CN114200323A - Battery short-circuit fault early warning information generation method and device, equipment and medium - Google Patents
Battery short-circuit fault early warning information generation method and device, equipment and medium Download PDFInfo
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Abstract
The embodiment provides a method, a device, equipment and a medium for generating battery short-circuit fault early warning information, which are applied to a charging process and belong to the technical field of fault diagnosis. The method comprises the following steps: acquiring charging data of a primary charging process, wherein the charging data comprises sampling time, charging current and voltages of at least two single batteries; calculating the difference value of the open circuit voltage of each single battery at each data sampling point compared with the average battery according to the charging current and the voltage of the single battery; calculating an open-circuit voltage difference characteristic value matrix according to the open-circuit voltage difference value of each single battery at each data sampling point; and generating battery short-circuit fault early warning information in the charging process according to the open-circuit voltage difference characteristic value matrix. The method can analyze the data of the battery charging process uploaded to the cloud in real time so as to diagnose and early warn the short circuit fault of the battery.
Description
Technical Field
The invention relates to the technical field of fault diagnosis, in particular to a method, a device, equipment and a medium for generating early warning information of a battery short-circuit fault.
Background
In the related art, a method for diagnosing and early warning a battery short-circuit fault through the voltage difference of a single battery is easily influenced by current, temperature and sampling to cause false alarm. In order to reduce false alarm, the early warning threshold is generally set to be higher, and early warning is only carried out when the voltage difference of the single battery caused by short circuit is very large, so that fault diagnosis is delayed. In addition, the method for diagnosing and early warning the short-circuit fault of the battery through the chargeable electric quantity of the single battery has strict requirements on data, and the method can only analyze the battery after the charging process is finished and cannot diagnose and early warn in real time.
Disclosure of Invention
The main purpose of the embodiments of the present disclosure is to provide a method, an apparatus, and a medium for generating battery short-circuit fault warning information, which can analyze data of a battery charging process uploaded to a cloud in real time to diagnose and warn a battery short-circuit fault.
In order to achieve the above object, a first aspect of the embodiments of the present disclosure provides a method for generating battery short-circuit fault warning information, which is applied to a charging process, and includes:
acquiring charging data of a primary charging process, wherein the charging data comprises sampling time, charging current and voltages of at least two single batteries;
calculating the difference value of the open circuit voltage of each single battery at each data sampling point compared with the average battery according to the charging current and the voltage of the single battery;
calculating an open-circuit voltage difference characteristic value matrix according to the open-circuit voltage difference value of each single battery at each data sampling point;
and generating battery short-circuit fault early warning information in the charging process according to the open-circuit voltage difference characteristic value matrix.
In some embodiments, the calculating the difference value of the open circuit voltage of each single battery at each data sampling point compared with the average battery according to the charging current and the voltage of the single battery comprises:
calculating to obtain a first open-circuit voltage of the single battery at the data sampling point and a second open-circuit voltage of the average battery at the data sampling point according to the charging current, the voltage and a preset internal resistance;
and calculating the difference value of the open circuit voltage of the single battery at the data sampling point according to the first open circuit voltage and the second open circuit voltage.
In some embodiments, the calculating a first open-circuit voltage of the single battery at the data sampling point and a second open-circuit voltage of the average battery at the data sampling point according to the charging current, the voltage, and a preset internal resistance includes:
identifying a charging current mutation point according to the mutation value of the charging current;
calculating the preset internal resistance according to the charging current at the charging current sudden change point and the voltage at the charging current sudden change point;
and calculating to obtain a first open-circuit voltage of the single battery at the data sampling point and a second open-circuit voltage of the average battery at the data sampling point according to the charging current at the data sampling point, the voltage at the data sampling point and the preset internal resistance.
In some embodiments, the calculating an open circuit voltage difference eigenvalue matrix according to the open circuit voltage difference value of each of the single cells at each of the data sampling points includes:
dividing a use voltage interval of the single battery into at least two subintervals, wherein the use voltage interval is an interval from a discharge cut-off voltage to a charge cut-off voltage;
classifying each data sampling point into a plurality of subintervals according to the open-circuit voltage value of the average battery at each data sampling point;
calculating to obtain an open-circuit voltage difference characteristic value of the single battery in the subinterval according to the open-circuit voltage difference value of the single battery in the data sampling point of the subinterval;
and calculating to obtain the open-circuit voltage difference characteristic value matrix according to the open-circuit voltage difference characteristic values of the single batteries in the subintervals.
In some embodiments, the generating, according to the open-circuit voltage difference eigenvalue matrix, battery short-circuit fault early warning information in a charging process includes:
acquiring an open-circuit voltage difference characteristic value reference matrix;
and generating the battery short-circuit fault early warning information according to the open-circuit voltage difference characteristic value matrix and the open-circuit voltage difference characteristic value reference matrix.
