CN112083347B - Screening method for power batteries of electric vehicles - Google Patents
Screening method for power batteries of electric vehicles Download PDFInfo
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- CN112083347B CN112083347B CN202010843021.5A CN202010843021A CN112083347B CN 112083347 B CN112083347 B CN 112083347B CN 202010843021 A CN202010843021 A CN 202010843021A CN 112083347 B CN112083347 B CN 112083347B
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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
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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
- G01R31/005—Testing of electric installations on transport means
- G01R31/006—Testing of electric installations on transport means on road vehicles, e.g. automobiles or trucks
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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]
- G01R31/3644—Constructional arrangements
- G01R31/3648—Constructional arrangements comprising digital calculation means, e.g. for performing an algorithm
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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]
- G01R31/385—Arrangements for measuring battery or accumulator variables
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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
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- General Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Engineering & Computer Science (AREA)
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- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
The invention relates to a screening method of an electric automobile power battery, which comprises the following steps: acquiring working data of a power battery of each electric automobile; selecting basic data for consistency judgment; reading a plurality of pieces of basic data; for each piece of basic data, calculating the voltage standard deviation of each single battery in the power battery; fitting the standard deviation of the voltage of each single battery in the corresponding power battery and the mileage of each electric automobile to obtain a fitting straight line; for each electric automobile, recording the slope and intercept of a corresponding fitting straight line as an inconsistency trend vector of the electric automobile; searching an inconsistent trend vector of the outlier; there is a problem in determining the consistency of the power batteries of the electric vehicle to which the outlier inconsistency trend vector corresponds. The invention can more accurately screen the power battery and the corresponding electric automobile with consistency problems, and is convenient to implement.
Description
Technical Field
The invention belongs to the technical field of power battery attribute analysis, and particularly relates to a method for diagnosing and screening power battery inconsistency.
Background
In order to meet the energy requirement of the electric automobile, the power battery pack often needs to be composed of tens to thousands of single batteries, is influenced by the complexity of the system, has unique behaviors, and can obtain the performance of the battery pack without simply adding and subtracting the single batteries. Taking a common battery pack formed by series connection and parallel connection as an example, the single batteries in all battery packs should be completely consistent under ideal conditions, but in practice, even single batteries produced in the same batch still have performance differences (including factors such as capacity and internal resistance), although screening can be performed before the battery packs are formed, 100% consistency of the performance of all batteries still cannot be ensured. In addition, the heat dissipation characteristics of different parts are also greatly different due to the influence of the volume of the battery pack, so that the battery pack also has a large temperature gradient in temperature distribution. These factors may lead to inconsistent rates of degradation of the cells within the stack during use, which may lead to reduced usable capacity of the stack (limited by the minimum capacity of the series cells in the stack), and may lead to reduced stack safety. Research shows that even though the cycle life of a single battery can reach more than 1000 times, when the battery pack is formed, if the battery pack is not protected by equalization equipment, the cycle life of the battery pack may be less than 200 times, so that the consistency of the single battery is a very important parameter for the battery pack, and further, how to find out the battery pack with the inconsistency problem in a plurality of power battery packs is a problem to be solved, and for an electric automobile using the power battery pack, it is very important to quickly find out vehicles with the inconsistency problem in vehicles of the same vehicle type.
Currently, the main indicator representing the cell inconsistency is the voltage difference, i.e. the voltage of the cell with the highest voltage in the battery minus the voltage of the cell with the lowest voltage in the battery. This index has certain limitations, and no obvious trend of change is seen in real vehicle data. Thus, it is difficult to predict and characterize the trend of the battery inconsistency. Therefore, it is difficult to find out which vehicles have a problem in the vehicle due to the index of the light-to-pressure difference.
Disclosure of Invention
The invention aims to provide a power battery screening method capable of accurately screening power batteries with consistency problems and electric automobile power batteries corresponding to electric automobiles.
In order to achieve the above purpose, the invention adopts the following technical scheme:
the electric automobile power battery screening method is used for screening a plurality of power batteries with inconsistencies from power batteries of V electric automobiles, and comprises the following steps of:
step 1: acquiring working data of a power battery of each electric automobile within the same time length;
step 2: screening basic data for consistency judgment from the working data according to the set screening conditions;
step 3: reading a plurality of pieces of basic data, wherein each piece of basic data at least comprises the mileage of one electric automobile and the voltage of a single battery in the corresponding power battery;
step 4: for each piece of basic data, calculating the voltage standard deviation of each single battery in the power battery, so as to obtain a plurality of groups of fitting points corresponding to each electric automobile, wherein the coordinates of each fitting point are the mileage of the electric automobile and the voltage standard deviation of each single battery in the power battery;
step 5: fitting the voltage standard deviation of each single battery in the corresponding power battery and the mileage of the electric automobile to obtain a fitting straight line;
step 6: for each electric automobile, recording the slope and intercept of the corresponding fitting straight line as the inconsistency trend vector;
step 7: searching an outlier inconsistent trend vector from inconsistent trend vectors corresponding to each electric automobile;
step 8: determining the consistency of the power batteries of the electric vehicle corresponding to the outlier inconsistency trend vector is problematic.
