CN105203963B - A kind of method of estimation of the state-of-charge based on open-circuit voltage hysteretic characteristic - Google Patents
A kind of method of estimation of the state-of-charge based on open-circuit voltage hysteretic characteristic Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 36
- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 claims abstract description 35
- 229910001416 lithium ion Inorganic materials 0.000 claims abstract description 35
- 230000003044 adaptive effect Effects 0.000 claims abstract description 11
- 239000013598 vector Substances 0.000 claims description 23
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000002474 experimental method Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 230000003247 decreasing effect Effects 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 230000001174 ascending effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 238000004146 energy storage Methods 0.000 description 1
- GELKBWJHTRAYNV-UHFFFAOYSA-K lithium iron phosphate Chemical compound [Li+].[Fe+2].[O-]P([O-])([O-])=O GELKBWJHTRAYNV-UHFFFAOYSA-K 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 229910052987 metal hydride Inorganic materials 0.000 description 1
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Abstract
The present invention relates to a kind of method of estimation of the state-of-charge based on open-circuit voltage hysteretic characteristic, for the state-of-charge of On-line Estimation lithium ion battery, comprise the following steps：1) the hysteretic characteristic curve of lithium ion battery open-circuit voltage and state-of-charge is obtained offline；2) initial parameter for determining the open-circuit voltage hysteretic characteristic adaptive model based on Preisach operators is trained according to hysteretic characteristic curve, and establishes the open-circuit voltage hysteretic characteristic adaptive model based on Preisach operators；3) according to the state-of-charge of the open-circuit voltage hysteretic characteristic adaptive model On-line Estimation lithium ion battery based on Preisach operators, the state-of-charge of current time lithium ion battery is obtained.Compared with prior art, the present invention has the advantages that accurate modeling, raising precision, estimation are accurate.
Description
Technical Field
The invention relates to a state of charge estimation method, in particular to a state of charge estimation method based on open-circuit voltage hysteresis characteristics.
Background
The power battery system is used as a key part and is increasingly applied to the fields of electric automobiles, power energy storage and the like. In the application process, a Battery Management System (BMS) is required to monitor the Battery state, prevent overcharge and overdischarge, and prolong the service life of the Battery. Among these, accurate estimation of SOC (state of charge) is particularly critical. Most SOC estimation methods are obtained by using a correspondence relationship between SOC and Open Circuit Voltage OCV (Open Circuit Voltage), such as an Open Circuit Voltage method and a model-based SOC estimation method. The description of the OCV and SOC correspondence is the core basis of these SOC estimation methods. The open-circuit voltage and the OCV in the lithium ion battery are not completely in one-to-one correspondence, but have a hysteresis relationship (the OCV in the charging process is greater than the OCV in the discharging process under the same SOC).
The traditional modeling method for the open-circuit voltage hysteresis characteristic of the lithium ion battery introduces more simplification, so that the modeling precision of a hysteresis model is low, and SOC estimation is influenced. The hysteresis model modeling method based on the Preisach operator is already applied to open-circuit voltage hysteresis modeling of a nickel-metal hydride battery (NiMH), but the discrete Preisach model cannot be well applied to the lithium ion battery because the open-circuit voltage hysteresis relation of the lithium ion battery is not obvious and has no symmetry compared with the NiMH battery.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide the state of charge estimation method based on the hysteresis characteristic of the open-circuit voltage, which is accurate in modeling, accuracy improving and estimation.
The purpose of the invention can be realized by the following technical scheme:
a state of charge estimation method based on open-circuit voltage hysteresis characteristics is used for estimating the state of charge of a lithium ion battery on line and comprises the following steps:
1) obtaining a hysteresis characteristic curve of the open circuit voltage and the charge state of the lithium ion battery in an off-line manner;
2) determining initial parameters of the open-circuit voltage hysteresis characteristic adaptive model based on the Preisach operator according to the hysteresis characteristic curve training, and establishing the open-circuit voltage hysteresis characteristic adaptive model based on the Preisach operator;
3) and estimating the charge state of the lithium ion battery on line according to the open-circuit voltage hysteresis characteristic self-adaptive model based on the Preisach operator to obtain the charge state of the lithium ion battery at the current moment.
