Method for predicting cycle life of battery

Abstract

The invention belongs to the field of battery testing, and particularly relates to a method for predicting the cycle life of a battery, and the cycle life of the battery is judged by performing accelerated testing on the battery to be tested in an overcharge mode to attenuate the content of Fe dissolved out and deposited on a negative electrode. According to the method, a fitting relational expression of a life prediction parameter-negative electrode Fe content and battery cycle index is obtained through short-term cycle test. And meanwhile, the negative electrode Fe content threshold value at the end of the battery cycle life is obtained through overcharge test acceleration, so that the predicted battery cycle life can be quickly calculated through a fitting relational expression, and the error is within 10%.

Description

Technical Field

[0001] The present invention belongs to the field of battery testing, and particularly relates to a method for predicting the cycle life of a battery. Background Art

[0002] Lithium iron phosphate batteries are widely used in new energy vehicles, energy storage, logistics vehicles, electric ships and other fields due to their high thermal stability, long cycle life and environmental protection characteristics, providing a reliable and lasting power source for them. As an important index for evaluating the service life of a battery, the cycle performance needs to be tested during the battery R & D stage. However, the cycle life of lithium iron phosphate batteries is as long as 5000 - 15000 times, resulting in a very long time required for cycle life testing, which seriously affects the product development cycle. Therefore, how to shorten the test time to predict the cycle life of lithium iron phosphate batteries is a technical problem that needs to be solved urgently by those skilled in the art.

[0003] Currently, there are many studies on the prediction of the cycle life of lithium iron phosphate batteries. With the deepening of the understanding of the cycle attenuation process of lithium iron phosphate batteries, the theory of the cycle prediction mechanism has become more mature. However, when using the established battery cycle life attenuation and prediction models for cycle life prediction, there are problems such as large errors and low credibility. Summary of the Invention

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a method for predicting the cycle life of a battery.

[0005] To achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0006] A method for predicting the cycle life of a battery, which performs an accelerated test on the battery to be tested in an overcharge manner, and judges the cycle life of the battery by the Fe content that decays and deposits on the negative electrode.

[0007] The method for predicting the cycle life of a battery includes the following steps: S1) Establishing a prediction formula for the life of the battery to be evaluated; S2) Testing the Fe content threshold of the negative electrode of the battery to be evaluated; S3) Predicting the cycle life of the battery to be evaluated.

[0008] The specific steps of step S1) are as follows:

[0009] 1.1) Performing a short-term cycle test on multiple batteries to be evaluated under a cycle regime;

[0010] 1.2) After the short-term cycle, the battery is fully discharged and then disassembled;

[0011] 1.3) Testing the Fe content in the negative electrode of the disassembled battery to be evaluated;

[0012] 1.4) Establishing a prediction formula for the life of the battery to be evaluated based on the Fe content in the negative electrode and the number of battery cycles.

[0013] The specific steps of step 1.1) are as follows: Take multiple batteries and conduct cyclic tests under the cyclic regime of the life to be evaluated, and set different numbers of cycles.

[0014] Alternatively, use the capacity retention rate as the test termination condition, set it with any capacity retention rate difference, and record the corresponding number of cycles of the battery.

[0015] The cyclic regime is kept consistent with the actual cyclic regime parameters of the battery to be evaluated.

[0016] Preferably, in the constant current and constant voltage mode, it is charged at a constant current of 0.2C - 1.0C to 3.65V, the cut-off current is 0.05C = 2.5A, left standing for 30 minutes, discharged at a constant current of 0.2C - 1.0C to 2.0V, and left standing for 30 minutes.

[0017] Preferably, in the constant power charge and discharge mode, it is charged at a constant power of 0.2CP - 1.0CP to 3.65V, the cut-off current is 0.05C = 2.5A, left standing for 30 minutes, discharged at a constant power of 0.2C - 1.0C to 2.0V, and left standing for 30 minutes.

[0018] Preferably, the current for full discharge in step 1.2) is less than or equal to 0.5C. Preferably, first discharge the battery to 2.0V at 0.5C = 25A, leave it standing for 30 minutes, then discharge it to 2.0V again at 0.1C = 5A, leave it standing for 30 minutes, and then discharge it to 2.0V at 0.05C = 2.5A.

