CN117465291B - Method for estimating electric quantity SOC of lithium iron phosphate battery hybrid vehicle and vehicle - Google Patents
Method for estimating electric quantity SOC of lithium iron phosphate battery hybrid vehicle and vehicle Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 46
- GELKBWJHTRAYNV-UHFFFAOYSA-K lithium iron phosphate Chemical compound [Li+].[Fe+2].[O-]P([O-])([O-])=O GELKBWJHTRAYNV-UHFFFAOYSA-K 0.000 title claims abstract description 25
- 238000012937 correction Methods 0.000 claims abstract description 174
- 238000004364 calculation method Methods 0.000 description 8
- 230000003068 static effect Effects 0.000 description 7
- 230000010354 integration Effects 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 230000005059 dormancy Effects 0.000 description 3
- 238000013507 mapping Methods 0.000 description 3
- 238000006243 chemical reaction Methods 0.000 description 2
- 230000007958 sleep Effects 0.000 description 2
- 208000011580 syndromic disease Diseases 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000004146 energy storage Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000013139 quantization Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000004622 sleep time Effects 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
- 230000001960 triggered effect Effects 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
- B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
- B60L58/12—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries responding to state of charge [SoC]
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L3/00—Electric devices on electrically-propelled vehicles for safety purposes; Monitoring operating variables, e.g. speed, deceleration or energy consumption
- B60L3/12—Recording operating variables ; Monitoring of operating variables
-
- 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
- G01R31/005—Testing of electric installations on transport means
- G01R31/006—Testing of electric installations on transport means on road vehicles, e.g. automobiles or trucks
-
- 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]
- G01R31/378—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC] specially adapted for the type of battery or accumulator
-
- 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]
- G01R31/385—Arrangements for measuring battery or accumulator variables
- G01R31/387—Determining ampere-hour charge capacity or SoC
-
- 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]
- G01R31/385—Arrangements for measuring battery or accumulator variables
- G01R31/387—Determining ampere-hour charge capacity or SoC
- G01R31/388—Determining ampere-hour charge capacity or SoC involving voltage measurements
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L2240/00—Control parameters of input or output; Target parameters
- B60L2240/40—Drive Train control parameters
- B60L2240/54—Drive Train control parameters related to batteries
- B60L2240/547—Voltage
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L2240/00—Control parameters of input or output; Target parameters
- B60L2240/40—Drive Train control parameters
- B60L2240/54—Drive Train control parameters related to batteries
- B60L2240/549—Current
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
Abstract
The invention relates to a method for estimating the electric quantity SOC of a lithium iron phosphate battery hybrid vehicle and the vehicle, and belongs to the technical field of lithium iron phosphate battery SOC. When any SOC correction time is met, acquiring the total SOC and the total credibility under the current correction time; judging whether the sub-credibility corresponding to the current correction time is greater than the total credibility, if so, correcting the current SOC at the correction time to obtain an SOC correction value, and estimating an SOC final value based on the SOC correction value, the total SOC and the sub-credibility corresponding to the current correction time; if not, correcting the SOC at the moment; wherein the total reliability is related to the number of capacity cycles last corrected to the moment, and the larger the number of capacity cycles last corrected to the moment is, the smaller the total reliability is. The scheme is used for solving the problem that correction errors under different correction occasions are not fully considered in the prior art to influence the SOC value.
Description
Technical Field
The invention relates to a method for estimating the electric quantity SOC of a lithium iron phosphate battery hybrid vehicle and the vehicle, and belongs to the technical field of lithium iron phosphate battery SOC.
