CN115877230A - Method, system, device and medium for determining fault of battery module - Google Patents
Method, system, device and medium for determining fault of battery module Download PDFInfo
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- CN115877230A CN115877230A CN202211524877.1A CN202211524877A CN115877230A CN 115877230 A CN115877230 A CN 115877230A CN 202211524877 A CN202211524877 A CN 202211524877A CN 115877230 A CN115877230 A CN 115877230A
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Abstract
The invention discloses a method, a system, equipment and a medium for determining the fault of a battery module, wherein the method for determining the fault comprises the following steps: acquiring voltage data of a battery core in a battery module; grouping the voltage data of the battery cells to obtain voltage data of a plurality of groups of battery cells; acquiring information entropy of the battery module based on voltage data of a plurality of groups of battery cells; and determining the fault of the battery module according to the information entropy. The invention realizes early warning of the fault problem of the battery.
Description
Technical Field
The invention relates to the technical field of batteries, in particular to a method, a system, equipment and a medium for determining a fault of a battery module.
Background
At present, "carbon reaches peak" and "carbon neutrality" promote new energy storage as clean, low-carbon, safe and efficient energy. The electrochemical energy storage machine has started to explode in scale on a global scale. The installation scale of the energy storage industry is accelerated and then continuously warmed after being slowed down, and the installation scale of the electrochemical energy storage project is continuously increased.
In the process of rapid development of energy storage, energy storage safety is always an industry hotspot problem. How to ensure the safety of the energy storage battery used in the energy storage power station is very important. At present, the internal strategy of the existing BSM (battery management system) system is generally adopted to manage and maintain the overcharge (overvoltage) and the overdischarge (undervoltage) of the battery, and the fault problem of the battery cannot be warned.
Disclosure of Invention
The invention provides a method, a system, equipment and a medium for determining a fault of a battery module, aiming at overcoming the defect that the fault problem of a battery cannot be pre-warned in the prior art.
The invention solves the technical problems through the following technical scheme:
the invention provides a fault determination method of a battery module, which comprises the following steps:
acquiring voltage data of a battery core in a battery module;
grouping the voltage data of the battery cells to obtain voltage data of a plurality of groups of battery cells;
acquiring information entropy of the battery module based on voltage data of a plurality of groups of battery cells;
and determining the faults of the battery module according to the information entropy.
Preferably, the step of grouping the voltage data of the battery cells includes:
acquiring a normal working voltage interval of a battery core in the battery module and a preset voltage deviation of the battery core in the battery module;
grouping the voltage data of the battery cells based on the normal working voltage interval and the preset voltage deviation;
and/or the step of acquiring the information entropy of the battery module comprises the following steps:
determining the frequency of each group of battery cells according to the voltage data of a plurality of groups of battery cells; the frequency represents the number of each group of battery cells;
determining the probability of each group of battery cells based on the number of the battery cells and the total number of the battery cells in the battery module;
and determining the information entropy of the battery module based on the probability of each group of battery cells.
Preferably, after the step of determining the frequency of each group of cells, the fault determination method further includes:
and judging whether the frequency is smaller than a first preset threshold value, and if so, determining that the battery module has a fault.
Preferably, the determining of the fault of the battery module includes:
and judging whether the information entropy is larger than a second preset threshold value, and if so, determining that the battery module has a fault.
And/or, the step of determining the fault of the battery module further comprises:
based on the information entropy, obtaining an information entropy curve corresponding to the information entropy;
and determining that the battery module has faults according to the information entropy curve.
The present invention also provides a fault determination system for a battery module, the fault determination system comprising:
the first acquisition module is used for acquiring voltage data of the battery cell in the battery module;
the grouping module is used for grouping the voltage data of the battery cells to obtain the voltage data of a plurality of groups of battery cells;
the second acquisition module is used for acquiring the information entropy of the battery module based on the voltage data of a plurality of groups of battery cells;
and the fault determining module is used for determining the fault of the battery module according to the information entropy.
Preferably, the grouping module comprises:
the acquisition unit is used for acquiring a normal working voltage interval of the battery cell in the battery module and a preset voltage deviation of the battery cell in the battery module;
the grouping unit is used for grouping the voltage data of the battery cells based on the normal working voltage interval and the preset voltage deviation;
and/or, the grouping module further comprises:
the frequency determining unit is used for determining the frequency of each group of battery cells according to the voltage data of a plurality of groups of battery cells; the frequency represents the number of each group of battery cells;
the probability determining unit is used for determining the probability of each group of battery cells based on the number of the battery cells and the total number of the battery cells in the battery module;
and the information entropy determining unit is used for determining the information entropy of the battery module based on the probability of each group of battery cells.