[0019] The specific steps of step 1.3) are as follows: Take the negative electrode sheet of the battery to be evaluated after disassembly, wash it with DMC solvent and then dry it; scrape an appropriate amount of sample from the negative electrode sheet, fully digest the sample with acid, make up the volume, and test the Fe element content with an inductively coupled plasma emission spectrometer or an atomic absorption spectrometer to obtain the Fe content in the negative electrode. Preferably, the acid is hydrochloric acid, nitric acid or a mixture of the two.

[0020] The specific steps of step 1.4) are as follows: Use the Fe content in the negative electrode as the abscissa (x), and the number of cycles of the battery as the ordinate (y), plot a graph, and conduct fitting analysis on its trend to obtain the relationship formula between the number of cycles and the Fe content in the negative electrode y = kx + b, where x is the Fe content in the negative electrode, y is the number of cycles of the battery, and k and b are constants respectively.

[0021] The specific steps of step S2) are as follows:

[0022] 2.1) Take one battery to be evaluated and overcharge it with the same charging regime as in step S1); preferably, charge the battery at a constant current of 0.5C - 1.0C until it reaches 4.9 - 5.3V, maintain a constant voltage for 0.5 - 1h, and then discharge it at 0.5C - 1.0C. The cut-off voltage is the same as the discharge cut-off voltage in the cycling regime of step 1.1);

[0023] 2.2) Discharge the battery obtained in step 2.1) fully with the same discharging regime as in step 1.2);

[0024] 2.3) Disassemble the battery obtained in step 2.2) and test the Fe content in the negative electrode in the same disassembly manner as in step 1.3); obtain the Fe content in the negative electrode, which is the threshold value of the Fe content in the negative electrode for predicting the battery cycle life.

[0025] The specific steps of step S3) are as follows: Substitute the threshold value of the negative electrode Fe content into the prediction formula in step 1.4) to obtain the predicted number of cycles for predicting the battery cycle life.

[0026] The battery mentioned above is a lithium iron phosphate battery.

[0027] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0028] During the battery cycling process, during charging, lithium deintercalation reaction occurs at the positive electrode, and due to reactions such as the formation of the SEI film at the negative electrode, the amount of lithium re-inserted into the positive electrode during discharge is insufficient. Repeating this process, the amount of lithium re-inserted into the positive electrode becomes less and less. Although the crystal structure of the lithium iron phosphate material is relatively stable and will not undergo crystal structure changes and collapses due to continuous lithium deintercalation, through in-situ XRD testing, it is found that after long-term cycling, the content of lithium iron phosphate in the positive electrode decreases, while the content of iron phosphate gradually increases, resulting in a decrease in the charge-discharge capacity of the battery. During the continuous cycling process, since the voltage range of the battery charge and discharge remains unchanged, for the remaining lithium iron phosphate in the positive electrode, excessive lithium deintercalation will occur during charging at the same voltage. Therefore, in principle, the lithium iron phosphate positive electrode is equivalent to undergoing mild overcharging during the battery cycling process, and with cycle attenuation, the degree of overcharging deepens.

[0029] The technical solution of this application uses an overcharging method to conduct accelerated test research on the battery and finds that the Fe content deposited on the negative electrode due to attenuation and dissolution of the lithium iron phosphate positive electrode is basically the same as the Fe content at the end of the battery cycle life.

[0030] Therefore, the present invention obtains the fitting relationship between the life prediction parameter - the Fe content of the negative electrode and the number of battery cycles through short-term cycle tests. At the same time, the threshold value of the Fe content of the negative electrode at the end of the battery cycle life is obtained by accelerating the overcharge test, so that the predicted battery cycle life can be quickly calculated through the fitting relationship, and the error is within 10%.

[0031] The prediction method provided by the present invention is based on short-term cycles under the actual battery cycle regime, so it is applicable to life prediction under various cycle regimes. It is not necessary to perform accelerated cycle tests by changing the battery test voltage, rate, and temperature conditions, ensuring that no other cycle influencing factors are introduced, so the prediction accuracy is relatively high.

