Method for predicting problem point of cycle failure of battery

Abstract

The invention belongs to the field of batteries, and particularly relates to a method for predicting a battery cycle failure problem point. Comprising the following steps of: 1, selecting a group of batteries; then the battery is charged and stored at high temperature; step 2, carrying out charging and discharging test on the stored battery, and stopping the test when the capacity of the battery is attenuated to a target SOH (state of health); and step 3, analyzing the batteries, taking the batteries out of the constant-temperature box, and disassembling the batteries to judge the cycle failure problem points of the batteries. According to the technical scheme, the possible electrical performance failure problem point of the specific battery can be quickly predicted, a cycle test does not need to be carried out for a long time, and the time cost is saved; according to the method, a specific battery cycle failure problem point can be locked, and compared with the prediction of the cycle life, the battery design can be optimized aiming at the specific problem point, so that the research and development period is greatly shortened.

Description

Technical Field

[0001] The invention belongs to the field of batteries, and in particular relates to a method for predicting battery cycle failure problem points. Background Art

[0002] In modern society, battery technology has become one of the indispensable and important technologies. Among them, lithium iron phosphate (LiFePO4) full batteries have become a widely used battery type in electric vehicles and energy storage systems due to their high safety, long cycle life and good environmental performance. However, the battery may have electrical performance failure problems during use, which will not only affect the performance and service life of the battery, but also may bring safety hazards. Therefore, how to quickly evaluate the methods that affect the cycle life of lithium iron phosphate full batteries, and how to predict in advance the causes of electrical performance failure that may occur during battery use, have become urgent problems to be solved in the field of battery technology.

[0003] In the existing technology, the cycle life test is usually used to evaluate the cycle life of lithium iron phosphate full batteries. This test method usually involves repeatedly charging and discharging the battery under constant current and constant temperature conditions until the battery capacity drops to a predetermined value, and then the battery cycle performance can be evaluated. Although this method can more accurately evaluate the cycle life of the battery, it takes a lot of time and resources. In addition, there are some methods that predict the cycle life by combining preliminary cycle data with simulation and other means. Although this method can predict the cycle life of the battery more quickly and accurately, it cannot predict the specific problems that affect the cycle life of the battery, and does not provide effective support for quickly solving problems in the product development process. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a method for predicting battery cycle failure problem points.

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

[0006] A method for predicting battery cycle failure problem points comprises the following steps:

[0007] Step 1: Select a set of batteries; then charge the batteries and store them at high temperature;

[0008] Step 2: Perform charge and discharge tests on the stored battery, and stop the test when the battery capacity decays to the target SOH;

[0009] Step 3: Battery analysis: remove the batteries from the constant temperature box and disassemble them to determine the battery cycle failure problem points.

[0010] In step 1, the battery is charged to 50% SOC for high temperature storage.

[0011] In step 1, the high temperature storage conditions are: storage temperature is T, 60°C ≥ T ≥ 30°C, storage time is M, 15 days ≥ M ≥ 1 day.

[0012] In step 2, the charge and discharge voltage range is B1≥voltage≥B2, 3.65V≥B1≥3.55V, 3.65V≥B2≥3.2V; preferably, B1 is 3.65V and B2 is 3.47V.

[0013] In step 2, the charge and discharge voltage range is C1≥voltage≥C2, 3.2V≥C1≥2.5V, 2.5V≥C2≥2V. Preferably, C1 is 3.2V and C2 is 2.5V.

[0014] Preferably, the batteries in step 2 are divided into two groups, group X and group Y, and charge and discharge tests are performed on each group;

[0015] Among them, the charge and discharge voltage range of group X is B1≥voltage≥B2, 3.65V≥B1≥3.55V, 3.65V≥B2≥3.2V;

[0016] The charge and discharge voltage range of group Y is C1≥voltage≥C2, 3.2V≥C1≥2.5V, 2.5V≥C2≥2V.

[0017] B1 is 3.65V, B2 is 3.47V; C1 is 3.2V, C2 is 2.5V.

[0018] 8. The method for predicting battery cycle failure problem points according to claim 1, characterized in that the full battery is a lithium iron phosphate full battery.

[0019] In step 2, the target SOH is 60% SOH.