In some embodiments, the generating the battery short-circuit fault early warning information according to the open-circuit voltage difference eigenvalue matrix and the open-circuit voltage difference eigenvalue reference matrix includes:
obtaining a first test result according to the open-circuit voltage difference characteristic value matrix and the open-circuit voltage difference characteristic value reference matrix; the first check result comprises that none of the elements of the corresponding position are null values;
obtaining a second test result according to the open-circuit voltage difference characteristic value matrix and the open-circuit voltage difference characteristic value reference matrix; the second detection result comprises that the element difference value of the corresponding position is smaller than a preset threshold value;
and generating first fault early warning information according to the first detection result and the second detection result.
In some embodiments, the battery short-circuit fault early-warning information includes second fault early-warning information, and the generating of the battery short-circuit fault early-warning information in the charging process according to the open-circuit voltage difference eigenvalue matrix further includes:
calculating to obtain a long-term evolution matrix of the difference characteristic value of the open-circuit voltage according to the matrix of the difference characteristic value of the open-circuit voltage;
calculating the evolution speed of the single battery open-circuit voltage difference characteristic value according to the open-circuit voltage difference characteristic value long-term evolution matrix;
and generating the second fault early warning information according to the evolution speed.
A second aspect of the embodiments of the present disclosure provides a battery short-circuit fault warning information generating apparatus, which is applied to a charging process, and includes:
the first acquisition module is used for acquiring charging data of a charging process, wherein the charging data comprises sampling time, charging current and voltages of at least two single batteries;
the first calculation module is used for calculating the difference value of the open-circuit voltage of each single battery at each data sampling point compared with the average battery according to the charging current and the voltage of the single battery;
the second calculation module is used for calculating an open-circuit voltage difference characteristic value matrix according to the open-circuit voltage difference value of each single battery at each data sampling point;
and the fault early warning information generating module is used for generating battery short circuit fault early warning information in the charging process according to the open-circuit voltage difference characteristic value matrix.
A third aspect of the embodiments of the present disclosure provides a computer device, which includes a memory and a processor, where the memory stores a program, and the processor is configured to execute the method according to any one of the embodiments of the first aspect of the present disclosure when the program is executed by the processor.
A fourth aspect of the embodiments of the present disclosure provides a storage medium, which is a computer-readable storage medium, and the computer readable storage medium stores a computer program, when the computer program is executed by a computer, the computer is configured to execute the method according to any one of the embodiments of the first aspect of the present application.
The method and the device, the equipment and the medium for generating the battery short-circuit fault early warning information are applied to a charging process, charging data of one charging process are obtained, the charging data comprise sampling time, charging current and voltages of at least two single batteries, the charging data are sampled according to the sampling time to obtain at least two data sampling points, the open-circuit voltage difference value of each single battery compared with an average battery at each data sampling point is calculated according to the charging current and the voltages of the single batteries, an open-circuit voltage difference characteristic value matrix is calculated according to the open-circuit voltage difference value, the battery short-circuit fault early warning information in the charging process is generated through the open-circuit voltage difference characteristic value matrix, and battery short-circuit fault diagnosis and early warning can be carried out in real time.
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Fig. 1 is a first flowchart of a method for generating battery short-circuit fault warning information according to an embodiment of the present disclosure;
FIG. 2 is a flowchart of step S120 in FIG. 1;
FIG. 3 is a flowchart of step S210 in FIG. 2;
FIG. 4 is a flowchart of step S130 in FIG. 1;
FIG. 5 is a first flowchart of step S140 in FIG. 1;
FIG. 6 is a flowchart of step S520 in FIG. 5;
FIG. 7 is a second flowchart of step S140 in FIG. 1;
fig. 8 is a second flowchart of a method for generating battery short-circuit fault warning information according to an embodiment of the disclosure;
fig. 9 is a third flowchart of a method for generating battery short-circuit fault warning information according to an embodiment of the present disclosure;
fig. 10 is a block diagram of a battery short-circuit fault warning information generation apparatus according to an embodiment of the present disclosure;
fig. 11 is a hardware structure diagram of a computer device provided in an embodiment of the present disclosure.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
It should be noted that although functional blocks are partitioned in a schematic diagram of an apparatus and a logical order is shown in a flowchart, in some cases, the steps shown or described may be performed in a different order than the partitioning of blocks in the apparatus or the order in the flowchart. The terms first, second and the like in the description and in the claims, and the drawings described above, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein is for the purpose of describing embodiments of the invention only and is not intended to be limiting of the invention.
At present, a method for diagnosing and early warning a short-circuit fault based on battery charging data generally judges whether a fault occurs and early warns according to a voltage difference of a single battery, and if the voltage difference or the change rate of the voltage difference of the single battery exceeds a preset threshold, the single battery is early warned. In addition, the method carries out fault diagnosis and early warning through the chargeable electric quantity of the single batteries, namely, the electric quantity which can be continuously charged by each single battery after the battery system is fully charged is calculated through battery charging data to judge whether a fault occurs. And if the chargeable electric quantity of a certain single battery exceeds a preset threshold value or the change speed of the chargeable electric quantity of a plurality of charging processes exceeds the preset threshold value, early warning is carried out on the single battery. However, the method for performing fault early warning and judgment through the voltage difference of the single voltage is greatly influenced by the charging current, the temperature and the sampling time, false alarm is easily generated, in order to reduce the false alarm, the threshold value is generally set to be higher, only when the voltage difference is very large, the battery is considered to have short circuit fault and early warning is performed, and certain delay exists in fault recognition. The method for performing fault early warning and judgment on the chargeable electric quantity has the advantages that the chargeable electric quantity can be calculated only after the battery system is fully charged, the charging data requirement is strict, the charging data in each charging process cannot meet the calculation requirement in the actual process, the method can perform fault analysis only when the charging is finished, fault diagnosis and early warning cannot be performed in real time, and the timeliness of short-circuit fault diagnosis is not strong.
