A Method for Parameter Identification and Optimization of a Dual-Tank Model for Lithium Iron Phosphate Batteries

Abstract

This invention discloses a method for parameter identification and optimization of a dual-tank model for lithium iron phosphate batteries, comprising the following steps: S1, acquiring low-rate charge / discharge data of the lithium iron phosphate battery and the equilibrium potential of the positive and negative electrode active materials to metallic lithium; S2, establishing a dual-tank model for the lithium iron phosphate battery, differentiating the full voltage-capacity curve and the negative electrode-electrochemical stoichiometry curve and performing curve fitting, and determining the negative electrode capacity C based on the correspondence between the extreme points of the two differential curves. neg With the initial electrochemical stoichiometry of the negative electrode x0; S3, using an optimization algorithm to minimize the root mean square error between the model voltage and the measured voltage, identify the remaining dual-tank model parameter set β. According to this invention, the number of parameters to be identified in the dual-tank model can be reduced, improving the accuracy and stability of parameter identification, and obtaining the globally optimal parameters for the lithium iron phosphate battery dual-tank model.

Description

Technical Field

[0001] This invention relates to the technical field of battery modeling and parameter identification, and in particular to a method for parameter identification and optimization of a dual-tank model of a lithium iron phosphate battery. Background Technology

[0002] The dual-tank model of a lithium-ion battery is a model with separate positive and negative electrodes, and its total voltage is composed of the positive and negative electrode potentials. It can simulate battery life degradation and also help determine the thermodynamic states of the positive and negative electrodes in complex electrochemical models. The optimization criterion for the lithium-ion battery dual-tank model is usually minimizing the root mean square error between the model voltage and the measured voltage, and optimization algorithms are used for parameter identification. The lithium-ion battery dual-tank model has five parameters, but only one optimization criterion. Lithium iron phosphate batteries exhibit a significant voltage plateau at low charge and discharge rates, with relatively small voltage changes within this plateau range. When using the above optimization methods to identify the parameters of the lithium iron phosphate battery dual-tank model, the identification results may get trapped in local optima. Therefore, obtaining accurate parameters for the lithium iron phosphate battery dual-tank model is quite challenging. Summary of the Invention

[0003] To address the shortcomings of existing technologies, the present invention aims to provide a method for parameter identification and optimization of a dual-tank lithium iron phosphate battery model. This method reduces the number of parameters to be identified in the dual-tank model, improves the accuracy and stability of parameter identification, and obtains globally optimal parameters for the dual-tank lithium iron phosphate battery model. To achieve the above-mentioned objectives and other advantages of the present invention, a method for parameter identification and optimization of a dual-tank lithium iron phosphate battery model is provided, comprising:

[0004] S1. Obtain low-rate charge / discharge data of lithium iron phosphate batteries and the equilibrium potential of positive and negative electrode active materials for metallic lithium.

[0005] S2. Establish a dual-tank model for a lithium iron phosphate battery. Differentiate the full voltage-capacity curve and the negative electrode equilibrium potential-electrochemical stoichiometry curve and perform curve fitting. Based on the correspondence between the extreme points of the two differential curves, determine the negative electrode capacity. With the initial electrochemical stoichiometry of the negative electrode ;

[0006] S3. Using an optimization algorithm, with the goal of minimizing the root mean square error between the model voltage and the measured voltage, identify the remaining parameter set for the dual-tank model. .

[0007] Preferably, step S2 further includes the following steps:

[0008] The characteristic equations for the S21 battery dual-water-tank model are as follows:

[0009] ;

[0010] in: This represents the terminal voltage of the battery model. The negative electrode electrochemical stoichiometry, The positive electrode electrochemical stoichiometry is... The positive equilibrium potential, The equilibrium potential is at the negative electrode. For time, For Coulomb efficiency, For current, For negative electrode capacity, For positive electrode capacity, The initial electrochemical stoichiometry of the negative electrode. The initial electrochemical stoichiometry of the positive electrode;

[0011] S22. Differentiate a segment of the full voltage-capacity curve and fit the differential curve to determine the two extreme points of the differential curve for the voltage plateau segment. and ;

[0012] S23. Differentiate a segment of the negative electrode equilibrium potential-electrochemical stoichiometry curve, and fit the differential curve to determine the two extreme points of the voltage plateau segment differential curve. and ;

[0013] S24. Based on the correspondence between the extreme points of the two differential curves in the voltage plateau segment, the negative electrode capacity of the dual-tank model is calculated using the cumulative charge method between two points. As shown in the following formula:

[0014] ;

[0015] in: and These are the discharge capacities corresponding to the two extreme points of the plateau segment of the differential curve of the full voltage-capacity curve of a lithium iron phosphate battery. and The electrostoichiometry numbers are the two extreme points of the differential curve of the negative electrode equilibrium potential-electrochemical stoichiometry.

