CN109358293A - Lithium ion battery SOC estimation method based on IPF - Google Patents
Lithium ion battery SOC estimation method based on IPF Download PDFInfo
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Abstract
The lithium ion battery SOC estimation method based on IPF that the invention discloses a kind of, comprising the following steps: the mathematical model for establishing lithium-ion battery systems obtains the state equation and observational equation of system, and sliding-model control；Constant-current pulse discharge test is carried out to lithium ion battery, obtains the residual current SOC of lithium ion battery open-circuit voltage and lithium ion battery；The relation curve of the residual current SOC of lithium ion battery open-circuit voltage and lithium ion battery is fitted on MATLAB, and recognizes and obtains battery model parameter, to establish the equivalent model of lithium ion battery；Lithium ion battery SOC is estimated using improved particle filter.The present invention obtains charge states of lithium ion battery by the mathematical model of lithium-ion battery systems and the estimation of improved particle filter, has the characteristics that estimate that accuracy height and estimation are quick, to guarantee the service life of lithium ion battery.
Description
Technical field
The present invention relates to a kind of lithium ion battery SOC estimation method, in particular to a kind of lithium ion battery based on IPF
SOC estimation method.
Background technique
In recent years, due to factors such as energy crisis, environmental pollution and energy securities, electric car industry is welcome
It flourishes.Currently, the industrialization process of electric car faces following key problem: 1, the effective energy storage density of battery is low and short
It is difficult to effectively improve in time；2, battery price is expensive, and production maintenance is at high cost；3, battery charge time is long.And to solve with
Upper problem can only start at present from the research and development of battery management system.Important set of the battery management system (BMS) as electric car
At part, voltage, temperature, electric current, SOC of battery etc. can be monitored in real time, control effectively and manage to car lithium battery,
To effectively improve battery pack service life, the course continuation mileage of electric car is improved.And SOC estimation is as in battery management system
Reflect the most important data of battery service condition, estimation it is accurate whether directly affect the workability of battery management system
Can, therefore a kind of accurately and rapidly SOC estimation method has very big impetus for the development of electric car industry.
Summary of the invention
The lithium ion battery SOC estimation method based on IPF that the object of the present invention is to provide a kind of.The present invention, which has, to be estimated
It calculates accuracy height and estimates quick feature.
A kind of technical solution of the present invention: lithium ion battery SOC estimation method based on IPF, comprising the following steps:
S1, the mathematical model for establishing lithium-ion battery systems obtain the state equation and observational equation of system, and discretization
Processing；
S2, constant-current pulse discharge test is carried out to lithium ion battery, obtains lithium ion battery open-circuit voltage and lithium-ion electric
The residual current SOC in pond；
S3, on MATLAB to the relation curve of the residual current SOC of lithium ion battery open-circuit voltage and lithium ion battery
It is fitted, and recognizes and obtain Li-ion battery model parameter, to establish the equivalent model of lithium ion battery；
S4, lithium ion battery SOC is estimated using improved particle filter.
In the above-mentioned lithium ion battery SOC estimation method based on IPF, the state equation is
The observational equation is
UL(k)=UOC (k)-i (k) × R0 (k)-U1 (k)+v (k)
In formula: SOC (k+1) is the charge states of lithium ion battery at system k+1 moment, U1It (k+1) is the system k+1 moment
Polarizing voltage value, Δ t indicate the sampling time, and R1 indicates polarization resistance, and R0 is ohmic internal resistance, and τ 1 indicates the polarization time, and η expression is filled
Discharging efficiency, QN indicate battery actual capacity, and i (k) indicates the discharge current at system k moment, when w (k) and v (k) indicate system k
Quarter state and measurement noise.
In lithium ion battery SOC estimation method above-mentioned based on IPF, the step of the described constant-current pulse discharge test such as
Under:
1. at room temperature, load of the connection with constant-current discharge function on lithium ion battery；
2. the pairs of maximum charging current values using lithium ion battery carries out constant-current charge to lithium ion battery, until lithium-ion electric
The voltage difference of pond two-stage reaches blanking voltage；
3. continuing to charge to lithium ion battery using lithium ion battery maximum charging voltage constant pressure, until charging current
Less than 0.033C, think that lithium ion battery has been filled with electricity at this time；
4. with the electric current of 0.3C to lithium ion battery carry out continuous discharge, discharge time 10min, if in discharge process lithium from
Sub- cell voltage is lower than minimum voltage, then stops discharging, and terminates test, otherwise continues to discharge；
5. disconnecting circuit after the 10min that discharges stands 1h to lithium ion battery, repeatedly step is 4. later；
6. test terminates；
7. Data Processing in Experiment；
The last 1s discharge voltage of step 4. is denoted as lithium-ion electric tank discharge operating voltage Udn(n=1,2,3 ...), passes through
Following formula calculates the charge that battery is released:
Wherein Idn(t) the real-time current size monitored in discharge process, t are indicateddnIndicate discharge time
According to formula:
The residual current SOC of lithium ion battery is calculated, wherein Q0Indicate the total charge dosage of lithium ion battery.
