CN106291375A - A kind of SOC estimation method based on cell degradation and device - Google Patents

Abstract

The present invention relates to a kind of SOC estimation method based on cell degradation and device, the present invention is by expressing SOC, it is contemplated that cell degradation degree and the cycle-index impact on SOC, so that estimation result is more accurate.And with Kalman filtering algorithm, mensuration being iterated of the ampere-hour meter after improving is eliminated cumulative errors.

Description

A kind of SOC estimation method based on cell degradation and device

Technical field

The present invention relates to a kind of SOC estimation method based on cell degradation, may be used for wind-solar-storage joint generating user side The SOC estimation of lithium battery.

Background technology

In order to more accurately and scientifically characterize the residual capacity of accumulator, generally characterize accumulator with state-of-charge Residual capacity, i.e. SOC (State Of Charge), it is the important parameter of the residual capacity state characterizing battery, and SOC can not Directly obtain from battery itself, and can only by measure set of cells external characteristics parameter (such as: voltage, electric current, internal resistance, temperature, Degree of aging etc.) indirectly obtain, accurately the SOC of estimation accumulator is an important and challenging task.

At wind-solar-storage joint generating user side, owing to the generated output of wind-force and photovoltaic generation needs to rely on local wind-force Determine with illumination, cause scene cogeneration not possess seriality and the crest of generated output and trough is the most obvious.Cause This, typically require installation energy storage device at wind-solar-storage joint generating user side and carry out peak load shifting, when generated output is bigger, and scene Storing cogeneration equipment charges in energy storage device, and when generated output is less, energy storage device discharges, and carries to user or electrical network For electric energy.At wind-solar-storage joint generating user side, energy storage device needs to carry out discharge and recharge frequently, so obtaining real-time and accurately The SOC of set of cells is the important prerequisite of design wind-solar-storage joint generating battery management system.

Existing SOC estimation method includes that ampere-hour meter is mensuration.

The mensuration Current integrating method that is also called of ampere-hour meter, the mensuration advantage of ampere-hour meter be it using battery as an entirety, Do not consider internal structure and the impact of the internal factor such as battery temperature, aging, self discharge of battery, and only consider outside system The impact in portion.It by obtaining the electricity Q released from the t0 moment to t1 moment to the integration of electric current, and then when estimating any Carve the residual capacity of battery.

The mensuration computing formula of ampere-hour meter is formula (1),

The computing formula of ampere-hour meter mensuration measuring and calculating SOC is:

$SOC={\mathrm{SOC}}_0-\frac{1}{Q_n}\underset{0}{\overset{t}{\∫}}\mathrm{\η}idt---\left(1\right)$

In above formula, SOC₀For initial SOC, Q_nFor battery active volume, η is coulombic efficiency, and i is electricity in battery current formula Stream symbol is just when electric discharge, is negative during charging.

The discrete form of formula (1) is:

${\mathrm{SOC}}_{t+1}={\mathrm{SOC}}_t-\frac{1}{Q_n}\underset{t}{\overset{t+1}{\∫}}\mathrm{\η}idt---\left(3\right)$

In above formula, SOC_tFor the SOC value of t, Q_nFor battery active volume, η is coulombic efficiency, and i is battery current formula Middle current symbol is just when electric discharge, is negative during charging.This formula can be used for t for calculating benchmark, the estimation t+1 moment SOC value.

Although the mensuration calculating of ampere-hour meter is simple, it is adaptable to various batteries, but initial value and discharging efficiency is bad determines, electricity Flow measurement will definitely not cause cumulative error.

Publication No. is that the patent documentation of CN103744027A discloses a kind of self-correcting battery SOC based on Kalman filtering Evaluation method, coordinates battery operated model, uses Kalman filtering method constantly it to be iterated correction, during corrected Calculation The error produced, can estimate SOC value accurately.

Publication No. is the patent documentation " SOC estimation method of a kind of battery " of CN10412250A, at the base of Kalman filtering On plinth, SOC equation is optimized, introduces the stable and charge-discharge magnification factor impact on SOC value, improve SOC estimation Degree of accuracy.

The task of the present invention is to improve SOC estimation precision further.

Summary of the invention

It is an object of the invention to provide a kind of SOC estimation method based on cell degradation, in order to solve the SOC of prior art The problem that estimation precision is not high enough.Meanwhile, present invention also offers a kind of battery SOC estimation device.

