CN111896875A - Power battery SOC estimation method considering hysteresis effect - Google Patents
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Abstract
The invention provides a power battery SOC estimation method considering hysteresis effect, which comprises the following steps: acquiring a hysteresis main loop characteristic curve and a hysteresis small loop characteristic curve of the power battery; acquiring SOC accumulation of the OCV conversion stage of charging and discharging of the power battery according to the hysteresis main loop and the small loop characteristic curve; establishing hysteresis factor according to SOC accumulation
An effective mathematical model of (a); according to
The simplified hysteresis OCV model of the power battery is constructed by the effective mathematical model; obtaining a first-order RC equivalent circuit model after the dispersion and linearization of the power battery according to the simplified hysteresis OCV model; and estimating the SOC of the power battery by adopting an EKF algorithm according to the first-order RC equivalent circuit model. The invention is based on powerThe simplified hysteresis OCV model of the power battery, which can balance the precision and the complexity, is constructed by the hysteresis loop characteristic curve of the battery, so that the precision of the equivalent circuit model of the battery is improved, and the estimation performance of the SOC is greatly improved.
Description
Technical Field
The invention relates to the technical field of batteries, in particular to a method for estimating the SOC (State of Charge) of a power battery by considering a hysteresis effect.
Background
The power battery pack is used as a key part of the electric automobile, the SOC of the power battery is used for directly reflecting the residual electric quantity of the battery, the power battery SOC is an important basis for a finished automobile control system to formulate an optimal energy management strategy, and the accurate estimation of the SOC value of the power electricity ground is of great significance for improving the safety and reliability of the battery, improving the energy utilization rate of the battery and prolonging the service life of the battery.
In the related art, when performing SOC estimation, a large number of battery models are used mainly as equivalent circuit models in cooperation with an Extended Kalman Filter (EKF) algorithm. In an equivalent circuit model, a nonlinear relationship (OCV-SOC) between an OCV (open circuit Voltage) and an SOC plays a crucial role in accurate estimation of a battery SOC, and an accurate OCV-SOC characteristic curve helps to improve estimation accuracy. Due to the uncertainty and complexity of the electrochemical reaction inside the cell, there are different OCVs, i.e. hysteresis effects, even under the same SOC conditions. If the influence of this effect is neglected in modeling, inevitable errors in the SOC estimation result will inevitably occur. At present, for equivalent circuit model modeling considering the hysteresis effect of a battery, the algorithm is not too complex, engineering is not easy to realize, and the accuracy and complexity of SOC estimation cannot be balanced if the error is large.
Disclosure of Invention
The invention aims to solve the technical problems and provides a power battery SOC estimation method considering the hysteresis effect.
The technical scheme adopted by the invention is as follows:
a method for estimating the SOC of a power battery considering the hysteresis effect comprises the following steps: step S1, acquiring the motionA hysteresis main loop characteristic curve and a hysteresis small loop characteristic curve of the force battery; step S2, acquiring SOC accumulation of the open-circuit voltage of the power battery in the conversion stage between the charging characteristic curve and the discharging characteristic curve according to the hysteresis main loop characteristic curve and the hysteresis small loop characteristic curve; step S3, establishing hysteresis factor by using ampere-hour integration method according to SOC accumulation of open-circuit voltage of power battery in conversion stage between charging characteristic curve and discharging characteristic curve
An effective mathematical model of (a); step S4, according to the hysteresis factor
The effective mathematical model of the power battery constructs a simplified hysteresis OCV model of the power battery; step S5, according to the simplified hysteresis OCV model, adopting the ampere-hour integration method and kirchhoff law to obtain a first-order RC equivalent circuit model after the power battery is dispersed and linearized; and step S6, estimating the SOC of the power battery by adopting an EKF algorithm according to the first-order RC equivalent circuit model after the power battery is dispersed and linearized.
