CN109683101B

CN109683101B - Method for obtaining battery residual energy based on SOC-OCV curve

Info

Publication number: CN109683101B
Application number: CN201811563902.0A
Authority: CN
Inventors: 来翔; 彭勇俊; 习清平; 王晓东
Original assignee: Anhui Udan Technology Co ltd
Current assignee: Anhui Udan Technology Co ltd
Priority date: 2018-12-20
Filing date: 2018-12-20
Publication date: 2021-02-19
Anticipated expiration: 2038-12-20
Also published as: CN109683101A

Abstract

The invention discloses a method for obtaining battery residual energy based on an SOC-OCV curve, and belongs to the field of automobile batteries. It comprises the following steps: s1, collecting a temperature-rated capacity curve, a temperature-total energy curve and SOC-OCV curves at different temperatures; s2, obtaining SOC-residual energy curves at different temperatures; s3, inputting SOC-residual energy curves at different temperatures into a BMS program; and S4, inquiring according to the two-dimensional table to obtain the real-time residual energy. The invention firstly provides the method for calculating the integration of the discharged energy by using the SOC-COV curve to obtain the residual energy of the battery, and further obtain the residual energy of the battery under different temperatures and SOC. According to the invention, the accurate residual energy can be obtained only by testing the most basic battery characteristics, the workload of battery testing is reduced, and the real-time residual energy of the battery can be obtained in the running process of the vehicle.

Description

Method for obtaining battery residual energy based on SOC-OCV curve

Technical Field

The invention belongs to the field of automobile batteries, and particularly relates to a method for obtaining battery residual energy based on an SOC-OCV curve.

Background

The power battery is a device for converting chemical energy into electric energy, the conversion process is a complex physical and chemical reaction process, and the calculation of the residual energy of the power battery is of great significance for estimating the residual driving mileage of the electric automobile, avoiding the incapability of driving due to the fact that the automobile is out of power, charging the automobile in time and the like.

The SOC, which is collectively referred to as State of Charge, reflects the remaining capacity of the battery, which is numerically defined as the ratio of the remaining capacity to the battery capacity. The SOC-OCV curve is generally used to estimate the SOC value, and a one-to-one correspondence relationship between the SOC and the battery SOC is indirectly fitted mainly according to a variation relationship between the OCV of the battery and the lithium ion concentration in the battery, that is, a certain functional relationship exists between the electromotive force of the battery and the SOC of the battery, so that the SOC value of the battery can be obtained by measuring the open-circuit voltage.

The residual energy represents the energy that the battery can accumulate and release from the current time to the discharge cut-off time, and the existing methods for obtaining the residual energy are generally classified into the following methods: (1) using the formula E ═ SOC × Q₀×U_batEstimating the residual energy of the power battery by the XSOH, wherein E represents the residual energy of the power battery, SOC (State of Charge) represents the current state of charge of the battery pack, and Q₀Indicating the rated capacity, U, of the battery_batThe voltage Of the battery pack, soh (section Of health), represents the health Of the battery. However, the method can only be used for the residual energy of the battery at the current moment, the voltage of the battery is lower and lower along with the discharge of the battery pack, and the calculation result is higher due to the fact that the future discharge working condition is not considered when the voltage at the current moment is adopted for calculating the residual energy. (2) The SOC is multiplied by the total energy to obtain the residual energy, the method does not consider the complex physical and chemical reaction of the battery, and the battery pack is not strictly linear in relation to the available energy at different states of charge. (3) Obtaining residual energy values of the battery under different currents, voltages, temperatures and SOH through laboratory tests, establishing a residual energy parameter lookup table, and looking up the table according to the real-time current, voltage, temperature and SOH of the battery in the actual operation process; a4-dimensional parameter table can be established only by carrying out a large number of experiments in the early stage of the method, and large manpower and material resources need to be released.

Disclosure of Invention

1. Problems to be solved

Aiming at the problems that the existing method for obtaining the residual energy is inaccurate or the time and the labor are consumed when related data are obtained, the invention provides a method for obtaining the residual energy of a battery based on an SOC-OCV curve. The invention can reduce the calculation complexity and reduce the resource consumption in the program running process under the condition of ensuring the precision of calculating the residual energy.

