CN119556155A

CN119556155A - Parameter analysis method and electronic equipment for energy storage battery

Info

Publication number: CN119556155A
Application number: CN202411925404.1A
Authority: CN
Inventors: 张艳辉; 冯威; 赵天任; 张栩; 熊学涛; 向花姮
Original assignee: Shenzhen Institute of Advanced Technology of CAS
Current assignee: Shenzhen Institute of Advanced Technology of CAS
Priority date: 2024-12-25
Filing date: 2024-12-25
Publication date: 2025-03-04

Abstract

The present application relates to the field of battery technologies, and in particular, to a method for analyzing parameters of an energy storage battery and an electronic device. According to the bearing fault diagnosis method, mixed pulse power testing is conducted on a target energy storage battery to obtain battery polarization parameters, a polarization characterization model is built based on the battery polarization parameters, hysteresis loop testing is conducted on the target energy storage battery to obtain voltage capacity distribution parameters, a hysteresis voltage characterization model is built based on the voltage capacity distribution parameters, equivalent modeling is 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 battery characteristic parameter prediction is conducted based on the target equivalent circuit model to obtain target battery prediction parameters. In this way, the accuracy of the characteristic parameter prediction of the energy storage battery can be improved.

Description

Parameter analysis method for energy storage battery and electronic equipment

Technical Field

The present application relates to the field of battery technologies, and in particular, to a method for analyzing parameters of an energy storage battery and an electronic device.

Background

The equivalent circuit model of the energy storage battery is a technical means for simulating and analyzing electrochemical behaviors and performances of the lithium battery in the charging and discharging processes, and simulates electrochemical behaviors and dynamic responses of the battery and voltage and current characteristics of the battery in the charging and discharging processes by equivalent complex electrochemical reactions inside the battery into a series of combinations of circuit elements (including a voltage source, ohmic internal resistance, polarized internal resistance, capacitance and the like).

The traditional equivalent circuit model is usually a Rint model, a Th venin model, a Shepherd model or a KiBaM model and the like, but the Rint model ignores the transient characteristic of the battery under current excitation and has larger deviation in the charging and discharging process of the battery, the Thevenin model still has insufficient accuracy in capturing high-frequency response, multi-stage polarization phenomenon and complex dynamic behaviors aiming at rapid charging and discharging conditions, the hysteresis effect of the battery is processed, the hysteresis phenomenon of a voltage-capacity curve cannot be accurately described, and neither the Shepherd model nor the KiBaM model fully considers the hysteresis effect of the battery, cannot accurately reflect the complex phenomena such as concentration polarization, electrochemical polarization and the like, so that the prediction of the characteristic parameters of the energy storage battery is inaccurate. Therefore, how to improve the accuracy of the prediction of the characteristic parameters of the energy storage battery is a urgent problem to be solved.

Disclosure of Invention

The embodiment of the application mainly aims to provide a parameter analysis method for an energy storage battery and electronic equipment, and aims to improve the accuracy of characteristic parameter prediction of the energy storage battery.

To achieve the above object, a first aspect of an embodiment of the present application provides a method for analyzing parameters of an energy storage battery, where the method includes:

Performing mixed pulse power test on a target energy storage battery to obtain battery polarization parameters;

Constructing a polarization characterization model based on the battery polarization parameters;

performing 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 representation model and the polarization representation model to obtain a target equivalent circuit model;

and predicting battery characteristic parameters based on the target equivalent circuit model to obtain target battery prediction parameters.

In some embodiments, the 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:

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

and performing circuit stability test on the initial equivalent circuit model to obtain the target equivalent circuit model.

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

acquiring 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 experimental voltage point pairs;

Calculating corresponding point pair state prediction data of each target experimental voltage point pair;

And taking the initial equivalent circuit model as the target equivalent circuit model when the point-to-point state prediction data meet the preset voltage state change condition.

In some embodiments, the calculating the corresponding point pair state prediction data for each target experimental voltage point pair includes:

Acquiring a target experimental current point pair corresponding to the target experimental voltage point pair in a preset time step;

calculating the slope corresponding to each time step according to the target experimental voltage point pair and the target experimental current point pair;

And predicting the voltage change state of the target experimental voltage point pair according to the slope of each time step, and obtaining the point pair state prediction data.

In some embodiments, the constructing a hysteresis voltage characterization model based on the voltage capacity distribution parameters includes:

acquiring a charge parameter of the target energy storage battery, and determining a charge terminal voltage of the target energy storage battery based on kirchhoff voltage law and the charge parameter;

determining an instantaneous hysteresis voltage and a discretized hysteresis voltage of the target energy storage battery based on the 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;

And constructing the hysteresis voltage characterization model based on the hysteresis factor, the target hysteresis voltage and the charge terminal voltage.

In some embodiments, the 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:

acquiring the state of charge in the state of charge parameter 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;

Deriving the hysteresis voltage charge related expression to obtain a hysteresis voltage derivative expression;

discretizing the hysteresis voltage derivative expression to obtain the discretized hysteresis voltage;

acquiring a current change state of the target energy storage battery under a preset detection time slot;

and determining the instantaneous hysteresis voltage of the target energy storage battery based on the current change state under the detection time slot.

In some embodiments, the performing the hybrid pulse power test on the target energy storage battery to obtain the battery polarization parameter includes:

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;

the battery polarization parameter is determined based on the ohmic resistance, the polarization resistance, and the concentration polarization resistance.

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

acquiring an initial open-circuit voltage of the energy storage battery;

And constructing the polarization characterization model according to the initial open-circuit voltage and the battery polarization parameters.

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

performing hysteresis main loop test on the target energy storage battery to obtain global voltage capacity distribution parameters;

Performing hysteresis loop test on the target energy storage battery to obtain local voltage capacity distribution parameters;

and updating the global voltage capacity distribution parameter through the local voltage capacity distribution parameter to obtain the voltage capacity distribution parameter.

