JP-7855206-B1 - Method for determining the degree of degradation of a secondary battery, device for determining the degree of degradation of a secondary battery, and program

JP7855206B1JP 7855206 B1JP7855206 B1JP 7855206B1JP-7855206-B1

Abstract

[Problem] To quickly determine the degradation of a secondary battery. [Solution] The system includes means for obtaining an approximation formula by approximating a voltage curve, which is either a charging curve or a discharge curve, or either a charging curve or a discharge curve, that shows the voltage v(t) across the secondary battery as a function of time t, measured during either charging or discharging of the secondary battery, or a current curve, which is either a charging curve or a discharge curve, or either a charging curve or a discharge curve, or either a charging curve or a discharge curve, or either a current I(t) across the secondary battery as a function of time t, measured during either charging or discharging of the secondary battery, and means for estimating the degree of degradation of the secondary battery from the approximation formula. [Selection Diagram] Figure 1

Inventors

高木淳
成井隆

Assignees

プロスペクティブ・テクノロジーズ株式会社

Dates

Publication Date: 20260508
Application Date: 20251205

Claims (20)

An approximation formula acquisition step involves approximating a voltage curve, which is either a charging curve or a discharge curve, or both, that shows the voltage v(t) across the terminals of the secondary battery as a function of time t, measured during either the charging or discharging of the secondary battery, or both, to obtain an approximation formula. The system includes a degradation degree estimation step for estimating the degree of degradation of the secondary battery from the aforementioned approximation formula , The aforementioned step of estimating the degree of deterioration is: A method for determining the degree of degradation of a secondary battery , which involves applying the coefficients of the aforementioned approximation formula to a model obtained by multivariate analysis or machine learning to estimate the full charge capacity .
The model acquisition step is provided before the aforementioned approximation formula acquisition step. The model acquisition step includes a model acquisition approximation formula acquisition step, which approximates a voltage curve that is either a charging curve or a discharge curve, or both, that shows the voltage v(t) across the secondary battery as a function of time t, measured during either charging or discharging of the secondary battery, and acquires an approximation formula for model acquisition. A method for determining the degree of degradation of a secondary battery according to claim 1 , comprising a model generation step of generating the model by performing machine learning or multiple regression analysis with the coefficients of the aforementioned approximation formula for acquiring the model as explanatory variables and the measured full charge capacity as the dependent variable.
A method for determining the degree of degradation of a secondary battery according to claim 1, wherein, in order to obtain the voltage v(t) across the terminals of the secondary battery with respect to time t, a regression curve is obtained for an interval including time t, and the v(t) is obtained from the regression curve.
An approximation formula acquisition step involves approximating the current curve, which is either a charging curve or a discharge curve, or both, that show the current I(t) flowing through the secondary battery as a function of time t, measured during either the charging or discharging of the secondary battery, and obtaining an approximation formula. The system includes a degradation degree estimation step for estimating the degree of degradation of the secondary battery from the aforementioned approximation formula , The aforementioned step of estimating the degree of deterioration is: A method for determining the degree of degradation of a secondary battery , which involves applying the coefficients of the aforementioned approximation formula to a model obtained by multivariate analysis or machine learning to estimate the full charge capacity .
After the aforementioned approximation formula acquisition step, The steps include taking the difference between the measured charging curve or the discharge curve and the approximation formula, The steps include determining whether the difference is discontinuous at each sampling period Δt of the measured charging curve or the discharging curve, The correction step includes the step of, if the discontinuity does not occur after a predetermined time interval Δt' from the time the discontinuity occurred, deleting the data for the time after the predetermined time interval Δt' from the time the discontinuity occurred, and shifting the data for the time after the deleted data by the predetermined time interval Δt'. A method for determining the degree of degradation of a secondary battery according to any one of claims 1 to 4 , wherein the approximate formula acquisition step is performed again after the correction step.
Before the step of obtaining the approximation formula, A method for determining the degree of degradation of a secondary battery according to any one of claims 1 to 4, further comprising the step of performing a time-series analysis on the measured charging curve or the discharge curve to remove systematic errors.
An approximation formula acquisition means for approximating a voltage curve, which is either a charging curve or a discharge curve, or both, that shows the voltage v(t) across the terminals of a secondary battery as a function of time t, measured during either the charging or discharging of the secondary battery, or both, and obtaining an approximation formula. The system includes a degradation degree estimation means for estimating the degree of degradation of the secondary battery from the aforementioned approximation formula , The aforementioned degradation degree estimation means is A secondary battery degradation determination device that estimates the full charge capacity by applying the coefficients of the aforementioned approximation formula to a model obtained by multivariate analysis or machine learning .
moreover, Equipped with a model acquisition means, The aforementioned model acquisition means is A means for obtaining an approximate formula for model acquisition, which approximates a voltage curve that is either a charging curve or a discharge curve, or both, showing the measured voltage v(t) across the terminals of a secondary battery as a function of time t, and obtains an approximate formula for model acquisition. The secondary battery degradation degree determination device according to claim 7 , further comprising a model generation means that generates the model by performing machine learning or multiple regression analysis with the coefficients of the model acquisition approximation formula as explanatory variables and the measured full charge capacity as the objective variable.
The secondary battery degradation determination device according to claim 7, wherein, in order to obtain the voltage v(t) across the terminals of the secondary battery with respect to time t, a regression curve is obtained for an interval including time t, and the v(t) is obtained from the regression curve.
An approximation formula acquisition means for approximating a current curve, which is either a charging curve or a discharge curve, or both, that shows the current I(t) flowing through a secondary battery as a function of time t, measured during either the charging or discharging of a secondary battery, or both, and obtaining an approximation formula, The system includes a degradation degree estimation means for estimating the degree of degradation of the secondary battery from the aforementioned approximation formula , The aforementioned degradation degree estimation means is A secondary battery degradation determination device that estimates the full charge capacity by applying the coefficients of the aforementioned approximation formula to a model obtained by multivariate analysis or machine learning .
