CN106908728B - A kind of soc optimization method based on Maximum-likelihood estimation - Google Patents
A kind of soc optimization method based on Maximum-likelihood estimation Download PDFInfo
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- CN106908728B CN106908728B CN201710029964.2A CN201710029964A CN106908728B CN 106908728 B CN106908728 B CN 106908728B CN 201710029964 A CN201710029964 A CN 201710029964A CN 106908728 B CN106908728 B CN 106908728B
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- 238000000034 method Methods 0.000 title claims abstract description 26
- 238000007476 Maximum Likelihood Methods 0.000 title claims abstract description 13
- 238000005457 optimization Methods 0.000 title claims abstract description 7
- 230000010354 integration Effects 0.000 claims abstract description 10
- 238000007599 discharging Methods 0.000 claims abstract description 4
- 238000012545 processing Methods 0.000 claims description 4
- 238000009795 derivation Methods 0.000 claims description 2
- 239000000446 fuel Substances 0.000 claims description 2
- 238000012360 testing method Methods 0.000 abstract description 3
- 238000009825 accumulation Methods 0.000 abstract description 2
- 238000005259 measurement Methods 0.000 abstract description 2
- 238000004422 calculation algorithm Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
Classifications
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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]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
- G01R31/3828—Arrangements for monitoring battery or accumulator variables, e.g. SoC using current integration
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- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Secondary Cells (AREA)
- Tests Of Electric Status Of Batteries (AREA)
Abstract
The invention belongs to technical field of battery management, specially a kind of soc optimization method based on Maximum-likelihood estimation.Current integration method is suitable for various batteries, but the accumulation of error will be made by error once occur.Maximum-likelihood estimation is a kind of probability theory in statistical application, is one of method of parameter Estimation.Parameter Estimation is by testing several times, and observation is as a result, release the value of parameter using result.The present invention estimates battery charging and discharging beginning on the basis of being based on ampere-hour integration method to reduce actual error；It is directed to the estimation of its parameter using Maximum-likelihood estimation, to make it have higher accuracy, makes the value of measurement closer to exact value, true value can be further reacted in practice, brings convenience to use.
Description
Technical field
The invention belongs to technical field of battery management, the soc being related in battery management system is specially a kind of based on very big
The soc optimization method of possibility predication.
Background technique
Battery management system is to the methods of the existing internal resistance Fa ﹑ open circuit voltage method of the calculation method of soc and current integration method.
The defect of internal resistance method is influenced by temperature very greatly, and when battery is in different state of charge, its internal resistance
It is worth different；Battery is under different service life states, its internal resistance value is also different, so measuring soc using internal resistance method
It is relatively difficult.
The shortcomings that open circuit voltage method is exactly that long time is needed to stand, and such battery terminal voltage can be only achieved stationary value,
Accurate soc value can be just estimated using stable open-circuit voltage, be suitable only for automobile in this way and stayed for a long time
Car state.
Current integration method is a kind of open-loop prediction, it is tried out in various batteries.But there are current integrations in algorithm, so
As the increase of automobilism time can generate error, and error gradually accumulates, and deviates estimated value more and more correctly
Soc value.
For current battery management system, the use scope of current integration method is and simple and clear than wide；
But current error affects the use of this method, and the precision for improving electric current becomes problem to be solved.
Summary of the invention
For above-mentioned there are problem or deficiency, to solve current error technical problem, the present invention provides one kind to be based on pole
The soc optimization method of maximum-likelihood estimation.
A kind of soc optimization method based on Maximum-likelihood estimation, comprising the following steps:
Step 1, with single order RC model to fuel cell modelling, obtain end voltage output equation when electric discharge:
V=Voc-IRe-IRs(1-e-t/τ) (1)
τ is timeconstantτ=RsC,VocIt is open-circuit voltage, ReIt is the Ohmic resistance of battery, Rs﹑ C is dynamic for simulated battery
The time constant showed in step response.
As t → 0, R can be obtainede=(Voc- V)/I, in this period of battery stable region when electric discharge since battery
Measure V1﹑ V2﹑ I, to obtain Re=(V1-V2)/I。
For RsFor, there is one stable discharging period can be according to formula R when constant-current discharges=Voc-V/I-Re?
