Parameter analysis method for energy storage battery and electronic equipment

Abstract

The invention relates to the technical field of batteries, in particular to a parameter analysis method for an energy storage battery and electronic equipment. According to the bearing fault diagnosis method provided by the embodiment of the invention, a mixed pulse power test is carried out on a target energy storage battery to obtain a battery polarization parameter; constructing a polarization characterization model based on the battery polarization parameters; carrying out a hysteresis loop test on the target energy storage battery to obtain a voltage capacity distribution parameter; constructing a hysteresis voltage characterization model based on the voltage capacity distribution parameters; performing equivalent modeling on the target energy storage battery according to the hysteresis voltage characterization model and the polarization characterization model to obtain a target equivalent circuit model; and performing battery characteristic parameter prediction based on the target equivalent circuit model to obtain a target battery prediction parameter. Therefore, the accuracy of predicting the characteristic parameters of the energy storage battery can be improved.

Description

Technical Field

[0001] The present application relates to the field of battery technology, and in particular to a parameter analysis method and electronic equipment for energy storage batteries. Background Art

[0002] The equivalent circuit model of energy storage batteries is a technical means to simulate and analyze the electrochemical behavior and performance of lithium batteries during the charging and discharging process. The equivalent circuit model simulates the electrochemical behavior, dynamic response, and voltage and current characteristics of the battery during the charging and discharging process by equating the complex electrochemical reactions inside the battery to a combination of a series of circuit elements (including voltage source, ohmic internal resistance, polarization internal resistance, and capacitor, etc.).

[0003] Traditional equivalent circuit models are usually Rint model, Thévenin model, Shepherd model or KiBaM model, etc. However, the Rint model ignores the transient characteristics of the battery under current excitation, and there are large deviations in the battery charging and discharging process; Thevenin model is still not accurate enough in capturing high-frequency response, multi-stage polarization phenomena and complex dynamic behaviors under fast charging and discharging conditions, and has deficiencies in dealing with the hysteresis effect of the battery, and cannot accurately describe the hysteresis phenomenon of the voltage-capacity curve; the Shepherd model and the KiBaM model both fail to fully consider the hysteresis effect of the battery, and cannot accurately reflect complex phenomena such as concentration polarization and electrochemical polarization, resulting in inaccurate prediction of energy storage battery characteristic parameters. Therefore, how to improve the accuracy of energy storage battery characteristic parameter prediction has become an urgent problem to be solved. Summary of the invention

[0004] The main purpose of the embodiments of the present application is to provide a parameter analysis method and electronic device for energy storage batteries, aiming to improve the accuracy of prediction of characteristic parameters of energy storage batteries.

[0005] To achieve the above-mentioned purpose, a first aspect of an embodiment of the present application proposes a parameter analysis method for an energy storage battery, the method comprising:

[0006] Conduct mixed pulse power test on target energy storage battery to obtain battery polarization parameters;

[0007] Constructing a polarization characterization model based on the battery polarization parameters;

[0008] Performing a hysteresis loop test on the target energy storage battery to obtain voltage capacity distribution parameters;

[0009] Constructing a hysteresis voltage characterization model based on the voltage capacity distribution parameters;

[0010] Performing equivalent modeling on the target energy storage battery according to the hysteresis voltage characterization model and the polarization characterization model to obtain a target equivalent circuit model;

[0011] Battery characteristic parameters are predicted based on the target equivalent circuit model to obtain target battery prediction parameters.

[0012] In some embodiments, performing equivalent modeling on the target energy storage battery according to the hysteresis voltage characterization model and the polarization characterization model to obtain a target equivalent circuit model includes:

[0013] Constructing an initial equivalent circuit model of the target energy storage battery based on the hysteresis voltage characterization model and the polarization characterization model;

[0014] A circuit stability test is performed on the initial equivalent circuit model to obtain the target equivalent circuit model.

[0015] In some embodiments, performing a circuit stability test on the initial equivalent circuit model to obtain the target equivalent circuit model includes:

[0016] Acquire a plurality of experimental voltage point pairs corresponding to the initial equivalent circuit model, and determine at least two target experimental voltage point pairs from the plurality of experimental voltage point pairs;

[0017] Calculating corresponding point pair state prediction data for each target experimental voltage point pair;

[0018] In response to each of the point pair state prediction data satisfying a preset voltage state change condition, the initial equivalent circuit model is used as the target equivalent circuit model.

[0019] In some embodiments, the step of calculating the corresponding point pair state prediction data for each target experimental voltage point pair includes:

[0020] Obtaining a target experimental current point pair corresponding to the target experimental voltage point pair within a preset time step;

[0021] Calculate the slope corresponding to each time step according to the target experimental voltage point pair and the target experimental current point pair;

[0022] The voltage change state of the target experimental voltage point pair is predicted according to the slope of each time step to obtain the point pair state prediction data.

[0023] In some embodiments, constructing a hysteresis voltage characterization model based on the voltage capacity distribution parameter includes:

[0024] Acquire a charge parameter of the target energy storage battery, and determine a charge terminal voltage of the target energy storage battery based on Kirchhoff's voltage law and the charge parameter;

[0025] Determining an instantaneous hysteresis voltage and a discretized hysteresis voltage of the target energy storage battery based on a charge parameter of the target energy storage battery;

[0026] determining a target hysteresis voltage based on the instantaneous hysteresis voltage and the discretized hysteresis voltage;

[0027] Determining a hysteresis factor according to the voltage capacity distribution parameter;

[0028] The hysteresis voltage characterization model is constructed based on the hysteresis factor, the target hysteresis voltage and the charged terminal voltage.

[0029] In some embodiments, determining the instantaneous hysteresis voltage and the discretized hysteresis voltage of the target energy storage battery based on the charge parameter of the target energy storage battery includes:

[0030] Acquire the state of charge in the charge parameter and the state of charge derivative of the state of charge, and determine a hysteresis voltage charge correlation expression according to the state of charge and the state of charge derivative;

[0031] Derivative the hysteresis voltage charge correlation expression to obtain a hysteresis voltage derivative expression;

[0032] Discretizing the hysteresis voltage derivative expression to obtain the discretized hysteresis voltage;

[0033] Obtaining a current change state of the target energy storage battery in a preset detection time slot;

[0034] Based on the current change state in the detection time slot, the instantaneous hysteresis voltage of the target energy storage battery is determined.

[0035] In some embodiments, performing a mixed pulse power test on a target energy storage battery to obtain a battery polarization parameter includes:

[0036] Performing a first mixed pulse power test on the target energy storage battery to obtain the ohmic resistance of the target energy storage battery;

[0037] Performing a second mixed pulse power test on the target energy storage battery to obtain a polarization resistance and a concentration polarization resistance of the target energy storage battery;

[0038] The battery polarization parameter is determined based on the ohmic resistance, the polarization resistance, and the concentration polarization resistance.

[0039] In some embodiments, constructing a polarization characterization model based on the battery polarization parameters includes:

[0040] Obtaining an initial open circuit voltage of the energy storage battery;

[0041] The polarization characterization model is constructed according to the initial open circuit voltage and the battery polarization parameters.

[0042] In some embodiments, performing a hysteresis loop test on the target energy storage battery to obtain voltage capacity distribution parameters includes:

[0043] Performing a hysteresis main loop test on the target energy storage battery to obtain a global voltage capacity distribution parameter;

[0044] Performing a hysteresis small loop test on the target energy storage battery to obtain a local voltage capacity distribution parameter;

[0045] The global voltage-capacity distribution parameter is updated by using the local voltage-capacity distribution parameter to obtain the voltage-capacity distribution parameter.