For achieving the above object, the solution of the present invention includes:

A kind of SOC estimation method based on cell degradation, step is as follows:

Step 1), set up the state-of-charge SOC equation of battery

${\mathrm{SOC}}_{t+1}={\mathrm{\αSOC}}_t-\frac{1}{Q_n}\underset{t}{\overset{t+1}{\∫}}\mathrm{\η}idt$

SOC_tFor the SOC value of t, SOC_t+1For the SOC value in t+1 moment, η is coulombic efficiency, and i is battery current formula Middle current symbol is just when electric discharge, is negative during charging；α is cell degradation coefficient；

Step 2), set up battery model；

Step 3), according to the battery model set up, estimate battery SOC by Kalman filtering algorithm.

Further, cell degradation factor alpha with the relation of battery charging and discharging number of times is:

$\mathrm{\&alpha;}=\left\{\begin{array}{cc}1& N\&le;500\\ 0.98& 500<N\&le;1000\\ 0.95& N>1000\end{array}\right.---\left(12\right)$

Wherein, N is battery charging and discharging number of times.

Further, described step 1) in, the state-of-charge SOC equation of battery is

${\mathrm{SOC}}_{t+1}={\mathrm{\&alpha;SOC}}_t-\frac{1}{Q^{\&prime;}}\underset{t}{\overset{t+1}{\&Integral;}}\mathrm{\&eta;}idt---\left(2\right)$

Q' is the battery active volume of the capacity compensation under different discharge-rates.

Further, shown in Peukert empirical equation such as formula (4):

IⁿT=K (4)

Wherein, I is the discharge current of battery；T is the discharge time of battery；N be the constant relevant with battery variety (n > 1)；K is the constant relevant with active substance；

According to formula (11):

$n=-\frac{lg{t}_2-lg{t}_1}{lg{I}_2-lg{I}_1}---\left(11\right)$

N is brought into Peukert empirical equation and can calculate the value of K；After oneself knows the value of n Yu K, can be according to formula (6):

The discharge electricity amount Q=I of battery under constant-current discharge state^1-nK (6)

Draw the capacity compensation Q' under different discharge-rates.

Further, the state equation of the state-space model of battery is as follows:

$\left[\begin{array}{c}{\mathrm{SOC}}_{k+1}\\ u_{k+1}\end{array}\right]=\left[\begin{array}{cc}1& 0\\ 0& \exp \left(\frac{-T}{R_{1}C}\right)\end{array}\right]\left[\begin{array}{c}{\mathrm{SOC}}_k\\ u_k\end{array}\right]+\left[\begin{array}{c}\frac{-T}{Q^{\&prime;}}\\ R_1(1-\exp (\frac{-T}{R_{1}C}))\end{array}\right]I_k+\left[\begin{array}{c}{w}_1\left(k\right)\\ w_2\left(k\right)\end{array}\right]---\left(33\right)$

Coefficient A, B, C, D, as follows:

$A=\left[\begin{array}{cc}1& 0\\ 0& \exp \left(\frac{-T}{R_{1}C}\right)\end{array}\right]---\left(34\right)$

$B=\left[\begin{array}{c}\frac{-T}{Q^{\&prime;}}\\ R_1(1-\exp (\frac{-T}{R_{1}C}\left)\right)\end{array}\right]---\left(35\right)$

$C=\left[\begin{array}{cc}\frac{\&part;F\left({\mathrm{SOC}}_k\right)}{\&part;{\mathrm{SOC}}_k}& -1\end{array}\right]---\left(36\right)$

D=-R₀ (37)

Wherein T, R1, C are battery equivalent circuit model parameter.

Present invention also offers a kind of SOC based on cell degradation and estimate device, including:

Module 1) for setting up the module of the state-of-charge SOC equation of battery；

The state-of-charge SOC equation of battery:

SOC_tFor the SOC value of t, SOC_t+1For the SOC value in t+1 moment, η is coulombic efficiency, and i is battery current formula Middle current symbol is just when electric discharge, is negative during charging；α is cell degradation coefficient；

Module 2) for setting up the module of battery model；

Module 3) for according to the battery model set up, by the module of Kalman filtering algorithm estimation battery SOC.

Further, cell degradation factor alpha with the relation of battery charging and discharging number of times is:

$\mathrm{\&alpha;}=\left\{\begin{array}{cc}1& N\&le;500\\ 0.98& 500<N\&le;1000\\ 0.95& N>1000\end{array}\right.---\left(12\right)$

Wherein, N is battery charging and discharging number of times.