According to an embodiment of the present invention, step S1, acquiring a hysteresis main loop characteristic curve of the power battery includes: step S101, fully standing the power battery after the electric quantity of the power battery is discharged; step S102, under the condition of 0.1C constant current pulse, charging the power battery with the charging depth of delta SOC (state of charge) 0.1 until the SOC is equal to 1, and acquiring charging data in the charging process; step S103, discharging the power battery with delta SOC (state of charge) of 0.1 under the condition of a 0.1C constant current pulse until the SOC is equal to 0, and acquiring discharge data in the discharging process; and step S104, acquiring a hysteresis main loop characteristic curve of the power battery according to the charging data and the discharging data.
According to an embodiment of the present invention, step S2, acquiring a hysteresis small loop characteristic curve of the power battery includes: step S201, fully charging the power battery, and fully standing; step S202, discharging the power battery with delta SOC being 0.2 under the condition of 1C constant current pulse, and stopping discharging for a preset time when the SOC is reduced by 0.2; step S203, under the condition of a 1C constant current pulse, charging the power battery with a charging depth of 0.1 as delta SOC, and stopping charging for a preset time when the SOC rises by 0.1; step S204, repeating the steps S201-S203, and acquiring charging data and discharging data; step S205, charging the power battery by the 1C constant current pulse until the SOC is 1, and acquiring charging data; and step S206, acquiring a hysteresis small loop characteristic curve of the power battery according to the charging data and the discharging data.
According to one embodiment of the invention, the hysteresis factor is established according to the following formula
Effective mathematical model of (1):
α＝(α1+α2) 2; wherein k represents a time step,
is the hysteresis factor at the time k,
is the hysteresis factor at time k-1, ikDelta t is the sampling period C for the working current of the power batterynIs the rated total capacity, alpha, of the power battery1And alpha2And the SOC accumulation amount is the open-circuit voltage of the power battery in the conversion stage between the charging characteristic curve and the discharging characteristic curve.
According to one embodiment of the invention, a simplified hysteresis OCV model of the power cell is constructed according to the following formula:
wherein the content of the first and second substances,
the open circuit voltage of the power cell increasing the hysteresis factor for time k,hysteresis factor, OCV, at time kch(SOCk) Open circuit voltage, OCV, for charging a power cell at time kdis(SOCk) The open-circuit voltage is the open-circuit voltage when the power battery k is discharged at the moment.
According to one embodiment of the invention, the first-order RC equivalent circuit model after the power battery is discretized and linearized is obtained by adopting the following formula:
wherein R isIIs the equivalent internal ohmic resistance, R, of the first-order RC equivalent circuitDIs the equivalent polarization resistance, C, of the first-order RC equivalent circuitDEquivalent polarization capacitance, U, for said first order RC equivalent circuitD,kIs the k-time resistance R of the first-order RC equivalent circuitDVoltage across, w1、w2And v is zero-mean Gaussian white noise, η is the efficiency of the charger reservoir, UkThe terminal voltage of the battery at the moment k in the first-order RC equivalent circuit.
The invention has the beneficial effects that:
according to the invention, a simplified hysteresis OCV model of the power battery, which can balance the precision and the complexity, is constructed according to the hysteresis loop characteristic curve of the power battery, so that the precision of the equivalent circuit model of the battery is improved, and the estimation performance of the SOC is further improved to a large extent.
Drawings
FIG. 1 is a flow chart of a power cell SOC estimation method that accounts for hysteresis effects according to one embodiment of the present disclosure;
FIG. 2 is a flowchart of a method for obtaining a hysteresis main loop characteristic according to an embodiment of the present invention;
FIG. 3 is a flow chart of a method for obtaining a hysteresis small loop characteristic according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a hysteresis main loop characteristic and a hysteresis small loop characteristic in accordance with one embodiment of the present invention;
FIG. 5 is a diagram of an equivalent circuit model according to one embodiment of the present invention;
FIG. 6 is a schematic diagram of estimating power cell SOC using an EKF algorithm, according to one embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a flowchart of a power battery SOC estimation method considering hysteresis effect according to an embodiment of the present invention. As shown in fig. 1, the method comprises the steps of:
and step S1, acquiring a hysteresis main loop characteristic curve and a hysteresis small loop characteristic curve of the power battery.