[0046] To achieve the above-mentioned purpose, the second aspect of an embodiment of the present application proposes an electronic device, which includes a memory and a processor, the memory stores a computer program, and the processor implements the method described in the first aspect when executing the computer program.

[0047] The parameter analysis method and electronic device for energy storage batteries according to the embodiments of the present application have at least the following beneficial effects:

[0048] By performing a mixed pulse power test on the target energy storage battery, the battery polarization parameters are obtained; a polarization characterization model is constructed based on the battery polarization parameters; a hysteresis loop test is performed on the target energy storage battery to obtain the voltage capacity distribution parameters; a hysteresis voltage characterization model is constructed based on the voltage capacity distribution parameters; the target energy storage battery is equivalently modeled according to the hysteresis voltage characterization model and the polarization characterization model to obtain the target equivalent circuit model; the battery characteristic parameters are predicted based on the target equivalent circuit model to obtain the target battery prediction parameters. In this way, the accuracy of the prediction of the characteristic parameters of the energy storage battery can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 is a flow chart of a parameter analysis method for an energy storage battery provided in an embodiment of the present application;

[0050] Figure 2 It is a pulse current-time and open circuit voltage-time curve variation diagram of a hybrid pulse power test on a target energy storage battery in an embodiment of the present application;

[0051] Figure 3 yes Figure 1 Flow chart of step S104 in FIG.

[0052] Figure 4 yes Figure 3 Flow chart of step S302 in FIG.

[0053] Figure 5 yes Figure 1 Flow chart of step S105 in FIG.

[0054] Figure 6 yes Figure 5 Flow chart of step S502 in FIG.

[0055] Figure 7 yes Figure 6 Flowchart of step S602 in FIG.

[0056] Figure 8 is a schematic diagram of the structure of the target equivalent circuit model provided in the embodiment of the present application;

[0057] Fig. 9 is a battery characteristic parameter prediction flow chart provided in an embodiment of the present application;

[0058] Fig.10 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0060] It should be noted that if the embodiments of the present application involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components in a certain specific posture. If the specific posture changes, the directional indication will also change accordingly.

[0061] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present application, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features limited to "first" and "second" may explicitly or implicitly include at least one of the features. In addition, if "and / or" or "and / or" appears in the full text, its meaning includes three parallel schemes. Taking "A and / or B" as an example, it includes scheme A, or scheme B, or a scheme that satisfies both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in the field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0062] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0063] The equivalent circuit model of energy storage batteries is a technical means to simulate and analyze the electrochemical behavior and performance of lithium batteries during the charging and discharging process. The equivalent circuit model simulates the electrochemical behavior, dynamic response, and voltage and current characteristics of the battery during the charging and discharging process by equating the complex electrochemical reactions inside the battery to a combination of a series of circuit elements (including voltage source, ohmic internal resistance, polarization internal resistance, and capacitor, etc.).

[0064] Traditional equivalent circuit models are usually Rint model, Thévenin model, Shepherd model or KiBaM model, etc. However, the Rint model ignores the transient characteristics of the battery under current excitation, and there are large deviations in the battery charging and discharging process; Thevenin model is still not accurate enough in capturing high-frequency response, multi-stage polarization phenomena and complex dynamic behaviors under fast charging and discharging conditions, and has deficiencies in dealing with the hysteresis effect of the battery, and cannot accurately describe the hysteresis phenomenon of the voltage-capacity curve; the Shepherd model and the KiBaM model both fail to fully consider the hysteresis effect of the battery, and cannot accurately reflect complex phenomena such as concentration polarization and electrochemical polarization, resulting in inaccurate prediction of energy storage battery characteristic parameters. Therefore, how to improve the accuracy of energy storage battery characteristic parameter prediction has become an urgent problem to be solved.

[0065] Therefore, an equivalent circuit model constructed based on the hysteresis voltage characterization model and the polarization characterization model is used to predict the battery characteristic parameters, which can effectively consider the polarization effect and hysteresis effect generated by the energy storage battery during the charging and discharging process, and contribute to the accuracy of the prediction of the energy storage battery characteristic parameters.

[0066] The following description is based on the accompanying drawings.

[0067] Reference Figure 1 According to the embodiment of the present application, the parameter analysis method for the energy storage battery may include, but is not limited to:

[0068] Step S101, performing a mixed pulse power test on a target energy storage battery to obtain battery polarization parameters;

[0069] Step S102, constructing a polarization characterization model based on battery polarization parameters;

[0070] Step S103, performing a hysteresis loop test on the target energy storage battery to obtain voltage capacity distribution parameters;

[0071] Step S104, constructing a hysteresis voltage characterization model based on the voltage capacity distribution parameters;

[0072] Step S105, performing equivalent modeling on the target energy storage battery according to the hysteresis voltage characterization model and the polarization characterization model to obtain a target equivalent circuit model;

[0073] Step S106, predicting battery characteristic parameters based on the target equivalent circuit model to obtain target battery prediction parameters.

[0074] The parameter analysis method for energy storage batteries shown in step S101 to step S106 of the embodiment of the present application requires that the target energy storage battery be subjected to a mixed pulse power test to obtain battery polarization parameters; a polarization characterization model be constructed based on the battery polarization parameters; a hysteresis loop test be conducted on the target energy storage battery to obtain voltage capacity distribution parameters; a hysteresis voltage characterization model be constructed based on the voltage capacity distribution parameters; an equivalent modeling be conducted on the target energy storage battery according to the hysteresis voltage characterization model and the polarization characterization model to obtain a target equivalent circuit model; and a battery characteristic parameter prediction be conducted based on the target equivalent circuit model to obtain target battery prediction parameters. In this way, the accuracy of the prediction of the characteristic parameters of the energy storage battery can be improved.

[0075] In step S101 of some embodiments, the battery polarization parameters may include but are not limited to ohmic resistance, polarization resistance, concentration polarization resistance, a first polarization time constant, a second polarization time constant, and the like.

[0076] Specifically, the battery polarization parameters are obtained by performing a mixed pulse power test on the target energy storage battery, which may include, but are not limited to: performing a first mixed pulse power test on the target energy storage battery to obtain the ohmic resistance of the target energy storage battery; performing a second mixed pulse power test on the target energy storage battery to obtain the polarization resistance and concentration polarization resistance of the target energy storage battery; and determining the battery polarization parameters based on the ohmic resistance, polarization resistance and concentration polarization resistance.

[0077] Specifically, the ohmic resistance is the inherent resistance inside the target energy storage battery, which is the reason why the open circuit voltage of the battery drops when discharging.

[0078] Furthermore, the first hybrid pulse power test is used to test the discharge process of the target energy storage battery. In the test, a discharge pulse current is applied to the battery until the current stops so that the electrochemical reaction inside the battery reaches a state of equilibrium, and the ohmic resistance of the battery can be calculated by measuring the voltage drop during the discharge pulse.

[0079] Specifically, ohmic resistance can be expressed by the following formula:

[0080]

[0081] Where R0 represents the ohmic resistance, V oc V1 represents the open circuit voltage when no discharge pulse current is applied, V2 represents the open circuit voltage after the discharge pulse current is applied, and I represents the pulse current.

[0082] Specifically, polarization resistance is due to the limited electrochemical reaction rate on the electrode surface. When the current density is large, the electrochemical reaction cannot proceed in time, causing the electrode potential to deviate from the equilibrium potential, thereby causing voltage resistance. Concentration polarization resistance refers to the resistance caused by the uneven migration of lithium ions inside the target energy storage battery during the charging process, resulting in a difference in lithium ion concentration between the electrode surface and the interior, causing voltage changes.