2. Technical scheme

In order to solve the above problems, the present invention adopts the following technical solutions.

A method for obtaining the residual energy of a battery based on an SOC-OCV curve comprises the following steps:

s1, collecting a temperature-rated capacity curve, a temperature-total energy curve and SOC-OCV curves at different temperatures;

s2, calculating residual energy of each SOC corresponding point in the SOC-OCV curves at different temperatures to obtain SOC-residual energy curves at different temperatures;

s3, inputting SOC-residual energy curves at different temperatures into a BMS program;

and S4, selecting SOC-residual energy two-dimensional tables with different temperatures according to the real-time temperature and SOC value of the battery for query to obtain the real-time residual energy.

As an optimization, in step S2, the residual energy is obtained by the following steps,

s21, firstly, calculating the released energy Uedeenergy of the battery:

s22, recalculating the residual energy LeftEnergy of the battery:

LeftEnergy ═ (totaleenergy-useedenergy) x SOH formula (2)

In formula (1) and formula (2): u shape_aVoltage corresponding to a state of charge, U_bVoltage corresponding to b state of charge, SOC_aIs SOC corresponding to a state of charge_bIs SOC, Q corresponding to b state of charge₀For rated capacity, TotalEnergy is the total energy of the battery, and SOH is the battery health.

As an optimization scheme, the interval length between the two charge states of a and b ranges from 5% to 10%.

As an optimization scheme, step S2 further includes a process of self-learning SOC-OCV curves at different temperatures, and the specific steps are as follows:

s23, calculating the energy actually released by the battery

S24, substituting E for UsedEnergy and substituting the E into the formula (2) to obtain LeftEnergy';

u is the current voltage, I is the current, dt is the duty cycle for calculating the accumulated discharge energy, T₁LeftEnergy for time to discharge full charge to SOC point requiring self-learning₀Is actually left overEnergy;

and S25, calculating a difference value delta E between the LeftEnergy and the LeftEnergy', and replacing the LeftEnergy at the current temperature and the SOC with the LeftEnergy when the delta E is greater than 3% TotalEnergy SOH.

As an optimization scheme, when the SOH is in the range of 80% -99%, the self-learning process for different SOC-OCV curves is started by taking 1% as an interval.

As an optimization scheme, in the self-learning process, when the SOC is in the range of 20% -90%, T is selected at intervals of 5% or 10%₁The actual remaining energy at different temperatures was calculated.

3. Advantageous effects

Compared with the prior art, the invention has the beneficial effects that:

(1) the invention firstly proposes that the SOC-COV curve is used for calculating the integral of the discharged energy to obtain the residual energy of the battery, further the residual energy of the battery under different temperatures and SOC is obtained, the data is input into software, and the current residual energy can be obtained by looking up a table according to the current SOC and the temperature of the battery. According to the invention, the accurate residual energy can be obtained only by testing the most basic battery characteristics, the workload of battery testing is reduced, and the real-time residual energy of the battery can be obtained in the running process of the vehicle.

During the running process of the vehicle, the battery energy is actually consumed, the SOC represents the remaining ampere hours of the battery, and the detected remaining energy can more accurately predict the remaining mileage of the vehicle than the SOC.

(2) Compared with the prior art, in the method for obtaining UsedEnergy, the calculation result of UsedEnergy is accurate because the SOC interval is small and the voltage change is not large during the OCV test. The method can effectively improve the calculation accuracy of the residual energy, provide the accuracy range of more than 10 percent, and reduce the resource emission in the software running process.

(3) According to the concept of integration, the more the interval division, the higher the accuracy, but for the SOC-OCV curve, if the interval division is too much, the test workload may be increased. A large number of experimental researches show that when the SOC test interval is selected to be 5% -10%, the calculation accuracy of the residual energy can be ensured, and the test workload can be reduced.

(4) Because the SOC-OCV curve of the battery during aging is different from the SOC-OCV curve of the new battery, the calculation deviation of the residual energy can be caused, the residual energy of each stage of the battery aging process can be obtained through self-learning, the preset table lookup value is replaced and updated, the table lookup value is always consistent with the current battery state, and the calculation deviation caused by battery aging is reduced.

