CN105954679B - A kind of On-line Estimation method of lithium battery charge state - Google Patents
A kind of On-line Estimation method of lithium battery charge state Download PDFInfo
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- 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]
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- G01R31/387—Determining ampere-hour charge capacity or SoC
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Abstract
The invention discloses a kind of On-line Estimation methods of lithium battery charge state (SOC).The present invention is based on Extended Kalman filter methods, combine TS fuzzy theory to lithium battery real-time parameter open-circuit voltage UOCIt is accurately estimated, and then realizes the accurate estimation to lithium battery SOC.The present invention includes: the foundation that lithium battery improves double RC equivalent-circuit models, with online TS fuzzy model to battery open circuit voltage UOCAccurately calculate, utilize expanded Kalman filtration algorithm real-time estimation lithium battery SOC.Estimation based on the present invention to lithium battery SOC, not only meets pre-provisioning request in the estimated accuracy of lithium battery SOC, but also while the application of TS fuzzy model is so that lithium battery SOC estimated accuracy improves, also ensures the rapidity and real-time of On-line Estimation.
Description
Technical field
The invention belongs to battery energy storage technical fields, in particular to the estimation of lithium battery charge state (SOC) a kind of
Method.
Background technique
In recent decades, the research and development of electricity storage technology is constantly subjected to various countries' energy, traffic, electric power, communication etc.
The attention of department.Under the overall background of new energy technology fast development, if can be in the new energy such as fuel cell power generation, wind power generation
It equipped with energy storage device in the generating equipment of source, on the one hand can be adjusted, be solved by power curve of the energy-storage travelling wave tube to unit
Certainly generation of electricity by new energy itself power output randomness, uncontrollable problem reduce impact of the new energy power output variation to power grid；Another party
Face can store electric energy when electric power is abundant, discharge electric energy in load peak, reach peak load shifting, reduce system reserve demand
Effect.The significant advantage of wherein battery energy storage technology, especially lithium ion battery due to having both high-energy-density and high-specific-power,
There is good application prospect in extensive energy storage field.
Battery management system (Battery Management System, BMS) is adopted by the full spectrum information to battery
Collection, accurate volume calculation, science balanced management and quick response Preservation tactics, realize battery group after intelligence
Management, to ensure that battery energy storage system is safely and reliably run.High-precision battery charge state (State of Charge,
SOC) one of key technology of the estimating techniques as BMS is to provide battery system at any time by on-line real time monitoring battery capacity
Residual capacity in the reasonable scope by the control of the working range of battery SOC prevent battery from super-charge super-discharge phenomenon occur, guarantee
It is used safely, while being also beneficial to extend the service life of battery.So SOC estimation is the main task and technology hardly possible of BMS
Point.There are many factor for influencing SOC, such as environment temperature, efficiency for charge-discharge, cycle life, self discharge, they are coupled to each other, because
This is not easy to according to these parameters accurately to estimate SOC.Traditional battery SOC evaluation method disadvantage is more apparent, the scope of application
Also limited.At present in practical applications, using it is more be method that open circuit voltage method is combined with current integration method.It needs to infuse
Meaning, there are biggish accumulated errors for current integration method, it is necessary to periodically it is modified, and open circuit voltage method is only long in battery
Time stands stable rear and can get accurate as a result, i.e. offline correct, this is relatively difficult to achieve in practical applications.Therefore, it is necessary to
Seek a kind of SOC real-time online estimation method with on-line amending ability.