Based on this, the main object of the embodiments of the present disclosure is to provide a method, an apparatus, a device, and a medium for generating battery short-circuit fault warning information, which can perform battery short-circuit fault diagnosis by using an open-circuit voltage difference value of a single battery, and can perform short-circuit fault analysis and warning in real time.
The method, the apparatus, the device, and the medium for generating battery short-circuit fault warning information provided in the embodiments of the present disclosure are specifically described in the following embodiments, and first, a method for generating battery short-circuit fault warning information in the embodiments of the present disclosure is described.
Referring to fig. 1, a method for generating battery short-circuit fault warning information according to an embodiment of the first aspect of the present disclosure includes, but is not limited to, step S110 to step S140.
S110, acquiring charging data of a charging process, wherein the charging data comprises sampling time, charging current and voltages of at least two single batteries;
s120, calculating the difference value of the open circuit voltage of each single battery at each data sampling point compared with the average battery according to the charging current and the voltage of the single battery;
s130, calculating an open-circuit voltage difference characteristic value matrix according to the open-circuit voltage difference value of each single battery at each data sampling point;
and S140, generating battery short-circuit fault early warning information in the charging process according to the open-circuit voltage difference characteristic value matrix.
In step S110, the charging data may be charging data uploaded by the vehicle to a vehicle battery system of the cloud-end platform according to the GB32960 standard, where the battery system includes a plurality of unit batteries connected in series. The GB32960 standard is the technical specification of the electric automobile remote service and management system. The charging data of a charging process refers to a complete parking charging data from the beginning of charging to the end of charging. The charging data of the primary charging process comprises sampling time, charging current and voltages of at least two single batteries, wherein the charging current and the voltages of the single batteries are changed along with the charging time.
In step S120, the charging data is sampled according to the sampling time to obtain at least two data sampling points, and then the difference value of the open circuit voltage of the single battery at the data sampling points compared with the average battery is calculated according to the charging current and the voltage of the single battery. Wherein the average cell is a centralized representation of a plurality of cells; a Difference of Open Circuit Voltage (dvcv), i.e., a Difference between an Open Circuit Voltage value of the unit cell and an Open Circuit Voltage value of the average cell; an Open Circuit Voltage (OCV) value, which is a terminal Voltage of the battery in an Open state. By calculating the difference value of the open circuit voltage of each single battery at each data sampling point compared with the average battery, the open circuit voltage difference between the single batteries connected in series can be identified in real time.
In steps S130 and S140, the SOC difference value of the single battery is approximately represented by the open-circuit voltage difference value of the single battery, the influence of current and temperature is eliminated, the single battery with rapidly increased open-circuit voltage difference and slowly increased open-circuit voltage difference can be timely identified and early warning is performed, all charging data uploaded to the cloud can be analyzed in real time, the timeliness is high, the problem can be found as early as possible, the problem that the cloud cannot directly identify the SOC difference between the single batteries by using the charging data is avoided, the OCV-SOC curve of the battery is not required to be supported, and the calculation complexity and the resource demand are reduced. Soc (state of charge), which indicates a state of charge, represents a ratio of the remaining capacity of the battery to the capacity of the battery in a fully charged state, and has a value range of [0, 1 ]. When the SOC value is 0, the battery is completely discharged. When the SOC value is 1, the battery is fully charged.
In some embodiments, as shown in fig. 2, step S120 specifically includes the steps of:
s210, calculating to obtain a first open-circuit voltage of the single battery at a data sampling point and a second open-circuit voltage of the average battery at the data sampling point according to the charging current, the charging voltage and the preset internal resistance;
and S220, calculating to obtain the open circuit voltage difference value of the single battery at the data sampling point according to the first open circuit voltage and the second open circuit voltage.
In step S210, a Rint equivalent circuit model based on the lithium ion battery is established according to the charging current, the charging voltage, and the preset internal resistance, so as to calculate a first open circuit voltage of the single battery at the data sampling point and a second open circuit voltage of the average battery at the data sampling point.
In step S220, the difference between the first open-circuit voltage of the single cell at the data sampling point and the second open-circuit voltage of the average cell at the data sampling point is used as the open-circuit voltage difference value of the single cell at the data sampling point.
