CN116794548A - Battery fault early warning and diagnosing method - Google Patents

Abstract

The invention discloses a battery fault early warning and diagnosing method, which comprises the following steps: acquiring charging history data of a battery system; extracting physical quantity data of all monomers of the charging terminal, wherein the physical quantity data are used for representing the state of a battery; calculating all moments of the charging terminal, ranking, recording and storing physical quantity of each single battery cell for representing the state of the battery; calculating, recording and storing each charging section; ranking the physical quantity of the single battery cells of all the charging sections for representing the battery state; filtering the ranking of the physical quantity of each battery cell for representing the battery state to obtain a ranking curve with time; calculating a change slope K of the physical quantity ranking used for representing the battery state by using the filtered physical quantity ranking used for representing the battery state; drawing a change curve of the slope and time for the obtained slope K; comparing the battery with faults with the battery without faults to obtain a judging threshold value of the slope K; and judging whether the battery fails or not according to the judging threshold K.

Description

Battery fault early warning and diagnosing method

Technical Field

The invention relates to the technical field of power batteries, in particular to a battery fault early warning and diagnosing method.

Background

With the continuous increase of the number of new energy automobiles, the safety problem of the electric automobiles is also more and more prominent. In the use process of the electric automobile, a series of problems such as consistency, thermal runaway, battery attenuation and the like can occur, and the personal and property safety of a user is threatened. However, for serious faults such as internal short circuit, lithium precipitation and thermal runaway of the battery, no effective means and methods for early warning exist at present, and many fault diagnosis and early warning methods are only applicable to experimental test data and do not consider the practical application scene, so that the conditions of false alarm, missing report and the like can occur in fault diagnosis and early warning.

An effective fault diagnosis means is needed to realize early warning and diagnosis of battery faults and guide the use of the battery.

Disclosure of Invention

The present invention provides a solution to at least one technical problem of the prior art.

The embodiment of the invention provides a battery fault early warning and diagnosing method, which comprises the following steps:

step 1: acquiring charging history data of a battery system;

step 2: extracting physical quantity data of all monomers at the charging terminal for representing the battery state from the charging history data;

step 3: calculating all moments of the charging terminal, ranking, recording and storing physical quantity of each single battery cell for representing the state of the battery;

step 4: calculating, recording and storing each charging section according to the step 3;

step 5: ranking the physical quantity of the single battery cells of all the charging sections for representing the battery state according to the time sequence;

step 6: filtering the ranking of the physical quantity of each battery cell for representing the battery state to obtain a ranking curve with time;

step 7: calculating the slope K of the physical quantity ranking used for representing the battery state by utilizing the physical quantity ranking used for representing the battery state and filtered in the step 6;

step 8: drawing a change curve of the slope and time for the slope K obtained in the step 7;

step 9: comparing the battery with faults with the battery without faults to obtain a judging threshold value of the slope K;

step 10: and judging whether the battery fails or not according to the judging threshold K.

Optionally, the battery system comprises a battery with a fault label such as internal short circuit, lithium precipitation or thermal runaway.

Optionally, the physical quantity used for representing the battery state is voltage or electric quantity SOC or energy.

Optionally, when filtering the physical quantity of the single battery core used for representing the battery state after ranking, the adopted filtering mode includes any one of a limiting filtering method, a median filtering method, an arithmetic average filtering method, a smoothing filtering method, a wiener filtering method and a Gaussian filtering method, so as to eliminate abnormal points and fluctuation points.

Optionally, in step 6, a ranking sequence Rij of each cell along with time is obtained, where i is a cell number, the maximum value of i is equal to the total number of cells, i is a natural number, j is the jth time value of the time sequence, and j is a natural number, so as to obtain a matrix of ranking of all cells along with time according to physical quantity used for representing the state of the battery.

Optionally, performing differential calculation on a physical quantity ranking curve of each battery cell for representing the battery state to obtain and store a slope K, wherein a specific calculation formula is as follows:

where i is the cell number, T (j) is the jth time in the time series, and m is the time interval.

Alternatively, the threshold is obtained by:

and drawing a K-T curve of K and time by using the obtained K, and comparing the K-T curve of the battery with internal short circuit, lithium precipitation or thermal runaway faults with the K-T curve of the battery without faults to obtain a threshold A.

