CN117054903B - Method and system for monitoring abnormality of automobile battery pack - Google Patents
Method and system for monitoring abnormality of automobile battery pack Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/385—Arrangements for measuring battery or accumulator variables
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
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Abstract
The invention provides an anomaly monitoring method and system for an automobile battery pack, which belong to the field of data processing, and calculate a state superposition grid through a plurality of temperature value matrixes, pressure value matrixes and resistance value time sequences corresponding to different times; according to the state stacking grid, abnormal state monitoring is carried out on the battery pack, the defects of the conventional technology in the aspects of lack of multidimensional information and lack of dynamic monitoring capability are overcome, more accurate, comprehensive and reliable abnormal state monitoring of the battery pack can be provided, and better guarantee is provided for safety and reliability of an electric automobile.
Description
Technical Field
The invention belongs to the field of data processing, and particularly relates to an automobile battery pack abnormality monitoring method and system.
Background
With the popularization of electric vehicles, battery packs play a vital role as energy storage devices for electric vehicles. However, the battery pack is susceptible to various abnormal conditions such as overheating, pressure abnormality, contact resistance change, and the like, in a long-term use and in a severe environment. These abnormal conditions may negatively affect the performance, life and safety of the battery pack. The traditional method is used for monitoring the whole temperature and the whole pressure of the battery pack, and cannot monitor the tiny subareas. Therefore, the accuracy and precision of monitoring are reduced, detailed analysis on specific abnormal conditions cannot be performed, for example, a high-voltage safety temperature detection system for a new energy automobile described in patent document with publication number of CN116278757A only focuses on single parameters such as temperature or pressure, and cannot comprehensively consider the influence of multiple parameters on the abnormal state of a battery pack. Other important factors are easily ignored, so that the monitoring result is incomplete and inaccurate. The conventional method is used for monitoring the battery pack only at a specific moment, for example, a lithium battery thermal runaway monitoring and early warning device and method described in patent document with publication number of CN115376289A cannot acquire the variation trend of parameters such as temperature, pressure, contact resistance and the like of the battery pack in real time. Thus, potential abnormal conditions cannot be found in time, and early warning and processing are performed.
Disclosure of Invention
The invention aims to provide a method and a system for monitoring abnormality of an automobile battery pack, which are used for solving one or more technical problems in the prior art and at least providing a beneficial selection or creation condition.
The invention provides an anomaly monitoring method and system for an automobile battery pack, wherein the temperature value of each divided subarea is acquired, a temperature value square matrix is formed by the temperature values corresponding to the divided subareas, and the temperature value square matrix is acquired at a plurality of different moments; the pressure received by each divided subarea is monitored to obtain pressure values, a pressure value square matrix is formed by the pressure values corresponding to each divided subarea, and the pressure value square matrix is obtained at the plurality of different moments; calculating a state superposition grid according to a plurality of temperature value square matrixes and pressure value square matrixes corresponding to different moments and a resistance value time sequence; and monitoring the abnormal state of the battery pack according to the state superposition grid. The method overcomes the defects of the traditional technology in the aspects of lack of multi-dimensional information and lack of dynamic monitoring capability by dividing subareas, multi-dimensional parameter monitoring and dynamic monitoring, can provide more accurate, comprehensive and reliable monitoring of abnormal states of the battery pack, and provides better guarantee for the safety and reliability of the electric automobile.
In order to achieve the above object, according to an aspect of the present invention, there is provided a method for monitoring abnormality of a battery pack of an automobile, the method comprising the steps of:
dividing a bottom plate of the battery pack to obtain a plurality of divided subareas, and arranging the divided subareas into a subarea matrix in a matrix form; in the subarea square matrix, acquiring a temperature value of each divided subarea, forming a temperature value square matrix by the temperature values corresponding to the divided subareas, and acquiring the temperature value square matrix from the subarea square matrix at a plurality of different moments; in the subarea square matrix, monitoring the pressure received by each divided subarea to obtain pressure values, forming a pressure value square matrix by the pressure values corresponding to the divided subareas, and obtaining the pressure value square matrix from the subarea square matrix at the plurality of different moments;
acquiring contact resistance values of the output end of the battery pack at a plurality of different moments to form a resistance value time sequence; calculating a state superposition grid according to a plurality of temperature value square matrixes and pressure value square matrixes corresponding to different moments and a resistance value time sequence; and monitoring the abnormal state of the battery pack according to the state superposition grid.