Summary of the invention
In view of the deficiencies of the prior art, the present invention proposes the On-line Estimation methods of lithium battery SOC a kind of.The present invention is based on expansions
Kalman filter method is opened up, in conjunction with TS fuzzy theory to lithium battery parameter open-circuit voltage UOCIt is accurately estimated, and then realization pair
The online real-time estimation of lithium battery SOC.It mainly includes the foundation that lithium battery improves double RC equivalent-circuit models, fuzzy with TS
Identification of the model to battery open circuit voltage utilizes the online real-time estimation lithium battery SOC of expanded Kalman filtration algorithm.Based on this hair
The bright On-line Estimation to lithium battery SOC not only meets pre-provisioning request in the estimated accuracy of lithium battery SOC, but also TS obscures mould
While the application of type is so that lithium battery SOC estimated accuracy improves, also guarantee the rapidity and real-time of On-line Estimation.
To achieve the above object, the invention proposes the On-line Estimation methods of lithium battery SOC a kind of, which is characterized in that institute
State method the following steps are included:
(1) initial value of any given lithium battery SOC finds out the pre- of battery open circuit voltage using compound empirical equation model
Valuation
(2) willLithium battery electric current Ibat, input of the work temperature as TS fuzzy model, utilize TS fuzzy model
Calculate lithium battery open-circuit voltage output valve UOC, realize open-circuit voltage discreet valueCarry out real-time optimization；
(3) by UOCIt substitutes into lithium battery to improve in double RC models, and model parameter is recognized using HPPC method of testing；
(4) Extended Kalman filter estimator is utilized, the real value SOC of lithium battery SOC is calculated onlinenew。
As it is further preferred that compound empirical equation model described in the step (1) is based on to Shepherd mould
Type, Unnewehr Universal model and Nernst model carry out synthesis improvement acquisition, and form is as follows:
Wherein,For present battery open-circuit voltage discreet value, z is last moment SOC value of battery, K0、K1、K2、K3、K4For
There is no the coefficient of physical significance.By the least square method of recursion with forgetting factor to above-mentioned COEFFICIENT K0~K4It is recognized.Band is lost
Forget the parameter identification formula of the least square method of recursion of the factor are as follows:
Wherein,For parameter vector to be estimated For data vectorK (k) is gain matrix, and P (k) is covariance matrix, and λ is forgetting factor, is taken
Close to 1 positive number, usually not less than 0.9.Steps are as follows for parameter identification:
(1.1) determination of primary data.Rule of thumb the priori knowledge of identification of Model Parameters gives vector to be estimatedIt assigns just
Value；The initial value P (0)=10 of identification is set6×I5×5(I is unit matrix), forgetting factor λ=0.998；
(1.2) current inputoutput data is sampledIt determines
(1.3) it is calculated using above-mentioned parameter identification formulaK (k) and P (k)；
(1.4) if k < N (N is number of samples), k → k+1, return step (1.2) continue cycling through；Otherwise algorithm terminates,
Output
As it is further preferred that calculating lithium battery open-circuit voltage output valve using TS fuzzy model in the step (2)
UOCSpecifically include following sub-steps:
(2.1) charge and discharge emulation experiment is carried out to lithium battery model, records and saves history inputoutput data；
(2.2) C clustering processing is carried out to history inputoutput data, calculates subordinating degree function uiAnd consequent parameter Θ
(k)；
(2.3) TS fuzzy rule is set up.Wherein, i-th TS fuzzy rule is expressed as:
Wherein, c is fuzzy rule number, and n is the input variable number of the TS fuzzy model, x1(k),x2
(k),···,xnIt (k) is kth moment and the regression variable of pervious inputoutput data,To represent Ge Mo
The fuzzy set with linear subordinating degree function of subspace is pasted, can be used to carry out the fuzzy reasoning of the i-th rule,For the consequent parameter of i-th fuzzy rule, yiIt (k+1) is the TS fuzzy model (k+ under the i-th rule
1) output valve at moment.
(2.4) β is definediFor the fitness of i-th fuzzy rule, then have:
Then, calculation formula of the TS fuzzy model in the output y (k+1) at (k+1) moment are as follows:
Define consequent parameter Θ (k) and former piece parameter Φ (k) are as follows:
Wherein, r=c (n+1), available:
Y (k+1)=Φ (k)T·Θ(k)
(2.5) definition output y (k+1)=UOC(k).Wherein, UOCIt (k) is k moment battery open circuit voltage.Enable k=k+1 simultaneously
Return step (2.2), until lithium battery SOC On-line Estimation process terminates.
