CN112067999A - Nondestructive acquisition system and method for open circuit potential curve of lithium ion battery anode - Google Patents

Nondestructive acquisition system and method for open circuit potential curve of lithium ion battery anode Download PDF

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CN112067999A
CN112067999A CN202010986401.4A CN202010986401A CN112067999A CN 112067999 A CN112067999 A CN 112067999A CN 202010986401 A CN202010986401 A CN 202010986401A CN 112067999 A CN112067999 A CN 112067999A
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curve
open
fitting
electrode potential
potential curve
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CN112067999B (en
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吕超
宋彦孔
王立欣
朱世怀
韩依彤
闫圣来
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Harbin Institute of Technology
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/367Software therefor, e.g. for battery testing using modelling or look-up tables
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/10Energy storage using batteries

Abstract

A system and a method for non-destructively acquiring an open circuit potential curve of a lithium ion battery anode relate to the field of lithium ion battery modeling and management application. The method comprises the steps of firstly adjusting the initial voltage value of a negative electrode potential curve of the lithium ion battery to obtain an adjusted negative electrode potential curve, superposing the adjusted negative electrode potential curve and an open-circuit voltage curve to obtain an adjusted positive electrode potential curve, then adopting a polynomial function, a 1-order Fourier function and a 1-order Gaussian function in sequence to continuously reduce errors, and repeatedly using the 1-order Gaussian function to reduce the errors until the maximum error value in the obtained error curve is smaller than a preset value, and considering that the finally obtained Gaussian function correction fitting curve is the real positive electrode potential curve of the lithium ion battery. The method is used for acquiring the open circuit potential curve of the anode of the lithium ion battery.

Description

Nondestructive acquisition system and method for open circuit potential curve of lithium ion battery anode
Technical Field
The invention relates to a system and a method for acquiring a battery anode open-circuit potential curve. Belonging to the field of modeling and management application of lithium ion batteries.
Background
The lithium ion battery is widely applied to energy storage units of new energy automobiles due to the advantages of high voltage, high power density, high energy density, long cycle life and the like.
The continuous development of new energy automobiles puts higher requirements on a battery management system. The electrochemical mechanism model of the lithium ion battery can represent the internal characteristics of the battery, and more accurate estimation of the battery performance state is realized.
When performing electrochemical modeling on a lithium ion battery, electrode potential curves of positive and negative electrode materials of the battery are required. The electrode potential curve of the battery refers to the potential change curve of an electrode material caused by the change of the dissolution degree and the ion adsorption degree of the electrode surface when the electrode is in contact with electrolyte with different concentrations. The acquisition of the electrode potential curve is particularly important for the simulation calculation of the electrochemical model.
Currently, lithium ion battery manufacturers generally do not provide electrode potential profiles for power cells due to commercial privacy and the like. The negative electrode material of the lithium ion battery is generally graphite, which can be found according to corresponding literature, while the positive electrode material has many systems, such as lithium cobaltate, lithium iron phosphate, lithium titanate and ternary systems. The positive electrode potential forms of different systems are different, and even the positive electrode potential curves are different for different battery material structures and different material proportions of the same system.
Laboratory testing of the potential curve of the positive electrode material requires disassembly of the battery and a series of tests, the whole testing process is complex and time-consuming.
Disclosure of Invention
The invention aims to solve the problem that the open-circuit potential curve of the anode of the lithium ion battery can be obtained only by disassembling the battery and performing a series of complex tests. A system and a method for non-destructively acquiring an open circuit potential curve of a lithium ion battery anode are provided.
