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CN104678316B - Charge states of lithium ion battery evaluation method and device - Google Patents

Charge states of lithium ion battery evaluation method and device Download PDF

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Publication number
CN104678316B
CN104678316B CN201510090685.8A CN201510090685A CN104678316B CN 104678316 B CN104678316 B CN 104678316B CN 201510090685 A CN201510090685 A CN 201510090685A CN 104678316 B CN104678316 B CN 104678316B
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lithium ion
ion battery
charge
soc
state
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CN104678316A (en
Inventor
姜久春
张彩萍
赵婷
张维戈
王占国
龚敏明
吴健
孙丙香
时玮
李雪
牛利勇
李景新
黄彧
黄勤河
鲍谚
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BEIJING BEIJIAO NEW ENERGY TECHNOLOGY CO., LTD.
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Beijing Jiaotong University
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Abstract

A kind of charge states of lithium ion battery evaluation method and device.Methods described includes step:A, the open-circuit voltage and state-of-charge relation for being fitted lithium ion battery;B, utilize observer method estimation charge states of lithium ion battery;C, the charge states of lithium ion battery for being estimated in step B, if greater than predetermined threshold, then using observer method estimation charge states of lithium ion battery, if less than predetermined threshold, then estimate charge states of lithium ion battery using current integration method.By the charge states of lithium ion battery evaluation method and device of the present invention, the shortcoming of current integration method and observer method can be avoided, high estimation precision is provided in life cycle management, full state-of-charge region.

Description

Charge states of lithium ion battery evaluation method and device
Technical field
The present invention relates to energy storage device technical field, the state-detection skill of rechargeable lithium ion batteries is especially related to Art.
Background technology
United States advanced battery federation (U.S.Advanced Battery Consortium, USABC) is at it《Electronic vapour Car Cell Experimentation An handbook》The middle state-of-charge (State of Charge, SOC) by battery is defined as dump energy to be held with actual The percentage of amount.The estimation of battery SOC becomes increasingly necessary in the application field of electric automobile and intelligent grid, electrokinetic cell SOC be used to reflect battery remaining available power situation, the work of conventional fuel oil automobile oil gauge is played for electric automobile With accurate reliable SOC estimation can not only strengthen handling and comfort level of the user to electric automobile, while its conduct The indispensable decision factor of electric automobile energy management system, is also the management of optimization electric automobile energy, improves battery capacity With capacity usage ratio, prevent battery overcharge and overdischarge, ensure battery security in use and service life Important parameter.
For pure electric automobile, battery management system is an important component in electric automobile, and estimation on line goes out The state-of-charge of battery is one of key issue of battery management system.In the prior art, the evaluation method for SOC includes opening Road voltage method, current integration method, internal resistance method, neutral net and Kalman filtering method etc., wherein one of most simple, conventional method It is current integration method.
So-called current integration method, refers to if discharge and recharge initial state is designated as SOC0, then the SOC of current state is:Wherein CNFor lithium ion battery rated capacity, I is lithium ion battery electric current, and η is discharge and recharge Efficiency.If current measurement is forbidden in current integration method application, SOC calculation errors will be caused, long term accumulation, error is increasing; In addition, current integration method needs to consider lithium ion battery efficiency for charge-discharge, and in the violent situation of the condition of high temperature and current fluctuation Under, error is larger.
In addition to current integration method, also some other conventional lithium ion battery SOC estimation method:Open circuit voltage method, electricity Chemical test, neural network, impedance spectrum method, Kalman filter method and based on sliding mode observer, Long Beige observe The evaluation method based on observer such as device, but all there is limitation:Open circuit voltage method is needed lithium ion battery sufficient standing, no Estimation on line can be met;Electrochemical method needs special test equipment to support;Neutral net needs lot of experiments and data to train, And the adaptivity of model has certain limit;Impedance Analysis is influenceed by factors such as temperature and agings;Kalman filtering It is difficult to eliminate due to the error that lithium ion battery temperature and aging cause model and its parameter Self-variation to bring.
Lithium ion battery SOC estimation method based on observer be by output of process amount come estimated state amount, and add Enter the error feedback of output quantity, current integration method estimation lithium ion battery SOC is modified, current integration method error is overcome Accumulate and need to know the shortcoming of lithium ion battery SOC initial values, greatly improve lithium ion battery SOC estimation precision, but should The accuracy of method estimation is ensured by the accuracy of model parameter, needs to realize that Li-ion battery model is joined in practical application Several on-line identification;Further, since the characteristic (open-circuit voltage-dump energy curve etc.) of lithium ion battery in itself causes lithium ion The estimation of battery SOC error in certain interval is larger.