Further, described module 1) in, the state-of-charge SOC equation of battery is

${\mathrm{SOC}}_{t+1}={\mathrm{\&alpha;SOC}}_t-\frac{1}{Q^{\&prime;}}\underset{t}{\overset{t+1}{\&Integral;}}\mathrm{\&eta;}idt---\left(2\right)$

Q' is the battery active volume of the capacity compensation under different discharge-rates.

Further, shown in Peukert empirical equation such as formula (4):

IⁿT=K (4)

Wherein, I is the discharge current of battery；T is the discharge time of battery；N be the constant relevant with battery variety (n > 1)；K is the constant relevant with active substance；

According to formula (11):

$n=-\frac{lg{t}_2-lg{t}_1}{lg{I}_2-lg{I}_1}---\left(11\right)$

N is brought into Peukert empirical equation and can calculate the value of K；After oneself knows the value of n Yu K, can be according to formula (6):

The discharge electricity amount Q=I of battery under constant-current discharge state^1-nK (6)

Draw the capacity compensation Q' under different discharge-rates.

Further, the state equation of the state-space model of battery is as follows:

$\left[\begin{array}{c}{\mathrm{SOC}}_{k+1}\\ u_{k+1}\end{array}\right]=\left[\begin{array}{cc}1& 0\\ 0& \exp \left(\frac{-T}{R_{1}C}\right)\end{array}\right]\left[\begin{array}{c}{\mathrm{SOC}}_k\\ u_k\end{array}\right]+\left[\begin{array}{c}\frac{-T}{Q^{\&prime;}}\\ R_1(1-\exp (\frac{-T}{R_{1}C}))\end{array}\right]I_k+\left[\begin{array}{c}{w}_1\left(k\right)\\ w_2\left(k\right)\end{array}\right]---\left(33\right)$

Coefficient A, B, C, D, as follows:

$A=\left[\begin{array}{cc}1& 0\\ 0& \exp \left(\frac{-T}{R_{1}C}\right)\end{array}\right]---\left(34\right)$

$B=\left[\begin{array}{c}\frac{-T}{Q^{\&prime;}}\\ R_1(1-\exp (\frac{-T}{R_{1}C}\left)\right)\end{array}\right]---\left(35\right)$

$C=\left[\begin{array}{cc}\frac{\&part;F\left({\mathrm{SOC}}_k\right)}{\&part;{\mathrm{SOC}}_k}& -1\end{array}\right]---\left(36\right)$

D=-R₀ (37)

Wherein T, R1, C are battery equivalent circuit model parameter.

The present invention passes throughExpress SOC, it is considered to cell degradation degree and cycle-index pair The impact of SOC.And with Kalman filtering algorithm, mensuration being iterated of the ampere-hour meter after improving is eliminated cumulative errors.

Further, useAlso contemplate the discharge-rate factor of the battery shadow to SOC Ring, so that estimation result is more accurate.

Above formula (2) is identical with hereafter formula (13).

Accompanying drawing explanation

Fig. 1 battery equivalent circuit model figure；

The flow chart of Fig. 2 embodiment of the present invention 1；

The Kalman Algorithm flow process of Fig. 3 embodiment of the present invention 1.

Detailed description of the invention

The present invention will be further described in detail below in conjunction with the accompanying drawings.

The present invention selects the error using Kalman filtering method generation mensuration to ampere-hour meter to be corrected, and is using Kalman Before filter method, need to set up suitable state-space model.Wherein, SOC is one of quantity of state of state-space model, so such as The result that fruit is wanted to make Kalman filtering method estimate more accurately, then needs to enter the state expression formula of ampere-hour meter SOC in mensuration Row improves.

Based on wind-solar-storage joint generating user side peak load shifting lithium ion battery energy storage system need summation function, frequency One of function of numerous use is that lithium battery carries out discharge and recharge operation, and different charge-discharge magnifications can be selected to complete battery Charge/discharge operation, therefore charge-discharge magnification factor the impact of SOC is intended to consider.Additionally, whole lithium battery energy storage battery system In lithium battery can not often change, and lithium battery can engender that after repeatedly circulating internal resistance increase and battery hold The phenomenon that amount declines, therefore the degree of aging of battery is also the condition needing emphasis to consider.