In the step 1, the electric vehicles have the same vehicle type.
In the step 2, the screening conditions include an operating current, an operating temperature and mileage.
In the step 2, basic data of which the working current is not 0, the working temperature is 20-35 ℃ and the mileage is 10000-50000 km are screened out.
In the step 3, v×n pieces of the basic data are read, and each electric vehicle correspondingly reads N pieces of the basic data, where N is a positive integer.
In the step 5, the fitted straight line is sigma n ＝k v *L n +b v Wherein σ is n For each of the power cellsStandard deviation of voltage, k of the single battery v For the slope of the fitted line, L n B, mileage of the electric automobile v For the intercept of the fit line, the variance of all the fit points from the fit line is minimized.
In the step 7, an isolated forest algorithm is used for searching the inconsistent trend vector of the outlier.
The electric automobile power battery screening method is realized by an execution system communicated with each electric automobile.
Due to the application of the technical scheme, compared with the prior art, the invention has the following advantages: the invention can more accurately screen the power battery and the corresponding electric automobile with consistency problem, and does not need to establish a test database in advance as a reference standard, thereby being convenient to implement.
Drawings
Fig. 1 is a flowchart of the screening method of the power battery of the electric automobile.
Detailed Description
The invention will be further described with reference to examples of embodiments shown in the drawings.
Embodiment one: as shown in fig. 1, an electric vehicle power battery screening method for screening a plurality of power batteries with inconsistency from power batteries of V (V is generally an integer greater than or equal to 3) electric vehicles includes the following steps:
step 1: and acquiring working data of the power batteries of each electric vehicle in the same time length in the V electric vehicles of the same vehicle type, wherein the working data must contain the voltage of each single battery in the power batteries and the mileage of the electric vehicle.
Step 2: and screening basic data for consistency judgment from the working data according to the set screening conditions. In this step, the screening conditions include operating current, operating temperature, and mileage. Basic data with working current not 0, working temperature 20-35 deg.c and mileage 10000-50000 km are usually screened out.
Step 3: reading a plurality of basic data, each of whichThe basic data at least comprises mileage of one electric automobile and voltage of a single battery in a corresponding power battery, so that the read basic data cover each electric automobile. Usually, N (N is a positive integer) basic data are read, i.e. N basic data are read for each electric vehicle, and for a certain electric vehicle, the N basic data include mileage L n And the voltage of each corresponding single battery under the mileage.
Step 4: for each piece of basic data, the voltage standard deviation of each single battery in the power battery is calculated respectively, namely, for the v (v E [0, V)]) The voltage sigma of the single battery in the power battery can be obtained from the nth basic data of the electric vehicle n Each electric automobile can obtain data corresponding to the voltage standard deviation of each single battery in the power batteries in N groups of mileage, so that a plurality of groups of fitting points corresponding to each electric automobile are respectively obtained, and the coordinates of each fitting point are the mileage of the electric automobile and the voltage standard deviation of each single battery in the corresponding power battery.
Step 5: and fitting the standard deviation of the voltage of each single battery in the corresponding power battery and the mileage of each electric automobile to obtain a fitting straight line. In this step, the fitted straight line is sigma n ＝k v *L n +b v Wherein σ is n Is the standard deviation, k of the voltage of each single battery in the power battery v To fit the slope of a straight line, L n Mileage of electric automobile, b v To fit the intercept of the line, the variance of all fitting points from the fitted line is minimized.
Step 6: for each electric automobile, the slope k of the corresponding fitting straight line is recorded v And intercept b v As its inconsistent trend vector, i.e. for the v-th electric vehicle, its inconsistent trend vector v v ＝[k v ,b v ]。
Step 7: using an isolated forest algorithm, finding an outlier inconsistent trend vector v from inconsistent trend vectors corresponding to each electric automobile o ，o∈[0,V]。
Step 8: determination ofOutlier inconsistency trend vector v o The consistency of the power batteries of the corresponding electric vehicles is problematic, namely, the consistency of the power batteries of the No. o electric vehicle is problematic, and inconsistencies occur.
