CN106443459A - Evaluation method of state of charge of vehicle lithium ion power battery - Google Patents
Evaluation method of state of charge of vehicle lithium ion power battery Download PDFInfo
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- CN106443459A CN106443459A CN201610803127.6A CN201610803127A CN106443459A CN 106443459 A CN106443459 A CN 106443459A CN 201610803127 A CN201610803127 A CN 201610803127A CN 106443459 A CN106443459 A CN 106443459A
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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]
- G01R31/385—Arrangements for measuring battery or accumulator variables
- G01R31/387—Determining ampere-hour charge capacity or SoC
- G01R31/388—Determining ampere-hour charge capacity or SoC involving voltage measurements
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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]
- G01R31/385—Arrangements for measuring battery or accumulator variables
- G01R31/387—Determining ampere-hour charge capacity or SoC
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Abstract
The invention provides an evaluation method of SOC of a power lithium ion battery management system. The method includes: firstly, simulating the battery by employing a first-order RC equivalent circuit model according to internal electrical characteristics of a lithium ion power battery; determining a polarized internal resistance R1, a polarized capacitance C1 and an ohmic internal resistance R0 etc. of the power battery as key parameters; performing preliminary identification on model parameters with the combination of a charge and discharge experiment; and on the basis, with the combination of a conventional SOC evaluation method, aiming at the lithium ion power battery, establishing an SOC estimation strategy based on Kalman filtering and with the combination of open-circuit voltage correction and an ampere-hour integration method. The test shows that the SOC estimation precision can reach less than 3%.
Description
Technical field
The present invention relates to new energy car battery management system field, more particularly, to one kind are based on lithium-ion-power cell mould
State-of-charge (SOC, the state of charge) evaluation method of type.
Background technology
As the energy storage unit of electric vehicle, its performance directly affects the fuel economy of vehicle and moves electrokinetic cell
Power.Because the actual motion environment of electric vehicle is extremely complex and protean, in order to ensure power battery pack
Can efficiently, reliably and securely work, an effective battery management system is necessary.Especially for activity
The lithium ion battery of (safety is poor) by force, the meaning of battery management system and necessity are then more prominent.
The core missions of battery management system are that inside battery state is estimated, because the internal state of battery can not
Direct measurement, so state estimation is also the difficult point in battery management and control.In practice, not good SOC estimation is often
Leading to SOC larger than expected to fluctuate, thus reducing the cycle life of battery, reducing the energy utilization efficiency of vehicle, and right
Charge and Balance route has very big negative effect.
The SOC method of estimation that automobile vendor, battery manufacturer and scientific research institution propose both at home and abroad at present substantially can be divided into several
Big class, including ampere-hour integration method, open circuit voltage method, fuzzy reasoning method, artificial neural network algorithm etc..
Classical ampere-hour integration method is frequently used for estimating the SOC of battery, conceptive, and this method is very simple and is easy to
Realize.Even so, this kind of method has three obvious shortcomings.First, the determination of initial SOC value is highly difficult, due to first
Beginning SOC error, all subsequent estimated values all possibly have inclined；Additionally, this kind of method is suitable to the precision of current sensor
Sensitivity, in practice, current sensor is often affected by noise, temperature drift and some other unknown random disturbance, long-pending
In point, these random quantitys easily cause larger add up error；Finally, the volume change that cell degradation causes also can affect to pacify
When integration method precision.
Open circuit voltage method simultaneously takes account of the monotonic relationshi between open-circuit voltage and SOC, and open-circuit voltage is through conventional in practice
In the initial SOC of determination.According to the open-circuit voltage of measurement, ask the inverse function (or tabling look-up) of open-circuit voltage function can obtain SOC and estimate
Evaluation.Sometimes open-circuit voltage function is very flat in SOC zone line (between such as 30% to 70%), a little open circuit electricity
Hold up difference and may result in very big SOC estimation difference.Because the set of cells of motor vehicle driven by mixed power is generally in half-full state (about
50%SOC), the SOC initial method being therefore based only on open-circuit voltage is less suitable for use in motor vehicle driven by mixed power.For pure electricity
Motor-car and plug-in hybrid vehicle, battery SOC can often reach SOC two end regions, corresponding open-circuit voltage function
Steeper, so the replacement based on open-circuit voltage in this case can be more efficient.