The initial parameters of the open-circuit voltage hysteresis characteristic adaptive model based on the Preisach operator in the step 2) comprise the mesh division number N of the Preisach triangle and the initial value mu of the weight vector.
The open-circuit voltage hysteresis characteristic self-adaptive model based on the Preisach operator in the step 2) is as follows:
wherein,is tkState of charge value, ω (t), corresponding to the open circuit voltage at that momentk) Is tkThe hysteresis state vector, mu (t), corresponding to the open circuit voltage value in the Preisach triangle at the momentk) Is tkThe hysteresis weight vectors of all meshes in the time preiach triangle.
The step 3) specifically comprises the following steps:
31) on-line acquisition of last time tk-1Weight vector mu (t) in the Preisach triangular mesh ofk-1) And the current time tkValue of hysteresis state ω (t)k) Calculating to obtain the prior state of charge value at the current momentComprises the following steps:
32) according to battery capacity Q0Last moment tk-1State of charge value ofAnd the current time tkPrior state of charge value ofCalculating to obtain a current estimation value I at the current momentcal(tk) Comprises the following steps:
Δt＝tk-tk-1；
33) according to the actual current value I of the current moment measured actuallym(tk) And current estimate Ical(tk) Obtain current error value η _ current (t) at the current momentk) Comprises the following steps:
η_current(tk)＝Im(tk)-Ical(tk)；
34) current error value η _ current (t) according to current timek) And prior state of charge value at the current timeAnd obtaining the current time weight vector increment by adopting a minimum mean square error methodAnd calculates a weight value mu (t) of the current timek) Comprises the following steps:
μ(tk)＝μ(tk-1)+λη(tk)ω(tk)
wherein lambda is a step factor, and lambda belongs to [0,1 ];
35) according to the weight vector mu (t) of the current timek) And a hysteresis state value ω (t)k) Obtaining the posterior charge state value of the current moment through the open-circuit voltage hysteresis characteristic self-adaptive modelI.e., the state of charge of the lithium ion battery at the present time, and returns to step 31) to perform the state of charge estimation of the lithium ion battery at the next time.
In the step 34), the weight vector increment at the current momentThe calculation formula of (A) is as follows:
where λ is the step factor and λ ∈ [0,1]]，η(tk) Is tkError values, ω (t), of the calculated and measured currents at timesk) Is tkThe hysteretic state vector in the triangle at time Preisach.
Compared with the prior art, the invention has the following advantages:
firstly, accurate modeling: according to the method, errors of the measured current and the calculated current are introduced, the weight values corresponding to the grids in the Preisach triangle are adjusted in a self-adaptive mode at each moment, and the open-circuit voltage hysteresis characteristics of the lithium ion battery are accurately modeled through iterative calculation of the prior charge state value, the hysteresis state value and the current actual value.
Secondly, improving the precision: according to the invention, the modeling precision is improved through the improvement of the algorithm, the measured current which plays a core role in the algorithm can be directly obtained through the original current sensor in the battery management system, and the hardware cost is not increased while the precision is improved.
Thirdly, accurate estimation: according to the method, the charge state of the lithium ion battery with serious hysteresis characteristics (such as a lithium iron phosphate battery) can be estimated more accurately and reliably by estimating the charge state of the lithium ion battery with hysteresis characteristics.
Drawings
Fig. 1 is a schematic diagram of an OCV-SOC hysteresis characteristic curve of a lithium ion battery.
Fig. 2 is a diagram of the basic preiach operator.
FIG. 3 is a diagram of Preisach triangle and ladder memory curves.
FIG. 4 is a schematic diagram of a discrete Preisach triangle and mesh.
FIG. 5 is a flow chart of lithium ion battery OCV-SOC hysteresis model training.
