CN106842060A - A kind of electrokinetic cell SOC estimation method and system based on dynamic parameter - Google Patents

A kind of electrokinetic cell SOC estimation method and system based on dynamic parameter Download PDF

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Publication number
CN106842060A
CN106842060A CN201710136569.4A CN201710136569A CN106842060A CN 106842060 A CN106842060 A CN 106842060A CN 201710136569 A CN201710136569 A CN 201710136569A CN 106842060 A CN106842060 A CN 106842060A
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battery
soc
equivalent
carried out
circuit model
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张瑞锋
王海帆
吴晋
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Shenzhen Haiyun Map New Energy Co Ltd
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Shenzhen Haiyun Map New Energy Co Ltd
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Priority to PCT/CN2017/092130 priority patent/WO2018161486A1/en
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/389—Measuring internal impedance, internal conductance or related variables
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables

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Abstract

The invention discloses a kind of electrokinetic cell SOC estimation method and system based on dynamic parameter, the method is comprised the following steps：Electric discharge is carried out to battery and stands experiment, obtain battery OCV SOC characteristic curves at different temperatures, fit the relational expression of OCV SOC；The voltage responsive during the pulsed discharge standing experiment of constant current, record is carried out to battery, according to gained voltage response curves, the initial parameter value of battery Order RC equivalent-circuit model is picked out by offline method；Using the least square method of recursion RRFLS containing forgetting factor, Identifying Dynamical Parameters are carried out to Order RC equivalent-circuit model；Estimation on line is carried out to battery SOC using EKF algorithms.The evaluation method overcomes that SOC initial values in current integration method are inaccurate and phenomenons of cumulative errors, adapt to the dynamic change of battery behavior, battery model high precision, fast convergence rate, it is reliable and stable, the precision of SOC estimation on line is improve, electric automobile and energy storage battery management system field is can be widely applied to.

