CN113406524B - Inconsistent fault diagnosis method and system for power battery system - Google Patents
Inconsistent fault diagnosis method and system for power battery system 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]
- G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
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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
- G01R31/005—Testing of electric installations on transport means
- G01R31/006—Testing of electric installations on transport means on road vehicles, e.g. automobiles or trucks
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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]
- G01R31/3644—Constructional arrangements
- G01R31/3648—Constructional arrangements comprising digital calculation means, e.g. for performing an algorithm
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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]
- G01R31/385—Arrangements for measuring battery or accumulator variables
Abstract
The invention discloses a method and a system for diagnosing inconsistency fault of a power battery system, which relate to the field of power battery systems and comprise the steps of obtaining real vehicle operation data of the power battery system of a vehicle and constructing a voltage amplitude characteristic matrix; one element in the voltage amplitude characteristic matrix represents an amplitude characteristic value of voltage data of a jth power battery monomer under the corresponding frequency of an xth sampling point; determining a voltage inconsistency abnormal coefficient matrix according to the voltage amplitude characteristic matrix; one element of the voltage inconsistency abnormal coefficient matrix represents a voltage inconsistency abnormal coefficient of a jth power battery monomer under the corresponding frequency of the xth sampling point; and determining the power battery monomer with the voltage inconsistency fault according to the voltage inconsistency abnormal coefficient matrix. According to the invention, the frequency domain index of the power battery monomer acquisition parameter is considered, so that the voltage inconsistency fault of the power battery monomer can be accurately diagnosed.
Description
Technical Field
The invention relates to the field of power battery systems, in particular to a method and a system for diagnosing inconsistency faults of a power battery system.
Background
The power battery is one of main factors influencing the safety of the new energy automobile, timely and effectively identifies and positions the faults of the power battery, and has important significance for improving the safety supervision level of the new energy automobile. In order to meet the requirements of voltage and capacity, a power battery system is generally formed by connecting a certain number of battery cells in series and parallel. The inconsistency of the battery cells caused by the difference of the battery cells is a key factor influencing the performance and the safety of the whole power battery system.
The non-uniformity of the cells originates from the manufacturing process of the cells and can be further exacerbated during operation of the power battery system. As the cell inconsistency deteriorates over the service life, accelerated degradation of power battery system capacity and power capability will result, possibly even leading to serious thermal runaway accidents. Therefore, a fault diagnosis system for power battery inconsistency is important.
At present, fault diagnosis methods for power battery inconsistency can be mainly classified into three categories, namely methods based on signal processing, models and information fusion. In the method based on signal processing, the inconsistency characteristics are mostly limited to the dimension of time domain analysis, the frequency domain index of the power battery acquisition parameters is ignored, and obviously, the method cannot accurately diagnose the inconsistency fault of the power battery.
Disclosure of Invention
In view of this, the present invention provides a method and a system for diagnosing an inconsistency fault of a power battery system.
In order to achieve the purpose, the invention provides the following scheme:
a method of diagnosing an inconsistency fault in a power battery system, comprising:
acquiring real vehicle operation data of a vehicle power battery system; the vehicle power battery system comprises n power battery monomers;
constructing a voltage amplitude characteristic matrix according to the real vehicle operation data; the voltage amplitude characteristic matrix is a matrix with N/2 rows and N columns, and an element a in the voltage amplitude characteristic matrixx,jRepresenting the amplitude characteristic value of voltage data of the jth power battery monomer under the corresponding frequency of the xth sampling point, wherein N represents the total number of the sampling points;
determining a voltage inconsistency abnormal coefficient matrix according to the voltage amplitude characteristic matrix; the voltage inconsistency abnormal coefficient matrix is a matrix with N/2 rows and N columns, and an element k of the voltage inconsistency abnormal coefficient matrixx,jThe voltage inconsistency abnormal coefficient of the jth power battery monomer under the corresponding frequency of the xth sampling point is represented;
and determining the power battery monomer with the voltage inconsistency fault according to the voltage inconsistency abnormal coefficient matrix.
Optionally, constructing a voltage amplitude characteristic matrix according to the real vehicle operation data specifically includes:
processing the real vehicle running data by adopting a big data preprocessing technology to extract a full life cycle original voltage data set corresponding to all the power battery monomers; the big data preprocessing technology comprises data cleaning, data dimension reduction and data transformation;
constructing a single power battery voltage matrix according to the full life cycle original voltage data set; the single power battery voltage matrix is a matrix with t rows and n columns, and an element v in the single power battery voltage matrixi,jThe voltage value of the jth power battery cell at the ith moment is shown, and t is the total number of the moments;
constructing a voltage amplitude characteristic matrix according to the single power battery voltage matrix, the fast Fourier transform algorithm and the modular arithmetic algorithm; the voltage amplitude characteristic matrix is a matrix with N/2 rows and N columns, and an element m in the voltage amplitude characteristic matrixx,jRepresenting the amplitude characteristic value of voltage data of the jth power battery monomer under the corresponding frequency of the xth sampling point, wherein N represents the total number of the sampling points;
and constructing a voltage amplitude characteristic matrix according to the voltage amplitude characteristic matrix.
