CN113533979B - Method for judging abnormal battery cell of battery pack - Google Patents
Method for judging abnormal battery cell of battery pack Download PDFInfo
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- CN113533979B CN113533979B CN202110798380.8A CN202110798380A CN113533979B CN 113533979 B CN113533979 B CN 113533979B CN 202110798380 A CN202110798380 A CN 202110798380A CN 113533979 B CN113533979 B CN 113533979B
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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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- 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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- 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 judging abnormal electric cores of a battery pack, which comprises the steps of obtaining voltage data of each electric core at the same time, and obtaining a voltage median U through calculation m And converting the median absolute deviation CMAD; according to the U i 、U m CMAD and a predetermined differential pressure threshold V 0 Obtaining a battery cell marking model for marking the battery cell with different abnormal mark symbols according to the condition relation; marking each section of battery cell in each preset measuring moment by using a battery cell marking model, and determining the total number M of voltage data of all battery cells of the battery pack in each preset measuring moment and the number M of voltage data of each section of battery cell marked with different abnormal mark symbols in each time interval i According to M, total voltage data number threshold M 0 And M i The condition relation between the two is used for determining the abnormal rate P of each section of the electric core marked by different abnormal mark symbols i . The invention solves the consistency problem of the battery pack, eliminates the influence of current on voltage, ensures that the result has comparability and improves the accuracy of the statistical result.
Description
Technical Field
The invention belongs to the technical field of power batteries of electric vehicles, and particularly relates to a method for judging abnormal battery cells of a battery pack.
Background
With the development of the new energy automobile industry, the new energy automobile becomes an indispensable important force in the automobile industry, and the retention capacity of the new energy automobile is larger and larger. As a core component of a new energy automobile, the quality of a power battery is directly related to the safety of the automobile. Along with the rapid development of the new energy automobile industry, the power battery system also makes great progress, but still has some problems to be solved, such as the problem of battery consistency.
The problem of battery consistency refers to that one or more battery cells in a battery pack are aged too fast, liquid leakage and self-discharge current are large due to factors such as battery manufacturing process or improper use, and final capacity, SOC and the like are obviously inconsistent with other battery cells. The consistency of the battery affects not only the range of the vehicle, but also the driving safety of the vehicle if the consistency of the battery does not affect the driving safety of the vehicle.
Therefore, whether the consistency problem of the battery pack occurs or not is judged, and the abnormal battery core is found out, so that the method has great practical significance and economic value.
Disclosure of Invention
The invention aims to provide a method for judging an abnormal battery cell of a battery pack in order to find the battery cell with problems, solve the problem of consistency of a battery pack and improve the driving safety of a vehicle.
The invention realizes the purpose through the following technical scheme:
a method for judging an abnormal battery cell of a battery pack comprises the following judging steps:
s1, measuring the voltage of all the battery cells of the battery pack, and acquiring the voltage data U of each battery cell measured at the same time i (i 1, 2.., N), the voltage median U is obtained by calculation m And converting the median absolute deviation CMAD;
s2, according to the U i 、U m CMAD and a predetermined differential pressure threshold V 0 Obtaining a battery cell marking model for marking the battery cell with different abnormal mark symbols according to the condition relation;
s3, obtaining voltage data of each battery cell in all preset measuring moments in a plurality of time intervals, marking each battery cell in each preset measuring moment by adopting a battery cell marking model, determining the total number M of voltage data of all battery cells of the battery pack in all preset measuring moments in each time interval and the number M of voltage data of each battery cell marked as different abnormal signs in each time interval i According to M, total voltage data number threshold M 0 And M i The condition relation between the two is used for determining the abnormal rate P of each section of the electric core marked by different abnormal mark symbols i ；
S4, according to the abnormal rate P of each battery cell i And an anomaly rate threshold P 0 And determining whether each battery cell is abnormal or not and the abnormal type of each battery cell according to the condition relation.