(5) When the SOH is in the range of 80% -99%, the battery starts to age, the SOC-OCV curve at the time is likely to deviate, in order to avoid the deviation, software can respond timely when the battery ages, and a self-learning process is started; but the self-learning starting cannot be too frequent so as to avoid consuming too much singlechip resources.

And starting the self-learning process of different SOC-OCV curves by taking 1% as a time interval, so that the self-learning calculated amount can be reduced, the tables of temperature, SOC and residual energy do not need to be updated in real time, and meanwhile, the self-learning function can be started and the residual energy table can be updated when the change of SOH is small.

(6)T₁The value of the SOC value is consistent with the SOC value when the SOC-OCV curve is tested, so that the residual energy value in each SOC state can be ensured to be updated.

Drawings

FIG. 1 is a flow chart of the method of the present invention;

FIG. 2 is a SOC-OCV curve at a certain temperature;

FIG. 3 is a flowchart of the method of example 1;

FIG. 4 is a flowchart of a self-learning process of embodiment 4.

Detailed Description

The invention is described in detail below with reference to the figures and specific embodiments.

Example 1

A method for obtaining a remaining energy of a battery based on an SOC-OCV curve, as shown in fig. 1, includes the steps of:

s1, obtaining SOC-OCV curves at different temperatures by using a charging and discharging cabinet and a high-low temperature box;

the rated capacity (Q0 in the formula 1) and the total energy (TotalEnergy in the formula 2) of the battery at each temperature can be obtained through the temperature-capacity curve and the temperature-energy curve;

s2, calculating the residual energy of each SOC corresponding point in the SOC-OCV curve at different temperatures according to the following formula, as shown in FIG. 2:

s21, firstly, calculating the released energy Uedeenergy of the battery:

s22, recalculating the residual energy LeftEnergy of the battery:

LeftEnergy (totalengegy-useedenergy) x SOH formula (2)

In formula (1) and formula (2): u shape_aVoltage corresponding to a state of charge, U_bVoltage corresponding to b state of charge, SOC_aIs SOC corresponding to a state of charge_bIs SOC, Q corresponding to b state of charge₀For rated capacity, TotalEnergy is total energy of the battery, and SOH is battery health;

obtaining SOC-residual energy curves at different temperatures through a formula (1) and a formula (2);

s3, inputting SOC-residual energy curves at different temperatures into a software program;

Since the remaining energy of the battery and the voltage and SOC of the battery are both related, the remaining energy of the battery at a certain time is:

E＝SOC×Q₀×U_bat×SOH (3)

in the formula: SOC is the state of charge at the present time, Q₀For rated capacity, U_batThe SOH is the current voltage and the current health.

The functional relationship between the cell voltage and the SOC can be expressed by the following formula:

U_bat＝f(SOC) (4)

thus substituting (4) into equation (3), one can obtain:

E＝SOC×Q₀×f(SOC)×SOH (5)；

rated capacity Q, since SOH is constant during a single discharge₀And is also a fixed value, therefore, the concept of integration is adopted, the SOC-OCV curve is divided into N equal parts (N is determined by the number of SOC points of the tested SOC-OCV), and the variation of the remaining energy between any two points is as follows:

ΔE＝ΔSOC×Q₀×f(SOC)×SOH (6)

at the SOC of 100%, the remaining energy is the total energy of the battery, and therefore equations (1) and (2) can be obtained. The SOC and residual energy curve at the temperature can be obtained according to the formula (1) and the formula (2), and similarly, the SOC and residual energy curves at other temperature points can be obtained according to the SOC-OCV curves at other temperature points.