In some embodiments, as shown in fig. 3, step S210 specifically includes the steps of:
s310, identifying a charging current mutation point according to the mutation value of the charging current;
s320, calculating a preset internal resistance according to the charging current at the charging current mutation point and the voltage at the charging current mutation point;
s330, calculating to obtain a first open circuit voltage of the single battery at the data sampling point and a second open circuit voltage of the average battery at the data sampling point according to the charging current at the data sampling point, the voltage at the data sampling point and the preset internal resistance.
In step S310, a charging current abrupt change point of the present charging process is identified according to an abrupt change value of the charging current of the present charging process. The abrupt change value of the charging current is the difference value of the charging current at a data sampling point and the charging current at the previous data sampling point. And if the mutation value is greater than or equal to a preset reference value, the data sampling point is a charging current mutation point. It should be noted that, the reference value can be set by a person skilled in the art according to actual requirements, for example, the reference value is 10. If the data sampling point is the kth data sampling point, the charging current is Ik. The last data sampling point is the kth-1 data sampling point, and the charging current is Ik-1. If Ik-Ik-1And | > 10, and k is greater than or equal to 2, then the kth data sampling point is a current mutation point.
In step S320, the charging current jump point is the kth data sampling point, and the charging current at the charging current jump point is IkThe voltage of the ith single battery at the charging current sudden change point is Vk,iWherein i is more than or equal to 2. The charging current at the last data sampling point is Ik-1The voltage of the ith single battery at the last data sampling point is Vk-1,i. According to the charging current I at the sudden change point of the charging currentkVoltage V at abrupt change point of charging currentk,iCharging current I at last data sampling pointk-1Voltage V at last data sampling pointk-1,iAnd calculating to obtain the internal resistance R of the single battery at the current mutation pointk,i. The calculation method is shown in formula (1):
Rk,i＝|Vk,i-Vk-1,i|/|Ik-Ik-1| (1)
it should be noted that specific values of k and i are not further limited in the embodiments of the present disclosure.
Usually, a plurality of current abrupt change points exist in a charging process, and each current abrupt change point can calculate the internal resistance of a single battery. The internal resistance of a single battery, such as the ith single battery, at each current break point is taken as a set and is expressed as { R }k,iAnd i is a fixed value, taking the average value or median of the internal resistances of the single battery calculated at all the current mutation points as the internal resistance of the single battery in the current charging process, namely taking the average value or median of the internal resistances of a certain single battery at all the current mutation points as a preset internal resistance, and storing the preset internal resistance. And for each single battery, taking the average value or the median of the internal resistance of the single battery calculated by each current mutation point as the preset internal resistance of each single battery.
It should be noted that, if the current discontinuity point is not identified in the current charging process, the internal resistance of the single battery in the previous charging process is used as the internal resistance of the current charging process, that is, the internal resistance preset by the single battery in the previous charging process is used as the internal resistance preset by the single battery in the current charging process.
It should be noted that, if the effective preset internal resistance of the single battery is not calculated in the first charging process, the preset internal resistance of each single battery is set to an initial value set manually in advance, for example, 0.5m Ω.
In step S330, a Rint equivalent circuit model based on the lithium ion battery is established according to the charging current at the data sampling point, the voltage at the data sampling point, and the preset internal resistance, and the first open circuit voltage and the second open circuit voltage are calculated according to the equivalent circuit model. The Rint equivalent circuit model is equivalent to a series connection of an ideal voltage source Uoc and a resistor R, the current is represented as I, the external voltage is represented as V, and the Rint equivalent circuit model is represented as formula (2):
Uoc＝V+IR (2)
wherein the ideal voltage source is the open circuit voltage of the battery.
Let the preset internal resistance be denoted as RiAccording to the charging current I at the data sampling pointkVoltage V of single battery at data sampling pointk,iAnd a predetermined internal resistance RiAnd establishing a first Rint equivalent circuit model, and calculating the first open-circuit voltage of the single battery at the data sampling point according to the first Rint equivalent circuit model. The first open circuit voltage is calculated as shown in equation (3):
OCVk,i＝Vk,i+IkRi (3)
let the preset internal resistances of all the single batteries be expressed as { RiAccording to preset internal resistances { R of all the single batteries }iCalculating the average internal resistance R of the batteryaveThat is, all the single batteries are preset with internal resistance { RiThe average value or median of the mean value is used as the internal resistance R of the average batteryave. According to the voltage V of all the single batteries at a certain data sampling point, such as the kth data sampling pointk,iCalculating the average cell voltage V at the data sampling pointk,aveWherein k is a fixed value, i.e. the average value or the median of the voltages of all the single batteries at the data sampling point is taken as the voltage V of the average battery at the data sampling pointk,ave. According to the charging current I at the data sampling pointkAverage the voltage V of the cell at the data sampling pointk,aveAverage internal resistance R of the batteryaveEstablishing a second Rint equivalent circuit model according to the second Rint equivalent circuitThe path model calculates a second open circuit voltage of the average cell at the data sampling point. The second open circuit voltage is calculated as shown in equation (4):
OCVk,ave＝Vk,ave+IkRave (4)
in some embodiments, as shown in fig. 4, step S130 specifically includes the steps of:
s410, dividing a service voltage interval of the single battery into at least two subintervals, wherein the service voltage interval is an interval from a discharge cut-off voltage to a charge cut-off voltage;
s420, classifying each data sampling point into a plurality of subintervals according to the open-circuit voltage value of the average battery at each data sampling point;
s430, calculating to obtain the open circuit voltage difference characteristic value of the single battery in the subinterval according to the open circuit voltage difference value of the single battery in the data sampling point of the subinterval;
and S440, calculating to obtain an open-circuit voltage difference characteristic value matrix according to the open-circuit voltage difference characteristic values of the single batteries in the subintervals.