Preferably, the fault determination system further comprises:
and the judging module is used for judging whether the frequency is smaller than a first preset threshold value, and if so, determining that the battery module has a fault.
Preferably, the determining module is specifically configured to:
and judging whether the information entropy is larger than a second preset threshold value, and if so, determining that the battery module has a fault.
And/or the judging module is further specifically configured to:
based on the information entropy, obtaining an information entropy curve corresponding to the information entropy;
and determining that the battery module has faults according to the information entropy curve.
The invention provides an electronic device, which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the computer program to realize the fault determination method of the battery module.
The present invention also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of determining a fault of a battery module as described above.
The positive progress effects of the invention are as follows:
the invention provides a method, a system, equipment and a medium for determining the faults of a battery module.
Drawings
Fig. 1 is a flowchart of a method for determining a fault of a battery module according to embodiment 1 of the present invention;
FIG. 2 is a flowchart of step S102 in embodiment 1 of the present invention;
FIG. 3 is a flowchart of step S103 in embodiment 1 of the present invention;
FIG. 4 is a schematic diagram of a normal voltage curve in example 1 of the present invention;
FIG. 5 is a schematic diagram of the information entropy of the normal curve calculation in embodiment 1 of the present invention;
FIG. 6 is a schematic diagram of an abnormal voltage curve in example 1 of the present invention;
FIG. 7 is a schematic diagram of information entropy calculated from abnormal voltage in example 1 of the present invention;
fig. 8 is a block diagram of a system for determining a failure of a battery module according to embodiment 2 of the present invention;
fig. 9 is a block diagram of a grouping module in embodiment 2 of the present invention;
fig. 10 is a block diagram of a second obtaining module in embodiment 2 of the present invention;
fig. 11 is a schematic structural diagram of an electronic device in embodiment 3 of the present invention.
Detailed Description
The invention is further illustrated by the following examples, which are not intended to limit the scope of the invention.
Example 1
As shown in fig. 1, the present embodiment discloses a method for determining a fault of a battery module, where the method includes:
s101, obtaining voltage data of a battery cell in a battery module;
specifically, voltage data of the battery cells in the battery module over a period of time may be acquired. And recording the number of lines of the data as m, recording the number of columns of the battery cell as n, and cleaning the data according to the voltage data and the corresponding time data, wherein the obtained number of lines is m, and the number of columns of the battery cell is n, and the cleaning of the data comprises the operations of removing duplicate data, deleting obvious abnormal data and the like.
Further, the voltage data of a proper time window can be selected according to the length of the acquired voltage data. The time window is selected to be as large as possible so as to ensure that the data volume of the counted time is enough.
Step S102, grouping the voltage data of the battery cells to obtain voltage data of a plurality of groups of battery cells;
step S103, acquiring information entropy of the battery module based on voltage data of a plurality of groups of battery cells;
and step S104, determining the fault of the battery module according to the information entropy.
According to the scheme, the voltage data of the plurality of groups of battery cells are obtained, the information entropy of the battery module is obtained based on the voltage data of the plurality of groups of battery cells, and the fault of the battery module is determined according to the information entropy, so that the early warning of the fault problem of the battery is realized.
As shown in fig. 2, in an implementable manner, the step S102 includes:
s1021, acquiring a normal working voltage interval of the battery cell in the battery module and a preset voltage deviation of the battery cell in the battery module;
step S1022, grouping the voltage data of the battery cell based on the normal working voltage interval and the preset voltage deviation;
in a specific embodiment, for example, the normal operating voltage of the lithium ion battery is 2.5V-3.65V, and the grouping interval of the cells in the battery module is 0.02V, so that the obtained voltage data of the cells can be divided into the following groups, such as (2.5V-2.52V), (2.52V-2.54V), (2.54V-2.56V) … … (3.60V-3.62V), (3.62V-3.64V), (3.64V-3.65V), and 58 groups in total. In this embodiment, can also set for the voltage deviation of electric core in the battery module to be littleer value to make the interval of grouping littleer, the information entropy of the battery module of acquireing is more accurate.
