Identification method, system, computing device and medium for lithium battery equivalent circuit model

Abstract

Embodiments of the present invention disclose a method, system, computing device, and medium for identifying a lithium battery equivalent circuit model. The identification method includes determining a frequency-domain state equation based on a second-order RC equivalent circuit model of a lithium battery; determining a first set of intermediate parameters based on the internal resistance, polarization resistance, and polarization capacitance of the second-order RC equivalent circuit model of the lithium battery, and determining a second set of intermediate parameters based on the first set of intermediate parameters; determining a correspondence between the first set of intermediate parameters and the second set of intermediate parameters, as well as a correspondence between parameters in the second-order RC equivalent circuit model of the lithium battery and the first set of intermediate parameters, using a VFFLMRLS algorithm; calculating the second set of intermediate parameters using a recursive algorithm based on the VFFLMRLS algorithm and an error value of the open-circuit voltage; and determining the parameters of the second-order RC equivalent circuit model of the lithium battery based on the correspondence between the parameters. The VFFLMRLS algorithm is used to improve the computational accuracy and efficiency of the model identification method.

Description

Technical Field

[0001] The present invention relates to the field of new energy battery technology, and in particular to a method, system, computing device and medium for identifying an equivalent circuit model of a lithium battery. Background Art

[0002] With growing public awareness of environmental protection, a large number of power batteries and energy storage devices are being widely adopted in electric vehicles and microgrid technologies. Lithium batteries, with their high energy density, long cycle life, excellent stability, environmental friendliness, and affordability, have become the preferred choice for the new generation of power energy storage devices. To ensure the safe and reliable operation of lithium battery packs in power energy storage devices, a comprehensive battery management system is essential to estimate and predict battery status. Establishing an accurate lithium battery model is one of the key technologies that need to be addressed in battery management systems.

[0003] Currently, common lithium battery models are primarily categorized into two main categories: electrochemical models and equivalent circuit models. The electrochemical model fundamentally explains the dynamic mass transfer process between the positive and negative electrodes of a lithium battery, offering high accuracy. However, the computational process is complex and challenging to implement, making it unsuitable for real-time systems. While the battery model represented by the equivalent circuit model may not be as accurate as the electrochemical model, its principles are clear, computation is simple, and it exhibits linear characteristics. Furthermore, it facilitates the estimation and prediction of the battery's state, making it easy to implement in real-time systems, leading to its wider application. Among lithium battery models based on equivalent circuit models, the most common include the Rint model, the Thevenin model, the PNGV model, and the RC model. Among these, the second-order RC equivalent circuit model is the preferred choice for equivalent lithium battery models due to its high computational complexity and accuracy, enabling it to accurately simulate the various characteristics of lithium batteries. For a specific lithium battery equivalent circuit model, the proper design of the model's parameter identification algorithm directly determines the reliability and accuracy of the lithium battery model, thereby ensuring the accuracy of the estimated state of charge (SOC) and state of health (SOH) of the lithium battery.

[0004] Currently commonly used identification methods include Kalman filtering algorithm, intelligent algorithm, RLS algorithm and FFRLS algorithm, etc., which have defects such as the increase in the number of identification parameters, the increase in system dimension, the large amount of calculation, and the high complexity, which are prone to "data saturation". Summary of the Invention

[0005] Embodiments of the present invention provide a method, system, computing device, and medium for identifying a lithium battery equivalent circuit model. The method for identifying a lithium battery equivalent circuit model is applied to the field of lithium battery model identification. The VFFLMRLS algorithm is used to achieve the advantages of small computational complexity, fast computational speed, and high identification accuracy during the identification process.

[0006] In a first aspect, an embodiment of the present invention provides a method for identifying an equivalent circuit model of a lithium battery, comprising:

[0007] Determine the frequency domain state equation based on the second-order RC equivalent circuit model of the lithium battery;

[0008]

[0009] Where U represents the load voltage, Uoc represents the open circuit voltage, I represents the current through the load, R0 represents the internal resistance, R1 and R2 represent the polarization resistance, and C1 and C2 represent the polarization capacitance.

[0010] Determining a first set of intermediate parameters based on the internal resistance, polarization resistance, and polarization capacitance of the second-order RC equivalent circuit model of the lithium battery, and determining the second set of intermediate parameters based on the first set of intermediate parameters;

[0011] The first set of intermediate parameters a, b, c, d and e satisfy:

[0012] a=R0;

[0013] b=R1C1R2C2;

[0014] c=R1C1+R2C2;

[0015] d=R0+R1+R2;

[0016] e=R0(R1C1+R2C2)+R1R2C1+R1R2C2;

[0017] The second set of intermediate parameters θ1, θ2, θ3, θ4 and θ5 satisfy:

[0018]

[0019]

[0020]

[0021]

[0022]

[0023] Where T is the time period;

[0024] Determine, by using a VFFLMRLS algorithm, a correspondence between the first set of intermediate parameters and the second set of intermediate parameters, and a correspondence between parameters in the second-order RC equivalent circuit model of the lithium battery and the first set of intermediate parameters;

[0025] The corresponding relationship between the first set of intermediate parameters and the second set of intermediate parameters satisfies:

[0026]

[0027]

[0028]

[0029]

[0030]

[0031] The corresponding relationship between the parameters in the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters satisfies:

[0032] R0=a;

[0033]

[0034]

[0035] R2 = da - R1;

[0036]

[0037] in,

[0038] Calculating the second set of intermediate parameters using a recursive algorithm according to the VFFLMRLS algorithm and an error value of the open circuit voltage;

[0039] Determine the parameters of the second-order RC equivalent circuit model of the lithium battery according to the second group of intermediate parameters, the correspondence between the first group of intermediate parameters and the second group of intermediate parameters, and the correspondence between the parameters of the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters.