[0083] Furthermore, the second mixed pulse power test is used to test the discharge process of the target energy storage battery. In the charging pulse test, a charging pulse current is applied to the energy storage battery, and the charging pulse current is equal to the discharge pulse current until the current stops. By analyzing the voltage rise during the charging pulse, the polarization resistance can be determined. And when the charging pulse stops, the charging state remains constant, and the battery voltage begins to increase slowly. This is because when the current stops, there are different lithium ion concentration gradients in the entire battery, so the concentration polarization resistance can be determined by the voltage change when the current stops.

[0084] Specifically, the polarization resistance can be determined by the following formula:

[0085]

[0086] Among them, R1 represents the polarization resistance, V3 represents the open circuit voltage after the charging pulse current is applied, V2 represents the open circuit voltage after the charging pulse current is just applied, and I represents the pulse current.

[0087] Specifically, the concentration polarization resistance can be determined by the following formula:

[0088]

[0089] Among them, R2 represents the concentration polarization resistance, V4 represents the open circuit voltage reached at a constant level during the charging process, V3 represents the open circuit voltage after the charging pulse current is applied, and I represents the pulse current.

[0090] In this embodiment, by performing a second mixed pulse power test on the target energy storage battery, the voltage drop caused by electrochemical polarization and concentration polarization of the target energy storage battery during charging can be simulated, which helps the subsequent equivalent circuit to consider the influence of electrochemical polarization and concentration polarization.

[0091] Specifically, the battery polarization parameters are the basis for constructing the battery equivalent circuit model, and directly affect the simulation accuracy of the equivalent circuit model for the target energy storage battery. Among them, the battery polarization parameters include the first polarization time constant, which refers to the polarization time constant corresponding to the first parallel RC pair in the equivalent circuit, and the second polarization time constant, which refers to the polarization time constant corresponding to the second parallel RC pair.

[0092] Specifically, the first polarization time constant can be expressed by the following formula:

[0093] τ1=R1C1

[0094] Wherein, τ1 represents the first polarization time constant, R1 represents the polarization resistance, and C1 represents the polarization capacitance.

[0095] Specifically, the second polarization time constant can be expressed by the following formula:

[0096] τ2=R2C2

[0097] Wherein, τ2 represents the second polarization time constant, R2 represents the concentration polarization resistance, and C2 represents the concentration polarization capacitance.

[0098] refer to Figure 2 In the above figure, the horizontal axis represents time (Time / s) and the vertical axis represents pulse current (A). The figure shows that at the 6th second, the discharge pulse current begins to be applied, and the current increases from 0A to -2A until the 38th second when the entire discharge process ends. The amplitude of the current change at the end of the discharge process is represented by ΔI. At the 38th second, the charging pulse current begins to be applied, and the current returns from -2A to 0A. The charging pulse current is applied again at the 80th second, and the current stops at the 90th second.

[0099] refer to Figure 2 In the figure below, the horizontal axis represents time (s) and the vertical axis represents open circuit voltage (V). The figure shows that when the discharge pulse current is applied at the 6th second, the open circuit voltage drops from Voc to V o ' c, and further dropped to V1 when the discharge pulse current tended to be stable, reflecting the internal resistance effect of the energy storage battery, and when the charging pulse current was applied at the 38th second, the open circuit voltage gradually recovered to V2, and when the current gradually stabilized, the open circuit voltage gradually recovered to V3, reflecting the polarization effect of the energy storage battery. At the 80th second, the charging pulse current was applied again, causing the open circuit voltage to gradually recover to V4, reflecting the concentration polarization effect of the energy storage battery.

[0100] In step S102 of some embodiments, specifically, the polarization characterization model is used to analyze the influence of the polarization effect on the equivalent circuit.

[0101] Specifically, constructing a polarization characterization model based on battery polarization parameters may include: obtaining an initial open circuit voltage of the energy storage battery; and constructing a polarization characterization model according to the initial open circuit voltage and the battery polarization parameters.

[0102] Specifically, the initial open circuit voltage refers to the voltage of the energy storage battery when no pulse current is applied.

[0103] Further, the polarization characterization model can be constructed by the initial open circuit voltage data and the polarization resistance and concentration polarization resistance obtained by the first and second mixed pulse power tests. In the polarization characterization model process, the polarization resistance and concentration polarization resistance are integrated into the equivalent circuit model, and the polarization effect of the battery is simulated by adding a parallel RC pair, which consists of a resistor and a capacitor, and the values ​​of the polarization resistance and the concentration polarization resistance are used to determine the resistance value of the RC pair.

[0104] In addition, the polarization characterization model also includes a polarization time constant, which is determined by the resistance and capacitance values ​​of the RC pair, and the polarization time constant will affect the voltage change rate of the energy storage battery.

[0105] Specifically, the polarization characterization model can be expressed by the following formula:

[0106]

[0107] Among them, U P represents the polarization representation model, U oc represents the initial open circuit voltage, R0 represents the ohmic resistance, I represents the pulse current, Δt1 represents the discharge time interval, Δt2 represents the charging time interval, R1 represents the polarization resistance, Δt2 represents the charging time interval, C1 represents the polarization capacitance, R2 represents the concentration polarization resistance, and C2 represents the concentration polarization capacitance.

[0108] In this embodiment, a polarization characterization model is constructed according to the initial open circuit voltage and the battery polarization parameters, which can accurately simulate and predict the voltage drop of the energy storage battery during the charging and discharging process. In combination with the polarization time constant during the charging and discharging process, the behavior characteristics of the energy storage battery at different charging and discharging rates can be more accurately simulated, which helps to improve the accuracy of the subsequent construction of the equivalent circuit model.

[0109] In step S103 of some embodiments, the voltage-capacity distribution parameters refer to the voltage and charge variation parameters of the energy storage battery after being updated during a complete charge and discharge cycle.

[0110] Specifically, the voltage-capacity distribution parameters are obtained by performing a hysteresis loop test on the target energy storage battery, which may include: performing a hysteresis main loop test on the target energy storage battery to obtain a global voltage-capacity distribution parameter; performing a hysteresis small loop test on the target energy storage battery to obtain a local voltage-capacity distribution parameter; and updating the global voltage-capacity distribution parameter by the local voltage-capacity distribution parameter to obtain the voltage-capacity distribution parameter.

[0111] Specifically, the global voltage capacity distribution parameters refer to the voltage and charge change parameters of the energy storage battery during a complete charge and discharge cycle.

[0112] Specifically, the local voltage capacity distribution parameters refer to the voltage and charge change parameters of the energy storage battery during the local charge and discharge cycle.

[0113] Furthermore, the hysteresis main loop test refers to the test of the relationship between voltage and capacity in a complete charge and discharge cycle. By discharging the energy storage battery after fully charging it, and recording the voltage and charge data during the discharge process, the global voltage and capacity distribution parameters can be obtained. The global voltage and capacity distribution parameters can be used to represent the voltage changes of the energy storage battery under different charges.

[0114] Furthermore, the hysteresis small loop test refers to the test of the relationship between voltage and capacity in the local charge and discharge cycle. During the charge and discharge process of the energy storage battery, the current changes frequently, which will form some small loops in the hysteresis main loop, namely the hysteresis small loop. By applying a small current pulse during the battery charge and discharge process and briefly resting between the pulses, the voltage change of the battery in the local charge and discharge cycle can be captured. The hysteresis small loop test is to determine the SOC accumulation required for the open circuit voltage to complete a complete conversion of charge and discharge in the hysteresis main loop.