In step S410, the cell is used in a voltage range from a discharge cutoff voltage to a charge cutoff voltage specified by a battery manufacturer. The use voltage interval is divided into a plurality of subintervals at equal intervals.
In step S420, the data sampling points are classified into the subintervals according to the subintervals where the open-circuit voltage values of the average battery at the data sampling points are located, until all the data sampling points are classified into the correct subintervals. According to the open circuit voltage value of the average battery at each data sampling point, which voltage subinterval the data sampling point is positioned in, for example, the number of subintervals is n, the subintervals are numbered from 1 to n according to the sequence from the discharge cut-off voltage to the charging medium voltage, namely according to the sequence of the used voltage intervals, and if the open circuit voltage value OCV of the average battery at the kth data sampling point isk,aveAnd in the 4 th subinterval, classifying the k-th data sampling point into the 4 th subinterval.
In step S430, an average open circuit voltage difference value of a certain cell in the sub-interval is calculated according to the open circuit voltage difference value of the data sampling point of the certain cell in the same sub-interval, and the average open circuit voltage difference value is used as the open circuit voltage difference characteristic value of the cell in the sub-interval. And on all data sampling points belonging to each subinterval, counting the average value of the open-circuit voltage difference values corresponding to the single batteries, and calculating the open-circuit voltage difference characteristic value of each single battery in each subinterval.
In step S440, the open-circuit voltage difference eigenvalue of each cell in each sub-interval is stored in a matrix to generate an open-circuit voltage difference eigenvalue matrix, where each row of the matrix represents a voltage sub-interval, each column represents a cell, and then one element in the matrix represents the open-circuit voltage difference eigenvalue of a certain cell in a certain voltage sub-interval. And if no data sampling point falls on a certain voltage subinterval in the charging process, the row of the voltage subinterval corresponding to the matrix is null.
In some embodiments, as shown in fig. 5, step S140 specifically includes the steps of:
s510, acquiring an open-circuit voltage difference characteristic value reference matrix;
and S520, generating battery short-circuit fault early warning information according to the open-circuit voltage difference characteristic value matrix and the open-circuit voltage difference characteristic value reference matrix.
In step S510, the open-circuit voltage difference eigenvalue reference matrix of the current charging process is calculated according to the open-circuit voltage difference eigenvalue matrix of the previous charging process, that is, all elements that are not null values in the open-circuit voltage difference eigenvalue matrix of the previous charging process are used to replace elements of the original open-circuit voltage difference eigenvalue reference matrix, so as to update the open-circuit voltage difference eigenvalue reference matrix, and the open-circuit voltage difference eigenvalue matrix of the current charging process is stored and used for updating the open-circuit voltage difference eigenvalue reference matrix of the next charging process. The open-circuit voltage difference characteristic value matrix of the current charging process is stored by clearing the open-circuit voltage difference characteristic value matrix of the last charging process.
It should be noted that, in the first charging process, no battery short-circuit fault early warning analysis is performed, and only the open-circuit voltage difference characteristic value matrix of the current charging process is stored as the open-circuit voltage difference characteristic value reference matrix of the subsequent charging process. The second charging process and the subsequent charging process need to be pre-warned and judged, and the pre-warned and judged only in the first charging process is not carried out.
In step S520, each element of the open-circuit voltage difference eigenvalue matrix is compared with an element corresponding to the open-circuit voltage difference eigenvalue reference matrix, and battery short-circuit fault early warning information is generated according to the comparison result.
In some embodiments, as shown in fig. 6, the battery short-circuit fault early-warning information includes first fault early-warning information, and step S520 specifically includes the steps of:
s610, obtaining a first inspection result according to the open-circuit voltage difference characteristic value matrix and the open-circuit voltage difference characteristic value reference matrix; the first check result comprises that none of the elements of the corresponding position are null values;
s620, obtaining a second inspection result according to the open-circuit voltage difference characteristic value matrix and the open-circuit voltage difference characteristic value reference matrix; the second detection result comprises that the element difference value of the corresponding position is smaller than a preset threshold value;
and S630, generating first fault early warning information according to the first detection result and the second detection result.
In step S610, if the element of the matrix of the characteristic value of the difference of the open-circuit voltage is not null, and the element of the same position of the matrix of the characteristic value of the difference of the open-circuit voltage is not null, the first test result is successful.
In step S620, if the first verification result is successful, a difference between an element related to the open-circuit voltage difference eigenvalue matrix and a corresponding element related to the open-circuit voltage difference eigenvalue reference matrix is calculated, and if the difference is smaller than a preset threshold, the second verification result is successful.