A non-destructive acquisition method for an open circuit potential curve of a lithium ion battery anode comprises the following steps:
step S1, adjusting the initial voltage value of the negative electrode potential curve of the lithium ion battery to obtain an adjusted negative electrode potential curve, and overlapping the adjusted negative electrode potential curve and the open-circuit voltage curve to obtain an adjusted positive electrode potential curve, wherein the adjusted positive electrode potential curve has no rising stage;
step S2, fitting the adjusted positive electrode potential curve by adopting a polynomial function to obtain a polynomial fitting curve, and subtracting the polynomial fitting curve from the adjusted positive electrode potential curve to obtain an initial error curve;
s3, fitting the initial error curve by adopting a 1-order Fourier function to obtain a Fourier function fitting curve, overlapping the Fourier function fitting curve and a polynomial fitting curve to obtain a Fourier function correction fitting curve, and subtracting the Fourier function correction fitting curve from the adjusted positive potential curve to obtain a new error curve;
step S4, correcting the maximum peak value on the new error curve by adopting a 1 st order Gaussian function to obtain a Gaussian function fitting curve, superposing the Gaussian function fitting curve and a Fourier function correction fitting curve to obtain a Gaussian function correction fitting curve, and subtracting the Gaussian function correction fitting curve and the adjusted positive electrode potential curve to obtain another new error curve;
and S5, repeatedly executing the step S4 until the maximum error value in the error curve obtained in the step S4 is smaller than a preset value, and taking the obtained Gaussian function correction fitting curve as the anode open-circuit potential curve of the lithium ion battery.
Preferably, the negative electrode potential curve and the open-circuit voltage curve are superimposed to obtain a positive electrode potential curve of the lithium ion battery, and the specific process is as follows:
taking data points with the same number as an open-circuit voltage curve from a position of a lithium intercalation concentration fraction of the battery cathode corresponding to the determined initial cathode potential to a region of the lithium intercalation concentration fraction of the battery cathode being 1;
adding the negative electrode potential corresponding to the initial battery negative electrode lithium intercalation concentration fraction in the negative electrode potential curve to the open circuit voltage when the charge state is 0 in the open circuit voltage curve, adding the negative electrode potential when the battery negative electrode lithium intercalation concentration fraction is 1 to the open circuit voltage when the charge state is 1, adding the negative electrode potential curve and the remaining data points of the open circuit voltage curve in a one-to-one correspondence manner, and obtaining the curve after the addition, which is the positive electrode potential curve of the lithium ion battery.
Preferably, in step S2, the polynomial function is a 6 th order polynomial function.
Preferably, in step S3, the 1 st order fourier function is expressed as:
y=a0+a1·cos(x·w)+b1·sin(x·w)
in the formula, a0、a1、w、b1The parameters are to-be-fitted parameters, x represents the embedded lithium concentration fraction of the battery anode, and y represents the open-circuit potential error of the battery anode.
Preferably, the order 1 gaussian function is expressed as:
y=a·exp((x-b)/c)
in the formula, a, b and c are parameters to be fitted, x represents the lithium insertion concentration fraction of the battery anode, y represents the open-circuit potential error of the battery anode, and exp represents an e index.
A non-destructive acquisition system for an open-circuit potential curve of a positive electrode of a lithium ion battery comprises a negative electrode potential curve adjusting module, a polynomial fitting module, an overall correcting module, a local correcting module and a positive electrode open-circuit potential curve acquisition module,
the negative electrode potential curve adjusting module is used for adjusting the initial voltage value of a negative electrode potential curve of the lithium ion battery to obtain an adjusted negative electrode potential curve, and superposing the adjusted negative electrode potential curve and an open-circuit voltage curve to obtain an adjusted positive electrode potential curve, wherein the adjusted positive electrode potential curve has no rising stage;
the polynomial fitting module is connected with the negative potential curve adjusting module and used for fitting the adjusted positive potential curve by adopting a polynomial function to obtain a polynomial fitting curve, and subtracting the polynomial fitting curve from the adjusted positive potential curve to obtain an initial error curve;
the integral correction module is connected with the polynomial fitting module and used for fitting the initial error curve by adopting a 1-order Fourier function to obtain a Fourier function fitting curve, superposing the Fourier function fitting curve and the polynomial fitting curve to obtain a Fourier function correction fitting curve, and subtracting the Fourier function correction fitting curve from the adjusted positive electrode potential curve to obtain a new error curve;
the local correction module is connected with the overall correction module and used for correcting the maximum peak value on the new error curve by adopting a 1-order Gaussian function to obtain a Gaussian function fitting curve, superposing the Gaussian function fitting curve and a Fourier function correction fitting curve to obtain a Gaussian function correction fitting curve, and subtracting the Gaussian function correction fitting curve and the adjusted positive electrode potential curve to obtain another new error curve;
and the positive open-circuit potential curve acquisition module is connected with the local correction module and used for continuously updating by using the local correction module to obtain an error curve until the maximum error value in the obtained error curve is smaller than a preset value, and taking the Gaussian function correction fitting curve obtained by the local correction module at the moment as a positive open-circuit potential curve of the lithium ion battery.
