CN107656190A - Charge-discharge characteristic curve fitting algorithm under a kind of RC charging and discharging circuits - Google Patents
Charge-discharge characteristic curve fitting algorithm under a kind of RC charging and discharging circuits Download PDFInfo
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Abstract
The invention provides charge-discharge characteristic curve fitting algorithm under a kind of RC charging and discharging circuits, including according to actual charging characteristic curve 1 and actual discharge characteristic curve 1, a charging characteristic curve 2 and a discharge characteristic curve 2 are assumed respectively, by actual charging characteristic curve 1 and charging characteristic curve 2, actual discharge characteristic curve 1 and discharge characteristic curve 2 are fitted respectively, respectively obtain filling under big step length, discharge characteristic curve eigenvalue cluster, by small step length, fitting obtains filling under small step length again respectively again, discharge curve characteristic value, so that it is determined that actual charging characteristic curve 1 and actual discharge characteristic curve 1, it expands the application of RC charging and discharging circuit curve fitting techniques, reach simultaneously and efficiently fill, discharge characteristic curve is fitted speed and the degree of accuracy.
Description
Technical field
The present invention relates to charge-discharge characteristic curve under a kind of charging and discharging circuit research, more particularly to a kind of RC charging and discharging circuits
Fitting algorithm.
Background technology
Parse RC charge-discharge circuit is exactly to find its corresponding physical characteristic at all, and a most important step is exactly among these
Find out its corresponding discharge and recharge equation.By curve matching, it can find and meet department of physics corresponding to RC charge and discharge characteristic curves
Number, so as to help to analyze.Existing charge and discharge characteristic curve efficient high-speed fitting technique realizes on PC ends, particularly base
In MATLAB fitting technique, the intrepid hardware processing capabilities of PC are all based on.But embedded platform hardware processing capability is
That height cannot be reached, this is just determined needs to reach the plan of high-speed and high-efficiency by algorithm optimization on embedded platform
Close effect.
Secondly, when electric automobile solves insulating resistance value using predictive algorithm at present, because RC circuits are present, chip is caused
Gather AD sample misalignments.Cause circuit components both end voltage misalignment because RC circuits are present, voltage delay stabilization, thus
Its result of calculation is often wrong, and causes great workload.
Thus, being badly in need of a kind of fitting algorithm can be applied to embedded platform, while can also solve to use in the presence of RC circuits
Accurate solution of the predictive algorithm to insulating resistance value.
The content of the invention
Based on above-mentioned background, the invention provides charge-discharge characteristic curve fitting algorithm under a kind of RC charging and discharging circuits, its
The application of RC charging and discharging circuit curve fitting techniques is expanded, while reaches efficient charge and discharge characteristic curve fitting speed
And the degree of accuracy.
To achieve the above object, the invention provides charge-discharge characteristic curve fitting algorithm under a kind of RC charging and discharging circuits,
Including：According to actual charging characteristic curve 1Vt=V0+ (Vu1-V0) * [1-exp (- t*B1)] and actual discharge characteristic curve 1Vt
=E1*exp (- t*B`1)+Vc1, charging characteristic curve 2Vt=V0+ (Vu2-V0) * [1-exp (- t*B2)] is assumed respectively
With discharge characteristic curve 2Vt=E2*exp (- t*B`2)+Vc2, by actual charging characteristic curve 1 and charging characteristic curve 2,
Actual discharge characteristic curve 1 and discharge characteristic curve 2 are fitted respectively, respectively obtain the charging characteristic curve under big step length
Eigenvalue cluster main (Vu2_a, B2_a) and discharge characteristic curve eigenvalue cluster main (E2_a, B`2_a, Vc2_a), then by small
Step length is in charging characteristic curve eigenvalue cluster main (Vu2_a, B2_a) and discharge characteristic curve eigenvalue cluster main (E2_a, B
`2_a, Vc2_a) on the basis of fit Vu2 and B2 exact value and discharge characteristic curve 2 in charging characteristic curve 2 again respectively
Middle E2, B`2, Vc2 exact value, obtain charging curve characteristic value Vu2_b, B2_b and discharge curve characteristic value under small step length
E2_b, B`2_b, Vc2_b, so that it is determined that actual charging characteristic curve 1 and actual discharge characteristic curve 1 are (when V0 starts for charging
Monitoring object magnitude of voltage；Vu1, Vu2 are charging complete monitoring object final voltage value；Vt is monitoring object t electricity at any time
Pressure value；B1, B2 are RC charge characteristic coefficients；E1, E2 are monitoring object, and from starting to discharge into electric discharge, to terminate total discharge voltage poor
Value；B`1, B`2 are RC flash-over characteristic coefficients；Vc1, Vc2 are itself existing stable voltage after monitoring object electric discharge terminates；
Exp () is exponential function).