To achieve the above object, a second aspect of the embodiments of the present application proposes an electronic device, including a memory and a processor, the memory storing a computer program, the processor implementing the method according to the first aspect when executing the computer program.

According to the parameter analysis method for the energy storage battery and the electronic equipment, the method and the electronic equipment have the following beneficial effects:

The method comprises the steps of carrying out mixed pulse power test on a target energy storage battery to obtain battery polarization parameters, constructing a polarization characterization model based on the battery polarization parameters, carrying out 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, carrying out 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 carrying out battery characteristic parameter prediction based on the target equivalent circuit model to obtain target battery prediction parameters. In this way, the accuracy of the characteristic parameter prediction of the energy storage battery can be improved.

Drawings

Fig. 1 is a flowchart of a method for analyzing parameters of an energy storage battery according to an embodiment of the present application;

FIG. 2 is a graph of pulse current versus time versus open circuit voltage versus time for a hybrid pulse power test of a target energy storage battery according to an embodiment of the present application;

fig. 3 is a flowchart of step S104 in fig. 1;

fig. 4 is a flowchart of step S302 in fig. 3;

fig. 5 is a flowchart of step S105 in fig. 1;

fig. 6 is a flowchart of step S502 in fig. 5;

fig. 7 is a flowchart of step S602 in fig. 6;

FIG. 8 is a schematic diagram of a target equivalent circuit model provided by an embodiment of the present application;

fig. 9 is a flowchart of battery characteristic parameter prediction provided by an embodiment of the present application;

fig. 10 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present application.

Detailed Description

The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

It should be noted that, if directional indications (such as up, down, left, right, front, and rear are referred to in the embodiments of the present application), the directional indications are merely used to explain the relative positional relationship, movement conditions, and the like between the components in a specific posture, and if the specific posture is changed, the directional indications are correspondingly changed.

In addition, if there is a description of "first", "second", etc. in the embodiments of the present application, the description of "first", "second", etc. is for descriptive purposes only and is not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In addition, if "and/or" and/or "are used throughout, the meaning includes three parallel schemes, for example," a and/or B "including a scheme, or B scheme, or a scheme where a and B are satisfied simultaneously. In addition, the technical solutions of the embodiments may be combined with each other, but it is necessary to base that the technical solutions can be realized by those skilled in the art, and when the technical solutions are contradictory or cannot be realized, the combination of the technical solutions should be considered to be absent and not within the scope of protection claimed in the present application.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of the application only and is not intended to be limiting of the application.

Therefore, the equivalent circuit model constructed according to the hysteresis voltage characterization model and the polarization characterization model is adopted to predict the characteristic parameters of the battery, so that the polarization effect and the hysteresis effect generated in the charge and discharge processes of the energy storage battery can be effectively considered, and the accuracy of the characteristic parameter prediction of the energy storage battery is facilitated.

The following description is made on the basis of the accompanying drawings.

Referring to fig. 1, a parameter analysis method for an energy storage battery according to an embodiment of the present application may include, but is not limited to:

step S101, performing mixed pulse power test on a target energy storage battery to obtain battery polarization parameters;

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

step S103, performing hysteresis loop test on the target energy storage battery to obtain voltage capacity distribution parameters;

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

step S105, performing equivalent modeling on the target energy storage battery according to the hysteresis voltage representation model and the polarization representation model to obtain a target equivalent circuit model;

And S106, predicting battery characteristic parameters based on the target equivalent circuit model to obtain target battery prediction parameters.

According to the parameter analysis method for the energy storage battery, which is shown in the steps S101 to S106 of the embodiment of the application, the battery polarization parameter is obtained by carrying out mixed pulse power test on the target energy storage battery, a polarization characterization model is built based on the battery polarization parameter, a hysteresis loop test is carried out on the target energy storage battery to obtain a voltage capacity distribution parameter, a hysteresis voltage characterization model is built based on the voltage capacity distribution parameter, equivalent modeling is carried out 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 battery characteristic parameter prediction is carried out based on the target equivalent circuit model to obtain a target battery prediction parameter. In this way, the accuracy of the characteristic parameter prediction of the energy storage battery can be improved.

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

The method comprises the steps of performing mixed pulse power testing on a target energy storage battery to obtain battery polarization parameters, and the method comprises the steps of performing first mixed pulse power testing on the target energy storage battery to obtain ohmic resistance of the target energy storage battery, performing second mixed pulse power testing on the target energy storage battery to obtain polarization resistance and concentration polarization resistance of the target energy storage battery, and determining the battery polarization parameters based on the ohmic resistance, the polarization resistance and the concentration polarization resistance.

In particular, ohmic resistance is the inherent resistance inside the target energy storage cell, which is responsible for the drop in open circuit voltage of the cell upon discharge.

Further, 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 is stopped so that the electrochemical reaction inside the battery reaches an equilibrium state, and the ohmic resistance of the battery can be calculated by measuring the voltage drop during the discharge pulse.

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

Where R ₀ denotes an ohmic resistance, V _oc denotes an open circuit voltage to which a discharge pulse current is not applied, V ₁ denotes an open circuit voltage after a discharge pulse current is applied, and I denotes a pulse current.

In particular, the polarization resistance is due to the fact that the electrochemical reaction rate of the electrode surface is limited, when the current density is high, the electrochemical reaction cannot be performed in time, and the electrode potential deviates from the balance potential, so that voltage resistance is caused. The concentration polarization resistance refers to the resistance of the target energy storage battery, which causes the lithium ion concentration difference between the surface and the inside of the electrode and causes the voltage change due to the uneven migration of lithium ions in the target energy storage battery in the charging process.

Further, a second hybrid pulse power test is used to test the discharge process of the target energy storage battery. In the charge pulse test, a charge pulse current is applied to the energy storage battery, which is equal to the discharge pulse current, until the current stops. By analyzing the voltage rise during the charge pulse, the polarization resistance can be determined. And when the charge pulse is stopped, the state of charge remains constant and the battery voltage begins to increase slowly, since there are different lithium ion concentration gradients throughout the battery when the current is stopped, and therefore the concentration polarization resistance can be determined by the voltage change when the current is stopped.

