CN104502844A - Power lithium battery deterioration degree diagnosis method based on AC impedance - Google Patents

Abstract

A method for diagnosing the degradation degree of a power lithium battery based on AC impedance. The method establishes a basic curve library of AC impedance of the power lithium ion battery, collects the AC impedance curve of the power lithium ion battery to be tested, and analyzes the charge of the power lithium ion battery to be tested. transfer impedance. The method collects the AC impedance curve of the power lithium-ion battery to be tested, and combines the curve intelligent matching model to intelligently match the power lithium-ion battery AC impedance basic curve library to obtain the corresponding battery degradation degree, and at the same time combines the charge transfer impedance model to obtain the battery degradation. The degree of degradation of the battery is finally output by the comprehensive evaluation model. The present invention provides a method for diagnosing the deterioration degree of a power lithium battery based on AC impedance. The battery deterioration degree obtained by the method can guide and optimize the use of the power lithium battery, improve the utilization rate of the power lithium battery, and prolong the service life of the power lithium battery.

Description

A method for diagnosing the deterioration degree of power lithium battery based on AC impedance

technical field

The invention relates to a method for diagnosing the deterioration degree of a power lithium battery, in particular to a method for diagnosing the deterioration degree of a power lithium battery based on AC impedance, which belongs to the technical field of lithium battery testing.

Background technique

Lithium-ion batteries are widely used in large-scale energy storage systems such as electric vehicles and energy storage power stations due to their significant advantages such as high specific energy, high specific power, long cycle life, and high charge-discharge efficiency. The state of charge of the battery and the degree of deterioration of the battery are important performance parameters during the use of the battery, which respectively represent the remaining capacity and remaining life of the battery. Reasonably and accurately estimating the degree of battery deterioration is conducive to grasping the degree of battery aging, providing reliable information for the maintenance and screening of battery packs, and prolonging the service life of batteries. More importantly, it can lay the foundation for accurately estimating the attenuation degree of each aging stage of the battery, preventing overcharging or overdischarging, and ensuring the safe use of the battery. As early as 1998, F. Huet reviewed the research on the estimation of the state of charge and the degree of battery deterioration of lead-acid and nickel-cadmium battery systems by AC impedance spectroscopy. And the application of the degree of deterioration provides a strong reference value. However, at present, the industry still lacks a method for evaluating the battery state of charge and deterioration degree by using AC impedance.

Therefore, the present invention proposes a method for diagnosing the degradation degree of a power lithium battery based on AC impedance, based on the change rules of electrochemical AC impedance spectroscopy, battery internal ohms, electrochemical polarization, and ion diffusion impedance obtained through a large number of experimental analyzes. It can effectively evaluate the deterioration degree of the power lithium battery, and then guide the optimization of the use of the power lithium battery and improve the utilization rate of the power lithium battery.

Contents of the invention

The technical problem to be solved by the present invention is to provide a method for diagnosing the deterioration degree of power lithium batteries based on AC impedance. The degree of deterioration of the battery.

The technical scheme of the present invention is,

A method for diagnosing the degradation degree of power lithium batteries based on AC impedance, including establishing a basic curve library of AC impedance for power lithium-ion batteries, collecting the AC impedance curves of the power lithium-ion batteries to be tested, and analyzing the charge transfer impedance of the power lithium-ion batteries to be tested .

The method collects the AC impedance curve of the power lithium-ion battery to be tested, and combines the curve intelligent matching model to intelligently match the power lithium-ion battery AC impedance basic curve library to obtain the corresponding battery degradation degree, and at the same time combines the charge transfer impedance model to obtain the battery degradation. The degree of degradation of the battery is finally output by the comprehensive evaluation model.

The establishment of the AC impedance basic curve library of the power lithium-ion battery is to put the AC impedance curves of the power lithium-ion batteries with different degrees of deterioration into the curve library as the basic curve; The curve is obtained.

The curve intelligent matching model is to calculate the correlation coefficient of the AC impedance curve of the battery to be tested and the basic curve in the curve library one by one, and obtain the required matching curve through the matching rules of the correlation coefficient and classify it into the first type of basic curve; Measure the Euclidean distance between the AC impedance curve and the first type of basic curve, obtain the required matching curve through the matching rule of the Euclidean distance, and calculate the degradation degree of the lithium battery to be tested according to the matching curve.