FIG. 6 is a flow chart of an application of an OCV-SOC adaptive discrete Preisach model of a lithium ion battery.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments.
Example (b):
the invention mainly aims to establish an accurate modeling method for hysteresis characteristics of open-circuit voltage of a lithium ion battery, so that the method can be finally used for accurately estimating the SOC of the lithium ion battery.
In order to achieve the above objects and other advantages of the present invention, as embodied and broadly described herein, there is provided a modeling method for an open-circuit voltage hysteresis characteristic of a lithium ion battery based on current regulation and a discrete preiach operator, where the conventional modeling method for an open-circuit voltage hysteresis characteristic has a disadvantage that a large error and a high precision are difficult to guarantee, and is not suitable for the present invention, the present invention takes a weight value corresponding to a grid triangularly divided by preiach as a time variable on the basis of modeling the hysteresis characteristic by the discrete preiach operator, obtains a current deviation value by obtaining a priori SOC defined at each time and a current value in the battery, obtains an increment of a change in the weight value at each time by combining a least mean square error theory (LMS), obtains a weight value at a current time by summing the weight value at the previous time, and further obtains a hysteresis state at the current time to obtain a posteriori SOC output at the current time, the initial values of the number of grid divisions and the weight vector in the model are determined off-line through an OCV-SOC hysteresis curve of the lithium ion battery.
According to a preferred embodiment of the invention, the complete implementation steps are as follows: 1) obtaining an OCV-SOC hysteresis characteristic curve of the lithium ion battery in an off-line manner in an experiment; 2) determining the number of Preisach triangular mesh divisions and the initial value of the corresponding weight vector in an off-line manner; 3) when the online application is carried out, the weight value corresponding to the Preisach triangular grid is regarded as time-varying, and the current value is obtained by adding the weight value at the previous moment and the variable quantity at the current moment; 4) changing the hysteresis state value of each grid of the Preisach triangle according to the OCV value at the current moment, and obtaining a prior SOC value at the current moment according to the weight value at the previous moment; 5) obtaining a current estimation value at the current moment by the prior SOC value, the SOC value at the last moment and the battery capacity, and comparing the current estimation value with the actual current to obtain an error value; 6) the current error value at the current moment is combined with a least mean square error (LMS) theory to obtain the increment of the weight value at the current moment and the weight value at the current moment; 7) and combining the weighted value of the current moment with the hysteresis state value of the current moment to obtain a posterior SOC value of the current moment, namely the SOC value of the current moment, and repeating the process at the next moment.
Fig. 1 shows an experimental lithium ion battery OCV-SOC hysteresis characteristic curve (OCV is fully static for more than 3 hours) for determining initial parameters of the hysteresis model provided by the present invention, in order to fully cover the hysteresis characteristic of the lithium ion battery, during the experimental measurement, the battery is discharged from a fully charged state, and OCV values are recorded every 5% SOC change and after static placement until SOC is equal to 0 fully discharged state; then entering a charging state, changing every 5% of SOC, standing, recording an OCV value until the SOC is 95%, converting to discharge, and changing to charge until the SOC is 5%; the process is circulated and ensures that each state of charge is reduced by 5% compared with the SOC value of the last state of charge, and each state of discharge is increased by 5% compared with the SOC value of the last state of discharge until the SOC is 50% of the end of the experiment; throughout the process, OCV was recorded after each 5% change in SOC.
As shown in fig. 2-4, the preiach operators (α, β) describe a relationship between input and output, that is, the output is 1 when the input is greater than the threshold α, the output is-1 when the input is less than the threshold β (β < α), and the output is constant when the input is between the thresholds α and β, because the input has a finite amplitude in the hysteresis relationship, as shown in fig. 3, all preiach operators (α, β) form a right triangle in a two-dimensional plane, history information of hysteresis characteristics can be represented by a memory curve in the triangle, and the memory curve is a staircase curve, and the formation rule is: when the input increases with time, the stepped curve reflects as a segment of the triangle that rises horizontally; when the input is reduced along with time, the step-shaped curve is reflected as a line segment which is vertically moved to the left in the triangle, the hysteresis state value of the left lower area of the step-shaped curve in the triangle is 1, the hysteresis state value of the right upper area of the step-shaped curve in the triangle is-1, meanwhile, each point in the triangle corresponds to a weight value, and the output value is obtained by integrating the product of the hysteresis state values of all the points in the triangle and the weight values.
