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CN112986828B - Methods for estimating battery health - Google Patents

Methods for estimating battery health Download PDF

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CN112986828B
CN112986828B CN202110388367.5A CN202110388367A CN112986828B CN 112986828 B CN112986828 B CN 112986828B CN 202110388367 A CN202110388367 A CN 202110388367A CN 112986828 B CN112986828 B CN 112986828B
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attenuation
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correction
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CN112986828A (en
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柯鹏
钱磊
朱卓敏
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Shanghai Powershare Information Technology Co ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/385—Arrangements for measuring battery or accumulator variables
    • G01R31/387—Determining ampere-hour charge capacity or SoC
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/392—Determining battery ageing or deterioration, e.g. state of health

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  • General Physics & Mathematics (AREA)
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Abstract

本发明涉及一种预估电池健康度的方法，包括以下步骤：步骤一：取n个同型号电池进行循环充放电衰减实验，拟合得到该型号电池的衰减基准曲线；步骤二：取若干个该型号电池进行不同温度、不同平均SOC、不同放电深度下的循环衰减实验，利用循环衰减实验的实验数据对衰减基准曲线中的参数进行修正，得到该型号电池的修正后衰减曲线；步骤三：当对属于该型号电池的待预估电池进行健康度预估时，利用待预估电池的使用数据和该型号电池的修正后衰减曲线预估待预估电池每个循环的衰减量，从而预估待预估电池的寿命和健康度。本发明扩展性强，只需有限次实验即可实现，精度加高，计算较为简便。

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 to obtain 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

Method for estimating battery health
Technical Field
The invention belongs to the technical field of power battery health assessment, and particularly relates to a method for estimating the health degree of a battery according to the service condition of the battery.
Background
The lithium ion battery is widely applied to various fields because of the advantages of high output voltage, long cycle life, high energy density, low self-discharge rate, wide working temperature range and the like, and the safety and reliability of the lithium ion battery are always important points of great attention.
Currently, the mainstream methods for estimating the health of the battery in the industry are mainly divided into the following methods:
1. Machine learning model method
The disadvantage of this method is that:
(1) A large amount of data with labels is needed, a large amount of experiments are needed, and the experiment cost is high;
(2) Migration from experimental data to actual conditions may result in reduced model accuracy because the experiment cannot cover all use cases.
2. Ampere-hour integration method
The disadvantage of this method is that:
(1) The error is relatively large;
(2) The accuracy of the health calculation is limited by the sensor accuracy;
(3) The calculated result fluctuates up and down.
3. Double Kalman filtering method
The disadvantage of this method is that:
(1) The calculation process is complex;
(2) It is necessary to establish a battery equivalent circuit diagram, and a device using a battery, such as a vehicle, is difficult to identify parameters in the equivalent circuit diagram in actual operation.
Therefore, the mainstream method is to evaluate the current state of health of the battery through the current battery performance, and the disadvantage is more.
Disclosure of Invention
The invention aims to provide a method for estimating the battery health, which has the advantages of limited required experiment times, easy expansion of application range, higher accuracy and lower complexity.
In order to achieve the above purpose, the invention adopts the following technical scheme:
A method of estimating battery health, comprising the steps of:
Step one, carrying out a cyclic charge-discharge attenuation experiment on N batteries with the same type, wherein N is an integer larger than 3, fitting an attenuation curve of the battery with the same type by using experimental data of the cyclic charge-discharge attenuation experiment to be used as an attenuation reference curve of the battery with the same type, wherein the attenuation curve represents the relation between the attenuation percentage P loss of the battery with the same type and the cycle number N of the battery with the same type, and the attenuation curve comprises three coefficients which are alpha sei、βsei、fd,1 respectively;
Step two, taking a plurality of batteries of the model to carry out cyclic attenuation experiments under different temperatures, different average SOCs and different discharge depths, solving a temperature correction form, an average SOC correction form, a discharge depth correction form and a calendar time correction form corresponding to the f d,1 by using experimental data of the cyclic attenuation experiments, correcting the f d,1 by using the temperature correction form, the average SOC correction form, the discharge depth correction form and the calendar time correction form to obtain a corrected f d,1, and correcting an attenuation reference curve of the battery of the model by using the corrected f d,1 to obtain a corrected attenuation curve of the battery of the model;
and thirdly, when the health degree of the battery to be estimated, which belongs to the battery of the model, is estimated, estimating the attenuation of each cycle of the battery to be estimated by using the use data of the battery to be estimated and the corrected attenuation curve of the battery of the model, so as to estimate the service life and the health degree of the battery to be estimated.