According to the scheme, the voltage data of the battery cells are grouped based on the normal working voltage interval and the preset voltage deviation, so that the information entropy of the subsequently acquired battery module is more accurate.
As shown in fig. 3, in an implementation manner, the step S103 includes:
step S1031, determining the frequency of each group of battery cells according to the voltage data of a plurality of groups of battery cells; the frequency represents the number of each group of battery cells;
step S1032, determining the probability of each group of battery cells based on the number of the battery cells and the total number of the battery cells in the battery module;
and S1033, determining the information entropy of the battery module based on the probability of each group of battery cells.
The information entropy is used for solving the quantization problem of information, and an original fuzzy information concept is calculated to obtain an accurate information entropy value, wherein the information entropy is a value for describing uncertainty in the information. The calculation formula of the information entropy is as follows:
wherein P is a probability mass function; i is an information quantity function; the unit of information entropy is bi (bit).
In an implementable manner, after step S104, the fault determination method further includes:
and judging whether the frequency is smaller than a first preset threshold value, and if so, determining that the battery module has faults.
In an implementation manner, the step S104 includes:
and judging whether the information entropy is larger than a second preset threshold value, and if so, determining that the battery module has a fault.
Specifically, whether the entropy is larger than a second preset threshold value or not is judged, and then the battery core in the battery module is judged to be abnormal, so that the battery module is determined to have a fault.
In an implementation manner, the step S104 further includes:
based on the information entropy, obtaining an information entropy curve corresponding to the information entropy;
and determining that the battery module has faults according to the information entropy curve.
According to the scheme, whether abnormity occurs in the charging and discharging process is judged according to the curve of the information entropy, for example, the calculation result of the information entropy is obviously influenced by the jump of the voltage. Fig. 4 is a schematic diagram of a normal voltage curve, fig. 5 is a schematic diagram of information entropy calculated by the normal curve, fig. 6 is a schematic diagram of an abnormal voltage curve, and fig. 7 is a schematic diagram of information entropy calculated by the abnormal voltage.
Example 2
As shown in fig. 8, the present embodiment discloses a failure determination system of a battery module, the failure determination system including:
the first acquisition module 1 is used for acquiring voltage data of a battery cell in the battery module;
specifically, voltage data of the battery cells in the battery module over a period of time may be acquired. And recording the number of rows of data as m, recording the number of columns of the battery cell as n, and performing data cleaning on the data according to the voltage data and the corresponding time data of which the number of rows is m and the number of columns is n, wherein the data cleaning comprises the operations of removing duplicate, deleting obvious abnormal data and the like.
Further, the voltage data of a proper time window can be selected according to the length of the acquired voltage data. The time window is selected to be as large as possible so as to ensure that the data volume of the counted time is enough.
The grouping module 2 is configured to group the voltage data of the battery cells to obtain voltage data of a plurality of groups of battery cells;
the second acquisition module 3 is configured to acquire information entropy of the battery module based on voltage data of a plurality of groups of the battery cells;
and the fault determining module 4 is used for determining the fault of the battery module according to the information entropy.
According to the scheme, the voltage data of the plurality of groups of battery cells are obtained, the information entropy of the battery module is obtained based on the voltage data of the plurality of groups of battery cells, and the fault of the battery module is determined according to the information entropy, so that the early warning of the fault problem of the battery is realized.
As shown in fig. 9, in an implementable manner, the grouping module 2 includes:
the acquiring unit 21 is configured to acquire a normal operating voltage interval of a battery cell in the battery module and a preset voltage deviation of the battery cell in the battery module;
the grouping unit 22 is configured to group the voltage data of the battery cells based on the normal operating voltage interval and the preset voltage deviation;
in a specific embodiment, for example, the normal operating voltage of the lithium ion battery is 2.5V-3.65V, and the grouping interval of the cells in the battery module is 0.02V, so the obtained voltage data of the cells can be divided into the following groups, such as (2.5V-2.52V), (2.52V-2.54V), (2.54V-2.56V) … … (3.62V-3.64V), (3.64V-3.65V), and 58 groups in total. In this embodiment, can also set for the voltage deviation of electric core in the battery module to be littleer value to make the interval of grouping littleer, the information entropy of the battery module of acquireing is more accurate.
