CN113805089A - Floating charge life estimation method and system for power lithium battery - Google Patents
Floating charge life estimation method and system for power lithium battery Download PDFInfo
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- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
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- G—PHYSICS
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Abstract
The invention discloses a floating charge life estimation method and system for a power lithium battery, belonging to the technical field of energy storage power batteries, and comprising the steps of obtaining floating charge information of a lithium battery to be detected, wherein the floating charge information comprises the temperature, the multiplying power, the storage days and the cycle number of the lithium battery to be detected in the floating charge process of the battery; and processing the floating charge information by adopting a pre-constructed battery floating charge life degradation estimation model, and predicting the floating charge life of the lithium battery to be tested. The method is combined with the power battery floating charge use scene of actual energy storage, and the floating charge service life of the power lithium battery in the actual scene is estimated by using the battery floating charge service life degradation estimation model, so that technical support and theoretical basis are provided for timely early warning when the battery reaches the end of service life.
Description
Technical Field
The invention relates to the technical field of energy storage power batteries, in particular to a method and a system for estimating the floating charge life of a power lithium battery.
Background
In the field of energy storage, a lead-acid battery is generally adopted in a traditional storage battery, and the lead-acid battery has the defects of large maintenance workload, short service life, large temperature influence on capacity and the like. The lithium battery has excellent rate discharge characteristic, higher energy density and stronger temperature adaptability, and is a good substitute of the lead-acid battery.
At present, a storage battery of a storage power station adopts floating charge management, and no good solution is provided at present for evaluating the floating charge life of the battery in real time according to the state of the service life of the power battery in an actual scene and whether safety risks exist.
Disclosure of Invention
The invention aims to provide a floating charge life estimation method and system for a power lithium battery, and aims to realize estimation of the floating charge life of the power lithium battery in an actual scene.
In order to achieve the above purpose, the invention provides a floating charge life estimation method for a power lithium battery, which comprises the following steps:
the method comprises the steps of obtaining floating charge information of a lithium battery to be tested, wherein the floating charge information comprises the temperature, the multiplying power, the storage days and the cycle number of the lithium battery to be tested in the floating charge process of the battery;
and processing the floating charge information by adopting a pre-constructed battery floating charge life degradation estimation model, and predicting the floating charge life of the lithium battery to be tested.
Further, the battery float charge life degradation estimation model is as follows:
Qloss＝a1*tz+a2*N
wherein Q islossFor the floating charge life capacity decay rate, a1 is a storage capacity decay coefficient, a2 is a cycle capacity decay coefficient, t is the storage days in the floating charge process of the lithium ion battery, N is the monthly cycle number in the floating charge process of the lithium ion battery, z is a constant coefficient, and x is a multiplication sign.
Further, the storage capacity fade coefficient a1 is a function of the storage temperature T1 and the SOC, and is expressed as follows: a1 ═ f (T1, SOC);
the cycle capacity attenuation coefficient a2 is a function of the cycle temperature T2, the depth of discharge DOD% and the charge-discharge multiplying power C, and the formula is as follows: a2 ═ f (T2, DOD%, C).
Further, the construction process of the battery float charge life degradation estimation model comprises the following steps:
under different cycle temperatures and charge-discharge multiplying powers, carrying out accelerated cycle life test on n1 test lithium batteries to obtain capacity retention rates corresponding to different cycle numbers;
storing n2 test lithium batteries with the charge states of 100% at different storage temperatures to obtain capacity retention rates corresponding to different storage days;
and constructing a battery floating charge life degradation estimation model according to the capacity retention rates corresponding to different cycle numbers and the capacity retention rates corresponding to different storage days.
Further, the circulation temperature and the storage temperature comprise 25 ℃, 35 ℃, 45 ℃ and 55 ℃; the charge and discharge multiplying power comprises 0.2C,0.5C and 1C.
In addition, to achieve the above object, the present invention further provides a floating charge life estimation system for a lithium power battery, including:
the device comprises a floating charge information acquisition module, a battery floating charge module and a battery management module, wherein the floating charge information acquisition module is used for acquiring floating charge information of a lithium battery to be tested, and the floating charge information comprises the temperature, the multiplying power, the storage days and the cycle number of the lithium battery to be tested in the floating charge process of the battery;
and the service life estimation module is used for processing the floating charge information by adopting a pre-constructed battery floating charge service life degradation estimation model and predicting the floating charge service life of the lithium battery to be tested.
Further, the battery float charge life degradation estimation model is as follows:
Qloss＝a1*tz+a2*N
wherein Q islossFor the floating charge life capacity decay rate, a1 is a storage capacity decay coefficient, a2 is a cycle capacity decay coefficient, t is the storage days in the floating charge process of the lithium ion battery, N is the monthly cycle number in the floating charge process of the lithium ion battery, z is a constant coefficient, and x is a multiplication sign.