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

wherein R ₁ denotes a polarization resistance, V ₃ denotes an open circuit voltage after application of a charging pulse current, V ₂ denotes an open circuit voltage immediately after application of a charging pulse current, and I denotes a pulse current.

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

Wherein, R ₂ represents concentration polarization resistance, V ₄ represents constant open circuit voltage in charging process, V ₃ represents open circuit voltage after charging pulse current is applied, and I represents pulse current.

In this embodiment, by performing the second hybrid pulse power test on the target energy storage battery, the voltage drop condition of electrochemical polarization and concentration polarization of the target energy storage battery during charging can be simulated, which is helpful for considering the influence of electrochemical polarization and concentration polarization in the subsequent equivalent circuit.

Specifically, the battery polarization parameter is the basis for constructing the equivalent circuit model of the battery, and directly influences the simulation precision of the equivalent circuit model to the target energy storage battery. The battery polarization parameter includes a first polarization time constant corresponding to a first parallel RC pair in the equivalent circuit, and a second polarization time constant corresponding to a second parallel RC pair.

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

τ₁＝R₁C₁

where τ ₁ denotes a first polarization time constant, R ₁ denotes a polarization resistance, and C ₁ denotes a polarization capacitance.

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

τ₂＝R₂C₂

Where τ ₂ denotes the second polarization time constant, R ₂ denotes the concentration polarization resistance, and C ₂ denotes the concentration polarization capacitance.

Referring to the upper graph of fig. 2, the horizontal axis represents Time (Time/s), the vertical axis represents pulse current (a), and the graph shows that the pulse current starts to apply the discharge pulse current at 6s, the current starts from 0A to-2A until 38s, the entire discharge process ends, the amplitude of the current change at the end of the discharge process is denoted by Δi, the application of the charge pulse current starts at 38, the current returns to 0A from-2A, and the charge pulse current is applied again at 80s until 90 s.

Referring to the lower graph of fig. 2, the horizontal axis represents Time(s) and the vertical axis represents open circuit voltage (V), it is shown that at 6s, when the discharge pulse current starts to be applied, the open circuit voltage is reduced from Voc to V _o′_c and further reduced to V1 when the discharge pulse current tends to stabilize, so as to reflect the internal resistance effect of the energy storage battery, and when the charge pulse current is applied at 38s, the open circuit voltage is gradually restored to V2, when the current tends to stabilize, the open circuit voltage is gradually restored to V3, so as to reflect the polarization effect of the energy storage battery, and at 80s, the charge pulse current is again applied, so that the open circuit voltage is gradually restored to V4, so as to reflect the concentration polarization effect of the energy storage battery.

In step S102 of some embodiments, in particular, a polarization characterization model is used to analyze the effect of polarization on the equivalent circuit.

Specifically, constructing the polarization characterization model based on the battery polarization parameters may include obtaining an initial open-circuit voltage of the energy storage battery, and constructing the polarization characterization model based on the initial open-circuit voltage and the battery polarization parameters.

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

Further, a 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 the concentration polarization resistance are integrated into an equivalent circuit model, the polarization effect of the battery is simulated by adding an RC pair which is connected in parallel, the RC pair consists of a resistor and a capacitor, and the values of the polarization resistance and the concentration polarization resistance are used for determining the resistance value of the RC pair.

The polarization characterization model also includes a polarization time constant, which is determined by the resistance and capacitance values of the RC pair, and which affects the voltage change rate of the energy storage cell.

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

Wherein U _P represents a polarization characterization model, U _oc represents an initial open circuit voltage, R ₀ represents an ohmic resistance, I represents a pulse current, Δt ₁ represents a discharge time interval, Δt ₂ represents a charge time interval, R ₁ represents a polarization resistance, Δt ₂ represents a charge time interval, C ₁ represents a polarization capacitance, R ₂ represents a concentration polarization resistance, and C ₂ represents a concentration polarization capacitance.

In the embodiment, the polarization characterization model is constructed according to the initial open-circuit voltage and the battery polarization parameters, so that the voltage drop condition of the energy storage battery in the charge and discharge process can be accurately simulated and predicted, and the behavior characteristics of the energy storage battery under different charge and discharge rates can be more accurately simulated by combining the polarization time constant in the charge and discharge process, thereby being beneficial to the follow-up improvement of the accuracy of the construction of the equivalent circuit model.

In step S103 of some embodiments, the voltage capacity distribution parameter refers to the updated voltage and charge variation parameter of the energy storage battery in the complete charge-discharge cycle.

The method comprises the steps of performing hysteresis loop test on a target energy storage battery to obtain voltage capacity distribution parameters, wherein the method comprises the steps of performing hysteresis main loop test on the target energy storage battery to obtain global voltage capacity distribution parameters, performing hysteresis small loop test on the target energy storage battery to obtain local voltage capacity distribution parameters, and updating the global voltage capacity distribution parameters through the local voltage capacity distribution parameters to obtain the voltage capacity distribution parameters.

Specifically, the global voltage capacity distribution parameter refers to a voltage and charge variation parameter of the energy storage battery in a complete charge-discharge cycle.

Specifically, the local voltage capacity distribution parameter refers to a voltage and charge variation parameter of the energy storage battery in a local charge-discharge cycle.

Further, the hysteresis main loop test refers to the test of the relation between the voltage and the capacity in the complete charge-discharge cycle. The energy storage battery is fully charged and then discharged, and voltage and charge data are recorded in the discharging process, so that global voltage capacity distribution parameters can be obtained, and the global voltage capacity distribution parameters can be used for representing corresponding voltage change conditions of the energy storage battery under different charges.

