles | Capacity retention rate |
| 1692 | 94.50％ |
| 1742 | 94.21％ |
| 1792 | 94.04％ |
| 1842 | 93.78％ |
| 1892 | 93.56％ |
Fig. 4 is a comparison of predicted and measured data for the same battery, and it can be seen from fig. 4 that the cyclic attenuation trend of the battery cell predicted by the method of example 1 is similar to the cyclic attenuation trend of the measured battery cell. When the capacity retention rate reaches 80%, the predicted life is 4458 times, the actual life is 4613 times, and the predicted life and the actual life are not greatly different, which shows that the accuracy of the lithium ion battery cycle life prediction method is higher.
Claims (6)
1. A method for predicting the cycle life of a lithium ion battery comprising the steps of:
s1, testing the first battery to be tested from the first time to the cycle time t under the acceleration working condition e A capacity retention rate at the target end condition until the capacity retention rate is equal to or lower than the capacity retention rate e of the target end condition; taking the circulation times x as an abscissa and the capacity retention rate y as an ordinate to obtain a first two-dimensional scatter diagram;
by piecewise fitting the data of the first two-dimensional scatter plot with a power function and a linear function, m inflection points (t 1 ，u 1 ）、（t 2 ，u 2 ) Up to (t) m ，u m ) The value of m represents the m inflection point, and m is more than or equal to 2; u represents a capacity retention rate;
the m inflection points are obtained by the following steps:
s1.1, fitting the data of the first two-dimensional scatter diagram by using a power function, and sequentially calculating until R by taking the cycle number as 1 as a starting point 2 When the total number is less than or equal to 0.95, recording the last meeting R 2 Coordinate value (t) corresponding to > 0.95 1 ，u 1 ) Is a first inflection point;
s1.2, continuing fitting the data of the rest first two-dimensional scatter diagram by using a linear function to obtain the number of loops as t 1 The first point is the starting point, and the calculation is sequentially carried out until R 2 When the temperature is less than or equal to 0.99, or selecting the last 3 or more points of the first two-dimensional scatter diagram to perform linear fitting, R 2 Less than or equal to 0.99, recording the last meeting R 2 Coordinate value (t) corresponding to > 0.99 2 ，u 2 ) Is a second inflection point;
wherein t is 2 And t 1 Not less than 50;
s1.3, repeating the step S1.2 until m inflection points are obtained;
s2, obtaining the relation between the cycle times and the capacity retention rate of the second battery to be tested, wherein the relation comprises the following steps of:
s2.1, testing the second battery to be tested which is the same as the first battery to be tested under the target working condition from the first time to the cycle times X 1 Capacity retention at number of cycles X 1 On the abscissa, capacity retention Y 1 Obtaining a second two-dimensional scatter diagram by taking the ordinate as the ordinate;
fitting the data of the second two-dimensional scatter plot by using a power function to satisfy R 2 > 0.95, resulting in function Y 1 =f（X 1 ）；
The first inflection point (t 1 ，u 1 ) Corresponding capacity retention u 1 Substituting the function Y 1 =f（X 1 ) The method comprises the steps of carrying out a first treatment on the surface of the Obtaining a first predicted cycle number v 1 ；
50≤X 1 ≤t 1 ；
S2.2, testing the second battery to be tested under the acceleration working condition from the (X) 1 +1) the capacity retention rate from the beginning when the capacity retention rate is equal to the u 1 Stopping at the time, and keeping the capacity equal to the u 1 The number of cycles of (2) is X 1 ’；
S2.3, testing the second battery to be tested under the target working condition from (X 1 ' +1) to (X) 1 ' number of cycles X 2 ) The capacity retention rate is X 2 And v 1 The sum is the abscissa, the capacity retention Y 2 A third two-dimensional scatter diagram is obtained by taking the ordinate as the ordinate;
fitting the data of the third two-dimensional scatter diagram by using a linear function to satisfy R 2 > 0.99, resulting in function Y 2 =f（X 2 +v 1 ）；
The second inflection point (t 2 ，u 2 ) Corresponding capacity retention u 2 Substituting the function Y 2 =f（X 2 +v 1 ) The method comprises the steps of carrying out a first treatment on the surface of the Obtaining the second predicted cycle number v 2 ；