[0115] Furthermore, by integrating the local voltage-capacity distribution parameters into the global voltage-capacity distribution parameters, more accurate voltage-capacity distribution parameters in the complete charge-discharge cycle can be obtained.

[0116] In one embodiment of the present application, the specific steps of the hysteresis main loop test may be: first, the energy storage battery is fully discharged and then left to stand for 2 hours; secondly, under the condition of a constant current pulse at a rate of 0.2C, the energy storage battery is gradually charged with a charging depth of △SOC=0.1, and left to stand for 1 hour until SOC=0.1; finally, after charging is completed, the energy storage battery is gradually discharged with the same charging C rate, △SOC and standing time until SOC=0, and during this process, the open circuit voltage and charge parameters are collected every 1s.

[0117] Furthermore, the specific steps of the hysteresis small loop test can be: first, after the energy storage battery is fully charged, it is left to stand for 2 hours, and under the condition of a constant current pulse at a rate of 1C, the energy storage battery is discharged at a discharge depth of △SOC=0.2, that is, when the SOC decreases by 0.2, the discharge stops; secondly, under the condition of a constant current pulse at a rate of 1C, the energy storage battery is charged at a charging depth of △SOC=0.1, that is, when the SOC increases by 0.1, the charging stops, and the charging and discharging steps are repeated until SOC=0.

[0118] In this embodiment, the global voltage capacity distribution parameters are updated through local voltage capacity distribution parameters to obtain voltage capacity distribution parameters, which can not only capture the voltage capacity distribution parameters of the energy storage battery in a stable state, but also simulate the voltage and charge changes of the energy storage battery during the dynamic charging and discharging process, providing data support for the subsequent consideration of the hysteresis effect, and helping to improve the accuracy of the subsequent equivalent circuit model construction.

[0119] refer to Figure 3 According to some embodiments of the present application, step S104 constructs a hysteresis voltage characterization model based on the voltage capacity distribution parameter, which may include, but is not limited to:

[0120] Step S301, acquiring a charge parameter of a target energy storage battery, and determining a charge terminal voltage of the target energy storage battery based on Kirchhoff's voltage law and the charge parameter;

[0121] Step S302, determining an instantaneous hysteresis voltage and a discretized hysteresis voltage of the target energy storage battery based on the charge parameters of the target energy storage battery;

[0122] Step S303, determining a target hysteresis voltage based on the instantaneous hysteresis voltage and the discretized hysteresis voltage;

[0123] Step S304, determining a hysteresis factor according to the voltage capacity distribution parameter;

[0124] Step S305: constructing a hysteresis voltage characterization model based on the hysteresis factor, the target hysteresis voltage and the charged terminal voltage.

[0125] In step S301 of some embodiments, specifically, the charging parameters include but are not limited to the charging state at different times and different time steps, the total charge capacity consumed, the voltage of two parallel RC pairs, the open circuit voltage corresponding to the charging state, the voltage on the ohmic resistor, etc.

[0126] Specifically, the state of charge at different times can be first determined, and the determined state of charge can be further discretized based on a preset sampling period and a Coulomb efficiency factor to obtain the state of charge at different time steps after discretization. Finally, Kirchhoff's voltage law is used to describe the influence between the state of charge at different times and its corresponding open-circuit voltage, the voltage of two parallel RC pairs, and the voltage of the ohmic resistor, so as to determine the charge terminal voltage corresponding to the state of charge of the energy storage battery at any time.

[0127] Specifically, the state of charge at different times can be expressed by the following formula:

[0128]

[0129] Among them, SOC(t) represents the state of charge at time t, SOC(t0) represents the state of charge at the initial time t0, C n represents the total charge capacity consumed when discharging the battery from SOC(t)=1 to SOC(t)=0, and i(w) represents the current of the target energy storage battery at time w. Among them, SOC(t)=1 represents the state of charge when the target energy storage battery is fully charged, and SOC(t)=0 represents the state of charge when the target energy storage battery is fully discharged.

[0130] Specifically, the state of charge at different time steps after discretization can be expressed by the following formula:

[0131]

[0132] Among them, SOC k+1 Indicates the state of charge at the k+1th time step, SOC k represents the state of charge at the kth time step, i k represents the current of the target energy storage battery at the kth time step, ρ k represents the Coulomb efficiency factor at the kth time step, Δt represents the sampling period, C n It represents the total charge capacity consumed when discharging the battery from SOC(t)=1 to SOC(t)=0.

[0133] Specifically, the charged terminal voltage can be expressed by the following formula:

[0134] u(t)=OCV(SOC(t))-U1-U2-iR0(SOC(t))

[0135] Wherein, u(t) represents the charged terminal voltage of the target energy storage battery at time t, OCV(SOC(t)) represents the open circuit voltage corresponding to the state of charge at time t, U1 represents the voltage corresponding to the first RC parallel pair, U2 represents the voltage corresponding to the second RC parallel pair, and iR0(SOC(t)) represents the ohmic resistance voltage of the state of charge at time t under current i.

[0136] In this embodiment, the charged terminal voltage of the target energy storage battery is determined based on Kirchhoff's voltage law and the charge parameter, so that the basic terminal voltage characteristics of the target energy storage battery at different state of charge levels can be determined, so that the target equivalent circuit constructed subsequently can fully consider a better charging and discharging strategy to maximize the energy output of charging and discharging of the target energy storage battery.

[0137] refer to Figure 4 According to some embodiments of the present application, step S302 determines the instantaneous hysteresis voltage and the discretized hysteresis voltage of the target energy storage battery based on the charge parameters of the target energy storage battery, which may include, but is not limited to:

[0138] Step S401, obtaining the state of charge in the charging parameters and the state of charge derivative of the state of charge, and determining a hysteresis voltage charge correlation expression according to the state of charge and the state of charge derivative;

[0139] Step S402, deriving the hysteresis voltage charge correlation expression to obtain the hysteresis voltage derivative expression;

[0140] Step S403, discretizing the hysteresis voltage derivative expression to obtain a discretized hysteresis voltage;

[0141] Step S404, obtaining the current change state of the target energy storage battery in a preset detection time slot;

[0142] Step S405: determining the instantaneous hysteresis voltage of the target energy storage battery based on the current change state in the detection time slot.

[0143] In step S401 of some embodiments, the hysteresis voltage charge correlation expression is used to express the correlation relationship between the hysteresis correlation state and the charge correlation state.

[0144] Specifically, during the charge and discharge process of the target energy storage battery, frequent charge and discharge will produce tiny loops. Due to the frequent changes in the sign of the current, the target energy storage battery will experience a hysteresis effect, so that during the charge and discharge process, the voltage of the target energy storage battery will lag behind the voltage during charging, that is, under the same SOC, the voltage at the end of discharge will be lower than the voltage at the beginning of charging. In order to solve this problem, it is necessary to consider the specific changes in the hysteresis voltage under different charge states.

[0145] Specifically, the hysteresis voltage charge correlation expression can be determined by the following formula:

[0146]

[0147] Wherein, h(SOC,t) represents the hysteresis voltage under the state of charge at time t, SOC represents the state of charge, γ represents the positive constant for adjusting the voltage decay rate, sgn(SOC) refers to the sign function of the state of charge, indicating the direction of the change of the state of charge. It refers to the function of the state of charge and the rate of change of the state of charge derivative, which indicates the maximum hysteresis voltage of the target energy storage battery caused by the hysteresis effect.

[0148] In step S402 of some embodiments, the chain method can be used to derive the hysteresis voltage charge-related expression, and different state variables of the battery (such as the battery voltage, current and SOC, etc.) can be associated through the chain rule. Moreover, the chain rule processing can more accurately simulate the dynamic behavior of the target energy storage battery, including the transient and steady-state responses of the energy storage battery during the charging and discharging process, which helps to improve the stability of the subsequent equivalent circuit model during the charging and discharging process.

