CN116299038A - Method, system, equipment and storage medium for detecting micro short circuit of battery cell - Google Patents
Method, system, equipment and storage medium for detecting micro short circuit of battery cell Download PDFInfo
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Abstract
The invention discloses a detection method, a system, equipment and a storage medium for micro-short circuit of an electric core, wherein the method comprises the following steps: calculating time weight probability according to the acquired sampling time; calculating the trend probability of all the cells and the trend probability of each cell according to the calculated average voltage difference of all the cells at each sampling time, the voltage difference of each cell and the time weight probability; calculating the cross entropy of the trend probability of all the electric cores and the trend probability of each electric core; and carrying out micro short circuit detection on the battery cell according to the cross entropy. According to the calculated trend probability of all the battery cells and the trend probability of each battery cell, the invention calculates the trend probability of each battery cell; calculating the cross entropy of the trend probability of all the electric cores and the trend probability of each electric core; and carrying out micro short circuit detection on the battery cell according to the cross entropy. The dependence of micro short circuit detection on the characteristic data of the battery core is reduced, the effects of real-time detection and early warning are achieved, and the detection efficiency and the detection accuracy of the micro short circuit are improved.
Description
Technical Field
The present invention relates to the field of battery cell detection technologies, and in particular, to a method, a system, an apparatus, and a storage medium for detecting a micro short circuit of a battery cell.
Background
When the separator of the lithium battery cell is punctured or broken, the positive and negative electrodes of the battery cell are caused to directly contact, which is called micro-short circuit. When the battery cell is in micro short circuit, the battery cell can continuously consume electric energy all the time, and the normal operation of the whole battery module is affected.
At present, the detection of the micro short circuit of the battery is mainly realized based on an inconsistent algorithm or a neural network algorithm, and the inconsistent algorithm has two modes, namely, the detection is based on the comparison of the characteristic parameters of the current battery core data and the characteristic of the historical data, and the abnormality is found; and the other is to find out abnormal cells by transverse comparison based on the characteristic parameters of all cells in the current battery pack. The neural network algorithm trains the neural network according to a large amount of cell historical data, and detects after obtaining a reliable model. When the data volume cannot meet the requirement, the obtained model is poor in effect.
The current main detection method is to use correlation coefficients of all the cell data in the same time period for detection, but in real work, the detection method is limited by detection equipment and working environment, and characteristic parameter acquisition of the cells is uneven, so that the detection requirement cannot be met frequently.
Disclosure of Invention
The invention aims to overcome the defect that the acquired battery cell characteristic data are uneven and cannot meet the detection requirement in the detection mode of the battery cell micro-short circuit in the prior art, and provides a detection method, a system, equipment and a storage medium of the battery cell micro-short circuit.
The invention solves the technical problems by the following technical scheme:
the first aspect of the invention provides a detection method for micro-short circuit of an electric core, which comprises the following steps:
acquiring sampling time of cell characteristic data, wherein the cell characteristic data comprises voltage;
calculating time weight probability according to the sampling time;
calculating the average voltage difference of all the battery cells of each sampling time and the voltage difference of each battery cell;
calculating trend probabilities of all the electric cores and trend probabilities of each electric core according to the average voltage difference of all the electric cores, the voltage difference of each electric core and the time weight probability;
calculating cross entropy of the trend probabilities of all the electric cores and the trend probability of each electric core;
and carrying out micro short circuit detection on the battery cell according to the cross entropy.
Preferably, the step of performing micro-short circuit detection on the battery cell according to the cross entropy includes:
screening out the maximum cross entropy from the cross entropies;
and detecting the battery cell which is about to be in the micro-short circuit state or is already in the micro-short circuit state according to the comparison result of the maximum cross entropy and the first battery cell safety value.
Preferably, the step of performing micro-short circuit detection on the battery cell according to the cross entropy further includes:
screening out the maximum cross entropy and the minimum cross entropy from the cross entropy;
dividing the maximum cross entropy by the minimum cross entropy to obtain an operation result;
and detecting the battery cell which is about to be in the micro-short circuit state or is in the micro-short circuit state according to the comparison result of the operation result and a second battery cell safety value, wherein the second battery cell safety value is larger than the first battery cell safety value.