The matching rule of the correlation coefficient is that a standard curve with a correlation coefficient within the range of 0.95-1 is a matching curve, and the matching rule of the Euclidean distance is the minimum Euclidean distance between curves.

The matching curve is the basic curve under the matching rules in the curve library. If the number of matching curves is zero, the basic curve with the largest correlation coefficient is selected as the final required matching curve. The battery degradation degree corresponding to the curve is the curve matching model The degree of degradation obtained; if the number of matching curves is greater than 1, the average value of the corresponding degradation degrees of each matching curve is the degree of degradation S1 obtained by the curve matching model.

The correlation coefficient is calculated according to formula (1):

$\mathrm{<span\; class="notranslate">\; G</span>}\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \{</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \}</span><span\; class="notranslate">\; =</span>\frac{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}<span\; class="notranslate">\; \{</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; \&times;</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; \}</span>}{\sqrt{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ]</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; \&times;</span>\sqrt{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ]</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

The Euclidean distance is calculated according to formula (2):

$\mathrm{<span\; class="notranslate">\; G</span>}\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \{</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \}</span><span\; class="notranslate">\; =</span>\sqrt{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ]</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

Among them, Z _i (r _j ) represents the imaginary part value corresponding to the real part r _j of the i-th basic curve impedance in the curve library, i is less than or equal to the number of curves in the curve library; Z ⁰ (r _j ) represents the lithium battery to be tested The value of the imaginary part corresponding to the real part r _j of the impedance curve; Indicates the average value of all imaginary part values of the i-th basic curve in the curve library; Indicates the average value of all the imaginary part values of the lithium battery to be tested; r _j indicates the real part value of the impedance at the jth point of the curve; m indicates the number of curve data points, 1≤j≤m.

The charge transfer impedance model is S2=a×R ² +b×R+c, where a, b, and c are characteristic parameters of the charge transfer impedance model.

The charge transfer impedance can be obtained by analyzing the AC impedance curve of the power lithium-ion battery through Zsimpwin software.

The comprehensive evaluation model is to obtain the degradation degree of the power lithium battery to be tested through weighted evaluation of the battery degradation degree output by the intelligent matching model and the charge transfer impedance model. It is calculated as follows:

S=w ₁ ×S1+w ₂ ×S2, w ₁ +w ₂ = ₁ , 0≤w 1 , w ₂ ≤1.

The beneficial effect of the present invention is that the method for diagnosing the deterioration degree of a power lithium battery based on AC impedance provided by the present invention can simply and effectively judge the power lithium battery by analyzing the data of the AC impedance curve and the charge transfer impedance and performing a comprehensive evaluation. The degradation degree of the ion battery, in the actual application environment, the battery degradation degree obtained by this method can guide the optimal use of the power lithium battery, improve the utilization rate of the power lithium battery, and prolong the service life of the power lithium battery.

The invention is applicable to the diagnosis of the deterioration degree of the power lithium battery.

Description of drawings

Fig. 1 is a block diagram of the main flow of the method for diagnosing the degree of deterioration of the present invention;

Fig. 2 is a flow chart of the curve matching algorithm;

Figure 3 is the AC impedance basic curve of different degradation degrees of power lithium batteries.

Detailed ways

The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

Referring to Figure 1, a method for diagnosing the deterioration degree of a power lithium battery based on AC impedance includes establishing a basic curve library of AC impedance for a power lithium-ion battery, collecting the AC impedance curve of the power lithium-ion battery to be tested, and analyzing the power lithium-ion battery to be tested. The charge transfer impedance of the power lithium-ion battery; the establishment of the power lithium-ion battery AC impedance basic curve library is to put the AC impedance curves of power lithium-ion batteries with different degrees of deterioration into the curve library as a basic curve; The AC impedance curve of the ion battery is obtained. The method provided by the invention includes a curve intelligent matching model, a charge transfer impedance model and a comprehensive evaluation model. The method is to intelligently match the AC impedance basic curve library of the power lithium ion battery by collecting the AC impedance curve of the power lithium ion battery to be checked to obtain the corresponding At the same time, the battery degradation degree is obtained by combining the charge transfer impedance model, and the battery degradation degree is finally output after comprehensive evaluation.