[0040] In a second aspect, an embodiment of the present invention further provides a system for identifying a second-order RC equivalent circuit model of a lithium battery, comprising:

[0041] The frequency domain state equation determination module is used to determine the frequency domain state equation based on the second-order RC equivalent circuit model of the lithium battery:

[0042]

[0043] Where U represents the load voltage, Uoc represents the open circuit voltage, I represents the current through the load, R0 represents the internal resistance, R1 and R2 represent the polarization resistance, and C1 and C2 represent the polarization capacitance.

[0044] a second set of intermediate parameter setting module, configured to set the first set of intermediate parameters according to the internal resistance, polarization resistance, and polarization capacitance of the second-order RC equivalent circuit model of the lithium battery, and determine the second set of intermediate parameters according to the first set of intermediate parameters;

[0045] Wherein, the first set of intermediate parameters a, b, c, d and e satisfy:

[0046] a=R0;

[0047] b=R1C1R2C2;

[0048] c=R1C1+R2C2;

[0049] d=R0+R1+R2;

[0050] e=R0(R1C1+R2C2)+R1R2C1+R1R2C2;

[0051] The second set of intermediate parameters θ1, θ2, θ3, θ4 and θ5 satisfy:

[0052]

[0053]

[0054]

[0055]

[0056]

[0057] Where T is the time period;

[0058] a corresponding relationship determining module, configured to determine, by using a VFFLMRLS algorithm, a corresponding relationship between the first group of intermediate parameters and the second group of intermediate parameters, and a corresponding relationship between parameters in the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters;

[0059] The corresponding relationship between the first set of intermediate parameters and the second set of intermediate parameters satisfies:

[0060]

[0061]

[0062]

[0063]

[0064]

[0065] The corresponding relationship between the parameters in the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters satisfies:

[0066] R0=a;

[0067]

[0068]

[0069] R2=daR l ;

[0070]

[0071] in,

[0072] a second group of intermediate parameter calculation module, configured to calculate the second group of intermediate parameters using a recursive algorithm based on the VFFLMRLS algorithm and an error value of the open circuit voltage;

[0073] A parameter determination module is used to determine the parameters of the second-order RC equivalent circuit model of the lithium battery based on the second group of intermediate parameters, the correspondence between the first group of intermediate parameters and the second group of intermediate parameters, and the correspondence between the parameters of the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters.

[0074] In a third aspect, an embodiment of the present invention provides a computing device, the computing device comprising:

[0075] one or more processors;

[0076] a storage device for storing one or more programs,

[0077] When the one or more programs are executed by the one or more processors, the one or more processors implement a method for identifying a lithium battery equivalent circuit model as described in any one of the first aspects.

[0078] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for identifying a lithium battery equivalent circuit model as described in any one of the first aspects.

[0079] The embodiment of the present invention provides a method for identifying a lithium battery equivalent circuit model. First, a frequency domain state equation is determined based on the lithium battery second-order RC equivalent circuit model. Then, a first group of intermediate parameters is determined based on the internal resistance, polarization resistance, and polarization capacitance in the lithium battery second-order RC equivalent circuit, and a second group of intermediate parameters is determined based on the first group of intermediate parameters. The VFFLMRLS algorithm is used to determine the correspondence between the first group of intermediate parameters and the second group of intermediate parameters, as well as the correspondence between the parameters in the lithium battery second-order RC equivalent circuit model and the first group of intermediate parameters. Then, a recursive algorithm is used to calculate the second group of intermediate parameters based on the VFFLMRLS algorithm and the error value of the open-circuit voltage. Finally, the parameters of the lithium battery second-order RC equivalent circuit model are determined based on the second group of intermediate parameters, the correspondence between the first group of intermediate parameters and the second group of intermediate parameters, and the correspondence between the parameters of the lithium battery second-order RC equivalent circuit model and the first group of intermediate parameters. This method solves the problems of large computational complexity, complex computation, and low identification accuracy in existing lithium battery equivalent circuit model parameter identification methods. The VFFLMRLS algorithm is used to improve the computational accuracy and efficiency of the model identification method. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings introduced here only illustrate some of the embodiments to be described by the present invention, and are not exhaustive. A person skilled in the art can derive other drawings based on these drawings without inventive effort.

[0081] Figure 1 This is a flow chart of a method for identifying a lithium battery equivalent circuit model provided in Example 1 of the present invention;

[0082] Figure 2 This is a schematic diagram of the topological structure of a lithium battery equivalent circuit model provided in Example 1 of the present invention;

[0083] Figure 3 This is a flow chart of a method for identifying a lithium battery equivalent circuit model provided in the second embodiment of the present invention;

[0084] Figure 4 This is a schematic diagram of a charge-open circuit voltage curve provided by the second embodiment of the present invention;

[0085] Figure 5 This is a schematic structural diagram of a lithium battery equivalent circuit model identification system provided by the third embodiment of the present invention;

[0086] Figure 6 This is a structural diagram of a computing device provided in Example 4 of the present invention. DETAILED DESCRIPTION

[0087] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be fully described below in conjunction with the accompanying drawings of the embodiments of the present invention through specific implementation methods. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0088] Example 1

[0089] Figure 1 This is a flow chart of a method for identifying a lithium battery equivalent circuit model provided in Example 1 of the present invention. Figure 2 This is a schematic diagram of the topological structure of a lithium battery equivalent circuit model provided in Example 1 of the present invention. This embodiment of the present invention is applicable to the case where new energy storage devices are used to identify parameters of model construction. This method can be performed by the identification system in the embodiment of the present invention, which can be installed on a computer device. The identification method includes the following specific steps:

[0090] S110. Determine a frequency domain state equation based on a second-order RC equivalent circuit model of a lithium battery.

