CN114624600A - Power battery cell capacity difference calculation method and computer readable storage medium - Google Patents
Power battery cell capacity difference calculation method and computer readable storage medium Download PDFInfo
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- CN114624600A CN114624600A CN202210067474.2A CN202210067474A CN114624600A CN 114624600 A CN114624600 A CN 114624600A CN 202210067474 A CN202210067474 A CN 202210067474A CN 114624600 A CN114624600 A CN 114624600A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
- G01R31/3842—Arrangements for monitoring battery or accumulator variables, e.g. SoC combining voltage and current measurements
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
Abstract
The invention discloses a method for calculating the capacity difference of a power battery cell and a computer readable storage medium, which solve the problems of low accuracy and large algorithm difficulty in calculating the capacity difference of the power battery cell in the prior art, and comprise the following steps: acquiring battery data reported by a vehicle; intercepting charging data of a vehicle; substituting the average temperature of the battery into an inflection point voltage formula to obtain the inflection point voltage of the charging curve at the temperature; acquiring corresponding vehicle-mounted machine time when the highest voltage of the single body and the lowest voltage of the single body successively reach the inflection point voltage; and calculating the charging amount of the battery system in the time difference by combining the current data, namely the cell capacity difference of the battery system. The invention can calculate only by charging the vehicle once according with the condition, and the result is accurate; the time difference when the battery core reaches the inflection point of the charging curve is calculated through the vehicle charging curve, and then the capacity difference between the battery cores is calculated according to the time difference, so that the algorithm complexity is low, and the method is more suitable for large-batch calculation and analysis of battery big data in an actual scene.
Description
Technical Field
The invention relates to the technical field of power batteries, in particular to a method for calculating the capacity difference of a power battery cell and a computer-readable storage medium.
Background
Due to rapid development of the industry and enhancement of environmental awareness of people, the electric automobile industry is rapidly developing. The safety problem of the power battery, which is used as a power source for electric vehicles, has been receiving much attention. The inconsistency exists between the single batteries in the battery pack system, and the complex service environment makes the difference of the batteries larger and larger in the operation process, so that the performance of the battery system is reduced, the service life of the battery is reduced, and even the safety problem is caused.
At present, the lithium iron phosphate battery is widely applied to the electric automobile industry by virtue of the advantages of low cost and good safety performance, but due to the characteristics of the lithium iron phosphate battery, the SOC value of the battery cell is difficult to calculate accurately, and the accuracy of judging the capacity difference of the battery cell in the battery system by calculating the SOC deviation is not high.
In the prior art, the cell capacity difference is mainly calculated by calculating the SOC of a single cell, and methods for calculating the SOC mainly include an open circuit voltage method (SOC-OCV), an ampere-hour integration method, a kalman filter method, a neural network method, and the like. Open circuit voltage requires long battery stand. The SOC accumulated error calculated by the ampere-hour integration method is larger and larger; the application cost of the Kalman filtering method and the neural network method is high.
Specifically, the method comprises the following steps: 1) calculating the SOC value of the battery cell by adopting an SOC-OCV method, namely calculating the SOC values of the highest monomer voltage and the lowest monomer voltage by using the static voltage of the lithium iron phosphate battery cell voltage in a non-platform area, and calculating the SOC deviation of the highest monomer voltage and the lowest monomer voltage to obtain the battery cell capacity difference of the power battery system; the method has the advantages that the platform area range of the voltage of the lithium iron phosphate core is large, the non-platform area is mostly positioned in a low SOC (state of charge) area, but the low SOC cannot be achieved when most vehicles are used; the SOC-OCV method needs to use static voltage, namely the voltage of a battery cell in a stable state, and the battery cell generally needs to stand for more than 6-12 hours. The two conditions are too harsh, and it is difficult to effectively judge the cell capacity difference of the battery system. 2) Fitting by adopting a sigmoid function through a charging curve of the lithium ion battery module, and calculating an SOC value corresponding to the inflection point of a charging SOC voltage curve according to fitting parameters; the defect is that the SOC deviation is judged by calculating the SOC value of the battery cell essentially, the difficulty of estimating the SOC by the lithium iron phosphate is high, and the accuracy rate of the SOC deviation is closely related to the fitting effect of a function; the online fitting of the function occupies more memory resources.
