CN109031141B - Lithium ion battery lithium analysis prediction method - Google Patents
Lithium ion battery lithium analysis prediction method Download PDFInfo
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Abstract
The invention provides a prediction method for lithium analysis of a lithium ion battery, which comprises the following steps: s1) carrying out linear fitting on the anode potential and the charging current or the charging multiplying power in the charging process of the lithium ion battery to obtain a slope; s2) linear fitting is carried out on the lithium ion battery charge transfer resistance and the slope, meanwhile, a condition model of the lithium ion battery charging current or charging rate and temperature is obtained according to the relation between the charge transfer resistance and the temperature T, and the critical lithium analysis charging current or charging rate at different temperatures is predicted according to the condition model. Compared with the prior art, the method can quantitatively pre-judge the lithium analysis critical conditions of the lithium ion battery at different environmental temperatures by utilizing the Arrhenius formula in a modeling mode, does not need to disassemble a battery core, saves time and labor, saves resources, realizes quantification and has high accuracy.
Description
Technical Field
The invention belongs to the technical field of lithium ion batteries, and particularly relates to a lithium analysis prediction method for a lithium ion battery.
Background
The lithium ion battery is taken as a novel green energy source and is generally concerned in recent years, the negative electrode material of the current commercial lithium ion battery mainly takes a graphite carbon material as a main material, the polarization inside the battery is increased when the battery is charged at a high multiplying power or charged at a low temperature, the overpotential of the negative electrode is large, lithium ions in the battery are separated out on the surface of the carbon negative electrode, lithium dendrites are seriously formed, a diaphragm is pierced, the short circuit of the positive electrode and the negative electrode is caused, the safety performance is greatly reduced, the critical condition that lithium is separated out from an electric core can be judged in advance, the charging.
Currently, the most common method for judging whether a lithium ion battery analyzes lithium is to charge the battery at different multiplying powers and temperatures, disassemble the battery, judge by naked eyes and subjectively give the lithium analysis state and severity. The method can only carry out qualitative judgment, consumes a large amount of manpower and material resources, and has certain potential safety hazard in the battery disassembling process.
Disclosure of Invention
In view of the above, the technical problem to be solved by the present invention is to provide a method for predicting lithium deposition of a lithium ion battery.
The invention provides a prediction method for lithium analysis of a lithium ion battery, which comprises the following steps:
s1) carrying out linear fitting on the anode potential and the charging current or the charging multiplying power in the charging process of the lithium ion battery to obtain a slope;
s2) linear fitting is carried out on the lithium ion battery charge transfer resistance and the slope, meanwhile, a condition model of the lithium ion battery charging current or charging rate and temperature is obtained according to the relation between the charge transfer resistance and the temperature T, and the critical lithium analysis charging current or charging rate at different temperatures is predicted according to the condition model.
Preferably, the equation obtained by linear fitting in step S1) is U ═ kX + b, U is a potential, k is a slope, b is an intercept, and X is a charging current or a charging rate.
Preferably, the step S1) is specifically:
and charging the lithium ion battery at the same temperature by adopting different charging multiplying factors or charging currents, recording the anode potential and the charge transfer resistance, and performing linear fitting on the anode potential and the charging current or the charging multiplying factor to obtain the slope.
Preferably, the temperature is 10 ℃ to 60 ℃.
Preferably, the charging rate is 0.1-5C.
Preferably, in step S2), the lithium ion battery charge transfer resistance and the slope are linearly fitted to obtain an equation k ═ α × Rct + β, where α and β are constants, and Rct is the charge transfer resistance.
Preferably, the relationship between the charge transfer resistance and the temperature T conforms to the equation:
A. b is a constant, Ea is the activation energy, R is the molar gas constant, T is the absolute temperature, and K is the rate constant.
Preferably, the condition model of the charging current or the charging rate and the temperature of the lithium ion battery is as follows:
The invention provides a prediction method for lithium analysis of a lithium ion battery, which comprises the following steps: s1) carrying out linear fitting on the anode potential and the charging current or the charging multiplying power in the charging process of the lithium ion battery to obtain a slope; s2) linear fitting is carried out on the lithium ion battery charge transfer resistance and the slope, meanwhile, a condition model of the lithium ion battery charging current or charging rate and temperature is obtained according to the relation between the charge transfer resistance and the temperature T, and the critical lithium analysis charging current or charging rate at different temperatures is predicted according to the condition model. Compared with the prior art, the method can quantitatively pre-judge the lithium analysis critical conditions of the lithium ion battery at different environmental temperatures by utilizing the Arrhenius formula in a modeling mode, does not need to disassemble a battery core, saves time and labor, saves resources, realizes quantification and has high accuracy.