Further, the hysteresis main loop characteristic is an OCV-SOC characteristic curve of the battery over a complete SOC cycle. Taking into account polarization reactions inside the cell. The experimental method selects a smaller C multiplying power to carry out constant-current pulse charging and discharging, a longer standing process is needed in a pulse gap to enable internal chemical reaction to reach a stable state, and the charging OCV is determined according to experimental datach-SOC and discharge OCVdis-hysteresis main loop characteristic curve constituted by SOC. As shown in fig. 2, the specific steps are as follows:
and step S101, fully standing the power battery after the electric quantity of the power battery is discharged.
And step S102, charging the power battery with a charging depth of 0.1 as delta SOC under the condition of 0.1C constant current pulse until the SOC is equal to 1, and acquiring charging data of the charging process. The charge data includes an open circuit voltage OCV and an SOC at the time of charging.
And step S103, discharging the power battery with the delta SOC being 0.1 under the condition of the 0.1C constant current pulse until the SOC is equal to 0, and acquiring discharge data of the discharge process. The discharge data includes open-circuit voltage OCV and SOC at the time of discharge.
And step S104, acquiring a hysteresis main loop characteristic curve of the power battery according to the charging data and the discharging data.
In view of the characteristic that the charging and discharging current of the battery frequently changes in the driving process of the new energy automobile, a plurality of small loops, namely the hysteresis small loop, exist in the hysteresis main loop, and are an OCV-SOC characteristic curve formed under a local SOC cycle period, in order to research the characteristics of the hysteresis small loop, the battery is tested by adopting the sawtooth-shaped charging and discharging current in an experiment, as shown in fig. 3, the specific steps are as follows:
and step S201, fully charging the power battery, and fully standing.
And step S202, discharging the power battery with the delta SOC being 0.2 under the condition of the 1C constant current pulse, stopping discharging for a preset time when the SOC is reduced by 0.2, and acquiring discharge data in the discharging process.
The preset time can be preset according to the actual condition of the power battery.
And step S203, charging the power battery with a charging depth of 0.1 of delta SOC under the condition of a 1C constant current pulse, stopping charging for a preset time when the SOC rises by 0.1, and acquiring charging data in the charging process.
In step S204, it is determined whether there is an SOC equal to 0. If not, returning to the step S202; if so, step S205 is performed.
And step S205, charging the power battery with a 1C constant current pulse until the SOC is 1, and acquiring charging data.
And step S206, acquiring a hysteresis small loop characteristic curve of the power battery according to the charging data and the discharging data.
The hysteresis main loop characteristic curve and the hysteresis small loop characteristic curve can be obtained in advance through the experiment, are prestored in corresponding memories, and are directly called when the SOC is estimated.
By performing the hysteresis characteristic test experiment on the power battery, a plurality of small hysteresis loops exist in the hysteresis main loop, and fig. 4 is a schematic diagram of a certain hysteresis small loop characteristic curve in the hysteresis main loop characteristic curve obtained by the experiment. Wherein the OCVchSOC is the charging characteristic curve, OCVdisSOC is a discharge characteristic curve, and an arrow part is a hysteresis small loop characteristic curve.
Step S2, according to the hysteresis main loop characteristic curve and the hysteresis small loop characteristic curve, obtaining the SOC accumulation alpha of the power battery at the stage of the open-circuit voltage conversion between the charging characteristic curve and the discharging characteristic curve1And alpha2。
Specifically, as shown in FIG. 4, segments of the heads AB and CD indicate the OCV at the OCV when the direction of the charging and discharging current is changedchSOC and OCVdisExcessive variation between SOC characteristics, with BC and DA segments representing OCV variation at OCVch-SOC and OCV when charging and discharging current direction is unchangeddis-change in one of the two characteristic curves of the SOC, the arrow segments combining into a hysteresis loop created by the hysteresis effect. Wherein alpha is1And alpha2Respectively corresponding to the OCV of the batterychSOC and OCVdisAB of the transition between the SOC characteristic curves and the SOC accumulation amount in the CD phase.
