A method for evaluating the cycle performance of lithium iron phosphate batteries

Abstract

The present invention relates to a method for evaluating the cycle performance of a lithium iron phosphate battery, specifically comprising: (1) taking charging data of a standard battery with different cycles, differentiating to obtain a dQ / dV-V curve, integrating the curve to obtain the area of ​​the peak corresponding to the highest voltage value, and then calculating the loss rate of the peak area; (2) using the same method to obtain the loss rate of the area of ​​the peak corresponding to the highest voltage value of a battery to be tested; (3) comparing the loss rates of the peak areas of the standard battery and the battery to be tested, and making a prediction of the cycle performance according to the magnitude relationship of the loss rates. The method for evaluating the cycle performance of a lithium iron phosphate battery of the present invention is simple, easy to operate and implement, and can shorten the evaluation period of the cycle performance of the lithium iron phosphate battery.

Description

Technical Field

[0001] The present invention belongs to the technical field of lithium batteries, and in particular relates to a method for evaluating the cycle performance of a lithium iron phosphate battery. Background Art

[0002] In recent years, lithium-ion batteries with ultra-long cycle life have gradually become the research focus of batteries and are widely used in various fields. 4 As a positive electrode material with ultra-long cycle life, excellent rate cycle performance and good safety, LFP battery has huge market prospects.

[0003] Currently, the cycle life of lithium iron phosphate batteries is generally more than 3,000 times. When evaluating the battery life, the test cycle is too long. According to the 1C cycle test, 3,000 cycle tests take about 1 year. The test time for long-life batteries will be even longer, which greatly prolongs the R&D work cycle.

[0004] Therefore, there is an urgent need for a method to quickly evaluate the cycle life of lithium iron phosphate batteries or a method to predict in advance to reduce the R&D work cycle. Summary of the invention

[0005] The purpose of the present invention is to provide a method for evaluating the cycle performance of a lithium iron phosphate battery, which can shorten the evaluation period of the battery cycle performance and has a simple method and is easy to operate and implement.

[0006] The technical solution adopted by the present invention to solve the above problem is: a method for evaluating the cycle performance of a lithium iron phosphate battery, comprising the following steps:

[0007] (1) Perform cycle test on standard battery B to obtain voltage V and capacity Q data of different cycle times (X times, Y times, Z times, X<Y<Z), perform differential processing on them respectively, and obtain differential dQ / dV-V curves of charge capacity of X times, Y times and Z times, then perform integration processing on the dQ / dV-V curves respectively, and obtain the area of ​​the peak corresponding to the highest voltage value, which are recorded as SB-peak (X times), SB-peak (Y times), SB-peak (Z times), respectively. Taking SB-peak (X times) as the benchmark, obtain the loss rate of SB-peak LB-peak (Y times) and LB-peak (Z times);

[0008] (2) The battery B1 to be tested is subjected to a cycle test to obtain voltage V and capacity Q data of different cycle times (X times, Y times, Z times, X<Y<Z), and the data are differentiated to obtain the differential dQ / dV-V curves of the charge capacity of X times, Y times and Z times, and then the dQ / dV-V curves are integrated to obtain the areas of the peaks corresponding to the highest voltage values, which are recorded as S-B1-peak (X times), S-B1-peak (Y times), and S-B1-peak (Z times), respectively. Taking S-B1-peak (X times) as the benchmark, the loss rates of S-B1-peak L-B1-peak (Y times) and L-B1-peak (Z times) are obtained;

[0009] (3) Compare the loss rate of SB-peak with the loss rate of S-B1-peak. If L-B1-peak (Y times) ≤LB-peak (Y times), and L-B1-peak (Z times) ≤LB-peak (Z times), then the cycle performance of the battery B1 to be tested is predicted to be better than or equal to that of the standard battery B; if L-B1-peak (Y times) >LB-peak (Y times), and L-B1-peak (Z times) >LB-peak (Z times), then the cycle performance of the battery B1 to be tested is predicted to be worse than that of the standard battery B; if L-B1-peak (Y times) ≤LB-peak (Y times), and L-B1-peak (Z times) >LB-peak (Z times), then the cycle performance of the battery B1 to be tested is predicted to be worse than that of the standard battery B; if L-B1-peak (Y times) >LB-peak (Y times), and L-B1-peak (Z times) >LB-peak (Z times) ≤LB-peak (Z times), it is predicted that the cycle performance of the tested battery B1 is better than or equal to that of the standard battery B.