Preferably, the cathode potential curve adjusting module comprises a data point selecting unit and a curve superposing unit,
the data point selection unit is used for selecting data points with the same number as the open-circuit voltage curve from the battery cathode lithium intercalation concentration fraction corresponding to the determined initial cathode potential to the interval with the battery cathode lithium intercalation concentration fraction of 1;
and the curve superposition unit is used for adding the negative electrode potential corresponding to the initial battery negative electrode lithium intercalation concentration fraction in the negative electrode potential curve and the open-circuit voltage when the charge state in the open-circuit voltage curve is 0, adding the negative electrode potential when the battery negative electrode lithium intercalation concentration fraction is 1 and the open-circuit voltage when the charge state is 1, adding the negative electrode potential curve and the remaining data points in the open-circuit voltage curve in a one-to-one correspondence manner, and obtaining the added curve as the positive electrode potential curve of the lithium ion battery.
Preferably, the polynomial function is a 6 th order polynomial function.
Preferably, a fourier function of order 1, expressed as:
y=a0+a1·cos(x·w)+b1·sin(x·w)
in the formula, a0、a1、w、b1The parameters are to-be-fitted parameters, x represents the embedded lithium concentration fraction of the battery anode, and y represents the open-circuit potential error of the battery anode.
Preferably, the order 1 gaussian function is expressed as:
y=a·exp((x-b)/c)
in the formula, a, b and c are parameters to be fitted, x represents the lithium insertion concentration fraction of the battery anode, y represents the open-circuit potential error of the battery anode, and exp represents an e index.
The invention has the beneficial effects that:
firstly, adjusting the initial voltage value of the negative electrode potential curve of the lithium ion battery to obtain an adjusted negative electrode potential curve, superposing the adjusted negative electrode potential curve and an open-circuit voltage curve to obtain an adjusted positive electrode potential curve, eliminating the rising stage of the positive electrode potential curve by adjusting the initial voltage value of the negative electrode potential curve, wherein the obtained adjusted positive electrode potential curve is still not a real positive electrode potential curve and has an error with the real positive electrode potential curve, therefore, a polynomial function, a Fourier function of 1 order and a Gaussian function of 1 order are sequentially adopted, the error is continuously reduced, and the 1 st order Gaussian function is repeatedly used to reduce errors until the maximum error value in the obtained error curve is smaller than a preset value, and the finally obtained Gaussian function correction fitting curve is considered to be the real positive electrode potential curve of the lithium ion battery. This application need not to disassemble the positive pole potential curve that just can obtain the battery to the battery. Compared with the existing complex test mode, the method for obtaining the anode potential curve is simple and high in accuracy.
