CN114545264A

CN114545264A - Method for evaluating storage trend of battery

Info

Publication number: CN114545264A
Application number: CN202210189263.6A
Authority: CN
Inventors: 刘静; 杨红新; 其他发明人请求不公开姓名
Original assignee: Svolt Energy Technology Co Ltd
Current assignee: Svolt Energy Technology Co Ltd
Priority date: 2022-02-28
Filing date: 2022-02-28
Publication date: 2022-05-27

Abstract

The invention discloses a method for evaluating a battery storage trend, which comprises the following steps: and (3) acquiring the stored data: the stored data comprises original voltage V0 of the battery before test, Kelvin temperature Tx corresponding to the test temperature, and voltage V of different test time Tx at the corresponding Kelvin temperature Tx_txTx(ii) a And (3) processing of stored data: determining the time t1 to be predicted, and acquiring the voltage V of different Kelvin temperatures Tx at the time t1_t1TxWhile calculating the corresponding voltage V_t1TxRate of change K of_t1TxAnd obtaining the rate of change K_t1TxLogarithm of Ln (K)_t1Tx) K is the same as_t1Tx＝(V0‑V_t1Tx) T 1; obtaining Ln (K)_t1Tx) And a linear relation of 1/Tx; to-be-estimated voltage change rate K_t1T1Obtaining: determining the temperature T1 to be estimated, substituting the temperature T1 into the linear relation, and calculating the voltage change rate K at the temperature T1 to be estimated_t1T1. The invention obtains the pressure drop and the temperatureAnd the voltage changes at other temperatures are predicted according to the change rule between the degrees, so that the storage performance trend is predicted, and the prediction result is accurate.

Description

Method for evaluating storage trend of battery

Technical Field

The invention relates to the field of battery performance detection, in particular to a method for evaluating a battery storage trend.

Background

Lithium ion batteries are widely used in electric vehicles, consumer electronics, energy storage and other fields due to their advantages of high voltage platform, high energy density, good cycle performance and the like. Although the performance requirements of each field for the lithium ion battery are different, the lithium ion battery in each field is expected to have high energy density and high safety performance, and the detection of the stability characteristics of the lithium ion battery is indispensable to acquire the safety performance data of the lithium ion battery.

At present, most performance tests for stability basically adopt a storage test mode at different temperatures. Specifically, under different temperature conditions, the battery state is detected by testing parameters such as voltage, internal resistance and the like at intervals. Therefore, most of storage tests at present need to be respectively tested at a plurality of temperatures, so that different experimental groups need to be respectively set for different temperatures and different times, a large number of batteries are needed, and a large number of manpower and material resources are wasted.

Disclosure of Invention

Therefore, the technical problem to be solved by the invention is to overcome the defect that in the prior art, a large number of batteries are needed to be used for performing a plurality of groups of tests in the performance test of stability, so that a large amount of manpower and material resources are wasted, and thus, the method for evaluating the storage trend of the batteries can predict the voltage drop condition of the batteries at different temperatures at the same time by using fewer batteries.

A method of evaluating battery storage trends, comprising:

and (3) acquiring the stored data: placing a plurality of identical batteries at least three groups of test temperatures, and acquiring storage data of each battery at different test times Tx, wherein the storage data comprises original voltage V0 of the battery before test, Kelvin temperature Tx corresponding to the test temperature, and voltage V at corresponding Kelvin temperature Tx_txTx；

And (3) processing of stored data: determining the time t1 to be estimated, and acquiring the voltage V of different Kelvin Tx temperatures Tx at the time t1_t1TxWhile calculating the corresponding voltage V_t1TxRate of change K of_t1TxAnd obtaining the rate of change K_t1TxLogarithm of Ln (K)_t1Tx) K is the same as_t1Tx＝(V0-V_t1Tx) T 1; acquiring the reciprocal 1/Tx of the Kelvin Tx; at 1/Tx and Ln (K)_t1Tx) Respectively drawing a curve graph as a horizontal coordinate and a vertical coordinate to obtain a linear relational expression;

rate of change K of battery at temperature T1 to be estimated_t1T1Obtaining: determining the temperature T1 to be estimated, substituting the temperature T1 into the linear relation, and calculating the change rate K of the battery at the temperature T1 to be estimated_t1T1。

Further comprising the step of converting the rate of change K_t1T1Substitution into K_t1Tx＝(V0-V_t1Tx) Acquiring voltage V at temperature T1 to be estimated from/T1_t1T1。

The SOC of the lithium ion battery is 100%.

When the SOC of the lithium ion battery is 100% and the time T1 to be estimated is 15d, the linear relation obtained is LnK ═ 1978.1(1/T) + 7.8465.