Further, it is described to be fitted actual charging characteristic curve 1 and charging characteristic curve 2, obtain big step length
Under charging characteristic curve eigenvalue cluster main (Vu2_a, B2_a), including：Assuming that actual charging characteristic curve 1Vt=V0+
(Vul-V0) * [1-exp (- t*B1)] has n sample point C0~Cn-1, in charging characteristic curve 2Vt=V0+ (Vu2-V0) * [1-
Exp (- t*B2)] on choose n there are the points of identical abscissa with sample point C0~Cn-1, using least square method, by not
Disconnected two coefficients Vu2 and B2 for changing charging characteristic curve 2 obtain various SUM values, and when the SUM value minimum, charge characteristic is bent
Line 2 and actual charging characteristic curve 1 are closest, and at this time the coefficient of two curves is closest, can obtain filling under big step length
Electrical characteristics eigenvalue of curve group main (Vu2_a, B2_a).
Further, it is described to be fitted actual discharge characteristic curve 1 and discharge characteristic curve 2, obtain big step length
Under discharge characteristic curve eigenvalue cluster main (E2_a, B`2_a, Vc2_a), including：Assuming that actual discharge characteristic curve 1Vt=
E1*exp (- t*B`1)+Vc1 has n sample point C0~Cn-1, on discharge characteristic curve 2Vt=E2*exp (- t*B`2)+Vc2
The n points with sample point C0~Cn-1 with identical abscissa are chosen, using least square method, by constantly changing flash-over characteristic
Three coefficients E2, B`2 and Vc2 of curve 2, obtain various SUM values, when the SUM value minimum, discharge characteristic curve 2 and reality
Discharge characteristic curve 1 is closest, and at this time the coefficient of two curves is closest, can obtain the discharge characteristic curve under big step length
Eigenvalue cluster main (E2_a, B`2_a, Vc2_a).
Further, it is described in charging characteristic curve eigenvalue cluster main (Vu2_a, B2_a) and to be discharged by small step length
Vu2 in charging characteristic curve 2 is fitted again respectively on the basis of characteristic curve eigenvalue cluster main (E2_a, B`2_a, Vc2_a)
Exact value with E2, B`2, Vc2 in B2 exact value and discharge characteristic curve 2 is by least square method, so that it is determined that actual
Charging characteristic curve 1 and actual discharge characteristic curve 1.
Further, it is described by least square method so that it is determined that actual charging characteristic curve 1 includes：Actual charging is special
The abscissa of linearity curve 1 is all set as being spaced identical moment value T [i] (i takes 0,1,2 ... n-1), and ordinate is the corresponding moment
The Vt values gathered out, by the actual charging characteristic curve 1 of abscissa identical and the quadratic sum of the ordinate difference of charging characteristic curve 2
SUM is fitting criterion, calculates the SUM value under various combination main (Vu2_a, B2_a), when SUM value is less than certain value,
Vu2_a, B2_a now is exactly actual charging characteristic curve characteristic value Vu2_b, B2_b.
SUM calculation is：
(i- represents i-th of sample point, the abscissa of actual i-th of the sample point of charging characteristic curve 1 of T [i]-expression, buf
[i]-represent ordinate of i-th of sample point on actual charging characteristic curve 1)
Further, the SUM value under the calculating various combination main (Vu2_a, B2_a) is by by various combination main
Vu2_a spans under (Vu2_a, B2_a) are (Vui, Vui+1), and Vui is that Vu2_a subtracts big twice step-length, and Vui+1 is
Vu2_a adds big twice step-length, and all SUM values that are related to are represented with SUMn, buffering array is stored in this, passes through program meter
When calculating and obtaining SUM value and be less than certain value, corresponding Vu2_a, B2_a are exactly actual charging characteristic curve characteristic value Vu2_b, B2_
b。
Further, it is described by least square method so that it is determined that actual discharge characteristic curve 1 includes：Actual discharge is special
The abscissa of linearity curve 1 is all set as being spaced identical moment value T [i] (i takes 0,1,2 ... n-1), and ordinate is the corresponding moment
The Vt values gathered out, by abscissa identical actual discharge characteristic curve 1 and the quadratic sum of the ordinate difference of discharge characteristic curve 2
SUM is fitting criterion, calculates the SUM value under various combination main (E2_a, B`2_a, Vc2_a), when SUM value is less than necessarily
During value, E2_a, B`2_a, Vc2_a now are exactly actual discharge characteristic curve characteristic value E2_b, B`2_b, Vc2_b.