Further, the storage capacity fade coefficient a1 is a function of the storage temperature T1 and the SOC, and is expressed as follows: a1 ═ f (T1, SOC);
the cycle capacity attenuation coefficient a2 is a function of the cycle temperature T2, the depth of discharge DOD% and the charge-discharge multiplying power C, and the formula is as follows: a2 ═ f (T2, DOD%, C).
Further, the system also comprises a model building module, including;
the first capacity retention rate obtaining unit is used for carrying out accelerated cycle life test on n1 test lithium batteries under different cycle temperatures and charge-discharge multiplying factors to obtain capacity retention rates corresponding to different cycle numbers;
the second capacity retention rate acquisition unit is used for storing n2 test lithium batteries with the charge states of 100% at different storage temperatures to obtain capacity retention rates corresponding to different storage days;
and the model building unit is used for building the battery floating charge life degradation estimation model according to the capacity retention rates corresponding to different cycle numbers and the capacity retention rates corresponding to different storage days.
Further, the circulation temperature and the storage temperature comprise 25 ℃, 35 ℃, 45 ℃ and 55 ℃; the charge and discharge multiplying power comprises 0.2C,0.5C and 1C.
Compared with the prior art, the invention has the following technical effects: the method estimates the floating charge life of the power lithium battery in the actual scene by using the battery floating charge life degradation estimation model, provides technical support and theoretical basis for timely early warning when the battery reaches the end of life, is favorable for improving the floating charge safety performance of the lithium iron phosphate battery, has universality and practicability, and is suitable for wide popularization and use.
Drawings
The following detailed description of embodiments of the invention refers to the accompanying drawings in which:
FIG. 1 is a flow chart of a method for estimating the floating charge life of a lithium power battery according to the present invention;
FIG. 2 is a block diagram of a floating charge life estimation system for a lithium battery according to the present invention;
fig. 3 is a schematic diagram of an estimation result in a specific actual scene of the floating charge life estimation method for a power lithium battery according to an embodiment of the present invention.
Detailed Description
To further illustrate the features of the present invention, refer to the following detailed description of the invention and the accompanying drawings. The drawings are for reference and illustration purposes only and are not intended to limit the scope of the present disclosure.
As shown in fig. 1, the present embodiment discloses a method for estimating a floating charge life of a power lithium battery, including steps S10 to S20:
s10: the method comprises the steps of obtaining floating charge information of a lithium battery to be tested, wherein the floating charge information comprises the temperature, the multiplying power, the storage days and the cycle number of the lithium battery to be tested in the floating charge process of the battery;
s20: and processing the floating charge information by adopting a pre-constructed battery floating charge life degradation estimation model, and predicting the floating charge life of the lithium battery to be tested.
As a further preferred technical solution, the battery float charge life degradation estimation model is:
Qloss＝a1*tz+a2*N
wherein Q islossFor the floating charge life capacity decay rate, a1 is a storage capacity decay coefficient, a2 is a cycle capacity decay coefficient, t is the storage days in the floating charge process of the lithium ion battery, N is the monthly cycle number in the floating charge process of the lithium ion battery, z is a constant coefficient, and x is a multiplication sign.
As a further preferred solution, the storage capacity fading coefficient a1 is a function of the storage temperature T1 and the SOC, and the expression formula is as follows: a1 ═ f (T1, SOC);
the cycle capacity attenuation coefficient a2 is a function of the cycle temperature T2, the depth of discharge DOD% and the charge-discharge multiplying power C, and the formula is as follows: a2 ═ f (T2, DOD%, C).
As a further preferable technical solution, the process of constructing the battery float charge life degradation estimation model includes the steps of:
s1: under different cycle temperatures and charge-discharge multiplying powers, carrying out accelerated cycle life test on n1 test lithium batteries to obtain capacity retention rates corresponding to different cycle numbers;
in addition, in this embodiment, accelerated life tests are performed on at least three lithium batteries under different temperatures and multiplying powers, so as to obtain data of capacity retention rates corresponding to different cycle numbers of the lithium batteries.
S2: storing n2 test lithium batteries with the charge states of 100% at different storage temperatures to obtain capacity retention rates corresponding to different storage days;
it should be noted that in this embodiment, at least five test lithium batteries are stored at different temperatures (SOC 100%), so as to obtain the capacity retention rate data corresponding to different storage days.
S3: and constructing a battery floating charge life degradation estimation model according to the capacity retention rates corresponding to different cycle numbers and the capacity retention rates corresponding to different storage days.
In practical applications, the parameters of the model also need to be corrected according to the measured data.
As a further preferred technical solution, the circulation temperature and the storage temperature include, but are not limited to, 25 ℃, 35 ℃, 45 ℃, 55 ℃; the charge and discharge rate includes, but is not limited to, 0.2C,0.5C, 1C; the SOC is 100%.