[0016] S25. Calculate the initial electrochemical stoichiometry of the negative electrode using the ampere-hour integration method. As shown in the following formula:

[0017] ;

[0018] in: The initial charge / discharge capacity of the lithium iron phosphate battery is 0.

[0019] Preferably, the low-rate charge / discharge data in step S1 is the lithium iron phosphate battery's full voltage-capacity curve showing a clear voltage plateau at that charge / discharge rate.

[0020] Preferably, the voltage plateau is the portion of the full voltage-capacity curve where the voltage does not change significantly during the charging and discharging process of the lithium iron phosphate battery.

[0021] Preferably, in step S2, the correspondence between the extreme points of the two differential curves is that when the differential curve of the negative electrode equilibrium potential-electrochemical stoichiometry appears at an extreme value in the voltage plateau segment, the differential curve of the full voltage-capacity also appears at an extreme value. Preferably, in step S3, an optimization algorithm is used to identify the parameters of the lithium iron phosphate battery dual-tank model with the goal of minimizing the root mean square error between the measured battery voltage and the dual-tank model voltage, and the identified parameter set is obtained. .

[0022] Compared with the prior art, the beneficial effects of this invention are:

[0023] The parameter identification and optimization method for the dual-tank lithium iron phosphate battery model of the present invention can preferentially determine the negative electrode capacity of the dual-tank model based on the correspondence between the two extreme points of the full voltage-capacity differential curve and the two extreme points of the negative electrode-electrochemical stoichiometry differential curve. and initial electrochemical stoichiometry of the negative electrode This reduces the number of parameters to be identified in the optimization algorithm. This optimization method can reduce the number of parameters to be identified in the dual-tank model, preventing the optimization algorithm from getting trapped in local optima and improving the accuracy and stability of parameter identification for the lithium iron phosphate dual-tank model. Attached Figure Description

[0024] Figure 1 A flowchart illustrating the parameter identification and optimization method for a dual-tank lithium iron phosphate battery model according to the present invention;

[0025] Figure 2 A schematic diagram of a dual-tank model for the parameter identification and optimization method of a lithium iron phosphate battery dual-tank model according to the present invention;

[0026] Figure 3 A schematic diagram of the full voltage-capacity curve and dVdQ curve of a lithium iron phosphate battery dual-tank model parameter identification and optimization method according to the present invention.

[0027] Figure 4 A schematic diagram of the battery negative electrode equilibrium potential-electrochemical stoichiometry curve and dφdx curve for the parameter identification and optimization method of the lithium iron phosphate battery dual water tank model according to the present invention.

[0028] Figure 5This diagram illustrates the correspondence between the extreme points of the battery's full voltage-capacity differential curve and the extreme points of the negative electrode equilibrium potential-electrochemical stoichiometry differential curve, based on the parameter identification and optimization method for the dual-tank model of lithium iron phosphate batteries according to the present invention. Detailed Implementation

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] Reference Figures 1-5 A method for parameter identification and optimization of a dual-tank model of a lithium iron phosphate battery includes the following steps:

[0031] S1. Obtain low-rate charge / discharge data of lithium iron phosphate batteries and the equilibrium potential of positive and negative electrode active materials for metallic lithium.

[0032] S2. Establish a dual-tank model for a lithium iron phosphate battery. Differentiate the full voltage-capacity curve and the negative electrode equilibrium potential-electrochemical stoichiometry curve and perform curve fitting. Based on the correspondence between the extreme points of the two differential curves, determine the negative electrode capacity. With the initial electrochemical stoichiometry of the negative electrode ;

[0033] S3. Using an optimization algorithm, with the goal of minimizing the root mean square error between the model voltage and the measured voltage, identify the remaining parameter set for the dual-tank model. .

[0034] Example 1

[0035] S1 acquires low-rate charge / discharge data of lithium iron phosphate batteries and the equilibrium potential of positive and negative electrode active materials for metallic lithium.