In practical application, the continuous preisac triangle needs to be discretized, that is, the triangle is divided in the horizontal direction and the vertical direction (generally, equal-length division) to finally form a plurality of rectangular grids, a hysteresis state value corresponding to each grid is determined by hysteresis state values of all points included in the grid, the values are located in an interval [ -1, +1], each grid also corresponds to a weight value, the model needs to be trained before application, an OCV-SOC hysteresis relation curve obtained through experiments is used for training to obtain the number of grid divisions and the weight value corresponding to each grid, and a flow chart of a training process is shown in fig. 5.
The initial parameters of the model mainly comprise Preis in the discrete Preisach modelThe side length division number n of the ach triangle and the initial value mu of the hysteresis weight corresponding to each grid in the Preisach triangle under the division, the Preisach triangle is a vertex coordinate on a α - β plane as (u)min,umax) (wherein uminAnd umaxOpen circuit voltage values corresponding to 0 and 100% state of charge, respectively) of an isosceles right triangle having its hypotenuse at α ═ β. the number n of the preiach triangle side length divisions is determined by the final accuracy requirement of the model, and is generally equal to or greater than 20 at the initial value of ni<αi+1I is 1,2, …, n (wherein α)1＝umin，αn+1＝umax) And βi<βi+1I is 1,2, …, n (wherein β)1＝umin，βn+1＝umax). Finally, the total number of N ═ N (N +1)/2 meshes is generated in the whole Preisach triangle. Each grid may be represented as Si(i-1)/2+j＝{(β,α)|βj≤β＜βj+1,αi≤α＜αi+1Where j ≦ i, i ≦ 1,2, …, n, j ≦ 1,2, …, n. Each grid in the discrete Preisach model corresponds to a weight value mu (called hysteresis weight, which needs to be obtained by off-line computation). And (3) taking the OCV value in the hysteresis characteristic experiment curve of the lithium ion battery as a model input u, updating each grid under each input, and generating a corresponding hysteresis state value omega under the input. The determination of the value of ω needs to be based on the staircase curve in the preiach triangle. The staircase curve is determined by an input value u (a horizontal ascending straight line is generated in the Preisach triangle when u is increased, a vertical left-moving straight line is generated in the Preisach triangle when u is decreased, and a staircase curve is generated in the Preisach triangle along with the increasing and decreasing of the input u), the hysteresis state omega corresponding to the grid S below the staircase curve is equal to 1, the hysteresis state omega corresponding to the grid S above the staircase curve is equal to-1, and when the staircase curve passes through the interior of the grid S, the corresponding hysteresis state omega is equal to the area of the part below the staircase curve in the grid minus the area of the part below the staircase curve; defining all the hysteresis states ω as a hysteresis state vector ω (ω ═ ω1,ω2,…,ωN]T) What is, what isSome hysteresis weights μ are a hysteresis weight vector μ (μ ═ μ [ μ ])1,μ2,…,μN]T) The corresponding output SOC at each input is equal to the product of the hysteretic state vector ω and the hysteretic weight vector μ, i.e.Finally, a linear equation system with unknown number as the hysteresis weight vector mu is obtained from input and output values obtained by all experiments, and mu is determined through off-line numerical operation.