Optionally, the determining a voltage inconsistency abnormal coefficient matrix according to the voltage amplitude feature matrix specifically includes:
carrying out dimension transformation on elements in the voltage amplitude characteristic matrix to obtain a voltage data frequency domain amplitude characteristic matrix; the voltage data frequency domain amplitude characteristic matrix is a matrix with N/2 rows and N columns, and elements a 'in the voltage data frequency domain amplitude characteristic matrix'x,jRepresenting a frequency domain amplitude characteristic value of a jth power battery monomer under the corresponding frequency of the xth sampling point;
calculating the mean value and the standard deviation of the frequency domain amplitude characteristics corresponding to all the power battery monomers under the frequency corresponding to the same sampling point according to the voltage data frequency domain amplitude characteristic matrix;
and determining a voltage inconsistency abnormal coefficient matrix based on a Z fraction theory according to the voltage data frequency domain amplitude characteristic matrix, the mean value and the standard deviation.
Optionally, the determining, according to the voltage inconsistency abnormal coefficient matrix, a power battery cell having an inconsistency fault specifically includes:
and if at least one voltage inconsistency abnormal coefficient in all the voltage inconsistency abnormal coefficients corresponding to the power battery monomers exceeds a fault threshold value, marking the power battery monomers as the power battery monomers with voltage inconsistency faults, and traversing all the power battery monomers in the vehicle power battery system to obtain all the power battery monomers with the voltage inconsistency faults.
Optionally, the method further includes:
when the number of the power battery monomers with the voltage inconsistency fault is 0, the voltage consistency of the vehicle power battery system is represented to be good;
when the number of the power battery single cells with the voltage inconsistency faults is 1, outputting the number corresponding to the power battery single cells with the voltage inconsistency faults;
when the number of the power battery cells with the voltage inconsistency faults is larger than 1, outputting the number and the abnormal rate corresponding to each power battery cell with the voltage inconsistency faults;
wherein the abnormal rate is the ratio of the first frequency to the total frequency; the first frequency is the frequency that the voltage inconsistency abnormal coefficient corresponding to the power battery single body with the voltage inconsistency fault exceeds the fault threshold value; the total frequency is the sum of the frequency that the voltage inconsistency abnormal coefficient corresponding to all the power battery cells with the voltage inconsistency faults exceeds the fault threshold value.
An inconsistency fault diagnostic system for a power battery system, comprising:
the real vehicle operation data acquisition module is used for acquiring real vehicle operation data of the vehicle power battery system; the vehicle power battery system comprises n power battery monomers;
the voltage amplitude characteristic matrix construction module is used for constructing a voltage amplitude characteristic matrix according to the real vehicle operation data; the voltage amplitude characteristic matrix is a matrix with N/2 rows and N columns, and an element a in the voltage amplitude characteristic matrixx,jRepresenting the amplitude characteristic value of voltage data of the jth power battery monomer under the corresponding frequency of the xth sampling point, wherein N represents the total number of the sampling points;
the voltage inconsistency abnormal coefficient matrix determining module is used for determining a voltage inconsistency abnormal coefficient matrix according to the voltage amplitude characteristic matrix; the voltage inconsistency abnormal coefficient matrix is a matrix with N/2 rows and N columns, and an element k of the voltage inconsistency abnormal coefficient matrixx,jThe voltage inconsistency abnormal coefficient of the jth power battery monomer under the corresponding frequency of the xth sampling point is represented;
and the fault power battery single body determining module is used for determining the power battery single body with the voltage inconsistency fault according to the voltage inconsistency abnormal coefficient matrix.
Optionally, the voltage amplitude feature matrix constructing module specifically includes:
the preprocessing unit is used for processing the real vehicle running data by adopting a big data preprocessing technology so as to extract a full life cycle original voltage data set corresponding to all the power battery monomers; the big data preprocessing technology comprises data cleaning, data dimension reduction and data transformation;
the power battery monomer voltage matrix construction unit is used for constructing a power battery monomer voltage matrix according to the full life cycle original voltage data set; the single power battery voltage matrix is a matrix with t rows and n columns, and an element v in the single power battery voltage matrixi,jThe voltage value of the jth power battery cell at the ith moment is shown, and t is the total number of the moments;
the voltage amplitude characteristic matrix construction unit is used for constructing a voltage amplitude characteristic matrix according to the single power battery voltage matrix, the fast Fourier transform algorithm and the modular arithmetic algorithm; the voltage amplitudeThe degree characteristic matrix is a matrix with N/2 rows and N columns, and an element m in the voltage amplitude characteristic matrixx,jRepresenting the amplitude characteristic value of voltage data of the jth power battery monomer under the corresponding frequency of the xth sampling point, wherein N represents the total number of the sampling points;
and the voltage amplitude characteristic matrix determining unit is used for constructing a voltage amplitude characteristic matrix according to the voltage amplitude characteristic matrix.