Disclosure of Invention
The technical problems to be solved by the invention are as follows:
the capacity difference of the single batteries of the power battery system is larger and larger in the using process, and due to the short plate effect, the performance of the battery system is reduced, the service life attenuation of the batteries is aggravated, and even the safety problem is caused;
the traditional method for judging the capacity difference between the battery cores is to calculate the SOC value of each single battery and then calculate the SOC deviation of the single batteries to obtain the capacity difference. However, due to the characteristics of the lithium iron phosphate battery cell (the platform area range of the lithium iron phosphate battery cell is large), the calculation of the SOC of the lithium iron phosphate battery cell is always a difficult point in the technical field of batteries. Therefore, the accuracy of determining the cell capacity difference of the battery system by calculating the SOC value is not high.
The invention provides a method for calculating the capacity difference of a power battery cell and a computer readable storage medium, which only need to substitute a formula according to the battery temperature during charging to calculate and obtain the voltage value of an inflection point, have small algorithm complexity, do not need to calculate the SOC value of the cell, and are more suitable for large-batch calculation and analysis in battery big data.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for calculating the capacity difference of a power battery cell comprises the following steps:
s1, acquiring battery data reported by a vehicle;
s2, intercepting the charging data of the vehicle;
s3, substituting the average temperature of the battery into an inflection point voltage formula to obtain the inflection point voltage of the charging curve at the temperature;
s4, obtaining corresponding vehicle-mounted machine time when the highest voltage of the single body and the lowest voltage of the single body successively reach the inflection point voltage;
and S5, calculating the charging amount of the battery system in the time difference by combining the current data, namely the cell capacity difference of the battery system.
According to the invention, the battery cell capacity difference of the battery system is calculated by screening the vehicle charging data, and the judgment is carried out without considering that the residual capacity of the vehicle reaches a low SOC interval and the static voltage is required. The cell capacity difference in the battery system can be calculated through the charging data of the vehicle only through the vehicle charging behavior. The threshold for calculating the capacity difference between the electric cores is greatly reduced.
Although the calculation is also performed according to the vehicle charging data, the essence of the invention is different from the two schemes described in the background art, and the invention does not need to calculate the value of the cell SOC, so the estimation deviation of the cell SOC is not considered. Meanwhile, if the sigmoid function is adopted for fitting and inflection point information is calculated according to fitting parameters, the charging curve of each battery system needs to be fitted on line by using the function, so that the method occupies great memory resources and is not suitable for large-batch calculation. The invention only needs to substitute the formula to calculate and obtain the inflection point voltage value according to the battery temperature during charging, and the algorithm complexity is much smaller. The method is more suitable for large-batch calculation and analysis in battery big data.
Preferably, the battery data described in S1 includes the following signals: maximum cell voltage, minimum cell voltage, SOC, current, on-board time, average temperature, and state of charge.
Preferably, S1 includes the following contents:
acquiring battery data reported to the cloud by a vehicle by a computer program in a database query mode;
the power battery system of the vehicle adopts a battery cell which is a lithium iron phosphate battery cell.
Preferably, S2 includes the following contents:
intercepting charging data of the vehicle SOC in a (45%, 80%) interval from the vehicle data acquired in S1;
the charging data needs to satisfy the following conditions:
condition 1: the SOC starting point of the vehicle charging is less than 45%, the SOC end point of the vehicle charging is more than 80%, if the conditions are met, intercepting is carried out, and if the conditions are not met, returning to S1;
condition 2: the vehicle is charged by slow charging, and the slow charging mode adopts constant current charging;
condition 3: the charging data of the battery includes: maximum cell voltage, minimum cell voltage, SOC, current, vehicle time, and average battery temperature.