Preferably, the step of detecting the cell to be in the micro-short state or already in the micro-short state according to the comparison result of the maximum cross entropy and the first cell safety value includes:
if the maximum cross entropy is larger than the first battery cell safety value within the preset time, detecting a battery cell which is in a micro short circuit state; if the maximum cross entropy exceeds the preset time and is larger than the first battery cell safety value, detecting a battery cell in a micro-short circuit state;
and/or the number of the groups of groups,
the step of detecting the cell which is about to be in the micro-short circuit state or is already in the micro-short circuit state according to the comparison result of the operation result and the second cell safety value comprises the following steps:
if the operation result is larger than the second battery cell safety value within the preset time, detecting a battery cell which is in a micro short circuit state; and if the operation result exceeds the preset time and is larger than the second battery cell safety value, detecting the battery cell in the micro-short circuit state.
The invention provides a detection system for micro-short circuit of a battery cell, which comprises an acquisition module, a first calculation module, a second calculation module, a third calculation module, a fourth calculation module and a detection module;
the acquisition module is used for acquiring sampling time of the battery cell characteristic data, wherein the battery cell characteristic data comprises voltage;
the first calculation module is used for calculating time weight probability according to the sampling time;
the second calculation module is used for calculating the average voltage difference of all the battery cells at each sampling time and the voltage difference of each battery cell;
the third calculation module is configured to calculate a trend probability of all the electric cells and a trend probability of each electric cell according to the average voltage difference of all the electric cells, the voltage difference of each electric cell and the time weight probability;
the fourth calculation module is used for calculating cross entropy of the trend probability of all the battery cells and the trend probability of each battery cell;
and the detection module is used for carrying out micro short circuit detection on the battery cell according to the cross entropy.
Preferably, the detection module comprises a first screening unit and a first detection unit;
the first screening unit is used for screening the maximum cross entropy from the cross entropies;
and the first detection unit is used for detecting the battery cell which is about to be in the micro-short circuit state or is already in the micro-short circuit state according to the comparison result of the maximum cross entropy and the first battery cell safety value.
Preferably, the detection module further comprises a second screening unit, a calculation unit and a second detection unit;
the second screening unit is used for screening out the maximum cross entropy and the minimum cross entropy from the cross entropy;
the computing unit is used for dividing the maximum cross entropy by the minimum cross entropy to obtain an operation result;
the second detection unit is used for detecting the battery cell which is about to be in the micro-short circuit state or is in the micro-short circuit state according to the comparison result of the operation result and a second battery cell safety value, and the second battery cell safety value is larger than the first battery cell safety value.
Preferably, the first detection unit is configured to detect a cell that will be in a micro-short state if the maximum cross entropy is greater than the first cell safety value within a preset time; if the maximum cross entropy exceeds the preset time and is larger than the first battery cell safety value, detecting a battery cell in a micro-short circuit state;
and/or the number of the groups of groups,
the second detection unit is used for detecting a battery cell which is in a micro short circuit state if the operation result is larger than the second battery cell safety value within a preset time; and if the operation result exceeds the preset time and is larger than the second battery cell safety value, detecting the battery cell in the micro-short circuit state.
A third aspect of the present invention provides an electronic device comprising a memory, a processor and a computer program stored on the memory for running on the processor, the processor implementing the method for detecting a micro-short of a cell according to the first aspect when executing the computer program.
A fourth aspect of the invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method for detecting a micro-short circuit of a cell according to the first aspect.
On the basis of conforming to the common knowledge in the field, the above preferred conditions can be arbitrarily combined to obtain the preferred examples of the invention.
The invention has the positive progress effects that:
according to the average voltage difference of all the electric cores obtained through calculation, the voltage difference of each electric core and the time weight probability, the trend probability of all the electric cores and the trend probability of each electric core are calculated; calculating the cross entropy of the trend probability of all the electric cores and the trend probability of each electric core; and carrying out micro short circuit detection on the battery cell according to the cross entropy. The analysis based on cross entropy is realized, the dependence of micro-short circuit detection on the characteristic data of the battery cell is greatly reduced, the effects of real-time detection and early warning are achieved, and the detection efficiency and the detection accuracy of the micro-short circuit are improved.
