A method for assessing battery storage trends

Abstract

The present invention discloses a method for evaluating battery storage trend, comprising: obtaining stored data: the stored data includes the original voltage V0 of the battery before the test, the Kelvin temperature Tx corresponding to the test temperature, the voltage V at different test times tx under the corresponding Kelvin temperature Tx, and the battery voltage V0 at different test times tx. txTx ; Processing of stored data: determine the time t1 to be estimated, and obtain the voltage V at different Kelvin temperatures Tx at time t1 t1Tx , and calculate the corresponding voltage V t1Tx The rate of change K t1Tx , and obtain the rate of change K t1Tx Logarithm Ln(K t1Tx ), the K t1Tx =(V0-V t1Tx ) / t1; obtain Ln(K t1Tx ) and 1 / Tx; the voltage change rate to be estimated K t1T1 Obtaining: Determine the temperature to be estimated T1, substitute the temperature to be estimated T1 into the linear relationship, and then calculate the voltage change rate K under the temperature to be estimated T1. t1T1 The present invention obtains the variation law between voltage drop and temperature, and then predicts the voltage variation at other temperatures, thereby realizing the estimation of storage performance trend, and the estimation result is accurate.

Description

Technical Field

[0001] The present invention relates to the field of battery performance detection, and in particular to a method for evaluating battery storage trends. Background Art

[0002] Lithium-ion batteries, due to their advantages such as high voltage platform, high energy density, and good cycle performance, are widely used in many fields such as electric vehicles, consumer electronics, and energy storage. Although the performance requirements for lithium-ion batteries vary from field to field, all fields expect lithium-ion batteries to have high energy density and high safety performance. To obtain the safety performance data of lithium-ion batteries, it is essential to test the stability characteristics of lithium-ion batteries.

[0003] Currently, most stability performance tests rely on storage tests at different temperatures. Specifically, battery status is monitored by measuring parameters such as voltage and internal resistance at intervals under varying temperature conditions. Consequently, most current storage tests require separate testing at multiple temperatures. This requires setting up separate experimental groups for different temperatures and time periods, requiring a large number of batteries and wasting significant manpower and resources. Summary of the Invention

[0004] Therefore, the technical problem to be solved by the present invention is to overcome the defect in the prior art that the stability performance test requires the use of a large number of batteries to conduct multiple groups of tests, resulting in a large waste of manpower and material resources, thereby providing a method for evaluating battery storage trends that can predict the voltage drop of batteries under different temperature conditions at the same time using only a small number of batteries.

[0005] A method for assessing battery storage trends, including:

[0006] Acquisition of stored data: Place several identical batteries under at least three test temperatures and obtain the stored data of each battery at different test times tx. The stored data includes the original voltage V0 of the battery before the test, the Kelvin temperature Tx corresponding to the test temperature, and the voltage V under the corresponding Kelvin temperature Tx. txTx ;

[0007] Processing of stored data: Determine the time t1 to be estimated and obtain the voltage V at different Kelvin temperatures Tx at time t1 t1Tx , and calculate the corresponding voltage V t1Tx The rate of change K t1Tx , and obtain the rate of change K t1Tx Logarithm Ln(K t1Tx ), the K t1Tx =(V0-V t1Tx) / t1; get the reciprocal of Kelvin temperature Tx 1 / Tx; with 1 / Tx and Ln(K t1Tx ) are used as horizontal and vertical coordinates to draw a curve graph and obtain a linear relationship;

[0008] Battery change rate K at the estimated temperature T1 t1T1 Obtaining: Determine the estimated temperature T1, substitute the estimated temperature T1 into the linear relationship, and then calculate the battery change rate K under the estimated temperature T1. t1T1 .

[0009] It also includes the rate of change K t1T1 Substitute K t1Tx =(V0-V t1Tx ) / t1 to obtain the voltage V at the estimated temperature T1 t1T1 .

[0010] The SOC of the lithium-ion battery is 100%.

[0011] When the SOC of the lithium-ion battery is 100% and the time to be estimated t1 is 15 days, the obtained linear relationship is LnK=-1978.1(1 / T)+7.8465.