Optionally, the module for determining the voltage inconsistency abnormal coefficient matrix specifically includes:
the dimension transformation unit is used for carrying out dimension transformation on the elements in the voltage amplitude characteristic matrix to obtain a voltage data frequency domain amplitude characteristic matrix; the voltage data frequency domain amplitude characteristic matrix is a matrix with N/2 rows and N columns, and elements a 'in the voltage data frequency domain amplitude characteristic matrix'x,jRepresenting a frequency domain amplitude characteristic value of a jth power battery monomer under the corresponding frequency of the xth sampling point;
the mean value and standard deviation calculation unit is used for calculating the mean value and standard deviation of the frequency domain amplitude characteristics corresponding to all the power battery monomers under the frequency corresponding to the same sampling point according to the voltage data frequency domain amplitude characteristic matrix;
and the voltage inconsistency abnormal coefficient matrix determining unit is used for determining a voltage inconsistency abnormal coefficient matrix based on a Z fraction theory according to the voltage data frequency domain amplitude characteristic matrix, the mean value and the standard deviation.
Optionally, the module for determining a single power battery with a fault specifically includes:
and the fault power battery single body determining unit is used for marking the power battery single body as the power battery single body with the voltage inconsistency fault when at least one voltage inconsistency abnormal coefficient exceeds a fault threshold value in all voltage inconsistency abnormal coefficients corresponding to the power battery single bodies, and traversing all power battery single bodies in the vehicle power battery system to obtain all power battery single bodies with the voltage inconsistency fault.
Optionally, the method further includes:
the voltage consistency good determination module is used for representing that the voltage consistency of the vehicle power battery system is good when the number of the power battery monomers with the voltage inconsistency faults is 0;
the fault single body number determining module is used for determining the number corresponding to the power battery single body with the voltage inconsistency fault when the number of the power battery single bodies with the voltage inconsistency fault is 1;
the fault single body number and abnormal rate determining module is used for determining the number and the abnormal rate corresponding to each power battery single body with the voltage inconsistency fault when the number of the power battery single bodies with the voltage inconsistency fault is larger than 1;
wherein the abnormal rate is the ratio of the first frequency to the total frequency; the first frequency is the frequency that the voltage inconsistency abnormal coefficient corresponding to the power battery single body with the voltage inconsistency fault exceeds the fault threshold value; the total frequency is the sum of the frequency that the voltage inconsistency abnormal coefficient corresponding to all the power battery cells with the voltage inconsistency faults exceeds the fault threshold value.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides an inconsistency fault diagnosis method and system for a power battery system. Obviously, the frequency domain index of the power battery monomer acquisition parameter is considered, so that the voltage inconsistency fault of the power battery monomer can be accurately diagnosed.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a flow chart of a method of diagnosing an inconsistency fault in a power battery system of the present invention;
FIG. 2 is a block diagram of an inconsistency diagnostic system for a power battery system of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a method and a system for diagnosing an inconsistency fault of a power battery system, so as to improve timeliness and accuracy of fault diagnosis.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
The power battery monomer: refers to the smallest module unit constituting the power battery, and the battery pack can be formed by series-parallel connection.
Monomer voltage: refers to the voltage of the power battery cell.
Single frame: refers to a certain acquisition instant.
Example one
As shown in fig. 1, the present embodiment provides a method for diagnosing an inconsistency fault of a power battery system, including:
step 101: acquiring real vehicle operation data of a vehicle power battery system; the vehicle power battery system comprises n power battery cells.
Step 102: constructing a voltage amplitude characteristic matrix according to the real vehicle operation data; the voltage amplitude characteristic matrix is a matrix with N/2 rows and N columns, and an element a in the voltage amplitude characteristic matrixx,jRepresents the j movement at the frequency corresponding to the x sampling pointThe amplitude characteristic value of the voltage data of the force battery cell, and N represents the total number of sampling points.
Step 103: determining a voltage inconsistency abnormal coefficient matrix according to the voltage amplitude characteristic matrix; the voltage inconsistency abnormal coefficient matrix is a matrix with N/2 rows and N columns, and an element k of the voltage inconsistency abnormal coefficient matrixx,jAnd the abnormal coefficient of voltage inconsistency of the jth power battery cell under the corresponding frequency of the xth sampling point is represented.
Step 104: and determining the power battery monomer with the voltage inconsistency fault according to the voltage inconsistency abnormal coefficient matrix.
As a preferred embodiment, the step of constructing a voltage amplitude characteristic matrix according to the real vehicle operation data specifically includes:
processing the real vehicle running data by adopting a big data preprocessing technology to extract a full life cycle original voltage data set corresponding to all the power battery monomers; the big data preprocessing technology comprises data cleaning, data dimension reduction, data transformation and the like.
Constructing a single power battery voltage matrix according to the full life cycle original voltage data set; the single power battery voltage matrix is a matrix with t rows and n columns, and an element v in the single power battery voltage matrixi,jThe voltage value of the jth power battery cell at the ith moment is shown, and t is the total number of the moments; the power battery monomer voltage matrix is used
i∈[1,2,…,t],j∈[1,2,…,n]And (4) showing.