As it is further preferred that lithium battery described in the step (3) improves double RC models, equivalent internal resistance is used
Thermistor indicates.In conjunction with kirchhoff Current Voltage law, the state equation and output equation that can obtain lithium battery are respectively as follows:
Wherein, WkFor systematic procedure noise, VkFor systematic survey noise.TsFor systematic sampling time, τbFor capacitor CbAnd electricity
Hinder RbThe RC ring time constant of composition, τpFor capacitor CpWith resistance RpThe RC ring time constant of composition, Ub、UpRespectively two RC rings
The voltage at both ends, η are battery coulombic efficiency, and SOC indicates model state amount battery SOC, CnFor battery capacity.UbatModel output
Hold voltage, IbatFor system power, electric current is positive value when electric discharge, and when charging is negative.RTFor equivalent thermosensitive resistance, identification side
Method is as follows:
Define thermistor RT=f (T)=aT2+b·T+c.Wherein, a, b, c are to fitting coefficient.By lithium battery not
Charge and discharge test is carried out under same electric current, different temperatures, and obtains cluster relation curve.With the method for curve matching can find out a,
B, the value of c.
The discrimination method of other model parameters is as follows: using HPPC (Hybrid Pulse Power at normal temperature
Characterization, mixed pulses power characteristic) operating condition to lithium battery carry out external drive, obtain input/output relation song
Line.Model parameter R can be found out also with the method for curve matchingb、Cb、Rp、CpValue.
As it is further preferred that improving double RC model output end voltage U for described in the step (4)bat, model shape
State amount battery SOC, system power Ibat, end voltage measuring value UtmAs the input quantity of the Extended Kalman filter estimator, and
It carries out obtaining the real value SOC of lithium battery SOC in line computationnew。
In general, through the invention it is contemplated above technical scheme is compared with the prior art, mainly have below
Technological merit:
1. the present invention is based on Extended Kalman filter method, in conjunction with TS fuzzy theory to lithium battery parameter open-circuit voltage UOC
It is accurately estimated, and then realizes the online real-time estimation to lithium battery SOC；
2. simultaneously, improving in double RC models using thermistor as equivalent internal resistance, and essence is carried out to it using experimental data
Really identification, effectively simulates influence of the temperature factor to lithium battery end voltage, and then improves the accurate of lithium battery SOC estimation
Property；
3. the lithium battery SOC estimation method proposed through the invention, so that lithium battery SOC estimation is repaired online with good
Positive ability not only increases lithium battery SOC On-line Estimation precision, also ensures its rapidity and real-time.
Detailed description of the invention
Fig. 1 is lithium battery SOC On-line Estimation method flow diagram；
Fig. 2 is lithium battery SOC On-line Estimation method structure chart；
Fig. 3 is that lithium battery improves double RC model equivalent circuit diagrams.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.As long as in addition, technical characteristic involved in the various embodiments of the present invention described below
Not constituting a conflict with each other can be combined with each other.
It is as shown in Figure 1 lithium battery SOC On-line Estimation method flow diagram, specifically includes:
(1) initial value of any given lithium battery SOC finds out the pre- of battery open circuit voltage using compound empirical equation model
Valuation
(2) willLithium battery electric current Ibat, input of the work temperature as TS fuzzy model, utilize TS fuzzy model
Calculate lithium battery open-circuit voltage output valve UOC, realize open-circuit voltage discreet valueCarry out real-time optimization；
(3) by UOCIt substitutes into lithium battery to improve in double RC models, and model parameter is recognized using HPPC method of testing；
(4) Extended Kalman filter estimator is utilized, the real value SOC of lithium battery SOC is calculated onlinenew。
It is illustrated in figure 2 lithium battery SOC On-line Estimation method structure chart.
