CN110261778A - A kind of lithium ion battery SOC estimation algorithm - Google Patents
A kind of lithium ion battery SOC estimation algorithm Download PDFInfo
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Abstract
The invention discloses a kind of lithium ion battery SOC estimation algorithms, key step includes establishing Li-ion battery model, the relationship of SOC-OCV is determined using electric discharge settled process, battery model initial parameter is estimated under off-line state, battery model parameter identification is carried out using with genic least square method under presence, observes SOC using state observer.The genic least square method of inventive algorithm inventive algorithm junction belt carries out real-time parameter identification and state observer carries out SOC observation, it realizes simple, it is practical, it is computationally intensive by solving traditional Kalman filter using state observer, it is difficult to using practical problem, and it ensure that the accuracy of lithium ion battery estimation algorithm by state observer, estimation precision is high.
Description
Technical field
The present invention relates to battery charge state (SOC) to estimate field, and in particular to a kind of lithium ion battery SOC estimation calculation
Method.
Background technique
Power battery, as the main energy sources of electric car, its SOC is most important in energy management system and most base
One of parameter of plinth；Only accurate SOC value estimation just can be carried out reasonable energy distribution, thus more effectively using limited
The energy；Also can correctly predicted vehicle remaining driving mileage.The definition of SOC is the state-of-charge of battery, it is used to indicate that electricity
The remaining capacity in pond.Accurate battery charge state is to carry out electric car energy system administration premise and prerequisite.Battery is one
The nonlinear system of a complexity, when being used for electric vehicle, because electronic equipment is various, noise jamming is complicated, it is difficult to obtain accurately
Noise statistics；In addition external environment and internal environment Parameters variation randomness, keep system mathematic model not accurate enough, generate model
Error, it is therefore necessary to the anti-interference ability and adaptive ability of battery charge state estimation be studied, the Shandong of estimation is improved
Validity of the stick to battery charge state.
In current existing SOC estimation method, the Ah counting method accumulated error easy to form based on Current integrating method；Base
In the open circuit voltage method and emf method of battery terminal voltage measurement, battery is needed to stand for a long time, it can not real-time estimation SOC
Value；Neural network based on great amount of samples data and neural network model needs to provide with a large amount of data sample for foundation
Reliable training method；Kalman filter method based on battery status spatial model and recurrence equation, it is computationally intensive, actually answer
With difficulty.
Summary of the invention
Goal of the invention: providing a kind of lithium ion battery SOC estimation algorithm, solves conventional lithium ion battery SOC estimation algorithm
Computationally intensive, estimation precision is low, realizes difficult problem.
Technical solution: a kind of lithium ion battery SOC estimation algorithm mainly comprises the steps that
Step 1: establishing Dai Weinan Li-ion battery model；
Step 2: the relationship of SOC-OCV is determined using intermittent discharge settled process；
Step 3: battery model initial parameter is estimated under off-line state；
Step 4: carrying out the identification of battery model parameter under presence with genic least square method；
Step 5: observing SOC using state observer.
According to an aspect of the present invention, second order Dai Weinan Li-ion battery model is established, open-circuit voltage E (t) table is used
Show that voltage source, R indicate the Ohmic resistance of battery, use the polarization process of second order capacitance-resistance loop simulated battery.
According to an aspect of the present invention, the relationship of SOC-OCV is determined using intermittent discharge settled process, it is first that battery is complete
100%SOC is charged to entirely, secondly, using negative arteries and veins under every 10%SOC, current versus cell discharges, and then static 1h is to eliminate
Polarization reaction seeks average value when standing finally to obtain SOC-OCV curve, and impulse discharge current is set as C/2, when discharging
Between width correspond to a certain amount of charge, i.e. 10%SOC.