[0091] Among them, the frequency domain state equation is:

[0092]

[0093] In the frequency domain state equation, U represents the load voltage, Uoc represents the open circuit voltage, I represents the current passing through the load, R0 represents the internal resistance, R1 and R2 represent the polarization resistance, and C1 and C2 represent the polarization capacitance.

[0094] Specifically, the equivalent circuit model is a circuit model constructed for estimating and presetting the battery state. It is suitable for implementation in real-time systems and has clear principles, gradual calculations, and linear characteristics. The second-order RC equivalent circuit model has the advantages of simple calculations and high accuracy, and can accurately simulate the various characteristics of lithium batteries. Figure 2 As shown in the figure, the constructed second-order RC equivalent circuit model of the lithium battery includes the internal resistance R0, polarization resistance and polarization capacitance, the load voltage U, the open-circuit voltage Uoc and the current passing through the load I. To determine the frequency domain state equation of the second-order RC equivalent circuit model of the lithium battery, the time domain state equation is first determined based on the topological structure of the second-order RC equivalent circuit model of the lithium battery.

[0095] Optionally, determining a time-domain state equation of a second-order RC equivalent circuit model of a lithium battery based on Kirchhoff's current law and Kirchhoff's voltage law;

[0096] Among them, the time domain state equation satisfies:

[0097] U=UOC -IR-U1-U2;

[0098] I=U1 / R1+C1(dU1 / d t );

[0099] I=U2 / R2+C2(dU2 / d t );

[0100] According to the time domain state equation, the frequency domain state equation of the second-order RC equivalent circuit model of the lithium battery is determined by Laplace transform.

[0101] Among them, Kirchhoff's current law and Kirchhoff's voltage law are the basic laws that voltage and current in the circuit must follow. Combined with the topological structure of the second-order RC equivalent circuit model of the lithium battery, the internal resistance R0, polarization resistances R1 and R2, and polarization capacitances C1 and C2 are determined. The relationship between the load voltage U, open-circuit voltage Uoc and the current I passing through the load is determined to determine the time domain state equation:

[0102] U=U OC -IR-U1-U2;

[0103] I=U1 / R1+C1(dU1 / d t );

[0104] I=U2 / R2+C2(dU2 / d t ).

[0105] The frequency domain state equation is further determined by performing Laplace transform on the time domain state equation:

[0106]

[0107] Optionally, a linear transformation is performed on the frequency domain state equation to obtain a linear transformation equation.

[0108] Among them, the linear transformation equation is:

[0109]

[0110] Among them, θ1, θ2, θ3, θ4 and θ5 are the second group of intermediate parameters.

[0111] According to the frequency domain state equation, the deformation equation of the frequency domain state mode is obtained:

[0112] Obtaining a linear transformation equation according to the first transformation parameter and the second transformation parameter;

[0113] Among them, the first transformation parameter G(s) satisfies:

[0114]

[0115] The second transformation parameter s satisfies:

[0116]

[0117] Among them, the frequency domain state equation is obtained:

[0118] Further equivalent transformation of the linear transformation equation:

[0119]

[0120] Then, a linear transformation is performed according to the first transformation parameter and the second transformation parameter to obtain a linear transformation equation with a second set of intermediate parameters;

[0121] Among them, the first transformation parameter G(S):

[0122] Second transformation parameter s:

[0123] That is, obtain the linear transformation equation:

[0124] S120 . Determine a first set of intermediate parameters based on the internal resistance, polarization resistance, and polarization capacitance of the second-order RC equivalent circuit model of the lithium battery, and determine a second set of intermediate parameters based on the first set of intermediate parameters.

[0125] Among them, the first set of intermediate parameters a, b, c, d and e satisfy:

[0126] a=R0;

[0127] b=R1C1R2C2;

[0128] c=R1C1+R2C2;

[0129] d=R0+R1+R2;

[0130] e=R0(R1C1+R2C2)+R1R2C1+R1R2C2;

[0131] The second set of intermediate parameters θ1, θ2, θ3, θ4 and θ5 satisfy:

[0132]

[0133]

[0134]

[0135]

[0136]

[0137] The second group of intermediate parameters θ1, θ2, θ3, θ4 and θ5 satisfy a relationship where T is the time period.

[0138] Specifically, the deformation equation of the frequency domain state mode is obtained based on the frequency domain state equation, and the first set of intermediate parameters a, b, c, d and e are represented by the internal resistance R0, polarization resistances R1 and R2, and polarization capacitances C1 and C2 of the second-order RC equivalent circuit model of the lithium battery. Among them, the first set of intermediate parameters a, b, c, d and e satisfy:

[0139] a=R0;

[0140] b=R1C1R2C2;

[0141] c=R1C1+R2C2;

[0142] d=R0+R1+R2;

[0143] e=R0(R1C1+R2C2)+R1R2C1+R1R2C2.

[0144] Then, the second set of intermediate parameters θ1, θ2, θ3, θ4 and θ5 are expressed according to the linear transformation equation and the determined first set of intermediate parameters a, b, c, d and e. Among them, the second set of intermediate parameters θ1, θ2, e3, θ4 and θ5 satisfy:

[0145]

[0146]

[0147]

[0148]

[0149]

[0150] S130 , determining, by using a VFFLMRLS algorithm, a correspondence between the first set of intermediate parameters and the second set of intermediate parameters, and a correspondence between parameters in a second-order RC equivalent circuit model of a lithium battery and the first set of intermediate parameters.