Drawings
FIG. 1 is a graph showing the relationship between critical lithium deposition current and temperature in example 1 of the present invention;
fig. 2 is a photograph of the cell interface when the charging magnification is 0.3C;
fig. 3 is a photograph of the cell interface when the charging magnification is 0.4C;
FIG. 4 is a graph showing the relationship between critical lithium deposition current and temperature in example 2 of the present invention;
fig. 5 is a photograph of a cell interface when the charging magnification is 1C in embodiment 2 of the present invention;
fig. 6 is a photograph of a cell interface when the charging magnification is 0.6C in embodiment 2 of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a prediction method for lithium analysis of a lithium ion battery, which comprises the following steps: s1) carrying out linear fitting on the anode potential and the charging current or the charging multiplying power in the charging process of the lithium ion battery to obtain a slope; s2) linear fitting is carried out on the lithium ion battery charge transfer resistance and the slope, meanwhile, a condition model of the lithium ion battery charging current or charging rate and temperature is obtained according to the relation between the charge transfer resistance and the temperature T, and the critical lithium analysis charging current or charging rate at different temperatures is predicted according to the condition model.
The present invention is not limited to the commercially available sources of all the raw materials.
Performing linear fitting on the anode potential and the charging current or the charging rate in the charging process of the lithium ion battery to obtain a slope; in the invention, the step is preferably to charge the lithium ion battery by adopting different charging multiplying factors or charging currents at the same temperature, record the anode potential and the charge transfer resistance and perform linear fitting on the anode potential and the charging current or the charging multiplying factor; preferably, the fitted equation is U ═ kX + b, U is a potential, k is a slope, b is an intercept, and X is a charging current or a charging rate; the temperature is preferably 10-60 ℃; the lithium ion battery is not particularly limited, but a lithium ion battery well known to those skilled in the art, and a lithium-plated electrode is preferably used as a reference electrode in the present invention; when the temperature condition of the lithium ion battery is changed, preferably standing for 30-240 min, more preferably 60-200 min, further preferably 100-180 min, and most preferably 120-140 min, and then charging by adopting different charging rates; in order to ensure that the charging conditions are the same each time, discharging is preferably carried out first, and then charging is carried out by adopting different charging multiplying powers; the discharge is preferably carried out with a current of 1C; the discharge is preferably discharged to a lower cut-off voltage; the charging multiplying power is preferably 0.1-5C; the charging is preferably to an upper cut-off voltage; after each charging, preferably standing for 1-10 min, more preferably standing for 4-8 min, still more preferably standing for 5-6 min, recording the anode potential, then discharging, and then charging for the next time; the discharge is preferably carried out with a current of 1C.
And performing linear fitting on the recorded charge transfer resistance and the slope to obtain the relation between the slope and the charge transfer resistance at the corresponding temperature, wherein the equation is preferably as follows: k is α × Rct + β, α, β are constants, and Rct is a charge transfer resistance.
Meanwhile, according to the relationship between the charge transfer resistance and the temperature T, namely an Allen-nius equation, the equation for establishing the charge transfer resistance and the temperature T is preferably as follows:
can also be written as
A. B is a constant, Ea is the activation energy, R is the molar gas constant, T is the absolute temperature, and K is the rate constant.
Obtaining a condition model of the charging current or the charging rate and the temperature of the lithium ion battery according to a linear fitting equation of the anode potential and the charging current or the charging rate, a linear fitting equation of the charge transfer resistance and the slope, and a relation between the charge transfer resistance and the temperature T, wherein the condition model is preferably as follows:
The critical lithium precipitation charging current or the charging rate at different temperatures can be predicted according to the obtained condition model.
The method can quantitatively pre-judge the critical condition of lithium ion battery lithium analysis at different environmental temperatures by utilizing an Arrhenius formula in a modeling mode, does not need to disassemble a battery core, saves time and labor, saves resources, realizes quantification and has high accuracy.
In order to further illustrate the present invention, the following describes in detail a prediction method for lithium deposition of a lithium ion battery provided by the present invention with reference to the following embodiments.
The reagents used in the following examples are all commercially available.
Example 1
The battery adopts ternary materials: NCM 523; anode material: graphite AK01 (g capacity of 340mAh/g, graphitization degree 94%); the electrolyte is prepared by taking lithium hexafluorophosphate (LiPF6) with the concentration of 1.0M as a lithium salt, ethylene carbonate as an additive and a mixture of Propylene Carbonate (PC), Ethylene Carbonate (EC) and dimethyl carbonate (DMC) as a solvent; measuring lithium ionAnode to lithium potential U of cell under specified conditions during charging at different ratesx。
The examples are specifically presented below:
embedding a copper wire in the battery cell in the preparation stage, and carrying out lithium plating treatment on the copper wire after the battery cell is activated to prepare a reference electrode; and then, placing the battery cell into a high-low temperature box and connecting the battery cell into a charging and discharging cabinet, completing testing according to the flow, and collecting data.
The specific test flow is as follows:
1) adjusting the ambient temperature to be T (T is set by experimental requirements);
2) standing for 120 min;
3) discharging the nominal 1C current to a lower cutoff voltage;
4) standing for 5 min;
5) charging to an upper cut-off voltage;
6) standing for 5 min.
Recording the corresponding potential U of the anode at the same temperature and different multiplying powersx。
And performing linear fitting on the anode potential and the charging current in the charging process of the lithium ion battery to obtain a fitting equation U which is kI + b, wherein U is the potential, k is the slope, b is the intercept, and I is the current.
The test data and the linear fit data are shown in table 1.