[0149] Specifically, the hysteresis voltage derivative expression can be determined by the following formula:

[0150]

[0151] in, represents the derivative of the hysteresis voltage at time t, ρ(t) represents the Coulomb efficiency factor at time t, i(t) represents the current of the target energy storage battery at time t, γ represents the positive constant for adjusting the voltage decay rate, C n represents the total charge capacity consumed when the battery is discharged from SOC(t)=1 to SOC(t)=0, h(t) represents the hysteresis voltage at time t, It indicates the maximum hysteresis voltage of the target energy storage battery caused by the hysteresis effect.

[0152] In step S403 of some embodiments, the discretization process can further determine the maximum hysteresis voltage of the target energy storage battery caused by the hysteresis effect of the energy storage battery during charging and discharging, that is, when the target energy storage battery is charged and discharged, the maximum hysteresis voltage M is a negative constant and a positive constant, respectively, which is crucial to ensure the stability of the energy output of the target energy storage battery during the charging and discharging process.

[0153] Specifically, the discretized hysteresis voltage can be determined by the following formula:

[0154]

[0155] Where h(k+1) represents the discretized hysteresis voltage at the k+1th time step, ρ(t) represents the Coulomb efficiency factor at time t, i(t) represents the current of the target energy storage battery at time t, Δt represents the sampling period, and C n represents the total charge capacity consumed when the battery is discharged from SOC(t)=1 to SOC(t)=0, h(k) represents the discretized hysteresis voltage at the kth time step, M represents the maximum hysteresis voltage, and sgn(i(k)) represents the direction of current change at the kth time step.

[0156] In step S404 of some embodiments, in the above expression for determining the discretized hysteresis voltage, in addition to the dynamic hysteresis effect that changes with the change of SOC during the charging and discharging process of the target energy storage battery, it also includes the instantaneous change hysteresis voltage generated by the target energy storage battery when the current sign changes. In order to further ensure the stability of the energy output of the target energy storage battery during the charging and discharging process, it is also necessary to consider the current change state that produces instantaneous changes.

[0157] Specifically, the preset detection time slots may be different time steps when the target energy storage battery is charged and discharged.

[0158] Specifically, the current change state can be determined by the following formula:

[0159]

[0160] Wherein, s[k] represents the current change state at the kth time step, sgn(i(k)) represents the current change direction at the kth time step, |i[k]|>0 represents that there is current passing through the target energy storage battery at the kth time step, if sgn(i[k]) is positive, it means that the target energy storage battery is charging, if sgn(i[k]) is negative, it means that the target energy storage battery is discharging, s[k-1] represents the current change state at the k-1th time step, i[k]=0 represents that there is no current passing through the target energy storage battery at the kth time step, and the current change state at the k-1th time step is the same as the current change state at the kth time step.

[0161] In step S405 of some embodiments, specifically, the instantaneous hysteresis voltage refers to the voltage of the target energy storage battery that responds promptly to the current change state during the charging and discharging process.

[0162] Specifically, the value obtained by multiplying the initial hysteresis voltage M0 by s[k] can be used as the instantaneous hysteresis voltage.

[0163] In this embodiment, the instantaneous hysteresis voltage of the target energy storage battery is determined based on the current change state in the detection time slot, and the instantaneous hysteresis voltage can be accurately determined, which improves the consideration of the influence of the instantaneous hysteresis voltage on the entire circuit during the subsequent charging and discharging process of the target energy storage battery, helps to ensure sufficient output of energy during the charging and discharging process, avoids overcharging or over-discharging, and thus ensures the safety of the target energy storage battery.

[0164] In step S303 of some embodiments, specifically, the target hysteresis voltage refers to the voltage corresponding to the hysteresis effect occurring during the charging and discharging process of the target energy storage battery, and is used to describe the change between the voltage and the state of charge generated by the target energy storage battery during the charging and discharging process.

[0165] Specifically, the target hysteresis voltage can be determined by the following formula:

[0166] U h =M0s[k]+Mh[k]

[0167] Among them, U h represents the target hysteresis voltage, M0 represents the initial hysteresis voltage, s[k] represents the current change state at the kth time step, M represents the maximum hysteresis voltage, and h[k] represents the discretized hysteresis voltage at the kth time step.

[0168] In this embodiment, the target hysteresis voltage is determined based on the instantaneous hysteresis voltage and the discretized hysteresis voltage, which can take into account the influence of the hysteresis effect on the voltage of the target energy storage battery during the charging and discharging process, and achieve an accurate description of the hysteresis phenomenon of the voltage-capacity curve, which is convenient for subsequent improvement of the accuracy of equivalent circuit model construction, thereby helping to improve the prediction accuracy of the characteristic parameters of the energy storage battery.

[0169] In step S304 of some embodiments, specifically, the hysteresis factor is a parameter that describes the degree of voltage hysteresis of the target energy storage battery during the charging and discharging process, that is, the hysteresis factor can determine the current proportions of the charging open circuit voltage and the discharging open circuit voltage in the subsequent hysteresis voltage characterization model, so as to adjust the real-time conversion of the open circuit voltage in the hysteresis main loop.

[0170] Specifically, when the target hysteresis voltage value does not vary much with the SOC, the hysteresis voltage may be defined as a variable related to the hysteresis factor.

[0171] Specifically, the hysteresis factor can be determined by the following formula:

[0172]

[0173] in, represents the hysteresis factor at the kth time step, represents the hysteresis factor at the k-1th time step, ik represents the current at the kth time step, ΔT represents the time step interval, ρ represents the Coulomb efficiency factor, C n It represents the total charge capacity consumed when discharging the battery from SOC(t)=1 to SOC(t)=0. α represents the conversion rate of the open circuit voltage of the target energy storage battery in the hysteresis main loop during the charging and discharging process. The value of α depends on the SOC accumulation required for the open circuit voltage to complete a complete conversion in the hysteresis main loop.

[0174] Furthermore, when the target energy storage battery is charging and discharging, the changing current mainly passes through Hysteresis Factor It can be seen from the ampere-hour integration method that The term represents the current working current i k The SOC change caused by the The hysteresis factor can be obtained by multiplying and accumulating The value of For the above, the coefficient of variation α is essentially a restrictive condition and is not affected by changes in operating conditions. When the absolute value of is greater than α, Can be directly changed to 1 or 0; when When the absolute value of is less than α, Then complete a pair accumulation; in particular, Each conversion between 0 and 1 can promptly eliminate the impact of the current accumulation error generated during the charging and discharging process on the target energy storage battery.

[0175] In step S305 of some embodiments, the hysteresis voltage characterization model is used to analyze the influence of the hysteresis effect generated during the charging and discharging process on the target energy storage battery.

[0176] Furthermore, the influence of the hysteresis factor on the open circuit voltage during the charge and discharge process can be described by the following formula:

[0177]

[0178] in, represents the hysteresis factor at the kth time step and the open circuit voltage at the state of charge at the kth time step, represents the hysteresis factor of the kth time step, SOC k represents the state of charge at the kth time step, OCV ch (SOC k ) represents the open circuit voltage at the kth time step, OCV dis (SOCk ) represents the discharge open circuit voltage at the charged state at the kth time step.

[0179] Furthermore, the hysteresis voltage characterization model can be described by the following formula:

[0180]

[0181] Among them, u′(t) represents the hysteresis terminal voltage of the target energy storage battery at time t considering the hysteresis effect, OCV(SOC(t)) represents the open circuit voltage corresponding to the state of charge at time t, U1 represents the voltage corresponding to the first RC parallel pair, U2 represents the voltage corresponding to the second RC parallel pair, iR0(SOC(t)) represents the ohmic resistance voltage of the state of charge at time t under current i, U h Indicates the target hysteresis voltage.