Constructing a voltage amplitude characteristic matrix according to the single power battery voltage matrix, the fast Fourier transform algorithm and the modular arithmetic algorithm; the voltage amplitude characteristic matrix is a matrix with N/2 rows and N columns, and an element m in the voltage amplitude characteristic matrixx,jRepresenting the amplitude characteristic value of voltage data of the jth power battery monomer under the corresponding frequency of the xth sampling point, wherein N represents the total number of the sampling points; for said voltage amplitude characteristic matrix
x∈[1,2,…,N/2],j∈[1,2,…,n]And (4) showing.
And constructing a voltage amplitude characteristic matrix according to the voltage amplitude characteristic matrix. For the voltage amplitude characteristic matrix
x∈[1,2,…,N/2],j∈[1,2,…,n]And (4) showing. Wherein, the element ax,jSee the formula of example three for the calculation formula.
As a preferred embodiment, the step of determining the voltage inconsistency abnormal coefficient matrix according to the voltage amplitude feature matrix specifically includes:
carrying out dimension transformation on elements in the voltage amplitude characteristic matrix to obtain a voltage data frequency domain amplitude characteristic matrix; the voltage data frequency domain amplitude characteristic matrix is a matrix with N/2 rows and N columns, and elements a 'in the voltage data frequency domain amplitude characteristic matrix'x,jRepresenting a frequency domain amplitude characteristic value of a jth power battery monomer under the corresponding frequency of the xth sampling point; see example three for its transformation.
Calculating the mean value and the standard deviation of the frequency domain amplitude characteristics corresponding to all the power battery monomers under the frequency corresponding to the same sampling point according to the voltage data frequency domain amplitude characteristic matrix; see example three for the calculation of the mean and standard deviation.
And determining a voltage inconsistency abnormal coefficient matrix based on a Z fraction theory according to the voltage data frequency domain amplitude characteristic matrix, the mean value and the standard deviation. The calculation process of the abnormal coefficient of the voltage inconsistency is shown in the third embodiment.
As a preferred embodiment, the step of determining the power battery cell with the inconsistency fault according to the voltage inconsistency abnormal coefficient matrix specifically includes:
and if at least one voltage inconsistency abnormal coefficient in all the voltage inconsistency abnormal coefficients corresponding to the power battery monomers exceeds a fault threshold value, marking the power battery monomers as the power battery monomers with voltage inconsistency faults, and traversing all the power battery monomers in the vehicle power battery system to obtain all the power battery monomers with the voltage inconsistency faults.
One example is as follows:
one row of data of the voltage inconsistency abnormal coefficient matrix corresponds to one power battery monomer, and whether the power battery monomer is a fault power battery monomer is sequentially judged by taking the one row of data as a unit; the judgment process is as follows:
sequentially judging whether the voltage inconsistency abnormal coefficient exceeds a fault threshold value or not according to a matrix sequence (from top to bottom or from bottom to top) by a column of data; when the voltage inconsistency abnormal coefficient exceeds the fault threshold value, stopping judging the data, and marking the power battery monomer corresponding to the data as the power battery monomer with the voltage inconsistency fault; and after the line of data is judged, when each data in the line of data is found to be smaller than or equal to the fault threshold value, marking the power battery single body corresponding to the line of data with a label with good consistency of the voltage. And repeating the process, and stopping when all the columns in the voltage inconsistency abnormal coefficient matrix are judged.
As a preferred embodiment, the method of the present invention further comprises:
when the number of the power battery cells with the voltage inconsistency faults is 0, the voltage consistency of the vehicle power battery system is represented to be good.
When the number of the power battery cells with the voltage inconsistency faults is 1, outputting the numbers corresponding to the power battery cells with the voltage inconsistency faults.
And when the number of the power battery cells with the voltage inconsistency faults is larger than 1, outputting the number and the abnormal rate corresponding to each power battery cell with the voltage inconsistency faults.
Wherein the abnormal rate is the ratio of the first frequency to the total frequency; the first frequency is the frequency that the voltage inconsistency abnormal coefficient corresponding to the power battery single body with the voltage inconsistency fault exceeds the fault threshold value; the total frequency is the sum of the frequency that the voltage inconsistency abnormal coefficient corresponding to all the power battery single cells with the voltage inconsistency faults exceeds the fault threshold value; see example three for its calculation.
Example two
As shown in fig. 2, the inconsistency fault diagnosis system of the power battery system according to the present embodiment includes:
the real vehicle operation data acquisition module 201 is used for acquiring real vehicle operation data of the vehicle power battery system; the vehicle power battery system comprises n power battery cells.
The voltage amplitude characteristic matrix construction module 202 is used for constructing a voltage amplitude characteristic matrix according to the real vehicle operation data; the voltage amplitude characteristic matrix is a matrix with N/2 rows and N columns, and an element a in the voltage amplitude characteristic matrixx,jAnd the amplitude characteristic value of the voltage data of the jth power battery cell under the corresponding frequency of the xth sampling point is represented, and N represents the total number of the sampling points.