It arrives.
It can be obtained by formula 1:
Step 2 enables F (t)=1-e-t/τ, the τ of λ=1/ is enabled in f (t), can be obtained:
F (t)=1-e-λt (3)
Density function is obtained according to the exponential distribution of probability:
F (t)=λ e-λt (4)
Step 3, using Maximum Likelihood Estimation processing parameter λ:
Derivation is carried out to formula 5 and enables functional value to be 0, is obtained:
Step 4 later brings formula 2 in current integration method into all parameter processings are complete, finally acquires the value of soc.
Maximum-likelihood estimation is a kind of probability theory in statistical application, is one of method of parameter Estimation.Parameter Estimation
It is by testing several times, observation is as a result, release the value of parameter using result.
Current integration method is suitable for various batteries, but the accumulation of error will be made by error once occur.Maximum-likelihood estimation,
It is a kind of probability theory in statistical application, is one of method of parameter Estimation.Parameter Estimation is observed by testing several times
As a result, releasing the value of parameter using result.
The present invention starts portion to battery charging and discharging on the basis of being based on ampere-hour integration method to reduce actual error
Divide and is estimated；It is directed to the estimation of its parameter using Maximum-likelihood estimation, to make it have higher accuracy, makes measurement
It is worth closer to exact value, true value can be further reacted in practice, brings convenience to use.
In conclusion the present invention compared with the prior art, ensure that while convenience, the precision of electric current is improved.
Detailed description of the invention
Fig. 1 is single order RC model schematic.
Specific embodiment
Claims (1)
1. a kind of soc optimization method based on Maximum-likelihood estimation, comprising the following steps:
Step 1, with single order RC model to fuel cell modelling, obtain end voltage output equation when electric discharge:
V=Voc-IRe-IRs(1-e-t/τ) (1)
τ is timeconstantτ=RsC,VocIt is open-circuit voltage, ReIt is the Ohmic resistance of battery, Rs﹑ C is special for simulated battery dynamic
The time constant showed in property；
As t → 0, R can be obtainede=(Voc- V)/I, to measuring in this period of battery stable region when electric discharge since battery
V1﹑ V2﹑ I, to obtain Re=(V1-V2)/I；
For RsFor, constant-current discharge stable discharging period according to formula Rs=(Voc-V)/I-ReIt obtains；
It can be obtained by formula (1):
Step 2 enables F (t)=1-e-t/τ, the τ of λ=1/ is enabled in f (t), can be obtained:
F (t)=1-e-λt (3)
Density function is obtained according to the exponential distribution of probability:
F (t)=λ e-λt (4)
Step 3, using Maximum Likelihood Estimation processing parameter λ:
Derivation is carried out to formula (5) and enables functional value to be 0, is obtained:
For the average value of measuring section；
Step 4 later brings formula (2) in current integration method into all parameter processings are complete, finally acquires the value of soc
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| CN107505574A (en) * | 2017-08-08 | 2017-12-22 | 中华人民共和国成都出入境检验检疫局 | The UKF lithium battery evaluation methods with fading factor based on maximum likelihood |
| CN111976542B (en) * | 2020-09-01 | 2022-06-14 | 广东高标电子科技有限公司 | SOC estimation method and device for lead-acid battery of electric vehicle |
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| CN102169168B (en) * | 2011-05-17 | 2013-04-24 | 杭州电子科技大学 | Battery dump energy estimation method based on particle filtering |
| JP5875037B2 (en) * | 2011-07-08 | 2016-03-02 | インターナショナル・ビジネス・マシーンズ・コーポレーションＩｎｔｅｒｎａｔｉｏｎａｌ Ｂｕｓｉｎｅｓｓ Ｍａｃｈｉｎｅｓ Ｃｏｒｐｏｒａｔｉｏｎ | Battery state prediction system, method and program |
| CN105203969B (en) * | 2015-10-23 | 2018-04-13 | 南昌航空大学 | State-of-charge method of estimation based on modified RC battery models |
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