[0182] In this embodiment, a hysteresis voltage characterization model is constructed based on the hysteresis factor, the target hysteresis voltage and the charged terminal voltage, which can take into account the influence of the hysteresis effect on the target energy storage battery during the charging process, further accurately simulate the dynamic behavior of the target energy storage battery during the charging and discharging process, and accurately describe the hysteresis phenomenon of the voltage-capacity curve, which is helpful to subsequently improve the accuracy of the prediction of the characteristic parameters of the energy storage battery.

[0183] refer to Figure 5 According to some embodiments of the present application, step S105 performs equivalent modeling on the target energy storage battery according to the hysteresis voltage characterization model and the polarization characterization model to obtain a target equivalent circuit model, which may include, but is not limited to:

[0184] Step S501, constructing an initial equivalent circuit model of a target energy storage battery based on a hysteresis voltage characterization model and a polarization characterization model;

[0185] Step S502 , performing a circuit stability test on the initial equivalent circuit model to obtain a target equivalent circuit model.

[0186] In step S501 of some embodiments, specifically, since the hysteresis voltage characterization model focuses on capturing the asymmetry between the voltage and the state of charge (SOC) of the target energy storage battery during the charging and discharging process, and the polarization characterization model is used to simulate the polarization effect of the voltage change caused by the electrochemical reaction and ion migration inside the battery, an initial equivalent circuit model considering the polarization effect and the hysteresis effect can be constructed according to the hysteresis voltage characterization model and the polarization characterization model.

[0187] Specifically, taking U1, U2 and SOC as observations, the changes of U1, U2 and SOC at different time steps can be determined by the following formula:

[0188]

[0189] Among them, SOC k+1 represents the state of charge at the k+1th time step, U 1,k+i represents the voltage corresponding to the first RC parallel pair at the k+1th time step, U 2,k+1 represents the voltage corresponding to the second RC parallel pair at the k+1th time step, Describes the exponential decay process of voltage with the first polarization time constant τ1 within the time step interval ΔT, where ΔT represents the time step interval and τ1 represents the first polarization time constant. It describes the exponential decay process of voltage with the second polarization time constant τ2 within the time step interval ΔT, where τ2 represents the second polarization time constant, U 1,k represents the voltage corresponding to the first RC parallel pair at the kth time step, U 2,k represents the voltage corresponding to the second RC parallel pair at the kth time step, ρ represents the Coulomb efficiency factor, C n represents the total charge capacity consumed when the battery is discharged from SOC(t)=1 to SOC(t)=0, R1 represents the polarization resistance, R2 represents the concentration polarization resistance, i k represents the current at the kth time step, w 1,k represents the uncorrelated zero-mean Gaussian white noise caused by the ohmic resistance at the kth time step, w 2,k represents the uncorrelated zero-mean Gaussian white noise caused by the first RC parallel pair at the kth time step, w 3,k represents the uncorrelated zero-mean Gaussian white noise caused by the second RC parallel pair at the k-th time step.

[0190] Specifically, based on the ampere-hour integration method and Kirchhoff's law, the initial equivalent circuit model can be determined by the following formula:

[0191]

[0192] Among them, u k represents the circuit terminal voltage at the kth time step, represents the hysteresis factor at the kth time step and the open circuit voltage at the state of charge at the kth time step, represents the hysteresis factor of the kth time step, SOC k represents the state of charge at the kth time step, U 1,k represents the voltage corresponding to the first RC parallel pair at the kth time step, U 2,k represents the voltage corresponding to the second RC parallel pair at the kth time step, R0i k represents the voltage of the ohmic resistance, R0 represents the ohmic resistance, ik represents the current at the kth time step, v k represents the uncorrelated zero-mean Gaussian white noise caused by all resistors at the kth time step, U h Represents hysteresis voltage, U p Represents the polarization voltage.

[0193] In this embodiment, an initial equivalent circuit model of the target energy storage battery is constructed based on the hysteresis voltage characterization model and the polarization characterization model, which can capture the influence of the polarization effect and the hysteresis effect on the circuit, so as to solve the problem that the hysteresis phenomenon of the voltage-capacity curve cannot be accurately described and the complex phenomena such as concentration polarization and electrochemical polarization cannot be accurately reflected, thereby improving the accuracy of the construction of the initial equivalent circuit model and thus improving the accuracy of the prediction of the characteristic parameters of the energy storage battery.

[0194] refer to Figure 6 According to some embodiments of the present application, step S502 performs a circuit stability test on the initial equivalent circuit model to obtain a target equivalent circuit model, which may include, but is not limited to:

[0195] Step S601, obtaining a plurality of experimental voltage point pairs corresponding to the initial equivalent circuit model, and determining at least two target experimental voltage point pairs from the plurality of experimental voltage point pairs;

[0196] Step S602, calculating corresponding point pair state prediction data for each target experimental voltage point pair;

[0197] Step S603, in response to the state prediction data of each point pair satisfying a preset voltage state change condition, taking the initial equivalent circuit model as a target equivalent circuit model.

[0198] In step S601 of some embodiments, specifically, the experimental voltage point pair is the voltages corresponding to two parallel RC pairs obtained when performing a charge and discharge test experiment on the target energy storage battery, and the experimental voltage point pair reflects the voltage response of the target energy storage battery under different charge states.

[0199] Furthermore, at least two experimental voltage point pairs may be arbitrarily selected from a plurality of experimental voltage point pairs as target experimental voltage point pairs, which helps to subsequently determine the stability of the initial equivalent circuit model based on the changing states of different experimental voltage point pairs.

[0200] refer to Figure 7 According to some embodiments of the present application, step S602 calculates the corresponding point pair state prediction data for each target experimental voltage point pair, which may include, but is not limited to:

[0201] Step S701, obtaining a target experimental current point pair corresponding to a target experimental voltage point pair within a preset time step;

[0202] Step S702, calculating the slope corresponding to each time step according to the target experimental voltage point pair and the target experimental current point pair;

[0203] Step S703 , predicting the voltage change state of the target experimental voltage point pair according to the slope of each time step, and obtaining point pair state prediction data.

[0204] In step S701 of some embodiments, specifically, the target experimental current point pair refers to the current value corresponding to the target experimental voltage point pair at the same time step.

[0205] Specifically, since the target energy storage battery has nonlinear and continuously time-varying characteristics, when testing the stability of the equivalent circuit model, its nonlinear characteristics and time-varying characteristics need to be considered in order to more accurately simulate and predict the charging and discharging process of the target energy storage battery.

[0206] Specifically, before determining the target experimental current point pair, the experimental voltage point pair needs to be used as a state variable to construct a state space model. The state variable of the experimental voltage point pair can be expressed by the following formula:

[0207]

[0208] Among them, U′1 represents the first experimental voltage corresponding to the first experimental RC parallel pair, U′2 represents the second experimental voltage corresponding to the second experimental RC parallel pair, τ′1 represents the first experimental polarization time constant, and τ′2 represents the second experimental polarization time constant.

[0209]

[0210] Among them, U′2 represents the second experimental voltage corresponding to the second experimental RC parallel pair, τ′1 represents the first experimental polarization time constant, τ′2 represents the second experimental polarization time constant, and U′ OC Represents the experimental open circuit voltage.

[0211] Furthermore, the target experimental current point pair can be obtained by connecting the capacitance of each experimental RC parallel pair to its corresponding or The product of is determined.