Preferably, S3 includes the following contents:
after the vehicle data is intercepted at S2, the average temperature value of the battery when the SOC is 45% is obtained, and the average temperature value is substituted into the inflection point voltage formula to obtain the inflection point voltage at the changed temperature.
Preferably, the inflection point voltage formula is y-ax2+bx+c，
Wherein x is the average temperature, y is the inflection point voltage, and a, b, c are inflection point voltage coefficients.
Preferably, S4 includes the following contents:
after the inflection point voltage value is obtained in S3, the time when the highest voltage of the cell reaches the inflection point voltage earliest is searched for and recorded as t1, and similarly, the corresponding vehicle time when the lowest voltage of the cell reaches the inflection point voltage earliest is searched for and recorded as t 2.
Preferably, S5 includes the following contents:
after the vehicle-mounted machine time t1 that the highest voltage of the single body reaches the inflection point voltage earliest and the vehicle-mounted machine time t2 that the lowest voltage of the single body reaches the inflection point voltage earliest are obtained at S4, integration operation is performed by combining current values in time periods t1 and t2 to obtain the charging amount of the battery system in the time period, and then the charging amount is divided by the rated capacity of the battery system to obtain the capacity difference of the battery cell.
Preferably, the cell capacity difference is calculated by using the following formula:
where Ce is the rated capacity of the battery system, t2 is the time when the lowest cell voltage reaches the knee voltage, t1 is the time when the highest cell voltage reaches the knee voltage, and I is the battery current.
A computer readable storage medium adopts the method, the computer readable storage medium stores a computer program, and the calculation of the cell capacity difference is realized through the computer program.
Therefore, the invention has the following beneficial effects: according to the invention, the capacity difference of the battery cell is judged without estimating the SOC of the battery cell and considering the SOC estimation deviation, and the vehicle can be used for calculating only by charging once according with the conditions, so that the result is accurate; the time difference when the battery cell reaches the inflection point of the charging curve is calculated through the vehicle charging curve, and then the capacity difference between the battery cells is calculated according to the time difference, so that the algorithm complexity is low, the memory resource is saved, the calculation can be completed without harsh conditions, the universality is higher, and the method is more suitable for large-batch calculation and analysis of big data.
Drawings
FIG. 1 is a flow chart of the present invention.
Fig. 2 is a cell charging curve for SOC at various temperatures ranging from 0% to 100%.
Fig. 3 is a cell charging curve for SOC between 45% and 80% at different temperatures.
Fig. 4 is a knee voltage curve at different temperatures.
Fig. 5 is a partial data plot.
Fig. 6 is a vehicle cell charging curve.
In the figure: a represents a temperature of 10 degrees, b represents a temperature of 20 degrees, and c represents a temperature of 35 degrees.
Detailed Description
The invention is further described with reference to the following figures and embodiments.
Example (b):
at present, the capacity difference of a battery cell of a battery system is calculated mainly by judging the SOC of the battery cell, but due to the characteristics of the lithium iron phosphate battery, a large error exists in calculating the SOC of the battery cell. If the SOC-OCV method is adopted to calculate the SOC of the battery cell, the calculation error can be reduced to a certain extent, but the conditions are too harsh, and the battery voltage is required to be in a non-plateau region and in a stable state (the battery needs to be kept still for a long time). If other methods such as a function fitting method are adopted, the method occupies excessive memory resources and is not suitable for large data analysis of large-batch vehicles.
Therefore, in the embodiment of the present invention, the vehicle charging curve is intercepted, and the cell capacity difference is calculated by determining and calculating the time difference between the highest cell voltage and the lowest cell voltage when the highest cell voltage and the lowest cell voltage reach the inflection point of the charging curve. The method has low algorithm complexity, and is suitable for battery big data analysis and monitoring and rapid quantitative analysis of consistency abnormity problems
Specifically, the embodiment provides a method for calculating a capacity difference between battery cores of a power battery, as shown in fig. 1, including the following steps:
step 1: obtaining powertrain data for a vehicle a on a day, comprising the following signals: maximum cell voltage, minimum cell voltage, SOC, battery current, vehicle time, average battery temperature, and state of charge.