Drawings
FIG. 1 is a schematic diagram of a non-destructive acquisition system for an open circuit potential curve of a positive electrode of a lithium ion battery according to the present invention;
FIG. 2 is a flow chart of a non-destructive acquisition method for an open circuit potential curve of a lithium ion battery anode in accordance with the present invention;
FIG. 3 is a positive electrode potential curve diagram of a lithium ion battery to be adjusted;
FIG. 4 is a graph of actual positive open circuit potential;
FIG. 5 is a diagram of fitting results of fitting the adjusted positive electrode potential curve using a 6 th order polynomial function;
FIG. 6 is a plot of polynomial fit error;
FIG. 7 is a fitting graph of fitting an initial error curve using a Fourier function of order 1;
FIG. 8 is a comparison of a Fourier function modified fit curve and an adjusted positive potential curve;
FIG. 9 is a graph of the maximum peak on a new error curve modified using a 1 st order Gaussian function;
FIG. 10 is a graph comparing another new fitted curve with an adjusted positive potential curve;
FIG. 11 is a graph of a second correction of the maximum peak on another new error curve using a Gaussian function;
FIG. 12 is a comparison of the first Gaussian function modified fit curve with the adjusted positive electrode potential curve;
FIG. 13 is a comparison graph of the resulting Gaussian function modified fit curve and the adjusted positive electrode potential curve;
FIG. 14 is a final error plot;
FIG. 15 is a comparison of a measured voltage curve and a simplified electrochemical model fitting graph.
Detailed Description
The technical solutions in the embodiments of the present invention will be described in detail below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of real-time embodiments of the invention, and not all embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
The invention is further described with reference to the following figures and specific examples.
Example 1:
the invention provides a nondestructive acquisition method of an open circuit potential curve of a lithium ion battery anode, as shown in figure 2, the method comprises the following steps:
step S1, adjusting the initial voltage value of the negative electrode potential curve of the lithium ion battery to obtain an adjusted negative electrode potential curve, and overlapping the adjusted negative electrode potential curve and the open-circuit voltage curve to obtain an adjusted positive electrode potential curve, wherein the adjusted positive electrode potential curve has no rising stage;
step S2, fitting the adjusted positive electrode potential curve by adopting a polynomial function to obtain a polynomial fitting curve, and subtracting the polynomial fitting curve from the adjusted positive electrode potential curve to obtain an initial error curve;
s3, fitting the initial error curve by adopting a 1-order Fourier function to obtain a Fourier function fitting curve, overlapping the Fourier function fitting curve and a polynomial fitting curve to obtain a Fourier function correction fitting curve, and subtracting the Fourier function correction fitting curve from the adjusted positive potential curve to obtain a new error curve;
step S4, correcting the maximum peak value on the new error curve by adopting a 1 st order Gaussian function to obtain a Gaussian function fitting curve, superposing the Gaussian function fitting curve and a Fourier function correction fitting curve to obtain a Gaussian function correction fitting curve, and subtracting the Gaussian function correction fitting curve and the adjusted positive electrode potential curve to obtain another new error curve;
and S5, repeatedly executing the step S4 until the maximum error value in the error curve obtained in the step S4 is smaller than a preset value, and taking the obtained Gaussian function correction fitting curve as the anode open-circuit potential curve of the lithium ion battery.
Specifically, the difference between the gaussian function correction fitting curve and the adjusted positive electrode potential curve refers to that the difference is made between different vertical coordinates corresponding to the same horizontal coordinate.
For cost, the positive electrode capacity of the power lithium ion battery is assumed to be the battery capacity. The negative electrode capacity exceeds the positive electrode capacity when the battery is designed. And adding the negative electrode potential curve and the open-circuit voltage curve of the battery to obtain an adjusted positive electrode potential curve.
Explanation of step S1: the adjusted positive potential curve resulting from the superposition of the negative potential curve and the open-circuit voltage curve may have a potential rise at the end, as shown in fig. 3, when the initial negative potential is 0.7096V. This is not consistent with the actual positive potential curve, and the shape of the positive potential curve is changed through adjusting the initial voltage value of the negative potential curve. And continuously reducing the initial voltage of the negative electrode potential curve to eliminate the rising stage of the positive electrode potential curve. Whether the anode potential curve has a rising stage or not is checked through a corresponding program, the actual anode potential curve of the ternary 50Ah lithium ion battery obtained by the method is shown in FIG. 4, and the initial anode potential is 0.4901V at the moment.