As shown in fig. 6, in order to improve the modeling accuracy of the hysteresis curve of the lithium ion battery, the present invention provides a modeling method that takes the weight value corresponding to each grid as a time variable and can be adaptively changed, when the method is specifically applied, the weight value obtained by model training is taken as an initial weight value, each time first updates the hysteresis state values corresponding to all grids in a discrete preiach triangle according to an OCV input value, obtains an SOC value (defined as a prior SOC at the current time) by weighted summation of the hysteresis state values and the weight values obtained at the previous time, and determines a current estimation value at the current time according to the known battery capacity and the SOC value obtained at the previous time, compares the estimation value with the current value detected by the BMS to obtain an error value, compares the error value with the current hysteresis state value and a constant (the constant takes a value between 0 and 1 according to the minimum mean square error theory, a proper value can be selected by multiple values) as the increment of the current time weighted value compared with the previous time weighted value, the obtained current time weighted value and the hysteresis state value at the current time are weighted and summed, the posterior SOC at the current time is obtained and is the corresponding SOC output under the current OCV input, and the process is repeated at the next time.
Claims (4)
1. A state of charge estimation method based on open-circuit voltage hysteresis characteristics is used for estimating the state of charge of a lithium ion battery on line, and is characterized by comprising the following steps:
1) obtaining a hysteresis characteristic curve of the open circuit voltage and the charge state of the lithium ion battery in an off-line manner;
2) determining initial parameters of the open-circuit voltage hysteresis characteristic adaptive model based on the Preisach operator according to the hysteresis characteristic curve training, and establishing the open-circuit voltage hysteresis characteristic adaptive model based on the Preisach operator;
3) the method comprises the following steps of estimating the charge state of the lithium ion battery on line according to the open-circuit voltage hysteresis characteristic self-adaptive model based on the Preisach operator to obtain the charge state of the lithium ion battery at the current moment:
31) on-line acquisition of last time tk-1Weight vector mu (t) in the Preisach triangular mesh ofk-1) And the current time tkValue of hysteresis state ω (t)k) Calculating to obtain the prior state of charge value at the current momentComprises the following steps:
<mrow> <msub> <mi>SOC</mi> <msub> <mi>t</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> </msub> <mrow> <mo>(</mo> <msub> <mi>t</mi> <mi>k</mi> </msub> <mo>)</mo> </mrow> <mo>=</mo> <msup> <mi>&omega;</mi> <mi>T</mi> </msup> <mrow> <mo>(</mo> <msub> <mi>t</mi> <mi>k</mi> </msub> <mo>)</mo> </mrow> <mi>&mu;</mi> <mrow> <mo>(</mo> <msub> <mi>t</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> <mo>)</mo> </mrow> <mo>;</mo> </mrow>
32) according to battery capacity Q0Last moment tk-1State of charge value ofAnd the current time tkPrior state of charge value ofCalculating to obtain a current estimation value I at the current momentcal(tk) Comprises the following steps:
<mrow> <msub> <mi>I</mi> <mrow> <mi>c</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> <mrow> <mo>(</mo> <msub> <mi>t</mi> <mi>k</mi> </msub> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>Q</mi> <mn>0</mn> </msub> <mo>&lsqb;</mo> <msub> <mi>SOC</mi> <msub> <mi>t</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> </msub> <mrow> <mo>(</mo> <msub> <mi>t</mi> <mi>k</mi> </msub> <mo>)</mo> </mrow> <mo>-</mo> <msub> <mi>SOC</mi> <msub> <mi>t</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> </msub> <mrow> <mo>(</mo> <msub> <mi>t</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> <mo>)</mo> </mrow> <mo>&rsqb;</mo> <mo>/</mo> <mi>&Delta;</mi> <mi>t</mi> </mrow>