Step S3, SOC accumulation quantity alpha is converted between the charging characteristic curve and the discharging characteristic curve according to the open-circuit voltage of the power battery1And alpha2Establishing hysteresis factor by ampere-hour integration method
An effective mathematical model of (1).
Further, according to an embodiment of the present invention, the hysteresis factor is established according to the following formula
Effective mathematical model of (1):
α＝(α1+α2)/2；
wherein k represents a time step,
is the hysteresis factor at the time k,
is the hysteresis factor at time k-1, ikDelta t is the sampling period C for the working current of the power batterynIs the rated total capacity, alpha, of the power battery1And alpha2The SOC accumulation amount is the conversion stage of the open-circuit voltage of the power battery between the charging characteristic curve and the discharging characteristic curve.
Step S4, according to hysteresis factor
The simplified hysteresis OCV model of the power cell is constructed.
Further, according to one embodiment of the invention, a simplified hysteresis OCV model of the power cell is constructed according to the following formula:
wherein the content of the first and second substances,
the open circuit voltage of the power cell increasing the hysteresis factor for time k,
hysteresis factor, OCV, at time kch(SOCk) Open circuit voltage, OCV, for charging a power cell at time kdis(SOCk) The open-circuit voltage is the open-circuit voltage when the power battery k is discharged at the moment.
Hysteresis factor
Can determine the OCVchAnd OCVdisThe proportion of each OCV in the hysteresis OCV model is used for adjusting the conversion of the OCV in the hysteresis main loop between the charge and discharge balance potential of the battery. In particular when
At the boundary 1 or 0, the OCV-SOC relationship is respectively with the charging OCVch-SOC and OCVdis-the SOC are identical.
And step S5, obtaining a first-order RC equivalent circuit model after the power battery is dispersed and linearized by adopting an ampere-hour integration method and kirchhoff law according to the simplified hysteresis OCV model.
From the aspects of both the accuracy and the complexity of modeling, the equivalent circuit model scheme considering the hysteresis effect can adopt a first-order RC circuit form shown in FIG. 5, wherein R isD、RIRepresents a resistance, CDRepresents a capacitance, UDIs RDThe voltage across the terminals, U represents the terminal voltage,
the open circuit voltage of the power cell is a function of the hysteresis factor. The circuit has the characteristic of simple operation, can reflect the static characteristic of the battery and the polarization phenomenon of the battery, and is easy to realize in engineering.
Selecting U in the model shown in FIG. 5DAnd SOC as a state quantity, and U as an observed quantity. According to an ampere-hour integral method and kirchhoff's law, a first-order RC model state equation after the battery is dispersed and linearized can be obtained:
wherein R isIIs the equivalent internal ohmic resistance, R, of the first-order RC equivalent circuitDEquivalent polarization for first-order RC equivalent circuitResistance, CDEquivalent polarization capacitance, U, for said first order RC equivalent circuitD,kIs a k-time resistor R of a first-order RC equivalent circuitDVoltage across, w1、w2And v is zero-mean Gaussian white noise, η is the efficiency of the charger reservoir, UKThe terminal voltage of the power battery at the moment k is a first-order RC equivalent circuit.
Definitions A, B, HkD is a state space model, A is a state transition matrix, B is a state control matrix, HkIs an observation matrix, D is an observation control matrix, wherein:
and step S6, estimating the SOC of the power battery by adopting an EKF algorithm according to the first-order RC equivalent circuit model after the power battery is dispersed and linearized.
According to the established first-order RC battery equivalent circuit model considering the hysteresis effect, the state space of the EKF discrete system is shown as the following formula:
in the formula, xk＝[SOCk,UD,k]Is a system state variable; u. ofk＝[ik]Inputting for the system; z is a radical ofk＝[Uk]Outputting for the system; w is ak＝[w1，k，w2，k]For Gaussian process noise, A is the state transition matrix, B is the state control matrix, HkD is an observation control matrix.