SUM calculation is：
(i- represents i-th of sample point, the abscissa of T [i]-i-th of sample point of expression actual discharge characteristic curve 1, buf
The ordinate of i-th of the sample point of [i]-expression actual discharge characteristic curve 1)
Further, the SUM value under the calculating various combination main (E2_a, B`2_a, Vc2_a), in various combination
E2_a span (Ei, Ei+1), Ei try to achieve E2_a for big step-length and subtract big twice step-length, and Ei+1 is that big step-length tries to achieve E2_a
Plus big twice step-length, Vt values during by assuming just to have started electric discharge be Vf0, then final electric discharge end Vt values in [0,
Vf0] between, the Vt values for taking T [0] moment are Vf0, are fully completed rear E+Vc=Vf0 according to electric discharge, it is specified that all be related to SUM
Value is represented with SUMn, and buffering array is stored in this, when being less than certain value by program calculating to obtain SUM value, E2_a, B`2_
A, Vc2_a is exactly actual discharge characteristic curve characteristic value E2_b, B`2_b, Vc2_b.
The present invention is exactly that big step length fitting is quick to be determined to terminate result by big step length and small step length twice fitting
Scope, small step length fit within and accurately determine final fitting result in the scope that big step length determines, its accuracy rate is high.Such RC
The characteristic Fast Fitting of charge and discharge, is just no longer limited only to PC ends, so as to promote RC curve fitting techniques embedding
Enter the utilization on formula platform, optimize the data processing method of embedded platform, reduce data processing amount, allow embedded platform
Have the high-speed and high-efficiency capability of fitting to meeting charge-discharge characteristic data.Likewise, the new fitting algorithm of the present invention takes into full account
To due to circuit components both end voltage misalignment problem caused by the presence of RC circuits, using thought is estimated, pass through and analyze existing sample
This point, the accurate voltage at component both ends in circuit after final RC circuit stabilities is estimated out, to the phenomenon with RC circuit characteristics
Insulating resistance value predictive algorithm accurately solve to analysis provide a kind of new method.
Brief description of the drawings
Fig. 1 is charging characteristic curve fitted figure.
Fig. 2 is charging characteristic curve coefficient characteristics value fit procedure figure.
Fig. 3 is discharge characteristic curve system fitted figure.
Fig. 4 is discharge characteristic curve coefficient characteristics value fit procedure figure.
Embodiment
Technical scheme is further illustrated below by embodiment, but does not form and the present invention is appointed
What is limited.
Illustrate charging characteristic curve first.
For charging characteristic curve equation, it would be desirable to which fitting has two coefficients, i.e. charging terminates rear final voltage Vu
With charging physical characteristic coefficient B.Specific approximating method is following (such as Fig. 1)：Assuming that the curve Vt where n sample point C0~Cn-1
=V0+ (Vu1-V0) * [1-exp (- t*B1)] is actual charging characteristic curve 1, i.e., we need the Charging equation coefficient solved
The charging characteristic curve of representative.In order to solve actual charging curve coefficient, we first give a charging characteristic curve Vt=V0+
(Vu2-V0) * [1-exp (- t*B2)], that is, charging characteristic curve 2 is assumed, assuming that choosing n and sample on charging characteristic curve 2
This C0~Cn-1 has point D0~Dn-1 of identical abscissa.By least square method, by two that constantly change curve 2
Coefficient Vu2 and B2, try to achieve corresponding SUM value, and curve 2 and curve 1 are obtained during SUM value minimum near at this moment two curves is
Number is closest, can obtain the charging characteristic curve eigenvalue cluster main (Vu2_a, B2_a) under big step length.