In lithium ion battery SOC estimation method above-mentioned based on IPF, the improved particle filter estimates lithium ion
Battery SOC, method and step are as follows:
(1): initialization: k=0
It is distributed from prior stateExtract one group of particleOne group of parameter is defined simultaneously:Wherein j=1,2 ..., L, L are the dimension of state x；
γ is scale factor
For k=1,2 ...
(2) important sampling process
For i=1,2 ..., N
I. state is carried out to each particle with UKF and updates generation transformation sampling point:
Time updates:
Measurement updaue:
In formula
II. it is sampled from IDF
For i=1,2 ..., N
It estimates the weight of each particle and is normalized:
It can thus be appreciated thatIt is sampled to obtain particleLater, accordingly
Weight be
(3) resampling process
After the weight for obtaining k moment all particles, the moment total posterior probability density can be calculated as
In formulaFor normalized weight.
(4) estimation output
By executing the recursion step of step 1- step 3, the estimation of quantity of state can be obtained；
The Posterior distrbutionp that mixed Gauss model approximation state is used in important sampling process, is then filtered using Unscented kalman
Wave (UKF), which generates, suggests distribution, estimates charge states of lithium ion battery (SOC) finally by residual error resampling technique.
Compared with prior art, the present invention passes through the mathematical models of lithium-ion battery systems and improved particle filter
Estimation obtains charge states of lithium ion battery, has the characteristics that estimate that accuracy height and estimation are quick, to guarantee lithium-ion electric
The service life in pond.It also have the advantage that
1, approximate by important method of sampling combination Gaussian Mixture, it effectively avoids due to covariance matrix in real process
When unusual, particle weight computing more difficulty and state estimation error co-variance matrix and process noise covariance matrix is being measured
When incomparable in value, the problems such as numerical value is sensitive or calculation overflow, the distribution character of particle weight is improved, thus effectively
It avoids sample degeneracy and greatly improves the estimation performance of filter；
2, it is generated using Unscented kalman filtering (UKF) and suggests distribution, be easy to implement and the preferably approximate weight being really distributed
It wants density function (Importance Density Function, IDF), and is effectively improved SOC in conjunction with residual error resampling technique and estimates
Calculate precision；
3, in lithium ion battery, process noise is relatively small under normal conditions, and state estimation error may be very big,
Correspondingly its covariance is in order to also will be very big comprising evaluated error, and is avoided that in state estimation algorithm through the invention
Numerical value tender subject, meanwhile, particle filter in use, solve the problems, such as sample degeneracy.
Detailed description of the invention
Fig. 1 is battery thevenin equivalent circuit model；
Fig. 2 is battery constant-current pulse discharge current voltage curve；
Fig. 3 is the relationship matched curve of OCV and SOC；
Fig. 4 is to wear Vernam model RLS algorithm parameter identification resistance result；
Fig. 5 is to wear Vernam model RLS algorithm parameter identification capacitor result；
Fig. 6 is the true SOC of battery, particle filter algorithm and improvement without mark particle filter algorithm comparison diagram；
Fig. 7 is particle filter algorithm and improves without mark particle filter algorithm error comparison diagram.
Specific embodiment
The present invention is further illustrated with reference to the accompanying drawings and examples, but be not intended as to the present invention limit according to
According to.