[0212] In step S702 of some embodiments, specifically, the slope is used to represent the rate at which the target experimental voltage changes over time, and can be determined based on the target experimental current and the target experimental voltage.

[0213] Specifically, the slope can be determined by the following fourth-order Runge-Kutta method:

[0214]

[0215] Among them, kl Uj represents the l-th order slope corresponding to the target experimental voltage of the j-th experimental RC parallel pair, ΔT′ represents the experimental time step interval, and I j,n represents the target experimental current corresponding to the nth time step corresponding to the target experimental voltage of the jth experimental RC parallel pair, U′ j,n represents the target experimental voltage corresponding to the nth time step of the target experimental voltage of the jth experimental RC parallel pair, C j represents the total charge capacity consumed by the jth experimental RC parallel pair, τ′ j represents the polarization time constant corresponding to the jth experimental RC parallel pair, It represents the l-1th order slope corresponding to the target experimental voltage of the jth experimental RC parallel pair.

[0216] Specifically, The slope of the target experimental voltage change in each order iteration is calculated. If l = 1, The slope is calculated based on the target experimental current and target experimental voltage of the current time step. If l = 2, 3, or 4, The slope is calculated based on the value of the previous slope and the average of the target experimental current and target experimental voltage for the time step.

[0217] In this embodiment, by calculating the slope corresponding to each time step based on the target experimental voltage point pair and the target experimental current point pair, it is possible to predict the change of the target experimental voltage in the next time step based on the slope, and all predicted target experimental voltage data constitute point pair state prediction data, providing data support for the subsequent stability evaluation of the initial equivalent circuit model.

[0218] In step S703 of some embodiments, specifically, the state prediction data refers to state data of the target experimental voltage point changing with time during the charging and discharging process.

[0219] Furthermore, the target experimental voltage can be updated by the slopes at different time steps, and the above slope calculation steps are repeated until the target experimental voltage stops changing, and it is ensured that the selected time step is small enough to capture the periodic behavior of the target experimental voltage.

[0220] Specifically, the state prediction data of the target experimental voltage can be expressed by the following formula:

[0221]

[0222] Among them, U′ 1,n+1 represents the first experimental voltage at the n+1th time step, U′ 1,n represents the first experimental voltage at the nth time step, represents the first-order slope corresponding to the first experimental voltage, represents the second-order slope corresponding to the first experimental voltage, represents the third-order slope corresponding to the first experimental voltage, Indicates the 4th-order slope corresponding to the first experimental voltage.

[0223]

[0224] Among them, U′ 2,n+1 represents the second experimental voltage at the n+1th time step, U′ 2,n represents the second experimental voltage at the nth time step, represents the first-order slope corresponding to the second experimental voltage, represents the second-order slope corresponding to the second experimental voltage, represents the third-order slope corresponding to the second experimental voltage, It represents the 4th-order slope corresponding to the second experimental voltage.

[0225] In this embodiment, the voltage change state of the target experimental voltage point pair is predicted according to the slope of each time step to obtain point pair state prediction data, which can determine the change state of the target experimental voltage point pair over time, provide data support for the subsequent stability detection of the initial equivalent circuit model, and serve as a basis for evaluating the performance and health status of the target energy storage battery to ensure that the target energy storage battery can accurately predict the behavior of the battery under different working conditions, so as to optimize the charging and discharging strategy, thereby improving the use efficiency and life of the target energy storage battery.

[0226] In step S603 of some embodiments, specifically, the preset voltage state change condition refers to the existence of the same point pair state prediction sub-data when the target experimental voltage point pair stops changing with time.

[0227] Furthermore, in the actual experiment process, the voltage state trajectory of the point-pair state prediction data corresponding to the target experimental voltage point can be depicted by the phase plane method to analyze the stability of the initial equivalent circuit model.

[0228] Furthermore, by analyzing the phase trajectory in the neighborhood of the equilibrium point, the stability of the target experimental voltage point pair near the equilibrium point can be determined. The stability of the equilibrium point can be determined by the attraction point (i.e., the same point pair state prediction sub-data) and the repulsion point (i.e., different point pair state prediction sub-data): if the phase trajectory is close to the attraction point, the trajectory gradually converges to the equilibrium point, then the equilibrium point is an attraction point, indicating that the initial equivalent circuit model is stable; if the phase trajectory is far away from the repulsion point, then the equilibrium point is a repulsion point, indicating that the initial equivalent circuit model is unstable; periodic trajectory: if the phase trajectory forms a closed loop near the equilibrium point, it means that the initial equivalent circuit model may have periodic motion, showing a periodic stable state; saddle point: if the phase trajectory of the equilibrium point presents a "saddle shape", it means that the point is a saddle point, and the initial equivalent circuit model is stable in some directions but unstable in other directions.

[0229] For example, the target experimental voltage point pairs are (0.4, 0.35), (1.2, 1.75) and (2.0, 2.5). By predicting that these target experimental voltage point pairs have the same point pair state when they stop changing over time, the predicted sub-data is (1.4, 1.65), indicating that the initial equivalent circuit model is stable, and the initial equivalent circuit model is used as the target equivalent circuit model.

[0230] In this embodiment, by responding to the state prediction data of each point satisfying the preset voltage state change condition, the initial equivalent circuit model is used as the target equivalent circuit model, so that the stability of the target energy storage voltage during the charging and discharging process can be accurately simulated, thereby improving the accuracy of the prediction of the characteristic parameters of the energy storage battery.

[0231] refer to Figure 8 , we can understand that the target equivalent circuit model is composed of the open circuit voltage considering the hysteresis factor The ohmic resistor R0, the input current source i, the hysteresis voltage Uh, the circuit terminal voltage and two parallel RC pairs are composed, wherein one RC is composed of a polarization resistor R1 and a polarization capacitor C1, and the other RC pair is composed of a concentration polarization resistor R2 and a concentration polarization capacitor C2.

[0232] Furthermore, the value of the two parallel RC pairs varies with SOC and The open circuit voltage OCV value is determined by SOC and hysteresis factor. Jointly decided.

[0233] In step S106 of some embodiments, the target battery prediction parameters may include, but are not limited to, open circuit voltage, state of charge, remaining battery life, and battery health status.

[0234] Specifically, the target equivalent circuit model can directly obtain the open circuit voltage under different charge states.

[0235] Specifically, a target pulse current may be applied to the target energy storage battery, and the current state of charge may be predicted through a target equivalent circuit model in combination with the coulomb efficiency factor and the ampere-hour integration method.

[0236] Specifically, the target equivalent circuit model is used to analyze the discharge capacity of the target energy storage battery at different states of charge and the degradation of the battery performance during the aging process to determine the remaining life of the battery.

[0237] Specifically, the target equivalent circuit model is used to analyze the internal resistance increase and capacitance attenuation of the target energy storage battery to determine the health status of the battery.

[0238] In this embodiment, the battery characteristic parameters are predicted based on the target equivalent circuit model. The target equivalent circuit model that takes into account the polarization effect and hysteresis effect can simulate the changes of the battery under different working conditions, thereby improving the accuracy of the prediction of the energy storage battery characteristic parameters.