Provide below three kinds of embodiments to be introduced:

Embodiment 1

The improved method mensuration to ampere-hour meter is as follows:

1) the discharge-rate factor of the consideration battery impact on SOC；

2) cell degradation degree and the cycle-index impact on SOC are considered.

1) the discharge-rate factor impact on SOC

Battery is when discharging with different discharge-rates, and the electricity released under identical initial condition is different.Typically For, in the case of constant current electric discharge, although heavy-current discharge can make battery reach cutting of battery in the short period of time But the electricity that only voltage battery is released is the least.

As far back as 1898, Peukert just proposed famous Peukert empirical equation, disclose discharge capacity of the cell with Relation between discharge current.Shown in Peukert empirical equation such as formula (4):

IⁿT=K (4)

Wherein, I is the discharge current of battery；T is the discharge time of battery；N be the constant relevant with battery variety (n > 1)；K is the constant relevant with active substance.

I is multiplied by equation both sides simultaneously^1-n, following formula:

It=I^1-nK (5)

The equation equal sign left side is the discharge electricity amount of battery under discharge current and the product of time i.e. constant-current discharge state Q, therefore formula can be expressed as shown in following formula:

Q=I^1-nK (6)

By formula it can be seen that K, n are constants, and n is the constant more than 1.If discharge current I is the biggest, then battery Discharge electricity amount Q will be the least；Otherwise, then can be the biggest.In order to determine constant n and K, it is possible to use I₁, and I₂Two kinds of different putting Electricity multiplying power is tested, and records t discharge time under both discharge-rates respectively₁And t₂.In substitution formula (4), Go out:

$I_1^n{t}_1=K---\left(7\right)$

$I_2^n{t}_2=K---\left(8\right)$

Are taken the logarithm in above formula two ends respectively, to obtain final product:

nlgI₁+lgt₁=lgK (9)

nlgI₂+lgt₂=lgK (10)

By both the above formula simultaneous, can draw:

$n=-\frac{lg{t}_2-lg{t}_1}{lg{I}_2-lg{I}_1}---\left(11\right)$

N is brought into Peukert empirical equation and can calculate the value of K.After oneself knows the value of n Yu K, can be according to formula (6) the capacity compensation Q' under different discharge-rates is drawn.

2) self-discharge of battery and the aging impact on battery SOC

After battery over multiple cycles uses, inside battery material structure can be gradually old and feeble, along with battery charging and discharging circulation time The increase of number, battery capacity declines can be obvious all the more, and the internal resistance of cell also can be gradually increased.Aging battery SOC is estimated if ignored The impact calculated, can cause the estimated value of battery SOC to be gradually increased with the gap of actual value.Through substantial amounts of experiment, lithium can be drawn The cell degradation coefficient of battery and the relation of battery charging and discharging cycle-index be:

$\mathrm{\&alpha;}=\left\{\begin{array}{cc}1& N\&le;500\\ 0.98& 500<N\&le;1000\\ 0.95& N>1000\end{array}\right.---\left(12\right)$

Wherein, α is cell degradation coefficient, and N is battery charging and discharging number of times.Calculated by and improvement the most mensuration for ampere-hour meter The analysis of method, the present invention show that the formula of the ampere-hour meter of improvement mensuration estimation SOC is as follows；

${\mathrm{SOC}}_{t+1}={\mathrm{\&alpha;SOC}}_t-\frac{1}{Q^{\&prime;}}\underset{t}{\overset{t+1}{\&Integral;}}\mathrm{\&eta;}idt---\left(13\right)$

Capacity compensation Q', α under different discharge-rates are cell degradation coefficient.

Formula (13) is the committed step of the inventive method, on this basis, also includes step 2 and step 3:

Step 2 introduces Kalman filtering algorithm

The core concept of Kalman filtering method is the optimal estimation that the state to dynamical system makes in minimum variance meaning, Linear processes system is the most applicable.