If the application of the anode potential curve in an electrochemical model is to be realized, a mathematical expression of the potential curve must be accurately fitted. A common fitting method is polynomial fitting, and fig. 5 and 6 show the fitting result and error curve of the 6 th order polynomial function to the adjusted positive electrode potential curve. It can be seen from the error curve that the fitting effect of the multi-form function on the adjusted positive electrode potential curve is poor, and the simulation application in the electrochemical model is difficult.
In order to accurately fit the positive potential curve, the fitting error of the polynomial function needs to be gradually reduced. And observing that the fitting error of the polynomial function is wavy, so that a 1-order Fourier function is selected to correct the overall error. The effect of using a 1 st order fourier function on the error correction and the effect of the corrected fit are shown in fig. 7 and 8.
Next, local correction of the error curve is continued. The order 1 gaussian function fits the local error well, so the subsequent error correction is based on the gaussian function. The general form of the 1 st order gaussian function is as follows: the peak value on the error curve can be selected from the region corresponding to the maximum error value according to the sequence from large to small for the first local correction. Fig. 9 and 10 are a graph obtained by correcting the maximum peak value on a new error curve using a gaussian function of order 1 and a fitted graph obtained by fitting an adjusted positive electrode potential curve using another new fitted curve, respectively.
A second gaussian error correction is then performed, which gives the error fit and the effect of the corrected fit in the same way as shown in fig. 11 and 12.
And continuously repeating the local error correction process to perform subsequent correction until the maximum error between the fitted curve and the adjusted positive potential curve is less than 10 mV. The resulting fit effect versus error curves are given in fig. 13 and 14.
The simplified electrochemical model (SP +) requires matching of the positive electrode potential curve when the basic operation process of the battery is matched. The positive electrode potential curve obtained based on the above process is given, and the curve fitting effect of the simplified electrochemical model to the battery terminal voltage is shown in fig. 15.
The absolute mean error of the fit was only 5.3mV and the correlation coefficient of the fit was 0.9996. This indicates that the positive electrode potential curve obtained above is correct and effective.
In step S5, the preset value may be 10 mV.
In a preferred embodiment of the present invention, the negative electrode potential curve and the open circuit voltage curve are superimposed to obtain a positive electrode potential curve of the lithium ion battery, and the specific process is as follows:
taking data points with the same number as an open-circuit voltage curve from a position of a lithium intercalation concentration fraction of the battery cathode corresponding to the determined initial cathode potential to a region of the lithium intercalation concentration fraction of the battery cathode being 1;
adding the negative electrode potential corresponding to the initial battery negative electrode lithium intercalation concentration fraction in the negative electrode potential curve to the open circuit voltage when the charge state is 0 in the open circuit voltage curve, adding the negative electrode potential when the battery negative electrode lithium intercalation concentration fraction is 1 to the open circuit voltage when the charge state is 1, adding the negative electrode potential curve and the remaining data points of the open circuit voltage curve in a one-to-one correspondence manner, and obtaining the curve after the addition, which is the positive electrode potential curve of the lithium ion battery.
In a preferred embodiment of the present invention, in step S2, the polynomial function is a 6 th order polynomial function.
In a preferred embodiment of the present invention, in step S3, the 1 st order fourier function is expressed as:
y=a0+a1·cos(x·w)+b1·sin(x·w)
in the formula, a0、a1、w、b1The parameters are to-be-fitted parameters, x represents the embedded lithium concentration fraction of the battery anode, and y represents the open-circuit potential error of the battery anode.
Specifically, the application selects a 1-order Fourier function to correct the positive open-circuit potential curve for the first time, and has the advantages that: the 1 st order fourier function is wavy, similar to the shape of the error curve. The error caused by the polynomial fitting function in the step one can be reduced on the whole, and the number of times of subsequent 1-order Gaussian function correction is reduced.