[0012] When the SOC of the lithium-ion battery is 100% and the time to be estimated t1 is 30 days, the obtained linear relationship is LnK=-1920.9(1 / T)+7.0704.

[0013] The SOC of the lithium-ion battery is 50%.

[0014] When the SOC of the lithium-ion battery is 50% and the time to be estimated t1 is 15 days, the obtained linear relationship is LnK=-4150.3(1 / T)+13.402.

[0015] When the SOC of the lithium-ion battery is 50% and the time to be estimated t1 is 30 days, the linear relationship is LnK=-3386.6(1 / T)+10.516.

[0016] There are three groups of battery test temperatures used in the process of acquiring storage data.

[0017] The number of batteries for each test temperature group shall be at least three.

[0018] The technical solution of the present invention has the following advantages:

[0019] 1. The present invention provides a method for evaluating battery storage trends. By acquiring a small amount of temperature and voltage data during the storage process, the variation pattern between voltage drop and temperature as storage progresses can be determined. This pattern can then be used to predict voltage changes at other temperatures, thereby realizing an estimation of storage performance trends.

[0020] 2. The method provided by the present invention can obtain a relationship between voltage drop and temperature by measuring only three temperature points. This relationship can be used to predict voltage changes at other temperatures during the storage period, greatly reducing the number of batteries required for testing. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 is 1 / Tx and Ln(K t1Tx ) as the horizontal and vertical coordinates respectively.

[0023] Figure 2 is 1 / Tx and Ln(K t1Tx ) as the horizontal and vertical coordinates respectively.

[0024] Figure 3 is 1 / Tx and Ln(K t1Tx ) as the horizontal and vertical coordinates respectively.

[0025] Figure 4 is 1 / Tx and Ln(K t1Tx ) as the horizontal and vertical coordinates respectively. DETAILED DESCRIPTION

[0026] The following examples are provided for a better understanding of the present invention and are not intended to limit the best mode of implementation. They do not limit the content and scope of protection of the present invention. Any product identical or similar to the present invention obtained by anyone under the guidance of the present invention or by combining the features of the present invention with other prior arts shall fall within the scope of protection of the present invention.

[0027] If no specific experimental steps or conditions are specified in the examples, the experiments can be carried out according to the conventional experimental steps or conditions described in the literature in the art.

[0028] Example 1

[0029] A method for assessing battery storage trends, including:

[0030] (1) Charge the battery to full charge, i.e., use a lithium-ion battery with 100% SOC for testing, and record the voltage V0 of the battery at full charge. Store the battery in a temperature chamber at 25°C, 45°C, and 60°C for 15 days. Measure the voltage of the battery at each temperature. Record it as V t1T25 、V t1T45 、V t1T60 The test results are shown in Table 1 below.

[0031] Table 1

[0032] 25℃ 45℃ 60℃ 0d 4191 4190 4191 15d 4141 4112 4091

[0033] (2) Obtain the stored data at the time t1 to be estimated. In this embodiment, the time t1 to be estimated is 15 days, that is, obtain the voltage V corresponding to different temperatures at 15 days. t1T25 、V t1T45 、V t1T60 After collecting the data, convert the temperature unit (°C) into Kelvin (K), and perform the reciprocal calculation of the Kelvin to obtain 1 / Tx, specifically 1 / T25, 1 / T45, and 1 / T60. At the same time, the voltage V at different temperatures is calculated. t1T25 、V t1T45 、V t1T60 Processing is performed to obtain the rate of change of voltage over time K t1T25 , K t1T45 , K t1T60 , get K t1T25 =(V0-V t1T25 ) / t1,K t1T45 =(V0-V t1T45 ) / t1,K t1T60 =(V0-V t1T60 ) / t1, and then respectively t1T25 , K t1T45 , K t1T60 Take the logarithm and get Ln(K t1Tx ).

[0034] (3) The Ln(K t1T25 )、Ln(K t1T45 )、Ln(K t1T60 ) and 1 / T25, 1 / T45, 1 / T60, such as Figure 1 As shown, and according to the Figure 1 The curve in the graph gives Ln(K t1Tx) and 1 / Tx, the linear relationship obtained in this embodiment is Ln(K t1Tx )=-1978.1*(1 / Tx)+7.8465.