[0036] Specifically, discharge data of lithium iron phosphate batteries at a rate of 0.05C were selected; the lower limit of the equilibrium potential of the positive electrode active material to lithium metal was 2.5V, and the upper limit was 3.95V; the lower limit of the equilibrium potential of the negative electrode active material to lithium metal was 0.005V, and the upper limit was 1.5V.

[0037] S2. A dual-tank model of a lithium iron phosphate battery is established. The negative electrode equilibrium potential-electrochemical stoichiometry curve and the full voltage-capacity curve are differentiated and curve-fitted. Based on the correspondence between the extreme points of the two differential curves, the negative electrode capacity is determined. With the initial electrochemical stoichiometry of the negative electrode ;

[0038] Step S2 specifically includes the following steps:

[0039] S21 Establish as Figure 2 The lithium iron phosphate battery dual-tank model shown in this embodiment has the following external characteristic equations:

[0040] ;

[0041] in: This represents the terminal voltage of the battery model. The negative electrode electrochemical stoichiometry, The positive electrode electrochemical stoichiometry is... The positive equilibrium potential, The equilibrium potential is at the negative electrode. For time, It is Coulomb efficiency. For current, For negative electrode capacity, For positive electrode capacity, The initial electrochemical stoichiometry of the negative electrode. This represents the initial electrochemical stoichiometry of the positive electrode.

[0042] S22 such as Figure 3 As shown, a segment of the full voltage-capacity curve is differentiated, and the differentiated curve is fitted to determine the two extreme points of the differential curve for the voltage plateau segment. and ;

[0043] S221 First, select a segment of the full voltage-charge curve. The selected segment should be in the voltage plateau segment. Specifically, in this embodiment, the charge range is selected from 0.2Ah to 1.6Ah.

[0044] S222 differentiates a selected segment of the full voltage-capacity curve, as shown in the following equation:

[0045] ;

[0046] In the formula: Battery voltage, For time, For time intervals; This represents the amount of discharge.

[0047] S223 fits the full voltage-capacity differential curve; specifically, polynomial fitting can be used.

[0048] S224 determines the two extreme points of the total voltage-capacity differential curve. and .

[0049] S23 such as Figure 4As shown, a partial segment of the negative electrode equilibrium potential-electrochemical stoichiometry curve is differentiated, and the differentiated curve is fitted to determine the two extreme points of the differential curve of the voltage plateau segment. and ;

[0050] S231 First, select a segment of the negative electrode equilibrium potential-electrochemical stoichiometry curve. The selected segment should be in the voltage plateau segment. Specifically, in this embodiment, the range of electrochemical stoichiometry x is selected from 0.90 to 0.09.

[0051] S232 differentiates a selected segment of the full voltage-capacity curve, as shown in the following equation:

[0052] ;

[0053] In the formula: To achieve the equilibrium potential of the battery's negative electrode. For time, For time intervals; The electrochemical stoichiometry is the equilibrium potential of the negative electrode.

[0054] S233 fits the differential curve of the negative electrode equilibrium potential-electrochemical stoichiometry. Specifically, polynomial fitting can be used.

[0055] S234 determines the two extreme points of the total voltage-capacity differential curve. and .

[0056] S24 Based on the correspondence between the extreme points of the two differential curves in the voltage plateau segment, such as Figure 5 As shown, the negative electrode capacity of the dual-tank model is calculated using the cumulative charge method between two points. The calculation formula is as follows:

[0057] ;

[0058] in: and These are the discharge capacities corresponding to the two extreme points of the plateau segment of the differential curve of the full voltage-capacity curve of a lithium iron phosphate battery. and The electrostoichiometry is the electrochemical stoichiometry corresponding to the two extreme points of the differential curve of the negative electrode equilibrium potential-electrochemical stoichiometry.

[0059] S25 such Figure 5 As shown, the initial electrochemical stoichiometry of the negative electrode was calculated using the ampere-hour integration method. The calculation formula is as follows:

[0060] ;

[0061] S3 employs an optimization algorithm, using the minimum root mean square error between the model voltage and the measured voltage as the optimization criterion, to identify the remaining parameter set of the dual-tank model. ;

[0062] S31 employs a genetic algorithm, with the minimum root mean square error between the measured battery voltage and the voltage of the dual-tank model as the optimization criterion. The optimization criterion is as follows:

[0063] ;

[0064] in, It is the set of parameters to be identified. It is to identify the data length. It is time. This is the actual measured voltage of the battery. It is the voltage of the dual-tank model.

[0065] S32 Obtain the identified parameter set .

