Methods for estimating battery health

Abstract

The present invention relates to a method for estimating battery health, comprising the following steps: Step 1: Take n batteries of the same model to conduct cyclic charge and discharge attenuation experiments, and fit the attenuation reference curve of the battery of this model; Step 2: Take a number of batteries of this model to conduct cyclic attenuation experiments at different temperatures, different average SOCs, and different discharge depths, and use the experimental data of the cyclic attenuation experiments to correct the parameters in the attenuation reference curve to obtain the corrected attenuation curve of the battery of this model; Step 3: When estimating the health of a battery to be estimated belonging to this model, use the usage data of the battery to be estimated and the corrected attenuation curve of the battery of this model to estimate the attenuation of each cycle of the battery to be estimated, thereby estimating the life and health of the battery to be estimated. The present invention has strong scalability, can be realized with only a limited number of experiments, has high accuracy, and is relatively simple to calculate.

Description

Technical Field

[0001] The present invention belongs to the technical field of power battery health assessment, and specifically relates to a method for estimating battery health based on battery usage. Background Art

[0002] Lithium-ion batteries are widely used in various fields due to their advantages such as high output voltage, long cycle life, high energy density, low self-discharge rate and wide operating temperature range. Their own safety and reliability have always been the focus of everyone's attention.

[0003] At present, the mainstream methods for estimating battery health in the industry are mainly divided into the following categories:

[0004] 1. Machine Learning Model Method

[0005] The disadvantages of this method are:

[0006] (1) It requires a large amount of labeled data and a large number of experiments, which results in high experimental costs;

[0007] (2) Since experiments cannot cover all usage scenarios, migrating from experimental data to actual situations may lead to reduced model accuracy.

[0008] 2. Ampere-hour integration method

[0009] The disadvantages of this method are:

[0010] (1) The error is relatively large;

[0011] (2) The accuracy of health calculation is limited by the accuracy of the sensor;

[0012] (3) The calculated results will fluctuate.

[0013] 3. Double Kalman Filtering

[0014] The disadvantages of this method are:

[0015] (1) The calculation process is complicated;

[0016] (2) It is necessary to establish a battery equivalent circuit diagram, but it is difficult to identify the parameters in the equivalent circuit diagram of a device that uses a battery, such as a vehicle, during actual operation.

[0017] It can be seen that the mainstream method is to evaluate the current health status of the battery based on the current battery performance, which has many shortcomings. Summary of the invention

[0018] The purpose of the present invention is to provide a method for estimating battery health which requires a limited number of experiments, is easy to expand the scope of application, has high accuracy and low complexity.

[0019] In order to achieve the above object, the technical solution adopted by the present invention is:

[0020] A method for estimating battery health comprises the following steps:

[0021] Step 1: Take n batteries of the same model and conduct a cyclic charge-discharge attenuation experiment, where n is an integer greater than 3, and use the experimental data of the cyclic charge-discharge attenuation experiment to fit the attenuation curve of the battery of this model as the attenuation reference curve of the battery of this model, and the attenuation curve represents the attenuation percentage P of the battery of this model. loss The relationship between the number of cycles N of the battery model, the attenuation curve contains three coefficients, namely α sei , β sei 、f d,1 ;

[0022] Step 2: Take a number of batteries of this model and conduct cycle decay experiments at different temperatures, different average SOCs, and different discharge depths, and use the experimental data of the cycle decay experiments to obtain the f d,1 The corresponding temperature correction form, average SOC correction form, discharge depth correction form and calendar time correction form are used to correct the f d,1 Correction is performed to obtain the corrected f d,1 , and then use the modified f d,1 Correcting the attenuation reference curve of the battery of this model to obtain the corrected attenuation curve of the battery of this model;

[0023] Step three: When estimating the health of the battery to be estimated that belongs to this model of battery, the attenuation of each cycle of the battery to be estimated is estimated using the usage data of the battery to be estimated and the corrected attenuation curve of the battery of this model, thereby estimating the life and health of the battery to be estimated.

[0024] In the step 1, the cyclic charge-discharge attenuation experiment is carried out at a standard temperature t0.

[0025] In the step 1, according to the number of cycles and the attenuation percentage of each battery of the model, the attenuation curve corresponding to each battery of the model is fitted to determine the α corresponding to each battery of the model. sei , β sei and f d,1 , and then get the battery type and And and As the α in the attenuation reference curve of this type of battery sei , β sei 、f d,1.

[0026] In the step 1, the expression of the attenuation curve is:

[0027] In the step 2, at least 10 different temperatures, 2 different average SOCs, and 4 different discharge depths are selected when performing the cycle decay experiment.