The steps of estimating the SOC of the battery by applying the simplified hysteresis OCV model by the EKF algorithm are as follows:
1. state and covariance initialization:
wherein x is0Is an initial value of state, P0Is an initial value of the state covariance P；
SOC estimation
Firstly, predicting a state variable in one step:
xk|k-1＝Axk-1+Buk
wherein x isk-1The state quantity, x, estimated for the time k-1k|k-1A is a state transition matrix and B is a state control matrix, wherein the current state estimated value is obtained by estimating the state quantity at the moment of k-1.
One-step prediction result P of state covariancek|k-1：
Pk|k-1＝APk-1AT+Q
Wherein Q is the observation noise covariance; a. theTA transposed matrix representing A, Pk|k-1Is the current state covariance derived from the state covariance at time k-1.
Computing hysteresis factor
And fourthly, estimating the current OCV by using the simplified hysteresis OCV model:
fifthly, updating the observation matrix
Calculating the voltage estimation errork：
k＝zk-Hkxk|k-1-Duk；
In the formula (I), the compound is shown in the specification,kfor voltage estimation error, zk＝[Uk]Is the system output, HkTo observe the matrix, xk|k-1Is the current state estimated value obtained by estimation according to the state quantity at the moment of k-1,d is an observation control matrix, uk＝[ik]Is the system input.
Seventhly, calculating Kalman filtering gain Kk：
In the formula, KkFor Kalman filter gain, Pk|k-1Is the current state covariance derived from the state covariance at time k-1, R is the observed noise covariance, HkIs an observation matrix.
Optimal estimation of state xk：
xk＝xk|k-1+Kk k；
In the formula, xk-1The state quantities estimated for time k.
(ninthly) optimal estimation result P of covariance of statek：
Pk＝(I+KkHk)Pk|k-1；
In the formula, PkThe state covariance is estimated for time k.
The principle of estimating the power battery SOC by using the EKF algorithm can be referred to FIG. 6.
In summary, according to the method for estimating SOC of a power battery considering hysteresis effect of the embodiment of the present invention, first, a hysteresis main loop characteristic curve and a hysteresis small loop characteristic curve of the power battery are obtained, then, according to the hysteresis main loop characteristic curve and the hysteresis small loop characteristic curve, an SOC accumulation amount of an open-circuit voltage of the power battery at a conversion stage between a charging characteristic curve and a discharging characteristic curve is obtained, and according to the SOC accumulation amount of the power battery at a conversion stage between the charging characteristic curve and the discharging characteristic curve, an ampere-hour integration method is used to establish a hysteresis factor
According to the effective mathematical model of
The method comprises the steps of constructing a simplified hysteresis OCV model of the power battery by using the effective mathematical model, obtaining a first-order RC equivalent circuit model after the power battery is dispersed and linearized by using an ampere-hour integration method and a kirchhoff law according to the simplified hysteresis OCV model, and estimating the SOC of the power battery by using an EKF algorithm according to the first-order RC equivalent circuit model after the power battery is dispersed and linearized. Therefore, under the condition that the hysteresis effect exists in charging and discharging of the power battery, the dynamic and static characteristics of the battery can be better reflected by using the equivalent circuit model constructed by the simplified hysteresis OCV model from the aspects of precision and complexity of balance construction of the OCV model, the precision of the battery model is effectively improved, the constructed battery equivalent circuit model considering the hysteresis effect is applied to the EKF algorithm, and the SOC estimation performance of the EKF algorithm is greatly improved.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
Claims (6)
1. A method for estimating the SOC of a power battery considering the hysteresis effect is characterized by comprising the following steps:
step S1, acquiring a hysteresis main loop characteristic curve and a hysteresis small loop characteristic curve of the power battery;
step S2, acquiring SOC accumulation of the open-circuit voltage of the power battery in the conversion stage between the charging characteristic curve and the discharging characteristic curve according to the hysteresis main loop characteristic curve and the hysteresis small loop characteristic curve;
step S3, establishing hysteresis factor by using ampere-hour integration method according to SOC accumulation of open-circuit voltage of power battery in conversion stage between charging characteristic curve and discharging characteristic curve
An effective mathematical model of (a);
step S4, according to the hysteresis factor
The effective mathematical model of the power battery constructs a simplified hysteresis OCV model of the power battery;
step S5, according to the simplified hysteresis OCV model, adopting the ampere-hour integration method and kirchhoff law to obtain a first-order RC equivalent circuit model after the power battery is dispersed and linearized;
and step S6, estimating the SOC of the power battery by adopting an EKF algorithm according to the first-order RC equivalent circuit model after the power battery is dispersed and linearized.