Further, the hysteresis loop test refers to a test of the relationship between voltage and capacity in a partial charge-discharge cycle. In the charging and discharging process of the energy storage battery, the current is changed frequently, a plurality of small loops, namely hysteresis small loops, can be formed in the hysteresis main loop, small-amplitude current pulses can be applied in the charging and discharging process of the battery, short standing is carried out between the pulses, so that voltage change of the battery in a partial charging and discharging period is captured, and the hysteresis small loops are tested to determine the SOC accumulation amount required by complete conversion of the open-circuit voltage in the hysteresis main loop.

Further, by integrating the local voltage capacity distribution parameter into the global voltage capacity distribution parameter, a more accurate voltage capacity distribution parameter in the complete charge-discharge cycle can be obtained.

In an embodiment of the application, the hysteresis main loop test comprises the specific steps of firstly fully discharging the electric quantity of an energy storage battery, standing for 2 hours, secondly, gradually charging the energy storage battery under the constant current pulse condition of 0.2C multiplying power by the charging depth of delta SOC=0.1, standing for 1 hour until SOC=0.1, and finally, gradually discharging the energy storage battery with the same C multiplying power, delta SOC and standing time after charging until SOC=0, wherein in the process, the open circuit voltage and the charge parameters are acquired every 1 s.

Further, the hysteresis loop test can specifically include the steps of firstly fully charging the energy storage battery, standing for 2 hours, discharging the energy storage battery with a discharge depth of delta SOC=0.2 under a constant current pulse condition of 1C multiplying power, namely stopping discharging when the SOC drops by 0.2, and secondly charging the energy storage battery with a charge depth of delta SOC=0.1 under a constant current pulse condition of 1C multiplying power, namely stopping charging when the SOC rises by 0.1, and repeating the steps of charging and discharging until the SOC=0.

In the embodiment, the global voltage capacity distribution parameters are updated through the local voltage capacity distribution parameters to obtain the voltage capacity distribution parameters, so that the voltage capacity distribution parameters of the energy storage battery in a stable state can be captured, the voltage and charge change condition of the energy storage battery in a dynamic charge-discharge process can be simulated, data support is provided for considering hysteresis effects later, and the accuracy of constructing a subsequent equivalent circuit model is improved.

Referring to fig. 3, step S104 builds a hysteresis voltage characterization model based on the voltage capacity distribution parameters, according to some embodiments of the present application, which may include, but are not limited to:

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 a kirchhoff voltage law and the charge parameter;

Step S302, determining 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;

step S303, determining a target hysteresis voltage based on the instantaneous hysteresis voltage and the discretized hysteresis voltage;

Step S304, determining hysteresis factors according to the voltage capacity distribution parameters;

step S305, a hysteresis voltage characterization model is constructed based on the hysteresis factor, the target hysteresis voltage and the charge terminal voltage.

In step S301 of some embodiments, specific charge parameters include, but are not limited to, states of charge at different times and different time steps, total charge capacity consumed, voltages of two parallel RC pairs, open circuit voltages corresponding to states of charge, voltages across ohmic resistors, and the like.

Specifically, the states of charge at different moments can be determined first, the determined states of charge are further discretized based on a preset sampling period and coulomb efficiency factors, the states of charge at different time steps after discretization are obtained, and finally the states of charge at different moments and the influences between the corresponding open circuit voltages, the voltages of two parallel RC pairs and the voltages of ohmic resistors are described through kirchhoff voltage law, so that the voltages of the corresponding ends of charge of the energy storage battery at any moment of charge are determined.

Specifically, the states of charge at different times can be expressed by the following formula:

Where SOC (t) represents the state of charge at time t, SOC (t ₀) represents the state of charge at initial time t ₀, 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. Where 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.

Specifically, the states of charge for different time steps after discretization can be expressed by the following formula:

Where SOC _k+1 represents the state of charge at the k+1th time step, SOC _k represents the state of charge at the k time step, i _k represents the current of the target energy storage battery at the k time step, ρ _k represents the coulomb efficiency factor at the k time step, Δt represents the sampling period, and C _n represents the total charge capacity consumed when discharging the battery from SOC (t) =1 to SOC (t) =0.

Specifically, the charge terminal voltage can be expressed by the following formula:

u(t)=OCV(SOC(t))-U₁-U₂-iR₀(SOC(t))

Where U (t) represents the voltage at the charge end 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, U ₁ represents the voltage corresponding to the first RC parallel pair, U ₂ represents the voltage corresponding to the second RC parallel pair, iR ₀ (SOC (t)) represents the ohmic resistance voltage of the state of charge at time t at current i.

In this embodiment, the charging terminal voltage of the target energy storage battery is determined based on kirchhoff's voltage law and the charging parameter, so that the basic terminal voltage characteristics of the target energy storage battery under different charge state levels can be determined, and a target equivalent circuit convenient to construct later can fully consider a better charging and discharging strategy to maximize the energy output of charging and discharging of the target energy storage battery.

Referring to fig. 4, step S302 determines the instantaneous and discretized hysteresis voltages of the target energy storage battery based on the charge parameters of the target energy storage battery, according to some embodiments of the present application, may include, but is not limited to:

step S401, acquiring the state of charge in the state of charge parameter 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;

Step S402, deriving the hysteresis voltage charge correlation expression to obtain a hysteresis voltage derivative expression;

step S403, discretizing the hysteresis voltage derivative expression to obtain discretized hysteresis voltage;

step S404, obtaining a current change state of a target energy storage battery under a preset detection time slot;

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

In step S401 of some embodiments, a hysteresis voltage charge correlation expression is used to represent a correlation between a hysteresis related state and a charge related state.

Specifically, in the charging and discharging process of the target energy storage battery, a tiny loop is generated by frequent charging and discharging, and due to frequent sign change of current, hysteresis effect can occur on the target energy storage battery, so that in the charging and discharging process, the voltage of the target energy storage battery can lag behind the voltage during charging, namely, under the same SOC, the voltage at the end of discharging can be lower than the voltage at the beginning of charging, and specific change conditions of hysteresis voltage under different charge states need to be considered for solving the problem.