Further, by setting and dividing the battery pack bottom plate, dividing subareas comprising a monitoring coordinate system and a plurality of numbers are obtained, wherein the number of the dividing subareas obtained by dividing the battery pack bottom plate can be decomposed into two positive integers with equal numerical values in numerical value factorization.
Further, the battery pack is evenly divided and sampled on the bottom plate, and the distances among all the divided subareas are equal.
Further, the divided subareas are arranged into subarea matrixes in the form of matrixes with equal row and column sizes.
Further, according to the temperature value square matrix, the pressure value square matrix and the resistance value time sequence which correspond to a plurality of different moments, the method for calculating the state superposition grid comprises the following steps:
forming a temperature value matrix sequence by using a plurality of temperature value matrixes corresponding to different moments, forming a pressure value matrix sequence by using a plurality of pressure value matrixes corresponding to different moments, and mutually aligning each element in the temperature value matrix sequence and each element in the pressure value matrix sequence according to the corresponding moments and keeping a corresponding relation;
calculating the temperature univariate vector of the temperature value square matrix at each moment, and taking the unit feature vector obtained by the matrix operation of the linear algebra of each temperature value square matrix as the temperature univariate vector;
calculating the pressure value single variable vector of the pressure value square matrix at each moment, and taking the unit feature vector obtained by the matrix operation of the linear algebra of each pressure value square matrix as the pressure value single variable vector;
calculating variable resistance densities of the resistance values corresponding to all the moments in the resistance value time sequence, respectively calculating the probability densities of the resistance values corresponding to all the moments in the probability distribution of the values of the resistance value time sequence, counting the probability distribution of the values of the resistance values corresponding to all the moments in the resistance value time sequence, and dividing the probability distribution of the values of the resistance values into intervals corresponding to the number of the moments of the plurality of different moments, thereby counting the probability densities of the resistance values corresponding to all the moments falling in the intervals as the variable resistance densities corresponding to all the moments, wherein the probability densities can be normalized to be 0 to 1;
temperature and pressure data of the battery pack are obtained in a regional mode at multiple moments, a temperature change comparison vector and a pressure value comparison vector are obtained through contrast calculation, and the state of health of the battery pack is estimated more comprehensively and accurately through the probability combination mode of the cross data types;
calculating cosine similarity of the temperature univariate vector at each moment and the temperature univariate vectors at other moments, calculating arithmetic average value of the cosine similarity as temperature contrast of the temperature univariate vector at the moment, multiplying the numerical value of each dimension of the temperature univariate vector at the moment by the temperature contrast to obtain a temperature variation contrast vector at the moment, and forming a temperature variation time matrix by the temperature variation contrast vectors at the moments;
calculating cosine similarity of the pressure value single variable vector at each moment and the pressure value single variable vectors at other moments, calculating arithmetic average value of the cosine similarity as pressure value contrast of the pressure value single variable vector at the moment, multiplying the value of each dimension of the pressure value single variable vector at the moment by the pressure value contrast to obtain a pressure value contrast vector at the moment, and forming a pressure change time matrix by the pressure value contrast vectors at the moments;
it is worth noting that the temperature change comparison vector composition temperature change time matrix at each moment compares the comparison characteristics of the temperature single change vectors at other moments in a cross-moment manner, so that the global property of the temperature characteristics is extracted, the temperature change comparison vectors at each moment can be parallelized, the calculation time cost is low, and the pressure value comparison vector composition pressure change time matrix at each moment also compares the comparison characteristics of the pressure value single change vectors at other moments in a cross-moment manner, so that the global property of the pressure value characteristics is better extracted under the condition of not increasing the calculation time cost;
the temperature change contrast vector and the pressure value contrast vector at each moment are subjected to dot multiplication to obtain a temperature pressure contrast vector at each moment;
the method comprises the steps of selecting a first characteristic of a maximum dimension value from temperature-pressure comparison vectors at each moment, selecting a second characteristic of the maximum dimension value, wherein the second characteristic of the maximum dimension value is the median or mode dimension value, taking the probability ratio between the first characteristic of the moment and the variable resistance density at the moment as the maximum state ratio at the moment, taking the probability ratio between the second characteristic of the moment and the variable resistance density at the moment as the general state ratio at the moment, wherein the probability ratio can be the ratio between two probability values or the distance on probability distribution, representing the difference of the two probability characteristics or the probability density and the like on the linear probability distribution, and calculating the maximum state ratio and the general state ratio in the temperature-pressure comparison vectors by monitoring and analyzing the temperature, the pressure and the contact resistance of different areas, so that potential problems can be better positioned and tracked, the safety of battery packs can be facilitated, the sequence consisting of the maximum state ratio at each moment is taken as a first state ratio chain, the sequence consisting of the maximum state ratios at each moment is taken as a second state ratio, and the second state ratio at each moment is taken as a second state ratio, and the first state ratio is better than the state ratio of a superposition state ratio.