For example, OCV tests are performed at 10% intervals at a certain temperature, and open circuit voltages corresponding to SOCs of 0, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, and 100% are obtained.

a. When the SOC is 100%, the energy discharged by the battery is 0; when the SOC is 0, the remaining energy of the battery is 0, and therefore the remaining energy with the SOC of 100% is:

LeftEnergy_{soc_100}＝TotalEnergy×SOH-UsedEnergy＝TotalEnergy×SOH

the remaining energy at 0% SOC is:

LeftEnergy_{soc_0}＝0

in the formula: TotalEnergy represents rated capacity at the current temperature, and SOH represents battery health.

b. When the SOC is 90%, the energy discharged from the battery is calculated according to the formula (1):

in the formula: u shape₁₀₀Represents the open circuit voltage, U, corresponding to the SOC of 100%₉₀Represents the open circuit voltage, Q, corresponding to a SOC of 90%₀Represents the rated capacity of the battery;

c. when the SOC is 90%, the remaining energy of the battery is calculated according to equation (2):

LeftEnergy_{soc_90}＝LeftEnergy_{SOC_100}-UsedEnergy

d. the residual energy LeftEnergy with SOC of 20%, 30%, 40%, 50%, 60%, 70% and 80% can be obtained by repeating the step 2 and the step 3_{soc_20}、LeftEnergy_{soc_30}、LeftEnergy_{soc_40}、LeftEnergy_{soc_50}、LeftEnergy_{soc_60}、LeftEnergy_{soc_70}、LeftEnergy_{soc_80}。

For example, the ampere-hour Q rating of a ternary cell at 25 deg.C₀At 50Ah, available energy TotalEnergy is 0.1883kwh, and SOC-OCV data are:

SOC(％)	0	10	20	30	40	50	60	70	80	90	100
												voltage (mv)	3413	3495	3570	3611	3645	3706	3811	3917	4030	4153	4323

SOC is 100%: LeftEnergy_{soc_100}＝TotalEnergy＝0.1883kwh；

When SOC is 0:

LeftEnergy_{soc_0}＝0；

SOC is 90%:

SOC is 80%:

SOC is 70%:

SOC is 60%:

SOC is 50%:

SOC is 40%:

SOC 30%:

SOC is 20%:

SOC is 10%:

e. the relation between each SOC point and the residual energy at the temperature is obtained according to the steps a-d.

f. And (e) repeating the steps a-e to obtain the relation between the SOC and the residual energy at each temperature, taking the temperature and the SOC as the input of a table look-up, and taking the residual energy as the output of the table look-up. During the running of the vehicle, a linear interpolation method is adopted for the data without corresponding SOC and temperature points, as shown in FIG. 3.

The invention firstly proposes that the SOC-COV curve is used for integrating the discharged energy to obtain the residual energy of the battery under different temperatures and SOC, the data are input into BMS software, and the current residual energy can be obtained by looking up the table according to the current SOC and the temperature of the battery. Compared with the existing method, the UsedEnergy is calculated by using the algorithm, and the calculation result of the UsedEnergy is accurate because the SOC interval is small and the voltage change is not large during the OCV test.

When a program runs, the residual energy exists in a two-dimensional table form of temperature, SOC and residual energy, and the residual energy can be obtained by directly looking up the table according to the current temperature and SOC of the battery, so that only data of the two-dimensional table needs to be input in advance during calculation, the data volume is small, and only a table look-up function needs to be directly called during table look-up, so that the consumption of complex operation on resources of the single chip microcomputer can be effectively reduced. According to the invention, the accurate residual energy can be obtained only by testing the most basic battery characteristics, the workload of battery testing is reduced, and the real-time residual energy of the battery can be obtained in the running process of the vehicle. Therefore, the method can effectively improve the calculation precision of the residual energy and reduce the resource emission in the software running process.

Example 2

Example 2 a further optimization was made based on the protocol of example 1, setting the interval between the two states of charge of a and b to 5% to 10%, preferably 5% and 10%.

For the integral, the more the interval division is, the higher the precision is; however, for the SOC-OCV curve, too many divisions increase the test workload. A large number of experimental researches show that when the SOC test interval is selected to be 5% -10%, the calculation accuracy of the residual energy can be ensured, and the test workload can be reduced.