[0010] Preferably, the cycle test is specifically as follows: under normal temperature conditions, the charge and discharge current of the battery is 1C, the charging is constant current and constant voltage charging, the cut-off current is 0.05C, the discharging is constant current discharge, the charge and discharge voltage range is set to 2.5-3.65V, and the battery is left to stand after the charging and discharging are completed, and the standing time is 30min.

[0011] Preferably, 800≤Z≤1200, YX>200, ZY>200.

[0012] Preferably, the charge capacity differential dQ / dV-V curve comprises three peaks, which are named P1, P1, and P3 in order from low to high voltage.

[0013] Preferably, LB-peak (Y times) = [SB-peak (X times) - SB-peak (Y times)] / SB-peak (X times);

[0014] LB-peak (Z times) = [SB-peak (X times) - SB-peak (Z times)] / SB-peak (X times);

[0015] L-B1-peak (Y times) = [ S-B1-peak (X times) - S-B1-peak (Y times) ] / S-B1-peak (X times);

[0016] L-B1-peak (Z times) = [S-B1-peak (X times) - S-B1-peak (Z times)] / S-B1-peak (X times).

[0017] Compared with the prior art, the advantages of the present invention are:

[0018] The invention provides a method for evaluating the cycle performance of a lithium iron phosphate battery, which can shorten the evaluation period of the battery cycle performance, and the method is simple, easy to operate and implement; the method evaluates the cycle performance of the lithium iron phosphate battery by the loss rate of the area of ​​the peak corresponding to the highest voltage value in a dQ / dV-V curve with three peaks, and the change of the peak area of ​​the peak corresponding to the highest voltage value can reflect the consumption speed of active lithium in the battery, thereby judging the cycle performance of the lithium iron phosphate battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is the dQ / dV-V curve of the charging capacity and voltage data of the lithium iron phosphate battery of the present invention. DETAILED DESCRIPTION

[0020] The present invention is further described in detail below with reference to the accompanying drawings.

[0021] like Figure 1 As shown, the dQ / dV-V curve of the capacity data and voltage data of the lithium iron phosphate battery of the present invention.

[0022] The present invention is further described in detail below with reference to the accompanying drawings.

[0023] Example 1

[0024] A method for evaluating the cycle performance of a lithium iron phosphate battery comprises the following steps:

[0025] (1) Standard battery B was cycled (at room temperature, 1C constant current and constant voltage charging to 3.65V, cut-off current 0.05C, standing for 30 minutes after charging, 1C constant current discharge to 2.5V, standing for 30 minutes after discharge), and the voltage V and capacity Q data of different cycle times (250 times, 500 times, 1000 times) were obtained. The data were differentiated to obtain dQ and dV, respectively. The collected voltage V data was used as the X-axis data, and the dQ / dV ratio was used as the Y-axis data. The dQ / dV-V curves of the charge capacity differentials of 250 times, 500 times, and 100 times were obtained, respectively. The dQ / dV-V curve had three obvious peaks. The dQ / dV-V curve was then integrated to obtain the peak corresponding to the highest voltage value (such as Figure 1The areas of P3 in the figure (shaded part) are recorded as SB-peak (250 times), SB-peak (500 times), and SB-peak (1000 times), respectively. Taking SB-peak (250 times) as the benchmark (loss rate is 0%), the loss rates of SB-peak are obtained as LB-peak (500 times) and LB-peak (1000 times), among which, LB-peak (500 times) = [SB-peak (250 times) - SB-peak (500 times)] / SB-peak (250 times); LB-peak (1000 times) = [SB-peak (250 times) - SB-peak (1000 times)] / SB-peak (250 times);