According to the scheme, the voltage data of the battery cells are grouped based on the normal working voltage interval and the preset voltage deviation, so that the information entropy of the subsequently acquired battery module is more accurate.
In an implementable manner, as shown in fig. 10, the second obtaining module 3 comprises:
the frequency determining unit 31 is configured to determine the frequency of each group of battery cells according to the voltage data of a plurality of groups of battery cells; the frequency represents the number of each group of battery cells;
a probability determination unit 32, configured to determine a probability of each group of battery cells based on the number of the battery cells and the total number of the battery cells in the battery module;
and the information entropy determining unit 33 is configured to determine the information entropy of the battery module based on the probability of each group of battery cells.
The information entropy is used for solving the quantization problem of information, and an original fuzzy information concept is calculated to obtain an accurate information entropy value, wherein the information entropy is a value for describing uncertainty in the information. The calculation formula of the information entropy is as follows:
wherein P is a probability mass function; i is an information quantity function; the unit of information entropy is bi (bit).
In one practical manner, the fault determination system further includes:
and the judging module 5 is used for judging whether the frequency is smaller than a first preset threshold value, and if so, determining that the battery module has a fault.
In an implementation manner, the determining module 5 is specifically configured to:
and judging whether the information entropy is larger than a second preset threshold value, and if so, determining that the battery module has a fault.
Specifically, whether the entropy is larger than a second preset threshold value or not is judged, and then the battery core in the battery module is judged to be abnormal, so that the battery module is determined to have a fault.
In an implementation manner, the determining module 5 is further specifically configured to:
based on the information entropy, obtaining an information entropy curve corresponding to the information entropy;
and determining that the battery module has faults according to the information entropy curve.
According to the scheme, whether abnormity occurs in the charging and discharging process is judged according to the curve of the information entropy, for example, the calculation result of the information entropy is obviously influenced by the jump of the voltage. Fig. 4 is a schematic diagram of a normal voltage curve, fig. 5 is a schematic diagram of information entropy calculated by the normal curve, fig. 6 is a schematic diagram of an abnormal voltage curve, and fig. 7 is a schematic diagram of information entropy calculated by the abnormal voltage.
Example 3
Fig. 11 is a schematic structural diagram of an electronic device according to embodiment 3 of the present invention. The electronic device comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, and the processor executes the program to realize the fault determination method of the battery module provided by the embodiment 1. The electronic device 40 shown in fig. 11 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiment of the present invention.
As shown in fig. 11, electronic device 40 may take the form of a general-purpose computing device, which may be, for example, a server device. The components of electronic device 40 may include, but are not limited to: the at least one processor 41, the at least one memory 42, and a bus 43 connecting the various system components (including the memory 42 and the processor 41).
The bus 43 includes a data bus, an address bus, and a control bus.
The memory 42 may include volatile memory, such as Random Access Memory (RAM) 421 and/or cache memory 422, and may further include Read Only Memory (ROM) 423.
The processor 41 executes various functional applications and data processing, such as a failure determination method of a battery module provided in embodiment 1 of the present invention, by running a computer program stored in the memory 42.
The electronic device 40 may also communicate with one or more external devices 44 (e.g., keyboard, pointing device, etc.). Such communication may be through an input/output (I/O) interface 45. Also, model-generating device 40 may also communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet) via network adapter 46. As shown, the network adapter 46 communicates with the other modules of the model-generated device 40 over a bus 43. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the model-generating device 40, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems, to name a few.
It should be noted that although in the above detailed description several units/modules or sub-units/modules of the electronic device are mentioned, such a division is merely exemplary and not mandatory. Indeed, the features and functionality of two or more of the units/modules described above may be embodied in one unit/module according to embodiments of the invention. Conversely, the features and functions of one unit/module described above may be further divided into embodiments by a plurality of units/modules.
Example 4
The present embodiment provides a computer-readable storage medium on which a computer program is stored, which when executed by a processor, implements the method for determining a failure of a battery module provided in embodiment 1.
More specific examples, among others, that the readable storage medium may employ may include, but are not limited to: a portable disk, a hard disk, random access memory, read only memory, erasable programmable read only memory, optical storage device, magnetic storage device, or any suitable combination of the foregoing.
In a possible implementation manner, the present invention can also be implemented in the form of a program product, which includes program codes for causing a terminal device to execute a method for determining a fault of a battery module, which is provided in implementation example 1, when the program product runs on the terminal device.