Drawings
Fig. 1 is a flowchart of a method for detecting a micro-short circuit of a battery cell according to embodiment 1 of the present invention.
Fig. 2 is a schematic block diagram of a detection system for micro-shorting of a battery cell according to embodiment 2 of the present invention.
Fig. 3 is a schematic structural diagram of an electronic device according to embodiment 3 of the present invention.
Detailed Description
The invention is further illustrated by means of the following examples, which are not intended to limit the scope of the invention.
Example 1
The method for detecting the micro short circuit of the battery cell provided in this embodiment, as shown in fig. 1, includes:
in this embodiment, the sampling time is set according to the actual situation, for example, the sampling time may be set to 15 seconds, or may be set to another value, which is not limited herein specifically.
In this embodiment, the cell characteristic data further includes a current.
102, calculating time weight probability according to sampling time;
in this embodiment, a calculation formula for calculating the time weight probability according to the sampling time is shown in formula (1):
wherein p is t Representing a time weight probability; x is x i Characteristic data (such as voltage or current) of the single battery cell corresponding to the ith sampling time; i represents the position of the characteristic data x of the single cell; steps represents the number of sampling times; alpha and beta are both adjustment values, which need to be adjusted according to the actual working environment and measurement conditions, wherein alpha is an amplification factor, when the working environment is stable, the adjustment is 1, when the conditions are not met, proper reduction is needed, the value range is 1 not less than alpha not less than 0.75, beta is an auxiliary calculation value, the value range is 0.01 not less than beta not less than 0.001, and the value is only used for preventing 0 removal error.
In the implementation process, when calculating the time weight probability, the time weight probability can also be calculated through sampling step length, specifically, a proper sampling step length is selected according to the sampling time of the obtained cell characteristic data (for example, the sampling time is 15 seconds, the sampling step length is 10 sampling times (for example, 10 15 seconds), and the cell characteristic data with 10 sampling times can be accurately detected), and the time weight probability is calculated according to the sampling step length; in addition, the time intervals of the sampling times are generally uniform.
in this embodiment, the calculation formulas for calculating the average voltage difference of all the cells at each sampling time and the voltage difference of each cell are shown in formula (2) and formula (3), respectively:
diff i ＝x i+1 -x i (3)
wherein diff is mean-i Representing the average voltage difference of all the battery cells;
mean value of all cell voltages in electric box at same sampling time, x i Cell voltage, diff, representing the current sampling time i Representing the voltage difference for each cell.
104, calculating trend probabilities of all the electric cores and trend probabilities of each electric core according to the average voltage difference of all the electric cores, the voltage difference of each electric core and the time weight probability;
in this embodiment, the calculation formulas of the trend probabilities of all the battery cells and the trend probability of each battery cell are shown in formula (4):
wherein, the liquid crystal display device comprises a liquid crystal display device,
representing a voltage difference dif greater than 0f time weight probability p corresponding to i position t ，p + Representing the probability of trend of voltage rise, the same p 0 And p - The trend probabilities of the voltage invariance and the voltage drop are respectively represented.
in this embodiment, a calculation formula for calculating the cross entropy is shown in formula (5):
wherein cross_entropy represents cross entropy; p represents the trend probability of each cell and q represents the trend probability of all cells.
And 106, performing micro short circuit detection on the battery cell according to the cross entropy.
In the embodiment, the characteristic data of all the battery cells in the same time period are used for detection, but the characteristic data are converted into short-time trend (namely trend probability), and the distribution of the characteristic data is compared by using a cross entropy method, so that the dependence of micro short circuit detection on the data quantity is greatly reduced, and the effects of real-time detection and early warning are achieved.
As an alternative embodiment, step 106 includes:
106-11, screening out the maximum cross entropy from the cross entropies;
in this embodiment, the maximum cross entropy indicates the cell most likely to have a micro short circuit in the electric box;
and step 106-12, detecting the battery cell which is about to be in the micro-short circuit state or is already in the micro-short circuit state according to the comparison result of the maximum cross entropy and the first battery cell safety value.