Background
The lithium iron phosphate battery has great charge and discharge performance, high safety and long cycle life, and has important application value in the energy storage fields of micro-grid systems, electric automobiles, communication base stations and the like. These application scenarios all need to be equipped with a battery management system BMS in order to fully utilize the power potential of the battery system, promote its safety in use, avoid battery overcharge or overdischarge, and extend the service life of the battery. For this purpose, an accurate estimation of the state of charge of the battery, SOC (State of Charge), must be made. SOC is a key parameter reflecting the chargeable and dischargeable capacity of lithium iron phosphate batteries during use. However, the existing scheme for estimating the SOC cannot achieve higher accuracy because 1) the estimated SOC has a small error correction chance, 2) the SOC is estimated without a long-time rest sleep correction condition, 3) the estimated SOC timing cannot be determined, and there is a concern about additional errors caused by the error correction method itself; the method is interfered by various factors, so that the method for estimating and predicting the electric quantity of the battery becomes complex, and the difficulty for accurately estimating the SOC is high. Therefore, selecting an appropriate lithium iron phosphate battery SOC correction strategy is critical to improving SOC estimation accuracy and display smoothness.
Disclosure of Invention
The invention aims to provide a method for estimating the electric quantity SOC of a lithium iron phosphate battery hybrid vehicle and the vehicle, which are used for solving the problem that correction errors under different correction occasions are not fully considered in the prior art to influence the SOC value.
In order to achieve the above object, the present invention provides a method comprising:
a method of estimating the charge SOC of a lithium iron phosphate battery hybrid vehicle, comprising the steps of: when any SOC correction time is met, acquiring the total SOC and the total credibility under the current correction time; judging whether the sub-credibility corresponding to the current correction time is greater than the total credibility, if so, correcting the current SOC at the correction time to obtain an SOC correction value, and estimating an SOC final value based on the SOC correction value, the total SOC and the sub-credibility corresponding to the current correction time; if not, correcting the SOC at the moment; wherein the total reliability is related to the number of capacity cycles last corrected to the moment, and the larger the number of capacity cycles last corrected to the moment is, the smaller the total reliability is.
The method comprises the steps of firstly obtaining total SOC and total credibility under current correction time, judging whether sub-credibility corresponding to the current correction time is larger than the total credibility, correcting the total SOC to obtain a final SOC when the total credibility is smaller than the sub-credibility, and estimating an SOC final value based on the SOC correction value, the total SOC and the sub-credibility corresponding to the current correction time; otherwise, not correcting; the problem that the additional error of the correction method affects the SOC value is solved by the judging method for the total SOC correction enabling, and the SOC estimation precision is improved by selecting proper SOC correction time of the lithium iron phosphate battery.
Further, the relationship between the total reliability and the capacity cycle number from the last correction to the moment is:
wherein: SOCCorrctCyclTimes is the number of capacity cycles last corrected to that moment, SOCCred is the confidence level.
The method is simple by converting the capacity cycle times corrected last time to the total reliability of the total SOC and effectively estimating the accuracy of the current total SOC through the total reliability.
Further, the expression of the capacity cycle number from the last correction to the moment is:
wherein: SOCCorrctCyclTimes is the number of capacity cycles last corrected to that moment; SOCCorrCred represents sub-credibility at different SOC correction occasions; socbasecocltimes represents a reference value of the number of capacity cycles converted from the last correction to the moment at which the different SOC correction timings are corrected; CN is the calibration value of the capacity; i is the absolute value of the battery current; k is charge-discharge efficiency.
The number of capacity cycles from the last correction to the moment is calculated through the sub-credibility under different SOC correction occasions, the conversion of the different SOC correction occasions into the reference value of the number of capacity cycles from the last correction to the moment, the calibration value of the capacity, the absolute value of the battery current and the charge and discharge efficiency, so that the effective estimation of the credibility of the total SOC is realized.
Further, the expression of the final value of SOC is:
wherein: SOCCorr is the corrected SOC correction value for the current correction opportunity, credSOCCorr is the corrected sub-confidence of the current correction opportunity, SOC Total (S) Is the total SOC at the current corrective opportunity.
The calculation formula further calculates an SOC final value through the corrected SOC correction value of the current correction time, the corrected sub-reliability of the current correction time and the total SOC under the current correction time, so that effective estimation of the current total SOC is realized.
Further, if the required standing time at the correction timing is smaller than the set time threshold, the OCV is estimated by using the SOC, the standing time, and the dynamic terminal voltage before correcting the SOC, and the corrected SOC at the current correction timing is determined based on the estimated OCV and the OCV-SOC table.