According to an aspect of the present invention, battery model initial parameter is estimated under off-line state, after electric discharge
The process that the pressure drop generated on inside battery Ohmic resistance disappears, can obtain battery ohmic internal resistance:
,
To export electric current, the polarization process of simulated battery, C in such a way that two capacitance-resistance links are superimposedsAnd RsThe RC of composition is simultaneously
It is smaller to join circuit time constant, for the process of quick changes in voltage of the simulated battery in current break, CpAnd RpParallel circuit
Larger, slowly varying for the analog voltage process of time constant, it is assumed that battery first discharge during (t0-tr) one section when
Between, then remaining time is in static condition, wherein t0For start time of discharging, tdFor stop timing of discharging, trStop to stand
Time, the in the process network RC voltage are as follows:
T is time variable, is enabled,, it is the time constant of two RC parallel circuits, by the pole of battery
Change voltage change process voltage output caused by reaction disappears are as follows:
,
E is voltage source, and I is output electric current, and the several Coefficient Fittings of two fingers can be carried out with Matlab, are recognizedR s 、R p 、C S 、C PValue.
According to an aspect of the present invention, battery model parameter is carried out with genic least square method under presence
Identification, equivalent-circuit model functional relation is as follows:
E(t) it is voltage source, U(t) it is open-circuit voltage, i is output electric current, and t is time variable, by with genic minimum
The recursive operation of square law can obtain equation such as following formula:
The more and more recursion results that will lead to of least square method legacy data during recursive operation cannot the good new number of reaction
According to characteristic introduce forgetting factor λ to avoid such case, k is the number of iterations,For parameter matrix estimated by system, Φ
For calculation matrix, P is covariance matrix,KFor gain feedback matrix, yFor system true output.
According to an aspect of the present invention, SOC, the state equation of state observer and output are observed using state observer
Equation such as following formula:
Wherein,=[u p u s SOC] T , u=I, A= ,B=[1/C p 1/C s -1/Q n ] T , )= E(soc)-u p -u s ,D=R 0 ,KFor gain feedback matrix,To export observation,yFor system true output, QnFor etc. compare number
Column common ratio.
The utility model has the advantages that the present invention can by with genic least square method carry out battery model parameter identification,
Reinforce the information content that new data provide, gradually weakens old data, data is prevented to be saturated；State observer is easy real simultaneously
Existing, calculation amount is small compared with Kalman filter, and estimation precision is high.
Detailed description of the invention
Fig. 1 is new road damage detection system structure of the invention.
Fig. 2 is second order Dai Weinan Li-ion battery model figure.
Fig. 3 is intermittent discharge current graph.
Fig. 4 is intermittent discharge voltage pattern.
Fig. 5 is that lithium ion battery puts an end voltage response curves schematic diagram.
Fig. 6 is SOC observation experiment result figure.
Specific embodiment
Inventive algorithm is described further with reference to the accompanying drawing.
As shown in Figure 1, illustrating SOC estimation algorithm detailed step.
As shown in Fig. 2, establishing second order Dai Weinan Li-ion battery model, voltage source, R table are indicated using open-circuit voltage E (t)
The Ohmic resistance for showing battery uses the polarization process of second order capacitance-resistance loop simulated battery.
As shown in Figure 3 and Figure 4, abscissa is the time, and the ordinate of Fig. 3 is discharge current, and the ordinate of Fig. 4 is open circuit electricity
Pressure, the relationship of SOC-OCV is determined using intermittent discharge settled process, first that battery is fully charged to 100%SOC, secondly, often
Negative arteries and veins is used under 10%SOC.Current versus cell discharges, and then static 1h finally asks putting down when standing to eliminate polarization reaction
Mean value is to obtain SOC-OCV curve.Impulse discharge current is set as C/2, and discharge time width corresponds to a certain amount of charge,
That is 10%SOC.
As shown in figure 5, (V1-V0) it is the process that the pressure drop generated on inside battery Ohmic resistance after discharging disappears, by
This can obtain battery ohmic internal resistance:
To export electric current, the polarization process of simulated battery in such a way that two capacitance-resistance links are superimposed.As shown in Fig. 2, (V2-
V1) be quick changes in voltage of the battery in current break process because time constant is smaller, this process CsAnd RsComposition
RC parallel circuit simulation, (V3-V2) it is the slowly varying process of voltage, because time constant is larger, this process CpAnd RpAnd
Join breadboardin.