Specifically, the hysteresis voltage charge correlation expression may be determined by the following formula:

Wherein h (SOC, t) represents hysteresis voltage under the state of charge at the time t, SOC represents the state of charge, gamma represents a positive constant for regulating the voltage decay rate, sgn (SOC) represents a sign function of the state of charge, represents the direction of change of the state of charge, Refers to a function of state of charge and the rate of change of the derivative of state of charge, representing the maximum hysteresis voltage of the target energy storage battery caused by the hysteresis effect.

In step S402 of some embodiments, the derivation of the hysteresis voltage charge correlation expression may be implemented by a chained method, different state variables (such as voltage, current, SOC, etc. of the battery) associated by the chained method may be implemented, and the dynamic behavior of the target energy storage battery may be more accurately simulated by the chained method, including transient and steady state responses of the energy storage battery during charging and discharging, which is helpful for improving stability of the subsequent equivalent circuit model during charging and discharging.

Specifically, the hysteresis voltage derivative expression may be determined by the following formula:

Wherein, A derivative of the hysteresis voltage at time t, ρ (t) a coulomb efficiency factor at time t, i (t) a current of the target energy storage battery at time t, γ a positive constant for regulating the voltage decay rate, C _n a total charge capacity consumed when discharging the battery from SOC (t) =1 to SOC (t) =0, h (t) a hysteresis voltage at time t,Indicating the maximum hysteresis voltage of the target energy storage cell caused by the hysteresis effect.

In step S403 of some embodiments, the discretization process can further determine that the hysteresis effect of the energy storage battery during charging and discharging causes the maximum hysteresis voltage of the target energy storage battery, that is, the maximum hysteresis voltage M is respectively a negative constant and a positive constant under the condition of charging and discharging the target energy storage battery, which is important for ensuring the stability of the output energy of the target energy storage battery during charging and discharging.

Specifically, the discretized hysteresis voltage may be determined by the following formula:

Where h (k+1) represents the discretized hysteresis voltage at the kth+1th time step, ρ (t) represents the coulomb efficiency factor at the time t, i (t) represents the current of the target energy storage battery at the time t, Δt represents the sampling period, C _n represents the total charge capacity consumed when discharging the battery 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, sgn (i (k)) represents the current change direction at the kth time step.

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 the SOC during the charging and discharging of the target energy storage battery, the transient change hysteresis voltage generated by the target energy storage battery during the change of the current sign is also included, so that in order to further ensure the stability of the output energy of the target energy storage battery during the charging and discharging, the current change state that generates the transient change needs to be considered.

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

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

Wherein, s [ k ] represents a current change state at the kth time step, sgn (i (k)) represents a current change direction at the kth time step, |i [ k ] | >0 represents that a current passes through the target energy storage battery at the kth time step, if sgn (i [ k ]) is positive, it represents that the target energy storage battery is being charged, if sgn (i [ k ]) is negative, it represents that the target energy storage battery is discharging, s [ k-1] represents a current change state at the kth-1 time step, i [ k ] = 0 represents that no current passes through the target energy storage battery at the kth time step, and at this time, the current change state at the kth-1 time step is the same as the current change state at the kth time step.

In step S405 of some embodiments, specifically, the transient hysteresis voltage refers to a voltage of the target energy storage battery that responds to the current change state in time during the charge and discharge process.

Specifically, the value obtained by multiplying the initial hysteresis voltage M ₀ by s [ k ] can be used as the instantaneous hysteresis voltage.

In this embodiment, based on the current change state under the detection time slot, the instantaneous hysteresis voltage of the target energy storage battery is determined, so that the instantaneous hysteresis voltage can be accurately determined, the influence of the instantaneous hysteresis voltage on the whole circuit is considered in the subsequent charging and discharging process of the target energy storage battery, the full output of energy in the charging and discharging process is facilitated, the phenomenon of overcharging or overdischarging is avoided, and the safety of the target energy storage battery is ensured.

In step S303 of some embodiments, specifically, the target hysteresis voltage refers to a voltage corresponding to a hysteresis effect that occurs during a charging and discharging process of the target energy storage battery, and is used to describe a change situation between the voltage and the state of charge generated during the charging and discharging process of the target energy storage battery.

Specifically, the target hysteresis voltage may be determined by the following formula:

U_h＝M₀s[k]+Mh[k]

Where U _h represents the target hysteresis voltage, M ₀ 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.

In the embodiment, the target hysteresis voltage is determined based on the instantaneous hysteresis voltage and the discretized hysteresis voltage, so that the voltage influence of the hysteresis effect on the target energy storage battery in the charge and discharge process can be considered, accurate description of hysteresis phenomenon about a voltage-capacity curve is realized, the construction accuracy of an equivalent circuit model is improved, and the prediction accuracy of the characteristic parameters of the energy storage battery is improved.

In step S304 of some embodiments, the hysteresis factor is a parameter describing the voltage hysteresis degree of the target energy storage battery during the charging and discharging processes, that is, the hysteresis factor may determine the current respective proportion 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.

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

Specifically, the hysteresis factor may be determined by the following formula:

Wherein, Representing the hysteresis factor at the kth time step,Indicating a hysteresis factor at a kth-1 time step, i _k indicating a current at the kth time step, Δt indicating a time step interval, ρ indicating a coulomb efficiency factor, C _n indicating a total charge capacity consumed when discharging the battery from SOC (T) =1 to SOC (T) =0, α indicating a conversion rate of an open-circuit voltage of the control target energy storage battery in the hysteresis main loop during charging and discharging, and a value of α depending on an SOC accumulation amount required for completing one complete conversion of the open-circuit voltage in the hysteresis main loop.