moreover, A means for taking the difference between the measured charging curve or the discharge curve and the approximation formula, Means for determining whether the difference is discontinuous at each sampling period Δt of the measured charging curve or the discharging curve, A secondary battery degradation determination device according to any one of claims 7 to 10, further comprising a correction means that, if the data does not become discontinuous after a predetermined time interval Δt' from the time of discontinuity, deletes the data for the time after the predetermined time interval Δt' from the time of discontinuity, and shifts the data for the time later than the time of the deleted data by the predetermined time interval Δt' .
moreover, A secondary battery degradation determination device according to any one of claims 7 to 10, comprising means for performing time-series analysis on the measured charging curve or the discharge curve and removing systematic errors.
A means for obtaining an approximation formula by approximating a voltage curve, which is either a charging curve or a discharge curve, or both, that shows the voltage v(t) across the terminals of a secondary battery as a function of time t, measured by a computer during either the charging or discharging of the secondary battery or both, and obtaining an approximation formula. This is used as a degradation degree estimation means to estimate the degree of degradation of the secondary battery from the aforementioned approximation formula . The aforementioned degradation degree estimation means is A program that estimates the full charge capacity by applying the coefficients of the aforementioned approximation formula to a model obtained by multivariate analysis or machine learning .
Furthermore, the computer is used as a means of acquiring models. The aforementioned model acquisition means is A means for obtaining an approximate formula for model acquisition, which approximates a voltage curve that is either a charging curve or a discharge curve, or both, showing the measured voltage v(t) across the terminals of a secondary battery as a function of time t, and obtains an approximate formula for model acquisition. The program according to claim 13, further comprising: a model generation means for generating the model by performing machine learning or multiple regression analysis with the coefficients of the aforementioned model acquisition approximation formula as explanatory variables and the measured full charge capacity as the objective variable.
The program according to claim 13, which obtains the voltage v(t) across the terminals of a secondary battery with respect to time t by obtaining a regression curve for an interval including time t, and obtaining v(t) from the regression curve.
An approximation formula acquisition means that approximates a current curve, which is either a charging curve or a discharge curve, or both, that shows the current I(t) flowing through a secondary battery as a function of time t, measured by a computer during either the charging or discharging of the secondary battery, or both, and obtains an approximation formula, and This is used as a degradation degree estimation means to estimate the degree of degradation of the secondary battery from the aforementioned approximation formula . The aforementioned degradation degree estimation means is A program that estimates the full charge capacity by applying the coefficients of the aforementioned approximation formula to a model obtained by multivariate analysis or machine learning .
Computers, further, A means for taking the difference between the measured charging curve or the discharge curve and the approximation formula, Means for determining whether the difference is discontinuous at each sampling period Δt of the measured charging curve or the discharging curve, The program according to any one of claims 13 to 16, wherein if the data does not become discontinuous after a predetermined time interval Δt' from the time of discontinuity, the program has a means for deleting data from the time of discontinuity after the predetermined time interval Δt', and for shifting data from a time later than the time of the deleted data by the predetermined time interval Δt' .
Computers, further, The program according to any one of claims 13 to 16 , which performs time-series analysis on the measured charging curve or the discharge curve and functions as a means to remove systematic errors.
An approximation formula acquisition step involves approximating a voltage curve, which is either a charging curve or a discharge curve, or both, that shows the voltage v(t) across the terminals of the secondary battery as a function of time t, measured during either the charging or discharging of the secondary battery, and obtaining two or more approximation formulas. The system includes a degradation degree estimation step of estimating the degree of degradation of the secondary battery from two or more of the aforementioned approximation formulas, The aforementioned step of estimating the degree of deterioration is: The coefficients of two or more of the aforementioned approximation formulas are applied to a model obtained by multivariate analysis or machine learning to estimate the full charge capacity. Furthermore, the model acquisition step is provided before the approximation formula acquisition step. The model acquisition step includes a model acquisition approximation formula acquisition step, which approximates a voltage curve that is either a charging curve or a discharge curve, or both, that shows the voltage v(t) across the secondary battery as a function of time t, measured during either charging or discharging of the secondary battery, to obtain two or more model acquisition approximation formulas, A method for determining the degree of degradation of a secondary battery, comprising: a model generation step of generating the model by performing machine learning or multiple regression analysis using the coefficients of two or more of the aforementioned approximation formulas for acquiring the model as explanatory variables and the measured full charge capacity as the dependent variable.
An approximation formula acquisition means for obtaining two or more approximation formulas by approximating the voltage curve, which is either a charging curve or a discharge curve, or both, that shows the voltage v(t) across the terminals of a secondary battery as a function of time t, measured during either the charging or discharging of the secondary battery, and the voltage curve, which is either a charging curve or a discharge curve, or both. The system includes a degradation degree estimation means for estimating the degree of degradation of the secondary battery from two or more of the aforementioned approximation formulas, The aforementioned degradation degree estimation means is The coefficients of two or more of the aforementioned approximation formulas are applied to a model obtained by multivariate analysis or machine learning to estimate the full charge capacity. moreover, Equipped with a model acquisition means, The aforementioned model acquisition means is A means for obtaining an approximate formula for model acquisition, which approximates a voltage curve that is either a charging curve or a discharge curve, or both, showing the measured voltage v(t) across the terminals of a secondary battery as a function of time t, and obtains two or more approximate formulas for model acquisition. A secondary battery degradation determination device comprising a model generation means for generating the model by performing machine learning or multiple regression analysis using the coefficients of two or more of the aforementioned model acquisition approximation formulas as explanatory variables and the measured full charge capacity as the dependent variable.