[0032] The prediction method provided by the present invention is based on short-term cycles under the actual battery cycle regime. Only three cycle numbers of tests are required to obtain the linear fitting relationship. Therefore, the cycle test can be shortened to within 200 - 400 times, which can greatly shorten the time of the cycle life test, shorten the battery development cycle, and thus improve the battery R & D efficiency. Description of the Drawings

[0033] Figure 1 It is a scatter plot and fitting relationship diagram of the Fe content of the negative electrode and the number of cycles in Example 1;

[0034] Figure 2 It is the cycle curve of the 50Ah experimental battery in Example 1;

[0035] Figure 3 It is a scatter plot and fitting relationship diagram of the Fe content of the negative electrode and the number of cycles in Example 2;

[0036] Figure 4 It is the cycle curve of the 50Ah experimental battery in Example 2. Detailed Embodiments

[0037] In order to enable those skilled in the art of the present technology to better understand the technical solutions of the present invention, the present invention will be further described in detail below with reference to the drawings and the best embodiments.

[0038] Example 1

[0039] In this example, the test sample is a 50Ah square experimental battery, the positive electrode of which is lithium iron phosphate and the negative electrode is graphite. The 1C (1C = 50A) cycle regime of this battery at 45°C is as follows: constant current charge at 1C to 3.65V, cut-off current is 0.05C, stand for 30 minutes, constant current discharge at 1C to 2.0V, stand for 30 minutes. In order to predict the 1C cycle life of this battery at 45°C, the following experiments and analyses are carried out:

[0040] A method for predicting the cycle life of a battery, which conducts an accelerated test on the battery to be tested by overcharging, and judges the cycle life of the battery based on the content of Fe dissolved and deposited on the negative electrode due to attenuation.

[0041] Specifically, it includes the following steps:

[0042] S1) Establishment of a prediction formula for the life of the battery to be evaluated;

[0043] 1.1) Conduct short-term cycle tests on multiple batteries to be evaluated under a cycle regime;

[0044] Take 3 batteries with a capacity of 50 Ah to be evaluated, keep 1 as a battery with a 100% capacity retention rate, and place the other 2 in a constant temperature oven at 45°C for short-term cycle tests.

[0045] Set the cycle regime as constant current charging at 1C = 50A to 3.65V, with a cut-off current of 0.05C = 2.5A, stand still for 30 minutes, then discharge at 1C = 50A to 2.0V, and stand still for 30 minutes.

[0046] The end condition of the battery cycle is based on capacity cut-off. The first battery stops when its capacity decays to 98%, that is, 50 * 98% = 49.00 Ah; the second battery stops when its capacity decays to 95%, that is, 50 * 95% = 47.50 Ah. Record the corresponding cycle times of the batteries respectively, and the results are shown in Table 1.

[0047] Table 1

[0048] Battery number Capacity retention rate Number of cycles Negative electrode Fe content / ppm 1 100％ 0 3.3 2 98％ 35 7.0 3 95％ 253 31.6

[0049] 1.2) Disassemble the battery after full discharge after short-term cycling;

[0050] Fully discharge the above-mentioned non-cycled retained battery and the battery after short-term cycling. First, discharge the battery at 0.5C = 25A to 2.0V, stand still for 30 minutes, then discharge again at 0.1C = 5A to 2.0V, stand still for 30 minutes, and then discharge at 0.05C = 2.5A to 2.0V. In this embodiment, this is used as the process of full discharge.

[0051] 1.3) Test the Fe content in the negative electrode of the battery to be evaluated after disassembly;

[0052] Disassemble the above-mentioned discharged battery, take its negative electrode plate, wash it with DMC solvent and dry it. Scrape an appropriate amount of powder sample from the negative electrode plate, fully digest it with hydrochloric acid, make up the volume, and then test the Fe element content with an inductively coupled plasma emission spectrometer to obtain the Fe content in the negative electrodes of 3 batteries respectively, as shown in Table 1.

[0053] 1.4) Establish a prediction formula for the life of the battery to be evaluated based on the Fe content in the negative electrode and the cycle times of the battery.

[0054] The above short - term cycle battery data was sorted out as shown in Table 1. Taking the Fe content in the negative electrode as the abscissa (x) and the cycle number of the battery as the ordinate (y), a scatter plot was made, as shown in Figure 1 , and the trend was fitted and analyzed to obtain the linear fitting relationship formula between the Fe content in the negative electrode and the cycle number: y = 8.9116x - 28.466, where x is the Fe content in the negative electrode and y is the cycle number of the battery.