In the first step, the cyclic charge-discharge decay experiment is performed at a standard temperature t 0.
In the first step, according to the cycle number and the attenuation percentage of each battery model, fitting to obtain an attenuation curve corresponding to each battery model, thereby determining alpha sei、βsei and f d,1 corresponding to each battery model, and further obtaining the battery modelAndAnd by combiningAndAs alpha sei、βsei、fd,1 in the decay reference curve of the model battery.
In the first step, the attenuation curve is expressed as
In the second step, at least different temperatures, 2 different average SOCs and 4 different discharge depths are taken when the cyclic attenuation experiment is carried out.
In the second step, the temperature correction is as followsWherein k T is a temperature correction coefficient, T is a current temperature, and T ref is a reference temperature;
The average SOC correction formula is Wherein k σ is an average SOC correction coefficient, σ is a current average SOC, and σ ref is a reference average SOC;
the calendar time correction formula is S t(t)＝kt t, wherein k t is a calendar time correction coefficient, and t is the current calendar time;
The depth of discharge correction is S δ(δ)＝kδ,e1δexp(kδ,e2 δ), where k δ,e1、kδ,e2 is the depth of discharge correction coefficient, and δ is the current depth of discharge.
In the second step, when the current temperature t=t A,F d,t[T＝TA is f d,1 data obtained through the cyclic attenuation experiment when the current temperature is T=T A, f d,t[T＝Tref is f d,1 data obtained through the cyclic attenuation experiment when the current temperature is T=T ref, and the temperature correction coefficient k T is solved by combining the temperature correction type, so that the temperature correction type is obtained;
when the current average SOC sigma=sigma A, F d,t[σ＝σA is f d,1 data obtained through the cyclic attenuation experiment when the current average SOC sigma=sigma A, f d,t[σ＝σref is f d,1 data obtained through the cyclic attenuation experiment when the current average SOC sigma=sigma ref, and the average SOC correction coefficient is solved by combining the average SOC correction coefficients, so that the average SOC correction formula is obtained;
The calendar time correction factor Wherein f d,t[T＝TA,σ＝σA is f d,1 data obtained by the cyclic decay experiment when the current temperature t=t A and the current average SOC σ=σ ref;
When the current depth of discharge δ=δ A, Wherein f d,1[δ＝δA,σ＝σA,T＝TA,t＝tp,A is f d,1 data obtained through the cyclic attenuation experiment when the current depth of discharge δ=δ A, the current average SOC σ=σ ref, the current temperature t=t A, and the current calendar time t=t p,A, and then the depth of discharge correction coefficient k δ,e1、kδ,e2 is solved in combination with the depth of discharge correction, thereby obtaining the depth of discharge correction formula.
In the second step, the corrected f d,1＝[Sδ(δ)+St(t)]Sσ(σ)ST (T).
And thirdly, counting the use data of the battery to be estimated according to a rain flow counting method.
Due to the application of the technical scheme, the invention has the advantages of strong expansibility, high precision and simple calculation, and can be realized only by limited experiments.
Drawings
FIG. 1 is a flow chart of a method for estimating battery health according to the present invention.
Detailed Description
The invention will be further described with reference to examples of embodiments shown in the drawings.