Acquisition system electric current Ibat, environment temperature T and estimated by the open-circuit voltage that the compound empirical equation model obtains
ValueAnd the input as the TS fuzzy model, operation TS fuzzy model obtain open-circuit voltage optimal value UOC.By UOCInput
It is improved in double RC models to the lithium battery.Lithium battery according to Fig.3, improves double RC model equivalent circuit diagrams, in conjunction with Kiel
The state equation and output equation of model can be obtained in Hough Current Voltage law, as follows respectively:
Wherein, WkFor systematic procedure noise, VkFor systematic survey noise.TsFor systematic sampling time, τbFor capacitor CbAnd electricity
Hinder RbThe RC ring time constant of composition, τpFor capacitor CpWith resistance RpThe RC ring time constant of composition, Ub、UpRespectively two RC rings
The voltage at both ends, η are battery coulombic efficiency, and SOC indicates model state amount battery SOC, CnFor battery capacity.UbatModel output
Hold voltage, IbatFor system power, electric current is positive value when electric discharge, and when charging is negative.
Double RC model output end voltage U are improved by describedbat, model state amount battery SOC, system power Ibat, end voltage
Measured value UtmIt as the input quantity of the Extended Kalman filter estimator, and is calculated online, obtains the reality of lithium battery SOC
Duration SOCnew。
Lithium battery SOC On-line Estimation method provided by the invention estimated accuracy with higher, while in turn ensuring very fast
Estimating speed.And due to the use of TS fuzzy model, mould can be adjusted according to the variation of system power and environment temperature
The output of shape parameter, the calculating output and practical lithium battery system that make model maintains good consistency.
As it will be easily appreciated by one skilled in the art that the foregoing is merely illustrative of the preferred embodiments of the present invention, not to
The limitation present invention, any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should all include
Within protection scope of the present invention.
Claims (6)
1. a kind of On-line Estimation method of lithium battery charge state, which is characterized in that the described method comprises the following steps:
(1) initial value of any given lithium battery charge state finds out battery open circuit voltage using compound empirical equation model
Discreet value
(2) willLithium battery electric current Ibat, input of the work temperature as TS fuzzy model, utilize TS fuzzy model calculate lithium
Battery open circuit voltage output valve UOC, realize open-circuit voltage discreet valueCarry out real-time optimization；
(3) by UOCIt substitutes into lithium battery to improve in double RC models, and model parameter is recognized using HPPC method of testing；
(4) Extended Kalman filter estimator is utilized, the real value SOC of lithium battery charge state is calculated onlinenew；
The compound empirical equation model is based on to Shepherd model, Unnewehr Universal model and Nernst
Model carries out synthesis improvement acquisition, and form is as follows:
Wherein,For present battery open-circuit voltage discreet value, z is last moment battery charge state value, K0、K1、K2、K3、K4For
There is no the coefficient of physical significance；By the least square method of recursion with forgetting factor to above-mentioned COEFFICIENT K0~K4It is recognized.
2. the On-line Estimation method of lithium battery charge state according to claim 1, which is characterized in that the band forget because
The parameter identification formula of the least square method of recursion of son are as follows:
Wherein,For parameter vector to be estimated For data vectorK (k) is gain matrix, and P (k) is covariance matrix, and λ is forgetting factor, is taken
Close to 1 positive number, I is unit matrix, zkFor the SOC value of battery at k moment, y (k) is output of the TS fuzzy model at the k moment.