In a preferred embodiment of the present invention, the order 1 gaussian function is expressed as:
y=a·exp((x-b)/c)
in the formula, a, b and c are parameters to be fitted, x represents the lithium insertion concentration fraction of the battery anode, y represents the open-circuit potential error of the battery anode, and exp represents an e index.
Specifically, the order-1 gaussian function has good local correction capability, and no error is introduced into another region when local correction is performed, so that the order-1 gaussian function is selected for fine correction. According to the size of the peak value of each area of the error curve, the maximum error area is selected, and the 1 st order Gaussian function is adopted for local correction, so that an invalid correction process is avoided, and the correction times required by accurate fitting are greatly reduced.
Example 2:
the invention provides a nondestructive acquisition system for an anode open-circuit potential curve of a lithium ion battery, which comprises a cathode potential curve adjusting module 1, a polynomial fitting module 2, an overall correcting module 3, a local correcting module 4 and an anode open-circuit potential curve acquisition module 5 as shown in figure 1,
the negative electrode potential curve adjusting module 1 is used for adjusting an initial voltage value of a negative electrode potential curve of the lithium ion battery to obtain an adjusted negative electrode potential curve, and superposing the adjusted negative electrode potential curve and an open-circuit voltage curve to obtain an adjusted positive electrode potential curve, wherein the adjusted positive electrode potential curve has no rising stage;
the polynomial fitting module 2 is connected with the negative potential curve adjusting module 1 and used for fitting the adjusted positive potential curve by adopting a polynomial function to obtain a polynomial fitting curve, and subtracting the polynomial fitting curve from the adjusted positive potential curve to obtain an initial error curve;
the integral correction module 3 is connected with the polynomial fitting module 2 and used for fitting the initial error curve by adopting a 1-order Fourier function to obtain a Fourier function fitting curve, superposing the Fourier function fitting curve and the polynomial fitting curve to obtain a Fourier function correction fitting curve, and subtracting the Fourier function correction fitting curve from the adjusted positive potential curve to obtain a new error curve;
the local correction module 4 is connected with the overall correction module 3 and used for correcting the maximum peak value on the new error curve by adopting a 1-order Gaussian function to obtain a Gaussian function fitting curve, superposing the Gaussian function fitting curve and the Fourier function correction fitting curve to obtain a Gaussian function correction fitting curve, and subtracting the Gaussian function correction fitting curve and the adjusted positive electrode potential curve to obtain another new error curve;
and the positive open-circuit potential curve acquisition module 5 is connected with the local correction module 4 and used for continuously updating by using the local correction module to obtain an error curve until the maximum error value in the obtained error curve is smaller than a preset value, and taking a Gaussian function correction fitting curve obtained by the local correction module at the moment as a positive open-circuit potential curve of the lithium ion battery.
In a preferred embodiment of the present invention, the negative potential curve adjustment module 1 includes a data point selection unit and a curve superposition unit,
the data point selection unit is used for selecting data points with the same number as the open-circuit voltage curve from the battery cathode lithium intercalation concentration fraction corresponding to the determined initial cathode potential to the interval with the battery cathode lithium intercalation concentration fraction of 1;
and the curve superposition unit is used for adding the negative electrode potential corresponding to the initial battery negative electrode lithium intercalation concentration fraction in the negative electrode potential curve and the open-circuit voltage when the charge state in the open-circuit voltage curve is 0, adding the negative electrode potential when the battery negative electrode lithium intercalation concentration fraction is 1 and the open-circuit voltage when the charge state is 1, adding the negative electrode potential curve and the remaining data points in the open-circuit voltage curve in a one-to-one correspondence manner, and obtaining the added curve as the positive electrode potential curve of the lithium ion battery.
In a preferred embodiment of the invention, the polynomial function is a 6 th order polynomial function.
In a preferred embodiment of the present invention, the 1 st order fourier function is expressed as:
y=a0+a1·cos(x·w)+b1·sin(x·w)
in the formula, a0、a1、w、b1The parameters are to-be-fitted parameters, x represents the embedded lithium concentration fraction of the battery anode, and y represents the open-circuit potential error of the battery anode.