In a first embodiment, as shown in fig. 1, a method for estimating the health of a battery includes the following steps:
Step one, solving an attenuation reference curve of a battery through a cyclic charge-discharge attenuation experiment
And (3) taking N (N is an integer larger than 3) batteries (lithium ion batteries) of the same type, carrying out a cyclic charge-discharge attenuation experiment, fitting an attenuation curve of the battery of the type by using experimental data of the cyclic charge-discharge attenuation experiment as an attenuation reference curve of the battery of the type, wherein the attenuation curve represents the relation between the attenuation percentage P loss of the battery of the type and the cycle number N of the battery of the type, and the attenuation curve comprises three coefficients which are alpha sei、βsei、fd,1 respectively.
1. N (n > 3) batteries with the same type are taken, and a cyclic charge-discharge attenuation experiment is carried out at a standard temperature t 0(t0 which is generally 25 ℃. In the cyclic charge-discharge attenuation experiment process, the cyclic range of the battery SOC is 0% -100%. The number of cycles N of each cell is recorded separately as a percentage of decay P loss corresponding to each cycle.
2. According to the cycle times N of each battery and the attenuation percentage P loss corresponding to each cycle, respectively fitting attenuation curves corresponding to the batteries according to a formula:
3. Alpha sei in the above formula is related to the first effect of the battery and represents the early duty cycle of lithium ions consumed by the battery to form a stable sei film.
4. And according to the cycle times and the attenuation percentages of each type of battery, determining alpha sei、βsei and f d,1 corresponding to each type of battery after fitting to obtain an attenuation curve corresponding to each type of battery, namely obtaining n alpha sei, n beta sei and n f d,1 in total. Averaging n alpha sei, n beta sei and n f d,1 to obtain the batteryAndAnd will be as followsAndAlpha sei、βsei、fd,1 in the attenuation reference curve of the battery of the model is used as the attenuation reference curve of the battery of the model to finally obtain the attenuation curve of the battery of the modelThis was used as a reference curve for attenuation of the battery of this model.
Step two, parameter correction under different conditions
And (3) dividing a plurality of batteries of the model into n z groups, carrying out cyclic attenuation experiments under different temperatures, different average SOCs and different discharge depths, obtaining a temperature correction formula, an average SOCs correction formula, a discharge depth correction formula and a calendar time correction formula corresponding to f d,1 by using experimental data of the cyclic attenuation experiments, correcting f d,1 by using the temperature correction formula, the average SOCs correction formula, the discharge depth correction formula and the calendar time correction formula to obtain a corrected f d,1, and correcting an attenuation reference curve of the battery of the model by using the corrected f d,1 to obtain a corrected attenuation curve of the battery of the model.
1. Since f d,1 in the attenuation reference curve of the battery of this model varies depending on the temperature, SOC, and depth of discharge, it is necessary to correct the attenuation reference curve for different conditions.
2. And (3) taking a plurality of batteries of the model, dividing the batteries into n z groups, and carrying out cyclic attenuation experiments on the batteries at different temperatures, different average SOCs and different depths of discharge by adopting a controlled variable method, namely at least taking different temperatures, 2 different average SOCs and 4 different depths of discharge during the experiment.
3. Corrected f d,1＝[Sδ(δ)+St(t)]Sσ(σ)ST (T).
4. In the above formula, S δ (δ) is a depth of discharge correction type, S t (T) is a calendar time correction type, S σ (σ) is an average SOC correction type, and S T (T) is a temperature correction type.
5. In the case of the temperature correction type,Where k T is a temperature correction coefficient, T is the current temperature, T ref is a reference temperature, when the current temperature t=t A,Wherein f d,t[T＝TA is f d,1 data obtained through a cyclic attenuation experiment when the current temperature T=T A, f d,t[T＝Tref is f d,1 data obtained through the cyclic attenuation experiment when the current temperature T=T ref, and then the temperature correction coefficient k T is solved by combining the temperature correction, so that a temperature correction type is obtained. Reference temperature T ref in this equation, if the temperature of the reference curve is the reference temperature, T ref＝t0.