It should be noted that, in practical application, the power battery floating charge service scenario of the actual energy storage may be decomposed to obtain the temperature and the rate in the actual scenario, and the number of days and the number of cycles in the storage process, and the temperature and the rate are substituted into the floating charge life estimation model to predict the service life of the energy storage battery in the actual scenario, and the estimation result in the actual scenario of the power lithium battery floating charge life estimation method in the embodiment may refer to fig. 2.
As shown in fig. 2, the present embodiment discloses a floating charge life estimation system for a lithium power battery, which includes:
the system comprises a floating charge information acquisition module 10, a battery floating charge information acquisition module and a battery management module, wherein the floating charge information acquisition module is used for acquiring floating charge information of a lithium battery to be tested, and the floating charge information comprises the temperature, the multiplying power, the storage days and the cycle number of the lithium battery to be tested in the floating charge process of the battery;
and the life estimation module 20 is configured to process the floating charge information by using a pre-established battery floating charge life degradation estimation model, and predict the floating charge life of the lithium battery to be tested.
As a further preferred technical solution, the battery float charge life degradation estimation model is:
Qloss＝a1*tz+a2*N
wherein Q islossFor the floating charge life capacity decay rate, a1 is a storage capacity decay coefficient, a2 is a cycle capacity decay coefficient, t is the storage days in the floating charge process of the lithium ion battery, N is the monthly cycle number in the floating charge process of the lithium ion battery, z is a constant coefficient, and is determined by design (such as an anode and a cathode), and x is a multiplication number.
As a further preferred solution, the storage capacity fading coefficient a1 is a function of the storage temperature T1 and the SOC, and the expression formula is as follows: a1 ═ f (T1, SOC);
the cycle capacity attenuation coefficient a2 is a function of the cycle temperature T2, the depth of discharge DOD% and the charge-discharge multiplying power C, and the formula is as follows: a2 ═ f (T2, DOD%, C).
As a further preferred technical solution, the method further comprises a model construction module, including;
the first capacity retention rate obtaining unit is used for carrying out accelerated cycle life test on n1 test lithium batteries under different cycle temperatures and charge-discharge multiplying factors to obtain capacity retention rates corresponding to different cycle numbers;
the second capacity retention rate acquisition unit is used for storing n2 test lithium batteries with the charge states of 100% at different storage temperatures to obtain capacity retention rates corresponding to different storage days;
and the model building unit is used for building the battery floating charge life degradation estimation model according to the capacity retention rates corresponding to different cycle numbers and the capacity retention rates corresponding to different storage days.
It should be noted that, the process of constructing the battery float charge life degradation estimation model is to establish an equation set according to certain measured data in the actual usage scene of the battery, solve the equation and calculate a relevant constant coefficient, thereby obtaining the battery float charge life degradation estimation model in the actual usage scene.
As a further preferred technical solution, the circulation temperature and the storage temperature include, but are not limited to, 25 ℃, 35 ℃, 45 ℃, 55 ℃; the charge and discharge rate includes but is not limited to 0.2C,0.5C,1C, and the SOC is 100%.
It should be noted that, in practical application, the floating charge use scenario of the power battery for actual energy storage needs to be decomposed, so as to obtain the temperature and the multiplying power in the actual scenario, and the number of days and the number of cycles in the storage process, and substitute the temperature and the multiplying power in the actual scenario into the floating charge life estimation model to predict the service life of the energy storage battery in the actual scenario.
For example: for class a temperature environments: the working temperature of the battery is less than or equal to 35 ℃ throughout the year, and the power grids of the same type: under the actual scene that the average monthly power failure of the communication equipment is less than 10 hours, the communication equipment carries out 0.2C charging and discharging, and the floating charging service life of the lithium battery is estimated by the following steps:
(1) at 35 ℃ and 0.2C multiplying power, at least three test lithium batteries are subjected to accelerated life test, at least five test lithium batteries are stored at different temperatures (SOC 100%), capacity retention rate data corresponding to different cycle numbers at different temperatures and multiplying powers and capacity retention rate data corresponding to different storage days are obtained, and a storage capacity attenuation coefficient a1 is determined to be 5.78 multiplied by 10 < -6 >, and a cycle capacity attenuation coefficient a2 is determined to be 6.0 multiplied by 10 < -4 >.
(2) Determining a power battery float charge life estimation model:
Qloss＝5.78×10-6*t1/2+6.0×10-4*N
(3) the decomposition of the actual scene is shown in the following table 1:
(4) and then estimating the service life under the scene by using the power battery float charge service life estimation model, wherein the result is shown in the following table 2:
| EOL(％) | 80％ | 70％ | 60％ | 50％ |
| years (years) | 3 | 5 | 6 | 8 |
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. A floating charge life estimation method for a power lithium battery is characterized by comprising the following steps:
the method comprises the steps of obtaining floating charge information of a lithium battery to be tested, wherein the floating charge information comprises the temperature, the multiplying power, the storage days and the cycle number of the lithium battery to be tested in the floating charge process of the battery;
and processing the floating charge information by adopting a pre-constructed battery floating charge life degradation estimation model, and predicting the floating charge life of the lithium battery to be tested.