Description

This invention relates to a method for determining the degree of degradation of a secondary battery, a secondary battery degradation determination device, and a program for determining the degree of degradation of a secondary battery. The rapid electrification of vehicles in recent years has led to an increase in demand for rechargeable batteries for vehicles. Along with this increase in demand for rechargeable batteries, the need for their reuse is also growing. When a vehicle is scrapped, the secondary battery is removed and its degradation is assessed. If the assessment determines that the secondary battery is reusable, it is rebuilt and reused in the second-hand market. One technique for determining the degradation of secondary batteries involves estimating the degree of degradation from the voltage values or the nth-order derivatives of either the charging voltage when a constant current is applied to the secondary battery, or the discharge voltage when the power supply is disconnected from the secondary battery (see, for example, Patent Document 1). Patent No. 7528148 This is a schematic diagram illustrating a secondary battery degradation level determination system.This is a schematic diagram to explain electrical discharge.Figure (1) shows the relationship between the measured Q value and the estimated Q value.Figure (2) shows the relationship between the measured Q value and the estimated Q value.This figure shows the test results for the selected explanatory variables.This shows a histogram of the error obtained by subtracting the estimated Q value from the measured Q value.This figure shows the results of the model's validation.This figure shows an example of a voltage curve when using a standard device.This figure shows another example of a voltage curve when using a standard device.This is the measured voltage curve (1).This is the measured voltage curve (2).This figure shows the difference between the measured voltage curve and the approximation formula.This is a schematic diagram showing the relationship between the charging curve among the measured voltage curves and the approximate curve obtained by approximating this charging thymus.This is a schematic diagram illustrating the correction steps.This is a schematic diagram illustrating another example of a secondary battery degradation degree determination system.This is a schematic diagram illustrating the parallel measurement of multiple secondary batteries.These are the calculated noise levels for each secondary battery.This is 3σ calculated from the noise waveform of each secondary battery.This shows a histogram of the errors in the secondary battery.This shows the 3σ histogram of the error of a secondary battery. The embodiments of this invention will be described below with reference to the figures, but the shapes, sizes, and arrangements of each component are only shown in a general manner to the extent that the invention can be understood. Furthermore, preferred configuration examples of this invention will be described below, but the numerical conditions and other details are merely examples. Therefore, this invention is not limited to the following embodiments, and many modifications or alterations can be made to achieve the effects of this invention without departing from the scope of its configuration. This section primarily describes the process of determining the degradation level of secondary batteries used in electric vehicles or hybrid vehicles. However, this invention is not limited to secondary batteries for vehicles and can be applied to determining the degradation level of various types of reusable secondary batteries. Traditionally, when a vehicle is scrapped, the secondary battery is removed and sent to a remanufacturing company. At the remanufacturing company, the battery's degradation level is assessed. If the assessment determines that the battery is reusable, it is remanufactured and used in the used vehicle market. A secondary battery degradation assessment system is used, for example, in such a remanufacturing company. The degree of degradation of a rechargeable battery is usually expressed as the ratio Q1/Q0 × 100 (%) of the full charge capacity Q0 (Ah) of a new rechargeable battery to the full charge capacity Q1 (Ah) of a used rechargeable battery, or as the full charge capacity Q1 (Ah) of the used battery. Here, the full charge capacity Q0 (Ah) of a new rechargeable battery and the full charge capacity Q1 (Ah) of a used rechargeable battery may simply be expressed as the full charge capacity Q (Ah). Here, the full charge capacity Q (Ah) is given by Q = It (Ah) after fully charging the battery, discharging it with a constant current I (A), and measuring the time t (h) until it is completely discharged. This measurement method is called precision measurement. Precise measurements allow for the accurate determination of the full charge capacity Q (Ah). However, precise measurements have the drawback of being time