Example 3

Embodiment 3 is further optimized on the basis of embodiment 1, and in step S2, a process of self-learning SOC-OCV curves at different temperatures is added, specifically including the following steps:

s23, calculating the energy actually released by the battery:

when the SOC is 90%, the energy actually released by the battery at this time is:

in the formula: u is the current voltage, I is the current, dt is the duty cycle for calculating the accumulated discharge energy, T₁SOC90_ T, which represents the time from the start of full charge to discharge when the SOC is 90%;

s24, substituting E for UsedEnergy and substituting the E into the formula (2) to obtain the corresponding residual energy LeftEnergy of 90% SOC_{SOC_90}’；

S25, calculating LeftEnergy_{SOC_90}' and LeftEnergy_{SOC_90}A difference value delta E between the current temperature and the current temperature, wherein when the delta E is more than 3% TotalEnergy SOH, 90% SOC corresponds to the new remaining energy NewLeftenergy_{SOC_90}Using LeftEnergy_{SOC_90}' instead; otherwise, no update is performed.

S26, repeating the steps S22, S23 and S24 to obtain the new remaining energy NewLeftenergy corresponding to 80%, 70%, 60%, 50%, 40%, 30%, 20% and 10% SOC_{SOC_80}、NewLeftEnergy_{SOC_70}、NewLeftEnergy_{SOC_60}、NewLeftEnergy_{SOC_50}、NewLeftEnergy_{SOC_40}、NewLeftEnergySOC_30、NewLeftEnergy_{SOC_20}、NewLeftEnergy_{SOC_10}。

Because the SOC-OCV curve of the battery during aging is different from the SOC-OCV curve of the new battery, the calculation deviation of the residual energy can be caused, the residual energy of each stage of the battery aging process can be obtained through self-learning, the preset table lookup value is replaced and updated, the table lookup value is always consistent with the current battery state, and the calculation deviation caused by battery aging is reduced.

Example 4

Embodiment 4 on the basis of embodiment 1, not only the self-learning process is added, but also the self-learning process is further optimized; in the whole life cycle of the battery, frequent self-learning is not possible, so that the resources of the single chip microcomputer are excessively consumed. After a number of studies we finally determined that the process of self-learning for different SOC-OCV curves starts with 1% as time interval when the SOH is in the range 80% -99%.

When the SOH is in the range of 80% -99%, the battery begins to age, the SOC-OCV curve at the time is likely to deviate, in order to avoid the deviation, software can respond timely when the battery ages, and a self-learning process is started.

Example 5

Example 5 on the basis of example 1, a self-learning process is added, and in order to optimize the scheme, in the self-learning process of example 5, when the SOC is in the range of 20% -90%, T is selected at intervals of 10%₁The actual remaining energy at different temperatures was calculated.

Examples 3 and 5T 1 were selected by spacing₁The value of the SOC value is consistent with the SOC value when the SOC-OCV curve is tested, so that the residual energy value in each SOC state can be ensured to be updated.

Claims

1. A method for obtaining the residual energy of a battery based on an SOC-OCV curve is characterized by comprising the following steps:

s4, selecting SOC-residual energy two-dimensional tables with different temperatures according to the real-time temperature and SOC value of the battery for query to obtain real-time residual energy;

in step S2, the residual energy is obtained by the following steps,

s21, firstly, calculating the released energy Uedeenergy of the battery:

s22, recalculating the residual energy LeftEnergy of the battery:

LeftEnergy ═ (totaleenergy-useedenergy) x SOH formula (2)

2. The method for obtaining the residual energy of the battery based on the SOC-OCV curve of claim 1, wherein the length of the interval between the two states of charge of a and b ranges from 5% to 10%.

3. The method for obtaining the remaining energy of the battery based on the SOC-OCV curve as claimed in claim 1, wherein the step S2 further includes a process of self-learning the SOC-OCV curve at different temperatures, and the specific steps are as follows:

s23, calculating the energy actually released by the battery

u is the current voltage, I is the current, dt is the duty cycle for calculating the accumulated discharge energy, T₁LeftEnergy for time to discharge full charge to SOC point requiring self-learning₀Is the actual remaining energy;

4. The method of claim 3, wherein said self-learning process for different SOC-OCV curves is started at 1% intervals when SOH is in the range of 80% -99%.

5. The method for obtaining the remaining energy of the battery according to claim 4, wherein in the self-learning process, when the SOC is in the range of 20% -90%, T is selected at intervals of 5% or 10%₁The actual remaining energy at different temperatures was calculated.