2. The method for estimating the float charge life of a power lithium battery as claimed in claim 1, wherein the model for estimating the float charge life degradation of the battery is:
z
Qloss＝a1*t+a2*N
wherein Q islossFor the floating charge life capacity decay rate, a1 is a storage capacity decay coefficient, a2 is a cycle capacity decay coefficient, t is the storage days in the floating charge process of the lithium ion battery, N is the monthly cycle number in the floating charge process of the lithium ion battery, z is a constant coefficient, and x is a multiplication sign.
3. The floating charge life estimation method of the power lithium battery as claimed in claim 2, wherein the storage capacity decay coefficient a1 is a function of the storage temperature T1 and the SOC, and is expressed by the following formula: a1 ═ f (T1, SOC);
the cycle capacity attenuation coefficient a2 is a function of the cycle temperature T2, the depth of discharge DOD% and the charge-discharge multiplying power C, and the formula is as follows: a2 ═ f (T2, DOD%, C).
4. The method for estimating the floating charge life of a lithium power battery as claimed in claim 1, wherein the process for constructing the model for estimating the floating charge life degradation of the lithium power battery comprises:
under different cycle temperatures and charge-discharge multiplying powers, carrying out accelerated cycle life test on n1 test lithium batteries to obtain capacity retention rates corresponding to different cycle numbers;
storing n2 test lithium batteries with the charge states of 100% at different storage temperatures to obtain capacity retention rates corresponding to different storage days;
and constructing a battery floating charge life degradation estimation model according to the capacity retention rates corresponding to different cycle numbers and the capacity retention rates corresponding to different storage days.
5. The method of claim 4, wherein the cycling temperature and the storage temperature each comprise 25 ℃, 35 ℃, 45 ℃, 55 ℃; the charge and discharge multiplying power comprises 0.2C,0.5C and 1C.
6. A floating charge life estimation system for a power lithium battery is characterized by comprising:
the device comprises a floating charge information acquisition module, a battery floating charge module and a battery management module, wherein the floating charge information acquisition module is used for acquiring floating charge information of a lithium battery to be tested, and the floating charge information comprises the temperature, the multiplying power, the storage days and the cycle number of the lithium battery to be tested in the floating charge process of the battery;
and the service life estimation module is used for processing the floating charge information by adopting a pre-constructed battery floating charge service life degradation estimation model and predicting the floating charge service life of the lithium battery to be tested.
7. The floating charge life estimation system of claim 6, wherein the battery floating charge life degradation estimation model is:
Qloss＝a1*tz+a2*N
wherein Q islossFor the floating charge life capacity decay rate, a1 is a storage capacity decay coefficient, a2 is a cycle capacity decay coefficient, t is the storage days in the floating charge process of the lithium ion battery, N is the monthly cycle number in the floating charge process of the lithium ion battery, z is a constant coefficient, and x is a multiplication sign.
8. The floating charge life estimation system of claim 7, wherein the storage capacity decay coefficient a1 is a function of storage temperature T1 and SOC, and is expressed by the following formula: a1 ═ f (T1, SOC);
the cycle capacity attenuation coefficient a2 is a function of the cycle temperature T2, the depth of discharge DOD% and the charge-discharge multiplying power C, and the formula is as follows: a2 ═ f (T2, DOD%, C).
9. The floating charge life estimation system of a lithium power battery of claim 6, further comprising a model building module comprising:
the first capacity retention rate obtaining unit is used for carrying out accelerated cycle life test on n1 test lithium batteries under different cycle temperatures and charge-discharge multiplying factors to obtain capacity retention rates corresponding to different cycle numbers;
the second capacity retention rate acquisition unit is used for storing n2 test lithium batteries with the charge states of 100% at different storage temperatures to obtain capacity retention rates corresponding to different storage days;
and the model building unit is used for building the battery floating charge life degradation estimation model according to the capacity retention rates corresponding to different cycle numbers and the capacity retention rates corresponding to different storage days.
10. The floating charge life estimation system for a lithium power battery of claim 9, wherein the cycling temperature and the storage temperature each comprise 25 ℃, 35 ℃, 45 ℃, 55 ℃; the charge and discharge multiplying power comprises 0.2C,0.5C and 1C.
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| CN105974326A (en) * | 2016-06-01 | 2016-09-28 | 华霆（合肥）动力技术有限公司 | Lithium battery service life pre-estimation method and device |
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