A voltage inconsistency abnormal coefficient matrix determination module 203, configured to determine a voltage inconsistency abnormal coefficient matrix according to the voltage amplitude feature matrix; the voltage inconsistency abnormal coefficient matrix is a matrix with N/2 rows and N columns, and an element k of the voltage inconsistency abnormal coefficient matrixx,jAnd the abnormal coefficient of voltage inconsistency of the jth power battery cell under the corresponding frequency of the xth sampling point is represented.
And the failure power battery cell determining module 204 is configured to determine a power battery cell with a voltage inconsistency failure according to the voltage inconsistency abnormal coefficient matrix.
The voltage amplitude feature matrix constructing module 202 specifically includes:
the preprocessing unit is used for processing the real vehicle running data by adopting a big data preprocessing technology so as to extract a full life cycle original voltage data set corresponding to all the power battery monomers; the big data preprocessing technology comprises data cleaning, data dimension reduction and data transformation.
The power battery monomer voltage matrix construction unit is used for constructing a power battery monomer voltage matrix according to the full life cycle original voltage data set; the single power battery voltage matrix is a matrix with t rows and n columns, and an element v in the single power battery voltage matrixi,jThe voltage value of the jth power battery cell at the ith moment is shown, and t represents the total number of moments.
The voltage amplitude characteristic matrix construction unit is used for constructing a voltage amplitude characteristic matrix according to the single power battery voltage matrix, the fast Fourier transform algorithm and the modular arithmetic algorithm; the voltage amplitude characteristic matrix is a matrix with N/2 rows and N columns, and an element m in the voltage amplitude characteristic matrixx,jAnd the amplitude characteristic value of the voltage data of the jth power battery monomer under the corresponding frequency of the xth sampling point is represented, and N represents the total number of the sampling points.
And the voltage amplitude characteristic matrix determining unit is used for constructing a voltage amplitude characteristic matrix according to the voltage amplitude characteristic matrix.
The voltage inconsistency abnormal coefficient matrix determining module 203 specifically includes:
the dimension transformation unit is used for carrying out dimension transformation on the elements in the voltage amplitude characteristic matrix to obtain a voltage data frequency domain amplitude characteristic matrix; the voltage data frequency domain amplitude characteristic matrix is a matrix with N/2 rows and N columns, and elements a 'in the voltage data frequency domain amplitude characteristic matrix'x,jAnd representing the frequency domain amplitude characteristic value of the jth power battery monomer under the corresponding frequency of the xth sampling point.
And the mean value and standard deviation calculation unit is used for calculating the mean value and standard deviation of the frequency domain amplitude characteristics corresponding to all the power battery monomers under the frequency corresponding to the same sampling point according to the voltage data frequency domain amplitude characteristic matrix.
And the voltage inconsistency abnormal coefficient matrix determining unit is used for determining a voltage inconsistency abnormal coefficient matrix based on a Z fraction theory according to the voltage data frequency domain amplitude characteristic matrix, the mean value and the standard deviation.
The failure power battery cell determining module 204 specifically includes:
and the fault power battery single body determining unit is used for marking the power battery single body as the power battery single body with the voltage inconsistency fault when at least one voltage inconsistency abnormal coefficient exceeds a fault threshold value in all voltage inconsistency abnormal coefficients corresponding to the power battery single bodies, and traversing all power battery single bodies in the vehicle power battery system to obtain all power battery single bodies with the voltage inconsistency fault.
The system of the present invention further comprises:
and the good voltage consistency determining module is used for representing that the voltage consistency of the vehicle power battery system is good when the number of the power battery cells with the voltage inconsistency faults is 0.
And the fault single cell number determining module is used for determining the number corresponding to the power battery single cell with the voltage inconsistency fault when the number of the power battery single cells with the voltage inconsistency fault is 1.
And the fault single cell number and abnormal rate determining module is used for determining the number and the abnormal rate corresponding to each power battery cell with the voltage inconsistency fault when the number of the power battery cells with the voltage inconsistency fault is larger than 1.
Wherein the abnormal rate is the ratio of the first frequency to the total frequency; the first frequency is the frequency that the voltage inconsistency abnormal coefficient corresponding to the power battery single body with the voltage inconsistency fault exceeds the fault threshold value; the total frequency is the sum of the frequency that the voltage inconsistency abnormal coefficient corresponding to all the power battery cells with the voltage inconsistency faults exceeds the fault threshold value.
EXAMPLE III
The embodiment provides a power battery system inconsistency fault diagnosis method based on frequency domain indexes, which comprises the following steps.
Step 1: vehicle operation data is acquired.
And acquiring real vehicle operation data of the vehicle power battery system based on the national supervision platform of the new energy vehicle. The vehicle power battery system comprises n power battery single cells (hereinafter referred to as single cells).
Step 2: and (4) preprocessing data.
And processing the real vehicle operation data based on big data preprocessing technologies such as data cleaning, data dimension reduction, data transformation and the like, and extracting the full life cycle original voltage data sets of all the monomers.