As a further optimization scheme of the invention, the voltage median U is obtained in step S1 m The calculation method comprises the following steps: for voltage data U i Sorting, respectively removing the highest and lowest values, and calculating the median U of voltage from the residual voltage data m 。
As a further optimized solution of the present invention, in step S1, voltage measurements are performed on all battery cells of the battery pack at the same time, so as to obtain a random variable vector a composed of N voltage scalar observations, where:
calculating the median absolute deviation of A, namely MAD:
MAD (Ai-mean (a)) in which i is 1,2, N;
calculating the absolute deviation of the converted median, namely CMAD as:
CMAD＝c*MAD
wherein
erfcinv is an inverse complement error function.
As a further preferred embodiment of the present invention, in step S2, the method is based on the U i 、U m CMAD and a predetermined differential pressure threshold V 0 The method for obtaining the battery cell marking model of the battery cell marked by different abnormal mark symbols comprises the following steps: calculate U i And U m I.e. the difference in voltage (U) i -U m ) If (U) i -U m ) Greater than k times CMAD, and greater than V 0 Setting the cell abnormality flag to 1; if (U) i -U m ) CMAD which is negative and has an absolute value greater than k times, and greater than V 0 If so, setting the cell abnormity mark to be-1; for the rest of the cases it is,the cell abnormality flag is set to 0.
As a further optimization of the present invention, the abnormality rate P described in step S3 i Including P i + And P i - Said P is i + The abnormal rate of each battery cell with the abnormal mark of 1, P i - For each cell with an abnormal mark of-1, M i Comprising M i + And M i - ，M i + The number of voltage data pieces, M, of each cell with an abnormal mark of 1 in each time interval i - The voltage data number of each section of the battery cell with an abnormal mark of-1 in each time interval is obtained; according to the total voltage data number M and the total voltage data number threshold value M 0 And determining the abnormal rate P of each section of battery cell marked by different abnormal mark symbols through the condition relation among the voltage data numbers marked by the battery cell marking model as the different abnormal mark symbols in all preset measuring moments of each section of battery cell i The method comprises the following steps: obtaining the threshold value M of the number of data pieces higher than the total voltage in each time interval 0 The total number M of the voltage data, and the abnormal rate P of each section of the battery cell i + And P i - ：
As a further optimization scheme of the present invention, in step S4, according to the abnormal rate P of each cell segment i And an anomaly rate threshold P 0 The method for determining whether each battery cell is abnormal and the abnormal type of each battery cell comprises the following steps: for each cell, if P i + >P 0 If the cell has a positive bias abnormality in the corresponding time interval; if P is i - <-P 0 If the cell has negative bias in the corresponding time intervalFrequently; if P is i + -P i - >P 0 If so, the cell has double bias abnormality in the corresponding time interval; otherwise, the cell is not abnormal.
The invention has the beneficial effects that:
1) according to the invention, by comparing the voltage states of different battery cells at the same moment, the influence of current on voltage is eliminated, so that the result has comparability;
2) the method and the device count the voltage abnormal conditions within a period of time, avoid the influence of individual data on the result and improve the accuracy of the statistical result.
Drawings
FIG. 1 is a flow chart of the implementation of the present invention.
Detailed Description
The present application will now be described in further detail with reference to the drawings, it should be noted that the following detailed description is given for illustrative purposes only and is not to be construed as limiting the scope of the present application, as those skilled in the art will be able to make numerous insubstantial modifications and adaptations to the present application based on the above disclosure.
Example 1
As shown in fig. 1, a method for determining an abnormal cell of a battery pack includes the following steps:
s1, measuring the voltage of all the battery cells of the battery pack, and acquiring the voltage data U of each battery cell measured at the same time i (i 1, 2.., N), the voltage median U is obtained by calculation m And converting the median absolute deviation CMAD;
the voltage median U m The calculating method comprises the following steps: for voltage data U i Sorting, respectively removing several highest and lowest values from data, and calculating voltage median U from residual voltage data m ；
And measuring the voltage of all the battery cells of the battery pack at the same moment to obtain a random variable vector A consisting of N voltage scalar observed values, wherein:
calculating the median absolute deviation of A, namely MAD:
MAD-mean (a)), where i ═ 1, 2.., N;
calculating the absolute deviation of the converted median, namely CMAD as:
CMAD＝c*MAD
wherein
erfcinv is the inverse complement error function.