When the SOC of the lithium ion battery is 100% and the time T1 to be estimated is 30d, the linear relation obtained is LnK ═ 1920.9(1/T) + 7.0704.

The SOC of the lithium ion battery is 50%.

When the SOC of the lithium ion battery is 50% and the time T1 to be estimated is 15d, the linear relation obtained is LnK ═ 4150.3(1/T) + 13.402.

When the SOC of the lithium ion battery is 50% and the time T1 to be estimated is 30d, a linear relation LnK ═ 3386.6(1/T) +10.516 is obtained.

The test temperatures of the batteries used in the acquisition of the stored data were three sets.

The number of cells per set of test temperatures is at least three.

The technical scheme of the invention has the following advantages:

1. according to the method for evaluating the storage trend of the battery, provided by the invention, the change rule between the voltage drop and the temperature along with the storage can be obtained by acquiring a small amount of temperature and voltage data in the storage process, so that the voltage change at other temperatures can be predicted by using the rule, and the estimation of the storage performance trend is realized.

2. The method provided by the invention can obtain the relation between the voltage drop and the temperature by only measuring 3 temperature points, and can predict the voltage changes of other temperatures in the storage time period through the relation, so that the number of batteries required by detection is greatly reduced.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.

FIG. 1 shows 1/Tx and Ln (K) in example 1 of the present invention_t1Tx) Graphs plotted as abscissa and ordinate, respectively.

FIG. 2 shows 1/Tx and Ln (K) in example 2 of the present invention_t1Tx) Graphs plotted as abscissa and ordinate, respectively.

FIG. 3 shows 1/Tx and Ln (K) in example 3 of the present invention_t1Tx) Graphs plotted as abscissa and ordinate, respectively.

FIG. 4 shows 1/Tx and Ln (K) in example 4 of the present invention_t1Tx) Graphs plotted as abscissa and ordinate, respectively.

Detailed Description

The following examples are provided to further understand the present invention, not to limit the scope of the present invention, but to provide the best mode, not to limit the content and the protection scope of the present invention, and any product similar or similar to the present invention, which is obtained by combining the present invention with other prior art features, falls within the protection scope of the present invention.

The examples do not show the specific experimental steps or conditions, and can be performed according to the conventional experimental steps described in the literature in the field.

Example 1

A method of evaluating battery storage trends, comprising:

(1) the battery is charged to full charge, i.e. the lithium ion battery with 100% SOC is used for detection, and the voltage V0 of the full charge state of the battery is recorded. The battery storage is stored in an incubator at 25 ℃, 45 ℃ and 60 ℃ for 15d respectively. The voltage of the cell at each temperature was measured. Are respectively marked as V_t1T25、V_t1T45、V_t1T60The results are shown in Table 1 below.

TABLE 1

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

(2) Obtaining the stored data at the time t1 to be estimated, where the time t1 to be estimated is 15d in this embodiment, that is, obtaining the voltages V corresponding to different temperatures at 15d_t1T25、V_t1T45、V_t1T60. After data collection, the temperature in units (. degree.C.) is converted to temperature in degrees Kelvin (K) and the temperature in degrees Kelvin is inverted to obtain 1 ^ 4Tx, specifically 1/T25, 1/T45, and 1/T60. At the same time, the voltage V at different temperatures is measured_t1T25、V_t1T45、V_t1T60Processing to obtain the change rate K of the voltage along with the time_t1T25、K_t1T45、K_t1T60To obtain K_t1T25＝(V0-V_t1T25)/t1，K_t1T45＝(V0-V_t1T45)/t1，K_t1T60＝(V0-V_t1T60) T1, and then respectively for the rate of change K_t1T25、K_t1T45、K_t1T60The logarithm processing is carried out to obtain Ln (K)_t1Tx)。

(3) Ln (K) in the storage data with the storage days of 15d acquired in the step (2)_t1T25)、Ln(K_t1T45)、Ln(K_t1T60) And 1/T25, 1/T45, 1/T60, as shown in FIG. 1, and Ln (K) is obtained from the graph in FIG. 1_t1Tx) And 1/Tx, the linear relationship obtained in this example is Ln (K)_t1Tx)＝-1978.1*(1/Tx)+7.8465。

(4) According to Ln (K) above_t1Tx) And 1/Tx, converted to K_t1TxA relation with temperature Tx, and a converted relation is K_t1Tx＝e^(-1978.1*(1/Tx)+7.8465)。

The voltage drop (i.e. the change rate K) stored in 15d is obtained through the steps_t1Tx) And the relation with the Kelvin Tx, and the pressure drop condition of 15d stored under the temperature condition can be obtained by inputting the specific value of the Kelvin.