The method is specifically divided into the following steps:

Step 1: Establish a power lithium-ion battery AC impedance basic curve library, as shown in Figure 3.

Step 2: Collect the AC impedance curve of the power lithium-ion battery to be tested.

The third step: intelligent matching, calculate the correlation coefficient of the AC impedance curve of the battery to be tested and the basic curve in the curve library one by one, and obtain the required matching curve through the matching rules of the correlation coefficient and classify it as the first type of basic curve; then calculate one by one Measure the Euclidean distance between the AC impedance curve and the first type of basic curve, and obtain the required matching curve through the matching rules of the Euclidean distance. The matching rule of the correlation coefficient is that a standard curve with a correlation coefficient within the range of 0.95-1 is a matching curve, and the matching rule of the Euclidean distance is the minimum Euclidean distance between curves.

Step 4: If the number of matching curves is zero, select the basic curve with the largest correlation coefficient as the final required matching curve, and the degree of battery degradation corresponding to this curve is the degree of degradation obtained by the curve matching model; Then the average value of the degree of degradation corresponding to each matching curve is the degree of degradation obtained by the curve matching model. The matching rules are shown in Figure 2.

The correlation coefficient is calculated according to formula (1):

$\mathrm{<span\; class="notranslate">\; G</span>}\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \{</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \}</span><span\; class="notranslate">\; =</span>\frac{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}<span\; class="notranslate">\; \{</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; \&times;</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; \}</span>}{\sqrt{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ]</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; \&times;</span>\sqrt{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ]</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

The Euclidean distance is calculated according to formula (2):

$\mathrm{<span\; class="notranslate">\; G</span>}\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \{</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \}</span><span\; class="notranslate">\; =</span>\sqrt{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ]</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

Among them, Z _i (r _j ) represents the imaginary part value corresponding to the real part r _j of the i-th basic curve impedance in the curve library, i is less than or equal to the number of curves in the curve library; Z ⁰ (r _j ) represents the lithium battery to be tested The value of the imaginary part corresponding to the real part r _j of the impedance curve; Indicates the average value of all imaginary part values of the i-th basic curve in the curve library; Indicates the average value of all the imaginary part values of the lithium battery to be tested; r _j indicates the real part value of the impedance at the jth point of the curve; m indicates the number of curve data points, 1≤j≤m.

Step 5: Then obtain the corresponding battery degradation degree S1 through the intelligent matching model.

Step 6: Calculate the deterioration degree S2 of the battery through the charge transfer impedance model and the charge transfer impedance of the lithium battery to be tested, that is, S2=a×R ² +b×R+c, where a, b, and c are the values of the charge transfer impedance model Characteristic Parameters.

Step 7: Use the comprehensive evaluation model to finally obtain the degradation degree S of the power lithium battery to be tested. It is calculated as follows:

S=w ₁ ×S1+w ₂ ×S2, w ₁ +w ₂ = ₁ , 0≤w 1 , w ₂ ≤1.

Step 8: Output the deterioration degree S of the power lithium battery to be tested.

Claims (8)