Optionally, the determining whether the battery fails according to the determination threshold K includes:

if K is more than or equal to A in the K-T curve, judging that the battery has internal short circuit, lithium precipitation or thermal runaway fault; if K < A, it is determined that the battery system has no fault.

Optionally, according to the above judgment conditions, judging the rest battery modules or systems, and distinguishing the reasons for the failure of the battery system.

In the process of realizing the invention, the inventor finds that various faults can occur in the use process of the battery, and the risk and the frequency of the occurrence of the faults of the battery can be obviously increased along with the extension of the use time of the electric automobile. Most battery faults occur along with obvious voltage (other physical quantities such as electric quantity/energy which can measure the battery state) changes, when the battery has faults, the voltage (other physical quantities such as electric quantity/energy which can measure the battery state) can be abnormally reduced, and further the voltage (other physical quantities such as electric quantity/energy which can measure the battery state) rank can be abnormally reduced, while the voltage of a normal battery cell (other physical quantities such as electric quantity/energy which can measure the battery state) cannot be abnormally reduced. The invention provides a method for extracting fault characteristics of a battery (other physical quantities such as electric quantity/energy and the like capable of measuring the state of the battery) by using battery test or operation data, realizes early warning and diagnosis of faults, and can be used for real vehicle fault assessment and fault cause analysis.

Drawings

In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of a battery fault diagnosis method according to an embodiment of the present invention;

fig. 2a and 2b are schematic K curves of an embodiment of the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without any inventive effort, are intended to be within the scope of the invention.

It should be noted that the terms "comprising" and "having" and any variations thereof in the embodiments of the present invention and the accompanying drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those listed steps or elements but may include other steps or elements not listed or inherent to such process, method, article, or apparatus.

The invention provides a battery fault early warning and diagnosing method, which is realized by the following technical scheme:

1. operation history data of the battery system is acquired.

2. The acquired data needs to include a battery having a failure tag such as an internal short circuit, a resolution, or a thermal runaway.

3. And carrying out data processing on the historical data, screening out charging sections, sequencing the charging sections according to a time sequence, and then extracting all monomer voltage data of the charging tail end from the charging historical data.

4. The voltage rank of each cell is calculated at each instant and arranged in a time sequence.

5. And filtering the voltage ranking of each cell to obtain a ranking curve along with time.

6. The obtained voltage range is arranged according to time sequence and then is subjected to smoothing filtering, wherein the filtering modes comprise a limiting filtering method, a median filtering method, an arithmetic average filtering method, a smoothing filtering method, a wiener filtering method, a Gaussian filtering method and the like, and the purpose of the smoothing filtering method is to eliminate abnormal points and fluctuation points.

7. The slope K of the voltage ranking is calculated as follows:

where i is the cell number, T (j) is the j-th time in the time sequence, and m is the time interval.

8. And drawing a curve (K-T) of K and time, and comparing the K-T curve of the battery with faults such as internal short circuit, lithium precipitation, thermal runaway and the like with the K-T curve of the battery without faults to obtain a threshold value A.

9. According to the obtained threshold A, whether the battery has faults or not can be judged, if K is more than or equal to A in a K-T curve, the battery is considered to have faults such as internal short circuit, lithium precipitation or thermal runaway, and if K is less than A, the battery is considered to have no faults.

10. If more operation history data of the battery system can be obtained to obtain a K-T curve, a threshold A can be used for judging whether the battery has faults or not.

In the implementation process, the voltage can be replaced by electric quantity, energy and other physical quantities which can measure the state of the battery for calculation.

In the embodiment of fig. 1, the following steps are included:

as S101, first, operation history data of the battery system is acquired. Acquisition means include, but are not limited to: historical data stored in laboratory test equipment, historical data generated and stored on running equipment carrying batteries, and storage media such as a background cloud platform for storing data generated by the equipment.

The history data needs to include a battery having a failure flag such as an internal short circuit, a failure due to analysis, or a thermal runaway.

In S102, the stored historical data is calculated for each cell voltage rank using data processing software and arranged in time order. A matrix of all cells according to voltage rank over time can be obtained, as shown in table 1.

TABLE 1

And filtering the voltage ranking of each cell to obtain a ranking curve along with time.