Description

A kind of electrokinetic cell SOC estimation method and system based on dynamic parameter
Technical field
It is more particularly to a kind of dynamic based on dynamic parameter the present invention relates to electric automobile and energy storage battery management system field Power battery SOC evaluation method and system.
Background technology
At present, mainly include on power battery charged state (State of Charge, SOC) method of estimation both at home and abroad： Internal resistance method, current integration method, open circuit voltage method, Kalman filtering method, observer method, particle filter method and neural network.Its In, internal resistance method calculates battery according to the functional relation between the internal resistance of cell and SOC by detecting internal resistance of cell detection internal resistance SOC, however online, accurately measure the internal resistance of cell exist because of difficulty, limit application of the method in Practical Project.Ampere-hour is accumulated Although point-score principle is simple, be easily achieved, SOC initial errors cannot be eliminated and caused because current measurement is inaccurate Cumulative errors.Open circuit voltage method calculates battery SOC, it is necessary to battery is filled according to the corresponding relation of open-circuit voltage (OCV) and SOC Dividing after standing could measure OCV, therefore not be suitable for the On-line Estimation of SOC.Kalman filtering method and observer method, can be very The initial error of battery SOC is corrected well, and with good anti-noise ability, but their requirements to model accuracy are very It is high.Particle filter method, convergence time is long., it is necessary to substantial amounts of training sample, our neural network can not in actual applications The sample data of all actual conditions can be obtained covering, therefore its precision will also be influenceed by certain, and also the method is calculated Amount is difficult to realize within hardware greatly.Electrokinetic cell is a complicated nonlinear dynamic system, and battery model parameter is substantially subject to The influence of the factors such as temperature, self-discharge of battery, aging.
In actual applications, all there is certain inconvenience and defect to some extent in existing battery SOC method of estimation, therefore It is necessary further to be improved.
The content of the invention
It is an object of the present invention to solve the problems, such as existing battery SOC estimation precision and speed.
To achieve the above object, in a first aspect, the invention provides a kind of electrokinetic cell SOC estimations based on dynamic parameter Method and system, the method is comprised the following steps：Carry out electric discharge-stand experiment to battery, obtain battery at different temperatures OCV-SOC characteristic curves, fit the relational expression of OCV-SOC；Pulsed discharge-standing that constant current is carried out to battery is real Test, the voltage responsive during record, according to gained voltage response curves, battery Order RC is picked out by offline method equivalent The initial parameter value of circuit model；Using the least square method of recursion RRFLS containing forgetting factor, to Order RC equivalent-circuit model Carry out Identifying Dynamical Parameters；Estimation on line is carried out to battery SOC using EKF algorithms.
Preferably, battery Order RC equivalent-circuit model is main by first resistor (R0), second resistance (R1), 3rd resistor (R2), the first electric capacity (C1) and the second electric capacity (C2) constitute.
Preferably, the value of forgetting factor is 0.95~0.98.
Second aspect, the invention provides a kind of electrokinetic cell SOC estimating systems based on dynamic parameter, the system bag Include：First computing module, for carrying out electric discharge-standing experiment to battery, obtains battery OCV-SOC characteristics at different temperatures Curve, fits the relational expression of OCV-SOC；Second computing module, for battery is carried out the pulsed discharge of constant current- The voltage responsive during experiment, record is stood, battery second order is picked out by offline method according to gained voltage response curves The initial parameter value of RC equivalent-circuit models；3rd computing module, for using the least square method of recursion containing forgetting factor RRFLS, Identifying Dynamical Parameters are carried out to Order RC equivalent-circuit model；4th computing module, for using EKF algorithms to battery SOC carries out estimation on line.
Instant invention overcomes the SOC initial values in current integration method are inaccurate and phenomenons of cumulative errors, battery behavior is adapted to Dynamic change, battery model high precision, fast convergence rate is reliable and stable, improves the precision of SOC estimation on line, can be extensive It is applied to electric automobile and energy storage battery management system field.
Brief description of the drawings
Fig. 1 is that a kind of electrokinetic cell SOC estimation method flow based on dynamic parameter provided in an embodiment of the present invention is illustrated Figure；
Fig. 2 is battery Order RC equivalent-circuit model structural representation.
Specific embodiment
To make the purpose, technical scheme and advantage of the embodiment of the present invention clearer, below in conjunction with the embodiment of the present invention In accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is A part of embodiment of the present invention, rather than whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art The every other embodiment obtained under the premise of creative work is not made, belongs to the scope of protection of the invention.
For ease of the understanding to the embodiment of the present invention, it is further explained with specific embodiment below in conjunction with accompanying drawing Bright, embodiment does not constitute the restriction to the embodiment of the present invention.
Fig. 1 is that a kind of electrokinetic cell SOC estimation method flow based on dynamic parameter provided in an embodiment of the present invention is illustrated Figure.As shown in figure 1, the method is comprised the following steps：
Step one, experiment that battery development is discharged-stood, acquisition battery OCV-SOC characteristic curves at different temperatures, Fit the relational expression of OCV-SOC.
Voltage responsive during step 2, pulsed discharge-standing experiment that constant current is carried out to battery, record, according to Gained voltage response curves, the initial parameter value of battery Order RC equivalent-circuit model is picked out by offline method.
In a preferred scheme, battery Order RC equivalent-circuit model is as shown in Fig. 2 the battery Order RC equivalent electric Road model is main by first resistor R0, second resistance R1, 3rd resistor R2, the first electric capacity C1And the second electric capacity C2Constitute；Wherein, UocRepresent the open-circuit voltage (OCV) of battery；U1It is the terminal voltage of battery pack；R0It is the ohmic internal resistance of battery；R1、R2It is respectively electric Activation polarization and concentration difference polarization resistance in the charge and discharge process of pond；C1、C2Transient state electricity respectively in battery charge and discharge process Hold effect, activation polarization and concentration difference polarization capacity；U1、U2Respectively pass through electric capacity C1、C2Magnitude of voltage；U is battery-end electricity Pressure；I is battery-end electric current.
Step 3, using the least square method of recursion RRFLS containing forgetting factor, Order RC equivalent-circuit model is joined Number identification.Preferably, the value of forgetting factor is 0.95~0.98.
Specifically, converted by Kirchhoff's law and granny rag Lars, obtain the shape under Order RC equivalent-circuit model frequency domain State equation is：
Make timeconstantτ1=R1C1, τ2=R2C2；
Then above formula can abbreviation be：
τ1τ2Uocs2+(τ1+τ2)Uccs+Ucc=τ1τ2IR0s2+Is|R1τ2+R2τ1+R0(τ1+τ2)|+I(R1+R2+R0)+τ1τ2Us2+(τ1+τ2)Us+U
If a=τ1τ2, b=τ1+τ2, c=R1+R2+R0, d=R1τ2+R2τ1+R0(τ1+τ2)
Then above formula can be reduced to：
aUocs2+bUocs+Uoc=aR0Is2+dIs+cI+aUs2+bUs+U；
Above formula is carried out into sliding-model control, wherein T is the sampling time, and arrangement can be obtained：
Uoc(k)-U=k1|U(k-1)-Uoc(k-1)|+k2|U(k-2)-Uoc(k-2)|+k3I(k)+k4I(k-1)+k5I(k- 2)
Wherein,
In formula, you can in substituting into the discrimination method of recursive least-squares, the θ at current time=| k1k2k3k4k5|TValue, then According to below equation：
R0=k5/k2
R1=(τ1c+τ2Ri-d)/(τ1-τ2)
R2=(c-R1-Ri
C1=τ1/R1
C2=τ2/R2
Calculate Order RC equivalent circuit model parameter R0、R1、R2、C1、C2, so that the Dynamic Identification of implementation model parameter.
Step 4, estimation on line is carried out to battery SOC using EKF algorithms, EKF algorithm full name ExtendedKalman Filter, i.e. extended Kalman filter, a kind of efficient recursion filter (autoregressive filter).
Specifically, according to selected Order RC equivalent-circuit model, the state equation and measurement equation of battery are obtained such as Under：
Discrete model after state equation discretization:
It is x=[x to make the state variable in battery model1 x2 x3]=[Uoc U1 U2]T, system input u is lithium-ion electric The operating current I in pond, and electric discharge is for just, system output y is the operating voltage U of lithium ion battery, and the sampling time is T.
Lithium ion battery separate manufacturing firms model is：
Wherein
Dk=-R0(K)
Algorithmic system parameter state amount is initialized
x0=[SOC (0) 0 0]T
Operation expanded Kalman filtration algorithm
Prediction module：
(1) status predication：
(2) status predication error co-variance matrix：
Correction module：
(1) kalman gain：
Wherein,
(2) state estimation：
(3) state estimation misses covariance matrix：
Pk=(I-GkCk)Pk|k-1
Wherein, PkIt is covariance；GkIt is kalman gain；Qk-1It is process noise error；Rk-1It is observation noise error.
Step 5, by SOC estimated values, according to the OCV-SOC characteristic curves that step one is obtained, obtain the open circuit at k moment Magnitude of voltage Uoc, using RRFLS algorithms must ask the θ at k moment=| k1k2k3k4k5|TValue, then calculate k moment model parameter values R0、R1、R2、C1、C2；
Step 6：Parameter value Ak, Bk, Ck, Dk of state equation in real-time update EFK algorithms, then rerun expansion card Kalman Filtering algorithm, obtains the SOC estimation at k+1 moment, is then back to step 4.
Renewal model parameter is calculated by step 6 and step 5 estimates the two circulation steps of SOC, will passed through each time The SOC and moment model parameter value R for obtaining0、R1、R2、C1、C2Substitute into separate manufacturing firms equation and obtain new predicted value, pass through Constantly the recursion mode of prediction and amendment is calculated, and just can obtain the real-time parameter value of lithium battery model and current with recursion SOC estimated values, make final SOC and model parameter value R0、R1、R2、C1、C2Filter result constantly levels off to the actual feelings of battery Condition.
Correspondingly, a kind of electrokinetic cell SOC estimating systems based on dynamic parameter, the system be the embodiment of the invention provides Including：
First computing module, for carrying out electric discharge-standing experiment to battery, obtains battery OCV- at different temperatures SOC characteristic curves, fit the relational expression of OCV-SOC；
Voltage during second computing module, the pulsed discharge-standing experiment for carrying out constant current to battery, record Response, according to gained voltage response curves, at the beginning of picking out the parameter of battery Order RC equivalent-circuit model by offline method Initial value；
3rd computing module, for using the least square method of recursion RRFLS containing forgetting factor, to Order RC equivalent circuit Model carries out Identifying Dynamical Parameters；
4th computing module, for carrying out estimation on line to battery SOC using EKF algorithms.
The embodiment of the present invention overcomes that SOC initial values in current integration method are inaccurate and phenomenons of cumulative errors, adapts to electricity The dynamic change of pond characteristic, battery model high precision, fast convergence rate is reliable and stable, improves the precision of SOC estimation on line, Can be widely applied to electric automobile and energy storage battery management system field.
The present invention is described in detail above, and the present invention is expanded on further in conjunction with specific embodiments, must It is noted that the explanation of above example is not used in limitation and is only intended to help and understands core concept of the invention, for this skill For the those of ordinary skill in art field, under the premise without departing from the principles of the invention, any improvement carried out to the present invention with And the alternative solution being equal to this product, fall within the protection domain of the claims in the present invention.