2. The method for estimating the SOC of the power battery considering the hysteresis effect according to claim 1, wherein the step S1 of obtaining the hysteresis main loop characteristic curve of the power battery comprises:
step S101, fully standing the power battery after the electric quantity of the power battery is discharged;
step S102, under the condition of 0.1C constant current pulse, charging the power battery with the charging depth of delta SOC (state of charge) 0.1 until the SOC is equal to 1, and acquiring charging data in the charging process;
step S103, discharging the power battery with delta SOC (state of charge) of 0.1 under the condition of a 0.1C constant current pulse until the SOC is equal to 0, and acquiring discharge data in the discharging process;
and step S104, acquiring a hysteresis main loop characteristic curve of the power battery according to the charging data and the discharging data.
3. The method for estimating the SOC of the power battery considering the hysteresis effect according to claim 1, wherein the step S2 of obtaining the hysteresis small loop characteristic curve of the power battery comprises:
step S201, fully charging the power battery, and fully standing;
step S202, discharging the power battery with delta SOC being 0.2 under the condition of 1C constant current pulse, stopping discharging for preset time when the SOC is reduced by 0.2, and acquiring discharging data in the discharging process;
step S203, under the condition of a 1C constant current pulse, charging the power battery with a charging depth of 0.1 as delta SOC, stopping charging for a preset time when the SOC rises by 0.1, and acquiring charging data in the charging process;
step S204, repeating the steps S201-S203 until the SOC is equal to 0;
step S205, charging the power battery by the 1C constant current pulse until the SOC is 1, and acquiring charging data;
and step S206, acquiring a hysteresis small loop characteristic curve of the power battery according to the charging data and the discharging data.
4. The method for estimating the SOC of the power battery considering the hysteresis effect as claimed in claim 1, wherein the hysteresis factor is established according to the following formula
Effective mathematical model of (1):
α＝(α1+α2)/2；
wherein k represents a time step,
is the hysteresis factor at the time k,
is the hysteresis factor at time k-1, ikDelta t is the sampling period C for the working current of the power batterynIs the rated total capacity, alpha, of the power battery1And alpha2And the SOC accumulation amount is the open-circuit voltage of the power battery in the conversion stage between the charging characteristic curve and the discharging characteristic curve.
5. The method for estimating the SOC of the power battery considering the hysteresis effect is characterized in that the simplified hysteresis OCV model of the power battery is constructed according to the following formula:
wherein the content of the first and second substances,
the open circuit voltage of the power cell increasing the hysteresis factor for time k,
hysteresis factor, OCV, at time kch(SOCk) Open circuit voltage, OCV, for charging a power cell at time kdis(SOCk) Open circuit for k-time discharge of power batteryA voltage.