In particular, the amount of the solvent to be used,
in a preferred embodiment of the present invention, the order 1 gaussian function is expressed as:
y=a·exp((x-b)/c)
in the formula, a, b and c are parameters to be fitted, x represents the lithium insertion concentration fraction of the battery anode, y represents the open-circuit potential error of the battery anode, and exp represents an e index.

Claims (10)

1. A non-destructive acquisition method for an open circuit potential curve of a lithium ion battery anode is characterized by comprising the following steps:
step S1, adjusting the initial voltage value of the negative electrode potential curve of the lithium ion battery to obtain an adjusted negative electrode potential curve, and overlapping the adjusted negative electrode potential curve and the open-circuit voltage curve to obtain an adjusted positive electrode potential curve, wherein the adjusted positive electrode potential curve has no rising stage;
step S2, fitting the adjusted positive electrode potential curve by adopting a polynomial function to obtain a polynomial fitting curve, and subtracting the polynomial fitting curve from the adjusted positive electrode potential curve to obtain an initial error curve;
s3, fitting the initial error curve by adopting a 1-order Fourier function to obtain a Fourier function fitting curve, overlapping the Fourier function fitting curve and a polynomial fitting curve to obtain a Fourier function correction fitting curve, and subtracting the Fourier function correction fitting curve from the adjusted positive potential curve to obtain a new error curve;
step S4, correcting the maximum peak value on the new error curve by adopting a 1 st order Gaussian function to obtain a Gaussian function fitting curve, superposing the Gaussian function fitting curve and a Fourier function correction fitting curve to obtain a Gaussian function correction fitting curve, and subtracting the Gaussian function correction fitting curve and the adjusted positive electrode potential curve to obtain another new error curve;
and S5, repeatedly executing the step S4 until the maximum error value in the error curve obtained in the step S4 is smaller than a preset value, and taking the obtained Gaussian function correction fitting curve as the anode open-circuit potential curve of the lithium ion battery.
2. The nondestructive acquisition method of the lithium ion battery anode open-circuit potential curve according to claim 1, characterized in that the anode potential curve and the open-circuit voltage curve are superimposed to obtain the lithium ion battery anode potential curve, and the specific process is as follows:
taking data points with the same number as an open-circuit voltage curve from a position of a lithium intercalation concentration fraction of the battery cathode corresponding to the determined initial cathode potential to a region of the lithium intercalation concentration fraction of the battery cathode being 1;
adding the negative electrode potential corresponding to the initial battery negative electrode lithium intercalation concentration fraction in the negative electrode potential curve to the open circuit voltage when the charge state is 0 in the open circuit voltage curve, adding the negative electrode potential when the battery negative electrode lithium intercalation concentration fraction is 1 to the open circuit voltage when the charge state is 1, adding the negative electrode potential curve and the remaining data points of the open circuit voltage curve in a one-to-one correspondence manner, and obtaining the curve after the addition, which is the positive electrode potential curve of the lithium ion battery.
3. The method according to claim 1, wherein in step S2, the polynomial function is a 6 th order polynomial function.
4. The method for nondestructive acquisition of the open circuit potential curve of the lithium ion battery anode according to claim 1, wherein in step S3, the fourier function of order 1 is expressed as:
y=a0+a1·cos(x·w)+b1·sin(x·w)
in the formula, a0、a1、w、b1The parameters are to-be-fitted parameters, x represents the embedded lithium concentration fraction of the battery anode, and y represents the open-circuit potential error of the battery anode.
5. The method for nondestructively acquiring the open-circuit potential curve of the lithium ion battery anode according to claim 1, wherein the 1 st order gaussian function is expressed as:
y=a·exp((x-b)/c)
in the formula, a, b and c are parameters to be fitted, x represents the lithium insertion concentration fraction of the battery anode, y represents the open-circuit potential error of the battery anode, and exp represents an e index.