S2, according to the U i 、U m CMAD and a predetermined differential pressure threshold V 0 Obtaining a battery cell marking model for marking the battery cell with different abnormal mark symbols according to the condition relation;
the specific method comprises the following steps: calculate U i And U m Difference of (D), i.e. voltage difference (U) i -U m ) If (U) i -U m ) Greater than k times the converted median absolute deviation CMAD and greater than the differential pressure threshold V 0 Setting the cell abnormality flag to 1; if pressure difference (U) i -U m ) A conversion median absolute deviation CMAD which is negative and has an absolute value greater than k times, and is greater than a pressure difference threshold V 0 If so, setting the cell abnormal flag to-1; for the remaining cases, the cell abnormality flag is set to 0.
S3, obtaining voltage data of each battery cell in all preset measuring moments in a plurality of time intervals, marking each battery cell in each preset measuring moment by adopting a battery cell marking model, determining the total number M of voltage data of all battery cells of the battery pack in all preset measuring moments in each time interval and the number M of voltage data of each battery cell marked as different abnormal signs in each time interval i According to M, total voltage data number threshold M 0 And M i The condition relation between the two is used for determining the abnormal rate P of each section of the electric core marked by different abnormal mark symbols i ；
The abnormality rate P i Including P i + And P i - Said P is i + The abnormal rate of each battery cell with the abnormal mark of 1, P i - The abnormal rate of each battery cell with an abnormal mark of-1 is obtained;
the M is i Comprising M i + And M i - ，M i + The number of voltage data pieces, M, of each cell with an abnormal mark of 1 in each time interval i - The voltage data number of each section of the battery cell with an abnormal mark of-1 in each time interval is obtained;
determining the abnormal rate P of each section of battery cell marked by different abnormal mark symbols i The method comprises the following steps: obtaining a threshold value M higher than the total voltage data number in each time interval 0 The total number M of the voltage data, and the abnormal rate P of each section of the battery cell i + And P i - ：
S4, according to the abnormal rate P of each battery cell i And an anomaly rate threshold P 0 Determining whether each battery cell is abnormal and the abnormal type of each battery cell according to the condition relation; specifically, the method comprises the following steps:
for each cell, if P i + >P 0 ，P 0 If the cell is the abnormal rate threshold, the cell has a positive bias abnormality in the corresponding time interval;
if P is i - <-P 0 If yes, the cell has negative bias abnormity in the corresponding time interval;
if P i + -P i - >P 0 If so, the cell has double bias abnormality in the corresponding time interval;
otherwise, the battery cell is not abnormal in the corresponding time interval.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention.