Assuming that for a period of time, then remaining time is in static condition to battery, wherein t for first electric discharge during (t0-tr)0For
It discharges start time, tdFor stop timing of discharging, trTo stand dwell time, the in the process network RC voltage are as follows:
T is time variable, is enabled,, it is the time constant of two RC parallel circuits, (V3-V1) stage
Voltage change is caused by being disappeared as the polarization reaction of battery, to export in this process voltage are as follows:
,
E is voltage source,To export electric current, the several Coefficient Fittings of two fingers can be carried out with Matlab, are recognizedR s 、R p 、C S 、C PValue.
As shown in Fig. 2, it is as follows to obtain equivalent-circuit model functional relation:
E(t) be voltage source, U(t) be open-circuit voltage values, i be output electric current, t is time variable, by with it is genic most
The recursive operation of small square law can obtain equation such as following formula:
The more and more recursion results that will lead to of least square method legacy data during recursive operation cannot the good new number of reaction
According to characteristic introduce forgetting factor to avoid such caseλ, k is the number of iterations,For parameter matrix estimated by system, Φ
For calculation matrix, P is covariance matrix,KFor gain feedback matrix, yFor system true output.
State equation and the output equation such as following formula of state observer:
Wherein,=[ u p u s SOC ] T ,u=I,A= ,B=[1/C p 1/C s -1/Q n ] T , )=E (soc)-u p -u s ,D=R 0 ,KFor gain feedback matrix,To export observation,yFor system true output, QnFor Geometric Sequence
Common ratio.
Experimental result picture is as shown in Figure 6, the results showed that follows well, SOC calculating error is small.
In short, the invention has the following advantages that the genic least square method of inventive algorithm junction belt carries out battery
The identification of model parameter reinforces the information content that new data provide, gradually weakens old data, data is prevented to be saturated；Shape simultaneously
State observer carries out SOC observation, and easy to accomplish, calculation amount is small compared with Kalman filter, and estimation precision is high.
It is further to note that specific technical features described in the above specific embodiments, in not lance
In the case where shield, it can be combined in any appropriate way.In order to avoid unnecessary repetition, the present invention to it is various can
No further explanation will be given for the combination of energy.
Claims (6)
1. a kind of lithium ion battery SOC estimation algorithm, which is characterized in that mainly comprise the steps that
Step 1: establishing Dai Weinan Li-ion battery model；
Step 2: the relationship of SOC-OCV is determined using intermittent discharge settled process；
Step 3: battery model initial parameter is estimated under off-line state；
Step 4: carrying out the identification of battery model parameter under presence with genic least square method；
Step 5: observing SOC using state observer.
2. a kind of lithium ion battery SOC estimation algorithm according to claim 1, which is characterized in that the lithium in the step 1
Ion battery model is that second order wears Vernam model, indicates that voltage source, R indicate the Ohmic resistance of battery using open-circuit voltage E (t),
Use the polarization process of second order capacitance-resistance loop simulated battery.
3. a kind of lithium ion battery SOC estimation algorithm according to claim 1, which is characterized in that the step 2 for
The relationship of SOC-OCV uses intermittent discharge settled process, first that battery is fully charged to 100%SOC, secondly, under every 10%SOC
Using negative arteries and veins, current versus cell discharges, and then static 1h finally asks average value when standing to obtain to eliminate polarization reaction
SOC-OCV curve, impulse discharge current are set as C/2, discharge time width corresponds to a certain amount of charge, i.e., 10%
SOC。
4. a kind of lithium ion battery SOC estimation algorithm according to claim 1, which is characterized in that the step 3 is offline
The initial parameter for calculating battery model under state using voltage response curves after battery intermittent discharge, using two capacitance-resistance rings
Save the polarization process of the mode simulated battery of superposition, setup parameter Rs、CsFor the resistance and capacitor of a capacitance-resistance link, setting ginseng
Number Rp、CpFor the resistance and capacitor of another capacitance-resistance link, the several Coefficient Fittings of two fingers can be carried out with Matlab, recognizedR s 、R p 、 C s 、C pValue, CsAnd RsThe RC parallel circuit time constant of composition is smaller, fast for voltage of the simulated battery in current break
The process of speed variation, CpAnd RpThe time constant of parallel circuit is larger, the process slowly varying for analog voltage, it is assumed that battery
It first discharges a period of time in period, then remaining time is in static condition, in the process the network RC voltage are as follows:
Wherein t0For start time of discharging, tdFor stop timing of discharging, trTo stand dwell time respectively, t is time variable, is enabled,, it is the time constant of two RC parallel circuits, voltage during the polarization reaction of battery disappears
Output are as follows:
,
Wherein E is voltage source,To export electric current.