Further, we determined that going out Vu2 and B2 exact value.By actual charging characteristic curve 1 and charging characteristic curve 2
Abscissa is set as being spaced identical moment value T [i] (i takes 0,1,2 ... n-1), such as 10,30,50,70 ..., and ordinate is phase
The Vt values that should be gathered out constantly.We are provided the actual charging characteristic curve 1 of abscissa identical and the vertical seat of charging characteristic curve 2
The quadratic sum SUM for marking difference is fitting criterion, calculates the SUM value under various combination main (Vu2_a, B2_a).
Calculation formula is as follows：
SUM calculation is：
(i- i-th of sample point of expression, the abscissa of actual i-th of the sample point of charging curve 1 of T [i]-expression, buf [i]-
Represent the ordinate of actual i-th of sample point of charging curve 1)
It is obvious that when SUM value is less than certain value, illustrate to assume charging characteristic curve and actual charging characteristic curve weight
Close, Vu2_a, B2_a now are exactly actual charging characteristic curve characteristic value Vu2_b, B2_b.
With the following method, realize by most it is fast it is most efficient in a manner of find actual charging characteristic curve coefficient.It is obvious that fill
After electricity terminates, Vt values that T [n-1] moment collects, terminate rear Vu2_a values closest to charging, and actual Vu2_a values are more than certainly
Or equal to this Vt value, then our cans searched in the certain limit more than this Vt value reality charging terminate after
Vu2_a values.Assuming that it is (Vui, Vui+1) that charging, which terminates rear Vu2_a spans, Vui is the Vt values collected at T [n-1] moment,
Vui+1 is the integral multiple of the Vt values collected at T [n-1] moment.All values for being related to SUM are provided in order to distinguish all with SUMn (n
Take 0,1,2 ...) represent；Sample point ordinate is stored in buffering array buf [n] (n is sample point number) successively, passes through journey
When sequence calculates and obtains SUM value and be less than certain value, corresponding Vu2_a, B2_a are exactly actual charging characteristic curve characteristic value Vu2_
b、B2_b.Charge characteristic fitting thinking is as shown in Figure 2.
Secondly, illustrate by taking discharge characteristic curve as an example.
For discharge characteristic curve equation, it should be noted that (Vc is monitoring object electric discharge knot to more fitting parameter Vc
Itself existing stable voltage after beam), but certain relation be present between Vc and discharge voltage variable quantity E, so from certain
Said in kind degree, or only two fitting coefficients B and E.Also assume that the curve Vt=where n sample point C0~Cn-1
E1*exp (- t*B`1)+Vc1 is actual discharge characteristic curve 1, and such as Fig. 3, i.e., the electric discharge equation coefficient that we need to solve represents
Discharge characteristic curve.In order to solve actual discharge characteristic curve coefficient, we first give a discharge characteristic curve Vt=E2*
Exp (- t*B`2)+Vc2, that is, assume discharge characteristic curve 2, assuming that chosen on discharge characteristic curve 2 n and sample point C0~
Cn-1 has point D0~Dn-1 of identical abscissa, by three coefficients E2, B`2 and Vc2 constantly changing curve 2 so that bent
Line 2 is with curve 1 near at this time the coefficient of two curves is closest, and the discharge characteristic curve that can obtain under big step length is special
Value indicative group main (E2_a, B`2_a, Vc2_a).
Further, we determined that going out E2 and B`2 exact value.By actual discharge characteristic curve 1 and discharge characteristic curve 2
Abscissa is set as being spaced identical moment value T [i] (i takes 0,1,2 ... n-1), such as 10,30,50,70 ..., and ordinate is phase
The Vt values that should be gathered out constantly.We are provided abscissa identical actual discharge characteristic curve 1 and the vertical seat of discharge characteristic curve 2
The quadratic sum SUM for marking difference is fitting criterion, calculates the SUM value under various combination main (E2_a, B`2_a, Vc2_a),
SUM calculation is：
(i- i-th of sample point of expression, the abscissa of T [i]-i-th of sample point of expression actual discharge curve 1, buf [i]-
Represent the ordinate of i-th of the sample point of actual discharge curve 1)
It is obvious that when SUM value is less than certain value, illustrate to assume discharge characteristic curve and actual discharge characteristic curve weight
Close, E2_a, B`2_a, Vc2_a now are exactly actual discharge characteristic curve characteristic value E2_b, B`2_b, Vc2_b.