[0026] Among them, the method for drawing the charging dQ / dV-V curve is as follows: a. Preparation: import the charging voltage V and capacity Q data of a certain time into Origin, where the voltage is the X-axis and the capacity is the Y-axis; b. Data processing: then select the two columns of voltage and capacity data and simplify them: open Analysis→Mathematics→Interpolate / Extrapolate, a dialog box will appear, select the number of points in the Number of points item (generally not more than one-fifth of all the data), then OK, and get the simplified data in the last column of the worksheet; then differentiate the simplified data: Analysis→Mathematics→Differentiate, a dialog box will appear, select 1 in the Derivative Order item, then OK, and the dQ / dV-V data will appear in the last column of the worksheet; c. Drawing: use voltage as the horizontal axis and dQ / dV as the vertical axis to get the charging dQ / dV-V curve.

[0027] Among them, the method for integrating the charging dQ / dV-V curve to obtain the peak area is as follows: a. Data interception: take the data corresponding to the peak that needs to be integrated, with the charging voltage as the X-axis and dQ / dV as the Y-axis, and add them to the origin; b. Data supplement: add 2 more columns after the previous 2 columns of data, with the first column set as the X-axis and the second column set as the Y-axis, and add the first and last two data corresponding to the peak; c. Integration processing: first integrate the peak curve: Analysis→Mathematics→Integrate, and get area 1; then integrate the straight line composed of the first and last data of the peak: Analysis→Mathematics→Integrate, and get area 2; the difference between area 1 and area 2 is the peak area.

[0028] (2) The battery B1 to be tested is subjected to a cycle test (at room temperature, 1C constant current and constant voltage charging to 3.65V, cut-off current 0.05C, standing for 30 minutes after charging, 1C constant current discharge to 2.5V, standing for 30 minutes after discharge), and the voltage V and capacity Q data of different cycle times (250 times, 500 times, 1000 times) are obtained. The data are differentiated to obtain dQ and dV, respectively. The collected voltage V data is used as the X-axis data, and the ratio of dQ / dV is used as the Y-axis data. The differential values ​​of the charging capacity of 250 times, 500 times, and 100 times are obtained, respectively. dQ / dV-V curve, the dQ / dV-V curve has three obvious peaks, and then the dQ / dV-V curve is integrated to obtain the area of ​​the peak corresponding to the highest voltage value, which are recorded as S-B1-peak (250 times), S-B1-peak (500 times), and S-B1-peak (1000 times). Taking S-B1-peak (250 times) as the benchmark (loss rate is 0%), the loss rate of S-B1-peak is L-B1-peak (500 times) and L-B1-peak (1000 times), where L-B1-peak (500 times) = [ S-B1-peak (250 times) — S-B1-peak (500 times)] / S-B1-peak (250 times); L-B1-peak (1000 times) = [ S-B1-peak (250 times) — S-B1-peak (1000 times)] / S-B1-peak (250 times);

[0029] (3) Compare the loss rate of the SB-peak with the loss rate of the S-B1-peak. The specific data are shown in Tables 1 and 2 below:

[0030] Table 1:

[0031] Standard battery B cycle number 250 500 1000 SB-Peak 14.31 12.55 9.17 LB-Peak 0% 12.29% 35.92%

[0032] Table 2:

[0033] Cycle number of the battery B1 under test 250 500 1000 S-B1-Peak 13.95 12.43 9.08 L-B1-Peak 0% 10.89% 34.91%

[0034] It can be seen from Table 1 and Table 2 that L-B1-peak (500 times) < LB-peak (500 times), and L-B1-peak (1000 times) < LB-peak (1000 times), so it is predicted that the cycle performance of the test battery B1 is better than that of the standard battery B.

[0035] The predicted results of Example 1 were verified by continuously performing cycle tests on batteries B1 and B until the capacity decayed to 80% of the initial capacity. The specific data are shown in Table 3 below:

[0036] Table 3:

[0037] Cycle times Capacity retention rate Battery to be tested B1 3850 80% Standard battery B 3100 80%

[0038] It can be seen from Table 3 that the actual cycle performance of the tested battery B1 is better than that of the standard battery B, which is consistent with the above predicted result, indicating that the predicted result is correct.