[0035] (4) According to the above Ln(K t1Tx ) and 1 / Tx, converted to K t1Tx The relationship between the temperature Tx is converted to K t1Tx =e^(-1978.1*(1 / Tx)+7.8465).

[0036] Through the above steps, the voltage drop stored to 15d (i.e., the rate of change K t1Tx ) and the Kelvin temperature Tx. By inputting a specific value of the Kelvin temperature, the pressure drop when stored for 15 days under that temperature condition can be obtained.

[0037] Example 2

[0038] A method for assessing battery storage trends, including:

[0039] (1) Charge the battery to half-charge state, i.e., use a lithium-ion battery with 50% SOC for testing, and record the half-charge voltage V0 of the battery. Store the battery in a temperature chamber at 25°C, 45°C, and 60°C for 15 days. Measure the battery voltage at each temperature. Record it as V t1T25 、V t1T45 、V t1T60 The test results are shown in Table 2 below.

[0040] Table 2

[0041] 25℃ 45℃ 60℃ 0d 3709 3709 3710 15d 3700 3688 3671

[0042] (2) Obtain the stored data at the time t1 to be estimated. In this embodiment, the time t1 to be estimated is 15 days, that is, obtain the voltage V corresponding to different temperatures at 15 days. t1T25 、V t1T45 、V t1T60 After collecting the data, convert the temperature unit (°C) into Kelvin (K), and perform the reciprocal calculation of the Kelvin to obtain 1 / Tx, specifically 1 / T25, 1 / T45, and 1 / T60. At the same time, the voltage V at different temperatures is calculated. t1T25 、V t1T45 、V t1T60 Processing is performed to obtain the rate of change of voltage over time K t1T25 , K t1T45 , K t1T60 , get K t1T25 =(V0-V t1T25 ) / t1,Kt1T45 =(V0-V t1T45 ) / t1,K t1T60 =(V0-V t1T60 ) / t1, and then respectively t1T25 , K t1T45 , K t1T60 Take the logarithm and get Ln(K t1Tx ).

[0043] (3) The Ln(K t1T25 )、Ln(K t1T45 )、Ln(K t1T60 ) and 1 / T25, 1 / T45, 1 / T60, such as Figure 2 As shown, and according to the Figure 2 The curve in the graph gives Ln(K t1Tx ) and 1 / Tx, the linear relationship obtained in this embodiment is Ln(K t1Tx )=-4150.3*(1 / Tx)+13.402.

[0044] (4) According to the above Ln(K t1Tx ) and 1 / Tx, converted to K t1Tx The relationship between the temperature Tx is converted to K t1Tx =e^(-4150.3*(1 / Tx)+13.402).

[0045] Through the above steps, the voltage drop stored to 15d (i.e., the rate of change K t1Tx ) and the Kelvin temperature Tx. By inputting a specific value of the Kelvin temperature, the pressure drop when stored for 15 days under that temperature condition can be obtained.

[0046] Example 3

[0047] A method for assessing battery storage trends, including:

[0048] (1) Charge the battery to full charge, i.e., use a lithium-ion battery with 100% SOC for testing, and record the voltage V0 of the fully charged battery. Store the battery in a temperature chamber at 25°C, 45°C, and 60°C for 30 days. Measure the voltage of the battery at each temperature. Record it as V t1T25 、V t1T45 、V t1T60 The test results are shown in Table 3 below.

[0049] Table 3

[0050] 25℃ 45℃ 60℃ 0d 4190 4190 4191 30d 4134 4105 4081

[0051] (2) Obtain the stored data at the time to be estimated t1. In this embodiment, the time to be estimated t1 = 30d, that is, obtain the voltage V corresponding to different temperatures at 30d. t1T25 、V t1T45 、V t1T60 After collecting the data, convert the temperature unit (°C) into Kelvin (K), and perform the reciprocal calculation of the Kelvin to obtain 1 / Tx, specifically 1 / T25, 1 / T45, and 1 / T60. At the same time, the voltage V at different temperatures is calculated. t1T25 、V t1T45 、V t1T60 Processing is performed to obtain the rate of change of voltage over time K t1T25 , K t1T45 , K t1T60 , get K t1T25 =(V0-V t1T25 ) / t1,K t1T45 =(V0-V t1T45 ) / t1,K t1T60 =(V0-V t1T60 ) / t1, and then respectively t1T25 , K t1T45 , K t1T60 Take the logarithm and get Ln(K t1Tx ).