[0151] The corresponding relationship between the first set of intermediate parameters and the second set of intermediate parameters satisfies:

[0152]

[0153]

[0154]

[0155]

[0156]

[0157] The corresponding relationship between the parameters in the second-order RC equivalent circuit model of lithium batteries and the first group of intermediate parameters:

[0158] R0=a;

[0159]

[0160]

[0161] R2 = da - R1;

[0162]

[0163] in,

[0164] Specifically, the identification method of the second-order RC equivalent circuit model of a lithium battery provided in an embodiment of the present invention identifies the parameters in the second-order RC equivalent circuit model through the VFFLMRLS algorithm. The parameters in the second-order RC equivalent circuit model of a lithium battery include: internal resistance R0, polarization resistances R1 and R2, and polarization capacitances C1 and C2. The VFFLMRLS algorithm is used to construct an equation for the corresponding relationship between the first group of intermediate parameters a, b, c, d and e and the second group of intermediate parameters θ1, θ2, θ3, θ4 and θ5, and then the parameters R0, R1, R2, C1 and C2 in the second-order RC equivalent circuit model of a lithium battery and the second group of intermediate parameters θ1, θ2, θ3, θ4 and θ5 are used to construct an equation for the corresponding relationship.

[0165] Specifically, the corresponding relationship between the first set of intermediate parameters and the second set of intermediate parameters satisfies:

[0166]

[0167]

[0168]

[0169]

[0170]

[0171] The corresponding relationship between the parameters in the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters satisfies:

[0172] R0=a;

[0173]

[0174]

[0175] R2 = da - R1;

[0176]

[0177] in,

[0178] S140 , calculating a second set of intermediate parameters using a recursive algorithm according to the VFFLMRLS algorithm and the error value of the open-circuit voltage.

[0179] Specifically, open-circuit voltage refers to the potential difference between the positive and negative electrodes of a lithium-ion battery when no current flows. In actual battery systems, the potential established between the two electrodes is generally stable. Using the VFFLMRLS algorithm and the continuously decreasing error in open-circuit voltage Uoc, a recursive algorithm is used to determine the second set of intermediate parameters θ1, θ2, θ3, θ4, and θ5. This allows the VFFLMRLS algorithm to identify the second set of intermediate parameters θ1, θ2, θ3, θ4, and θ5.

[0180] S150. Determine the parameters of the second-order RC equivalent circuit model of the lithium battery according to the second group of intermediate parameters, the corresponding relationship between the first group of intermediate parameters and the second group of intermediate parameters, and the corresponding relationship between the parameters of the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters.

[0181] Specifically, the specific values ​​of the second set of intermediate parameters θ1, θ2, θ3, θ4, and θ5 are obtained through identification using the VFFLMRLS algorithm. Based on the correspondence between the first and second sets of intermediate parameters, the specific values ​​of the first set of intermediate parameters a, b, c, d, and e can be obtained. Based on the correspondence between the parameters in the lithium battery second-order RC equivalent circuit model and the first set of intermediate parameters, the specific values ​​of the parameters R0, R1, R2, C1, and C2 of the lithium battery second-order RC equivalent circuit model are obtained, completing the identification process of the lithium battery second-order RC equivalent circuit model.

[0182] In summary, the identification method of the second-order RC equivalent circuit model of a lithium battery provided in an embodiment of the present invention determines the correspondence between the first group of intermediate parameters and the second group of intermediate parameters, as well as the correspondence between the parameters in the second-order RC equivalent circuit model and the first group of intermediate parameters through the VFFLMRLS algorithm; then, based on the VFFLMRLS algorithm and the error value of the open-circuit voltage, a recursive algorithm is used to calculate the second group of intermediate parameters; finally, based on the second group of intermediate parameters, the correspondence between the first group of intermediate parameters and the second group of intermediate parameters, and the correspondence between the parameters of the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters, the parameters of the second-order RC equivalent circuit model of the lithium battery are determined, thereby solving the problems of large computational complexity and low identification accuracy of the existing lithium battery equivalent circuit model parameter identification method, and adopting the VFFLMRLS algorithm to improve the computational accuracy and efficiency of the model identification method.

[0183] Example 2

[0184] Figure 3 This is a flow chart of a method for identifying a lithium battery equivalent circuit model provided in the second embodiment of the present invention. Figure 4 This is a charge-open circuit voltage curve diagram provided by the second embodiment of the present invention. This second embodiment is refined based on the above embodiment, specifically refining how to use the recursive algorithm to calculate the second set of intermediate parameters. In this embodiment, the identification method includes:

[0185] S210. Determine a frequency domain state equation based on a second-order RC equivalent circuit model of a lithium battery.

[0186] S220: Determine a first set of intermediate parameters based on the internal resistance, polarization resistance, and polarization capacitance of the second-order RC equivalent circuit model of the lithium battery, and determine a second set of intermediate parameters based on the first set of intermediate parameters.

[0187] S230. Determine a discretization recursive formula according to the linear transformation equation.

[0188] Specifically, based on the linear transformation equation: Determine the discretization recursive formula: E k =θ1E k-1 +θ2E k-2 +θ3I k +θ4I k-1 +θ5I k-2 .

[0189] S240: Determine a third group of intermediate parameters according to the second group of intermediate parameters and a discretized recursive formula.