And step 3: and constructing a monomer voltage matrix.
And extracting the voltage values of all the single cells in a certain time segment based on the full life cycle original voltage data set. The total frame number of the selected time segment is t, the total monomer number is n, and thus a monomer voltage matrix V is formedt×n。
Wherein i represents the ith frame; j represents the jth monomer; v. ofi,jThe voltage value of the jth cell at the ith time (frame) is shown in units of V.
And 4, step 4: and extracting voltage amplitude characteristics.
Setting the number of sampling points in fast Fourier transform to be N, traversing the voltage data of N monomers, respectively carrying out fast Fourier transform, carrying out modular operation on a plurality of results obtained by the transform to obtain amplitude values corresponding to different frequencies in a frequency domain, and further forming a voltage amplitude characteristic matrix MN/2×n. Because the fast Fourier transform has symmetry, the sampling point region of the emphasis analysis is determined as [1, N/2 ]]。
Wherein x represents the xth sample point; j represents the jth monomer; m isx,jAnd representing the amplitude characteristic value of the voltage data of the jth monomer at the corresponding frequency of the xth sampling point.
And 5: and calculating the voltage amplitude characteristic.
The amplitude can be divided into DC component amplitude and chordThe amplitude of the wave component is based on the voltage amplitude characteristic matrix, and then a voltage amplitude characteristic matrix A is obtainedN/2×n。
Wherein, ax,jAnd the amplitude characteristic value of the voltage data of the jth monomer under the corresponding frequency of the xth sampling point is shown. The specific calculation formula is as follows:
step 6: and transforming amplitude characteristic dimension.
In order to describe a wide amplitude characteristic range by using smaller coordinates, the unit of the amplitude characteristic value is converted into decibels which are common in engineering, and therefore a final voltage data frequency domain amplitude characteristic matrix A'N/2×n。
A′N/2×n＝(a′x,j)N/2×nx∈[1,2,…,N/2],j∈[1,2,…,n]；
Wherein, a'x,jAnd the unit of the amplitude characteristic value is dB, wherein the amplitude characteristic value is the amplitude characteristic value of the frequency domain after the unit transformation is carried out on the jth monomer under the corresponding frequency of the xth sampling point. The specific calculation formula is as follows:
a′x,j＝20log10(ax,j)。
and 7: and calculating an abnormal coefficient.
Firstly, calculating the mean value E (a ') of the frequency domain amplitude characteristics of all the monomers under the corresponding frequency of the same sampling point'x) And standard deviation σ (a'x)。
Secondly, in order to realize quantitative evaluation of frequency domain amplitude characteristic discreteness and voltage inconsistency faults, a voltage inconsistency abnormal system is calculated and obtained on the basis of a Z fraction theoryNumber matrix KN/2×n。
Wherein x represents the xth sample point; j represents the jth monomer; k is a radical ofx,jAnd the abnormal coefficient of voltage inconsistency of the jth monomer under the corresponding frequency of the xth sampling point is shown. Wherein k isx,jThe specific calculation formula of (A) is as follows:
and 8: and setting a fault threshold value.
Based on a national supervision platform of the new energy automobile, voltage data of the same automobile type are retrieved, so that a sufficient sample size is obtained, the steps 2 to 7 are repeated, the obtained voltage inconsistency abnormal coefficient value is subjected to statistical analysis, and a corresponding fault threshold value is set (generally, when | k | > 4, a voltage serious inconsistency fault exists between single power batteries).
And step 9: and detecting and positioning fault single bodies.
And (4) comparing the voltage inconsistency abnormal coefficient value k obtained by calculation in the step (7) with a fault threshold value, and if one voltage inconsistency abnormal coefficient value corresponding to a certain single body exceeds the fault threshold value, the single body is a fault single body. And repeating the steps, traversing all the monomers, and recording the number of the fault monomers and the serial number of the fault monomers.
Step 10: and sequencing the fault degrees of the single batteries.
According to the number of the fault single body in the step 9, if the number of the fault single bodies is equal to 0, the consistency of the battery single bodies of the vehicle power battery system is good; if the number of the fault monomers is equal to 1, directly outputting the serial numbers of the fault monomers; and if the number of the fault single bodies is more than 1, recording the frequency of the abnormal coefficient of the fault single bodies exceeding the threshold value, judging the fault degrees of the fault single bodies based on the abnormal rate, and ranking the serial numbers and the fault degrees of the fault single bodies for output. The specific calculation formula of the abnormal rate is as follows:
wherein R iskRepresenting the abnormal rate of the kth fault single body; f. ofkRepresenting the frequency of the k-th failure monomer abnormal coefficient exceeding the failure threshold value; ft represents the total frequency of all fault single body abnormal coefficients exceeding the threshold value in the diagnosis result.