Under the working condition of insufficient standing, the OCV cannot be accurately measured at the moment, the scheme utilizes the SOC, the standing time and the dynamic terminal voltage to estimate the OCV, and then the corresponding SOC is obtained through the estimated value of the OCV; thereby increasing and improving the correction precision under the working condition of insufficient standing.
Further, the ratio of OCV and dynamic terminal voltage under different state of charge (SOC) at different rest times is measured to form an OCV estimation model table for estimating OCV.
If the chip does not support floating point multiplication and division, exponential operation or slower speed, the OCV can be estimated by using an OCV estimation model table, so that the correction opportunity of the SOC is increased.
Further, the OCV estimation model is obtained by fitting data in the OCV estimation model table, and the OCV under the current SOC correction time is estimated by using the OCV estimation model.
If the chip supports floating point multiply-divide and exponential operation, the calculation capability is strong, and the OCV under the current SOC correction time can be estimated under the condition that a large amount of data is not required to be stored, so that the storage space is saved.
Further, when the difference between the final SOC and the total SOC is greater than the set difference, correction is performed in several times, and a part of the difference is corrected at regular intervals until the difference correction is completed.
The SOC correction method can effectively prevent the condition of transition of the SOC value when the SOC is corrected, and cause bad experience to the user, so that the SOC is smoothly displayed to the user.
The invention also provides a vehicle using the method for estimating the electric quantity SOC of the lithium iron phosphate battery hybrid vehicle, and the method for estimating the electric quantity SOC of the lithium iron phosphate battery hybrid vehicle is adopted when the vehicle displays the SOC.
Drawings
FIG. 1 is a general flowchart of SOC estimation in the present embodiment;
FIG. 2 is a schematic diagram of the result of identifying parameters to be fitted of the OCV estimation model in the present embodiment;
FIG. 3 is a schematic diagram showing the results after the OCV estimation model fitting in the present embodiment;
fig. 4 is a correspondence relationship between ocv_k and SOC under different rest time conditions in the present embodiment;
FIG. 5 is a diagram showing the correspondence between SOCByEstOCV and sub-confidence CredSOCByEstOCV under different standing time conditions in the present embodiment;
fig. 6 is a correspondence relationship between OCV and SOC under different temperature conditions in the present embodiment;
fig. 7 is a correspondence relationship between OCV and SOC under different temperature and current conditions in the present embodiment;
fig. 8 is a correspondence relationship between SOC and sub-reliability under different current conditions in the present embodiment.
Detailed Description
The present invention will be further described in detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent.
Method embodiment:
as shown in fig. 1, a method for estimating an electric quantity SOC of a lithium iron phosphate battery hybrid vehicle according to the embodiment mainly includes: the method comprises the steps of a total SOC error reliability estimation model, a correction enabling strategy of the SOC, calculation of a final SOC, an OCV estimation model and initial value acquisition of the SOC.
Total SOC error reliability estimation model:
the total SOC reliability characterizes the SOC error degree at the moment and is mainly related to whether the current integration accumulation capacity and the SOC correction time are corrected or not. And developing a total SOC error credibility estimation model, and determining the enabling time of the error correction model according to the credibility, so as to solve the problem of error correction.
The total SOC reliability correction lithium iron phosphate battery cell voltage OCV-SOC is in a region with good correlation characteristics, and after quantization, the better the correlation characteristics are, the higher the reliability is, and the smaller the level is. And calculating the reliability (0-100, the larger the numerical value is, the higher the reliability) of the total SOC value according to the capacity cycle times from the last correction to the moment.
The conversion relation between the total reliability SOCCred (0-100) and the "capacity cycle number corrected last time" SOCCorrctCyclTimes (0-30 times, avoiding precision loss, and expanding 100 times to 0-3000 times) is as follows:
each kind of SOC correction time has different SOC sub-credibility, so when certain kind of SOC correction time is enabled once, relevant parameters for calculating the total SOC credibility and the SOC have corresponding changes; and converting the current ampere-hour integral value of each period into capacity circulation times, wherein the capacity circulation times are continuously increased along with the increase of the time interval after the last correction, and determining the total reliability in real time through updated relevant parameters for calculating the total SOC reliability and the capacity circulation times. And determining the sub-credibility of each SOC correction opportunity according to the test data, and taking the sub-credibility as a basis for enabling the correction opportunity in the later period.