With the following method, realize by most it is fast it is most efficient in a manner of find actual discharge characteristic curve coefficient.Assuming that just open
The Vt values of beginning discharging time are Vf0, then final electric discharge terminates rear Vt values and is necessarily between [0, Vf0], and we can take T
[0] the Vt values at moment are Vf0.It is obvious that electric discharge is fully completed rear E+Vc=Vf0；Provide all values for being related to SUM for area
Divide and all represented with SUMn (n takes 0,1,2 ...)；Sample point ordinate is stored in buffering array buf [n] successively, and (n is sample point
Number) in, when being less than certain value by program calculating to obtain SUM value, E2_a, B`2_a, Vc2_a are exactly actual discharge characteristic song
Line characteristic value E2_b, B`2_b, Vc2_b.Flash-over characteristic fitting thinking is as shown in Figure 4.
By the charge and discharge characteristic equation coefficient solved, we it is known that actual charge and discharge characteristic curve, this
Sample we it is known that charge and discharge terminate the Vt values after rear charging complete.
Claims (8)
1. charge-discharge characteristic curve fitting algorithm under a kind of RC charging and discharging circuits, including：According to actual charging characteristic curve 1Vt=
V0+ (Vu1-V0) * [1-exp (- t*B1)] and actual discharge characteristic curve 1Vt=E1*exp (- t*B`1)+Vc1, assumes respectively
One charging characteristic curve 2Vt=V0+ (Vu2-V0) * [1-exp (- t*B2)] and a discharge characteristic curve 2Vt=E2*exp
(- t*B`2)+Vc2, actual charging characteristic curve 1 and charging characteristic curve 2, actual discharge characteristic curve 1 and flash-over characteristic is bent
Line 2 is fitted respectively, is respectively obtained the charging characteristic curve eigenvalue cluster main (Vu2_a, B2_a) under big step length and is put
Electrical characteristics eigenvalue of curve group main (E2_a, B`2_a, Vc2_a), then by small step length in charging characteristic curve eigenvalue cluster
Intend again respectively on the basis of main (Vu2_a, B2_a) and discharge characteristic curve eigenvalue cluster main (E2_a, B`2_a, Vc2_a)
The exact value of E2, B`2, Vc2 in Vu2 and B2 exact value and discharge characteristic curve 2 in charging characteristic curve 2 are closed out, is obtained small
Charging curve characteristic value Vu2_b, B2_b and discharge curve characteristic value E2_b, B`2_b, Vc2_b under step length, so that it is determined that real
Border charging characteristic curve 1 and actual discharge characteristic curve 1
(monitoring object magnitude of voltage when V0 starts for charging；Vu1, Vu2 are charging complete monitoring object final voltage value；Vt is prison
Survey object t magnitudes of voltage at any time；B1, B2 are RC charge characteristic coefficients；E1, E2 are monitoring object from starting to discharge into electric discharge
Terminate total discharge voltage difference；B`1, B`2 are RC flash-over characteristic coefficients；Vc1, Vc2 are that monitoring object electric discharge terminates afterwards in itself
Existing stable voltage；Exp () is exponential function).
2. charge-discharge characteristic curve fitting algorithm under RC charging and discharging circuits according to claim 1, it is characterised in that described
Actual charging characteristic curve 1 and charging characteristic curve 2 are fitted, obtain the charging characteristic curve characteristic value under big step length
Group main (Vu2_a, B2_a), including：Assuming that actual charging characteristic curve 1Vt=V0+ (Vu1-V0) * [1-exp (- t*B1)] has
N sample point C0~Cn-1, n and sample are chosen on charging characteristic curve 2Vt=V0+ (Vu2-V0) * [1-exp (- t*B2)]
This C0~Cn-1 has the point of identical abscissa, using least square method, by two that constantly change charging characteristic curve 2
Coefficient Vu2 and B2, obtain various SUM values, and when the SUM value minimum, charging characteristic curve 2 and actual charging characteristic curve 1 are most
It is close, it at this time can obtain the charging characteristic curve eigenvalue cluster main (Vu2_a, B2_a) under big step length.