[0039] Example 2

[0040] A method for evaluating the cycle performance of a lithium iron phosphate battery comprises the following steps:

[0041] (1) The standard battery B was subjected to a cycle test (at room temperature, 1C constant current and constant voltage charging to 3.65V, cut-off current 0.05C, standing for 30 minutes after charging, 1C constant current discharge to 2.5V, standing for 30 minutes after discharge), and the voltage V and capacity Q data of different cycle times (250 times, 500 times, and 1000 times) were obtained. The differential processing was performed to obtain dQ and dV, respectively. The collected voltage V data was used as the X-axis data, and the dQ / dV ratio was used as the Y-axis data. The data of 250 times, 500 times, and 1000 times were obtained, respectively. 0 times charge capacity differential dQ / dV-V curve, dQ / dV-V curve has three obvious peaks, and then the dQ / dV-V curve is integrated to obtain the area of ​​the peak corresponding to the highest voltage value, which are recorded as SB-peak (250 times), SB-peak (500 times), and SB-peak (1000 times), respectively. Taking SB-peak (250 times) as the benchmark (loss rate is 0%), the loss rate of SB-peak is obtained as LB-peak (500 times) and LB-peak (1000 times), among which, LB-peak (500 times) = [SB-peak (250 times) - SB-peak (500 times)] / SB-peak (250 times); LB-peak (1000 times) = [SB-peak (250 times) - SB-peak (1000 times)] / SB-peak (250 times);

[0042] (2) The battery B2 to be tested was subjected to a cycle test (at room temperature, 1C constant current and constant voltage charging to 3.65V, cut-off current 0.05C, standing for 30 minutes after charging, 1C constant current discharge to 2.5V, standing for 30 minutes after discharge), and the voltage V and capacity Q data of different cycle times (250 times, 500 times, 1000 times) were obtained. The data were differentiated to obtain dQ and dV, respectively. The collected voltage V data was used as the X-axis data, and the ratio of dQ / dV was used as the Y-axis data. The differential values ​​of the charging capacity of 250 times, 500 times, and 100 times were obtained, respectively. dQ / dV-V curve, the dQ / dV-V curve has three obvious peaks, and then the dQ / dV-V curve is integrated to obtain the area of ​​the peak corresponding to the highest voltage value, which are recorded as S-B2-peak (250 times), S-B2-peak (500 times), and S-B2-peak (1000 times). Taking S-B2-peak (250 times) as the benchmark (loss rate is 0%), the loss rate of S-B2-peak is L-B2-peak (500 times) and L-B2-peak (1000 times), where L-B2-peak (500 times) = [ S-B2-peak (250 times) — S-B2-peak (500 times)] / S-B2-peak (250 times); L-B2-peak (1000 times) = [ S-B2-peak (250 times) — S-B2-peak (1000 times)] / S-B2-peak (250 times);

[0043] (3) Compare the loss rate of the SB-peak with the loss rate of the S-B1-peak. The specific data are shown in Tables 4 and 5 below:

[0044] Table 4:

[0045] Standard battery B cycle number 250 500 1000 SB-Peak 14.31 12.55 9.17 LB-Peak 0% 12.29% 35.92%

[0046] Table 5:

[0047] Cycle number of battery B2 under test 250 500 1000 S-B2-Peak 14.15 12.1 8.80 L-B2-Peak 0% 14.49% 37.81%

[0048] It can be seen from Tables 4 and 5 that L-B2-peak (500 times) > LB-peak (500 times), and L-B2-peak (1000 times) > LB-peak (1000 times), so it is predicted that the cycle performance of the battery B2 to be tested is worse than that of the standard battery B.

[0049] The predicted result of Example 2 was verified, and the batteries B2 and B were continuously cycled (at room temperature, 1C constant current and constant voltage charging to 3.65V, cut-off current 0.05C, standing for 30 minutes after charging, 1C constant current discharging to 2.5V, standing for 30 minutes after discharging), until the capacity decayed to 80% of the initial capacity. The specific data are shown in Table 6 below:

[0050] Table 6:

[0051] Cycle times Capacity retention rate Battery under test B2 2400 80% Standard battery B 3100 80%

[0052] It can be seen from Table 6 that the actual cycle performance of the tested battery B2 is worse than that of the standard battery B, which is consistent with the above predicted result, indicating that the predicted result is correct.