If the correction time of the SOC is enabled once, updating the related parameters for calculating the total SOC reliability, and calculating the capacity cycle times from last correction to the moment through the sub-reliability as follows:
wherein: SOCCorrctCyclTimes represents the number of capacity cycles from last correction to the moment, and ranges from 0 to 3000 times; SOCCorrCred represents sub-credibility under different SOC correction occasions, and the range is 0-100; SOCBaseClyclTimes represents the reference value of the capacity cycle times from the last correction of different SOC correction occasions to the moment, the range is set to be 0-3000 times in the embodiment, and CN is the capacity calibration value; i is the absolute value of the battery current, k is the charge-discharge efficiency, and is set to 1 by default, and in this embodiment, 0.95.
When a certain SOC correction opportunity is enabled once, the relevant parameters for calculating the total SOC reliability are updated. The method for updating the relevant parameters for calculating the total SOC reliability in the embodiment is described below by taking several types of SOC correction occasions as examples; the calibration of the socbasecocltimes in the relevant parameters for calculating the total SOC reliability is as follows when the following corrective occasions are satisfied:
1) When the full charge condition is reached, soc=100%, a full charge signal is received or (terminal voltage UcellMax is not less than 3.65V for 5 seconds and current is less than Max (0.1 c,5 a)), socbasecocltimes is 0, and syndrome credibility soccor cred is 100%;
2) When the emptying condition is met, SOC=0, the terminal voltage UcellMax is less than or equal to 2.5V and lasts for 20 seconds, the absolute value of the current is smaller than Max (0.1C, 5A), SOCBaseClyclTimes is 100, and the reliability of the correction SOCCorrCred is 98%;
3) The low-stage OCV-SOC table is checked, the SOC is less than or equal to 25 percent, (the current is less than Max (0.02C, 3A) and the duration is more than or equal to 1 h), or the rest time is more than or equal to 1h, and the OCV-SOC table is checked to obtain: SOCBaseClyclTimes is 200, and the syndrome credibility SOCCorrCred is 97%;
4) The middle section OCV-SOC table is checked, the SOC is more than or equal to 60% and less than or equal to 70%, (the current is less than Max (0.02C, 3A) and the duration is more than or equal to 1 h), or the rest time is more than or equal to 1h, and the OCV-SOC table is checked to obtain: SOCBaseCryclTimes is 500, the reliability of the correction SOCCorrCred is 95%, and on the premise that other conditions are met, SOCCorrCred is less than or equal to 95% and correction is enabled;
5) High-stage OCV-SOC table lookup, SOC is more than or equal to 98%, (current is less than Max (0.02C, 3A) and duration is more than or equal to 1 h) or rest time is more than or equal to 1h, and OCV-SOC table lookup is performed to obtain: SOCBaseCryclTimes is 700, the reliability of the correction SOCCorrCred is 93%, and on the premise that other conditions are met, SOCCorrCred is less than or equal to 93% and correction is enabled;
the above values of the correction reliability soccor cred and the reference value socbasecocltime of the capacity cycle number are all calibratable, in this embodiment, only temporary calibration values are used, calibration can be adjusted according to actual situations in actual use, and when the SOC correction timing is enabled, the total SOC reliability is recalculated according to the corresponding values of the sub-reliability soccor cred and socbasecocltime under the above five correction timings.
The SOC final value estimation method of the present embodiment is as follows: when any one of the above correction occasions is triggered, further calculating an SOC final value according to the corrected SOC correction value soccor of the current correction occasion, the corrected sub-reliability credsoc of the current correction occasion and the total SOC at the current correction occasion, and finally determining that a certain seed SOC correction occasion is enabled according to the total SOC reliability, wherein the total SOC can be obtained by ampere-hour integration, and the expression of the SOC final value is as follows:
wherein: SOCCorr is the corrected SOC correction value for the current correction opportunity, credSOCCorr is the corrected sub-confidence of the current correction opportunity, SOC Total (S) Is the total SOC at the current corrective opportunity.