[0055] S2) Testing the threshold of the Fe content in the negative electrode of the battery to be evaluated;

[0056] 2.1) Another 50Ah battery to be evaluated was taken and charged at a constant current of 1C = 50A to 5.0V with the same charging regime as the cycle regime, held at a constant voltage for 1h, and then discharged at 1.0C until the cut - off voltage of 2.0V.

[0057] 2.2) The above battery was fully discharged. First, the battery was discharged to 2.0V at 0.5C = 25A, left standing for 30 minutes, then discharged to 2.0V again at 0.1C = 5A, left standing for 30 minutes, and then discharged to 2.0V at 0.05C = 2.5A.

[0058] 2.3) The discharged battery was disassembled, and its negative electrode plate was taken, cleaned with DMC solvent and dried. An appropriate amount of powder sample was scraped from the negative electrode plate, fully digested with hydrochloric acid and made up to volume, and then the Fe element content was tested with an inductively coupled plasma emission spectrometer. The Fe content in the negative electrode of the over - charged battery was obtained as 577ppm, which is the threshold x of the Fe content in the negative electrode for predicting the battery cycle life. L = 577ppm.

[0059] S3) Prediction of the cycle life of the battery to be evaluated

[0060] Substitute the threshold x of the Fe content in the negative electrode obtained in step 2.3) L = 577ppm into the life prediction formula y = 8.9116x - 28.466, and calculate y = 8.9116 * 577 - 28.466 = 5113, that is, the cycle life of the 50Ah experimental battery to be evaluated is 5113 times.

[0061] The cycle curve of this experimental battery is as shown in Figure 2 shown. It can be seen from Figure 2 that the decay trend of the cycle curve of this battery changes at 4700 times, that is, the actual cycle life of this battery is 4700 times, while the life prediction value calculated by the life prediction method provided by the present invention is 5113 times, and the prediction error is 8.8%.

[0062] Example 2

[0063] To enable those skilled in the art of this technology to better understand the technical solution of the present invention, the present invention will be further described in detail below in conjunction with the accompanying drawings and the best embodiments.

[0064] In this embodiment, the test sample is a 50Ah square experimental battery, the positive electrode of the battery is lithium iron phosphate, and the negative electrode is graphite. The battery is subjected to constant power charge and discharge cycling at 45°C. Specifically, it is charged at a constant power of 1CP (160W) until the cut-off voltage of 3.65V, left standing for 30 minutes, and then discharged at a constant power of 1CP (160W) until the cut-off voltage of 2.0V, left standing for 30 minutes. In order to predict the 1CP constant power charge and discharge cycle life of the battery at 45°C, the following experiments and analyses are carried out:

[0065] A method for predicting the cycle life of a battery, accelerating the test on the battery to be tested by overcharging, and judging the cycle life of the battery based on the Fe content that decays and deposits on the negative electrode.

[0066] Specifically, it includes the following steps:

[0067] S1) Establishment of the battery life prediction formula to be evaluated;

[0068] 1.1) Conduct short-term cycle tests on multiple batteries to be evaluated under a cycle system;

[0069] Take 3 50Ah batteries to be evaluated, keep 1 as a battery with a 100% capacity retention rate, and place the other 2 in a 45°C constant temperature oven for short-term cycle tests.

[0070] Set the cycle system to charge at a constant power of 1CP = 160W to 3.65V, left standing for 30 minutes, discharge at a constant power of 1CP = 160W to 2.0V, left standing for 30 minutes.

[0071] The battery cycle end conditions are all based on capacity cut-off. The first battery stops when its capacity decays to 98%, that is, 50 * 98% = 49Ah; the second battery stops when its capacity decays to 96%, that is, 50 * 96% = 48Ah, and record the corresponding cycle times of the batteries respectively, as shown in Table 2.

[0072] Table 2

[0073] Battery number Capacity retention rate Number of cycles Negative electrode Fe content / ppm 1 100％ 0 3.2 2 98％ 180 35.1 3 96％ 400 76.2

[0074] 1.2) Disassemble the battery after full discharge after short-term cycling;

[0075] Fully discharge the above-mentioned non-cycled reserved batteries and the batteries after short-term cycling. First, discharge the battery at 0.5C = 25A until 2.0V, let it stand for 30 minutes, then discharge it again at 0.1C = 5A until 2.0V, and after standing for 30 minutes, discharge it at 0.05C = 2.5A until 2.0V. In this embodiment, this is used as the process of full discharge.