[0053] In addition to the above embodiments, the present invention also includes other implementation modes. Any technical solutions formed by equivalent transformation or equivalent replacement should fall within the protection scope of the claims of the present invention.

Claims

1. A method for evaluating the cycle performance of a lithium iron phosphate battery, characterized in that: The following steps are involved: (1) Perform cycle test on standard battery B to obtain voltage V and capacity Q data of different cycle numbers, where the cycle numbers are X, Y, and Z, respectively, and X<Y<Z. Differentiation processing is performed on them to obtain differential dQ / dV-V curves of charge capacity of X, Y, and Z times, respectively. Then, integration processing is performed on the dQ / dV-V curves to obtain the areas of the peaks corresponding to the highest voltage values, which are recorded as SB-peak (X times), SB-peak (Y times), and SB-peak (Z times), respectively. Taking SB-peak (X times) as the benchmark, the loss rates of SB-peak LB-peak (Y times) and LB-peak (Z times) are obtained. (2) The battery B1 to be tested is subjected to a cycle test to obtain voltage V and capacity Q data at different cycle times, where the cycle times are X times, Y times, and Z times, respectively, and X<Y<Z. Differentiation processing is performed on the different battery B1 to obtain differential dQ / dV-V curves of the charge capacity at X times, Y times, and Z times, respectively. The dQ / dV-V curves are then integrated to obtain the areas of the peaks corresponding to the highest voltage values, which are recorded as S-B1-peak (X times), S-B1-peak (Y times), and S-B1-peak (Z times), respectively. Taking S-B1-peak (X times) as the benchmark, the loss rates of S-B1-peak are obtained as L-B1-peak (Y times) and L-B1-peak (Z times); (3) Compare the loss rate of SB-peak with the loss rate of S-B1-peak. If L-B1-peak (Y times) ≤LB-peak (Y times), and L-B1-peak (Z times) ≤LB-peak (Z times), then the cycle performance of the battery B1 to be tested is predicted to be better than or equal to that of the standard battery B; if L-B1-peak (Y times) >LB-peak (Y times), and L-B1-peak (Z times) >LB-peak (Z times), then the cycle performance of the battery B1 to be tested is predicted to be worse than that of the standard battery B; if L-B1-peak (Y times) ≤LB-peak (Y times), and L-B1-peak (Z times) >LB-peak (Z times), then the cycle performance of the battery B1 to be tested is predicted to be worse than that of the standard battery B; if L-B1-peak (Y times) >LB-peak (Y times), and L-B1-peak (Z times) >LB-peak (Z times) ≤LB-peak (Z times), it is predicted that the cycle performance of the tested battery B1 is better than or equal to that of the standard battery B; LB-peak (Y times) = [SB-peak (X times) - SB-peak (Y times)] / SB-peak (X times); LB-peak (Z times) = [SB-peak (X times) - SB-peak (Z times)] / SB-peak (X times); L-B1-peak (Y times) = [ S-B1-peak (X times) - S-B1-peak (Y times) ] / S-B1-peak (X times); L-B1-peak (Z times) = [S-B1-peak (X times) - S-B1-peak (Z times)] / S-B1-peak (X times).

2. The method for evaluating the cycle performance of a lithium iron phosphate battery according to claim 1, characterized in that: The cycle test is specifically as follows: under normal temperature conditions, the charge and discharge current of the battery is 1C, the charging is constant current and constant voltage charging, the cut-off current is 0.05C, the discharging is constant current discharge, the charge and discharge voltage range is set to 2.5-3.65V, and the battery is left to stand after the charging and discharging are completed, and the standing time is 30 minutes.

3. The method for evaluating the cycle performance of a lithium iron phosphate battery according to claim 1, characterized in that: The said 800≤Z≤1200, YX>200, ZY>200.

4. The method for evaluating the cycle performance of a lithium iron phosphate battery according to claim 1, characterized in that: The charge capacity differential dQ / dV-V curve includes three obvious peaks, which are named P1, P1, and P3 in order from low to high voltage.

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