The invention utilizes the monomer voltage parameters transmitted in real time, and has simple judgment method and higher real-time property. In addition, the method can quickly and accurately diagnose the voltage inconsistency fault of the power battery monomer based on the frequency domain amplitude index and the abnormal coefficient calculation of the voltage data, and accurately position the fault monomer, thereby effectively preventing the occurrence of the thermal runaway event of the new energy vehicle.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (8)
1. A method of diagnosing an inconsistency fault in a power battery system, comprising:
acquiring real vehicle operation data of a vehicle power battery system; the vehicle power battery system comprises n power battery monomers;
according to the said real vehicleOperating data, and constructing a voltage amplitude characteristic matrix; the voltage amplitude characteristic matrix is a matrix with N/2 rows and N columns, and an element a in the voltage amplitude characteristic matrixx,jRepresenting the amplitude characteristic value of voltage data of the jth power battery monomer under the corresponding frequency of the xth sampling point, wherein N represents the total number of the sampling points;
determining a voltage inconsistency abnormal coefficient matrix according to the voltage amplitude characteristic matrix; the voltage inconsistency abnormal coefficient matrix is a matrix with N/2 rows and N columns, and an element k of the voltage inconsistency abnormal coefficient matrixx,jThe voltage inconsistency abnormal coefficient of the jth power battery monomer under the corresponding frequency of the xth sampling point is represented;
determining a power battery monomer with voltage inconsistency fault according to the voltage inconsistency abnormal coefficient matrix;
the determining a voltage inconsistency abnormal coefficient matrix according to the voltage amplitude characteristic matrix specifically includes:
carrying out dimension transformation on elements in the voltage amplitude characteristic matrix to obtain a voltage data frequency domain amplitude characteristic matrix; the voltage data frequency domain amplitude characteristic matrix is a matrix with N/2 rows and N columns, and elements a 'in the voltage data frequency domain amplitude characteristic matrix'x,jRepresenting a frequency domain amplitude characteristic value of a jth power battery monomer under the corresponding frequency of the xth sampling point; calculating the mean value and the standard deviation of the frequency domain amplitude characteristics corresponding to all the power battery monomers under the frequency corresponding to the same sampling point according to the voltage data frequency domain amplitude characteristic matrix; and determining a voltage inconsistency abnormal coefficient matrix based on a Z fraction theory according to the voltage data frequency domain amplitude characteristic matrix, the mean value and the standard deviation.
2. The inconsistency fault diagnosis method for a power battery system according to claim 1, wherein the constructing a voltage amplitude feature matrix according to the real vehicle operation data specifically comprises:
processing the real vehicle running data by adopting a big data preprocessing technology to extract a full life cycle original voltage data set corresponding to all the power battery monomers; the big data preprocessing technology comprises data cleaning, data dimension reduction and data transformation;
constructing a single power battery voltage matrix according to the full life cycle original voltage data set; the single power battery voltage matrix is a matrix with t rows and n columns, and an element v in the single power battery voltage matrixi,jThe voltage value of the jth power battery cell at the ith moment is shown, and t is the total number of the moments;
constructing a voltage amplitude characteristic matrix according to the single power battery voltage matrix, the fast Fourier transform algorithm and the modular arithmetic algorithm; the voltage amplitude characteristic matrix is a matrix with N/2 rows and N columns, and an element m in the voltage amplitude characteristic matrixx,jRepresenting the amplitude characteristic value of voltage data of the jth power battery monomer under the corresponding frequency of the xth sampling point, wherein N represents the total number of the sampling points;
and constructing a voltage amplitude characteristic matrix according to the voltage amplitude characteristic matrix.
3. The inconsistency fault diagnosis method for the power battery system according to claim 1, wherein the determining of the power battery cell with the inconsistency fault according to the voltage inconsistency abnormal coefficient matrix specifically comprises:
and if at least one voltage inconsistency abnormal coefficient in all the voltage inconsistency abnormal coefficients corresponding to the power battery monomers exceeds a fault threshold value, marking the power battery monomers as the power battery monomers with voltage inconsistency faults, and traversing all the power battery monomers in the vehicle power battery system to obtain all the power battery monomers with the voltage inconsistency faults.
4. The method of diagnosing an inconsistency fault in a power battery system of claim 1, further comprising:
when the number of the power battery monomers with the voltage inconsistency fault is 0, the voltage consistency of the vehicle power battery system is represented to be good;
when the number of the power battery single cells with the voltage inconsistency faults is 1, outputting the number corresponding to the power battery single cells with the voltage inconsistency faults;
when the number of the power battery cells with the voltage inconsistency faults is larger than 1, outputting the number and the abnormal rate corresponding to each power battery cell with the voltage inconsistency faults;
wherein the abnormal rate is the ratio of the first frequency to the total frequency; the first frequency is the frequency that the voltage inconsistency abnormal coefficient corresponding to the power battery single body with the voltage inconsistency fault exceeds the fault threshold value; the total frequency is the sum of the frequency that the voltage inconsistency abnormal coefficient corresponding to all the power battery cells with the voltage inconsistency faults exceeds the fault threshold value.