Further, according to the state stacking grid, the abnormal state of the battery pack is monitored, specifically:
in the first state ratio chain of the state stacking grid, calculating the ratio of the maximum state ratio of each time except the first time to the numerical value of the maximum state ratio of each time respectively to the first time as the maximum state trend, calculating the ratio of the numerical value of the general state ratio of each time except the first time to the numerical value of the general state ratio of each time respectively to the first time as the general state trend, in order to prevent that the numerical value of the denominator between the two maximum state ratios is zero, and therefore the ratio cannot be calculated, in some embodiments, the average value in each maximum state ratio or the average value in each general state ratio can be respectively and correspondingly added on the numerator and the denominator, and the abnormal state monitoring can be carried out on the battery pack according to the maximum state trend and the general state trend, wherein: in some embodiments, calculating a ratio of the maximum state trend to the general state trend, and if the ratio of the maximum state trend to the general state trend is greater than a preset threshold, preferably taking 1.36 to 1.45 as the preset threshold, indicating that the battery pack is in an abnormal state and the battery pack is overloaded; in some embodiments, the difference between the maximum state trend and the general state trend is calculated, and if the difference between the maximum state trend and the general state trend is negative, the battery pack is in an abnormal state, and a part of the battery pack is not operated and needs to be stopped for detection. Different from the prior art, which lacks multidimensional information and lacks dynamic monitoring capability, the method for monitoring the abnormal state of the battery pack according to the state superposition grid can provide more accurate, comprehensive and reliable monitoring of the abnormal state of the battery pack, and provides better guarantee for the safety and reliability of the electric automobile.
The invention also provides an automobile battery pack abnormality monitoring system, which comprises: the processor executes the computer program to implement steps in the method for monitoring abnormal automobile battery pack, the system for monitoring abnormal automobile battery pack can be operated in a computing device such as a desktop computer, a notebook computer, a palm computer and a cloud data center, and the operable system can comprise, but is not limited to, a processor, a memory and a server cluster, and the processor executes the computer program to operate in the following units:
the device comprises a dividing unit, a dividing unit and a control unit, wherein the dividing unit is used for dividing a bottom plate of a battery pack to obtain a plurality of dividing subareas, arranging the dividing subareas into subarea matrixes in a matrix form, acquiring a temperature value of each dividing subarea in the subarea matrixes, forming a temperature value matrix by the temperature value corresponding to each dividing subarea, acquiring the temperature value matrix by the subarea matrixes at a plurality of different moments, monitoring the pressure received by each dividing subarea in the subarea matrixes to acquire a pressure value, forming a pressure value matrix by the pressure value corresponding to each dividing subarea, and acquiring the pressure value matrix by the subarea matrixes at the plurality of different moments;
the calculating unit is used for obtaining the contact resistance values of the output end of the battery pack at the plurality of different moments to form a resistance value time sequence, and calculating a state superposition grid according to the temperature value square matrix, the pressure value square matrix and the resistance value time sequence corresponding to the plurality of different moments;
and the monitoring unit is used for monitoring the abnormal state of the battery pack according to the state superposition grid.
The beneficial effects of the invention are as follows: the invention provides a method and a system for monitoring abnormality of an automobile battery pack, which calculate a state superposition grid through a plurality of temperature value matrixes, pressure value matrixes and resistance value time sequences corresponding to different moments; according to the state stacking grid, abnormal state monitoring is carried out on the battery pack, the defects of the conventional technology in the aspects of lack of multidimensional information and lack of dynamic monitoring capability are overcome, more accurate, comprehensive and reliable abnormal state monitoring of the battery pack can be provided, and better guarantee is provided for safety and reliability of an electric automobile.