The content of the invention
In consideration of it, it is an object of the invention to overcome the current integration method of prior art to need to know lithium ion battery SOC initial values, and there is larger accumulated error, the SOC estimation method based on observer lacks partial section error is larger Fall into, by the two new SOC estimation method of composition that combines.
In order to realize this purpose, the technical scheme that the present invention takes is as follows.
A kind of charge states of lithium ion battery evaluation method, methods described includes step:
A, the open-circuit voltage and state-of-charge relation for being fitted lithium ion battery;
B, utilize observer method estimation charge states of lithium ion battery;
C, the charge states of lithium ion battery for being estimated in step B, if greater than predetermined threshold, then using observer Method estimates charge states of lithium ion battery, if less than predetermined threshold, then estimates lithium ion battery lotus using current integration method Electricity condition.
Wherein described predetermined threshold is:Lithium ion according to corresponding to open-circuit voltage and state-of-charge relation derivative minimum value Battery charge state value.
In addition, the open-circuit voltage of lithium ion battery is fitted in step A to be included with state-of-charge relation:
A1, the terminal voltage of collection lithium ion battery, lithium ion battery charge or discharge electric current, lithium ion under identification operating mode The ratio of battery charging and discharging ampere-hour number and capacity;
A2, the collection capacity using step A1, recognize the ohmic internal resistance of lithium ion battery, polarization resistance, polarization capacity and The coefficient of open-circuit voltage and state-of-charge fit correlation.
In addition, open-circuit voltage OCV and state-of-charge s fit correlation are:
OCV=f (s)=a+b (- ln (s))α+ cs+dexp (s),
Wherein α is provisional index,
Correspondingly, the coefficient of the open-circuit voltage and state-of-charge fit correlation is a, b, c and d.
On the other hand, the identification operating mode is:A number of sample lithium ion battery is taken, by sample lithium ion battery State-of-charge charge or discharge are to median, according to I1, I2, I3... Ik..., IN,-I1,-I2,-I3...-Ik... ,-INAmpere Electric current carry out the charge and discharge of equal time distances, and the number of pre-determined number is gathered according to step A1 in each time interval According to.
Or the identification operating mode is:A number of sample lithium ion battery is taken, by the charged of sample lithium ion battery State charge or discharge are to median, according to I1,-I1, I2,-I2, I3,-I3... Ik,-Ik..., IN,-INThe electric current of ampere is carried out The charge and discharge of equal time distances, and the data of pre-determined number are gathered according to step A1 in each time interval.
Recognize the ohmic internal resistance of lithium ion battery in the step A2, polarization resistance, polarization capacity and open-circuit voltage with The method of the coefficient of state-of-charge fit correlation is:
With the terminal voltage collected, lithium ion battery charge or discharge electric current, lithium ion battery discharge and recharge ampere-hour number with holding The ratio of amount constitutes input matrix Φ (1) as mode input by mathematical operation, and Φ (2) ... Φ (n), wherein n are total Data acquisition number of times;
Iteration, recognizes ohmic internal resistance, polarization resistance, polarization capacity and the open circuit electricity of lithium ion battery in such a way Pressure and the coefficient of state-of-charge fit correlation:
P (0)=CI
Wherein C is arbitrary constant,For the ohmic internal resistance of the lithium ion battery in kth time iteration, polarization resistance, polarization The vector that the coefficient of electric capacity and open-circuit voltage and state-of-charge fit correlation is constituted, total iterations is n, and λ is forgetting factor, Value is between 0 to 1, and Y (k) is the terminal voltage value of lithium ion battery in kth time iteration.
The charge states of lithium ion battery evaluation method samples sample lithium ion battery, discharge and recharge in life-cycle region Range of measuring temp is between 0 DEG C -45 DEG C.
Device is estimated present invention additionally comprises a kind of charge states of lithium ion battery, described device includes:
Open-circuit voltage fitting unit, open-circuit voltage and state-of-charge relation for being fitted lithium ion battery;
Observer evaluation unit, charge states of lithium ion battery is estimated using observer method;
Ampere-hour integrates evaluation unit, and charge states of lithium ion battery is estimated using current integration method;
Controller, for the charge states of lithium ion battery estimated for observer evaluation unit, if greater than predetermined Threshold value, then using observer evaluation unit estimation charge states of lithium ion battery, if less than predetermined threshold, then accumulated using ampere-hour Divide evaluation unit estimation charge states of lithium ion battery.