6. In the case of the average SOC correction type,Where k σ is an average SOC correction coefficient, σ is a current average SOC, σ ref is a reference average SOC, when the current average SOC σ=σ A,Wherein, f d,t[σ＝σA is f d,1 data obtained by a cyclic attenuation experiment when the current average SOC σ=σ A, and f d,t[σ＝σref is f d,1 data obtained by a cyclic attenuation experiment when the current average SOC σ=σ ref, then the average SOC correction coefficient is solved in combination with the average SOC correction formula, and the average SOC correction formula is obtained. If the average SOC of the reference curve is taken as a reference, the average SOC σ ref＝avg(SOCcycle is referred to).
7. For the calendar time correction type, S t(t)＝kt t, wherein k t is a calendar time correction coefficient, t is the current calendar time, and the calendar time correction coefficientWherein f d,t[T＝TA,σ＝σA is f d,1 data obtained by a cyclic decay experiment when the current temperature t=t A and the current average SOC σ=σ ref. From this, a calendar time correction coefficient k t is calculated.
8. For depth of discharge correction, S δ(δ)＝kδ,e1δexp(kδ,e2 delta), where k δ,e1、kδ,e2 is the depth of discharge correction factor, delta is the current depth of discharge, when the current depth of discharge delta = delta A,Wherein f d,1[δ＝δA,σ＝σA,T＝TA,t＝tp,A is f d,1 data obtained through a cyclic attenuation experiment when the current depth of discharge δ=δ A, the current average SOC σ=σ ref, the current temperature t=t A, and the current calendar time t=t p,A, and then the depth of discharge correction factor k δ,e1、kδ,e2 is solved in combination with the depth of discharge correction formula, thereby obtaining the depth of discharge correction formula.
Step three, estimating the actual battery
When the health degree of the battery to be estimated, which belongs to the type battery, is estimated, the use data of the battery to be estimated, including the cycle times, the average temperature, the discharge depth, the average SOC and the like in the use of the battery, are counted according to a rain flow counting method, and the use data of the battery to be estimated and the corrected attenuation curve of the type battery are utilized to estimate the attenuation of each cycle of the battery to be estimated, so that the service life and the health degree of the battery to be estimated are estimated.
The advantages of the above scheme are:
1. the expansibility is strong, and the batteries of the same model can be used universally only by carrying out limited experiments;
2. Considering and being compatible with different conditions, the device is used in different environments;
3. The precision is high;
4. The electrochemical characteristics of the battery are fused;
5. the concept of cumulative damage is incorporated.
Compared with the existing machine learning model method, the scheme only needs limited experiments, can be suitable for other batteries of the same model, is high in accuracy, free of up-and-down fluctuation and insensitive to sensor accuracy, does not need an equivalent circuit diagram and parameter identification, and reduces algorithm complexity.
The above embodiments are provided to illustrate the technical concept and features of the present invention and are intended to enable those skilled in the art to understand the content of the present invention and implement the same, and are not intended to limit the scope of the present invention. All equivalent changes or modifications made in accordance with the spirit of the present invention should be construed to be included in the scope of the present invention.