In this embodiment, the first cell safety value is set according to the actual situation, for example, the first cell safety value may be set to 5, and may be set to other values, which are not limited herein specifically;
as an alternative embodiment, step 106-12 includes:
if the maximum cross entropy is larger than the first battery cell safety value within the preset time, detecting a battery cell which is in a micro short circuit state; if the maximum cross entropy exceeds the preset time and is larger than the first battery cell safety value, detecting a battery cell in a micro-short circuit state;
in this embodiment, the preset time is set according to the actual situation, for example, the preset time may be set to 1 minute, and may be set to other values;
in this embodiment, the maximum cross entropy is directly used to perform the micro-short circuit detection on the battery cell, specifically, when the maximum cross entropy is greater than the first battery cell safety value (for example, the maximum cross entropy is greater than 5 in 1 minute) in a preset time, the battery cell will be considered to be in the micro-short circuit state, and when the maximum cross entropy is continuously greater than the first battery cell safety value (for example, when the maximum cross entropy is continuously greater than the first battery cell safety value in more than 1 minute), the battery cell can be considered to be in the micro-short circuit state, and the battery cell needs to be processed, and the detection mode of performing the micro-short circuit detection on the battery cell directly using the maximum cross entropy is simple and stable.
As an optional implementation, step 106 further includes:
106-21, screening out the maximum cross entropy and the minimum cross entropy from the cross entropy;
in this embodiment, the minimum cross entropy represents the safest cell in the cell box.
106-22, dividing the maximum cross entropy by the minimum cross entropy to obtain an operation result;
in this embodiment, the calculation formula of the operation result is shown in formula (6):
wherein max { cross_entropy } represents the maximum cross entropy; min { cross_entropy } represents the minimum cross entropy, and y represents the result of the operation (i.e., the result after amplification).
In this embodiment, dividing the maximum cross entropy by the minimum cross entropy may make the data more obvious, and it is actually the least stable cell and the most stable cell divided, so that the data is amplified, and the unstable data can be more intuitively seen.
And step 106-23, detecting the battery cell which is about to be in the micro-short circuit state or is in the micro-short circuit state according to the comparison result of the operation result and the second battery cell safety value, wherein the second battery cell safety value is larger than the first battery cell safety value.
In this embodiment, the second cell safety value is set according to the actual situation, for example, the second cell safety value may be set to 15, and may be set to other values, which are not limited herein specifically;
as an alternative embodiment, steps 106-23 include:
if the maximum cross entropy is larger than the second battery cell safety value within the preset time, detecting a battery cell which is in a micro short circuit state; and if the maximum cross entropy exceeds the preset time and is larger than the second battery cell safety value, detecting the battery cell in the micro-short circuit state.
In a specific implementation process, scaling treatment can be performed on the cross entropy, and a scaling treatment result is subjected to salifying treatment (namely amplifying treatment), specifically, the maximum cross entropy and the minimum cross entropy are screened out from the cross entropy; dividing the maximum cross entropy by the minimum cross entropy to obtain an operation result; and finer results can be obtained after the salification treatment, so that the problem condition of each piece of data can be more obviously seen, which is equivalent to amplifying the results.
For example, if a large portion of the cells in the electrical box have been problematic, accurate results cannot be obtained, requiring the detection of unsafe electrical boxes using the electrical box data in the power plant battery cluster. According to the method, the data are subjected to salification processing by dividing the maximum cross entropy by the minimum cross entropy, and a finer result can be seen, for example, a second cell safety value used by the method is 15, and when the operation result after the salification processing is larger than the second cell safety value in a preset time, the cell can be considered to be in a micro-short circuit state. When the operation result after the salification exceeds the preset time and is continuously larger than the second cell safety value, the cell can be considered to be in the micro-short circuit state. If some data in micro short circuit is repeated in a period of time in the method of directly detecting the battery cell by using the maximum cross entropy, the data processed by the salifying method can be judged to be abnormal, and a measuring tool is required to be checked instead of checking the micro short circuit.
In the embodiment, the detection result is more visual and finer by using the mode of performing micro short circuit detection on the battery cell through the salification treatment.