In step S630, first fault warning information is generated according to the first and second inspection results, that is, the first fault warning information is generated according to the abrupt change value of the open-circuit voltage difference characteristic value of the two consecutive charging processes. And if the first detection result and the second detection result are both successful, generating first fault early warning information. The first fault early warning information represents that a serious short circuit roadblock occurs in the battery, at the moment, a single battery corresponding to the row where the element of the open-circuit voltage difference characteristic value matrix is located is early warned, and the first fault early warning information is marked as warning _ flag 1.
It should be noted that if a single battery is in M series1And if the warning _ flag1 appears in the secondary charging process, the warning is considered to be an effective warning. Wherein M is1Not less than 1, the disclosed embodiment is for M1The value of (b) is not limited, and can be set by a person skilled in the art according to actual needs. Effective early warning is judged through the first fault alarm information of the continuous charging process for multiple times, and false alarm can be reduced.
In some embodiments, as shown in fig. 7, the battery short-circuit fault early-warning information includes second fault early-warning information, and the step S140 specifically includes the steps of:
s710, calculating to obtain a long-term evolution matrix of the difference characteristic value of the open-circuit voltage according to the matrix of the difference characteristic value of the open-circuit voltage;
s720, calculating the evolution speed of the single battery open-circuit voltage difference characteristic value according to the open-circuit voltage difference characteristic value long-term evolution matrix;
and S730, generating second fault early warning information according to the evolution speed.
In step S710, a voltage subinterval at a high end is randomly selected and fixed, and if the element of the corresponding row in the open-circuit voltage difference eigenvalue matrix of the subinterval is not null in the current charging process, the value of the element of the row is added to the latest row in the long-term evolution matrix of the open-circuit voltage difference eigenvalue, and the start time of the current charging process is stored in a time sequence. The voltage subinterval at the high end means that the end point value of the interval is close to the charge cut-off voltage.
In step S720, when the number of rows of the long-term evolution matrix of the difference characteristic value of the open-circuit voltage is greater than the preset number of row reference value N, obtaining the last N rows of elements and the corresponding time sequence of the corresponding column of each single battery in the long-term evolution matrix of the difference characteristic value of the open-circuit voltage, and fitting the last N rows of elements and the time sequence by using a linear least square algorithm to obtain the evolution speed of the difference value of the open-circuit voltage of the single battery with time, that is, calculating the evolution speed of the single battery according to the difference value of the open-circuit voltage of the single battery in N consecutive charging processes and the start time of the corresponding N charging processes.
It should be noted that, when the number of rows of the open-circuit voltage difference characteristic value long-term evolution matrix is less than or equal to the preset number of rows reference value N, steps S720 to S730 are not performed.
In step S730, second fault warning information is generated according to an evolution speed of the open-circuit voltage difference value of the consecutive charging processes. And if the evolution speed exceeds a preset evolution speed threshold, generating second fault early warning information. And the second fault early warning information represents that the battery has a micro short circuit fault, and the early warning is carried out on the battery at the moment, and the second fault early warning information is marked as warning _ flag 2.
It should be noted that if a single battery is in M series2And if the warning _ flag2 appears in the secondary charging process, the warning is considered to be an effective warning. Wherein M is2Not less than 1, the disclosed embodiment is for M2The value of (b) is not limited, and can be set by a person skilled in the art according to actual needs. Effective early warning is judged through second fault alarm information of continuous charging processes for multiple times, and false alarm can be reduced.
In some embodiments, as shown in fig. 8, in the actual battery short-circuit fault analyzing and warning process, the method for generating the battery short-circuit fault warning information includes, but is not limited to, steps S8010 to S8100.
S8010, judging whether the vehicle is in a parking charging process, if so, executing steps S8020 to S8100, and if not, continuing to execute step S8010;
s8020, identifying a complete parking charging process data segment;
s8030, calculating the difference value of the open circuit voltage of each single battery at each data sampling point compared with the average battery according to the parking charging process data segment;
s8040, calculating an open-circuit voltage difference characteristic value matrix of the current charging process according to the open-circuit voltage difference value of each single battery;
s8050, calling an open-circuit voltage difference characteristic value reference matrix;
s8060, performing serious short circuit fault early warning on the battery according to the open circuit voltage difference characteristic value matrix and the open circuit voltage difference characteristic value reference matrix;
s8070, updating an open-circuit voltage difference characteristic value reference matrix according to the open-circuit voltage difference characteristic value matrix in the current charging process;
s8080, after the step S8040, updating the long-term evolution matrix of the difference characteristic value of the open-circuit voltage according to the matrix of the difference characteristic value of the open-circuit voltage;
s8090, carrying out early warning on micro short circuit faults of the battery according to the long-term evolution matrix of the difference characteristic value of the open circuit voltage;
and S8100, identifying the next parking charging process.
In some embodiments, as shown in fig. 9, in real life, the battery short-circuit fault warning information generating method includes, but is not limited to, steps S9010 to S9140.