Wherein, the controller includes threshold value determination unit, and the threshold value determination unit is according to state-of-charge and open circuit electricity The corresponding SOC of pressure relation derivative minimum value, is used as predetermined threshold.
By the charge states of lithium ion battery evaluation method and device of the present invention, current integration method and observation can be avoided The shortcoming of device method, high estimation precision is provided in full state-of-charge region.
In addition, by the charge states of lithium ion battery evaluation method and device of the present invention, applicable ampere-hour product can be found The optimal separation of point-score and observer method, it is to avoid simply chosen using empirical method, so can further improve and estimate The precision of calculation.
In addition, in the present invention by way of iteration, the ohmic internal resistance of lithium ion battery, polarization resistance, polarization are picked out The coefficient of electric capacity and open-circuit voltage and state-of-charge fit correlation, so can accurately know lithium ion battery parameter, it is to avoid In observer method due to lithium ion battery parameter it is inaccurate caused by mistake.
OCV-SOC relation fit approach precision in the present invention is high, the OCV-SOC in whole SOC intervals with reality Curve, which has, higher agrees with degree.
In addition, different identification operating modes are devised in the present invention, for different temperatures, different lithium ion cells type, difference The lithium ion battery of capacity is tested and data acquisition, so expands charge states of lithium ion battery estimation side of the present invention The application of method.Especially for the lithium ion battery state-of-charge estimation of life cycle management, evaluation method of the invention The precision of prior art can be significantly improved with device, with good technique effect.
Brief description of the drawings
Fig. 1 is the schematic diagram of embodiment of the present invention on-line parameter identification operating mode.
Fig. 2 is to be directed to different temperatures, different type, the lithium ion battery OCV-SOC curve maps of different aging conditions.
Fig. 3 is the fitting precision schematic diagram of SOC-OCV functions in embodiment of the present invention.
Fig. 4 is the contrast signal of lithium ion battery terminal voltage true value, estimated value and terminal voltage estimation error under DST operating modes Figure.
Fig. 5 is the schematic flow sheet of parameter identification method in embodiment of the present invention.
Fig. 6 is the Method And Principle block diagram of observer estimation SOC in embodiment of the present invention.
Fig. 7 is the stepwise schematic views of lithium ion battery SOC-OCV curves in embodiment of the present invention.
Fig. 8 is the first derivative figure of lithium ion battery SOC-OCV function curves in embodiment of the present invention.
Fig. 9 is the second dervative figure of lithium ion battery SOC-OCV function curves in embodiment of the present invention.
Figure 10 is lithium ion battery SOC estimation method schematic flow sheet in embodiment of the present invention.
The SOC estimation method result schematic diagram that Figure 11 is DST operating modes under 25 degree, utilize observer and ampere-hour method to combine.
Embodiment
Below in conjunction with the accompanying drawings, the present invention is elaborated.
The detailed example embodiment of following discloses.However, concrete structure disclosed herein and function detail merely for the sake of The purpose of example embodiment is described.
It should be appreciated, however, that the present invention is not limited to disclosed particular exemplary embodiment, but covering falls into disclosure model Enclose interior all modifications, equivalent and alternative.In the description to whole accompanying drawings, identical reference represents identical member Part.
It will also be appreciated that term "and/or" includes one or more related listing any of item as used in this With all combinations.It will further be appreciated that when part or unit are referred to as " connecting " or during " coupled " to another part or unit, it Miscellaneous part or unit are can be directly connected or coupled to, or can also have intermediate member or unit.In addition, for describing Between part or unit other words of relation should understand in the same fashion (for example, " between " to " directly between ", " adjacent " is to " direct neighbor " etc.).
Figure 10 is the schematic flow sheet of lithium ion battery SOC estimation method in embodiment of the present invention.With reference to Figure 10, this hair Charge state estimation method includes in bright embodiment:A, the open-circuit voltage and SOC relations for being fitted lithium ion battery;B, utilize sight Survey device method estimation lithium ion battery SOC;C, the lithium ion battery SOC for being estimated in step B, if greater than predetermined threshold Value, then using observer method estimation lithium ion battery SOC, if less than predetermined threshold, then estimate lithium using current integration method Ion battery SOC.