[0076] 1.3) Test the Fe content in the negative electrode of the battery to be evaluated after disassembly;

[0077] Disassemble the above-mentioned discharged battery, take its negative electrode plate, wash it with DMC solvent and then dry it. Scrape an appropriate amount of powder sample from the negative electrode plate, fully digest it with hydrochloric acid, make up the volume, and then test the Fe element content with an inductively coupled plasma emission spectrometer to obtain the Fe content in the negative electrodes of 3 batteries, as shown in Table 2.

[0078] 1.4) Establish a prediction formula for the battery life to be evaluated based on the Fe content in the negative electrode and the number of battery cycles.

[0079] Organize the above-mentioned short-term cycling battery data as shown in Table 2. Use the Fe content in the negative electrode as the abscissa (x) and the number of battery cycles as the ordinate (y) to make a scatter plot, as Figure 3 shown, and perform fitting analysis on its trend to obtain the linear fitting relationship formula between the Fe content in the negative electrode and the number of cycles y = 5.4735x - 15.572, where x is the Fe content in the negative electrode and y is the number of battery cycles.

[0080] S2) Test the threshold of the Fe content in the negative electrode of the battery to be evaluated;

[0081] Take another 50Ah battery to be evaluated, charge it at a constant current of 1C = 50A to 4.9V with the same charging current as the cycling regime, keep it at a constant voltage for 1h, and then discharge it at 1.0C, with a cut-off voltage of 2.0V;

[0082] 2.2) Fully discharge the above-mentioned battery. First, discharge the battery at 0.5C = 25A until 2.0V, let it stand for 30 minutes, then discharge it again at 0.1C = 5A until 2.0V, and after standing for 30 minutes, discharge it at 0.05C = 2.5A until 2.0V.

[0083] Disassemble the above-mentioned discharged battery, take its negative electrode plate, wash it with DMC solvent and then dry it. Scrape an appropriate amount of powder sample from the negative electrode plate, fully digest it with hydrochloric acid, make up the volume, and then test the Fe element content with an inductively coupled plasma emission spectrometer. The Fe content in the negative electrode of the overcharged battery is obtained as 549 ppm, which is the threshold x L = 549 ppm of the Fe content in the negative electrode for predicting the battery cycle life.

[0084] S3) Prediction of the cycle life of the battery to be evaluated

[0085] Substitute the negative electrode Fe content threshold x L = 549 ppm obtained in step 2.3) into the life prediction formula y = 5.4735x - 15.572, and calculate y = 5.4735 * 549 - 15.572 = 2989, that is, the cycle life of the 50 Ah experimental battery to be evaluated is 2989 times.

[0086] The cycle curve of this experimental battery is as Figure 4 shown. It can be seen from Figure 4 that the cycle life of this battery is 3200 times, while the life prediction value calculated by the life prediction method provided by the present invention is 2989 times, and the prediction error is -6.6%.

[0087] In summary, the present invention obtains the fitting relationship between the life prediction parameter - the negative electrode Fe content and the battery cycle times through short-term cycle tests. At the same time, the negative electrode Fe content threshold at the end of the battery cycle life is obtained by accelerating through overcharge tests, so that the predicted battery cycle life can be quickly calculated through the fitting relationship, and the error is within 10%.

[0088] The prediction method provided by the present invention is based on short-term cycles under the actual battery cycle regime, so it is applicable to life prediction under various cycle regimes. It is not necessary to perform accelerated cycle tests by changing the battery test voltage, rate, and temperature conditions, ensuring that no other cycle influencing factors are introduced, so the prediction accuracy is relatively high.

[0089] The prediction method provided by the present invention is based on short-term cycles under the actual battery cycle regime. Only three cycle times of tests are required to obtain a linear fitting relationship. Therefore, the cycle test can be shortened to within 200 - 400 times, which can greatly shorten the time of the cycle life test, shorten the battery development cycle, and thus improve the battery R & D efficiency.

[0090] The above are only the preferred embodiments of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A method for predicting battery cycle life, characterized in that: The test battery is accelerated by overcharging to determine the battery cycle life based on the Fe content that is dissolved and deposited at the negative electrode.