For discrete system, the system state space model of Kalman is as follows:

X_k+1=A_kX_k+B_kU_k+W_k (14)

Y_k=C_kX_k+D_kU_k+V_k (15)

Wherein, U_kFor the defeated people vector of system, the controlled quentity controlled variable of etching system when being k；From the output for system, it it it is the k moment Measured value Y_k, be the quantity of state of system, wherein comprise SOC, A of accumulator_k、B_k、C_k、D_kThe parameter determination obtained by experiment, W_k It is process noise variable, V_kFor observation noise variable.W_kAnd V_kMeet:

E[W_k]=0 (16)

E[V_k]=0 (17)

$E\&lsqb;W_m{W}_n\&rsqb;=\left\{\begin{array}{cc}Q& m=n\\ 0& m\&NotEqual;n\end{array}\right.---\left(18\right)$

$E\&lsqb;V_m{V}_n\&rsqb;=\left\{\begin{array}{cc}R& m=n\\ 0& m\&NotEqual;n\end{array}\right.---\left(19\right)$

Battery model is nonlinear model, and therefore the present invention uses extended BHF approach method to nonlinear battery Model is estimated.Extended BHF approach method and standard Kalman filter maximum difference and are the state space of system The difference of model: use f (X_k, U_k) instead of the A in standard Kalman filtering_kX_k+B_kU_k, use g (X_k, U_k) instead of C_kX_k+ D_kU_k.Both algorithms are substantially similar.

For nonlinear system, its system state space model is as follows:

X_k+1=f (X_k,U_k)+W_k (20)

Y_k=g (X_k,U_k)+V_k (21)

Wherein, f (X_k, U_k) it is state transition function, g (X_k, U_k) it is measurement functions.Around estimated value X again₀.Use Taylor's level Number launches f (X_k, U_k) and g (X_k, U_k), remove secondary and above item thereof, can be by nonlinear function linearisation, i.e. formula (22) With formula (23).

$f(X_k,U_k)\&ap;f({\hat{X}}_k,U_k)+\frac{\&part;f(X_k,U_k)}{\&part;X_k}{|}_{X_k={\hat{X}}_k}(X_k-{\hat{X}}_k)---\left(22\right)$

$g(X_k,U_k)\&ap;g({\hat{X}}_k,U_k)+\frac{\&part;g(X_k,U_k)}{\&part;X_k}{|}_{X_k={\hat{X}}_k}(X_k-{\hat{X}}_k)---\left(23\right)$

By formula (20), (21), (22), (23), the state equation after linearisation can be obtained as follows:

$X_{k+1}\&ap;A_k{X}_k+f({\hat{X}}_k,U_k)-A_k{X}_k+W_k---\left(24\right)$

$Y_k\&ap;C_k{X}_k+g({\hat{X}}_k,U_k)-C_k{X}_k+V_k---\left(25\right)$

Discounting for W_k、V_k, then definition:

$A_k=\frac{\&part;f(X_k,U_k)}{\&part;X_k}{|}_{X_k={\hat{X}}_k}---\left(26\right)$

$C_k=\frac{\&part;g(X_k,U_k)}{\&part;X_k}{|}_{X_k={\hat{X}}_k}---\left(27\right)$

EKF method estimation flow process is as follows:

(1) first initialize, as k=0, obtainP₀:

${\hat{X}}_0=E\&lsqb;{\hat{X}}_0\&rsqb;---\left(28\right)$

$P_0=E\&lsqb;(X_0-{\hat{X}}_0){(X_0-{\hat{X}}_0)}^T\&rsqb;---\left(29\right)$

(2) when k=1,2 ..., spreading kalman algorithm is as shown in Figure 3.

By flow diagram, in Kalman filtering algorithm, interative computation each time is required for being predicted and revising, So that state optimization value is closer to actual value, reach the purpose of error correction.

Step 3 sets up battery equivalent circuit model

Equivalent circuit describes electrokinetic cell Voltammetric Relation in the course of the work, and battery equivalent circuit model determines The degree of accuracy that Kalman filtering method can reach, the battery model of foundation should be the simplest, so can simplify calculating Complexity.The present invention sets up battery equivalent circuit model as it is shown in figure 1, wherein T, and R1, C are battery equivalent circuit model parameter.

According to Kirchhoff's second law and Kirchhoff's current law (KCL), formula can be obtained as follows:

E (t)=V (t)+R₀I(t)+u(t) (30)

$I\left(t\right)=\frac{u\left(t\right)}{R_1}+C\frac{du}{dt}---\left(31\right)$

Wherein, E (t) is the electromotive force of battery, and V (t) is the terminal voltage of battery, and I (t) is the charging and discharging currents of battery.? Under same temperature, cell emf E Yu SOC has certain functional relationship.Relational expression is as follows:

E (t)=F (SOC (t)) (32)

And the mensuration computing formula of the ampere-hour meter that improves is formula (13), the state-space model of battery is established below, will After formula (13), (30), (31), (32) simultaneous discretization, the state equation of the state-space model i.e. obtaining battery is as follows:

$\left[\begin{array}{c}SO{C}_{k+1}\\ u_{k+1}\end{array}\right]=\left[\begin{array}{cc}1& 0\\ 0& \exp \left(\frac{-T}{R_{1}C}\right)\end{array}\right]\left[\begin{array}{c}SO{C}_k\\ u_k\end{array}\right]+\left[\begin{array}{c}\frac{-T}{Q^{\&prime;}}\\ R_1(1-\exp (\frac{-T}{R_{1}C}\left)\right)\end{array}\right]I_k+\left[\begin{array}{c}{w}_1\left(k\right)\\ w_2\left(k\right)\end{array}\right]---\left(33\right)$

Because state equation is linear, and F (SOC in measurement equation_k) it is nonlinear, so measurement equation is carried out line Propertyization processes.I.e. can get coefficient A, B, C, D, as follows:

$A=\left[\begin{array}{cc}1& 0\\ 0& \exp \left(\frac{-T}{R_{1}C}\right)\end{array}\right]---\left(34\right)$

$B=\left[\begin{array}{c}\frac{-T}{Q^{\&prime;}}\\ R_1(1-\exp (\frac{-T}{R_{1}C}\left)\right)\end{array}\right]---\left(35\right)$

$C=\left[\begin{array}{cc}\frac{\&part;F\left({\mathrm{SOC}}_k\right)}{\&part;{\mathrm{SOC}}_k}& -1\end{array}\right]---\left(36\right)$

D=-R₀ (37)

Matrix A, B, C, D are substituted in the algorithm of EKF and calculate, constantly carry out " prediction-correction " this Step, makes the estimated value of lithium battery SOC gradually approach actual value.

Invention herein uses ampere-hour meter mensuration (i.e. formula (13)) the estimation battery SOC after improving, and then uses expansion card It is constantly corrected by Kalman Filtering method, revises mensuration being continuously increased over time of ampere-hour meter, and cumulative error can gradually increase Big defect.The algorithm flow chart of embodiment 1 is as shown in Figure 2.

The method of the present invention is except applying in wind-solar-storage joint generating user side lithium battery SOC estimation, it is also possible to use Other kinds of accumulator SOC in other occasions is estimated.

Embodiment 2

Difference with embodiment 1 is, the present embodiment only considers cell degradation degree and the cycle-index impact on SOC. After battery over multiple cycles uses, inside battery material structure can be gradually old and feeble, along with the increase of battery charging and discharging cycle-index, Battery capacity declines can be obvious all the more, and the internal resistance of cell also can be gradually increased.If ignoring the aging impact on battery SOC estimation, The estimated value of battery SOC can be caused to be gradually increased with the gap of actual value.Through substantial amounts of experiment, the battery of lithium battery can be drawn The relation of aging coefficient and battery charging and discharging cycle-index is:

$\mathrm{\&alpha;}=\left\{\begin{array}{cc}1& N\&le;500\\ 0.98& 500<N\&le;1000\\ 0.95& N>1000\end{array}\right.$

Wherein, α is cell degradation coefficient, and N is battery charging and discharging number of times.For different batteries, the value of α phase the most not to the utmost With, it should determine through experiment.

The formula of estimation SOC is as follows:

${\mathrm{SOC}}_{t+1}={\mathrm{\&alpha;SOC}}_t-\frac{1}{Q_n}\underset{t}{\overset{t+1}{\&Integral;}}\mathrm{\&eta;}idt$

Similar to Example 1, then introduce Kalman filtering algorithm, set up battery equivalent circuit model, resolve battery The state equation of state-space model, constantly " prediction correction ", make the estimated value of lithium battery SOC gradually approach truly Value.

Embodiment 3

Different from embodiment 1 it is, only considers the impact on SOC of the discharge-rate factor of battery, obtain SOC estimation equation For

Wherein parameter definition is identical with embodiment 1, follow-up Kalman filtering, builds Vertical circuit model, resolving process the most essentially identical, therefore repeat no more.

Present invention also offers the embodiment of a kind of battery SOC estimation device, including such as lower module:

Module 1), for setting up the state-of-charge SOC equation of battery

Or

SOC_tFor the SOC value of t, SOC_t+1For the SOC value in t+1 moment, η is coulombic efficiency, and i is battery current formula Middle current symbol is just when electric discharge, is negative during charging；Q' is that the battery of the capacity compensation under different discharge-rates can be used Capacity, α is cell degradation coefficient；

Module 2), it is used for setting up battery model；

Module 3), for according to the battery model set up, estimating battery SOC by Kalman filtering algorithm.