The method of fuzzy reasoning is to initially set up the fuzzy logic model of an electrokinetic cell, in the work process of battery
Method using closed loop fuzzy reasoning estimates the SOC of battery, but the fuzzy logic model of electrokinetic cell is set up and needed substantial amounts of reality
Test data, and deeply find mathematical law, training logic, method is complicated, and engineering is difficult to realize.
And artificial neural network algorithm, because artificial neural network has nonlinear fundamental characteristics, there is parallel organization
And learning capacity, for external drive, corresponding output can be provided, thus can simulated battery dynamic characteristic, and then estimate SOC
Value.Neural network is applied to various batteries, and shortcoming is to need substantial amounts of reference data to be trained, and estimation difference is subject to training number
According to very big with the impact of training method.
As can be seen here, open circuit voltage method and ampere-hour integration method principle are simple, easily realize, but because its Consideration has
Limit, therefore its range is restricted, the strategy that above two is commonly used especially in HEV all cannot be counted exactly when being used alone
Amount SOC.Although fuzzy reasoning method and artificial neural network algorithm can solve the problems such as the non-linear of battery and multivariate, algorithm
Excessively complexity is it is difficult to realize it is impossible to be applied in the middle of Practical Project.
Content of the invention
The present invention is to solve above-mentioned technical problem, proposes a kind of vehicle lithium-ion power battery charge state estimation method,
Set up the model of electrokinetic cell based on the intrinsic characteristic of battery, based on single order RC model, can preferably characterize battery static characteristic
And dynamic characteristic, in combination with open circuit voltage method, ampere-hour integration and kalman filter method estimation SOC value, realize estimation by mistake
Difference is less than 3%.
To achieve these goals, the present invention adopts the following technical scheme that.
A kind of vehicle lithium-ion power battery charge state estimation method, is a kind of with the karr based on battery dynamic model
Based on graceful filtering, in conjunction with the SOC estimation method of open-circuit voltage correction, ampere-hour integration method, wherein dynamic model adopts single order RC etc.
Effect circuit model；The polarization resistance R1 of electrokinetic cell in model, polarization capacity C1, ohmic internal resistance R0 as key parameter, including
Following steps：
When wherein discharging, the internal relation of each parameter is：
Uo(t)=Uocv(SOC, T)-Up(t)-i(t)*Rd(T, SOC, I) (1)
During charging, the internal relation of each parameter is：
Uo(t)=Uocv(SOC, T)-Up(t)-i(t)*Rc(T, SOC, I) (2)
Wherein
I (t)=Up(t)/Rp+Cp*d(Up(t))/dt (3)
Wherein formula 3 is first-order linear nonhomogeneous equation, and its general solution is formula 4, in the single order RC model revised, has four
Individual important parameter, respectively polarization resistance Rp, polarization capacity Cp, internal charging resistance Rc, electric discharge internal resistance Rd.
Wherein Rp=0.02844, polarization capacity Cp=1054.85, internal charging resistance Rc=0.07, electric discharge internal resistance Rd=0.09
(no, example)
The present invention is further using the EKF correction combining based on electrokinetic cell revision single order RC model
Method, open-circuit voltage correction and ampere-hour integration method realize the estimation to SOC value：First, when BMS goes up electricity first, judge electricity on this
With the time difference in previous lower electricity moment, if greater than calibration value, then table look-up (SOC-OCV) and revise SOC value；If less than demarcation
Value, then read the SOC value in memorizer, then judge whether dynamic current meets KF condition, if meet revising；Finally, quiet
Further ampere-hour integration on the basis of state voltage correction and Kalman filtering correction.
The present invention combines electrokinetic cell revision single order RC model and kalman filtering theory in a upper section, derivation battery
Estimation voltage.Thinking is as follows, in the k moment, the current value being collected by SOC value of battery and the current time in k-1 moment, according to
Output equation (dynamic model of battery) calculates voltage estimated value U (k | k-1) in the k moment for the battery, then by estimated voltage value U
(k | k-1) compare with actual cell voltage U, obtain the estimation difference △ U in k moment, further according to estimation difference and filter gain
Calculate modified gain to SOC, according to this modified gain, estimated value SOC (k | k-1) is modified, you can obtain the k moment
Filter value output result SOC (k | k), this output result is calculated as k+1 moment battery SOC initial value.So follow
Ring is back and forth calculated, and filtering passes through gradually to revise SOC estimation, makes estimated value close to model value.