[0190] Specifically, the second set of intermediate parameters θ1, θ2, θ3, θ4 and θ5 and the discrete recursive formula determine the third set of intermediate parameters θ k :

[0191] θ k =[θ1 θ2 θ3 θ4 θ5] T ;

[0192] h k =[E k-1 E k-2 I k I k-1 I k-2 ] T ;

[0193] y k =h k T θ k ;

[0194] The third set of intermediate parameters θ k The second set of intermediate parameters θ1, θ2, θ3, θ4, and θ5 are expressed in the form of a matrix, where k in the formula represents the number of recursions.

[0195] S250 , calculating a third set of intermediate parameters according to the VFFLMRLS algorithm.

[0196] Specifically, the third set of intermediate parameters e is calculated by the VFFLMRLS algorithm k , when we get θ k The second group of intermediate parameters θ1, θ2, θ3, θ4 and θ5 can be obtained.

[0197] S260. Determine, based on the first group of intermediate parameters, the second group of intermediate parameters, and the third group of intermediate parameters, a correspondence between the first group of intermediate parameters and the second group of intermediate parameters, and a correspondence between the parameters in the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters.

[0198] S270: Calculate the error value of the open circuit voltage.

[0199] Specifically, by increasing the number of recursions, the error value of the open circuit voltage is accurately calculated; the error value calculation formula of the open circuit voltage is:

[0200] Optionally, calculate the error value of the open circuit voltage, including:

[0201] Obtain the actual charge capacity value and actual open circuit voltage value through measurement;

[0202] Draw a charge-open circuit voltage curve based on the actual charge capacity value and the actual open circuit voltage value;

[0203] Fitting the charge-open circuit voltage function relationship according to the charge-open circuit voltage curve;

[0204] Determine the open circuit voltage value at any charge capacity value according to the charge-open circuit function relationship;

[0205] The error value of the open circuit voltage is calculated based on the open circuit voltage value.

[0206] Specifically, firstly, the actual charge capacity value and the actual open circuit voltage value are obtained by measuring with an instrument. By performing charge and discharge tests on the lithium battery at different current densities, the actual open circuit voltage values ​​corresponding to different actual charge capacity values ​​are obtained. Figure 4 As shown, the actual charge amount obtained and the actual open circuit voltage value corresponding to the actual charge capacity value are used to draw a charge-open circuit voltage curve, where SOC represents the charge capacity value and OCV represents the open circuit voltage value. The charge-open circuit voltage function relationship is fitted according to the charge-open circuit voltage curve by a polynomial fitting method. Based on different lithium batteries, the drawn charge-open circuit voltage curve is not unique, and therefore the fitted charge-open circuit voltage function relationship is not unique, so the embodiment of the present invention does not limit the specific charge-open circuit voltage function relationship. According to the charge-open circuit voltage function relationship, the open circuit voltage value at any charge capacity can be determined, and the error value of the open circuit voltage is calculated by the error calculation formula.

[0207] S280, determine the initial values ​​of the model parameter vector θ, the covariance matrix P, and the forgetting factor λ; and determine the memory length L.

[0208] Specifically, the parameters involved in the VFFLMRLS algorithm include: model parameter vector θ, covariance matrix P, forgetting factor λ, and memory length L. Setting the initial values ​​of the model parameter vector θ, covariance matrix P, and forgetting factor λ ensures the integrity of the VFFLMRLS algorithm. Setting the memory length L prevents data saturation during the calculation process, ensuring the continued normal operation of the VFFLMRLS algorithm.

[0209] S290 , according to the VFFLMRLS algorithm, performing iterative operations on the error value of the open circuit voltage, the forgetting factor λ, the gain matrix K, the model parameter vector θ, and the covariance matrix P, respectively.

[0210] Among them, the recursive formula for iterative operation is:

[0211]

[0212]

[0213]

[0214]

[0215]

[0216] Among them, the current recursive formula is used to receive new data, and the next level recursive formula is used to remove old data;

[0217] According to the iterative operation results, output the iterative results

[0218] in is the calculated value of the third set of intermediate parameters.

[0219] Specifically, according to the VFFLMRLS algorithm, an iterative operation is performed according to a recursive formula to obtain an iterative result.

[0220] Among them, the recursive formula for iterative operation is:

[0221]

[0222]

[0223]

[0224]

[0225]

[0226] NEXT;

[0227]

[0228]

[0229]

[0230]

[0231]

[0232] The recursive formula before NEXT is used to receive new data, and the recursive formula after NEXT is used to remove old data. By increasing the number of iterations, the calculation error is reduced and the final iterative result is obtained.

[0233] According to the recursive formula of the VFFLMRLS algorithm, the error value of the open circuit voltage, the forgetting factor λ, the gain matrix K, the model parameter vector θ and the covariance matrix P are iteratively calculated. According to the iterative calculation results, the iterative results are output.

[0234] in, is the calculated value of the third set of intermediate parameters, and the third set of intermediate parameters is obtained by obtaining the calculated value of the third set of intermediate parameters. And the third set of intermediate parameters θ k是The second group of intermediate parameters θ1, θ2, θ3, θ4 and θ5 are represented in the form of a matrix, and then specific values ​​of the second group of intermediate parameters are obtained.

[0235] S2100. Determine the parameters of the second-order RC equivalent circuit model of the lithium battery according to the second group of intermediate parameters, the correspondence between the first group of intermediate parameters and the second group of intermediate parameters, and the correspondence between the parameters of the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters.

[0236] In summary, the embodiment of the present invention specifically describes the process of recursively calculating the second intermediate parameter using the VFFLMRLS algorithm, which embodies the advantages of the VFFLMRLS algorithm used in the embodiment of the present invention, that is, the calculation process is simple and data saturation does not occur, thereby ensuring that the identification effect of the second-order RC equivalent circuit model of the lithium battery is better.