In this embodiment, for example, when a micro-short condition occurs, the maximum cross entropy calculation generally exceeds the first cell safety value 5, and when the salification processing method of this embodiment is used, the micro-short can be more obvious and exceeds 15; the cross entropy of the normal battery core can be maintained within 5 no matter how complicated the voltage change condition is, as long as the voltage change condition has no obvious micro short circuit trend, and the result can be maintained within 3 after the salification processing method of the embodiment is used. The detection accuracy is improved.
According to the embodiment, the trend probability of all the electric cores and the trend probability of each electric core are calculated according to the calculated average voltage difference of all the electric cores, the voltage difference of each electric core and the time weight probability; calculating the cross entropy of the trend probability of all the electric cores and the trend probability of each electric core; and carrying out micro short circuit detection on the battery cell according to the cross entropy. The analysis based on cross entropy is realized, the dependence of micro-short circuit detection on the characteristic data of the battery cell is greatly reduced, the effects of real-time detection and early warning are achieved, and the detection efficiency and the detection accuracy of the micro-short circuit are improved.
Example 2
As shown in fig. 2, the detection system for micro-short circuit of the battery cell provided in this embodiment includes an acquisition module 21, a first calculation module 22, a second calculation module 23, a third calculation module 24, a fourth calculation module 25, and a detection module 26;
the acquisition module 21 is configured to acquire sampling time of cell characteristic data, where the cell characteristic data includes voltage;
in this embodiment, the sampling time is set according to the actual situation, for example, the sampling time may be set to 15 seconds, or may be set to another value, which is not limited herein specifically.
In this embodiment, the cell characteristic data further includes a current.
The first calculation module 22 is configured to calculate a time weight probability according to the sampling time;
in the present embodiment, a calculation formula for calculating the time weight probability from the sampling time is shown as formula (1) in embodiment 1.
In the implementation process, when calculating the time weight probability, the time weight probability can also be calculated through sampling step length, specifically, a proper sampling step length is selected according to the sampling time of the obtained cell characteristic data (for example, the sampling time is 15 seconds, the sampling step length is 10 sampling times (for example, 10 15 seconds), and the cell characteristic data with 10 sampling times can be accurately detected), and the time weight probability is calculated according to the sampling step length; in addition, the time intervals of the sampling times are generally uniform.
The second calculating module 23 is configured to calculate a mean voltage difference of all the cells at each sampling time and a voltage difference of each cell;
in this embodiment, the calculation formulas for calculating the average voltage difference of all the cells at each sampling time and the voltage difference of each cell are shown in the formula (2) and the formula (3) in embodiment 1, respectively.
The third calculation module 24 is configured to calculate a trend probability of all the cells and a trend probability of each cell according to the average voltage difference of all the cells, the voltage difference of each cell and the time weight probability;
in this embodiment, the calculation formulas of the trend probabilities of all the cells and the trend probability of each cell are shown in formula (4) in embodiment 1.
The fourth calculation module 25 is configured to calculate cross entropy of the trend probabilities of all the cells and the trend probability of each cell;
in this embodiment, a calculation formula for calculating the cross entropy is shown as formula (5) in embodiment 1.
The detection module 26 is used for performing micro-short circuit detection on the battery cells according to the cross entropy.
In the embodiment, the characteristic data of all the battery cells in the same time period are used for detection, but the characteristic data are converted into short-time trend (namely trend probability), and the distribution of the characteristic data is compared by using a cross entropy method, so that the dependence of micro short circuit detection on the data quantity is greatly reduced, and the effects of real-time detection and early warning are achieved.
As an alternative embodiment, as shown in fig. 2, the detection module 26 includes a first screening unit 261 and a first detection unit 262;
the first screening unit 261 is configured to screen out a maximum cross entropy from the cross entropies;
in this embodiment, the maximum cross entropy indicates the cell most likely to have a micro short circuit in the electric box;
the first detection unit 262 is configured to detect a cell that is about to be in a micro-short state or is already in a micro-short state according to a comparison result of the maximum cross entropy and the first cell safety value.