Claims (4)

1. a kind of electrokinetic cell SOC estimation method based on dynamic parameter, it is characterised in that comprise the following steps：
Carry out electric discharge-standing experiment to battery, obtain battery OCV-SOC characteristic curves at different temperatures, fit OCV- The relational expression of SOC；
The voltage responsive during the pulsed discharge-standing experiment of constant current, record is carried out to battery, according to gained voltage responsive Curve, the initial parameter value of battery Order RC equivalent-circuit model is picked out by offline method；
Using the least square method of recursion RRFLS containing forgetting factor, Identifying Dynamical Parameters are carried out to Order RC equivalent-circuit model；
Estimation on line is carried out to battery SOC using EKF algorithms.
2. method according to claim 1, it is characterised in that the battery Order RC equivalent-circuit model is main by first Resistance (R0), second resistance (R1), 3rd resistor (R2), the first electric capacity (C1) and the second electric capacity (C2) constitute.
3. the method according to profit requires 1, it is characterised in that the value of the forgetting factor is 0.95~0.98.
4. a kind of electrokinetic cell SOC estimating systems based on dynamic parameter, it is characterised in that including：
First computing module, for carrying out electric discharge-standing experiment to battery, obtains battery OCV-SOC at different temperatures special Linearity curve, fits the relational expression of OCV-SOC；
Voltage during second computing module, the pulsed discharge-standing experiment for carrying out constant current to battery, record rings Should, according to gained voltage response curves, the parameter for picking out battery Order RC equivalent-circuit model by offline method is initial Value；
3rd computing module, for using the least square method of recursion RRFLS containing forgetting factor, to Order RC equivalent-circuit model Carry out Identifying Dynamical Parameters；
4th computing module, estimation on line is carried out using using EKF algorithms to battery SOC.
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