2. The method for predicting battery cycle life according to claim 1, characterized in that: The steps include: S1) Establishment of a life prediction formula for the battery to be evaluated; S2) Testing of the Fe content threshold of the negative electrode of the battery to be evaluated; S3) Prediction of cycle life of the battery to be evaluated.

3. The method for predicting battery cycle life according to claim 2, characterized in that: The specific steps of step S1) are: 1.1) Conduct short-term cycle tests on multiple batteries to be evaluated under the cycle system; 1.2) After short-term cycling, the battery is fully discharged and then disassembled; 1.3) Testing the Fe content in the negative electrode of the disassembled battery to be evaluated; 1.4) Establish a life prediction formula for the battery to be evaluated based on the negative electrode Fe content and the number of battery cycles.

4. The method for predicting battery cycle life according to claim 3, characterized in that: The specific steps of step 1.1) are: taking multiple batteries to perform cycle tests under the cycle format of the life to be evaluated, setting different cycle times; Alternatively, the capacity retention rate is used as the test termination condition, and any capacity retention rate difference is set to record the corresponding number of cycles of the battery; The cycle format is to maintain the same parameters as the actual cycle of the battery to be evaluated; Preferably, the constant current and constant voltage mode is 0.2C-1.0C constant current charging to 3.65V, the cut-off current is 0.05C=2.5A, standing for 30 minutes, 0.2C-1.0C constant current discharge to 2.0V, standing for 30 minutes; Preferably, the constant power charge and discharge mode is 0.2CP-1.0CP constant power charging to 3.65V, the cut-off current is 0.05C=2.5A, standing for 30 minutes, 0.2C-1.0C constant power discharging to 2.0V, standing for 30 minutes.

5. The method for predicting battery cycle life according to claim 3, characterized in that: Step 1.2) The current for full discharge is less than or equal to 0.5C. Preferably, the battery is first discharged to 2.0V at 0.5C=25A, left standing for 30 minutes, and then discharged to 2.0V at 0.1C=5A. After leaving standing for 30 minutes, it is discharged to 2.0V at 0.05C=2.5A.

6. The method for predicting battery cycle life according to claim 3, characterized in that: The specific steps of step 1.3) are: take the disassembled negative electrode sheet of the battery to be evaluated, wash it with DMC solvent and then dry it; scrape an appropriate amount of sample from the negative electrode sheet, fully digest the sample with acid, and after constant volume, use an inductively coupled plasma emission spectrometer or an atomic absorption spectrometer to test the Fe element content to obtain the Fe content in the negative electrode; preferably, the acid is hydrochloric acid, nitric acid or a mixture of the two.

7. The method for predicting battery cycle life according to claim 3, characterized in that: The specific steps of step 1.4) are: use the Fe content in the negative electrode as the horizontal axis (x) and the number of battery cycles as the vertical axis (y), draw a graph, and perform fitting analysis on its trend to obtain the relationship between the number of cycles and the Fe content in the negative electrode, y=kx+b, where x is the Fe content in the negative electrode, y is the number of battery cycles, and k and b are constants.

8. The method for predicting battery cycle life according to claim 3, characterized in that: The specific steps of step S2) are: 2.1) Take a battery to be evaluated and overcharge it using the same charging method as the cycle method in step S1); Preferably, the battery is charged at a constant current of 0.5C-1.0C to 4.9-5.3V, at a constant voltage of 0.5-1h, and then discharged at 0.5C-1.0C, with the cut-off voltage being consistent with the discharge cut-off voltage in the cycle system in step 1.1); 2.2) fully discharging the battery obtained in step 2.1) using the same discharge method as in step 1.2); 2.3) disassembling the battery obtained in step 2.2) in the same disassembly manner as in step 1.3) and testing the Fe content in the negative electrode of the battery; obtaining the Fe content in the negative electrode, which is the threshold value of the Fe content in the negative electrode for predicting the battery cycle life.

9. The method for predicting battery cycle life according to claim 8, characterized in that: The specific steps of step S3) are: substituting the threshold value of the negative electrode Fe content into the prediction formula in step 1.4) to obtain the number of cycles to predict the battery cycle life.

10. The method for predicting battery cycle life according to claim 1, characterized in that: The battery is a lithium iron phosphate battery.

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