The technology of the present invention effect is：Filter gain have adjusted the speed of correction, and therefore makeover process does not result in SOC
The mutation of value, this is also beneficial to be avoided the impact to hybrid-power electric vehicle full-vehicle control for the SOC mutation.
Brief description
The equivalent-circuit model of the single order RC adopting in Fig. 1 present invention.
Fig. 2 is under different SOC with different current impulse charge-discharge test steps.
Fig. 3 checking to battery model under different SOC, different current impulse charge-discharge test.
The SOC estimation flow chart that Fig. 4 present invention adopts.
Fig. 5 is directed to the SOC estimation error of a certain real vehicle floor data estimation.
Specific embodiments
With reference to embodiment, the invention will be further described.
Fig. 1 is the revision single order RC model adopting in invention, and in model, Uocv is electrokinetic cell open-circuit voltage, Cp and Rp
The polarization link of description battery in parallel, the dynamic characteristic being showed in the generation of polarization with during eliminating for simulated battery,
The effect of middle diode is to represent the direction that electric current flows through, and internal charging resistance and electric discharge internal resistance is separated, output voltage is Uo.
Testing process of the present invention uses composite pulse power characteristic to test (HPPC Test), and battery behavior testing experiment was both
Parameter characteristic under electric discharge for the battery need to be considered, simultaneously also parameter characteristic under charging for the battery to be considered, in equally spaced SOC
At point, the parameter of battery is recognized, and then realize to the parameter identification under different state-of-charges.The data mould recognizing
Shape parameter result be polarization resistance Rp=0.02844, polarization capacity Cp=1054.85, internal charging resistance Rc=0.07, electric discharge internal resistance
Rd=0.09；
The present invention verifies to the precision of the battery model set up, and devises some under different use conditions to electricity
Pond carries out the experiment of discharge and recharge, and the output result of battery model is compared with actual samples result, analyzes its error.Carry out
Model confirmatory experiment have in the pulse charge-discharge test under different battery SOCs, the pulse charge and discharge under different charging and discharging currents
Electricity experiment and the experiment of the simulated condition under different SOC etc..Under different battery SOCs, horizontal pulse is entered with different electric currents,
The experimental procedure of discharge and recharge is as shown in Figure 2.Although result is as shown in figure 3, model error in the case of high current work is larger,
But from the point of view of this process, model remains able to preferably follow the tracks of virtual voltage, especially in charge and discharge process and subsequent quiet
The gradual effect of delay of virtual voltage can be followed the tracks of well during putting.
The present invention is further using the EKF correction combining based on electrokinetic cell revision single order RC model
Method, open-circuit voltage correction and ampere-hour integration method realize the estimation to SOC value.SOC estimation strategic process is as shown in Figure 4.First, when
BMS goes up electricity first, judges the time difference in electric and previous lower electricity moment on this, if greater than calibration value, then table look-up (SOC-
OCV) revise SOC value；If less than calibration value, then read the SOC value in memorizer, then judge dynamic current (note：Cause exists
Find in development process, electric current is excessive, and model calculation error can increase, and therefore carries out some term restrictions) whether meet KF bar
Part, if meet revise；Finally, further ampere-hour integration on the basis of quiescent voltage correction and Kalman filtering correction.
The present invention combines electrokinetic cell revision single order RC model and kalman filtering theory in a upper section, derivation battery
Estimation voltage：In the k moment, the current value being collected by SOC value of battery and the current time in k-1 moment, according to output equation
(dynamic model of battery) calculates voltage estimated value U (k | k-1) in the k moment for the battery, then by estimated voltage value U (k | k-1)
Compare with actual cell voltage U, obtain the estimation difference △ U in k moment, it is right to calculate further according to estimation difference and filter gain
The modified gain of SOC, is modified to estimated value SOC (k | k-1) according to this modified gain, you can obtain the filtering in k moment
Value output result SOC (k | k), this output result is calculated as k+1 moment battery SOC initial value.So move in circles
Calculated.Filtering passes through gradually to revise SOC estimation, makes estimated value close to model value, filter gain have adjusted to be repaiied
Positive speed, therefore makeover process do not result in the mutation of SOC value, and this is also beneficial to be avoided SOC to be mutated to hybrid electric
The impact of car full-vehicle control.