[0237] Example 3

[0238] Figure 5 This is a structural diagram of a system for identifying a second-order RC equivalent circuit model of a lithium battery provided in the third embodiment of the present invention. The device is applicable to the situation of equivalent circuit model identification.

[0239] like Figure 5 As shown, the identification system of the second-order RC equivalent circuit model includes: a frequency domain state equation determination module 310, a second set of intermediate parameter setting module 320, a corresponding relationship determination module 330, a second set of intermediate parameter estimation module 340 and a parameter determination module 350.

[0240] The frequency domain state equation determination module 310 is used to determine the frequency domain state equation according to the second-order RC equivalent circuit model:

[0241]

[0242] Among them, U represents the load voltage, Uoc represents the open circuit voltage, I represents the current passing through the load, R0 represents the internal resistance, R1 and R2 represent the polarization resistance, and C1 and C2 represent the polarization capacitance.

[0243] a second set of intermediate parameter setting module 320, configured to determine the first set of intermediate parameters based on the internal resistance, polarization resistance, and polarization capacitance of the second-order RC equivalent circuit model of the lithium battery, and to determine the second set of intermediate parameters based on the first set of intermediate parameters;

[0244] Among them, the first set of intermediate parameters a, b, c, d and e satisfy:

[0245] a=R0;

[0246] b=R1C1R2C2;

[0247] c=R1C1+R2C2;

[0248] d=R0+R1+R2;

[0249] e=R0(R1C1+R2C2)+R1R2C1+R1R2C2;

[0250] The second set of intermediate parameters e1, θ2, θ3, θ4 and θ5 satisfy:

[0251]

[0252]

[0253]

[0254]

[0255]

[0256] Where T is the time period.

[0257] A corresponding relationship determination module 330 is configured to determine, by using a VFFLMRLS algorithm, a corresponding relationship between the first set of intermediate parameters and the second set of intermediate parameters, and a corresponding relationship between parameters in a second-order RC equivalent circuit model of a lithium battery and the first set of intermediate parameters;

[0258] Among them, the corresponding relationship between the first group of intermediate parameters and the second group of intermediate parameters is:

[0259]

[0260]

[0261]

[0262]

[0263]

[0264] The corresponding relationship between the parameters in the second-order RC equivalent circuit model of lithium batteries and the first group of intermediate parameters:

[0265] R0=a;

[0266]

[0267]

[0268] R2 = da - R1;

[0269]

[0270] in,

[0271] The second set of intermediate parameter calculation module 340 is configured to calculate the second set of intermediate parameters using a recursive algorithm according to the VFFLMRLS algorithm and the error value of the open circuit voltage.

[0272] The parameter determination module 350 is used to determine the parameters of the second-order RC equivalent circuit model of the lithium battery based on the second group of intermediate parameters, the correspondence between the first group of intermediate parameters and the second group of intermediate parameters, and the correspondence between the parameters of the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters.

[0273] In summary, the identification system of the second-order RC equivalent circuit model of a lithium battery provided by an embodiment of the present invention first uses a frequency domain state equation determination module to determine the frequency domain state equation of the second-order RC equivalent circuit model; a second group of intermediate parameter setting module is used to determine the first group of intermediate parameters based on the internal resistance, polarization resistance and polarization capacitance of the second-order RC equivalent circuit model of the lithium battery, and determine the second group of intermediate parameters based on the first group of intermediate parameters; a corresponding relationship determination module is used to determine the corresponding relationship between the first group of intermediate parameters and the second group of intermediate parameters, as well as the corresponding relationship between the parameters in the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters through the VFFLMRLS algorithm; a second group of intermediate parameter calculation module is used to calculate the second group of intermediate parameters using a recursive algorithm based on the VFFLMRLS algorithm and the error value of the open circuit voltage. A parameter determination module is used to determine the parameters of the second-order RC equivalent circuit model of the lithium battery based on the second group of intermediate parameters, the corresponding relationship between the first group of intermediate parameters and the second group of intermediate parameters, and the corresponding relationship between the parameters of the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters. Improve the computational accuracy and efficiency of the identification system for the second-order RC equivalent circuit model of lithium batteries.

[0274] Example 4

[0275] Figure 6 is a schematic diagram of the structure of a computing device provided by the fourth embodiment of the present invention, such as Figure 6 As shown, the computing device provided by the embodiment of the present invention includes: one or more processors 41 and a storage device 42; the processor 41 in the device can be one or more, Figure 6 A processor 41 is taken as an example; the storage device 42 is used to store one or more programs; the one or more programs are executed by one or more processors 41, so that the one or more processors 41 implement the identification method of the lithium battery equivalent circuit model as any one of the embodiments of the present invention.

[0276] The processor 41, storage device 42, input device 43 and output device 44 in the device can be connected via a bus or other means. Figure 6 The bus connection is taken as an example.

[0277] The storage device 42 in the device is a computer-readable storage medium that can be used to store one or more programs. The program can be a software program, a computer executable program, and a module, such as the program instructions / modules corresponding to the identification method of the second-order RC equivalent circuit model of a lithium battery provided in an embodiment of the present invention (for example, the attached Figure 5 The modules in the device shown include: a frequency-domain state equation determination module 310, a second set of intermediate parameter determination module 320, a correspondence relationship determination module 330, a second set of intermediate parameter estimation module 340, and a parameter determination module 350. The processor 41 executes the software programs, instructions, and modules stored in the storage device 42 to execute various functional applications and data processing of the terminal device, thereby implementing the lithium battery circuit model identification method in the above-mentioned method embodiment.