The device of indication in said apparatus embodiment, is actually based on a kind of computer solution party of the inventive method flow process Case, i.e. a kind of software component, above-mentioned module is the treatment progress corresponding with method flow.This software can run on battery Management and control equipment in.Due to complete to the introduction sufficiently clear of said method, and the device that the present embodiment is claimed A kind of software sharing, therefore be described the most in detail.

It is presented above the detailed description of the invention that the present invention relates to, but the present invention is not limited to described embodiment. Under the thinking that the present invention provides, use the mode being readily apparent that to those skilled in the art to the skill in above-described embodiment Art means carry out converting, replace, revise, and the effect played is essentially identical with the relevant art means in the present invention, realize Goal of the invention the most essentially identical, so formed technical scheme above-described embodiment is finely adjusted formation, this technology Scheme still falls within protection scope of the present invention.

Claims (10)

1. a SOC estimation method based on cell degradation, it is characterised in that step is as follows:

Step 1), set up the state-of-charge SOC equation of battery

${\mathrm{SOC}}_{t+1}={\mathrm{\&alpha;SOC}}_t-\frac{1}{Q_n}\underset{t}{\overset{t+1}{\&Integral;}}\mathrm{\&eta;}idt$

SOC_tFor the SOC value of t, SOC_t+1For the SOC value in t+1 moment, η is coulombic efficiency, and i is electric current in battery current formula Symbol is just when electric discharge, is negative during charging；α is cell degradation coefficient；

Step 2), set up battery model；

Step 3), according to the battery model set up, estimate battery SOC by Kalman filtering algorithm.

A kind of SOC estimation method based on cell degradation the most according to claim 1, it is characterised in that cell degradation system Number α with the relation of battery charging and discharging number of times is:

$\mathrm{\&alpha;}=\left\{\begin{array}{cc}1& N\&le;500\\ 0.98& 500<N\&le;1000\\ 0.95& N>1000\end{array}\right.---\left(12\right)$

Wherein, N is battery charging and discharging number of times.

A kind of SOC estimation method based on cell degradation the most according to claim 1 and 2, it is characterised in that described step 1), in, the state-of-charge SOC equation of battery is

${\mathrm{SOC}}_{t+1}={\mathrm{\&alpha;SOC}}_t-\frac{1}{Q^{\&prime;}}\underset{t}{\overset{t+1}{\&Integral;}}\mathrm{\&eta;}idt---\left(2\right)$

Q' is the battery active volume of the capacity compensation under different discharge-rates.

A kind of SOC estimation method based on cell degradation the most according to claim 3, it is characterised in that Peukert experience Shown in formula such as formula (4):

IⁿT=K (4)

Wherein, I is the discharge current of battery；T is the discharge time of battery；N is the constant (n > 1) relevant with battery variety；K is The constant relevant with active substance；

According to formula (11):

$n=-\frac{\lg t_2-\lg t_1}{\lg I_2-\lg I_1}---\left(11\right)$

N is brought into Peukert empirical equation and can calculate the value of K；After oneself knows the value of n Yu K, can be according to formula (6):

The discharge electricity amount Q=I of battery under constant-current discharge state^1-nK (6)

Draw the capacity compensation Q' under different discharge-rates.

A kind of SOC estimation method based on cell degradation the most according to claim 4, it is characterised in that

The state equation of the state-space model of battery is as follows:

$\left[\begin{array}{c}SO{C}_{k+1}\\ u_{k+1}\end{array}\right]=\left[\begin{array}{cc}1& 0\\ 0& \exp \left(\frac{-T}{R_{1}C}\right)\end{array}\right]\left[\begin{array}{c}SO{C}_k\\ u_k\end{array}\right]+\left[\begin{array}{c}\frac{-T}{Q^{\&prime;}}\\ R_1(1-\exp (\frac{-T}{R_{1}C}\left)\right)\end{array}\right]I_k+\left[\begin{array}{c}{w}_1\left(k\right)\\ w_2\left(k\right)\end{array}\right]---\left(33\right)$

Coefficient A, B, C, D, as follows:

$A=\left[\begin{array}{cc}1& 0\\ 0& \exp \left(\frac{-T}{R_{1}C}\right)\end{array}\right]---\left(34\right)$

$B=\left[\begin{array}{c}\frac{-T}{Q^{\&prime;}}\\ R_1(1-\exp (\frac{-T}{R_{1}C}\left)\right)\end{array}\right]---\left(35\right)$

$C=\&lsqb;\begin{array}{cc}\frac{\&part;F\left({\mathrm{SOC}}_k\right)}{\&part;{\mathrm{SOC}}_k}& -1\end{array}\&rsqb;---\left(36\right)$

D=-R₀ (37)

Wherein T, R1, C are battery equivalent circuit model parameter.