Where program code for carrying out the invention is written in any combination of one or more programming languages, the program code may be executed entirely on the user device, partly on the user device, as a stand-alone software package, partly on the user device and partly on a remote device or entirely on the remote device.
While specific embodiments of the invention have been described above, it will be appreciated by those skilled in the art that this is by way of example only, and that the scope of the invention is defined by the appended claims. Various changes or modifications to these embodiments may be made by those skilled in the art without departing from the principle and spirit of this invention, and these changes and modifications are within the scope of this invention.
Claims (10)
1. A method for determining a fault of a battery module is characterized by comprising the following steps:
acquiring voltage data of a battery core in a battery module;
grouping the voltage data of the battery cells to obtain voltage data of a plurality of groups of battery cells;
acquiring information entropy of the battery module based on voltage data of a plurality of groups of battery cells;
and determining the fault of the battery module according to the information entropy.
2. The method for determining the fault of the battery module according to claim 1, wherein the step of grouping the voltage data of the battery cells includes:
acquiring a normal working voltage interval of a battery core in the battery module and a preset voltage deviation of the battery core in the battery module;
grouping the voltage data of the battery cells based on the normal working voltage interval and the preset voltage deviation;
and/or the step of acquiring the information entropy of the battery module comprises the following steps:
determining the frequency of each group of battery cells according to the voltage data of a plurality of groups of battery cells; the frequency represents the number of each group of battery cells;
determining the probability of each group of battery cells based on the number of the battery cells and the total number of the battery cells in the battery module;
and determining the information entropy of the battery module based on the probability of each group of battery cells.
3. The method for determining the fault of the battery module according to claim 2, wherein after the step of determining the frequency of each group of cells, the method for determining the fault further comprises:
and judging whether the frequency is smaller than a first preset threshold value, if so, determining that the battery module has faults.
4. The method for determining the malfunction of the battery module according to claim 1, wherein the step of determining the malfunction of the battery module comprises:
judging whether the information entropy is larger than a second preset threshold value or not, and if so, determining that the battery module has a fault;
and/or, the step of determining the fault of the battery module further comprises:
based on the information entropy, obtaining an information entropy curve corresponding to the information entropy;
and determining that the battery module has faults according to the information entropy curve.
5. A fault determination system of a battery module, the fault determination system comprising:
the first acquisition module is used for acquiring voltage data of the battery cell in the battery module;
the grouping module is used for grouping the voltage data of the battery cells to obtain the voltage data of a plurality of groups of battery cells;
the second acquisition module is used for acquiring the information entropy of the battery module based on the voltage data of a plurality of groups of battery cells;
and the fault determining module is used for determining the fault of the battery module according to the information entropy.
6. The system for determining a fault in a battery module according to claim 5, wherein the grouping module comprises:
the acquisition unit is used for acquiring a normal working voltage interval of the battery cell in the battery module and a preset voltage deviation of the battery cell in the battery module;
the grouping unit is used for grouping the voltage data of the battery cells based on the normal working voltage interval and the preset voltage deviation;
and/or, the grouping module further comprises:
the frequency determining unit is used for determining the frequency of each group of battery cells according to the voltage data of a plurality of groups of battery cells; the frequency represents the number of each group of battery cells;
the probability determining unit is used for determining the probability of each group of battery cells based on the number of the battery cells and the total number of the battery cells in the battery module;
and the information entropy determining unit is used for determining the information entropy of the battery module based on the probability of each group of battery cells.
7. The fault determination system for a battery module according to claim 6, wherein the fault determination system further comprises:
and the judging module is used for judging whether the frequency is smaller than a first preset threshold value, and if so, determining that the battery module has faults.
8. The system of claim 7, wherein the determining module is specifically configured to:
judging whether the information entropy is larger than a second preset threshold value or not, and if so, determining that the battery module has a fault;
and/or the judging module is further specifically configured to:
based on the information entropy, obtaining an information entropy curve corresponding to the information entropy;
and determining that the battery module has faults according to the information entropy curve.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method for determining a fault of a battery module according to any one of claims 1 to 4 when executing the computer program.
10. A computer-readable storage medium on which a computer program is stored, the computer program implementing a method of determining a fault of a battery module according to any one of claims 1 to 4 when executed by a processor.
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