Claims (4)
1. A method for judging an abnormal battery cell of a battery pack is characterized by comprising the following judging steps:
s1, measuring the voltage of all the battery cells of the battery pack, and acquiring the voltage data U of each battery cell measured at the same time i (i 1, 2.., N), the voltage median U is obtained by calculation m And converting the median absolute deviation CMAD;
s2, according to the U i 、U m CMAD and a predetermined differential pressure threshold V 0 Obtaining a battery cell marking model for marking the battery cell with different abnormal mark symbols according to the condition relation;
s3, obtaining voltage data of each battery cell in all preset measuring moments in a plurality of time intervals, marking each battery cell in each preset measuring moment by using a battery cell marking model, determining the total number M of voltage data of all battery cells of the battery pack in all preset measuring moments in each time interval and the number M of voltage data of each battery cell marked as different abnormal signs in each time interval i According to M, total voltage data number threshold M 0 And M i The condition relation between the two is used for determining the abnormal rate P of each battery cell marked by different abnormal mark symbols i ；
S4, according to the abnormal rate P of each battery cell i And an anomaly rate threshold P 0 Determining whether each cell core is abnormal and the abnormal type of each cell core according to the condition relation;
wherein according to the U i 、U m CMAD and a predetermined differential pressure threshold V 0 The method for obtaining the battery cell marking model of the battery cell marked by different abnormal mark symbols comprises the following steps: calculate U i And U m Difference of (D), i.e. voltage difference (U) i -U m ) If (U) i -U m ) Greater than k times CMAD, and greater than V 0 Then the cell is put intoThe exception flag is set to 1; if (U) i -U m ) CMAD which is negative and has an absolute value greater than k times, and greater than V 0 If so, setting the cell abnormity mark to be-1; for the remaining situation, setting the cell abnormality flag to 0;
the abnormality rate P described in step S3 i Comprising P i + And P i - Said P is i + The abnormal rate of each section of the battery cell with the abnormal mark of 1, P i - For the abnormal rate of each section of the battery cell with the abnormal mark of-1, M i Comprising M i + And M i - ，M i + The number of voltage data pieces, M, of each cell with an abnormal mark of 1 in each time interval i - The voltage data number of each section of the battery cell with an abnormal mark of-1 in each time interval is obtained; according to the total number M of voltage data and the total number threshold value M of voltage data 0 And determining the abnormal rate P of each section of battery cell marked by different abnormal mark symbols through the condition relation among the voltage data numbers marked by the battery cell marking model as the different abnormal mark symbols in all preset measuring moments of each section of battery cell i The method comprises the following steps: obtaining a threshold value M higher than the total voltage data number in each time interval 0 The total number M of the voltage data, and the abnormal rate P of each section of the battery cell i + And P i - ：
2. The method for judging the abnormal battery cell of the battery pack according to claim 1, wherein: the voltage median U in step S1 m The calculation method comprises the following steps: for voltage data U i Sorting, respectively removing the highest and lowest ones of the dataDry value, calculating the median U of the voltage from the residual voltage data m 。
3. The method for judging the abnormal battery cell of the battery pack according to claim 2, wherein: in step S1, voltage measurements are performed on all the battery cells of the battery pack at the same time, so as to obtain a random variable vector a composed of N voltage scalar observations, where:
calculating the median absolute deviation of A, namely MAD:
MAD ═ medium (Ai-medium (a)) |, where i ═ 1,2,. ang., N;
calculating the absolute deviation of the converted median, namely CMAD as:
CMAD＝c*MAD
wherein
erfcinv is an inverse complement error function.
4. The method for judging the abnormal battery cell of the battery pack according to claim 1, wherein: in step S4, according to the abnormal rate P of each cell i And an anomaly rate threshold P 0 The method for determining whether each battery cell is abnormal and the abnormal type of each battery cell comprises the following steps: for each cell, if P i + >P 0 If the cell has a positive bias abnormality in the corresponding time interval; if P is i - <-P 0 If yes, the cell has negative bias abnormity in the corresponding time interval; if P is i + -P i - >P 0 If so, the cell has double bias abnormality in the corresponding time interval; otherwise, the battery cell has no abnormality.
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| CN114415054B (en) * | 2022-01-27 | 2022-10-11 | 中国汽车工程研究院股份有限公司 | New energy automobile battery sampling abnormal fault identification method |
| CN115015768B (en) * | 2022-08-10 | 2022-11-11 | 力高(山东)新能源技术股份有限公司 | Method for predicting abnormal battery cell of battery pack |
| CN116106757A (en) * | 2022-12-06 | 2023-05-12 | 北汽福田汽车股份有限公司 | Battery cell detection method and device, storage medium and electronic equipment |
| CN116338474B (en) * | 2023-05-29 | 2023-08-04 | 力高(山东)新能源技术股份有限公司 | Method for judging consistency of sodium ion batteries |
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