Claims (7)

1.一种预估电池健康度的方法，其特征在于：所述预估电池健康度的方法包括以下步骤：1. A method for estimating battery health, characterized in that: the method for estimating battery health comprises the following steps: 步骤一：取n个同型号电池进行循环充放电衰减实验，n为大于3的整数，利用所述循环充放电衰减实验的实验数据拟合该型号电池的衰减曲线作为该型号电池的衰减基准曲线，所述衰减曲线表征该型号电池的衰减百分比Ploss与该型号电池的循环次数N的关系，所述衰减曲线中包含三个系数，分别为αsei、βsei、fd,1；Step 1: Take n batteries of the same model to 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. The attenuation curve represents the relationship between the attenuation percentage P loss of the battery of this model and the number of cycles N of the battery of this model. The attenuation curve contains three coefficients, namely α sei , β sei , and f d,1 ; 步骤二：取若干个该型号电池进行不同温度、不同平均SOC、不同放电深度下的循环衰减实验，利用所述循环衰减实验的实验数据求取所述fd,1对应的温度修正式、平均SOC修正式、放电深度修正式和日历时间修正式，再利用所述温度修正式、所述平均SOC修正式、所述放电深度修正式和所述日历时间修正式对所述fd,1进行修正得到修正后的fd,1，进而利用所述修正后的fd,1修正该型号电池的衰减基准曲线得到该型号电池的修正后衰减曲线；Step 2: taking a number of batteries of the same model and conducting cycle decay experiments at different temperatures, different average SOCs, and different discharge depths, using the experimental data of the cycle decay experiments to obtain the temperature correction form, average SOC correction form, discharge depth correction form, and calendar time correction form corresponding to the f d,1 , then using the temperature correction form, the average SOC correction form, the discharge depth correction form, and the calendar time correction form to correct the f d,1 to obtain a corrected f d,1 , and then using the corrected f d,1 to correct the decay reference curve of the battery of the same model to obtain a corrected decay curve of the battery of the same model; 步骤三：当对属于该型号电池的待预估电池进行健康度预估时，利用所述待预估电池的使用数据和所述该型号电池的修正后衰减曲线预估所述待预估电池每个循环的衰减量，从而预估所述待预估电池的寿命和健康度；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; 所述步骤一中，所述衰减曲线的表达式为 In the step 1, the expression of the attenuation curve is: 所述步骤二中，所述温度修正式为其中，kT为温度修正系数，T为当前温度，Tref为参考温度；In step 2, the temperature correction formula is: Where, kT is the temperature correction coefficient, T is the current temperature, and Tref is the reference temperature; 所述平均SOC修正式为其中，kσ为平均SOC修正系数，σ为当前平均SOC，σref为参考平均SOC；The average SOC correction formula is Wherein, k σ is the average SOC correction coefficient, σ is the current average SOC, and σ ref is the reference average SOC; 所述日历时间修正式为St(t)＝ktt，其中，kt为日历时间修正系数，t为当前日历时间；The calendar time correction formula is St(t)=ktt, where kt is the calendar time correction coefficient and t is the current calendar time; 所述放电深度修正式为Sδ(δ)＝kδ,e1δexp(kδ,e2δ)，其中，kδ,e1、kδ,e2均为放电深度修正系数，δ为当前放电深度。The discharge depth correction formula is S δ (δ) = k δ,e1 δexp(k δ,e2 δ), wherein k δ,e1 and k δ,e2 are both discharge depth correction coefficients, and δ is the current discharge depth. 2.根据权利要求1所述的预估电池健康度的方法，其特征在于：所述步骤一中，在标准温度t0下进行所述循环充放电衰减实验。2. The method for estimating battery health according to claim 1, characterized in that: in the step 1, the cyclic charge and discharge attenuation experiment is performed at a standard temperature t 0 . 3.根据权利要求1所述的预估电池健康度的方法，其特征在于：所述步骤一中，根据每个该型号电池的循环次数和衰减百分比，拟合得到每个该型号电池对应的衰减曲线，从而确定每个该型号电池对应的αsei、βsei和fd,1，进而得到该型号电池的和并以和作为所述该型号电池的衰减基准曲线中的αsei、βsei、fd,1。