In this embodiment, the first cell safety value is set according to the actual situation, for example, the first cell safety value may be set to 5, and may be set to other values, which are not limited herein specifically;
as an optional implementation manner, the first detection unit 262 is configured to detect the cell that is in the micro-short state if the maximum cross entropy is greater than the first cell safety value within a preset time; if the maximum cross entropy exceeds the preset time and is larger than the first battery cell safety value, detecting a battery cell in a micro-short circuit state;
in this embodiment, the preset time is set according to the actual situation, for example, the preset time may be set to 1 minute, and may be set to other values;
in this embodiment, the maximum cross entropy is directly used to perform the micro-short circuit detection on the battery cell, specifically, when the maximum cross entropy is greater than the first battery cell safety value (for example, the maximum cross entropy is greater than 5 in 1 minute) in a preset time, the battery cell will be considered to be in the micro-short circuit state, and when the maximum cross entropy is continuously greater than the first battery cell safety value (for example, when the maximum cross entropy is continuously greater than the first battery cell safety value in more than 1 minute), the battery cell can be considered to be in the micro-short circuit state, and the battery cell needs to be processed, and the detection mode of performing the micro-short circuit detection on the battery cell directly using the maximum cross entropy is simple and stable.
As an alternative embodiment, as shown in fig. 2, the detection module 26 further includes a second screening unit 263, a calculation unit 264, and a second detection unit 265;
the second screening unit 263 is used for screening the maximum cross entropy and the minimum cross entropy from the cross entropy;
in this embodiment, the minimum cross entropy represents the safest cell in the cell box.
The calculating unit 264 is configured to divide the maximum cross entropy by the minimum cross entropy to obtain an operation result;
in this embodiment, the calculation formula of the operation result is shown as formula (6) in embodiment 1.
In this embodiment, dividing the maximum cross entropy by the minimum cross entropy may make the data more obvious, and it is actually the least stable cell and the most stable cell divided, so that the data is amplified, and the unstable data can be more intuitively seen.
The second detecting unit 265 is configured to detect a cell that is about to be in a micro-short state or is already in a micro-short state according to a comparison result of the operation result and a second cell safety value, where the second cell safety value is greater than the first cell safety value.
In this embodiment, the second cell safety value is set according to the actual situation, for example, the second cell safety value may be set to 15, and may be set to other values, which are not limited herein specifically;
as an optional implementation manner, the second detecting unit 265 is configured to detect a cell that is to be in a micro-short circuit state if the operation result is greater than the second cell safety value within a preset time; if the operation result exceeds the preset time and is larger than the second cell safety value, detecting the cell in the micro-short circuit state.
In a specific implementation process, scaling treatment can be performed on the cross entropy, and a scaling treatment result is subjected to salifying treatment (namely amplifying treatment), specifically, the maximum cross entropy and the minimum cross entropy are screened out from the cross entropy; dividing the maximum cross entropy by the minimum cross entropy to obtain an operation result; and finer results can be obtained after the salification treatment, so that the problem condition of each piece of data can be more obviously seen, which is equivalent to amplifying the results.
For example, if a large portion of the cells in the electrical box have been problematic, accurate results cannot be obtained, requiring the detection of unsafe electrical boxes using the electrical box data in the power plant battery cluster. According to the method, the data are subjected to salification processing by dividing the maximum cross entropy by the minimum cross entropy, and a finer result can be seen, for example, a second cell safety value used by the method is 15, and when the operation result after the salification processing is larger than the second cell safety value in a preset time, the cell can be considered to be in a micro-short circuit state. When the operation result after the salification exceeds the preset time and is continuously larger than the second cell safety value, the cell can be considered to be in the micro-short circuit state. If some data in micro short circuit is repeated in a period of time in the method of directly detecting the battery cell by using the maximum cross entropy, the data processed by the salifying method can be judged to be abnormal, and a measuring tool is required to be checked instead of checking the micro short circuit.
In the embodiment, the detection result is more visual and finer by using the mode of performing micro short circuit detection on the battery cell through the salification treatment.
In this embodiment, for example, when a micro-short condition occurs, the maximum cross entropy calculation generally exceeds the first cell safety value 5, and when the salification processing method of this embodiment is used, the micro-short can be more obvious and exceeds 15; the cross entropy of the normal battery core can be maintained within 5 no matter how complicated the voltage change condition is, as long as the voltage change condition has no obvious micro short circuit trend, and the result can be maintained within 3 after the salification processing method of the embodiment is used. The detection accuracy is improved.