Why to take with upper type, when being because of using observer method estimation lithium ion battery SOC, the lithium of use Ion battery model parameter, such as resistance or capacitance take fixed value, but the value and the parameter of SOC low sides in full SOC intervals Difference is larger, and the terminal voltage of the Li-ion battery model estimation of such SOC low sides is had than larger error, while SOC-OCV Relation curve is complicated in the Property comparison of SOC low sides.Such as Fig. 4 be ambulatory stress test (Dynamic Stress Test, DST) under operating mode lithium ion battery terminal voltage actual value, estimated value and terminal voltage estimation error contrast schematic diagram.From Fig. 4 It can be seen that:With the extension of time, lithium ion battery terminal voltage is gradually reduced in discharge process, and the actual end of lithium ion battery Voltage U and estimate U*Between gap it is increasing, illustrate that, in SOC low sides, the error of observer method is increasing.This is Because observer method estimation SOC is largely dependent upon lithium ion battery SOC-OCV relation curves and model parameter, for example The accuracy of resistance or electric capacity, such SOC low sides there is problem using observer method estimation SOC, therefore the present invention is implemented Lithium ion battery SOC estimation method in mode needs to combine both approaches:SOC upper regions using observer method come Estimation lithium ion battery SOC, SOC low region estimates lithium ion battery SOC using current integration method.
Therefore, by using the lithium ion battery SOC estimation method in embodiment of the present invention, observer side can be combined The advantage of method and current integration method, reaches the precision improvement in the full SOC intervals of lithium ion battery, relative to list of the prior art Pure use observer method or current integration method, all with obvious advantage.
How the predetermined threshold is determined, it may be considered that rule of thumb choose, such as when lithium ion battery SOC is less than 30% When consider carried out using current integration method estimate lithium ion battery SOC, can also be selected according to the characteristic of SOC-OCV relations Select.
For example in an embodiment of the invention, the corresponding lithium ion of SOC-OCV relation derivative minimum values is utilized SOC value of battery is used as the specific threshold, when the lithium ion battery SOC value that observer method is estimated is more than the certain threshold During value, using observer method, otherwise use current integration method instead to estimate lithium ion battery SOC.
Presently in connection with the principle and specific method of brief description of the drawings embodiment of above.Due to being estimated using observer method Lithium ion battery SOC is largely dependent upon Li-ion battery model parameter, especially dependent on SOC-OCV curve characteristics, Fig. 7 is the SOC-OCV relation curves of lithium ion battery, and the curve can substantially be divided into four sections:0%-6%SOC, 6%-32% SOC, 32%-60%SOC, 60%-100%SOC, as seen from Figure 7,0%-6%SOC voltage change ratios are larger, 6%- 32%SOC voltage curves slow down, and this stage curve is more complicated, may infer that lithium ion battery material there occurs in the interval More complicated phase transformation reaction;32%-60%SOC, 60%-100%SOC voltage change are the different straight line of two slope over 10, lithium from Sub- battery does not change in the high-end equilibrium potential amplification of SOC.
Therefore in some special segment (lithium ion battery SOC low sides logarithmic region and the characteristics of SOC-OCV relation curves Relative complex region) in, had using observer method estimation lithium ion battery SOC than larger estimation error;Due to logical Current integration method needs to be known a priori by lithium ion battery SOC initial values, there is accumulated error, and observer estimation is in certain journey These problems are solved on degree;It therefore, it can realize lithium by combining two methods of observer estimation and ampere-hour integral and calculating Ion battery SOC estimation:Estimated in SOC upper regions using observer evaluation method, SOC low regions are accumulated using ampere-hour Point-score, and the SOC critical nodes of two methods are foregoing specific threshold, the specific threshold can be based on analysis lithium ion electricity The SOC-OCV relation curves characteristic in pond judges.
OCV=f (SOC) relation curves of the Fig. 8 corresponding to Fig. 7, can by the figure to lithium ion battery SOC derivative curve Increased afterwards with finding out that OCV derivative value first reduces, i.e. the slope of SOC-OCV relations has minimum value.Can with reference to the analysis to Fig. 7 To judge, the SOC value corresponding to the minimum point of desirable SOC-OCV relation function derivatives is estimated as observer and current integration method SOC critical point is calculated, i.e., OCV function second dervatives as shown in Figure 9 are taken at the SOC value of 0 value.