A partial data curve is shown in fig. 5, where Vmax is the highest cell voltage, Vmin is the lowest cell voltage, SOC represents the SOC curve, and the data table at partial time is shown in table 1:
table 1
Step 2: intercepting charging data of vehicle (SOC 45% -80%)
And intercepting charging data (SOC 45% -80%) of the vehicle from the obtained vehicle battery data, wherein the charging data of the battery comprises the highest cell voltage, the lowest cell voltage, the SOC, the battery current, the vehicle-mounted time and the average battery temperature.
And step 3: after intercepting the charge data of the vehicle at step 2, the average temperature value of the battery when the SOC is 45% is obtained as 24 ℃. Substituting this value into the knee voltage equation yields a knee voltage of 3358mV at this temperature. Wherein the inflection point voltage formula is: y is 0.0373x2-2.52x+3396.5。
And 4, step 4: the vehicle-mounted time when the highest cell voltage and the lowest cell voltage reach the inflection point voltage 3358mv is searched and recorded as t1 and t2, as shown in fig. 6, Vmax in the graph is the highest cell voltage, Vmin is the lowest cell voltage, and an inflection point is arranged on each of the cell charging curves of the highest cell voltage and the lowest cell voltage.
And 5: calculating the charging capacity of the battery system in the time difference by combining the current data, namely the capacity difference between the battery cores of the battery system;
the specific calculation formula is as follows:
wherein Ce is the rated capacity of the battery system, and the rated capacity in this embodiment is 104 Ah; t2 is the time corresponding to the lowest voltage of the monomer reaching the inflection point voltage; t1 is the time when the highest cell voltage reaches the knee voltage, and I is the battery current.
Substituting t1 and t2 into a formula, calculating the ampere-hour charged in the period of time by combining current data, and dividing the ampere-hour by the capacity 104Ah of the battery to obtain the capacity difference.
Solving the following steps:
△SOC＝13.6％
the final capacity difference was 13.6%.
Therefore, the method can realize the calculation of the capacity difference of the battery cell only by acquiring and intercepting the vehicle charging curve without harsh precondition and calculating the SOC of the battery cell, thereby saving various errors caused by the calculation, having quick final calculation process, saving memory resources, realizing mass production, low algorithm complexity and high calculation accuracy.
The present embodiment also provides a computer-readable storage medium, which stores a computer program, and implements the steps of any one of the methods through the computer program.
In the description of the above embodiment, the cell capacity difference may also be understood as a cell SOC deviation. Changes in the generic terms do not affect the definition of technical solutions and protection areas.
The above embodiments are described in detail for the purpose of further illustrating the present invention and should not be construed as limiting the scope of the present invention, and the skilled engineer can make insubstantial modifications and variations of the present invention based on the above disclosure.
Claims (10)
1. A method for calculating the capacity difference of a battery cell of a power battery system is characterized by comprising the following steps:
s1, acquiring battery data reported by the vehicle;
s2, intercepting the charging data of the vehicle;
s3, substituting the average temperature of the battery into an inflection point voltage formula to obtain the inflection point voltage of the charging curve at the temperature;
s4, obtaining corresponding vehicle-mounted machine time when the highest voltage of the single body and the lowest voltage of the single body successively reach the inflection point voltage;
and S5, calculating the charging amount of the battery system in the time difference by combining the current data, namely the cell capacity difference of the battery system.
2. The method of claim 1, wherein the battery data in S1 includes the following signals: cell maximum voltage, cell minimum voltage, SOC, current, on-board time, average temperature, and state of charge.
3. The method for calculating the cell capacity difference of the power battery system according to claim 1 or 2, wherein the step S1 comprises the following steps:
acquiring battery data reported to the cloud by a vehicle by a computer program in a database query mode;
the power battery system of the vehicle adopts a battery cell which is a lithium iron phosphate battery cell.