Further, the target energy storage battery is charged and discharged with a changed current mainly passing throughTerm pair hysteresis factorThe influence is generated, and as known from the ampere-hour integration method,The term indicates the amount of change in SOC due to the current operating current i _k, and the amount of change in SOC is amplifiedDoubling and accumulating to obtain hysteresis factorFor the value of (a)In other words, the change coefficient alpha is a limiting condition and is not affected by the change of the working condition whenWhen the absolute value of (a) is greater than a,Can be directly changed into 1 or 0 whenWhen the absolute value of (a) is smaller than a,Then finish one time of alignmentIn particular, the accumulation of (a) in the matrix,And each time the conversion is completed between 0 and 1, the influence of the current accumulation error generated in the charge and discharge process on the target energy storage battery can be timely removed.

In step S305 of some embodiments, the hysteresis voltage characterization model is used to analyze the effect of hysteresis effects generated during charge and discharge on the target energy storage battery.

Further, the influence of the hysteresis factor on the open circuit voltage in the charge-discharge process can be described by the following formula:

Wherein, A hysteresis factor representing at the kth time stepAnd an open circuit voltage at the state of charge of the kth time step,A hysteresis factor representing a kth time step, SOC _k representing a state of charge at the kth time step, OCV _ch(SOC_k) representing a charge open circuit voltage at the state of charge at the kth time step, OCV _dis(SOC_k) representing a discharge open circuit voltage at the state of charge at the kth time step.

Further, the hysteresis voltage characterization model may be described by the following formula:

Where U' (t) represents a hysteresis terminal voltage of the target energy storage battery taking the hysteresis effect into account at time t, OCV (SOC (t)) represents an open circuit voltage corresponding to the state of charge at time t, U ₁ represents a voltage corresponding to the first RC parallel pair, U ₂ represents a voltage corresponding to the second RC parallel pair, iR ₀ (SOC (t)) represents an ohmic resistance voltage of the state of charge at time t at current i, and U _h represents a target hysteresis voltage.

In the embodiment, the hysteresis voltage characterization model is constructed based on the hysteresis factor, the target hysteresis voltage and the charge end voltage, so that the influence of the hysteresis effect on the target energy storage battery in the charging process can be considered, the dynamic behavior of the target energy storage battery in the charging and discharging process can be further accurately simulated, the hysteresis phenomenon of accurately describing the voltage-capacity curve is realized, and the accuracy of the characteristic parameter prediction of the energy storage battery can be improved.

Referring to fig. 5, 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 according to some embodiments of the present application, which may include, but is not limited to:

step S501, an initial equivalent circuit model of a target energy storage battery is constructed based on a hysteresis voltage characterization model and a polarization characterization model;

And step S502, performing circuit stability test on the initial equivalent circuit model to obtain a target equivalent circuit model.

In step S501 of some embodiments, in particular, since the hysteresis voltage characterization model is focused on capturing asymmetry between voltage and state of charge (SOC) of the target energy storage battery during charging and discharging, the polarization characterization model is used to simulate polarization effects of voltage changes caused by electrochemical reactions and ion migration inside the battery, so an initial equivalent circuit model considering the polarization effects and the hysteresis effects can be constructed according to the hysteresis voltage characterization model and the polarization characterization model.

Specifically, taking U1, U2 and SOC as observables, the change condition of U1, U2 and SOC at different time steps can be determined by the following formula:

Wherein SOC _k+1 represents the state of charge at the (k+1) th time step, U _1,k+i represents the voltage corresponding to the first RC parallel pair at the (k+1) th time step, U _2,k+1 represents the voltage corresponding to the second RC parallel pair at the (k+1) th time step, An exponential decay of the voltage with the first polarization time constant tau ₁ is described over a time step interval deltat, deltat representing the time step interval, tau ₁ representing the first polarization time constant,Describing the exponential decay of the voltage with the second polarization time constant τ ₂ over a time step interval Δt, τ ₂ 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 to discharge the battery from SOC (T) =1 to SOC (T) =0, R ₁ represents the polarization resistance, R ₂ 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, and w _3,k represents the uncorrelated zero-mean gaussian white noise caused by the second RC parallel pair at the kth time step.

Specifically, based on the ampere-hour integration method and kirchhoff's law, the initial equivalent circuit model may be determined by the following formula:

Where u _k denotes the circuit-side voltage at the kth time step, A hysteresis factor representing at the kth time stepAnd an open circuit voltage at the state of charge of the kth time step,The hysteresis factor of the kth time step is represented by SOC _k, the state of charge of the kth time step, U _1,k, the voltage corresponding to the first RC parallel pair of the kth time step, U _2,k, the voltage corresponding to the second RC parallel pair of the kth time step, R ₀i_k, the voltage of the ohmic resistor, R ₀, the ohmic resistor, i _k, the current of the kth time step, v _k, the uncorrelated zero-mean gaussian white noise caused by all resistors of the kth time step, U _h, the hysteresis voltage, and U _p.

In the 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, so that the influence of the polarization effect and the hysteresis effect on the circuit can be captured, the problems that the hysteresis phenomenon of a voltage-capacity curve cannot be accurately described and complex phenomena such as concentration polarization and electrochemical polarization cannot be accurately reflected are solved, the construction accuracy of the initial equivalent circuit model is improved, and the accuracy of the characteristic parameter prediction of the energy storage battery is improved.

Referring to fig. 6, in accordance with 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:

Step S601, a plurality of experimental voltage point pairs corresponding to an initial equivalent circuit model are obtained, and at least two target experimental voltage point pairs are determined from the plurality of experimental voltage point pairs;

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

In step S603, when the state prediction data of each point meets the preset voltage state change condition, the initial equivalent circuit model is used as the target equivalent circuit model.

In step S601 of some embodiments, specifically, the experimental voltage point pair is a voltage corresponding to each of two parallel RC obtained when the charge-discharge test is performed on the target energy storage battery, where the experimental voltage point pair reflects a voltage response of the target energy storage battery under different states of charge.

Furthermore, at least two experimental voltage point pairs can be selected as target experimental voltage point pairs at will from a plurality of experimental voltage point pairs, so that the stability of the initial equivalent circuit model can be determined based on the change states of different experimental voltage point pairs.