Embodiment: one kind being based on the lithium ion battery of IPF (the improved particle filter of improve Particle Filter)
SOC estimation method, comprising the following steps:
S1, the mathematical model for establishing lithium-ion battery systems obtain the state equation and observational equation of system, and discretization
Processing；
The state equation is
The observational equation is
UL(k)=UOC (k)-i (k) × R0(k)-U1(k)+v(k)
In formula: SOC (k+1) is the charge states of lithium ion battery at system k+1 moment, U1It (k+1) is the system k+1 moment
Polarizing voltage value, Δ t indicate the sampling time, and R1 indicates polarization resistance, and R0 is ohmic internal resistance, and τ 1 indicates the polarization time, and η expression is filled
Discharging efficiency, QN indicate battery actual capacity, and i (k) indicates the discharge current at system k moment, when w (k) and v (k) indicate system k
Quarter state and measurement noise.Lithium ion battery thevenin equivalent circuit illustraton of model is as shown in Figure 1.
S2, constant-current pulse discharge test is being carried out to lithium ion battery, is obtaining lithium ion battery open-circuit voltage and lithium ion
The residual current SOC of battery；Steps are as follows for specific experiment:
1. at room temperature, load of the connection with constant-current discharge function on lithium ion battery；
2. the pairs of maximum charging current values using lithium ion battery carries out constant-current charge to lithium ion battery, until lithium-ion electric
The voltage difference of pond two-stage reaches blanking voltage；
3. continuing to charge to lithium ion battery using lithium ion battery maximum charging voltage constant pressure, until charging current
Less than 0.033C, think that lithium ion battery has been filled with electricity at this time；
4. with the electric current of 0.3C to lithium ion battery carry out continuous discharge, discharge time 10min, if in discharge process lithium from
Sub- cell voltage is lower than minimum voltage, then stops discharging, and terminates test, otherwise continues to discharge；
5. disconnecting circuit after the 10min that discharges stands 1h to lithium ion battery, repeatedly step is 4. later；
6. test terminates；
7. Data Processing in Experiment.
The last 1s discharge voltage of step 4. is denoted as lithium-ion electric tank discharge operating voltage Udn(n=1,2,3 ...), passes through
Following formula calculates the charge that lithium ion battery is released:
Wherein Idn(t) the real-time current size monitored in discharge process, t are indicateddnIndicate discharge time
According to formula:
The residual current SOC of lithium ion battery is calculated, wherein Q0Indicate the total charge dosage of lithium ion battery.It tested
The electric current and voltage tester waveform of journey are as shown in Figure 3.The electric current and voltage tester waveform of experimentation are as shown in Figure 2.
S3, on MATLAB to the relation curve of the residual current SOC of lithium ion battery open-circuit voltage and lithium ion battery
It is fitted, and recognizes and obtain Li-ion battery model parameter, to establish the equivalent model of lithium ion battery；Most using recursion
Small square law (RLS) is fitted the relation curve of lithium ion battery open-circuit voltage and SOC, and the lithium ion battery of fitting is opened
The relation curve of road voltage and SOC are as shown in Figure 3；The parameter of equivalent circuit identification is as shown in Figure 4 and Figure 5.
S4, lithium ion battery SOC is estimated using improved particle filter, steps are as follows for specific method:
(1): initialization: k=0
It is distributed from prior stateExtract one group of particleOne group of parameter is defined simultaneously:Wherein j=1,2 ..., L, L are the dimension of state x；γ
For scale factor
For k=1,2 ...
(2) important sampling process
For i=1,2 ..., N
I. state update is carried out to each particle with UKF
Generate transformation sampling point:
Time updates:
Measurement updaue:
In formula
II. it is sampled from IDF
For i=1,2 ..., N
It estimates the weight of each particle and is normalized:
It can thus be appreciated thatIt is sampled to obtain particleLater, accordingly
Weight be
(3) resampling process
After the weight for obtaining k moment all particles, the moment total posterior probability density can be calculated as
In formulaFor normalized weight.
(4) estimation output
By executing the recursion step of step 1- step 3, the estimation of quantity of state can be obtained；
The Posterior distrbutionp that mixed Gauss model approximation state is used in important sampling process, is then filtered using Unscented kalman
Wave (UKF), which generates, suggests distribution, estimates charge states of lithium ion battery (SOC) finally by residual error resampling technique.
(5) experimental result
As shown in Figure 6, it can be seen that the true SOC of lithium ion battery, particle filter algorithm and improvement are calculated without mark particle filter
The estimation result of method, IPF estimating algorithm are better than particle filter estimating algorithm.
As shown in fig. 7, passing through the estimation error of comparison particle filter and IPF, it can be seen that IPF has more accurate effect
Fruit.