3. the On-line Estimation method of lithium battery charge state according to claim 2, which is characterized in that parameter identification step
It is as follows:
(1.1) determination of primary data；Rule of thumb the priori knowledge of identification of Model Parameters gives vector to be estimatedAssign initial value；If
Set the initial value P (0)=10 of identification6×I5×5, wherein I is unit matrix, forgetting factor λ=0.998；
(1.2) current inputoutput data is sampledzk, determine
(1.3) priori knowledge is calculated to vector to be estimated using above-mentioned parameter identification formulaGain matrix K (k) and
Covariance matrix P (k)；
(1.4) if k < N, N are number of samples, then k=k+1, return step (1.2) continue cycling through；Otherwise terminate, export
4. method according to claim 1 or 2, which is characterized in that calculate lithium using TS fuzzy model in the step (2)
Battery open circuit voltage output valve UOCSpecifically include following sub-steps:
(2.1) charge and discharge emulation experiment is carried out to lithium battery model, records and saves history inputoutput data；
(2.2) C clustering processing is carried out to history inputoutput data, calculates subordinating degree function uiAnd consequent parameter Θ (k)；
(2.3) TS fuzzy rule is set up；Wherein, i-th TS fuzzy rule is expressed as:
Wherein, c is fuzzy rule number, and n is the input variable number of the TS fuzzy model, x1(k),x2(k),…,xn(k)
For kth moment and the regression variable of pervious inputoutput data,For represent each Fuzzy subspaee have line
Property subordinating degree function fuzzy set, can be used to carry out the fuzzy reasoning of the i-th rule,For i-th fuzzy rule
Consequent parameter then, yiIt (k+1) is the output valve at TS fuzzy model (k+1) moment under the i-th rule；
(2.4) β is definediFor the fitness of i-th fuzzy rule, then have:
Calculation formula of the TS fuzzy model in the output y (k+1) at (k+1) moment are as follows:
Define consequent parameter Θ (k) and former piece parameter Φ (k) are as follows:
Wherein, r=c (n+1), available:
Y (k+1)=Φ (k)TΘ(k)
(2.5) definition output y (k+1)=UOC(k)；Wherein, UOCIt (k) is k moment battery open circuit voltage；It enables k=k+1 and returns to step
Suddenly (2.2), until lithium battery charge state On-line Estimation process terminates.
5. method according to claim 1 or 2, which is characterized in that the lithium battery improves its equivalent internal resistance of double RC models
It is indicated using thermistor；In conjunction with kirchhoff Current Voltage law, the state equation and output equation difference of lithium battery can be obtained
Are as follows:
Wherein, WkFor systematic procedure noise, VkFor systematic survey noise；TsFor systematic sampling time, τbFor capacitor CbWith resistance Rb
The RC ring time constant of composition, τpFor capacitor CpWith resistance RpThe RC ring time constant of composition, Ub、UpRespectively two RC ring both ends
Voltage, η be battery coulombic efficiency, state-of-charge be model state amount battery charge state, CnFor battery capacity；UbatFor mould
Type output terminal voltage, IbatFor lithium battery electric current, electric current is positive value when electric discharge, and when charging is negative；RTFor equivalent thermosensitive resistance,
Its discrimination method is as follows:
Define RT=f (T)=aT2+bT+c；Wherein, a, b, c are to fitting coefficient；By lithium battery in different electric currents, different temperatures
Lower carry out charge and discharge test, and obtain cluster relation curve；The value of a, b, c are found out with Matlab iunction for curve polyfit.
6. method according to claim 1 or 2, which is characterized in that in the step (4) that the double RC models of the improvement are defeated
Outlet voltage Ubat, model state amount battery charge state, lithium battery electric current Ibat, end voltage measuring value UtmAs the expansion card
The input quantity of Kalman Filtering estimator, and carry out the real value SOC that lithium battery charge state is calculated onlinenew。
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| CN112595979B (en) * | 2020-12-02 | 2021-10-08 | 华中科技大学 | Lithium battery parameter online identification method and system considering insufficient excitation |
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| CN114881316B (en) * | 2022-04-24 | 2023-06-16 | 上海玫克生储能科技有限公司 | Lithium battery remaining life prediction method, system, terminal equipment and storage medium |
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