The sub-confidence level soccor cred in this embodiment has the same meaning as the sub-confidence level credsoc.
If the correction timing condition is satisfied, the correction is started, and when the difference between the final SOC and the total SOC is greater than the set difference, the correction can be cut into several small corrections (for example, 5 times), and the difference is corrected by 0.2 times each time, and the correction is performed once every 3 minutes. Taking the correction of the SOC by a dynamic terminal voltage Ucell-SOC correction method as an example, calculating the difference between the pre-correction SOC and the post-correction SOC, dividing the difference into 5 equal parts, correcting the pre-correction SOC value by 20% of the difference every 3 minutes, correcting the pre-correction SOC value to the post-correction SOC value slowly every 3 minutes to obtainThe condition that the SOC value of the battery changes at the correcting moment in the using process is prevented, and bad experience is caused to a user.
Where n is the number of times the difference correction can be cut (n=1, 2,3,4,5 in this embodiment), and socread (t) is the SOC actually displayed to the user after several small corrections; SOCCorr (t) is the corrected SOC final value; SOCCred is the reliability of the correction, the range is 0-100, and the larger the SOCCred is, the larger the reliability is; SOCReal (t-1) is the SOC calculated before correction; and the SOCByUcell corrects the SOC according to the dynamic terminal voltage Ucell-SOC correction method under the correction opportunity.
Total SOC correction enable strategy in this embodiment: and obtaining the total SOC through ampere-hour integration and an OCV-SOC table lookup, obtaining corresponding sub-correction values SOCCorr and sub-credibility CredSOCCorr under different sub-SOC correction occasions, and finally determining whether the sub-SOC correction occasion is enabled or not according to the total SOC credibility.
The corrective enabling strategy in this embodiment is specifically illustrated by way of example below:
when the BMS system is powered on, the total SOC and the total credibility CredSOC (same as SOCCred) are calculated, and the correction value SOCCorr and the sub-credibility CredSOCCorr (same as SOCCorrCred) at each correction time are calculated.
If the calculation result shows that the total SOC is 61% and the total reliability CredSOC is 95%, the correction value SOCCorr at a certain correction time (for example, the middle OCV-SOC lookup table is 60%. Ltoreq.SOC is less than 70%, the correction time) is 67% and the sub-reliability CredSOCCorr is 90%, because 90% (CredSOCCorr) is less than 95% (CredSOC), the correction is not enabled and the total SOC value is not updated.
If the calculation result shows that the total SOC is 61% and the total reliability CredSOC is 88%, the corrected value soccor at a certain correction time (for example, middle OCV-SOC lookup table, 60%. Ltoreq.soc.ltoreq.70%, correction time) is 67% and the sub-reliability CredSOC is 90%, because 90% (CredSOC) is greater than 88% (CredSOC), the correction is enabled, and the total SOC value is updated once:
。
if the calculation result shows that the total SOC is 72% and the total reliability CredSOC is 94%, the correction value SOCCorr at a certain correction time (for example, the dynamic voltage middle section Ucell-SOC lookup table is 60% or less and the SOC is 70% or less, the correction time) is 62% and the sub-reliability CredSOCCorr is 90%, because 90% (CredSOCCorr) is less than 94% (CredSOC), the correction is not enabled and the total SOC value is not updated.
If the calculation result shows that the total SOC is 72% and the total reliability CredSOC is 85%, the corrected value soccor is 62% and the sub-reliability CredSOC is 88% at a certain correction time (for example, the middle OCV-SOC table is searched for, 60%. Ltoreq.soc is not more than 70%, the corrected value soccor is updated once because 88% (CredSOC) is greater than 85% (CredSOC), and the corrected value is enabled once:
。
and estimating the SOC under the insufficient standing working condition, and if the standing time required by the correction time is smaller than a set time threshold value based on the correction conditions of the five correction times, estimating the OCV by using the SOC, the standing time and the dynamic terminal voltage before correcting the SOC, and determining the correction SOC under the current correction time according to the estimated OCV and an OCV-SOC table.