According to the embodiment, the trend probability of all the electric cores and the trend probability of each electric core are calculated according to the calculated average voltage difference of all the electric cores, the voltage difference of each electric core and the time weight probability; calculating the cross entropy of the trend probability of all the electric cores and the trend probability of each electric core; and carrying out micro short circuit detection on the battery cell according to the cross entropy. The analysis based on cross entropy is realized, the dependence of micro-short circuit detection on the characteristic data of the battery cell is greatly reduced, the effects of real-time detection and early warning are achieved, and the detection efficiency and the detection accuracy of the micro-short circuit are improved.
Example 3
Fig. 3 is a schematic structural diagram of an electronic device according to embodiment 3 of the present invention. The electronic device includes a memory, a processor, and a computer program stored on the memory and configured to run on the processor, wherein the processor implements the method for detecting a micro-short circuit of the battery cell of embodiment 1 when executing the program. The electronic device 30 shown in fig. 3 is only an example and should not be construed as limiting the functionality and scope of use of embodiments of the present invention.
As shown in fig. 3, the electronic device 30 may be embodied in the form of a general purpose computing device, which may be a server device, for example. Components of electronic device 30 may include, but are not limited to: the at least one processor 31, the at least one memory 32, a bus 33 connecting the different system components, including the memory 32 and the processor 31.
The bus 33 includes a data bus, an address bus, and a control bus.
The processor 31 executes various functional applications and data processing, such as the method for detecting a micro-short circuit of a cell of embodiment 1 of the present invention, by running a computer program stored in the memory 32.
The electronic device 30 may also communicate with one or more external devices 34 (e.g., keyboard, pointing device, etc.). Such communication may be through an input/output (I/O) interface 35. Also, model-generating device 30 may also communicate with one or more networks, such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet, via network adapter 36. As shown in fig. 3, network adapter 36 communicates with the other modules of model-generating device 30 via bus 33. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in connection with the model-generating device 30, including, but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, data backup storage systems, and the like.
It should be noted that although several units/modules or sub-units/modules of an electronic device are mentioned in the above detailed description, such a division is merely exemplary and not mandatory. Indeed, the features and functionality of two or more units/modules described above may be embodied in one unit/module in accordance with embodiments of the present invention. Conversely, the features and functions of one unit/module described above may be further divided into ones that are embodied by a plurality of units/modules.
Example 4
The present embodiment provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method for detecting a micro-short circuit of a battery cell provided in embodiment 1.
More specifically, among others, readable storage media may be employed including, but not limited to: portable disk, 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 embodiment, the invention may also be implemented in the form of a program product comprising program code for causing a terminal device to carry out the method for detecting a micro-short of a cell as described in embodiment 1, when the program product is run on the terminal device.
Wherein the program code for carrying out the invention may be written in any combination of one or more programming languages, the program code may execute entirely on the user device, partly on the user device, as a stand-alone software package, partly on the user device, 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 the scope of the invention is defined by the appended claims. Various changes and modifications to these embodiments may be made by those skilled in the art without departing from the principles and spirit of the invention, but such changes and modifications fall within the scope of the invention.
Claims (10)
1. The detection method of the micro short circuit of the battery cell is characterized by comprising the following steps of:
acquiring sampling time of cell characteristic data, wherein the cell characteristic data comprises voltage;
calculating time weight probability according to the sampling time;
calculating the average voltage difference of all the battery cells of each sampling time and the voltage difference of each battery cell;
calculating trend probabilities of all the electric cores and trend probabilities of each electric core according to the average voltage difference of all the electric cores, the voltage difference of each electric core and the time weight probability;
calculating cross entropy of the trend probabilities of all the electric cores and the trend probability of each electric core;
and carrying out micro short circuit detection on the battery cell according to the cross entropy.
2. The method for detecting a micro-short circuit of a battery cell according to claim 1, wherein the step of performing the micro-short circuit detection on the battery cell according to the cross entropy comprises:
screening out the maximum cross entropy from the cross entropies;
and detecting the battery cell which is about to be in the micro-short circuit state or is already in the micro-short circuit state according to the comparison result of the maximum cross entropy and the first battery cell safety value.