Referring to fig. 7, step S602 calculates, for each target experimental voltage point pair, its corresponding point pair state prediction data, which may include, but is not limited to:

Step S701, obtaining a target experiment current point pair corresponding to a target experiment voltage point pair in a preset time step;

step S702, calculating the slope corresponding to each time step according to the target experiment voltage point pair and the target experiment current point pair;

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

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

Specifically, since the target energy storage battery has a nonlinear continuous time-varying characteristic, the nonlinear characteristic and the time-varying characteristic thereof need to be considered when testing the stability of the equivalent circuit model, so as to more accurately simulate and predict the charge and discharge process of the target energy storage battery.

Specifically, before determining the target experimental current point pair, an experimental voltage point pair needs to be used as a state variable, and a state space model is constructed, wherein the state variable condition of the experimental voltage point pair can be expressed by the following formula:

Where U '₁ represents a first experimental voltage corresponding to a first experimental RC parallel pair, U' ₂ represents a second experimental voltage corresponding to a second experimental RC parallel pair, τ '₁ represents a first experimental polarization time constant, and τ' ₂ represents a second experimental polarization time constant.

Where 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.

Further, the target experimental current point pair can be respectively corresponding to the capacitance of each experimental RC parallel pairOr (b)Is determined by the product of (c).

In step S702 of some embodiments, in particular, the slope is used to represent the rate at which the target experimental voltage changes over time, and may be determined jointly based on the target experimental current and the target experimental voltage.

Specifically, the slope can be determined by the following fourth-order longge-kutta method:

Wherein kl _Uj represents a first-order slope corresponding to a target experiment voltage of a jth experiment RC parallel pair, deltaT ' represents an experiment time step interval, I _j,n represents a target experiment current corresponding to an nth time step corresponding to a target experiment voltage of the jth experiment RC parallel pair, U ' _j,n represents a target experiment voltage corresponding to an nth time step corresponding to a target experiment voltage of the jth experiment RC parallel pair, C _j represents a total capacity of charges consumed by the jth experiment RC parallel pair, tau ' _j represents a polarization time constant corresponding to the jth experiment RC parallel pair, The first-1 order slope corresponding to the target experimental voltage of the j-th experimental RC parallel pair is shown.

In particular, the method comprises the steps of,The slope of the target experimental voltage change in each order iteration is calculated and, if l=1,The slope is calculated based on the target experimental current and the target experimental voltage for the present time step, and if l=2, 3,4,The slope is calculated based on the value of the previous slope and the average of the target experimental current and the target experimental voltage for the time step.

In this embodiment, by calculating the slope corresponding to each time step according to the target experimental voltage point pair and the target experimental current point pair, it is possible to predict the change situation of the target experimental voltage in the next time step according to the slope, and form the point-to-point state prediction data from all the predicted target experimental voltage data, thereby providing data support for the subsequent stability evaluation of the initial equivalent circuit model.

In step S703 of some embodiments, specifically, the state prediction data refers to state data of the target experimental voltage point over time during the charge and discharge processes.

Further, the target experimental voltage can be updated by the slope of different time steps, and the above slope calculation steps are repeated until the target experimental voltage change is stopped, and the selected time step is ensured to be small enough to capture the periodic behavior of the target experimental voltage.

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

Where 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 n-th time step, Represents the 1 st order slope corresponding to the first experimental voltage,Representing the corresponding 2 nd order slope of the first experimental voltage,Representing the 3 rd order slope corresponding to the first experimental voltage,Indicating the 4 th order slope corresponding to the first experimental voltage.

Where 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 n-th time step,Representing the corresponding 1 st order slope of the second experimental voltage,Representing the corresponding 2 nd order slope of the second experimental voltage,Representing the 3 rd order slope corresponding to the second experimental voltage,Indicating the 4 th order slope corresponding to the second experimental voltage.

In this embodiment, the voltage change state prediction is performed on the target experimental voltage point pair according to the slope of each time step to obtain the point-to-state prediction data, so that the change state of the target experimental voltage point pair along with time can be determined, data support is provided for the stability detection of the subsequent initial equivalent circuit model, and the data support can also be used as a basis for evaluating the performance and the health condition of the target energy storage battery, so that the target energy storage battery can be ensured to accurately predict the behavior of the battery under different working conditions, and the charge and discharge strategy is optimized, thereby improving the service efficiency and the service life of the target energy storage battery.

In step S603 of some embodiments, specifically, the preset voltage state change condition refers to that the same point-to-state predictor data exists when the target experimental voltage point pair is stopped with time change.

Furthermore, in the actual experimental process, the voltage state track of the corresponding point-to-state prediction data of the target experimental voltage point pair can be drawn through a phase plane method, so that the stability of the initial equivalent circuit model is analyzed.

Further, by analyzing the phase trajectory in the neighborhood of the balance point, the stability of the target experimental voltage point pair near the balance point can be judged. The stability of the balance point can be determined through a suction point (namely the same point-to-state predictor data) and a rejection point (namely different point-to-state predictor data), wherein if the phase track approaches the suction point, the balance point is the suction point and represents that the initial equivalent circuit model is stable, if the phase track is far away from the rejection point, the balance point is the rejection point and represents that the initial equivalent circuit model is unstable, the periodic track represents that the initial equivalent circuit model possibly has periodic motion and represents a periodic stable state if the phase track forms a closed loop near the balance point, and the saddle point represents that the point is the saddle point and the initial equivalent circuit model is stable in certain directions and unstable in other directions if the phase track of the balance point represents a saddle shape.

For example, the target experimental voltage point pairs (0.4,0.35), (1.2,1.75) and (2.0, 2.5) are each represented as (1.4,1.65) by predicting that the same point pair state predictor data exists when the target experimental voltage point pairs stop with time, and the initial equivalent circuit model is taken as the target equivalent circuit model.

In this embodiment, when the state prediction data of each point meets 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 in the charging and discharging process can be accurately simulated, and the accuracy of predicting the characteristic parameters of the energy storage battery is improved.