Underlaying conditions estimate SOC:
and when the BMS system is in static dormancy or small-current equivalent static, but is not fully static (if the static time does not meet the sufficient static condition of more than or equal to 3 hours), the OCV can be estimated according to the static time and the dynamic terminal voltage, so that the OCV-SOC correction is realized.
1) If the chip supports floating point multiply-divide and exponential operation and has stronger computing capacity, the OCV prediction can be realized by using a data fitting method;
2) If the chip does not support floating point multiply-divide, exponential operation or slower speed, OCV prediction can be realized by using a table look-up method. OCV, SOC, time of standing, dynamic terminal voltage make up array table.
The data fitting method realizes OCV prediction:
the fitting identification model is as follows:。
wherein: OCV_k is the ratio of the dynamic terminal voltage to OCV, x is the rest time, U0, a1, a2, b1, b2 are the identification parameters to be fitted.
By using the measurement data OCV, the standing time and the dynamic terminal voltage of the laboratory, a set of relatively excellent identification parameters to be fitted are obtained by using a fitting identification model in corresponding software (for example MATLAB, etc.), as shown in fig. 2, u0=1, a1= 0.007868, a2=1.978, b1= 0.004824, b2=76.3, and the obtained set of parameters are brought into the fitting model, so as to obtain a curve as shown in fig. 3, wherein the specific formula of the curve is as follows:
。
if the chip supports floating point multiply-divide and exponential operation and has stronger computing capability, the OCV prediction can be realized by using the formula OCV_k, the corresponding value of the OCV_k is obtained according to the x standing time, and then the corresponding OCV is obtained according to the corresponding value of the OCV_k, wherein the relationship between the OCV_k, the OCV and the dynamic terminal voltage is as follows:
OCV=Ub/OCV_k
wherein: ub is the terminal voltage acquired in real time.
If the chip does not support floating point multiplication and division, exponential operation or has slower speed, the data calibration of the OCV, the SOC, the standing time and the dynamic terminal voltage can be carried out by utilizing experimental data, and the OCV prediction is realized by using a table look-up method according to an array table of the data calibration. The ocv_k, SOC, and settling time composition array table is shown in fig. 4.
The x-axis in FIG. 4 is the rest time, minutes; the y-axis is SOC (percent); the data in the middle are the ratio: ocv=ub/ocv_k, where Ub is the terminal voltage acquired at different rest times when experimentally calibrated;
the specific application is as follows: after the BMS wakes up and powers up, the standing time Slee can be obtained through a clock system or a timing modulepTime, the same as the acquisition module acquires the real-time dynamic terminal voltage Ucell, the table is used for looking up the table, the input SleepTime, SOC is used for looking up the table to acquire the output ratio OCV_k, and finally the output ratio OCV_k is obtained according toAnd obtaining a final predicted OCV value.
Based on the estimated OCV, SOCByEstOCV is further estimated by using a table look-up method according to the OCV-SOC table. And determining that the sub-reliability of the SOC under the correction time is 99% (range 0-100%) according to the test data.
According to the estimated SOCByEstOCV, the sub-credibility credsobbyestocv (0-100, the larger the value, the higher the credibility) of the correction method is finally calculated, and fig. 5 shows the corresponding relationship between the SOCByEstOCV and the sub-credibility credsobbyestocv under different standing time conditions.
As shown in fig. 5, the sub-reliability of the SOC at the correction timing of 99% refers to the highest sub-reliability of the SOC obtained by the OCV-SOC lookup table, such as the sub-reliability of the SOC at the correction method of 99% when the SOC is completely stationary (the stationary time exceeds 180 minutes) and at the low stage of the SOC (SOC < 3%).