5. An inconsistency fault diagnostic system for a power battery system, comprising:
the real vehicle operation data acquisition module is used for acquiring real vehicle operation data of the vehicle power battery system; the vehicle power battery system comprises n power battery monomers;
the voltage amplitude characteristic matrix construction module is used for constructing a voltage amplitude characteristic matrix according to the real vehicle operation data; the voltage amplitude characteristic matrix is a matrix with N/2 rows and N columns, and an element a in the voltage amplitude characteristic matrixx,jRepresenting the amplitude characteristic value of voltage data of the jth power battery monomer under the corresponding frequency of the xth sampling point, wherein N represents the total number of the sampling points;
the voltage inconsistency abnormal coefficient matrix determining module is used for determining a voltage inconsistency abnormal coefficient matrix according to the voltage amplitude characteristic matrix; the voltage inconsistency abnormal coefficient matrix is a matrix with N/2 rows and N columns, and an element k of the voltage inconsistency abnormal coefficient matrixx,jThe voltage inconsistency abnormal coefficient of the jth power battery monomer under the corresponding frequency of the xth sampling point is represented;
the fault power battery single body determining module is used for determining a power battery single body with voltage inconsistency fault according to the voltage inconsistency abnormal coefficient matrix;
the voltage inconsistency abnormal coefficient matrix determining module specifically includes:
the dimension transformation unit is used for carrying out dimension transformation on the elements in the voltage amplitude characteristic matrix to obtain a voltage data frequency domain amplitude characteristic matrix; the voltage data frequency domain amplitude characteristic matrix is a matrix with N/2 rows and N columns, and elements a 'in the voltage data frequency domain amplitude characteristic matrix'x,jRepresenting a frequency domain amplitude characteristic value of a jth power battery monomer under the corresponding frequency of the xth sampling point; the mean value and standard deviation calculation unit is used for calculating the mean value and standard deviation of the frequency domain amplitude characteristics corresponding to all the power battery monomers under the frequency corresponding to the same sampling point according to the voltage data frequency domain amplitude characteristic matrix; and the voltage inconsistency abnormal coefficient matrix determining unit is used for determining a voltage inconsistency abnormal coefficient matrix based on a Z fraction theory according to the voltage data frequency domain amplitude characteristic matrix, the mean value and the standard deviation.
6. The system for diagnosing the inconsistency fault in the power battery system according to claim 5, wherein the voltage amplitude feature matrix building module specifically comprises:
the preprocessing unit is used for processing the real vehicle running data by adopting a big data preprocessing technology so as to extract a full life cycle original voltage data set corresponding to all the power battery monomers; the big data preprocessing technology comprises data cleaning, data dimension reduction and data transformation;
the power battery monomer voltage matrix construction unit is used for constructing a power battery monomer voltage matrix according to the full life cycle original voltage data set; the single power battery voltage matrix is a matrix with t rows and n columns, and an element v in the single power battery voltage matrixi,jThe voltage value of the jth power battery cell at the ith moment is shown, and t is the total number of the moments;
a voltage amplitude characteristic matrix constructing unit for fast Fourier transform according to the single voltage matrix of the power batteryConstructing a voltage amplitude characteristic matrix by using a inner leaf transformation algorithm and a modulus operation algorithm; the voltage amplitude characteristic matrix is a matrix with N/2 rows and N columns, and an element m in the voltage amplitude characteristic matrixx,jRepresenting the amplitude characteristic value of voltage data of the jth power battery monomer under the corresponding frequency of the xth sampling point, wherein N represents the total number of the sampling points;
and the voltage amplitude characteristic matrix determining unit is used for constructing a voltage amplitude characteristic matrix according to the voltage amplitude characteristic matrix.
7. The inconsistency fault diagnosis system for a power battery system according to claim 5, wherein the faulty power battery cell determination module specifically comprises:
and the fault power battery single body determining unit is used for marking the power battery single body as the power battery single body with the voltage inconsistency fault when at least one voltage inconsistency abnormal coefficient exceeds a fault threshold value in all voltage inconsistency abnormal coefficients corresponding to the power battery single bodies, and traversing all power battery single bodies in the vehicle power battery system to obtain all power battery single bodies with the voltage inconsistency fault.
8. The inconsistency fault diagnostic system of a power battery system according to claim 5, further comprising:
the voltage consistency good determination module is used for representing that the voltage consistency of the vehicle power battery system is good when the number of the power battery monomers with the voltage inconsistency faults is 0;
the fault single body number determining module is used for determining the number corresponding to the power battery single body with the voltage inconsistency fault when the number of the power battery single bodies with the voltage inconsistency fault is 1;
the fault single body number and abnormal rate determining module is used for determining the number and the abnormal rate corresponding to each power battery single body with the voltage inconsistency fault when the number of the power battery single bodies with the voltage inconsistency fault is larger than 1;
wherein the abnormal rate is the ratio of the first frequency to the total frequency; the first frequency is the frequency that the voltage inconsistency abnormal coefficient corresponding to the power battery single body with the voltage inconsistency fault exceeds the fault threshold value; the total frequency is the sum of the frequency that the voltage inconsistency abnormal coefficient corresponding to all the power battery cells with the voltage inconsistency faults exceeds the fault threshold value.
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