[0020] The method for determining battery cycle failure in step three is to observe and record the status of the positive and negative electrode materials of the battery, whether there is gas production inside the battery, make button batteries for the disassembled electrodes, and perform physical and chemical analysis to further determine the changes that have occurred in the battery during the test.

[0021] Compared with the prior art, the present invention has the following beneficial effects:

[0022] The technical solution of the present invention can quickly predict the electrical performance failure problem points that may exist in a specific battery, without spending a long time on cycle testing, thus saving time costs; the present invention can lock in specific battery cycle failure problem points, and compared with the prediction of cycle life, the battery design can be optimized according to the specific problem points, greatly shortening the research and development cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1is the SEM image of the negative electrode after cycling of Example 1 (Group X);

[0024] Figure 2 This is the SEM image of the negative electrode after the cycle of Comparative Example 1;

[0025] Figure 3 It is the cycle diagram of Example 1 (Group X) and Comparative Example 2. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and the best embodiments.

[0027] Example 1

[0028] A method for predicting battery cycle failure problem points comprises the following steps:

[0029] Step 1: Select 6 fresh 2Ah lithium iron phosphate soft-pack batteries with good consistency, charge the batteries to 50% SOC, place the batteries in a constant temperature incubator at 45°C, and let them stand for 15 days.

[0030] Step 2: After the placement, take out the batteries and divide them into two groups, Group X and Group Y. Perform charge and discharge cycle test at 1C rate. The test ranges are 3.47V-3.65V (Group X) and 2.5V-3.2V (Group Y). The test temperature is 45°C. The test is stopped when the battery capacity decays to 60% SOH.

[0031] Step 3: Analyze the battery data after the test, dissect the battery, and analyze the components and phases of the disassembled electrodes, gases, and electrolytes to find the failure points.

[0032] Example 2

[0033] A method for predicting battery cycle failure problem points comprises the following steps:

[0034] Step 1: Select 6 fresh 2Ah lithium iron phosphate soft-pack batteries with good consistency, charge the batteries to 50% SOC, place the batteries in a constant temperature incubator at 45°C, and let them stand for 15 days.

[0035] Step 2: After the placement, take out the batteries and divide them into two groups, Group X and Group Y. Perform charge and discharge cycle test at 1C rate. The test ranges are 3.51V-3.65V (Group X) and 2.0V-3.0V (Group Y). The test temperature is 45°C. Stop the test when the battery capacity decays to 60% SOH.

[0036] Step 3: Analyze the battery data after the test and dissect the battery. Perform composition and phase analysis on the disassembled pole pieces, gas composition, and electrolyte to find the failure point.

[0037] Example 3

[0038] A method for predicting battery cycle failure problem points comprises the following steps:

[0039] Step 1: Select 6 fresh 2Ah lithium iron phosphate soft-pack batteries with good consistency, charge the batteries to 50% SOC, place the batteries in a constant temperature incubator at 60°C, and let them stand for 15 days.

[0040] Step 2: After the placement, take out the batteries and divide them into two groups, Group X and Group Y. Perform charge and discharge cycle test at 1C rate. The test ranges are 3.47V-3.65V (Group X) and 2.5V-3.2V (Group Y). The test temperature is 60°C. Stop the test when the battery capacity decays to 60% SOH.

[0041] Step 3: Analyze the battery data after the test and dissect the battery. Perform composition and phase analysis on the disassembled pole pieces, gas composition, and electrolyte to find the failure point.

[0042] Comparative Example 1

[0043] Six 2Ah fresh lithium iron phosphate soft-pack batteries with good consistency were selected, the batteries were charged to 50% SOC, and the batteries were placed in a constant temperature incubator at 45°C for 15 days.

[0044] After the placement, the battery was taken out and a charge and discharge cycle test was performed at a 1C rate. The test range was 2.5V-3.65V, the test temperature was 45°C, and the test was stopped when the battery capacity decayed to 60% SOH.

[0045] The battery data after the test is analyzed, and the battery is dissected, and the components and phases of the disassembled electrodes, gas composition, and electrolyte are analyzed to find the failure points.

[0046] Comparative Example 2

[0047] Six 2Ah fresh lithium iron phosphate soft-pack batteries with good consistency were selected, the batteries were charged to 50% SOC, and the batteries were placed in a constant temperature incubator at 25°C for 15 days.