[0028] In step 2, the temperature correction formula is: Among them, k T is the temperature correction coefficient, T is the current temperature, T ref is the reference temperature;

[0029] The average SOC correction formula is Among them, k σ is the average SOC correction coefficient, σ is the current average SOC, σ ref is the reference average SOC;

[0030] The calendar time correction formula is S t (t) = k t t, where k t is the calendar time correction coefficient, t is the current calendar time;

[0031] The discharge depth correction formula is S δ (δ) = k δ,e1 δexp(k δ,e2 δ), where k δ,e1 , k δ,e2 are all discharge depth correction coefficients, and δ is the current discharge depth.

[0032] In step 2, when the current temperature T=T A hour, where f d,t [T=T A ] is the current temperature T = T A f obtained by the cyclic decay experiment d,1 Data, f d,t [T=T ref ] is the current temperature T = T ref f obtained by the cyclic decay experiment d,1 The temperature correction coefficient k is solved by combining the temperature correction formula T , and then obtain the temperature correction formula;

[0033] When the current average SOCσ=σ A hour, Among them, f d,t [σ=σ A ] is the current average SOCσ=σA f obtained by the cyclic decay experiment d,1 Data, f d,t [σ=σ ref ] is the current average SOCσ=σ ref f obtained by the cyclic decay experiment d,1 data, then the average SOC correction coefficient is solved in combination with the average SOC correction formula, thereby obtaining the average SOC correction formula;

[0034] The calendar time correction factor Among them, f d,t [T=T A ,σ=σ A ] is the current temperature T = T A 、Current average SOCσ=σ ref f obtained by the cyclic decay experiment d,1 data;

[0035] When the current discharge depth δ=δ A hour, Among them, f d,1 [δ=δ A ,σ=σ A ,T=T A ,t=t p,A ] is the current discharge depth δ = δ A 、Current average SOCσ=σ ref 、Current temperature T=T A , the current calendar time t = t p,A f obtained by the cyclic decay experiment d,1 The discharge depth correction coefficient k is solved by combining the discharge depth correction formula. δ,e1 , k δ,e2 , and then the discharge depth correction formula is obtained.

[0036] In the step 2, the corrected f d,1 =[S δ (δ)+S t (t)]S σ (σ)S T (T).

[0037] In the step three, the usage data of the battery to be estimated is counted according to the rain flow counting method.

[0038] Due to the application of the above technical solution, the present invention has the following advantages compared with the prior art: the present invention has strong scalability, can be realized with only a limited number of experiments, has high accuracy, and is relatively simple to calculate. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Attached Figure 1 The flowchart of the method for estimating battery health of the present invention is shown. DETAILED DESCRIPTION

[0040] The present invention will be further described below in conjunction with the embodiments shown in the accompanying drawings.

[0041] Embodiment 1: As shown in the attached Figure 1 As shown, a method for estimating battery health includes the following steps:

[0042] Step 1: Determine the battery’s attenuation benchmark curve through a cyclic charge and discharge attenuation experiment

[0043] Take n (n is an integer greater than 3) batteries of the same model (lithium-ion batteries) and conduct a cyclic charge-discharge attenuation experiment. Use the experimental data of the cyclic charge-discharge attenuation experiment to fit the attenuation curve of the battery of this model as the attenuation reference curve of the battery of this model. The attenuation curve represents the attenuation percentage P of the battery of this model. loss The relationship between the number of cycles N of this type of battery, the attenuation curve contains three coefficients, namely α sei , β sei 、f d,1 .

[0044] 1. Take n (n>3) batteries of the same model and conduct a cyclic charge-discharge attenuation experiment at a standard temperature t0 (t0 is generally 25°C). During the cyclic charge-discharge attenuation experiment, the battery SOC cycle range is 0% to 100%. Record the number of cycles N of each battery and the attenuation percentage P corresponding to each cycle. loss .

[0045] 2. According to the number of cycles N of each battery and the decay percentage P corresponding to each cycle loss , and fit the decay curves of each battery according to the formula:

[0046] 3. α in the above formula sei It is related to the first effect of the battery and represents the proportion of lithium ions consumed in the early stage of the battery to form a stable SEI film.

[0047] 4. According to the number of cycles and attenuation percentage of each battery of this model, the attenuation curve corresponding to each battery of this model is fitted, and the α corresponding to each battery of this model is determined. sei , β sei and f d,1 , that is, a total of n α sei , n β sei and n f d,1 . For n α sei , n β sei and n f d,1Find the average value to get the battery type and and will and As the α in the attenuation reference curve of this type of battery sei , β sei 、f d,1 , and finally get the attenuation curve of this type of battery It is used as the attenuation reference curve for this type of battery.