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 attenuation percentage of each battery of the model, the attenuation curve corresponding to each battery of the model is fitted, so as to determine α sei , β sei and f d,1 corresponding to each battery of the model, and then obtain the battery of the model and And and α sei , β sei , and f d,1 in the attenuation reference curve of the battery of this model. 4.根据权利要求1所述的预估电池健康度的方法，其特征在于：所述步骤二中，进行所述循环衰减实验时至少取2个不同温度、2个不同平均SOC、4个不同放电深度。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 performing the cycle decay experiment. 5.根据权利要求1所述的预估电池健康度的方法，其特征在于：所述步骤二中，当所述当前温度T＝TA时，其中fd,t[T＝TA]为当前温度T＝TA时通过所述循环衰减实验得到的fd,1数据，fd,t[T＝Tref]为当前温度T＝Tref时通过所述循环衰减实验得到的fd,1数据，则结合所述温度修正式求解所述温度修正系数kT，进而得到所述温度修正式；5. The method for estimating battery health according to claim 1, wherein: in step 2, when the current temperature T= TA , Wherein f d,t [T＝ TA ] is the f d ,1 data obtained through the cyclic decay experiment when the current temperature T＝TA, and f d,t [T＝T ref ] is the f d , 1 data obtained through the cyclic decay experiment when the current temperature T＝T ref , then the temperature correction coefficient k T is solved in combination with the temperature correction formula to obtain the temperature correction formula; 当所述当前平均SOCσ＝σA时，其中，fd,t[σ＝σA]为当前平均SOCσ＝σA时通过所述循环衰减实验得到的fd,1数据，fd,t[σ＝σref]为当前平均SOCσ＝σref时通过所述循环衰减实验得到的fd,1数据，则结合所述平均SOC修正式求解所述平均SOC修正系数，进而得到所述平均SOC修正式；When the current average SOCσ＝ σA , Wherein, f d,t [σ＝σ A ] is the f d,1 data obtained through the cyclic decay experiment when the current average SOC σ＝σ A , and f d,t [σ＝σ ref ] is the f d,1 data obtained through the cyclic decay experiment when the current average SOC σ＝σ ref , then the average SOC correction coefficient is solved in combination with the average SOC correction formula to obtain the average SOC correction formula; 所述日历时间修正系数其中，fd,t[T＝TA,σ＝σA]为当前温度T＝TA、当前平均SOCσ＝σref时通过所述循环衰减实验得到的fd,1数据；The calendar time correction factor Wherein, f d,t [T＝ TA ,σ＝ σA ] is the f d,1 data obtained through the cyclic decay experiment when the current temperature T＝ TA and the current average SOCσ＝ σref ; 当所述当前放电深度δ＝δA时，其中，fd,1[δ＝δA,σ＝σA,T＝TA,t＝tp,A]为当前放电深度δ＝δA、当前平均SOCσ＝σref、当前温度T＝TA、当前日历时间t＝tp,A时通过所述循环衰减实验得到的fd,1数据，则结合所述放电深度修正式求解所述放电深度修正系数kδ,e1、kδ,e2，进而得到所述放电深度修正式。When the current discharge depth δ = δ A , Among them, f d,1 [δ＝δ A ,σ＝σ A ,T＝ TA ,t＝t p,A ] is the f d,1 data obtained through the cycle decay experiment when the current discharge depth δ＝δ A , the current average SOCσ＝σ ref , the current temperature T＝ TA , and the current calendar time t＝t p,A . The discharge depth correction coefficients k δ,e1 and k δ,e2 are solved in combination with the discharge depth correction formula to obtain the discharge depth correction formula. 6.根据权利要求5所述的预估电池健康度的方法，其特征在于：所述步骤二中，所述修正后的fd,1＝[Sδ(δ)+St(t)]Sσ(σ)ST(T)。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.根据权利要求1所述的预估电池健康度的方法，其特征在于：所述步骤三中，根据雨流计数法统计出所述待预估电池的使用数据。7. The method for estimating battery health according to claim 1, characterized in that: in the step 3, the usage data of the battery to be estimated is counted according to the rain flow counting method.
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