[0066] This embodiment provides a method for parameter identification and optimization of a dual-tank model for lithium iron phosphate batteries. Based on the correspondence between the two extreme points of the full voltage-capacity curve and the two extreme points of the negative electrode-electrochemical stoichiometry curve, the negative electrode capacity can be determined. With the initial electrochemical stoichiometry of the negative electrode Based on this, the present invention can reduce the number of parameters that the optimization algorithm needs to identify, improve the accuracy and stability of parameter identification for the dual-tank model of lithium iron phosphate batteries, and obtain the globally optimal model parameters.

[0067] The number of devices and processing scale described herein are for the purpose of simplifying the description of the invention, and applications, modifications and variations thereof will be apparent to those skilled in the art.

[0068] Although embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and embodiments. They can be applied to various fields suitable for the present invention. For those skilled in the art, other modifications can be easily made. Therefore, without departing from the general concept defined by the claims and their equivalents, the present invention is not limited to the specific details and illustrations shown and described herein.

Claims

1. A lithium iron phosphate battery double water tank model parameter identification and optimization method, characterized in that, The method comprises the following steps: S1, obtaining low-rate charge-discharge data of the lithium iron phosphate battery and the equilibrium potential of the positive and negative active materials to metal lithium; S2, a lithium iron phosphate battery double-water tank model is established, the voltage platform section full voltage-capacity curve and the negative electrode equilibrium potential-electrochemical stoichiometry number curve are differentiated and curve fitting is performed, based on the corresponding relationship of the extreme points of the two kinds of differential curves, the negative electrode capacity and the negative electrode initial electrochemical stoichiometry number ; S3, through the optimization algorithm, with the root mean square error of the model voltage and the measured voltage being the optimization goal, identifying the remaining double water tank model parameter set .

2. The lithium iron phosphate battery dual water tank model parameter identification and optimization method of claim 1, wherein, The step S2 further comprises the following steps: S21, the characteristic equation of the battery double-water tank model is as follows: The low-rate charge-discharge data in the step S1 is that the full voltage-capacity curve of the lithium iron phosphate battery at the charge-discharge rate has an obvious voltage platform. ； wherein: is the end voltage of the battery model, is the negative electrode stoichiometry, is the positive electrode stoichiometry, is the positive electrode equilibrium potential, is the negative electrode equilibrium potential, is time, is the coulombic efficiency, is the current, is the negative electrode capacity, is the positive electrode capacity, is the negative electrode initial stoichiometry, is the positive electrode initial stoichiometry; S22, differentiating the full voltage-capacity curve partial segment, and fitting the differential curve to determine two extreme points of the voltage platform segment differential curve and ; S23, differentiating the part segment of the negative electrode equilibrium potential-electrochemical quantity curve, and fitting the differential curve to determine two extreme points of the differential curve of the voltage platform segment and ; S24, based on the corresponding relationship between the extreme points of the two differential curves of the voltage platform segment, the cumulative charge method between two points is used to calculate the negative capacity of the double water tank model As shown in the following formula: ； wherein: and are the discharge electric quantities corresponding to the two extreme points of the platform section of the full voltage-capacity differential curve of the lithium iron phosphate battery, and are the electrochemical amounts corresponding to the two extreme points of the equalization potential-electrochemical amount differential curve of the negative electrode. S25, calculating the initial electrochemical number of the negative electrode by the ampere-hour integration method as shown in the following formula: ； wherein: is the initial charge / discharge capacity of the lithium iron phosphate battery is 0.

3. The lithium iron phosphate battery dual water tank model parameter identification and optimization method of claim 1, wherein, The voltage platform is a part in which the full voltage-capacity curve voltage does not change obviously in the charge-discharge process of the lithium iron phosphate battery.

4. The lithium iron phosphate battery dual water tank model parameter identification and optimization method of claim 3, wherein, The corresponding relationship between the two differential curve extreme points in the step S2 is that when the negative electrode equilibrium potential-electrochemical stoichiometry differential curve has an extreme value, the full voltage-capacity differential curve also has an extreme value in the voltage platform section.

5. The lithium iron phosphate battery dual-tank model parameter identification and optimization method of claim 1, wherein, ​ 6. The lithium iron phosphate battery dual-tank model parameter identification and optimization method of claim 1, wherein, In step S3, the lithium iron phosphate battery double-tank model parameters are identified by an optimization algorithm with the minimum root mean square error of the measured battery voltage and the double-tank model voltage as the optimization target, to obtain the identified parameter set .

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