3. The method for detecting a micro-short circuit of a battery cell according to claim 2, wherein the step of performing the micro-short circuit detection on the battery cell according to the cross entropy further comprises:
screening out the maximum cross entropy and the minimum cross entropy from the cross entropy;
dividing the maximum cross entropy by the minimum cross entropy to obtain an operation result;
and detecting the battery cell which is about to be in the micro-short circuit state or is in the micro-short circuit state according to the comparison result of the operation result and a second battery cell safety value, wherein the second battery cell safety value is larger than the first battery cell safety value.
4. The method for detecting a micro-short circuit of a battery cell according to claim 3, wherein the step of detecting the battery cell which is about to be in a micro-short circuit state or is already in a micro-short circuit state according to the comparison result of the maximum cross entropy and the first battery cell safety value comprises:
if the maximum cross entropy is larger than the first battery cell safety value within the preset time, detecting a battery cell which is in a micro short circuit state; if the maximum cross entropy exceeds the preset time and is larger than the first battery cell safety value, detecting a battery cell in a micro-short circuit state;
and/or the number of the groups of groups,
the step of detecting the cell which is about to be in the micro-short circuit state or is already in the micro-short circuit state according to the comparison result of the operation result and the second cell safety value comprises the following steps:
if the operation result is larger than the second battery cell safety value within the preset time, detecting a battery cell which is in a micro short circuit state; and if the operation result exceeds the preset time and is larger than the second battery cell safety value, detecting the battery cell in the micro-short circuit state.
5. The detection system of the micro short circuit of the battery cell is characterized by comprising an acquisition module, a first calculation module, a second calculation module, a third calculation module, a fourth calculation module and a detection module;
the acquisition module is used for acquiring sampling time of the battery cell characteristic data, wherein the battery cell characteristic data comprises voltage;
the first calculation module is used for calculating time weight probability according to the sampling time;
the second calculation module is used for calculating the average voltage difference of all the battery cells at each sampling time and the voltage difference of each battery cell;
the third calculation module is configured to calculate a trend probability of all the electric cells and a trend probability of each electric cell according to the average voltage difference of all the electric cells, the voltage difference of each electric cell and the time weight probability;
the fourth calculation module is used for calculating cross entropy of the trend probability of all the battery cells and the trend probability of each battery cell;
and the detection module is used for carrying out micro short circuit detection on the battery cell according to the cross entropy.
6. The system for detecting a micro-short circuit of a cell according to claim 5, wherein the detection module comprises a first screening unit and a first detection unit;
the first screening unit is used for screening the maximum cross entropy from the cross entropies;
and the first detection unit is used for detecting the battery cell which is about to be in the micro-short circuit state or is already in the micro-short circuit state according to the comparison result of the maximum cross entropy and the first battery cell safety value.
7. The system for detecting a micro-short circuit of a cell according to claim 6, wherein the detection module further comprises a second screening unit, a calculation unit, and a second detection unit;
the second screening unit is used for screening out the maximum cross entropy and the minimum cross entropy from the cross entropy;
the computing unit is used for dividing the maximum cross entropy by the minimum cross entropy to obtain an operation result;
the second detection unit is used for detecting the battery cell which is about to be in the micro-short circuit state or is in the micro-short circuit state according to the comparison result of the operation result and a second battery cell safety value, and the second battery cell safety value is larger than the first battery cell safety value.
8. The system for detecting a micro-short circuit of a battery cell according to claim 7, wherein the first detection unit is configured to detect the battery cell that is in a micro-short circuit state if the maximum cross entropy is greater than the first battery cell safety value within a preset time; if the maximum cross entropy exceeds the preset time and is larger than the first battery cell safety value, detecting a battery cell in a micro-short circuit state;
and/or the number of the groups of groups,
the second detection unit is used for detecting a battery cell which is in a micro short circuit state if the operation result is larger than the second battery cell safety value within a preset time; and if the operation result exceeds the preset time and is larger than the second battery cell safety value, detecting the battery cell in the micro-short circuit state.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory for execution on the processor, wherein the processor implements the method of detecting a cell micro-short according to any one of claims 1-4.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the method for detecting a micro-short of a cell according to any one of claims 1-4.
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