[0278] The storage device 42 may include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function; the data storage area may store data generated based on the use of the device, etc. Furthermore, the storage device 42 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state memory device. In some instances, the storage device 42 may further include a memory remotely located relative to the processor 41, and such remote memory may be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0279] The input device 43 may be used to receive input digital or character information and generate key signal input related to user settings and function control of the device. The output device 44 may include a display device such as a display screen.

[0280] Moreover, when one or more programs included in the above-mentioned device are executed by one or more processors 41, the program performs the following operations: determining the frequency domain state equation of the lithium battery circuit model; determining the first group of intermediate parameters according to the internal resistance, polarization resistance and polarization capacitance of the second-order RC equivalent circuit model of the lithium battery, and determining the second group of intermediate parameters according to the first group of intermediate parameters; determining the correspondence between the first group of intermediate parameters and the second group of intermediate parameters, as well as the correspondence between the parameters in the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters through the VFFLMRLS algorithm; calculating the second group of intermediate parameters using a recursive algorithm based on the VFFLMRLS algorithm and the error value of the open-circuit voltage; determining the parameters of the second-order RC equivalent circuit model of the lithium battery according to the second group of intermediate parameters, the correspondence between the first group of intermediate parameters and the second group of intermediate parameters, and the correspondence between the parameters of the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters.

[0281] Example 5

[0282] Embodiment 5 of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is used to execute a method for identifying a lithium battery equivalent circuit model, the method comprising: determining a frequency domain state equation based on a second-order RC equivalent circuit model of a lithium battery; determining a first group of intermediate parameters based on the internal resistance, polarization resistance, and polarization capacitance of the second-order RC equivalent circuit model of the lithium battery, and determining a second group of intermediate parameters based on the first group of intermediate parameters; determining a correspondence between the first group of intermediate parameters and the second group of intermediate parameters, as well as a correspondence between the parameters in the second-order RC equivalent circuit model and the first group of intermediate parameters through a VFFLMRLS algorithm; calculating the second group of intermediate parameters using a recursive algorithm based on the VFFLMRLS algorithm and an error value of the open-circuit voltage; determining the parameters of the second-order RC equivalent circuit model of the lithium battery based on the second group of intermediate parameters, the correspondence between the first group of intermediate parameters and the second group of intermediate parameters, and the correspondence between the parameters of the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters.

[0283] Optionally, when the program is executed by a processor, it can also be used to execute the lithium battery equivalent circuit model identification method provided by any embodiment of the present invention.

[0284] The computer storage medium of the embodiment of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable CD-ROM, an optical storage device, a magnetic storage device, or any suitable combination thereof. The computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or device.

[0285] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such a propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0286] The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wire, optical cable, radio frequency (RF), etc., or any suitable combination of the foregoing.

[0287] Computer program code for performing the operations of the present invention may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0288] The above is the core concept of the present invention. The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0289] Note that the above are only preferred embodiments of the present invention and the technical principles employed. Those skilled in the art will appreciate that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments, combinations, and substitutions are possible for those skilled in the art without departing from the scope of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments and may include many other equivalent embodiments without departing from the scope of the present invention. The scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for identifying a lithium battery equivalent circuit model, characterized in that: include: Determine the frequency domain state equation based on the second-order RC equivalent circuit model of the lithium battery; Where U represents the load voltage, Uoc represents the open circuit voltage, I represents the current through the load, R0 represents the internal resistance, R1 and R2 represent the polarization resistance, and C1 and C2 represent the polarization capacitance. Determining a first set of intermediate parameters based on the internal resistance, polarization resistance, and polarization capacitance of the second-order RC equivalent circuit model of the lithium battery, and determining a second set of intermediate parameters based on the first set of intermediate parameters; Wherein, the first set of intermediate parameters a, b, c, d and e satisfy: a=R0; b=R1C1R2C2; c=R1C1+R2C2; d=R0+R1+R2; e=R0(R1C1+R2C2)+R1R2C1+R1R2C2; The second set of intermediate parameters θ1, θ2, θ3, θ4 and θ5 satisfy: Where T is the time period; Determine, by using a VFFLMRLS algorithm, a correspondence between the first set of intermediate parameters and the second set of intermediate parameters, and a correspondence between parameters in the second-order RC equivalent circuit model of the lithium battery and the first set of intermediate parameters; The corresponding relationship between the first set of intermediate parameters and the second set of intermediate parameters satisfies: The corresponding relationship between the parameters in the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters satisfies: in, Calculating the second set of intermediate parameters using a recursive algorithm according to the VFFLMRLS algorithm and an error value of the open circuit voltage; Determine the parameters of the second-order RC equivalent circuit model of the lithium battery according to the second group of intermediate parameters, the correspondence between the first group of intermediate parameters and the second group of intermediate parameters, and the correspondence between the parameters of the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters.

2. The identification method according to claim 1, characterized in that: Before determining the corresponding relationship between the first group of intermediate parameters and the second group of intermediate parameters, and the corresponding relationship between the parameters in the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters through the VFFLMRLS algorithm, the method further includes: Determine the discretization recursive formula based on the linear transformation equation: E k =θ1E k-1 +θ2E k-2 +θ3I k +θ4I k-1 +θ5I k-2 ; determining a third group of intermediate parameters according to the second group of intermediate parameters and the discretization recursive formula; i k =[θ1 θ2 θ3 θ4 θ5] T ; h k =[E k-1 E k-2 I k I k-1 I k-2 ] T ; y k =h k T θ k ; Determining, by the VFFLMRLS algorithm, a correspondence between the first set of intermediate parameters and the second set of intermediate parameters, and a correspondence between parameters in the second-order RC equivalent circuit model of the lithium battery and the first set of intermediate parameters, including: Calculating the third set of intermediate parameters according to the VFFLMRLS algorithm; Determine the correspondence between the first group of intermediate parameters and the second group of intermediate parameters, and the correspondence between the parameters in the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters based on the first group of intermediate parameters, the second group of intermediate parameters, and the third group of intermediate parameters.