Claims (4)
1. the lithium ion battery SOC estimation method based on IPF, it is characterised in that: the following steps are included:
S1, the mathematical model for establishing lithium-ion battery systems obtain the state equation and observational equation of system, and at discretization
Reason；
S2, constant-current pulse discharge test is carried out to lithium ion battery, obtains lithium ion battery open-circuit voltage and lithium ion battery
Residual current SOC；
S3, the relation curve of the residual current SOC of lithium ion battery open-circuit voltage and lithium ion battery is carried out on MATLAB
Fitting, and recognize and obtain Li-ion battery model parameter, to establish the equivalent model of lithium ion battery；
S4, lithium ion battery SOC is estimated using improved particle filter.
2. the lithium ion battery SOC estimation method according to claim 1 based on IPF, it is characterised in that: the state
Equation is
The observational equation is
UL(k)=UOC (k)-i (k) × R0(k)-U1(k)+v(k)
In formula: SOC (k+1) is the charge states of lithium ion battery at system k+1 moment, U1It (k+1) is the polarization at system k+1 moment
Voltage value, Δ t indicate the sampling time, and R1 indicates polarization resistance, and R0 is ohmic internal resistance, and τ 1 indicates the polarization time, and η indicates charge and discharge
Efficiency, QN indicate that battery actual capacity, i (k) indicate that the discharge current at system k moment, w (k) and v (k) indicate system k moment shape
The noise of state and measurement.
3. the lithium ion battery SOC estimation method according to claim 1 based on IPF, it is characterised in that: the constant current
The step of pulsed discharge is tested is as follows:
1. at room temperature, load of the connection with constant-current discharge function on lithium ion battery；
2. the pairs of maximum charging current values using lithium ion battery carries out constant-current charge to lithium ion battery, until lithium ion battery two
The voltage difference of grade reaches blanking voltage；
3. continuing to charge to lithium ion battery using lithium ion battery maximum charging voltage constant pressure, until charging current is less than
0.033C thinks that lithium ion battery has been filled with electricity at this time；
4. carrying out continuous discharge, discharge time 10min, if lithium-ion electric in discharge process to lithium ion battery with the electric current of 0.3C
Cell voltage is lower than minimum voltage, then stops discharging, and terminates test, otherwise continues to discharge；
5. disconnecting circuit after the 10min that discharges stands 1h to lithium ion battery, repeatedly step is 4. later；
6. test terminates；
7. Data Processing in Experiment；
The last 1s discharge voltage of step 4. is denoted as lithium-ion electric tank discharge operating voltage Udn(n=1,2,3 ...), by following
Formula calculates the charge that lithium ion battery is released:
Wherein Idn(t) the real-time current size monitored in discharge process, t are indicateddnIndicate discharge time；
According to formula:
The residual current SOC of lithium ion battery is calculated, wherein Q0Indicate the total charge dosage of lithium ion battery.
4. the lithium ion battery SOC estimation method according to claim 1 based on IPF, it is characterised in that: the improvement
Particle filter estimate lithium ion battery SOC, method and step is as follows:
(1): initialization: k=0
It is distributed from prior stateExtract one group of particleOne group of parameter is defined simultaneously:Wherein j=1,2 ..., L, L are the dimension of state x；γ
For scale factor
For k=1,2 ...
(2) important sampling process
For i=1,2 ..., N
I. state update is carried out to each particle with UKF
Generate transformation sampling point:
Time updates:
Measurement updaue:
In formula
II. it is sampled from IDF
For i=1,2 ..., N
It estimates the weight of each particle and is normalized:
It can thus be appreciated thatIt is sampled to obtain particleLater, corresponding weight
For
(3) resampling process
After the weight for obtaining k moment all particles, the moment total posterior probability density can be calculated as
In formulaFor normalized weight；
(4) estimation output
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| CN110988722A (en) * | 2019-12-27 | 2020-04-10 | 湖南中大新能源科技有限公司 | Method for rapidly detecting residual energy of lithium ion battery |
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| CN109895657A (en) * | 2019-03-22 | 2019-06-18 | 芜湖职业技术学院 | A kind of power battery SOC estimation device, automobile and method |
| CN110320472A (en) * | 2019-05-17 | 2019-10-11 | 枣庄学院 | A kind of self-correction SOC estimation method for mining lithium battery |
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| CN110988709A (en) * | 2019-10-24 | 2020-04-10 | 延锋伟世通电子科技（南京）有限公司 | SOE and SOP joint estimation method for battery management system |
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