Therefore, in the specific embodiment of the invention, the spy of the SOC-OCV relation curves of lithium ion battery has been used Point, carrys out accurate have selected using the separation between observer method and current integration method.Which further increases the present invention The precision of embodiment.
For the SOC-OCV relation curves in Fig. 6, a variety of approximating methods can be used, one in the present invention is specific real Apply in mode, it is proposed that a kind of method that mode of utilization iteration is fitted, by experiment show, this approximating method is obtained The SOC-OCV relations precision arrived is high, there is good implementation result.
For example in a detailed embodiment, SOC-OCV relation curves are fitted according to following SOC-OCV relational expressions.
Open-circuit voltage OCV and state-of-charge s fit correlation is:
OCV=f (s)=a+b (- ln (s))α+ cs+dexp (s),
Wherein α is provisional index, and value is 2.1 in a detailed embodiment, and those skilled in that art should be bright In vain, the provisional index can also be adjusted according to actual conditions, belong to protection scope of the present invention.
SOC-OCV relation curves are thus fitted by the adjustment to parameter a, b, c and d.
In a detailed embodiment, come fitting parameter a, b, c and d by way of iteration, and lithium ion is obtained The parameter of battery model, such as ohmic internal resistance, polarization resistance, polarization capacity.These parameters are meant that the one of lithium ion battery Various parameters in rank Dai Weining models.
For the acquisition of parameter a, b, c and d fitting, and ohmic internal resistance, polarization resistance, polarization capacity, below by It is referred to as the identification to ohmic internal resistance, polarization resistance, polarization capacity and parameter a, b, c and d, the ginseng of the specific embodiment of the invention The flow chart of number discrimination method is as shown in figure 5, specifically parameter identification method comprises the following steps:
Step A1, the terminal voltage of collection lithium ion battery, lithium ion battery charge or discharge electric current, lithium under identification operating mode The ratio of ion battery discharge and recharge ampere-hour number and capacity;
Step A2, the collection capacity using step A1, recognize ohmic internal resistance, polarization resistance, the polarization capacity of lithium ion battery And the coefficient of open-circuit voltage and state-of-charge fit correlation.
For example identification operating mode under acquire n data altogether, then with collect terminal voltage, lithium ion battery charging or put The ratio of electric current, lithium ion battery discharge and recharge ampere-hour number and capacity is as mode input, by mathematical operation composition input square Battle array Φ (1), Φ (2) ... ..., Φ (n).
At this moment it is iterated in such a way, has recognized ohmic internal resistance, polarization resistance, the polarization capacity of lithium ion battery And the coefficient of open-circuit voltage and state-of-charge fit correlation:
P (0)=CI
Wherein C is arbitrary constant,For the ohmic internal resistance of the lithium ion battery in kth time iteration, polarization resistance, polarization The vector that the coefficient of electric capacity and open-circuit voltage and state-of-charge fit correlation is constituted, total iterations is n, and λ is forgetting factor, Value is between 0 to 1, and Y (k) is the lithium ion battery terminal voltage that kth time is collected.
In one of the invention more specifically embodiment, forgetting factor λ values are 0.995.This is rule of thumb to choose Numerical value, the present invention is not restricted to this, and actually those skilled in that art can according to circumstances carry out forgetting factor value Selection, the realization of the specific embodiment of the invention can't be hindered.
In addition, described identification operating mode, can also be realized by specifically choosing mode, such as in a specific implementation In mode, identification operating mode is designed in the way of Fig. 1 (a), specifically the identification operating mode is:Take a number of sample Lithium ion battery, by the state-of-charge charge or discharge of sample lithium ion battery to median, according to I1, I2, I3... Ik..., IN,-I1,-I2,-I3...-Ik... ,-INThe electric current of ampere carries out the charge and discharge of equal time distances, is adopted in each time interval Collect the data of pre-determined number.Such as each time interval is 5 seconds, per second to take 1 time, then gathers 2N × 5 time data altogether.
In another embodiment, identification operating mode is designed in the way of Fig. 1 (b), it is specifically described to distinguish Knowing operating mode is:A number of sample lithium ion battery is taken, by the state-of-charge charge or discharge of sample lithium ion battery into Between be worth, according to I1,-I1, I2,-I2, I3,-I3... Ik,-Ik..., IN,-INThe electric current of ampere carries out filling, putting for equal time distances Electricity, the data of pre-determined number are gathered in each time interval.Such as each time interval is 5 seconds, per second to take 1 time, then adopts altogether Collect 2N × 5 time data.