S9010, judging whether the vehicle is in a parking charging process, if so, executing the steps S9020 to S9140, and if not, continuing to execute the step S9010;
s9020, identifying a complete parking charging process data segment;
s9030, judging whether a current mutation point meeting the memory calculation condition exists in the charging process; if yes, executing step S9050; if the judgment result is no, executing the step S9040;
s9040, calling the internal resistance of the single battery and the average internal resistance of the battery calculated in the previous charging process, and participating in subsequent calculation;
s9050, calculating and storing the internal resistance of the single battery and the average internal resistance of the battery in the charging process;
s9060, calculating an open-circuit voltage difference value of the single battery compared with an average battery;
s9070, calculating an open-circuit voltage difference characteristic value matrix of the charging process according to the open-circuit voltage difference value;
s9080, calling an open-circuit voltage difference characteristic value reference matrix;
s9090, judging serious short-circuit faults of the battery according to the open-circuit voltage difference characteristic value matrix and the open-circuit voltage difference characteristic value reference matrix, and giving early warning information;
s9100, updating an open-circuit voltage difference characteristic value reference matrix according to the open-circuit voltage difference characteristic value matrix;
s9110, after the step S9060, judging whether the charging process meets the updating condition of the open-circuit voltage difference characteristic value long-term evolution matrix; if yes, executing S9120; if the judgment result is negative, executing S9150;
s9120, updating the open-circuit voltage difference characteristic value long-term evolution matrix according to the open-circuit voltage difference characteristic value matrix;
s9130, judging whether the row number of the open-circuit voltage difference characteristic value long-term evolution matrix meets an early warning analysis condition; if yes, executing S9140; if the judgment result is negative, executing S9150;
s9140, performing early warning on micro short circuit faults of the battery according to the long-term evolution matrix of the difference characteristic value of the open-circuit voltage;
s9150, identifying the next parking charging process.
The method has the advantages that battery short-circuit fault early warning is carried out according to parking charging data, whether the voltage of a single battery in the vehicle-mounted power battery system is greatly abnormally and suddenly reduced compared with the voltage of other batteries can be found in time, and therefore whether the single battery has serious short-circuit fault or not is identified in time, and accurate positioning of a fault battery is given; and the phenomenon that the voltage of a single battery is slowly reduced compared with the voltage of other batteries in a long-term trend can be found, so that whether the single battery has a micro short circuit or a self-discharge high fault is identified in time, and accurate positioning of the fault battery is given. By identifying the short-circuit fault of the single battery and giving out safety early warning information, a manufacturer is guided to replace the fault battery as soon as possible, the occurrence of the thermal runaway accident of the new energy automobile battery can be prevented, and the use safety of the automobile is improved.
The method for generating the early warning information of the short circuit fault of the battery provided by the embodiment of the disclosure comprises the steps of acquiring charging data of a charging process, wherein the charging data comprises sampling time, charging current and voltages of at least two single batteries, sampling the charging data according to the sampling time to obtain at least two data sampling points, calculating the difference value of an open circuit voltage of each single battery at each data sampling point compared with an average battery according to the charging current and the voltages of the single batteries, calculating an open circuit voltage difference characteristic value matrix according to the difference value of the open circuit voltage, generating the early warning information of the short circuit fault of the battery in the charging process through the open circuit voltage difference characteristic value matrix, diagnosing and early warning the short circuit fault of the battery in real time, solving the problem that a cloud end cannot directly identify the SOC difference between the single batteries by using the charging process data, and needing no support of an OCV-SOC curve of the battery, the method has the advantages that the calculation complexity and the resource requirement are reduced, and the problem of high false alarm rate caused by the fact that the cloud end is easily influenced by charging current, temperature and sampling when short-circuit fault diagnosis is carried out through the pressure difference at present is solved.
The embodiment of the present disclosure further provides a device for generating battery short-circuit fault warning information, which is applied to a charging process, and as shown in fig. 10, the method for generating battery short-circuit fault warning information may be implemented, where the device includes: the system comprises a first obtaining module 1010, a first calculating module 1020, a second calculating module 1030 and a fault early warning information generating module 1040, wherein the first obtaining module 1010 is used for obtaining charging data in a charging process, and the charging data comprises sampling time, charging current and voltages of at least two single batteries; the first calculating module 1020 is configured to calculate an open circuit voltage difference value of each cell at each data sampling point compared to an average cell according to the charging current and the voltage of the cell; the second calculating module 1030 is configured to calculate an open-circuit voltage difference eigenvalue matrix according to the open-circuit voltage difference value of each single battery at each data sampling point; the fault warning information generating module 1040 is configured to generate battery short-circuit fault warning information in the charging process according to the open-circuit voltage difference characteristic value matrix. The battery short-circuit fault early-warning information generation device of the embodiment of the present disclosure is configured to execute the battery short-circuit fault early-warning information generation method in the above embodiment, and a specific processing procedure of the battery short-circuit fault early-warning information generation device is the same as the battery short-circuit fault early-warning information generation method in the above embodiment, and details are not repeated here.