The SOC estimating algorithm that the present invention is built, has tentatively carried out stand checking.Integrated engine bench test is directed to certain battery
Producer's lithium-ion-power cell group 5.3Ah, is changed a social system to battery bag, and using Digatron test equipment, it is carried out
Working condition measurement.Current value using Digatron record carrys out reference value true as SOC to time integral, records BMS work simultaneously
Voltage sample value during work, estimated value and SOC value of calculation.Fig. 5 is a certain real vehicle working condition tests result, passing by algorithm
Push away calculating, the actual error of SOC estimation starts rapid reduction from 36%, and after 32s, the actual error of SOC estimation is little
In 3%；In estimation steps afterwards, the actual error most of the time of SOC estimation is all not more than 2%.It can be seen that, in real vehicle
Under driving cycle, this algorithm still has quick convergence and stability, so, the SOC estimating algorithm that the present invention adopts is fitted
Estimation together in electric automobile power battery state-of-charge.
Claims (3)
1. the present invention relates to a kind of vehicle lithium-ion power battery charge state estimation method it is characterised in that：
For a kind of based on the Kalman filtering based on battery dynamic model, in conjunction with the SOC of open-circuit voltage correction, ampere-hour integration method
Evaluation method, wherein dynamic model adopt single order RC equivalent-circuit model；The polarization resistance R1 of electrokinetic cell, polarization electricity in model
Hold C1, ohmic internal resistance R0 as key parameter, comprise the steps：
When wherein discharging, the internal relation of each parameter is：
Uo(t)=Uocv(SOC, T)-Up(t)-i(t)*Rd(T, SOC, I) (1)
During charging, the internal relation of each parameter is：
Uo(t)=Uocv(SOC, T)-Up(t)-i(t)*Rc(T, SOC, I) (2)
Wherein
I (t)=Up(t)/Rp+Cp*d(Up(t))/dt (3)
Wherein formula 3 is first-order linear its equation of n th order n non-, and its general solution is formula 4.In the single order RC model revised, there are four weights
The parameter wanted, respectively polarization resistance Rp, polarization capacity Cp, internal charging resistance Rc, electric discharge internal resistance Rd.Because parameters are subject to electricity
The state-of-charge (SOC) of pond discharge and recharge, the size of electric current, sense of current, the impact of temperature, therefore have selected suitable test
Condition and testing process battery is carried out charge-discharge test, and then each parameter of the identification different conditions drag of system.
2. vehicle lithium-ion power battery charge state estimation method according to claim 1 it is characterised in that：
Methods described, based on Kalman filtering, in conjunction with the SOC estimation method of open-circuit voltage correction, ampere-hour integration method, is comprehensively transported
With voltage, electric current, temperature information estimation SOC value：First, when BMS goes up electricity first, judge the electric and previous lower electricity moment on this
Time difference, if greater than calibration value, then looks into SOC-OCV table correction SOC value；If less than calibration value, then read in memorizer
SOC value, then judges whether dynamic current meets KF condition, if meet revising；Finally, filter in quiescent voltage correction and Kalman
Further ampere-hour integration on the basis of ripple correction.
3. vehicle lithium-ion power battery charge state estimation method according to claim 1 it is characterised in that：
Described single order RC equivalent circuit, carries out mould by equivalent circuit to lithium-ion-power cell inside electrochemical reaction process
Intend, the polarization resistance R1 of the internal association of construction force battery status amount and input quantity, the wherein electrokinetic cell in model, pole
Change：
In the k moment, the current value being collected by SOC value of battery and the current time in k-1 moment, defeated according to the dynamic model of battery
Go out voltage estimated value U (k | k-1) in the k moment for the Equation for Calculating battery, then by estimated voltage value U (k | k-1) and actual battery
Voltage U compares, and obtains the estimation difference △ U in k moment, calculates the correction to SOC further according to estimation difference and filter gain and increases
Benefit, is modified to estimated value SOC (k | k-1) according to this modified gain, you can obtain the filter value output result in k moment
SOC (k | k), this output result is calculated as k+1 moment battery SOC initial value, so moves in circles and calculated, filter
Wave process passes through gradually to revise SOC estimation.
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| CN106646268A (en) * | 2017-03-07 | 2017-05-10 | 安徽江淮汽车集团股份有限公司 | SOC compensation method for power battery |
| CN106772104A (en) * | 2017-02-27 | 2017-05-31 | 安徽江淮汽车集团股份有限公司 | A kind of electrokinetic cell SOC value evaluation method |
| CN107066722A (en) * | 2017-04-06 | 2017-08-18 | 北京理工大学 | A kind of combined estimation method of electrokinetic cell system state-of-charge and health status based on electrochemical model |
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