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The above and other features of the present invention will become more apparent from the detailed description of the embodiments thereof given in conjunction with the accompanying drawings, in which like reference characters designate like or similar elements, and it is apparent that the drawings in the following description are merely some examples of the present invention, and other drawings may be obtained from these drawings without inventive effort to those of ordinary skill in the art, in which:
FIG. 1 is a flow chart of a method for monitoring anomalies in an automotive battery pack;
fig. 2 is a system configuration diagram of an abnormality monitoring system for an automobile battery pack.
Detailed Description
The conception, specific structure, and technical effects produced by the present invention will be clearly and completely described below with reference to the embodiments and the drawings to fully understand the objects, aspects, and effects of the present invention. It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other.
In the description of the present invention, a number means one or more, a number means two or more, and greater than, less than, exceeding, etc. are understood to not include the present number, and above, below, within, etc. are understood to include the present number. The description of the first and second is for the purpose of distinguishing between technical features only and should not be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
Referring to fig. 1, a flowchart of an abnormality monitoring method for an automobile battery pack according to the present invention is shown, and an abnormality monitoring method and system for an automobile battery pack according to an embodiment of the present invention are described below with reference to fig. 1.
The invention provides an anomaly monitoring method for an automobile battery pack, which specifically comprises the following steps:
dividing a bottom plate of the battery pack to obtain a plurality of divided subareas, and arranging the divided subareas into a subarea matrix in a matrix form; in the subarea square matrix, acquiring a temperature value of each divided subarea, forming a temperature value square matrix by the temperature values corresponding to the divided subareas, and acquiring the temperature value square matrix from the subarea square matrix at a plurality of different moments; in the subarea square matrix, monitoring the pressure received by each divided subarea to obtain pressure values, forming a pressure value square matrix by the pressure values corresponding to the divided subareas, and obtaining the pressure value square matrix from the subarea square matrix at the plurality of different moments;
acquiring contact resistance values of the output end of the battery pack at a plurality of different moments to form a resistance value time sequence; calculating a state superposition grid according to a plurality of temperature value square matrixes and pressure value square matrixes corresponding to different moments and a resistance value time sequence;
and monitoring the abnormal state of the battery pack according to the state superposition grid.
Further, by setting and dividing the battery pack bottom plate, dividing subareas comprising a monitoring coordinate system and a plurality of numbers are obtained, wherein the number of the dividing subareas obtained by dividing the battery pack bottom plate can be decomposed into two positive integers with equal numerical values in numerical value factorization.
Further, the battery pack is evenly divided and sampled on the bottom plate, and the distances among all the divided subareas are equal.
Further, the divided subareas are arranged into subarea matrixes in the form of matrixes with equal row and column sizes.
Further, according to the temperature value square matrix, the pressure value square matrix and the resistance value time sequence which correspond to a plurality of different moments, the method for calculating the state superposition grid comprises the following steps:
forming a temperature value matrix sequence by using a plurality of temperature value matrixes corresponding to different moments, forming a pressure value matrix sequence by using a plurality of pressure value matrixes corresponding to different moments, and mutually aligning each element in the temperature value matrix sequence and each element in the pressure value matrix sequence according to the corresponding moments and keeping a corresponding relation;
calculating the temperature univariate vector of the temperature value square matrix at each moment, and taking the unit feature vector obtained by the matrix operation of the linear algebra of each temperature value square matrix as the temperature univariate vector;
calculating the pressure value single variable vector of the pressure value square matrix at each moment, and taking the unit feature vector obtained by the matrix operation of the linear algebra of each pressure value square matrix as the pressure value single variable vector;
calculating variable resistance densities of the resistance values corresponding to all the moments in the resistance value time sequence, respectively calculating the probability densities of the resistance values corresponding to all the moments in the probability distribution of the values of the resistance value time sequence, counting the probability distribution of the values of the resistance values corresponding to all the moments in the resistance value time sequence, and dividing the probability distribution of the values of the resistance values into intervals corresponding to the number of the moments of the plurality of different moments, thereby counting the probability densities of the resistance values corresponding to all the moments falling in the intervals as the variable resistance densities corresponding to all the moments, wherein the probability densities can be normalized to be 0 to 1;
calculating cosine similarity of the temperature univariate vector at each moment and the temperature univariate vectors at other moments, calculating arithmetic average value of the cosine similarity as temperature contrast of the temperature univariate vector at the moment, multiplying the numerical value of each dimension of the temperature univariate vector at the moment by the temperature contrast to obtain a temperature variation contrast vector at the moment, and forming a temperature variation time matrix by the temperature variation contrast vectors at the moments;