3. charge-discharge characteristic curve fitting algorithm under RC charging and discharging circuits according to claim 1, it is characterised in that described
Actual discharge characteristic curve 1 and discharge characteristic curve 2 are fitted, obtain the discharge characteristic curve characteristic value under big step length
Group main (E2_a, B`2_a, Vc2_a), including：Assuming that actual discharge characteristic curve 1Vt=E1*exp (- t*B`1)+Vc1 has n
Individual sample point C0~Cn-1, chosen on discharge characteristic curve 2Vt=E2*exp (- t*B`2)+Vc2 n and sample point C0~
Cn-1 has the point of identical abscissa, using least square method, by three coefficients E2, B constantly changing discharge characteristic curve 2
`2 and Vc2, various SUM values are obtained, when the SUM value minimum, discharge characteristic curve 2 and actual discharge characteristic curve 1 are closest,
It at this time can obtain the discharge characteristic curve eigenvalue cluster main (E2_a, B`2_a, Vc2_a) under big step length.
4. charge-discharge characteristic curve fitting algorithm under RC charging and discharging circuits according to claim 1, it is characterised in that described
By small step length in charging characteristic curve eigenvalue cluster main (Vu2_a, B2_a) and discharge characteristic curve eigenvalue cluster main
It is special to fit Vu2 and B2 exact value and electric discharge in charging characteristic curve 2 on the basis of (E2_a, B`2_a, Vc2_a) again respectively
E2, B`2, Vc2 exact value are by least square method, so that it is determined that actual charging characteristic curve 1 and actually putting in linearity curve 2
Electrical characteristics curve 1.
5. charge-discharge characteristic curve fitting algorithm under RC charging and discharging circuits according to claim 4, it is characterised in that described
By least square method so that it is determined that actual charging characteristic curve 1 includes：The abscissa of actual charging characteristic curve 1 is all set
For interval identical moment value T [i] (i takes 0,1,2 ... n-1), ordinate is the Vt values gathered out at the corresponding moment, by abscissa
The actual charging characteristic curve 1 of identical and the quadratic sum SUM of the ordinate difference of charging characteristic curve 2 are fitting criterion, are counted
The SUM value under various combination main (Vu2_a, B2_a) is calculated, when SUM value is less than certain value, Vu2_a, B2_a now are exactly
Actual charging characteristic curve characteristic value Vu2_b, B2_b.
6. charge-discharge characteristic curve fitting algorithm under RC charging and discharging circuits according to claim 5, it is characterised in that described
SUM value under various combination main (Vu2_a, B2_a) is calculated by by the Vu2_ under various combination main (Vu2_a, B2_a)
A spans are (Vui, Vui+1), and Vui tries to achieve Vu2_a for big step-length and subtracts big twice step-length, and Vui+1 is that big step-length is tried to achieve
Vu2_a adds big twice step-length, and all SUM values that are related to are represented with SUMn, buffering array is stored in this, passes through program meter
When calculating and obtaining SUM value and be less than certain value, corresponding Vu2_a, B2_a are exactly actual charging characteristic curve characteristic value Vu2_b, B2_
b。
7. charge-discharge characteristic curve fitting algorithm under RC charging and discharging circuits according to claim 4, it is characterised in that described
By least square method so that it is determined that actual discharge characteristic curve 1 includes：The abscissa of actual discharge characteristic curve 1 is all set
For interval identical moment value T [i] (i takes 0,1,2 ... n-1), ordinate is the Vt values gathered out at the corresponding moment, by abscissa
Identical actual discharge characteristic curve 1 and the quadratic sum SUM of the ordinate difference of discharge characteristic curve 2 are fitting criterion, are counted
Calculate the SUM value under various combination main (E2_a, B`2_a, Vc2_a), when SUM value is less than certain value, E2_a, B`2_ now
A, Vc2_a is exactly actual discharge characteristic curve characteristic value E2_b, B`2_b, Vc2_b.
8. charge-discharge characteristic curve fitting algorithm under RC charging and discharging circuits according to claim 7, it is characterised in that described
Calculate the SUM value under various combination main (E2_a, B`2_a, Vc2_a), E2_a span (Ei, Ei+ in various combination
1), Ei tries to achieve E2_a for big step-length and subtracts big twice step-length, and Ei+1 tries to achieve E2_a for big step-length and adds big twice step-length, passes through vacation
Vt values when determining just to start electric discharge are Vf0, then final electric discharge terminates E values and is between [0, Vf0], takes the Vt values at T [0] moment
For Vf0, rear E+Vc=Vf0 is fully completed according to electric discharge, it is specified that all SUM values that are related to are represented with SUMn, is stored in this slow
Array is rushed, when being less than certain value by program calculating to obtain SUM value, E2_a, B`2_a, Vc2_a are exactly actual discharge characteristic song
Line characteristic value E2_b, B`2_b, Vc2_b.