The electric automobile power battery screening method can be realized by an execution system communicated with each electric automobile.
The above embodiments are provided to illustrate the technical concept and features of the present invention and are intended to enable those skilled in the art to understand the content of the present invention and implement the same, and are not intended to limit the scope of the present invention. All equivalent changes or modifications made in accordance with the spirit of the present invention should be construed to be included in the scope of the present invention.
Claims (7)
1. The utility model provides an electric automobile power battery screening method for select from the power batteries of V electric automobile that there is a plurality of power batteries of inconsistency, its characterized in that: the screening method of the power battery of the electric automobile comprises the following steps:
step 1: acquiring working data of a power battery of each electric automobile within the same time length;
step 2: screening basic data for consistency judgment from the working data according to the set screening conditions;
step 3: reading a plurality of pieces of basic data, wherein each piece of basic data at least comprises the mileage of one electric automobile and the voltage of a single battery in the corresponding power battery;
step 4: for each piece of basic data, calculating the voltage standard deviation of each single battery in the power battery, so as to obtain a plurality of groups of fitting points corresponding to each electric automobile, wherein the coordinates of each fitting point are the mileage of the electric automobile and the voltage standard deviation of each single battery in the power battery;
step 5: fitting the voltage standard deviation of each single battery in the corresponding power battery and the mileage of the electric automobile to obtain a fitting straight line;
step 6: for each electric automobile, recording the slope and intercept of the corresponding fitting straight line as the inconsistency trend vector;
step 7: using an isolated forest algorithm, and finding an outlier inconsistent trend vector from the inconsistent trend vectors corresponding to each electric automobile;
step 8: determining the consistency of the power batteries of the electric vehicle corresponding to the outlier inconsistency trend vector is problematic.
2. The method for screening the power battery of the electric automobile according to claim 1, wherein the method comprises the following steps: in the step 1, the electric vehicles have the same vehicle type.
3. The method for screening the power battery of the electric automobile according to claim 1, wherein the method comprises the following steps: in the step 2, the screening conditions include an operating current, an operating temperature and mileage.
4. The method for screening the power battery of the electric automobile according to claim 3, wherein the method comprises the following steps: in the step 2, basic data of which the working current is not 0, the working temperature is 20-35 ℃ and the mileage is 10000-50000 km are screened out.
5. The method for screening the power battery of the electric automobile according to claim 1, wherein the method comprises the following steps: in the step 3, v×n pieces of the basic data are read, and each electric vehicle correspondingly reads N pieces of the basic data, where N is a positive integer.
6. The method for screening the power battery of the electric automobile according to claim 1, wherein the method comprises the following steps: in the step 5, the fitted straight line is sigma n ＝k v *L n +b v Wherein σ is n For the standard deviation, k of the voltage of each single battery in the power battery v For the inclination of the fitting straight lineRate, L n B, mileage of the electric automobile v For the intercept of the fit line, the variance of all the fit points from the fit line is minimized.
7. The method for screening the power battery of the electric automobile according to claim 1, wherein the method comprises the following steps: the electric automobile power battery screening method is realized by an execution system communicated with each electric automobile.
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| CN110703107B (en) * | 2019-11-05 | 2022-03-08 | 中国第一汽车股份有限公司 | Consistency judgment method, device and equipment for power battery and storage medium |
| CN116381514B (en) * | 2023-06-07 | 2023-08-08 | 广汽埃安新能源汽车股份有限公司 | Cell differential pressure early warning method, device, storage medium and equipment |
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| CN106311634B (en) * | 2016-08-30 | 2018-09-11 | 北京华特时代电动汽车技术有限公司 | Battery modules screening technique and power battery pack screening technique |
| CN109655200B (en) * | 2017-10-12 | 2021-01-29 | 中车株洲电力机车研究所有限公司 | Method and system for diagnosing unbalance of wind wheel of wind generating set |
| CN110045298B (en) * | 2019-05-06 | 2021-05-11 | 重庆大学 | Method for diagnosing parameter inconsistency of power battery pack |
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Patent Citations (5)
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| CN101515022A (en) * | 2008-02-19 | 2009-08-26 | 比亚迪股份有限公司 | Method for evaluating consistency of batteries |
| CN101944638A (en) * | 2010-09-08 | 2011-01-12 | 奇瑞汽车股份有限公司 | Manufacturing method of lithium-ion battery pack used for electric automobile |
| CN103488894A (en) * | 2013-09-23 | 2014-01-01 | 浙江大学 | Method for performance evaluation of vehicle-mounted power batteries of electric automobiles |
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