Referring to FIG. 8, it can be appreciated that the target equivalent circuit model is composed of open circuit voltages taking hysteresis factors into accountThe ohmic resistor R0, the input current source i, the hysteresis voltage Uh and the circuit terminal voltage are formed by two parallel RC pairs, wherein one RC consists of a polarization resistor R1 and a polarization capacitor C1, and the other RC pair consists of a concentration polarization resistor R2 and a concentration polarization capacitor C2.

Further, the values of two parallel RC pairs follow the SOC andIs varied by a variation of (1) the value of the open circuit voltage OCV is determined by the SOC and the hysteresis factorAnd (3) jointly determining.

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

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

Specifically, a target pulse current can be applied to a target energy storage battery, and the current state of charge can be predicted through a target equivalent circuit model by combining a coulomb efficiency factor and an ampere-hour integration method.

Specifically, the discharging capacity of the target energy storage battery under different charge states and the degradation capacity of the battery in the aging process are analyzed through the target equivalent circuit model so as to determine the residual life of the battery.

Specifically, the internal resistance increase, capacitance capacity decay and the like of the target energy storage battery are analyzed through the target equivalent circuit model so as to determine the health state of the battery.

In the embodiment, the battery characteristic parameter prediction is performed based on the target equivalent circuit model, so that the change condition of the battery under different working conditions can be simulated by the target equivalent circuit model taking the polarization effect and the hysteresis effect into consideration, and the accuracy of the characteristic parameter prediction of the energy storage battery is improved.

Referring to fig. 9, it can be understood that the corresponding global voltage capacity distribution parameter can be determined through the hysteresis main loop test, the corresponding local voltage capacity distribution parameter can be determined through the hysteresis minor loop test, the global voltage capacity distribution parameter is updated by the local voltage capacity distribution parameter, the final voltage capacity distribution parameter is determined, the hysteresis voltage characterization model is constructed based on the voltage capacity distribution parameter, the battery polarization parameter is determined through the HPPC test, the polarization characterization model is constructed according to the battery polarization parameter, further, a second-order RC equivalent circuit model considering polarization and hysteresis effect is constructed by combining the hysteresis voltage characterization model and the polarization characterization model, finally, the state space model corresponding to each target experiment voltage is constructed by taking the target experiment voltage as an observation state quantity, the change state of the target experiment voltage along with time is analyzed based on the longger-library method, the evolution of the target experiment voltage along with time is determined, the analysis step of the longger-library method is repeated until the periodic change of the target experiment voltage along the whole experiment period is obtained, if the end point of the phase trajectory along with the change along with the time of the target experiment voltage along with the phase plane method is equal to the second-order RC equivalent circuit, and the state of charge of the battery is drawn through the battery life and the state of a stable state of charge, and the battery life is stable.

According to the embodiment of the application, the battery polarization parameters are obtained by carrying out mixed pulse power test on the target energy storage battery, the polarization characterization model is built based on the battery polarization parameters, the hysteresis loop test is carried out on the target energy storage battery to obtain the voltage capacity distribution parameters, the hysteresis voltage characterization model is built based on the voltage capacity distribution parameters, the equivalent modeling is carried out on the target energy storage battery according to the hysteresis voltage characterization model and the polarization characterization model to obtain the target equivalent circuit model, and the battery characteristic parameter prediction is carried out based on the target equivalent circuit model to obtain the target battery prediction parameters. In this way, the accuracy of the characteristic parameter prediction of the energy storage battery can be improved.

Referring to fig. 10, fig. 10 illustrates a hardware structure of an electronic device according to another embodiment, the electronic device includes:

The processor 1001 may be implemented by using a general purpose CPU (Central Processing Unit ), a microprocessor, an Application SPECIFIC INTEGRATED Circuit (ASIC), or one or more integrated circuits, etc. to execute related programs to implement the technical solution provided by the embodiments of the present application;

The Memory 1002 may be implemented in the form of a Read Only Memory (ROM), a static storage device, a dynamic storage device, or a random access Memory (Random Access Memory, RAM). The memory 1002 may store a processing system and other application programs, and when the technical solutions provided in the embodiments of the present disclosure are implemented by software or firmware, relevant program codes are stored in the memory 1002, and the processor 1001 invokes a parameter analysis method for an energy storage battery to perform an embodiment of the present disclosure;

an input/output interface 1003 for implementing information input and output;

The communication interface 1004 is configured to implement communication interaction between the present device and other devices, and may implement communication in a wired manner (e.g. USB, network cable, etc.), or may implement communication in a wireless manner (e.g. mobile network, WIFI, bluetooth, etc.);

a bus 1005 for transferring information between the various components of the device (e.g., the processor 1001, memory 1002, input/output interface 1003, and communication interface 1004);

Wherein the processor 1001, the memory 1002, the input/output interface 1003, and the communication interface 1004 realize communication connection between each other inside the device through the bus 1005.

Claims

1. A parameter analysis method for an energy storage battery, characterized in that the method comprises:

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

Performing a hysteresis loop test on the target energy storage battery to obtain 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 an energy storage battery 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 comprises:

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 an energy storage battery according to claim 2, characterized in that the circuit stability test is performed on the initial equivalent circuit model to obtain the target equivalent circuit model, comprising:

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 corresponding point pair state prediction data for each target experimental voltage point pair comprises:

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 hysteresis voltage characterization model is constructed based on the voltage capacity distribution parameters, comprising:

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;

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 an energy storage battery 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 parameters 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;

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 an 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;

8. The parameter analysis method for energy storage batteries according to claim 1, characterized in that the polarization characterization model is constructed based on the battery polarization parameters, comprising:

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 an energy storage battery according to claim 1, characterized in that the hysteresis loop test is performed on the target energy storage battery to obtain the 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 comprises a memory and a processor, the memory stores a computer program, and the processor implements the parameter analysis method for an energy storage battery according to any one of claims 1 to 9 when executing the computer program.