calculating cosine similarity of the pressure value single variable vector at each moment and the pressure value single variable vectors at other moments, calculating arithmetic average value of the cosine similarity as pressure value contrast of the pressure value single variable vector at the moment, multiplying the value of each dimension of the pressure value single variable vector at the moment by the pressure value contrast to obtain a pressure value contrast vector at the moment, and forming a pressure change time matrix by the pressure value contrast vectors at the moments;
the temperature change contrast vector and the pressure value contrast vector at each moment are subjected to dot multiplication to obtain a temperature pressure contrast vector at each moment;
the method comprises the steps of selecting a first characteristic of a moment in which a value of a dimension with the largest value is the first characteristic of the moment, selecting a second characteristic of the moment in which a value of a dimension with the middle or mode is the second characteristic of the moment, taking the probability ratio between the first characteristic of the moment and the variable resistance density of the moment as the maximum state ratio of the moment, taking the probability ratio between the second characteristic of the moment and the variable resistance density of the moment as the general state ratio of the moment, wherein the probability ratio can be the ratio between two probability values or the distance on a probability distribution, representing the difference of the two probability characteristics or the probability density and the like on the linear probability distribution, taking a sequence formed by the maximum state ratio of the moment as a first state ratio chain, taking a sequence formed by the general state ratio of the moment as a second state ratio chain, and mutually aligning the first state ratio chain and the second state ratio chain to obtain a state stack grid.
Further, according to the state stacking grid, the abnormal state of the battery pack is monitored, specifically:
in the first state ratio chain of the state stacking grid, calculating the ratio of the maximum state ratio of each time except the first time to the numerical value of the maximum state ratio of each time respectively to the first time as the maximum state trend, calculating the ratio of the numerical value of the general state ratio of each time except the first time to the numerical value of the general state ratio of each time respectively to the first time as the general state trend, in order to prevent that the numerical value of the denominator between the two maximum state ratios is zero, and therefore the ratio cannot be calculated, in some embodiments, the average value in each maximum state ratio or the average value in each general state ratio can be respectively and correspondingly added on the numerator and the denominator, and the abnormal state monitoring can be carried out on the battery pack according to the maximum state trend and the general state trend, wherein:
in some embodiments, calculating a ratio of the maximum state trend to the general state trend, and if the ratio of the maximum state trend to the general state trend is greater than a preset threshold, preferably taking 1.36 to 1.45 as the preset threshold, indicating that the battery pack is in an abnormal state and the battery pack is overloaded;
in some embodiments, the difference between the maximum state trend and the general state trend is calculated, and if the difference between the maximum state trend and the general state trend is negative, the battery pack is in an abnormal state, and a part of the battery pack is not operated and needs to be stopped for detection.
The abnormal monitoring system of the automobile battery pack is operated in any computing device of a desktop computer, a notebook computer, a palm computer or a cloud data center, and the computing device comprises: a processor, a memory, and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the method for monitoring the anomaly of the battery pack of the automobile when executing the computer program, and the operable system can comprise, but is not limited to, a processor, a memory, and a server cluster.
As shown in fig. 2, an abnormality monitoring system for an automobile battery pack according to an embodiment of the present invention includes: a processor, a memory, and a computer program stored in the memory and executable on the processor, the processor implementing the steps in one embodiment of the method for monitoring an anomaly of a battery pack of an automobile when the computer program is executed, the processor executing the computer program to run in a unit of the following system:
the device comprises a dividing unit, a dividing unit and a control unit, wherein the dividing unit is used for dividing a bottom plate of a battery pack to obtain a plurality of dividing subareas, arranging the dividing subareas into subarea matrixes in a matrix form, acquiring a temperature value of each dividing subarea in the subarea matrixes, forming a temperature value matrix by the temperature value corresponding to each dividing subarea, acquiring the temperature value matrix by the subarea matrixes at a plurality of different moments, monitoring the pressure received by each dividing subarea in the subarea matrixes to acquire a pressure value, forming a pressure value matrix by the pressure value corresponding to each dividing subarea, and acquiring the pressure value matrix by the subarea matrixes at the plurality of different moments;
the calculating unit is used for obtaining the contact resistance values of the output end of the battery pack at the plurality of different moments to form a resistance value time sequence, and calculating a state superposition grid according to the temperature value square matrix, the pressure value square matrix and the resistance value time sequence corresponding to the plurality of different moments;
and the monitoring unit is used for monitoring the abnormal state of the battery pack according to the state superposition grid.