The initial value of the SOC in this embodiment is mainly calculated from SOCByNvm (obtained by reading the SOC value stored by EEPRON before last sleep), OCV-SOC lookup table, SOCByEstOCV, and sub-confidence credsockyestocv.
After the BMS wakes up and is electrified, the SOC is calculated 0 The initial value is calculated according to the real-time dynamic terminal voltage OCV_k and the OCV, then the corrected value Ucell of the corresponding SOC and the corresponding sub-reliability CredSOCByEstOCV (converted into 0-1) are obtained according to the OCV and the OCV-SOC table lookup, and finally the SOC is obtained 0 Initial value. The specific calculation formula is as follows:
。
and obtaining the total SOC under the insufficient standing working condition by the obtained initial value of the SOC and the ampere-hour integration method, and then calculating to obtain the final value of the SOC by using the total SOC error reliability estimation model and the correction enabling strategy of the SOC.
In the prior art, the initial value correcting time of the SOC is only the working conditions that the battery is in a static condition, the battery SOC is fully charged or fully discharged, and the low section and the high section of the OCV-SOC lookup table are adopted, and the initial value correcting time of the SOC in the embodiment is increased by the initial value correcting time of the OCV-SOC of which the battery SOC is in the middle section.
Middle OCV-SOC correction: when correcting an initial value of the SOC by an OCV-SOC table lookup method, a non-platform phase is generally selected, namely a low segment and a high segment of the OCV-SOC table lookup, wherein the low segment is a data segment when the SOC is more than or equal to 0 and less than or equal to 25%, the high segment is a data segment when the SOC is more than or equal to 98% and less than or equal to 100%, the two data segments have a certain mapping relation with the SOC, the distinction degree is large, and the two segments of data are used for correcting the initial value of the SOC; however, for the correction conditions of full charge and full discharge of the battery after sufficient standing are relatively less, in order to increase the time for correcting the initial value of the SOC by the OCV-SOC table lookup method, as shown in FIG. 6, experimental data research shows that the middle-stage OCV-SOC has a certain mapping relation between the OCV and the SOC when the SOC is more than or equal to 60% and less than or equal to 70%, and the degree of distinction is relatively larger, so that the embodiment increases the time for correcting the middle-stage OCV-SOC.
In addition, in this embodiment, the middle dynamic terminal voltage Ucell-SOC correction is also added: when the SOC is more than or equal to 60% and less than or equal to 70%. The working condition of the battery system is relatively stable during charging (SOP and a thermal management strategy are determined), the charging current is smaller (less than 1C), and the real-time terminal voltage Ucell and the SOC have a mapping relation, so that SOCByUcell can be estimated according to a dynamic terminal voltage Ucell-SOC correction method, and SOC estimation accuracy is provided. The correction confidence level soccor cred is 88%. On the premise of meeting other conditions, SOCCorrCred is less than or equal to 88% and can be corrected.
FIG. 7 shows a special three-dimensional array, wherein part of the inputs are multidimensional, but the x-axis of the output is the value of a one-dimensional array table, and the x-axis is the SOC and is 0-100%; the y-axis is the system average temperature; the Z axis is the system current, and the unit is represented by current multiplying power C; the value in the middle of the array table is the dynamic terminal voltage Ucell, and the unit is 0.1mV. According to the sub-correction SOC value SOCByUcell obtained by the dynamic terminal voltage Ucell under the condition of a certain temperature and a small current in FIG. 7.
In FIG. 8, the x-axis is SOCByUcell, 0-100%; the y-axis is the system current, the unit is represented by current multiplying power C; the value of the array table is the SOC sub-reliability value, and the value is 0-100. The SOC sub-reliability value credsucbyucell for this sub-correction opportunity obtained from fig. 8.
According to the scheme, the BMS system is subjected to standing dormancy or small-current equivalent standing, but is not fully subjected to standing (if the standing time is not more than 3h, and the sufficient standing condition is not met), and the OCV can be estimated according to the SOC, the standing time and the dynamic terminal voltage, so that OCV-SOC correction is realized. Solves the problem of lack of long-time standing dormancy OCV-SOC correction opportunities.