S103, calculating the slope K of the voltage ranking of each cell according to the following formula:

where m is the number of physical quantities, n is the time interval (corresponding to the size of one sliding window), m-n is the number of K values, and T (j) is the jth time in the time series.

If j=50 and n=10 are selected, the calculation of K is performed according to the following formula:

the sequence of slope K of each cell (K (1), K (2) … K (40)) is obtained, and then the K-T curve of each cell is obtained.

In S104, according to the curve (K-T) of K and time T, the K-T curve of the battery with faults such as internal short circuit, lithium precipitation or thermal runaway and the K-T curve of the battery without faults are compared to obtain a threshold A equal to-40, and the threshold A can distinguish the battery with faults such as internal short circuit or lithium precipitation from the battery without faults. As shown in fig. 2a and 2b (fig. 2a and 2b show K-value graphs for individual cells in a battery system of one embodiment).

In S105, it is possible to determine whether or not the battery has a failure based on the obtained threshold a.

Those of ordinary skill in the art will appreciate that: the drawing is a schematic diagram of one embodiment and the modules or flows in the drawing are not necessarily required to practice the invention.

Those of ordinary skill in the art will appreciate that: the modules in the apparatus of the embodiments may be distributed in the apparatus of the embodiments according to the description of the embodiments, or may be located in one or more apparatuses different from the present embodiments with corresponding changes. The modules of the above embodiments may be combined into one module, or may be further split into a plurality of sub-modules.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (9)

1. The battery fault early warning and diagnosing method is characterized by comprising the following steps:

step 1: acquiring charging history data of a battery system;

step 2: extracting physical quantity data of all monomers at the charging terminal for representing the battery state from the charging history data;

step 3: calculating all moments of the charging terminal, ranking, recording and storing physical quantity of each single battery cell for representing the state of the battery;

step 4: calculating, recording and storing each charging section according to the step 3;

step 5: ranking the physical quantity of the single battery cells of all the charging sections for representing the battery state according to the time sequence;

step 6: filtering the ranking of the physical quantity of each battery cell for representing the battery state to obtain a ranking curve with time;

step 7: calculating a change slope K of the physical quantity ranking used for representing the battery state by utilizing the physical quantity ranking used for representing the battery state and filtered in the step 6;

step 8: drawing a change curve of the slope and time for the slope K obtained in the step 7;

step 9: comparing the battery with faults with the battery without faults to obtain a judging threshold value of the slope K;

step 10: and judging whether the battery fails or not according to the judging threshold K.

2. The method of claim 1, wherein the battery system comprises a battery having a fault flag for internal short circuit, lithium precipitation, thermal runaway, or the like.

3. The method according to claim 1, wherein the physical quantity used to characterize the battery state is voltage or charge SOC or energy, etc.

4. The method according to claim 1, wherein when the physical quantities of the individual cells for representing the battery state are ranked and then filtered, the filtering method includes any one of clipping filtering method, median filtering method, arithmetic average filtering method, smoothing filtering method, wiener filtering method and gaussian filtering method, so as to eliminate abnormal points and fluctuation points.

5. The method according to claim 1, wherein in step 6, a ranking sequence Rij of each cell over time is obtained, where i is a cell number, i is a maximum value equal to the total number of cells, i is a natural number, j is a jth time value of the time sequence, j is a natural number, and a matrix of all cells ranked over time according to a physical quantity used to characterize the state of the battery is obtained.

6. The method of claim 1, wherein the physical quantity ranking curve of each cell for characterizing the battery state is differentially calculated to obtain and store a slope K, and a specific calculation formula is as follows:

where i is the cell number, T (j) is the jth time in the time series, and m is the time interval.

7. The method of claim 6, wherein the threshold is obtained by:

by using the K obtained in claim 6, a K-T curve of K and time is drawn, and the K-T curve of a battery with internal short circuit, lithium precipitation or thermal runaway fault and the K-T curve of a battery without fault are compared to obtain a threshold A.

8. The method of claim 7, wherein determining whether the battery is malfunctioning based on the determination threshold K comprises:

if K is more than or equal to A in the K-T curve, judging that the battery has internal short circuit, lithium precipitation or thermal runaway fault; if K < A, it is determined that the battery system has no fault.

9. The method according to claim 9, wherein the remaining battery modules or systems are judged according to the judgment conditions of claim 8, and the cause of the malfunction of the battery system is distinguished.