Preferably, all undefined variables in the present invention may be threshold set manually if not explicitly defined.
The automobile battery pack abnormality monitoring system can be operated in computing equipment such as a desktop computer, a notebook computer, a palm computer, a cloud data center and the like. The automobile battery pack abnormality monitoring system comprises, but is not limited to, a processor and a memory. It will be appreciated by those skilled in the art that the examples are merely examples of an automobile battery pack abnormality monitoring method and system, and do not constitute limitation of an automobile battery pack abnormality monitoring method and system, and may include more or fewer components than examples, or may combine certain components, or different components, e.g., the automobile battery pack abnormality monitoring system may further include an input/output device, a network access device, a bus, etc.
The processor may be a central processing unit (Central Processing Unit, CPU), other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete component gate or transistor logic devices, discrete hardware components, or the like. The general processor may be a microprocessor or the processor may be any conventional processor, etc., and the processor is a control center of the automobile battery pack abnormality monitoring system, and various interfaces and lines are used to connect various sub-areas of the entire automobile battery pack abnormality monitoring system.
The memory may be used to store the computer program and/or module, and the processor may implement various functions of the method and system for monitoring the anomaly of the battery pack of the vehicle by running or executing the computer program and/or module stored in the memory and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data (such as audio data, phonebook, etc.) created according to the use of the handset, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash Card (Flash Card), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
The invention provides a method and a system for monitoring abnormality of an automobile battery pack, which calculate a state superposition grid through a plurality of temperature value matrixes, pressure value matrixes and resistance value time sequences corresponding to different moments; according to the state stacking grid, abnormal state monitoring is carried out on the battery pack, the defects of the conventional technology in the aspects of lack of multidimensional information and lack of dynamic monitoring capability are overcome, more accurate, comprehensive and reliable abnormal state monitoring of the battery pack can be provided, and better guarantee is provided for safety and reliability of an electric automobile.
Although the present invention has been described in considerable detail and with particularity with respect to several described embodiments, it is not intended to be limited to any such detail or embodiment or any particular embodiment so as to effectively cover the intended scope of the invention. Furthermore, the foregoing description of the invention has been presented in its embodiments contemplated by the inventors for the purpose of providing a useful description, and for the purposes of providing a non-essential modification of the invention that may not be presently contemplated, may represent an equivalent modification of the invention.
Claims (6)
1. An automobile battery pack abnormality monitoring method, characterized by comprising the following steps:
dividing a bottom plate of the battery pack to obtain a plurality of divided subareas, and arranging the divided subareas into a subarea matrix in a matrix form; in the subarea square matrix, acquiring a temperature value of each divided subarea, forming a temperature value square matrix by the temperature values corresponding to the divided subareas, and acquiring the temperature value square matrix from the subarea square matrix at a plurality of different moments; in the subarea square matrix, monitoring the pressure received by each divided subarea to obtain pressure values, forming a pressure value square matrix by the pressure values corresponding to the divided subareas, and obtaining the pressure value square matrix from the subarea square matrix at the plurality of different moments;
acquiring contact resistance values of the output end of the battery pack at a plurality of different moments to form a resistance value time sequence;
calculating a state superposition grid according to a plurality of temperature value square matrixes and pressure value square matrixes corresponding to different moments and a resistance value time sequence;
according to the state superposition grid, monitoring the abnormal state of the battery pack: in a first state ratio chain of the state superposition grid, calculating the ratio of the maximum state ratio of each time except the first time to the numerical value of the maximum state ratio of each time except the first time as a maximum state trend, calculating the ratio of the general state ratio of each time except the first time to the numerical value of the general state ratio of each time except the first time as a general state trend, and monitoring the abnormal state of the battery pack according to the maximum state trend and the general state trend, wherein the method comprises the following steps of: calculating the ratio of the maximum state trend to the general state trend, and if the ratio of the maximum state trend to the general state trend is larger than a preset threshold value, indicating that the battery pack is in an abnormal state and the battery pack is overloaded; or calculating the difference value between the maximum state trend and the general state trend, if the difference value between the maximum state trend and the general state trend is negative, the battery pack is in an abnormal state, and the battery pack is not operated and needs to be stopped for detection.