Although proposing specific identification operating mode in two above embodiment, this is not intended to the present invention and is limited to this side Formula, actually those skilled in the art can design other identification operating modes.In order to ensure accuracy, guarantee charging is generally required It is identical with the ampere-hour number of discharge process.
After so passing through iterations for the iteration of total sampling number, identificationIn each parameter value, bag Include ohmic internal resistance, polarization resistance, polarization capacity and the open-circuit voltage of lithium ion battery and the coefficient of state-of-charge fit correlation A, b, c and d.
In order that obtaining lithium ion battery SOC estimation method of the invention has the broader scope of application, for sample lithium The selection of ion battery can select the lithium ion battery of different degree of agings as sample lithium ion battery, can also be in difference At a temperature of tested.
From Fig. 2 (a) as can be seen that under different temperatures situation between 0 DEG C -45 DEG C, SOC-OCV relation curves difference is not Greatly, therefore, lithium ion battery SOC estimation method of the invention can be applied under various temperature conditionss, especially, it is adaptable to 0 Between DEG C -45 DEG C.
From Fig. 2 (b) and Fig. 2 (c) as can be seen that for different types of lithium ion battery (A classes, B Li-like ions battery) With the lithium ion battery (capacity A, capacity B and capacity C) of different degree of agings, lithium ion battery SOC estimation method of the invention It can be applicable.
, can from figure shown in the SOC-OCV relation curves such as Fig. 3 (a) for being fitted obtained SOC-OCV relation curves and reality To find out, the matched curve has a small amount of error in SOC low sides and individual cells, and in SOC upper region, matched curve Almost it is completely superposed with actual curve, OCV fitting precision is all that comparison is high on overall SOC intervals.
From Fig. 3 (b) as can be seen that for three kinds of lithium ion batteries (capacity A, capacity B and capacity C) of different capabilities, intending Close obtained SOC-OCV relation curves and actual SOC-OCV relation curves meet above feature:In SOC low region, The error being fitted between obtained SOC-OCV relation curves and the SOC-OCV relation curves of reality is larger, and in the high-end of SOC Region, the error is smaller, and this show again the technique effect of the specific embodiment of the invention.
After having recognized SOC-OCV relations, the ohmic internal resistance of lithium ion battery, polarization resistance, polarization capacity, so that it may so that The SOC of lithium ion battery is estimated with observer method.
Estimate that the structured flowchart of lithium ion battery is as shown in Figure 6 using observer method.
Y in Fig. 6 is the terminal voltage of lithium ion battery,It is the actual terminal voltage y of lithium ion battery and lithium-ion electric Pool model calculates the terminal voltage obtainedBetween error, L is observer Error Gain matrix.Represent and estimate accordingly Evaluation.
Li-ion battery model in Fig. 6 uses single order Dai Weining models, therefore the terminal voltage and open circuit of lithium ion battery Relation between voltage OCV is:Y=OCV+Up+iRo
Wherein UpFor the voltage at polarization resistance or polarization capacity two ends in the single order Dai Weining models of lithium ion battery, and iRo For the voltage at lithium ion battery ohmic internal resistance two ends.
So the parameters relationship in observer method is:
Y=OCV+Up+iRo,
Wherein Rp,CpRespectively polarization resistance and polarization capacity, Q are the rated capacity of lithium ion battery, and UoFor lithium ion Battery terminal voltage lithium ion battery.
Lithium ion battery OCV evaluation methods based on the present invention, it can be deduced that 25 degree of lower DST operating modes, utilize observer side The lithium ion battery SOC estimation results that method and current integration method are combined, as shown in figure 11.As seen from the figure, in SOC upper regions, Because observer method estimation SOC initial values are 0%, and the actual initial values of SOC are 95%, i.e. SOC estimations have very big initial mistake Difference, and observer method estimation SOC needs preferably trace into SOC true value through adjustment after a while.From Figure 11 As can be seen that observer estimation is realized by 500s or so and preferably tracked, metastable estimation effect, lithium-ion electric are reached Error between pond SOC estimate and actual value is within positive and negative 3%, therefore the lithium ion battery SOC estimations of the present invention Method has higher estimation precision.