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0980130A (en) * | 1995-09-18 | 1997-03-28 | Nippon Telegr & Teleph Corp <Ntt> | Storage battery capacity measurement method |
| CN1431521A (en) * | 2003-01-16 | 2003-07-23 | 华南理工大学 | Method for measuring electric quantity of lithium ion batteries and its device |
| CN102624017A (en) * | 2012-03-22 | 2012-08-01 | 清华大学 | Battery energy storage system peak clipping and valley filling real-time control method based on load prediction |
| CN103592579A (en) * | 2013-07-30 | 2014-02-19 | 中国电力科学研究院 | Impulse discharge voltage calculating model construction method |
| DE102013113951A1 (en) * | 2013-01-31 | 2014-07-31 | GM Global Technology Operations LLC | A method of detecting open circuit voltage shifts by optimization by adjusting the anode electrode half cell voltage waveform |
| WO2014185163A1 (en) * | 2013-05-16 | 2014-11-20 | 日本電気株式会社 | Cell state-maintaining device, cell state management system, cell, method for maintaining cell state, and program |
| CN104657520A (en) * | 2013-11-18 | 2015-05-27 | 国家电网公司 | Battery modeling method based on large capacity energy accumulation lithium ion battery |
| CN104749529A (en) * | 2015-04-01 | 2015-07-01 | 上海理工大学 | Calibration method of charge and discharge characteristics of lithium battery and charge and discharge characteristics calibration apparatus |
| CN105677979A (en) * | 2016-01-07 | 2016-06-15 | 北京北交新能科技有限公司 | Lithium titanate battery improvement model based on Butler-Volmer equation |
| US20170212170A1 (en) * | 2016-01-21 | 2017-07-27 | Yokogawa Electric Corporation | Secondary battery capacity measuring system and secondary battery capacity measuring method |
| CN106997028A (en) * | 2017-05-19 | 2017-08-01 | 江苏大学 | A kind of battery differential voltage and incremental capacity plot Efficient Solution method |
-
2017
- 2017-09-18 CN CN201710846926.6A patent/CN107656190B/en not_active Expired - Fee Related
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0980130A (en) * | 1995-09-18 | 1997-03-28 | Nippon Telegr & Teleph Corp <Ntt> | Storage battery capacity measurement method |
| CN1431521A (en) * | 2003-01-16 | 2003-07-23 | 华南理工大学 | Method for measuring electric quantity of lithium ion batteries and its device |
| CN102624017A (en) * | 2012-03-22 | 2012-08-01 | 清华大学 | Battery energy storage system peak clipping and valley filling real-time control method based on load prediction |
| DE102013113951A1 (en) * | 2013-01-31 | 2014-07-31 | GM Global Technology Operations LLC | A method of detecting open circuit voltage shifts by optimization by adjusting the anode electrode half cell voltage waveform |
| WO2014185163A1 (en) * | 2013-05-16 | 2014-11-20 | 日本電気株式会社 | Cell state-maintaining device, cell state management system, cell, method for maintaining cell state, and program |
| CN103592579A (en) * | 2013-07-30 | 2014-02-19 | 中国电力科学研究院 | Impulse discharge voltage calculating model construction method |
| CN104657520A (en) * | 2013-11-18 | 2015-05-27 | 国家电网公司 | Battery modeling method based on large capacity energy accumulation lithium ion battery |
| CN104749529A (en) * | 2015-04-01 | 2015-07-01 | 上海理工大学 | Calibration method of charge and discharge characteristics of lithium battery and charge and discharge characteristics calibration apparatus |
| CN105677979A (en) * | 2016-01-07 | 2016-06-15 | 北京北交新能科技有限公司 | Lithium titanate battery improvement model based on Butler-Volmer equation |
| US20170212170A1 (en) * | 2016-01-21 | 2017-07-27 | Yokogawa Electric Corporation | Secondary battery capacity measuring system and secondary battery capacity measuring method |
| CN106997028A (en) * | 2017-05-19 | 2017-08-01 | 江苏大学 | A kind of battery differential voltage and incremental capacity plot Efficient Solution method |
Non-Patent Citations (1)
| Title |
|---|
| 张彩萍 等: "用基于遗传优化的扩展卡尔曼滤波算法辨识电池模型参数", 《吉林大学学报（工学版）》 * |
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