[0048] Step 2: Parameter correction under different conditions

[0049] Take several batteries of this model and divide them into n z The group conducted cycle decay experiments at different temperatures, different average SOCs, and different discharge depths, and used the experimental data of the cycle decay experiments to obtain f d,1 The corresponding temperature correction form, average SOC correction form, discharge depth correction form and calendar time correction form are then used to correct f d,1 Correction is performed to obtain the corrected f d,1 , and then use the corrected f d,1 The attenuation reference curve of the battery of this model is corrected to obtain the corrected attenuation curve of the battery of this model.

[0050] 1. The f in the above-mentioned attenuation reference curve of this type of battery d,1 It will vary depending on temperature, SOC, and depth of discharge, so it needs to be corrected for different conditions.

[0051] 2. Take a number of batteries of this model and divide them into n z The control variable method is used to carry out cycle decay experiments on the batteries at different temperatures, different average SOCs, and different discharge depths. That is, at least 10 different temperatures, 2 different average SOCs, and 4 different discharge depths are taken in the experiment.

[0052] 3. Corrected f d,1 =[S δ (δ)+S t (t)]S σ (σ)S T (T).

[0053] 4. In the above formula, S δ (δ) is the discharge depth correction formula, S t (t) is the calendar time correction form, S σ (σ) is the average SOC correction formula, S T (T) is the temperature correction form.

[0054] 5. For temperature correction, In, k T is the temperature correction coefficient, T is the current temperature, T ref is the reference temperature. When the current temperature T=T A hour, where f d,t [T=T A ] is the current temperature T = T A f obtained by cyclic decay experiment d,1 Data, f d,t [T=T ref ] is the current temperature T = T ref f obtained by cyclic decay experiment d,1 Data, then the temperature correction coefficient k is solved by combining the temperature correction formula T , and then get the temperature correction formula. The reference temperature T ref , if the temperature of the reference curve is taken as the reference temperature, then T ref =t0.

[0055] 6. For average SOC correction, Among them, k σ is the average SOC correction coefficient, σ is the current average SOC, σ ref is the reference average SOC, when the current average SOCσ=σ A hour, Among them, f d,t [σ=σ A ] is the current average SOCσ=σ A f obtained by cyclic decay experiment d,1 Data, f d,t [σ=σ ref ] is the current average SOCσ=σ ref f obtained by cyclic decay experiment d,1 If the average SOC of the reference curve is used as a reference, then the reference average SOCσ ref =avg(SOC cycle ).

[0056] 7. For calendar time correction, S t (t) = k t t, where k t is the calendar time correction coefficient, t is the current calendar time, and the calendar time correction coefficient Among them, f d,t [T=T A ,σ=σ A ] is the current temperature T = T A 、Current average SOCσ=σref f obtained by cyclic decay experiment d,1 Data. Based on this, the calendar time correction factor k is calculated t .

[0057] 8. Correction formula for discharge depth, S δ (δ) = k δ,e1 δexp(k δ,e2 δ), where k δ,e1 , k δ,e2 are the discharge depth correction coefficients, δ is the current discharge depth, when the current discharge depth δ=δ A hour, Among them, f d,1 [δ=δ A ,σ=σ A ,T=T A ,t=t p,A ] is the current discharge depth δ = δ A 、Current average SOCσ=σ ref 、Current temperature T=T A , the current calendar time t = t p,A f obtained by cyclic decay experiment d,1 The discharge depth correction factor k is calculated by combining the discharge depth correction formula. δ,e1 , k δ,e2 , and then the discharge depth correction formula is obtained.

[0058] Step 3: Estimates for actual batteries

[0059] When estimating the health of a battery to be estimated that belongs to this model of battery, the usage data of the battery to be estimated is counted according to the rain flow counting method, including the number of cycles of this battery in use, the average temperature of each time, the depth of discharge each time and the average SOC each time, etc. The usage data of the battery to be estimated and the corrected attenuation curve of this model of battery are used to estimate the attenuation of the battery to be estimated in each cycle, thereby estimating the life and health of the battery to be estimated.

[0060] The advantages of the above scheme are:

[0061] 1. Strong scalability, the same model of battery can be used universally with limited experiments;

[0062] 2. Considering and being compatible with different conditions and uses in different environments;

[0063] 3. High precision;

[0064] 4. Integrates the electrochemical characteristics of batteries;

[0065] 5. Incorporates the concept of cumulative damage.

[0066] Compared with the existing machine learning model method, this scheme only requires a limited number of experiments and can be applied to other batteries of the same model; compared with the existing ampere-hour integration method, this scheme has high accuracy, will not fluctuate up and down, and is insensitive to sensor accuracy; compared with the existing dual Kalman filtering method, this scheme does not require an equivalent circuit diagram, does not require parameter identification, and reduces the complexity of the algorithm.