[0052] (3) The Ln(K t1T25 )、Ln(K t1T45 )、Ln(K t1T60 ) and 1 / T25, 1 / T45, 1 / T60, such as Figure 3 As shown, and according to the Figure 3 The curve in the graph gives Ln(K t1Tx ) and 1 / Tx, the linear relationship obtained in this embodiment is Ln(K t1Tx )=-1920.9*(1 / Tx)+7.0704.

[0053] (4) According to the above Ln(K t1Tx ) and 1 / Tx, converted to K t1Tx The relationship between the temperature Tx is converted to K t1Tx =e^(-1920.9*(1 / Tx)+7.0704).

[0054] Through the above steps, the voltage drop stored to 30d (i.e., the rate of change K t1Tx) and the Kelvin temperature Tx. By inputting a specific value of the Kelvin temperature, the pressure drop when stored at that temperature for 30 days can be obtained.

[0055] Example 4

[0056] A method for assessing battery storage trends, including:

[0057] (1) Charge the battery to half-charge state, i.e., use a lithium-ion battery with 50% SOC for testing, and record the half-charge voltage V0 of the battery. Store the battery in a temperature chamber at 25°C, 45°C, and 60°C for 30 days. Measure the battery voltage at each temperature. Record it as V t1T25 、V t1T45 、V t1T60 The test results are shown in Table 4 below.

[0058] Table 4

[0059] 25℃ 45℃ 60℃ 0d 3710 3710 3710 30d 3697 3684 3667

[0060] (2) Obtain the stored data at the time to be estimated t1. In this embodiment, the time to be estimated t1 = 30d, that is, obtain the voltage V corresponding to different temperatures at 30d. t1T25 、V t1T45 、V t1T60 After collecting the data, convert the temperature unit (°C) into Kelvin (K), and perform the reciprocal calculation of the Kelvin to obtain 1 / Tx, specifically 1 / T25, 1 / T45, and 1 / T60. At the same time, the voltage V at different temperatures is calculated. t1T25 、V t1T45 、V t1T60 Processing is performed to obtain the rate of change of voltage over time K t1T25 , K t1T45 , K t1T60 , get K t1T25 =(V0-V t1T25 ) / t1,K t1T45 =(V0-V t1T45 ) / t1,K t1T60 =(V0-V t1T60 ) / t1, and then respectively t1T25 , K t1T45 , K t1T60 Take the logarithm and get Ln(K t1Tx ).

[0061] (3) The Ln(K t1T25 )、Ln(K t1T45 )、Ln(K t1T60) and 1 / T25, 1 / T45, 1 / T60, such as Figure 4 As shown, and according to the Figure 4 The curve in the graph gives Ln(K t1Tx ) and 1 / Tx, the linear relationship obtained in this embodiment is Ln(K t1Tx )=-3386.6*(1 / Tx)+10.516.

[0062] (4) According to the above Ln(K t1Tx ) and 1 / Tx, converted to K t1Tx The relationship between the temperature Tx is converted to K t1Tx =e^(-3386.6*(1 / Tx)+10.516).

[0063] Through the above steps, the voltage drop stored to 30d (i.e., the rate of change K t1Tx ) and the Kelvin temperature Tx. By inputting a specific value of the Kelvin temperature, the pressure drop when stored at that temperature for 30 days can be obtained.

[0064] Similarly, the present invention can also obtain the voltage change rate K under other storage days. t1Tx The relationship between the voltage and temperature Tx is used to predict the voltage change rate at different storage temperatures for other storage days, thereby evaluating the impact of different temperatures on the battery storage trend at specific storage times. For example, the impact of different temperatures on the battery storage trend at specific storage times such as 60 days and 120 days can be evaluated. The specific implementation methods are not listed one by one in this invention.