Also include in order to realize the lithium ion battery SOC estimation method of the present invention, in embodiment of the present invention a kind of lithium from Sub- battery SOC estimates device, and described device includes:
Open-circuit voltage fitting unit, open-circuit voltage and state-of-charge relation for being fitted lithium ion battery;
Observer evaluation unit, charge states of lithium ion battery is estimated using observer method;
Ampere-hour integrates evaluation unit, and charge states of lithium ion battery is estimated using current integration method;
Controller, for the charge states of lithium ion battery estimated for observer evaluation unit, if greater than predetermined Threshold value, then using observer evaluation unit estimation charge states of lithium ion battery, if less than predetermined threshold, then accumulated using ampere-hour Divide evaluation unit estimation charge states of lithium ion battery.
Especially, the controller includes threshold value determination unit, and the threshold value determination unit is fitted single according to open-circuit voltage The open-circuit voltage SOC corresponding with state-of-charge relation derivative minimum value that member is fitted, is used as predetermined threshold.
It should be noted that above-mentioned embodiment is only the present invention preferably embodiment, it is impossible to be understood as to this The limitation of invention protection domain, under the premise of without departing from present inventive concept, any minor variations done to the present invention and modification Belong to protection scope of the present invention.

Claims (6)

1. a kind of charge states of lithium ion battery evaluation method, methods described includes step:
A, the open-circuit voltage and state-of-charge relation for being fitted lithium ion battery;
B, utilize observer method estimation charge states of lithium ion battery;
C, the charge states of lithium ion battery for being estimated in step B, if greater than predetermined threshold, then using observer method Charge states of lithium ion battery is estimated, if less than predetermined threshold, then the charged shape of lithium ion battery is estimated using current integration method State;
The open-circuit voltage of lithium ion battery is fitted in step A to be included with state-of-charge relation:
A1, the terminal voltage of collection lithium ion battery, lithium ion battery charge or discharge electric current, lithium ion battery under identification operating mode The ratio of discharge and recharge ampere-hour number and capacity;
A2, the collection capacity using step A1, recognize ohmic internal resistance, polarization resistance, polarization capacity and the open circuit of lithium ion battery The coefficient of voltage and state-of-charge fit correlation;
It is described identification operating mode be:A number of sample lithium ion battery is taken, the state-of-charge of sample lithium ion battery is charged Or median is discharged to, according to I1, I2, I3... Ik..., IN,-I1,-I2,-I3...-Ik... ,-INThe electric current of ampere carries out phase The charge and discharge of constant duration, and the data of pre-determined number are gathered according to step A1 in each time interval.
2. the charge states of lithium ion battery evaluation method according to claim 1, it is characterised in that the predetermined threshold For:Charge states of lithium ion battery value according to corresponding to open-circuit voltage and state-of-charge relation derivative minimum value.
3. the charge states of lithium ion battery evaluation method according to claim 1, it is characterised in that open-circuit voltage OCV Fit correlation with state-of-charge s is:
OCV=f (s)=a+b (- ln (s))α+ cs+dexp (s),
Wherein α is provisional index,
Correspondingly, the coefficient of the open-circuit voltage and state-of-charge fit correlation is a, b, c and d.
4. the charge states of lithium ion battery evaluation method according to claim 1, it is characterised in that the identification operating mode For:A number of sample lithium ion battery is taken, by the state-of-charge charge or discharge of sample lithium ion battery to median, is pressed According to I1,-I1, I2,-I2, I3,-I3... Ik,-Ik..., IN,-INThe electric current of ampere carries out the charge and discharge of equal time distances, and root The data of pre-determined number are gathered in each time interval according to step A1.