3. The identification method according to claim 1, characterized in that: Before determining a first set of intermediate parameters based on the internal resistance, polarization resistance, and polarization capacitance of the second-order RC equivalent circuit model of the lithium battery and determining a second set of intermediate parameters based on the first set of intermediate parameters, the method further includes: Performing a linear transformation on the frequency domain state equation to obtain a linear transformation equation; Wherein, θ1, θ2, θ3, θ4 and θ5 are the second set of intermediate parameters; the deformation equation of the frequency domain state mode is determined according to the frequency domain state equation; determining a linear transformation equation based on the first transformation parameter and the second transformation parameter; Among them, the first transformation parameter G( S )satisfy: The second transformation parameter s satisfies:

4. The identification method according to claim 1, wherein: Before calculating the second set of intermediate parameters using a recursive algorithm based on the VFFLMRLS algorithm and the error value of the open circuit voltage, the method further includes: Calculating an error value of the open circuit voltage; 5. The identification method according to claim 4, characterized in that: Calculating the error value of the open circuit voltage includes: Obtain the actual charge capacity value and actual open circuit voltage value through measurement; Draw a charge-open circuit voltage curve according to the actual charge capacity value and the actual open circuit voltage value; Fitting a charge-open circuit voltage function relationship according to the charge-open circuit voltage curve; Determine the open circuit voltage value at any charge capacity value according to the charge-open circuit function relationship; An error value of the open circuit voltage is calculated according to the open circuit voltage value.

6. The identification method according to claim 1, characterized in that: Before calculating the second set of intermediate parameters using a recursive algorithm based on the VFFLMRLS algorithm and the error value of the open circuit voltage, the method further includes: Determine the initial values ​​of the model parameter vector θ, the covariance matrix P, and the forgetting factor λ; Determine the memory length L; Calculating the second set of intermediate parameters using a recursive algorithm according to the VFFLMRLS algorithm and the error value of the open circuit voltage includes: According to the VFFLMRLS algorithm, iterative operations are performed on the error value of the open circuit voltage, the forgetting factor λ, the gain matrix K, the model parameter vector θ, and the covariance matrix P respectively; Among them, the recursive formula for iterative operation is: The current recursive formula is used to receive new data, and the next level recursive formula is used to remove old data; According to the iterative operation results, output the iterative results in is the calculated value of the third set of intermediate parameters.

7. The identification method according to claim 1, characterized in that: The frequency domain state equation is determined based on the second-order RC equivalent circuit model of the lithium battery, including: Determine the time domain state equation of the second-order RC equivalent circuit model of the lithium battery according to Kirchhoff's current law and Kirchhoff's voltage law; Wherein, the time domain state equation satisfies: You=You OC -IR-U1-U2; l=U1 / R1+C1(dU1 / d t ); I=U2 / R2+C2(dU2 / d t ); According to the time-domain state equation, the frequency-domain state equation of the second-order RC equivalent circuit model of the lithium battery is determined using Laplace transform.

8. A lithium battery second-order RC equivalent circuit model identification system, characterized in that: include: The frequency domain state equation determination module is used to determine the frequency domain state equation based on the second-order RC equivalent circuit model of the lithium battery: Where U represents the load voltage, Uoc represents the open circuit voltage, I represents the current through the load, R0 represents the internal resistance, R1 and R2 represent the polarization resistance, and C1 and C2 represent the polarization capacitance. a second set of intermediate parameter setting module, configured to determine the first set of intermediate parameters according to the internal resistance, polarization resistance, and polarization capacitance of the second-order RC equivalent circuit model of the lithium battery, and determine the second set of intermediate parameters according to the first set of intermediate parameters; The first set of intermediate parameters a, b, c, d and e satisfy: a=R0; b=R1C1R2C2; c=R1C1+R2C2; d=R0+R1+R2; e=R0(R1C1+R2C2)+R1R2C1+R1R2C2; The second set of intermediate parameters θ1, θ2, θ3, θ4 and θ5 satisfy: Where T is the time period; a corresponding relationship determining module, configured to determine, by using a VFFLMRLS algorithm, a corresponding relationship between the first group of intermediate parameters and the second group of intermediate parameters, and a corresponding relationship between parameters in the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters; The corresponding relationship between the first set of intermediate parameters and the second set of intermediate parameters satisfies: The corresponding relationship between the parameters in the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters satisfies: in, a second group of intermediate parameter calculation module, configured to calculate the second group of intermediate parameters using a recursive algorithm based on the VFFLMRLS algorithm and an error value of the open circuit voltage; A parameter determination module is used to determine the parameters of the second-order RC equivalent circuit model of the lithium battery based on the second group of intermediate parameters, the correspondence between the first group of intermediate parameters and the second group of intermediate parameters, and the correspondence between the parameters of the second-order RC equivalent circuit model of the lithium battery and the first group of intermediate parameters.

9. A computing device, characterized in that The computing device comprises: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement a method for identifying a lithium battery equivalent circuit model as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for identifying a lithium battery equivalent circuit model as described in any one of claims 1 to 7 is implemented.

Images