4. The method for calculating the cell capacity difference of the power battery system according to claim 1, wherein S2 includes the following contents:
intercepting charging data of the vehicle SOC in a (45%, 80%) interval from the vehicle data acquired in S1;
the charging data needs to satisfy the following conditions:
condition 1: the SOC starting point of the vehicle charging is less than 45%, the SOC end point of the vehicle charging is more than 80%, if the conditions are met, intercepting is carried out, and if the conditions are not met, returning to S1;
condition 2: the vehicle is charged by slow charging, and the slow charging mode adopts constant current charging;
condition 3: the charging data of the battery includes: maximum cell voltage, minimum cell voltage, SOC, current, vehicle time, and average battery temperature.
5. The method for calculating the cell capacity difference of the power battery system according to claim 1, wherein the step S3 comprises the following steps:
after the vehicle data is intercepted at S2, the average temperature value of the battery when the SOC is 45% is obtained, and the average temperature value is substituted into the inflection point voltage formula to obtain the inflection point voltage at the changed temperature.
6. The method for calculating the cell capacity difference of the power battery system according to claim 5, wherein the inflection point voltage formula is that y-ax2+bx+c，
Wherein x is the average temperature, y is the inflection point voltage, and a, b, c are inflection point voltage coefficients.
7. The method for calculating the cell capacity difference of the power battery system according to claim 1, wherein the step S4 comprises the following steps:
after the inflection point voltage value is obtained in S3, the time when the highest voltage of the cell reaches the inflection point voltage earliest is found and recorded as t1, and similarly, the corresponding vehicle time when the lowest voltage of the cell reaches the inflection point voltage earliest is found and recorded as t 2.
8. The method for calculating the cell capacity difference of the power battery system according to claim 1, wherein the step S5 comprises the following steps:
after the vehicle time t1 that the highest voltage of the single body reaches the inflection point voltage at the earliest and the vehicle time t2 that the lowest voltage of the single body reaches the inflection point voltage at the earliest are obtained in S4, integration operation is performed by combining current values in time periods t1 and t2, the charging amount of the battery system in the time period is obtained, and then the charging amount is divided by the rated capacity of the battery system, so that the capacity difference of the battery core is obtained.
9. The method for calculating the cell capacity difference of the power battery system according to claim 8, wherein the cell capacity difference is calculated by using the following formula:
where Ce is the rated capacity of the battery system, t2 is the time when the lowest cell voltage reaches the knee voltage, t1 is the time when the highest cell voltage reaches the knee voltage, and I is the battery current.
10. A computer-readable storage medium, which employs the method of claim 1, and which stores a computer program, by means of which the calculation of the cell capacity difference is implemented.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115007503A (en) * | 2022-07-19 | 2022-09-06 | 湖北亿纬动力有限公司 | Battery cell sorting method, device, equipment and storage medium |
| CN115629325A (en) * | 2022-10-26 | 2023-01-20 | 上海玫克生储能科技有限公司 | Method, device, medium and equipment for identifying attenuation degree of battery cell |
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- 2022-01-20 CN CN202210067474.2A patent/CN114624600A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115007503A (en) * | 2022-07-19 | 2022-09-06 | 湖北亿纬动力有限公司 | Battery cell sorting method, device, equipment and storage medium |
| CN115007503B (en) * | 2022-07-19 | 2023-07-28 | 湖北亿纬动力有限公司 | Cell sorting method, device, equipment and storage medium |
| CN115629325A (en) * | 2022-10-26 | 2023-01-20 | 上海玫克生储能科技有限公司 | Method, device, medium and equipment for identifying attenuation degree of battery cell |
| CN115629325B (en) * | 2022-10-26 | 2024-01-26 | 上海玫克生储能科技有限公司 | Method, device, medium and equipment for identifying attenuation degree of battery cell |
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