5. a kind of lithium ion battery SOC estimation algorithm according to claim 1, which is characterized in that the step 4 is in online
Using the identification for carrying out battery model parameter with genic least square method under state, equivalent-circuit model functional relation is such as
Under:
E(t) be voltage source, U(t) be open-circuit voltage values, i be output electric current, t is time variable, by with it is genic most
The recursive operation of small square law can obtain equation such as following formula:
The more and more recursion results that will lead to of least square method legacy data during recursive operation cannot the good new number of reaction
According to characteristic introduce forgetting factor λ to avoid above situation, k is the number of iterations,For parameter matrix estimated by system, Φ
For calculation matrix, P is covariance matrix,KFor gain feedback matrix, yFor system true output.
6. a kind of lithium ion battery SOC estimation algorithm according to claim 1, which is characterized in that the step 5 utilizes shape
State observer is observed SOC value, state equation and the output equation such as following formula of state observer:
Wherein,=[ u p u s SOC ] T ,U=I, A=,B=[ 1/C p 1/C s -1/Q n ] T , )= E(soc)-u p -u s ,D=R 0 ,KFor gain feedback matrix,To export observation,yFor system true output, QnFor Geometric Sequence
Common ratio.
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| CN111308371A (en) * | 2019-11-29 | 2020-06-19 | 湖南海博瑞德电智控制技术有限公司 | Lithium ion battery state of charge estimation method |
| CN112147514A (en) * | 2020-09-25 | 2020-12-29 | 河南理工大学 | RLS-based lithium battery all-condition self-adaptive equivalent circuit model |
| CN112373346A (en) * | 2020-12-01 | 2021-02-19 | 国网智慧能源交通技术创新中心(苏州)有限公司 | Refinement control method for matrix V2G pile |
| CN112415391A (en) * | 2020-10-27 | 2021-02-26 | 中船动力有限公司 | Marine lithium ion battery parameter identification method based on improved particle swarm optimization |
| CN112782586A (en) * | 2020-11-12 | 2021-05-11 | 上海空间电源研究所 | Lithium ion battery capacity estimation method and system based on actual local data |
| CN112946480A (en) * | 2021-01-28 | 2021-06-11 | 中国矿业大学 | Lithium battery circuit model simplification method for improving SOC estimation real-time performance |
| CN113176505A (en) * | 2021-04-30 | 2021-07-27 | 重庆长安新能源汽车科技有限公司 | On-line estimation method and device for state of charge and state of health of vehicle-mounted power battery and storage medium |
| CN116381513A (en) * | 2023-06-07 | 2023-07-04 | 广东电网有限责任公司东莞供电局 | Lithium ion battery model parameter robust identification method considering measured value abnormality |
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| CN113176505A (en) * | 2021-04-30 | 2021-07-27 | 重庆长安新能源汽车科技有限公司 | On-line estimation method and device for state of charge and state of health of vehicle-mounted power battery and storage medium |
| CN113176505B (en) * | 2021-04-30 | 2022-10-04 | 重庆长安新能源汽车科技有限公司 | On-line estimation method and device for state of charge and state of health of vehicle-mounted power battery and storage medium |
| CN116381513A (en) * | 2023-06-07 | 2023-07-04 | 广东电网有限责任公司东莞供电局 | Lithium ion battery model parameter robust identification method considering measured value abnormality |
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