[0067] The above embodiments are only for illustrating the technical concept and features of the present invention, and their purpose is to enable people familiar with the technology to understand the content of the present invention and implement it accordingly, and they cannot be used to limit the protection scope of the present invention. Any equivalent changes or modifications made according to the spirit of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for estimating battery health, characterized in that: The method for estimating battery health comprises the following steps: Step 1: Take n batteries of the same model and conduct a cyclic charge-discharge attenuation experiment, where n is an integer greater than 3, and use the experimental data of the cyclic charge-discharge attenuation experiment to fit the attenuation curve of the battery of this model as the attenuation reference curve of the battery of this model, and the attenuation curve represents the attenuation percentage P of the battery of this model. loss The relationship between the number of cycles N of the battery model, the attenuation curve contains three coefficients, namely α sei , β sei 、f d,1 ; Step 2: Take a number of batteries of this model and conduct cycle decay experiments at different temperatures, different average SOCs, and different discharge depths, and use the experimental data of the cycle decay experiments to obtain the f d,1 The corresponding temperature correction form, average SOC correction form, discharge depth correction form and calendar time correction form are used to correct the f d,1 Correction is performed to obtain the corrected f d,1 , and then use the modified f d,1 Correcting the attenuation reference curve of the battery of this model to obtain the corrected attenuation curve of the battery of this model; Step 3: When estimating the health of the battery to be estimated that belongs to the battery model, the attenuation amount of each cycle of the battery to be estimated is estimated using the usage data of the battery to be estimated and the corrected attenuation curve of the battery model, thereby estimating the life and health of the battery to be estimated; In the step 1, the expression of the attenuation curve is: In step 2, the temperature correction formula is: Among them, k T is the temperature correction coefficient, T is the current temperature, T ref is the reference temperature; The average SOC correction formula is Among them, k σ is the average SOC correction coefficient, σ is the current average SOC, σ ref is the reference average SOC; The calendar time correction formula is St(t)=ktt, where k t is the calendar time correction coefficient, t is the current calendar time; The discharge depth correction formula is S δ (δ) = k δ,e1 δexp(k δ,e2 δ), where k δ,e1 , k δ,e2 are all discharge depth correction coefficients, and δ is the current discharge depth.

2. The method for estimating battery health according to claim 1, characterized in that: In the step 1, the cyclic charge-discharge attenuation experiment is carried out at a standard temperature t0.

3. The method for estimating battery health according to claim 1, characterized in that: In the step 1, according to the number of cycles and the attenuation percentage of each battery of the model, the attenuation curve corresponding to each battery of the model is fitted to determine the α corresponding to each battery of the model. sei , β sei and f d,1 , and then get the battery type and And and As the α in the attenuation reference curve of this type of battery sei , β sei 、f d,1 .

4. The method for estimating battery health according to claim 1, characterized in that: In the step 2, at least 2 different temperatures, 2 different average SOCs, and 4 different discharge depths are taken when conducting the cycle decay experiment.

5. The method for estimating battery health according to claim 1, characterized in that: In step 2, when the current temperature T=T A hour, where f d,t [T=T A ] is the current temperature T = T A f obtained by the cyclic decay experiment d,1 Data, f d,t [T=T ref ] is the current temperature T = T ref f obtained by the cyclic decay experiment d,1 The temperature correction coefficient k is solved by combining the temperature correction formula T , and then obtain the temperature correction formula; When the current average SOCσ=σ A hour, Among them, f d,t [σ=σ A ] is the current average SOCσ=σ A f obtained by the cyclic decay experiment d,1 Data, f d,t [σ=σ ref ] is the current average SOCσ=σ ref f obtained by the cyclic decay experiment d,1 data, then combining the average SOC correction formula to solve the average SOC correction coefficient, and then obtain the average SOC correction formula; The calendar time correction factor Among them, f d,t [T=T A ,σ=σ A ] is the current temperature T = T A 、Current average SOCσ=σ ref f obtained by the cyclic decay experiment d,1 data; When the current discharge depth δ=δ A hour, Among them, f d,1 [δ=δ A ,σ=σ A ,T=T A ,t=t p,A ] is the current discharge depth δ = δ A 、Current average SOCσ=σ ref 、Current temperature T=T A 、Current calendar time t=t p,A f obtained by the cyclic decay experiment d,1 The discharge depth correction coefficient k is solved by combining the discharge depth correction formula. δ,e1 , k δ,e2 , and then the discharge depth correction formula is obtained.

6. The method for estimating battery health according to claim 5, characterized in that: In the step 2, the corrected f d,1 =[S δ (δ)+S t (t)]S σ (σ)S T (T).

7. The method for estimating battery health according to claim 1, characterized in that: In the step three, the usage data of the battery to be estimated is counted according to the rain flow counting method.

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