According to the scheme, the correction time of the middle-section OCV-SOC lookup table is increased, the SOC is more than or equal to 60% and less than or equal to 70%, the final SOC value is finally obtained comprehensively through the correction value SOCCorr and the sub-credibility CredSOCCorr, and the problem of less OCV correction opportunities is solved on the premise of ensuring the SOC precision.
According to the scheme, the correction time of the intermediate Ucell-SOC dynamic end voltage lookup table is increased, the SOC is more than or equal to 60% and less than or equal to 70%, the final SOC value is finally obtained comprehensively through the correction value SOCCorr and the sub-credibility CredSOCCorr, and the problem of low SOC correction opportunity is solved on the premise of ensuring the SOC correction precision.
Vehicle embodiment:
the vehicle in this embodiment adopts a method for estimating the electric quantity SOC of the lithium iron phosphate battery hybrid vehicle, which is sufficiently clear as described in the method embodiment, and will not be described here again.
Claims (7)
1. A method for estimating the electric quantity SOC of a lithium iron phosphate battery hybrid vehicle, comprising the steps of: when any SOC correction time is met, acquiring the total SOC and the total credibility under the current correction time; judging whether the sub-credibility corresponding to the current correction time is greater than the total credibility, if so, correcting the current SOC at the correction time to obtain an SOC correction value, and estimating an SOC final value based on the SOC correction value, the total SOC and the sub-credibility corresponding to the current correction time; if not, correcting the SOC at the moment; wherein the total reliability is related to the number of capacity cycles last corrected to the moment, and the larger the number of capacity cycles last corrected to the moment is, the smaller the total reliability is;
the relation between the total credibility and the capacity cycle times from the last correction to the moment is as follows:
wherein: SOCCorrctCyclTimes is the number of capacity cycles from last correction to the moment, SOCCred is the credibility;
the expression of the capacity cycle times from the last correction to the moment is as follows:
wherein: SOCCorrctCyclTimes is the number of capacity cycles last corrected to that moment; SOCCorrCred represents sub-credibility at different SOC correction occasions; socbasecocltimes represents a reference value of the number of capacity cycles converted from the last correction to the moment at which the different SOC correction timings are corrected; CN is the calibration value of the capacity; i is the absolute value of the battery current; k is charge-discharge efficiency.
2. The method of estimating a battery state of charge, SOC, of a lithium iron phosphate battery hybrid vehicle of claim 1, wherein the final value of SOC is expressed as:
wherein: SOCCorr is the corrected SOC correction value for the current correction opportunity, credSOCCorr is the corrected sub-confidence of the current correction opportunity, SOC Total (S) Is the total SOC at the current corrective opportunity.
3. The method for estimating an SOC of a lithium iron phosphate battery hybrid vehicle according to claim 1, wherein if the required rest time at the correction timing is less than the set time threshold, the OCV is estimated by using the SOC, the rest time, and the dynamic terminal voltage before correcting the SOC, and the corrected SOC at the current correction timing is determined based on the estimated OCV and the OCV-SOC table.
4. The method for estimating an electric quantity SOC of a lithium iron phosphate battery hybrid vehicle according to claim 3, wherein ratios of the OCV and the dynamic terminal voltage in different standing times and different SOC states are measured to form an OCV estimation model table for estimating the OCV.
5. The method for estimating an SOC of a lithium iron phosphate battery hybrid vehicle of claim 4, wherein the OCV estimation model is obtained by fitting data in an OCV estimation model table, and the OCV at the current SOC correction opportunity is estimated using the OCV estimation model.
6. The method for estimating an electric quantity SOC of a lithium iron phosphate battery hybrid vehicle according to claim 1, wherein when the difference between the final SOC and the total SOC is greater than a set difference, correction is performed in several times, and a part of the difference is corrected at regular intervals until the difference correction is completed.
7. A vehicle using the method of estimating the SOC of a lithium iron phosphate battery hybrid vehicle, wherein the method of estimating the SOC of a lithium iron phosphate battery hybrid vehicle according to any one of claims 1 to 6 is employed when the vehicle displays the SOC.
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