1. A method for diagnosing the deterioration degree of power lithium battery based on AC impedance, characterized in that, The method establishes a power lithium-ion battery AC impedance basic curve library, collects the AC impedance curve of the power lithium-ion battery to be tested, and analyzes to obtain the charge transfer impedance of the power lithium-ion battery to be tested; The method collects the AC impedance curve of the power lithium-ion battery to be tested, and combines the curve intelligent matching model to intelligently match the power lithium-ion battery AC impedance basic curve library to obtain the corresponding battery degradation degree, and at the same time combines the charge transfer impedance model to obtain the battery degradation. The degree of degradation of the battery is finally output by the comprehensive evaluation model. 2. A method for diagnosing the deterioration degree of a power lithium battery based on AC impedance according to claim 1, wherein said establishment of a power lithium-ion battery AC impedance basic curve library is the power lithium-ion battery with different degrees of deterioration The AC impedance curve is put into the curve library as the basic curve; the charge transfer impedance can be obtained from the AC impedance curve of the power lithium-ion battery. 3. A method for diagnosing the deterioration degree of a power lithium battery based on AC impedance according to claim 1, wherein the curve intelligent matching model is to calculate the correlation between the AC impedance curve of the battery to be tested and the basic curve in the curve library one by one. The required matching curve is obtained through the matching rule of the correlation coefficient and classified as the first type of basic curve; then the Euclidean distance between the AC impedance curve to be tested and the first type of basic curve is calculated one by one, and the required matching curve is obtained through the matching rule of the Euclidean distance. According to the matching curve, the degradation degree of the lithium battery to be tested is calculated. 4. A method for diagnosing the deterioration degree of a power lithium battery based on AC impedance according to claim 1, wherein the charge transfer impedance model is S2=a×R ² +b×R+c, a, b and c are the characteristic parameters of the charge transfer impedance model, where S2 represents the degree of degradation obtained through the charge transfer impedance model, and R represents the charge transfer impedance. 5. A method for diagnosing the deterioration degree of a power lithium battery based on AC impedance according to claim 1, wherein the comprehensive evaluation model is based on the battery deterioration degree output by the intelligent matching model and the charge transfer impedance model. Weighted evaluation, and finally get the degradation degree of the power lithium battery to be tested; It is calculated as follows: S=w ₁ ×S1+w ₂ ×S2, w ₁ +w ₂ = ₁ , 0≤w 1 , w ₂ ≤1; Among them, S represents the degree of battery degradation, S1 represents the degree of degradation obtained through intelligent matching, and S2 represents the degree of degradation obtained through the charge transfer impedance model; w ₁ and w ₂ represent the weight coefficients of the two methods, respectively. 6. A method for diagnosing the deterioration degree of a power lithium battery based on AC impedance according to claim 3, wherein the matching rule of the correlation coefficient is that a standard curve with a correlation coefficient in the range of 0.95-1 is a matching curve, The matching rule of the Euclidean distance is the minimum Euclidean distance between curves. 7. A method for diagnosing the deterioration degree of a power lithium battery based on AC impedance according to claim 3, wherein the matching curve is a basic curve under matching rules in the curve library, and if the number of matching curves is zero, Then select the basic curve with the largest correlation coefficient as the final required matching curve, and the battery degradation degree corresponding to this curve is the degradation degree obtained by the curve matching model; if the number of matching curves is greater than 1, the average value of the corresponding degradation degree of each matching curve is The degree of degradation S1 obtained by the curve matching model. 8. A method for diagnosing the deterioration degree of a power lithium battery based on AC impedance according to claim 3, wherein the correlation coefficient is calculated according to formula (1): $\mathrm{<span\; class="notranslate">\; G</span>}\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; \{</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \}</span><span\; class="notranslate">\; =</span>\frac{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}<span\; class="notranslate">\; \{</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; \&times;</span>{<span\; class="notranslate">\; |</span><span\; class="notranslate">\; [</span>\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ]</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; \}</span>}{\sqrt{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ]</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}\sqrt{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; ]</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$ The Euclidean distance is calculated according to formula (2): $\mathrm{<span\; class="notranslate">\; G</span>}\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \{</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \}</span><span\; class="notranslate">\; =</span>\sqrt{\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{<span\; class="notranslate">\; [</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}^{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; r</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ]</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$ Among them, Z _i (r _j ) represents the imaginary part value corresponding to the real part r _j of the i-th basic curve impedance in the curve library, i is less than or equal to the number of curves in the curve library; Z ⁰ (r _j ) represents the lithium battery to be tested The value of the imaginary part corresponding to the real part r _j of the impedance curve; Indicates the average value of all imaginary part values of the i-th basic curve in the curve library; Indicates the average value of all the imaginary part values of the lithium battery to be tested; r _j indicates the real part value of the impedance at the jth point of the curve; m indicates the number of curve data points, 1≤j≤m.