Example 2

A method of evaluating battery storage trends, comprising:

(1) the battery is charged to a half-charge state, namely, a lithium ion battery with 50% SOC is adopted for detection, and the voltage V0 of the half-charge state of the battery is recorded. The battery storage is stored in an incubator at 25 ℃, 45 ℃ and 60 ℃ for 15d respectively. The voltage of the cell at each temperature was measured. Are respectively marked as V_t1T25、V_t1T45、V_t1T60The results are shown in Table 2 below.

TABLE 2

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

(2) Obtaining the stored data at the time t1 to be estimated, where the time t1 to be estimated is 15d in this embodiment, that is, obtaining the voltages V corresponding to different temperatures at 15d_t1T25、V_t1T45、V_t1T60. After data collection, the temperature units (. degree. C.) were converted to the temperature in degrees Kelvin (K) and the temperature in degrees Kelvin was inverted to obtain 1/Tx, specifically 1/T25, 1/T45, 1/T60. At the same time, the voltage V at different temperatures is measured_t1T25、V_t1T45、V_t1T60Processing to obtain the change rate K of the voltage along with the time_t1T25、K_t1T45、K_t1T60To obtain K_t1T25＝(V0-V_t1T25)/t1，K_t1T45＝(V0-V_t1T45)/t1，K_t1T60＝(V0-V_t1T60) T1, and then respectively for the rate of change K_t1T25、K_t1T45、K_t1T60The logarithm processing is carried out to obtain Ln (K)_t1Tx)。

(3) Ln (K) in the storage data with the storage days of 15d acquired in the step (2)_t1T25)、Ln(K_t1T45)、Ln(K_t1T60) And 1/T25, 1/T45, 1/T60, as shown in FIG. 2, and Ln (K) is obtained from the graph in FIG. 2_t1Tx) And 1/Tx, the linear relationship obtained in this example is Ln (K)_t1Tx)＝-4150.3*(1/Tx)+13.402。

(4) According to Ln (K) above_t1Tx) And 1/Tx, converted to K_t1TxA relation with temperature Tx, and a converted relation is K_t1Tx＝e^(-4150.3*(1/Tx)+13.402)。

Example 3

A method of evaluating battery storage trends, comprising:

(1) the battery is charged to a full state, namely, the lithium ion battery with 100% SOC is used for detection, and the voltage V0 of the full state of the battery is recorded. The battery storage is stored in an incubator at 25 ℃, 45 ℃ and 60 ℃ for 30d respectively. The voltage of the cell at each temperature was measured. Are respectively marked as V_t1T25、V_t1T45、V_t1T60The results are shown in Table 3 below.

TABLE 3

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

(2) Obtaining the stored data at the time t1 to be estimated, where the time t1 to be estimated is 30d in this embodiment, that is, obtaining the voltages V corresponding to different temperatures at 30d_t1T25、V_t1T45、V_t1T60. After data collection, the temperature units (. degree. C.) were converted to the temperature in degrees Kelvin (K) and the temperature in degrees Kelvin was inverted to obtain 1/Tx, specifically 1/T25, 1/T45, 1/T60. At the same time, the voltage V at different temperatures is measured_t1T25、V_t1T45、V_t1T60Processing to obtain the change rate K of the voltage along with the time_t1T25、K_t1T45、K_t1T60To obtain K_t1T25＝(V0-V_t1T25)/t1，K_t1T45＝(V0-V_t1T45)/t1，K_t1T60＝(V0-V_t1T60) T1, and then respectively for the rate of change K_t1T25、K_t1T45、K_t1T60The logarithm processing is carried out to obtain Ln (K)_t1Tx)。

(3) Ln (K) in the storage data with the storage days of 30d acquired in the step (2)_t1T25)、Ln(K_t1T45)、Ln(K_t1T60) And 1/T25, 1/T45, 1/T60, as shown in FIG. 3, and Ln (K) is obtained from the graph in FIG. 3_t1Tx) And 1/Tx, the linear relationship obtained in this example is Ln (K)_t1Tx)＝-1920.9*(1/Tx)+7.0704。

(4) According to Ln (K) above_t1Tx) And 1/Tx, scalingTo K_t1TxA relation with temperature Tx, and a converted relation is K_t1Tx＝e^(-1920.9*(1/Tx)+7.0704)。

The voltage drop (i.e. the change rate K) stored to 30d is obtained by the steps_t1Tx) And the relation with the Kelvin Tx, and the pressure drop condition of 30d stored under the temperature condition can be obtained by inputting the specific value of the Kelvin.