6. The method for estimating the SOC of the power battery considering the hysteresis effect is characterized in that the first-order RC equivalent circuit model after the power battery is discretized and linearized is obtained by adopting the following formula:
wherein R isIIs the equivalent internal ohmic resistance, R, of the first-order RC equivalent circuitDIs the equivalent polarization resistance, C, of the first-order RC equivalent circuitDEquivalent polarization capacitance, U, for said first order RC equivalent circuitD,kIs the k-time resistance R of the first-order RC equivalent circuitDVoltage across, w1、w2And v is zero-mean Gaussian white noise, η is the efficiency of the charger reservoir, UkAnd the terminal voltage of the power battery at the moment k is the first-order RC equivalent circuit.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112485680A (en) * | 2020-11-27 | 2021-03-12 | 浙江零跑科技有限公司 | Battery SOC estimation method |
| CN112684342A (en) * | 2020-12-01 | 2021-04-20 | 郑州大学 | Method for evaluating heat generation rate in charging/discharging process of sodium ion battery |
| CN114325199A (en) * | 2022-01-04 | 2022-04-12 | 中国船舶重工集团公司第七一一研究所 | Supercapacitor internal resistance detection method and device and storage medium |
| CN116500461A (en) * | 2023-06-29 | 2023-07-28 | 安徽锐能科技有限公司 | SOC estimation method and system under battery hysteresis model |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101946187A (en) * | 2008-02-19 | 2011-01-12 | 通用汽车环球科技运作公司 | Battery hysteresis based on model is estimated |
| CN107368619A (en) * | 2017-06-02 | 2017-11-21 | 华南理工大学 | EKF SOC estimation method based on battery hysteresis voltage characteristic and resilience voltage characteristic |
| CN107894570A (en) * | 2017-10-23 | 2018-04-10 | 北京新能源汽车股份有限公司 | The evaluation method and device of battery pack SOC based on Thevenin models |
-
2020
- 2020-07-28 CN CN202010735056.7A patent/CN111896875A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101946187A (en) * | 2008-02-19 | 2011-01-12 | 通用汽车环球科技运作公司 | Battery hysteresis based on model is estimated |
| CN107368619A (en) * | 2017-06-02 | 2017-11-21 | 华南理工大学 | EKF SOC estimation method based on battery hysteresis voltage characteristic and resilience voltage characteristic |
| CN107894570A (en) * | 2017-10-23 | 2018-04-10 | 北京新能源汽车股份有限公司 | The evaluation method and device of battery pack SOC based on Thevenin models |
Non-Patent Citations (4)
| Title |
|---|
| CHANG YOONCHUN ET AL.: "Covariance controlled state-of-charge estimator of LiFePO4 cells using a simplified hysteresis model", 《ELECTROCHIMICA ACTA》 * |
| ZHICHENG XU ET AL.: "Improving the state of charge estimation of reused lithium-ion batteries by abating hysteresis using machine learning technique", 《JOURNAL OF ENERGY STORAGE》 * |
| 程泽等: "等效滞回模型在锂离子电池SOC估计中的应用", 《湖南大学学报(自然科学版)》 * |
| 谈发明等: "基于简化滞回OCV模型的锂电池SOC自适应估计策略", 《中国电机工程学报》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112485680A (en) * | 2020-11-27 | 2021-03-12 | 浙江零跑科技有限公司 | Battery SOC estimation method |
| CN112485680B (en) * | 2020-11-27 | 2024-04-23 | 浙江零跑科技股份有限公司 | Battery SOC estimation method |
| CN112684342A (en) * | 2020-12-01 | 2021-04-20 | 郑州大学 | Method for evaluating heat generation rate in charging/discharging process of sodium ion battery |
| CN114325199A (en) * | 2022-01-04 | 2022-04-12 | 中国船舶重工集团公司第七一一研究所 | Supercapacitor internal resistance detection method and device and storage medium |
| CN114325199B (en) * | 2022-01-04 | 2023-11-14 | 中国船舶集团有限公司第七一一研究所 | Method and device for detecting internal resistance of super capacitor and storage medium |
| CN116500461A (en) * | 2023-06-29 | 2023-07-28 | 安徽锐能科技有限公司 | SOC estimation method and system under battery hysteresis model |
| CN116500461B (en) * | 2023-06-29 | 2023-10-27 | 安徽锐能科技有限公司 | SOC estimation method and system under battery hysteresis model |
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