X 2 Not less than 50, and (X) 1 ’+X 2 ）≤t 2 ；
S2.4. Alternately repeating steps S2.2 and S2.3 until the capacity retention in step S2.2 is equal to said u m Stopping at the time, and keeping the capacity equal to the u m The number of cycles of (2) is X m ’；
S2.5, testing the second battery to be tested under the target working condition from (X m ' +1) to (X) m ’+Number of cycles X m+1 ) The capacity retention rate is X m+1 And v m The sum is the abscissa, the capacity retention Y m+1 Taking the ordinate as the ordinate, obtaining an (m+1) th two-dimensional scatter diagram;
fitting the data of the (m+1) th two-dimensional scatter diagram by using a linear function to satisfy R 2 > 0.99, resulting in function Y m+1 =f（X m+1 +v m ）；
X m+1 Not less than 50, and (X) m ’+X m+1 ）≤t e ；
Substituting the e into the function Y m+1 =f（X m+1 +v m ) The method comprises the steps of carrying out a first treatment on the surface of the Obtaining the target termination prediction cycle number v e ；
The test conditions of the target working condition comprise: the test temperature is 23-27 ℃, the constant current charge of 1C is 3.65V, the constant voltage is 0.05C, the constant current discharge of 1C is 2.5V, the full discharge cut-off voltage is 2.0V, and the standing time during the charge and discharge period is 30min;
the test temperature of the acceleration working condition is higher than the test temperature of the target working condition, and the acceleration working condition is the same as other working conditions of the target working condition; the test temperature of the acceleration working condition is 40-60 ℃; the other working conditions comprise a charge cut-off voltage, a discharge cut-off voltage, a charge power size, a discharge power size and a standing time during charge and discharge.
2. The method of predicting the cycle life of a lithium ion battery of claim 1, wherein the lithium ion battery is a lithium iron phosphate battery, a ternary lithium battery, a lithium manganate battery, or a lithium nickel manganate battery.
3. The method for predicting the cycle life of a lithium ion battery according to claim 1, wherein the number of inflection points is 2 to 3.
4. The method for predicting the cycle life of a lithium-ion battery of claim 3, wherein when the number of inflection points is 2, fitting the data of the first two-dimensional scattergram with a power functionSequentially calculating with the cycle number of 1 as the starting point until R 2 When the total number is less than or equal to 0.95, recording the last meeting R 2 Coordinate value (t) corresponding to > 0.95 1 ，u 1 ) Is a first inflection point; continuing fitting the data of the remaining first two-dimensional scatter diagram by using a linear function, selecting the last 3 or more points of the first two-dimensional scatter diagram to perform linear fitting, R 2 Less than or equal to 0.99, recording the last meeting R 2 Coordinate value (t) corresponding to > 0.99 2 ，u 2 ) Is a second inflection point;
or when the number of the inflection points is 3, fitting the data of the first two-dimensional scatter diagram by using a power function, and sequentially calculating until R by taking the cycle number as 1 as a starting point 2 When the total number is less than or equal to 0.95, recording the last meeting R 2 Coordinate value (t) corresponding to > 0.95 1 ，u 1 ) Is a first inflection point; fitting the remaining data of the first two-dimensional scatter plot with a linear function to a number of loops t 1 The first point is the starting point, and the calculation is sequentially carried out until R 2 When the total number is less than or equal to 0.99, recording the last meeting R 2 Coordinate value (t) corresponding to > 0.99 2 ，u 2 ) Is a second inflection point; continuing fitting the data of the remaining first two-dimensional scatter diagram by using a linear function, selecting the last 3 or more points of the first two-dimensional scatter diagram to perform linear fitting, R 2 Less than or equal to 0.99, recording the last meeting R 2 Coordinate value (t) corresponding to > 0.99 3 ，u 3 ) And is the third inflection point.
5. The method of predicting the cycle life of a lithium ion battery of claim 1, wherein t 1 ≤30。
6. The method of predicting cycle life of a lithium ion battery of claim 1, wherein in S2.1, fitting the data of the second two-dimensional scattergram with a power function satisfies R 2 > 0.99, resulting in function Y 1 =f（X 1 ）。
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