[0239] refer to Fig. 9 It can be understood that firstly, the corresponding global voltage capacity distribution parameters can be determined through the hysteresis main loop test, and the corresponding local voltage capacity distribution parameters can be determined through the hysteresis small loop test, and the local voltage capacity distribution parameters are used to update the global voltage capacity distribution parameters to determine the final voltage capacity distribution parameters, and a hysteresis voltage characterization model is constructed based on the voltage capacity distribution parameters; secondly, the battery polarization parameters are determined through the HPPC test, and the polarization characterization model is constructed according to the battery polarization parameters; then, a second-order RC equivalent circuit model considering polarization and hysteresis effects is constructed by combining the hysteresis voltage characterization model and the polarization characterization model; finally, The target experimental voltage is used as the observed state quantity to construct the state space model corresponding to each target experimental voltage, and the change state of the target experimental voltage over time is analyzed based on the Runge-Kutta method to determine the evolution of the target experimental voltage over time. The analytical steps of the Runge-Kutta method are repeated until the periodic change of the target experimental voltage in the entire experimental cycle is obtained. The phase trajectory of the target experimental voltage changing with time is plotted based on the phase plane method. If the end points of the phase trajectory intersect at the same point, it means that the second-order RC equivalent circuit model is stable. The open circuit voltage, state of charge, remaining battery life and battery health status of the target energy storage battery are calculated through the second-order RC equivalent circuit model.

[0240] The embodiment of the present application obtains the battery polarization parameters by performing a mixed pulse power test on the target energy storage battery; constructs a polarization characterization model based on the battery polarization parameters; performs a hysteresis loop test on the target energy storage battery to obtain the voltage capacity distribution parameters; constructs a hysteresis voltage characterization model based on the voltage capacity distribution parameters; performs equivalent modeling on the target energy storage battery according to the hysteresis voltage characterization model and the polarization characterization model to obtain a target equivalent circuit model; and performs battery characteristic parameter prediction based on the target equivalent circuit model to obtain the target battery prediction parameters. In this way, the accuracy of the prediction of the characteristic parameters of the energy storage battery can be improved.

[0241] See also Fig.10 , Fig.10 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:

[0242] The processor 1001 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0243] The memory 1002 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 1002 can store processing systems and other applications. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program codes are stored in the memory 1002, and the processor 1001 calls and executes the parameter parsing method for the energy storage battery in the embodiments of this application;

[0244] Input / output interface 1003, used to implement information input and output;

[0245] The communication interface 1004 is used to realize the communication interaction between the device and other devices. The communication can be realized through a wired manner (such as USB, network cable, etc.) or a wireless manner (such as mobile network, WIFI, Bluetooth, etc.);

[0246] A bus 1005 , which transmits information between various components of the device (e.g., the processor 1001 , the memory 1002 , the input / output interface 1003 , and the communication interface 1004 );

[0247] The processor 1001 , the memory 1002 , the input / output interface 1003 and the communication interface 1004 are connected to each other in communication within the device via the bus 1005 .

Claims

1. A parameter analysis method for energy storage batteries, characterized in that: The method comprises: Conduct mixed pulse power test on target energy storage battery to obtain battery polarization parameters; Constructing a polarization characterization model based on the battery polarization parameters; Performing a hysteresis loop test on the target energy storage battery to obtain voltage capacity distribution parameters; Constructing a hysteresis voltage characterization model based on the voltage capacity distribution parameters; Performing equivalent modeling on the target energy storage battery according to the hysteresis voltage characterization model and the polarization characterization model to obtain a target equivalent circuit model; Battery characteristic parameters are predicted based on the target equivalent circuit model to obtain target battery prediction parameters.

2. The parameter analysis method for energy storage batteries according to claim 1, characterized in that: The equivalent modeling of the target energy storage battery according to the hysteresis voltage characterization model and the polarization characterization model to obtain a target equivalent circuit model includes: Constructing an initial equivalent circuit model of the target energy storage battery based on the hysteresis voltage characterization model and the polarization characterization model; A circuit stability test is performed on the initial equivalent circuit model to obtain the target equivalent circuit model.

3. The parameter analysis method for energy storage batteries according to claim 2, characterized in that: The performing a circuit stability test on the initial equivalent circuit model to obtain the target equivalent circuit model includes: Acquire a plurality of experimental voltage point pairs corresponding to the initial equivalent circuit model, and determine at least two target experimental voltage point pairs from the plurality of experimental voltage point pairs; Calculating corresponding point pair state prediction data for each target experimental voltage point pair; In response to each of the point pair state prediction data satisfying a preset voltage state change condition, the initial equivalent circuit model is used as the target equivalent circuit model.

4. The parameter analysis method for energy storage batteries according to claim 3, characterized in that: The step of calculating the point pair state prediction data corresponding to each target experimental voltage point pair includes: Obtaining a target experimental current point pair corresponding to the target experimental voltage point pair within a preset time step; Calculate the slope corresponding to each time step according to the target experimental voltage point pair and the target experimental current point pair; The voltage change state of the target experimental voltage point pair is predicted according to the slope of each time step to obtain the point pair state prediction data.

5. The parameter analysis method for energy storage batteries according to claim 1, characterized in that: The constructing of a hysteresis voltage characterization model based on the voltage capacity distribution parameter comprises: Acquire a charge parameter of the target energy storage battery, and determine a charge terminal voltage of the target energy storage battery based on Kirchhoff's voltage law and the charge parameter; Determining an instantaneous hysteresis voltage and a discretized hysteresis voltage of the target energy storage battery based on a charge parameter of the target energy storage battery; determining a target hysteresis voltage based on the instantaneous hysteresis voltage and the discretized hysteresis voltage; Determining a hysteresis factor according to the voltage capacity distribution parameter; The hysteresis voltage characterization model is constructed based on the hysteresis factor, the target hysteresis voltage and the charged terminal voltage.

6. The parameter analysis method for energy storage batteries according to claim 5, characterized in that: The step of determining the instantaneous hysteresis voltage and the discretized hysteresis voltage of the target energy storage battery based on the charge parameter of the target energy storage battery comprises: Acquire the state of charge in the charge parameter and the state of charge derivative of the state of charge, and determine a hysteresis voltage charge correlation expression according to the state of charge and the state of charge derivative; Derivative the hysteresis voltage charge correlation expression to obtain a hysteresis voltage derivative expression; Discretizing the hysteresis voltage derivative expression to obtain the discretized hysteresis voltage; Obtaining a current change state of the target energy storage battery in a preset detection time slot; Based on the current change state in the detection time slot, the instantaneous hysteresis voltage of the target energy storage battery is determined.

7. The parameter analysis method for energy storage batteries according to claim 1, characterized in that: The mixed pulse power test is performed on the target energy storage battery to obtain the battery polarization parameters, including: Performing a first mixed pulse power test on the target energy storage battery to obtain the ohmic resistance of the target energy storage battery; Performing a second mixed pulse power test on the target energy storage battery to obtain a polarization resistance and a concentration polarization resistance of the target energy storage battery; The battery polarization parameter is determined based on the ohmic resistance, the polarization resistance, and the concentration polarization resistance.

8. The parameter analysis method for energy storage batteries according to claim 1, characterized in that: The step of constructing a polarization characterization model based on the battery polarization parameters comprises: Obtaining an initial open circuit voltage of the energy storage battery; The polarization characterization model is constructed according to the initial open circuit voltage and the battery polarization parameters.

9. The parameter analysis method for energy storage batteries according to claim 1, characterized in that: The hysteresis loop test is performed on the target energy storage battery to obtain voltage capacity distribution parameters, including: Performing a hysteresis main loop test on the target energy storage battery to obtain a global voltage capacity distribution parameter; Performing a hysteresis small loop test on the target energy storage battery to obtain a local voltage capacity distribution parameter; The global voltage-capacity distribution parameter is updated by using the local voltage-capacity distribution parameter to obtain the voltage-capacity distribution parameter.

10. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the parameter analysis method for the energy storage battery as described in any one of claims 1 to 9 when executing the computer program.

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