6. a SOC based on cell degradation estimates device, it is characterised in that including:

Module 1) for setting up the module of the state-of-charge SOC equation of battery；

The state-of-charge SOC equation of battery:

SOC_tFor the SOC value of t, SOC_t+1For the SOC value in t+1 moment, η is coulombic efficiency, and i is electric current in battery current formula Symbol is just when electric discharge, is negative during charging；α is cell degradation coefficient；

Module 2) for setting up the module of battery model；

Module 3) for according to the battery model set up, by the module of Kalman filtering algorithm estimation battery SOC.

A kind of SOC based on cell degradation the most according to claim 6 estimates device, it is characterised in that cell degradation system Number α with the relation of battery charging and discharging number of times is:

$\mathrm{\&alpha;}=\left\{\begin{array}{cc}1& N\&le;500\\ 0.98& 500<N\&le;1000\\ 0.95& N>1000\end{array}\right.---\left(12\right)$

Wherein, N is battery charging and discharging number of times.

8. estimate device according to a kind of based on cell degradation the SOC described in claim 6 or 7, it is characterised in that described module 1), in, the state-of-charge SOC equation of battery is

${\mathrm{SOC}}_{t+1}={\mathrm{\&alpha;SOC}}_t-\frac{1}{Q^{\&prime;}}\underset{t}{\overset{t+1}{\&Integral;}}\mathrm{\&eta;}idt---\left(2\right)$

Q' is the battery active volume of the capacity compensation under different discharge-rates.

A kind of SOC based on cell degradation the most according to claim 8 estimates device, it is characterised in that Peukert experience Shown in formula such as formula (4):

IⁿT=K (4)

Wherein, I is the discharge current of battery；T is the discharge time of battery；N is the constant (n > 1) relevant with battery variety；K is The constant relevant with active substance；

According to formula (11):

$n=-\frac{\lg t_2-\lg t_1}{\lg I_2-\lg I_1}---\left(11\right)$

N is brought into Peukert empirical equation and can calculate the value of K；After oneself knows the value of n Yu K, can be according to formula (6):

The discharge electricity amount Q=I of battery under constant-current discharge state^1-nK (6)

Draw the capacity compensation Q' under different discharge-rates.

A kind of SOC based on cell degradation the most according to claim 9 estimates device, it is characterised in that

The state equation of the state-space model of battery is as follows:

$\left[\begin{array}{c}SO{C}_{k+1}\\ u_{k+1}\end{array}\right]=\left[\begin{array}{cc}1& 0\\ 0& \exp \left(\frac{-T}{R_{1}C}\right)\end{array}\right]\left[\begin{array}{c}SO{C}_k\\ u_k\end{array}\right]+\left[\begin{array}{c}\frac{-T}{Q^{\&prime;}}\\ R_1(1-\exp (\frac{-T}{R_{1}C}\left)\right)\end{array}\right]I_k+\left[\begin{array}{c}{w}_1\left(k\right)\\ w_2\left(k\right)\end{array}\right]---\left(33\right)$

Coefficient A, B, C, D, as follows:

$A=\left[\begin{array}{cc}1& 0\\ 0& \exp \left(\frac{-T}{R_{1}C}\right)\end{array}\right]---\left(34\right)$

$B=\left[\begin{array}{c}\frac{-T}{Q^{\&prime;}}\\ R_1(1-\exp (\frac{-T}{R_{1}C}\left)\right)\end{array}\right]---\left(35\right)$

$C=\&lsqb;\begin{array}{cc}\frac{\&part;F\left({\mathrm{SOC}}_k\right)}{\&part;{\mathrm{SOC}}_k}& -1\end{array}\&rsqb;---\left(36\right)$

D=-R₀ (37)

Wherein T, R1, C are battery equivalent circuit model parameter.