2. The method for monitoring the abnormality of the battery pack of the automobile according to claim 1, wherein the dividing subareas comprising the monitoring coordinate system and a plurality of numbers are obtained by setting and dividing the battery pack bottom plate, wherein the number of the dividing subareas obtained by dividing the battery pack bottom plate can be decomposed into two positive integers with equal values in the factorization of the values.
3. The method for monitoring the abnormality of the battery pack of the automobile according to claim 2, wherein the battery pack is divided and sampled uniformly on the bottom plate of the battery pack, and distances between the divided sub-areas are equal.
4. The method for monitoring the abnormality of the battery pack of the automobile according to claim 1, wherein the divided subareas are arranged in a subarea matrix in the form of a matrix of equal row and column sizes.
5. The method for monitoring the abnormality of the automobile battery pack according to claim 1, wherein the method for calculating the state superposition grid according to the temperature value square matrix, the pressure value square matrix and the resistance value time series corresponding to a plurality of different moments is as follows: forming a temperature value matrix sequence by using a plurality of temperature value matrixes corresponding to different moments, and forming a pressure value matrix sequence by using a plurality of pressure value matrixes corresponding to different moments;
the unit eigenvector calculated by each temperature value square matrix through linear algebra matrix operation is used as the temperature univariate vector;
the unit eigenvector calculated by each pressure value matrix through linear algebraic matrix operation is used as the pressure value univariate vector;
calculating the variable resistance density of the resistance value corresponding to each moment in the resistance value time sequence, respectively calculating the probability density corresponding to the resistance value corresponding to each moment in the probability distribution of the numerical value of the resistance value time sequence, and counting the probability density of the resistance value corresponding to each moment falling in the interval as the variable resistance density corresponding to each moment;
calculating cosine similarity of the temperature univariate vector at each moment and the temperature univariate vectors at other moments, calculating arithmetic average value of the cosine similarity as temperature contrast of the temperature univariate vector at the moment, multiplying the numerical value of each dimension of the temperature univariate vector at the moment by the temperature contrast to obtain a temperature variation contrast vector at the moment, and forming a temperature variation time matrix by the temperature variation contrast vectors at the moments;
calculating cosine similarity of the pressure value single variable vector at each moment and the pressure value single variable vectors at other moments, calculating arithmetic average value of the cosine similarity as pressure value contrast of the pressure value single variable vector at the moment, multiplying the value of each dimension of the pressure value single variable vector at the moment by the pressure value contrast to obtain a pressure value contrast vector at the moment, and forming a pressure change time matrix by the pressure value contrast vectors at the moments;
the temperature change contrast vector and the pressure value contrast vector at each moment are subjected to dot multiplication to obtain a temperature pressure contrast vector at each moment;
and selecting a first characteristic of which the value is the largest dimension as the moment in the temperature-pressure comparison vector of each moment, selecting a second characteristic of which the value is the middle or mode dimension as the moment, taking the probability ratio between the first characteristic of the moment and the variable resistance density of the moment as the maximum state ratio of the moment, taking the probability ratio between the second characteristic of the moment and the variable resistance density of the moment as the general state ratio of the moment, taking the sequence formed by the maximum state ratios of the moment as a first state ratio chain, taking the sequence formed by the general state ratios of the moments as a second state ratio chain, and mutually aligning the first state ratio chain and the second state ratio chain to obtain a state superposition grid.
6. An automobile battery pack abnormality monitoring system, wherein the automobile battery pack abnormality monitoring system operates in any one of a desktop computer, a notebook computer or a cloud data center, the computing device comprising: a processor, a memory and a computer program stored in the memory and running on the processor, the processor implementing the steps in a method for monitoring anomalies in an automotive battery pack according to any one of claims 1 to 5 when the computer program is executed.
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