6. A non-destructive acquisition system for an open-circuit potential curve of a positive electrode of a lithium ion battery is characterized by comprising a negative electrode potential curve adjusting module (1), a polynomial fitting module (2), an overall correcting module (3), a local correcting module (4) and a positive electrode open-circuit potential curve acquiring module (5),
the negative electrode potential curve adjusting module (1) is used for adjusting the initial voltage value of a negative electrode potential curve of the lithium ion battery to obtain an adjusted negative electrode potential curve, and superposing the adjusted negative electrode potential curve and an open-circuit voltage curve to obtain an adjusted positive electrode potential curve, wherein the adjusted positive electrode potential curve has no rising stage;
the polynomial fitting module (2) is connected with the negative potential curve adjusting module (1) and is used for fitting the adjusted positive potential curve by adopting a polynomial function to obtain a polynomial fitting curve, and subtracting the polynomial fitting curve from the adjusted positive potential curve to obtain an initial error curve;
the integral correction module (3) is connected with the polynomial fitting module (2) and is used for fitting the initial error curve by adopting a 1-order Fourier function to obtain a Fourier function fitting curve, superposing the Fourier function fitting curve and the polynomial fitting curve to obtain a Fourier function correction fitting curve, and subtracting the Fourier function correction fitting curve from the adjusted positive potential curve to obtain a new error curve;
the local correction module (4) is connected with the overall correction module (3) and used for correcting the maximum peak value on the new error curve by adopting a 1-order Gaussian function to obtain a Gaussian function fitting curve, superposing the Gaussian function fitting curve and the Fourier function correction fitting curve to obtain a Gaussian function correction fitting curve, and subtracting the Gaussian function correction fitting curve and the adjusted positive electrode potential curve to obtain another new error curve;
and the positive open-circuit potential curve acquisition module (5) is connected with the local correction module (4) and used for continuously updating by using the local correction module to obtain an error curve until the maximum error value in the obtained error curve is smaller than a preset value, and taking the Gaussian function correction fitting curve obtained by the local correction module at the moment as a positive open-circuit potential curve of the lithium ion battery.
7. The system for non-destructive acquisition of open-circuit potential curve of lithium ion battery anode according to claim 1, wherein the adjustment module (1) of potential curve of cathode comprises a data point selection unit and a curve superposition unit,
the data point selection unit is used for selecting data points with the same number as the open-circuit voltage curve from the battery cathode lithium intercalation concentration fraction corresponding to the determined initial cathode potential to the interval with the battery cathode lithium intercalation concentration fraction of 1;
and the curve superposition unit is used for adding the negative electrode potential corresponding to the initial battery negative electrode lithium intercalation concentration fraction in the negative electrode potential curve and the open-circuit voltage when the charge state in the open-circuit voltage curve is 0, adding the negative electrode potential when the battery negative electrode lithium intercalation concentration fraction is 1 and the open-circuit voltage when the charge state is 1, adding the negative electrode potential curve and the remaining data points in the open-circuit voltage curve in a one-to-one correspondence manner, and obtaining the added curve as the positive electrode potential curve of the lithium ion battery.
8. The system of claim 1, wherein the polynomial function is a 6 th order polynomial function.
9. The system according to claim 1, wherein the system for non-destructively acquiring the open circuit potential curve of the positive electrode of the lithium ion battery is characterized by a 1 st order fourier function expressed as:
y=a0+a1·cos(x·w)+b1·sin(x·w)
in the formula, a0、a1、w、b1The parameters are to-be-fitted parameters, x represents the embedded lithium concentration fraction of the battery anode, and y represents the open-circuit potential error of the battery anode.
10. The system according to claim 1, wherein the 1 st order gaussian function is represented as:
y=a·exp((x-b)/c)
in the formula, a, b and c are parameters to be fitted, x represents the lithium insertion concentration fraction of the battery anode, y represents the open-circuit potential error of the battery anode, and exp represents an e index.
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