5. the charge states of lithium ion battery evaluation method according to any one of claim 1 or 4, it is characterised in that institute The ohmic internal resistance that lithium ion battery is recognized in step A2 is stated, polarization resistance, polarization capacity and open-circuit voltage are intended with state-of-charge The method of the coefficient of conjunction relation is:
With the terminal voltage collected, lithium ion battery charge or discharge electric current, lithium ion battery discharge and recharge ampere-hour number and capacity Ratio constitutes input matrix Φ (1) as mode input by mathematical operation, and Φ (2) ... Φ (n), wherein n are total data Times of collection;
Iteration in such a way, recognize ohmic internal resistance, polarization resistance, polarization capacity and the open-circuit voltage of lithium ion battery with The coefficient of state-of-charge fit correlation:
θ ^ ( k + 1 ) = θ ^ ( k ) + P ( k ) · Φ ( k + 1 ) λ + Φ T ( k + 1 ) · P ( k ) · Φ ( k + 1 ) · [ Y ( k + 1 ) - Φ T ( k + 1 ) · θ ^ ( k ) ]
P ( k + 1 ) = 1 λ [ P ( k ) - P ( k ) · Φ ( k + 1 ) · Φ T ( k + 1 ) · P ( k ) λ + Φ T ( k + 1 ) · P ( k ) · Φ ( k + 1 ) ]
θ ^ ( 0 ) = 0
P (0)=CI
Wherein C is arbitrary constant,For ohmic internal resistance, polarization resistance, the polarization capacity of the lithium ion battery in kth time iteration And the vector that the coefficient of open-circuit voltage and state-of-charge fit correlation is constituted, total iterations is n, and λ is forgetting factor, value Between 0 to 1, Y (k) is the terminal voltage value of lithium ion battery in kth time iteration.
6. the charge states of lithium ion battery evaluation method any one of claim 1 or 4, it is characterised in that in the full longevity Order and sample lithium ion battery is sampled in region, charge-discharge test temperature range is between 0 DEG C -45 DEG C.
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Families Citing this family (30)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102756661A (en) * 2011-04-27 2012-10-31 北京八恺电气科技有限公司 Determination method and device for state of charge of vehicular battery
CN102930173A (en) * 2012-11-16 2013-02-13 重庆长安汽车股份有限公司 SOC(state of charge) online estimation method for lithium ion battery
CN103389468A (en) * 2012-05-08 2013-11-13 通用汽车环球科技运作有限责任公司 Battery state-of-charge observer
CN103698713A (en) * 2013-12-30 2014-04-02 长城汽车股份有限公司 Method for assessing SOH (state of health) of lithium ion battery
CN103901354A (en) * 2014-04-23 2014-07-02 武汉市欧力普能源与自动化技术有限公司 Methods for predicting SOC of vehicle-mounted power battery of electric automobile
CN203786271U (en) * 2014-04-22 2014-08-20 桂林电子科技大学 Device for testing state of charge (SOC) of electric automobile battery pack
CN104007395A (en) * 2014-06-11 2014-08-27 北京交通大学 Lithium ion battery charge state and parameter adaptive joint estimation method
CN104076293A (en) * 2014-07-07 2014-10-01 北京交通大学 Quantitative analysis method for observer-based SOC estimation errors of lithium batteries

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP4984527B2 (en) * 2005-12-27 2012-07-25 トヨタ自動車株式会社 Secondary battery charge state estimation device and charge state estimation method
JP2014139520A (en) * 2013-01-21 2014-07-31 Toyota Industries Corp Charging rate estimation device and charging rate estimation method

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102756661A (en) * 2011-04-27 2012-10-31 北京八恺电气科技有限公司 Determination method and device for state of charge of vehicular battery
CN103389468A (en) * 2012-05-08 2013-11-13 通用汽车环球科技运作有限责任公司 Battery state-of-charge observer
CN102930173A (en) * 2012-11-16 2013-02-13 重庆长安汽车股份有限公司 SOC(state of charge) online estimation method for lithium ion battery
CN103698713A (en) * 2013-12-30 2014-04-02 长城汽车股份有限公司 Method for assessing SOH (state of health) of lithium ion battery
CN203786271U (en) * 2014-04-22 2014-08-20 桂林电子科技大学 Device for testing state of charge (SOC) of electric automobile battery pack
CN103901354A (en) * 2014-04-23 2014-07-02 武汉市欧力普能源与自动化技术有限公司 Methods for predicting SOC of vehicle-mounted power battery of electric automobile
CN104007395A (en) * 2014-06-11 2014-08-27 北京交通大学 Lithium ion battery charge state and parameter adaptive joint estimation method
CN104076293A (en) * 2014-07-07 2014-10-01 北京交通大学 Quantitative analysis method for observer-based SOC estimation errors of lithium batteries

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
储能锂离子电池荷电状态估算方法;许伟等;《上海电气技术》;20140331;第7卷(第01期);第22-25页 *
电动汽车动力电池荷电状态估计方法探讨;曾求勇等;《电测与仪表》;20141225;第51卷(第24期);第76-84页 *
电动汽车用动力电池SOC估算方法概述;李琳辉等;《汽车电器》;20131231(第12期);第12-15页 *

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