[0065] Test example

[0066] This test is used to verify whether the voltage data predicted by the present invention is accurate. The specific test process is as follows: the predicted change rate K is obtained by using the method of each embodiment under the temperature conditions of 20℃, 30℃, 50℃, and 70℃ for 15 days and 30 days. t1Tx and the predicted voltage V t1Tx , as shown in Table 5.

[0067] At the same time, the same type of lithium-ion batteries corresponding to each embodiment are used, and they are placed at the predicted temperatures of 20°C, 30°C, 50°C, and 70°C for the corresponding storage days in the corresponding embodiments, such as 15 days in Examples 1 and 2, and 30 days in Examples 3 and 4. After the storage for the corresponding days, the actual change rate K is measured. Tx and the actual voltage V Tx The test results are shown in Table 5 below.

[0068] Table 5

[0069]

[0070] The data in Table 5 above demonstrates that by acquiring a small amount of temperature and voltage data during the storage process, we can derive the relationship between voltage drop and temperature as storage progresses. This relationship can then be used to predict voltage changes at other temperatures, enabling an estimate of storage performance trends. Comparing the predicted data with the actual data reveals minimal discrepancies, demonstrating the accuracy of the predictions. This further demonstrates that the method provided by the present invention can effectively and accurately assess battery storage trends.

[0071] Obviously, the above embodiments are merely examples for clarity of explanation and are not intended to limit the implementation methods. Those skilled in the art will readily appreciate that other variations or modifications based on the above descriptions are possible. It is not necessary and impossible to enumerate all implementation methods here. Obvious variations or modifications arising therefrom remain within the scope of protection of the present invention.

Claims

1. A method for evaluating battery storage trends, characterized in that: include: Acquisition of stored data: Place several identical batteries under at least three test temperatures and obtain the stored data of each battery at different test times tx. The stored data includes the original voltage V0 of the battery before the test, the Kelvin temperature Tx corresponding to the test temperature, and the voltage V under the corresponding Kelvin temperature Tx. txTx ; Processing of stored data: Determine the time t1 to be estimated and obtain the voltage V at different Kelvin temperatures Tx at time t1 t1Tx , and calculate the corresponding voltage V t1Tx The rate of change K t1Tx , and obtain the rate of change K t1Tx Logarithm Ln (K t1Tx ), the K t1Tx = (V0-V t1Tx ) / t1; Get the reciprocal of Kelvin temperature Tx (1 / Tx); With 1 / Tx and Ln (K t1Tx ) are used as horizontal and vertical coordinates to draw a curve graph and obtain a linear relationship; Battery change rate K at the estimated temperature T1 t1T1 Obtaining: Determine the estimated temperature T1, substitute the estimated temperature T1 into the linear relationship, and then calculate the battery change rate K under the estimated temperature T1. t1T1 ; The rate of change K t1T1 Substitute K t1Tx = (V0-V t1Tx ) / t1 to obtain the voltage V at the estimated temperature T1 t1T1 .

2. The method according to claim 1, characterized in that The battery is a lithium-ion battery, and the SOC of the lithium-ion battery is 100%.

3. The method according to claim 2, characterized in that When the SOC of the lithium-ion battery is 100% and the time to be estimated t1 is 15 days, the obtained linear relationship is LnK=-1978.1(1 / T)+7.8465.

4. The method according to claim 2, characterized in that When the SOC of the lithium-ion battery is 100% and the time to be estimated t1 is 30 days, the obtained linear relationship is LnK=-1920.9(1 / T)+7.0704.

5. The method according to claim 1, wherein The battery is a lithium-ion battery, and the SOC of the lithium-ion battery is 50%.

6. The method according to claim 5, characterized in that When the SOC of the lithium-ion battery is 50% and the time to be estimated t1 is 15 days, the obtained linear relationship is LnK=-4150.3(1 / T)+13.

402.

7. The method according to claim 5, characterized in that When the SOC of the lithium-ion battery is 50% and the time to be estimated t1 is 30 days, the linear relationship obtained is LnK=-3386.6(1 / T)+10.

516.

8. The method according to any one of claims 1 to 7, characterized in that There are three groups of battery test temperatures used in the process of acquiring storage data.

9. The method according to claim 8, characterized in that The number of batteries for each test temperature group shall be at least three.

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