TABLE 1 test data and Linear fitting data
Performing linear fitting according to the tested charge transfer resistance and the obtained slope k to obtain a linear fitting equation of the slope k and the Rct at the corresponding temperature: k is 0.8474 Rct + 8.9234.
Based on the lithium ion battery principle, an equation of Rct and temperature T is established: LnRct 7120.1(1/T) -21.059.
Based on the steps, an equation of critical charging current and temperature is established to obtain fitting models of lithium analysis critical conditions of different temperatures of the lithium ion battery:
The data in table 1 were substituted into the fitted model to obtain a fitted curve as shown in fig. 1.
According to the model, the critical lithium deposition rate at 0 ℃ (273.15K) is predicted to be 0.3C.
Controlling the temperature to be 0 ℃, sequentially charging under the conditions of multiplying power of 0.3C and 0.4C, then manually disassembling a fully charged cell core in a safety house, observing the lithium precipitation condition of an interface, and judging the critical lithium precipitation multiplying power; wherein fig. 2 is a photograph of the cell interface at a charging magnification of 0.3C, which shows no lithium deposition, and fig. 3 is a photograph of the cell interface at a charging magnification of 0.4C, which shows slight lithium deposition; from fig. 2 and fig. 3, it can be concluded that the critical lithium deposition rate at 0 ℃ of the lithium ion battery is 0.3C, which is consistent with the prediction result of the fitting model.
Example 2
The battery adopts ternary materials: NCM 523; anode material: artificial graphite SF01 (g capacity of 350mAh/g, graphitization degree 96.5%); the electrolyte is prepared by taking lithium hexafluorophosphate (LiPF6) with the concentration of 1.0M as a lithium salt, ethylene carbonate as an additive and a mixture of Propylene Carbonate (PC), Ethylene Carbonate (EC) and dimethyl carbonate (DMC) as a solvent; the anode-to-lithium potential U of the lithium ion battery under the specified conditions during charging at different multiplying powers is measuredx。
The examples are specifically presented below:
embedding a copper wire in the battery cell in the preparation stage, and carrying out lithium plating treatment on the copper wire after the battery cell is activated to prepare a reference electrode; and then, placing the battery cell into a high-low temperature box and connecting the battery cell into a charging and discharging cabinet, completing testing according to the flow, and collecting data.
Recording the corresponding potential U of the anode at the same temperature and different multiplying powersx。
And performing linear fitting on the anode potential and the charging current in the charging process of the lithium ion battery to obtain a fitting equation U which is kI + b, wherein U is the potential, k is the slope, b is the intercept, and I is the current.
The test data and the linear fit data are shown in table 2.
TABLE 2 test data and Linear fitting data
Performing linear fitting according to the tested charge transfer resistance and the obtained slope k to obtain a linear fitting equation of the slope k and the Rct at the corresponding temperature: k is 0.6987 Rct + 7.4753.
Based on the lithium ion battery principle, an equation of Rct and temperature T is established: LnRct 6440.6 (1/T) -18.678.
Based on the steps, an equation of critical charging current and temperature is established to obtain fitting models of lithium analysis critical conditions of different temperatures of the lithium ion battery:
The data in table 2 were substituted into the fitted model to obtain a fitted curve as shown in fig. 4.
Verifying a lithium precipitation test at 10 ℃, and fig. 5 is a picture of a cell interface with slight lithium precipitation when the charging magnification is 1C; fig. 6 shows that the cell interface is good when the charge rate is 0.6C. Therefore, the critical lithium-analysis rate is between 0.6C and 1C, which is consistent with the prediction result of the fitting model.
Claims (4)
1. A prediction method for lithium analysis of a lithium ion battery is characterized by comprising the following steps:
s1) charging the lithium ion battery by adopting different charging multiplying factors or charging currents at the same temperature, recording the anode potential and the charge transfer resistance, and performing linear fitting on the anode potential and the charging current or the charging multiplying factor to obtain a slope;
s2) linear fitting is carried out on the charge transfer resistance and the slope of the lithium ion battery, meanwhile, a condition model of the charging current or the charging rate and the temperature of the lithium ion battery is obtained according to the relation between the charge transfer resistance and the temperature T, and the critical lithium analysis charging current or the charging rate at different temperatures is predicted according to the condition model;
the equation obtained by linear fitting in step S1) is U ═ kX + b, U is a potential, k is a slope, b is an intercept, and X is a charging current or a charging rate;
in the step S2), linear fitting is performed on the lithium ion battery charge transfer resistance and the slope, so as to obtain an equation of k ═ α × Rct + β, where α and β are constants, and Rct is the charge transfer resistance;
the relationship between the charge transfer resistance and the temperature T conforms to the equation:
A. b is a constant, Ea is the activation energy, R is the molar gas constant, T is the absolute temperature, and K is the rate constant.
2. The prediction method according to claim 1, wherein the temperature is 10 ℃ to 60 ℃.
3. The prediction method according to claim 1, wherein the charging rate is 0.1-5C.
4. The prediction method according to claim 1, wherein the condition model of the charging current or the charging rate and the temperature of the lithium ion battery is as follows:
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