[0048] After the placement, the battery was taken out and a charge and discharge cycle test was performed at a 1C rate. The test range was 2.5V-3.65V, the test temperature was 25°C, and the test was stopped when the battery capacity decayed to 60% SOH.

[0049] The battery data after the test is analyzed, and the battery is dissected, and the components and phases of the disassembled electrodes, gas composition, and electrolyte are analyzed to find the failure points.

[0050] Table 1 shows the cycle results of the examples and comparative examples.

[0051] Table 1 Battery parameters after cycling

[0052]

[0053] Tests and Results

[0054] Figure 1 is the SEM image of the negative electrode after cycling of Example 1 (Group X); Figure 2 This is the SEM image of the negative electrode after the cycle of Comparative Example 1; Figure 3 It is the cycle diagram of Example 1 (Group X) and Comparative Example 2. By comparing the results after the battery cycle, it can be found that the final battery internal resistance of the embodiment of the rapid test of this application is higher, the gas production is more, and the failure characteristics are more obvious compared with the comparative example of the normal test, and the results of the final cycle can be used as a reference for comparison. The negative electrode of this group of batteries is quickly evaluated to continuously fall off and react with the electrolyte, produce gas, and Fe dissolves from the positive electrode, resulting in the cycle failure of the battery, and the results are not much different. The experimental time is short, achieving the purpose of predicting the failure problem point in advance.

[0055] In summary, the technical solution of the present invention can quickly predict the electrical performance failure problem points that may exist in a specific battery, without spending a long time on cycle testing, thus saving time and cost; the present invention can lock in specific battery cycle failure problem points, and compared with the prediction of cycle life, the battery design can be optimized according to specific problem points, greatly shortening the research and development cycle.

[0056] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for predicting battery cycle failure problem points, characterized in that: The steps include: Step 1: Select a set of batteries; then charge the batteries and store them at high temperature; Step 2: Perform charge and discharge tests on the stored battery, and stop the test when the battery capacity decays to the target SOH; Step 3: Battery analysis: remove the batteries from the constant temperature box and disassemble them to determine the battery cycle failure problem points.

2. The method for predicting battery cycle failure problem points according to claim 1, characterized in that: In step 1, the battery is charged to 50% SOC for high temperature storage.

3. The method for predicting battery cycle failure problem points according to claim 1, characterized in that: In step 1, the high temperature storage conditions are: storage temperature is T, 60°C ≥ T ≥ 30°C, storage time is M, 15 days ≥ M ≥ 1 day; preferably, T is 45°C and M is 15 days.

4. The method for predicting battery cycle failure problem points according to claim 1, characterized in that: In step 2, the charge and discharge voltage range is B1≥voltage≥B2, 3.65V≥B1≥3.55V, 3.65V≥B2≥3.2V; preferably, B1 is 3.65V and B2 is 3.47V.

5. The method for predicting battery cycle failure problem points according to claim 1, characterized in that: In step 2, the charge and discharge voltage range is C1≥voltage≥C2, 3.2V≥C1≥2.5V, 2.5V≥C2≥2V. Preferably, C1 is 3.2V and C2 is 2.5V.

6. The method for predicting battery cycle failure problem points according to claim 1, characterized in that: Divide the batteries in step 2 into two groups, group X and group Y, and perform charge and discharge tests on each group; Among them, the charge and discharge voltage range of group X is B1≥voltage≥B2, 3.65V≥B1≥3.55V, 3.65V≥B2≥3.2V; The charge and discharge voltage range of group Y is C1≥voltage≥C2, 3.2V≥C1≥2.5V, 2.5V≥C2≥2V.

7. The method for predicting battery cycle failure problem points according to claim 6, characterized in that: B1 is 3.65V, B2 is 3.47V; C1 is 3.2V, C2 is 2.5V.

8. The method for predicting battery cycle failure problem points according to claim 1, characterized in that: The full battery is a lithium iron phosphate full battery.

9. The method for predicting battery cycle failure problem points according to claim 1, characterized in that: In step 2, the target SOH is 60% SOH.

10. The method for predicting battery cycle failure problem points according to claim 1, characterized in that: The method for determining battery cycle failure in step three is to observe and record the status of the positive and negative electrode materials of the battery, whether there is gas production inside the battery, make button batteries for the disassembled electrodes, and perform physical and chemical analysis to further determine the changes that have occurred in the battery during the test.

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