Example 4

A method of evaluating battery storage trends, comprising:

(1) the battery is charged to a half-charge state, namely, a lithium ion battery with 50% SOC is adopted for detection, and the voltage V0 of the half-charge state of the battery is recorded. The battery storage is stored in an incubator at 25 ℃, 45 ℃ and 60 ℃ for 30d respectively. The voltage of the cell at each temperature was measured. Are respectively marked as V_t1T25、V_t1T45、V_t1T60The results are shown in Table 4 below.

TABLE 4

	25℃	45℃	60℃
				0d	3710	3710	3710
30d	3697	3684	3667

(3) Ln (K) in the storage data with the storage days of 30d acquired in the step (2)_t1T25)、Ln(K_t1T45)、Ln(K_t1T60) And 1/T25, 1/T45, 1/T60, as shown in FIG. 4, and Ln (K) is obtained from the graph in FIG. 4_t1Tx) And 1/Tx, the linear relationship obtained in this example is Ln (K)_t1Tx)＝-3386.6*(1/Tx)+10.516。

(4) According to Ln (K) above_t1Tx) And 1/Tx, converted to K_t1TxA relation with temperature Tx, and a converted relation is K_t1Tx＝e^(-3386.6*(1/Tx)+10.516)。

The voltage drop (i.e. the change rate K) stored to 30d is obtained through the steps_t1Tx) And the relation with the Kelvin Tx, and the pressure drop condition of 30d stored under the temperature condition can be obtained by inputting the specific value of the Kelvin.

Similarly, the voltage change rate K under other storage days can be obtained_t1TxRelation with temperature TxAnd further, the voltage change rate conditions during storage at different temperatures are predicted under other storage days, and the influence of different temperatures on the storage trend of the battery under specific storage time is evaluated. For example: under the specific storage time of 60d, 120d and the like, the evaluation of the influence of different temperatures on the storage trend of the battery is realized, and the specific implementation manner is not illustrated in the invention.

Test examples

The test is used for verifying whether the predicted voltage data is accurate or not, and the specific test process is as follows: the predicted change rates K at 15d and 30d at 20 deg.C, 30 deg.C, 50 deg.C, and 70 deg.C were obtained by the methods of the examples_t1TxAnd a predicted voltage V_t1TxAs shown in table 5.

Meanwhile, lithium ion batteries of the same kind corresponding to the respective examples were used and stored at the predicted temperatures of 20 ℃, 30 ℃, 50 ℃, and 70 ℃ for the storage days corresponding to the respective examples, such as 15d in examples 1 and 2, and 30d in examples 3 and 4, respectively, and the actual change rate K was performed after the storage for the respective days_TxAnd the actual voltage V_TxThe results of the measurements are shown in Table 5 below.

TABLE 5

As can be seen from the data in table 5, by obtaining a small amount of data of the temperature and the voltage in the storage process, the change rule between the voltage drop and the temperature along with the storage can be obtained, and the voltage change at other temperatures can be predicted by using the rule, so that the storage performance trend can be estimated. And the comparison of the predicted data and the actual data shows that the data difference is small, the predicted result is accurate, and the method provided by the invention can effectively evaluate the storage trend of the battery and has accurate evaluation result.

It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.

Claims

1. A method of evaluating battery storage trends, comprising:

2. The method of claim 1, further comprising assigning a rate of change K_t1T1Substitution into K_t1Tx＝(V0-V_t1Tx) Acquiring voltage V at temperature T1 to be estimated from/T1_t1T1。

3. The method of claim 1 or 2, wherein the lithium ion battery has a SOC of 100%.

4. The method of claim 3, wherein the linear relation LnK ═ 1978.1(1/T) +7.8465 is obtained when the SOC of the lithium ion battery is 100% and the time T1 to be estimated is 15 d.

5. The method of claim 3, wherein the linear relation LnK ═ 1920.9(1/T) +7.0704 is obtained when the SOC of the lithium ion battery is 100% and the time T1 to be estimated is 30 d.

6. The method of claim 1 or 2, wherein the lithium ion battery has a SOC of 50%.

7. The method of claim 6, wherein the linear relation LnK ═ 4150.3(1/T) +13.402 is obtained when the SOC of the lithium ion battery is 50% and the time T1 to be estimated is 15 d.

8. The method of claim 6, wherein the linear relation LnK ═ 3386.6(1/T) +10.516 is obtained when the SOC of the lithium ion battery is 50% and the time T1 to be estimated is 30 d.

9. The method of any one of claims 1 to 8, wherein the test temperatures of the batteries used in the acquisition of the stored data are in three groups.

10. The method of claim 9, wherein the number of cells per set of test temperatures is at least three.