Δt＝tk-tk-1；
33) according to the actual current value I of the current moment measured actuallym(tk) And current estimate Ical(tk) Obtain current error value η _ current (t) at the current momentk) Comprises the following steps:
η_current(tk)＝Im(tk)-Ical(tk)；
34) current error value η _ current (t) according to current timek) And prior state of charge value at the current timeAnd obtaining the current time weight vector increment by adopting a minimum mean square error methodAnd calculates a weight value mu (t) of the current timek) Comprises the following steps:
μ(tk)＝μ(tk-1)+λη(tk)ω(tk)
<mrow> <mi>&eta;</mi> <mrow> <mo>(</mo> <msub> <mi>t</mi> <mi>k</mi> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mi>&Delta;</mi> <mi>t</mi> </mrow> <mrow> <msub> <mi>Q</mi> <mn>0</mn> </msub> <mi>&eta;</mi> <mo>_</mo> <mi>c</mi> <mi>u</mi> <mi>r</mi> <mi>r</mi> <mi>e</mi> <mi>n</mi> <mi>t</mi> <mrow> <mo>(</mo> <msub> <mi>t</mi> <mi>k</mi> </msub> <mo>)</mo> </mrow> </mrow> </mfrac> </mrow>
wherein lambda is a step factor, and lambda belongs to [0,1 ];
35) according to the weight vector mu (t) of the current timek) And a hysteresis state value ω (t)k) Obtaining the posterior charge state value of the current moment through the open-circuit voltage hysteresis characteristic self-adaptive modelI.e., the state of charge of the lithium ion battery at the present time, and returns to step 31) to perform the state of charge estimation of the lithium ion battery at the next time.
2. The method according to claim 1, wherein the initial parameters of the adaptive model of the open circuit voltage hysteresis characteristic based on the Preisach operator in the step 2) include mesh division number N of the Preisach triangle and initial value μ of the weight vector.
3. The method according to claim 1, wherein the adaptive model of the open circuit voltage hysteresis characteristic based on the preiach operator in step 2) is:
<mrow> <msub> <mi>SOC</mi> <msub> <mi>t</mi> <mi>k</mi> </msub> </msub> <mrow> <mo>(</mo> <msub> <mi>t</mi> <mi>k</mi> </msub> <mo>)</mo> </mrow> <mo>=</mo> <msup> <mi>&omega;</mi> <mi>T</mi> </msup> <mrow> <mo>(</mo> <msub> <mi>t</mi> <mi>k</mi> </msub> <mo>)</mo> </mrow> <mi>&mu;</mi> <mrow> <mo>(</mo> <msub> <mi>t</mi> <mi>k</mi> </msub> <mo>)</mo> </mrow> </mrow>
wherein,is tkState of charge value, ω (t), corresponding to the open circuit voltage at that momentk) Is tkThe hysteresis state vector, mu (t), corresponding to the open circuit voltage value in the Preisach triangle at the momentk) Is tkThe hysteresis weight vectors of all meshes in the time preiach triangle.
4. The method according to claim 1, wherein in step 34), the weight vector at the current time is incrementedThe calculation formula of (A) is as follows:
<mrow> <msub> <mi>&Delta;&mu;</mi> <msub> <mi>t</mi> <mi>k</mi> </msub> </msub> <mo>=</mo> <mi>&lambda;</mi> <mi>&eta;</mi> <mrow> <mo>(</mo> <msub> <mi>t</mi> <mi>k</mi> </msub> <mo>)</mo> </mrow> <mi>&omega;</mi> <mrow> <mo>(</mo> <msub> <mi>t</mi> <mi>k</mi> </msub> <mo>)</mo> </mrow> </mrow>
where λ is the step factor and λ ∈ [0,1]]，η(tk) Is tkError values, ω (t), of the calculated and measured currents at timesk) Is tkThe hysteretic state vector in the triangle at time Preisach.
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| 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 |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102005026597A1 (en) * | 2005-06-09 | 2006-12-21 | Daimlerchrysler Ag | Rechargeable battery charge state determination method for vehicle, entails carrying out mathematical inversion of Preisach model after defining off-load voltage of battery, and from this calculating actual charge state of battery |
| 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 |
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| US11899071B2 (en) | 2019-06-24 | 2024-02-13 | Contemporary Amperex Technology Co., Limited | Method and apparatus for determining state of charge of battery, management system and storage medium |
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