The device for generating the early warning information of the short circuit fault of the battery provided by the embodiment of the disclosure can acquire the charging data of a charging process by realizing the method for generating the early warning information of the short circuit fault of the battery, wherein the charging data comprises sampling time, charging current and voltages of at least two single batteries, the charging data is sampled according to the sampling time to obtain at least two data sampling points, the difference value of the open circuit voltage of each single battery at each data sampling point compared with the average battery is calculated according to the charging current and the voltages of the single batteries, the characteristic value matrix of the open circuit voltage difference is calculated according to the difference value of the open circuit voltage, the early warning information of the short circuit fault of the battery in the charging process is generated by the characteristic value matrix of the open circuit voltage difference, the diagnosis and the early warning of the short circuit fault of the battery can be carried out in real time, the problem that the SOC difference between the single batteries cannot be directly identified by the charging process data in a cloud is solved, and the support of an OCV-SOC curve of the battery is not needed, the calculation complexity and the resource requirement are reduced, and the problem of high false alarm rate caused by the influence of charging current, temperature and sampling when the short-circuit fault diagnosis is carried out by the cloud end through the pressure difference at present is solved.
An embodiment of the present disclosure further provides a computer device, including:
at least one processor, and,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions for execution by the at least one processor to cause the at least one processor, when executing the instructions, to implement a method as in any one of the embodiments of the first aspect of the application.
The hardware structure of the computer apparatus will be described in detail below with reference to fig. 11. The computer device includes: a processor 1110, a memory 1120, an input/output interface 1130, a communication interface 1140, and a bus 1150.
The processor 1110 may be implemented by a general CPU (Central processing Unit), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits, and is configured to execute related programs to implement the technical solution provided by the embodiment of the present disclosure;
the Memory 1120 may be implemented in a ROM (Read Only Memory), a static Memory device, a dynamic Memory device, or a RAM (Random Access Memory). The memory 1120 may store an operating system and other application programs, and when the technical solution provided by the embodiments of the present disclosure is implemented by software or firmware, the relevant program codes are stored in the memory 1120, and the processor 1110 calls the method for generating the battery short circuit fault warning information according to the embodiments of the present disclosure;
an input/output interface 1130 for implementing information input and output;
a communication interface 1140, which is used for realizing communication interaction between the device and other devices, and may realize communication in a wired manner (e.g., USB, network cable, etc.) or in a wireless manner (e.g., mobile network, WIFI, bluetooth, etc.); and
a bus 1150 that transfers information between the various components of the device (e.g., the processor 1110, the memory 1120, the input/output interface 1130, and the communication interface 1140);
wherein the processor 1110, memory 1120, input/output interface 1130, and communication interface 1140 enable communication connections within the device with each other via the bus 1150.
The embodiment of the present disclosure also provides a storage medium, which is a computer-readable storage medium, in which computer-executable instructions are stored, and the computer-executable instructions are used to enable a computer to execute the method for generating the battery short-circuit fault early-warning information according to the embodiment of the present disclosure.
The memory, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs as well as non-transitory computer executable programs. Further, the memory may include high speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory located remotely from the processor, and these remote memories may be connected to the processor through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The embodiments described in the embodiments of the present disclosure are for more clearly illustrating the technical solutions of the embodiments of the present disclosure, and do not constitute a limitation to the technical solutions provided in the embodiments of the present disclosure, and it is obvious to those skilled in the art that the technical solutions provided in the embodiments of the present disclosure are also applicable to similar technical problems with the evolution of technology and the emergence of new application scenarios.
Those skilled in the art will appreciate that the solutions shown in fig. 1-9 are not meant to limit embodiments of the present disclosure, and may include more or fewer steps than those shown, or may combine certain steps, or different steps.
The above-described embodiments of the apparatus are merely illustrative, wherein the units illustrated as separate components may or may not be physically separate, i.e. may be located in one place, or may also be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
One of ordinary skill in the art will appreciate that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof.
The terms "first," "second," "third," "fourth," and the like in the description of the application and the above-described figures, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be understood that in the present application, "at least one" means one or more, "a plurality" means two or more. "and/or" for describing an association relationship of associated objects, indicating that there may be three relationships, e.g., "a and/or B" may indicate: only A, only B and both A and B are present, wherein A and B may be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one of the following" or similar expressions refer to any combination of these items, including any combination of single item(s) or plural items. For example, at least one (one) of a, b, or c, may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes multiple instructions for causing a computer device (which may be a personal computer, a server, or a network device) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing programs, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The preferred embodiments of the present disclosure have been described above with reference to the accompanying drawings, and therefore do not limit the scope of the claims of the embodiments of the present disclosure. Any modifications, equivalents and improvements within the scope and spirit of the embodiments of the present disclosure should be considered within the scope of the claims of the embodiments of the present disclosure by those skilled in the art.
Claims (10)
1. A battery short-circuit fault early warning information generation method is applied to a charging process and is characterized by comprising the following steps:
acquiring charging data of a primary charging process, wherein the charging data comprises sampling time, charging current and voltages of at least two single batteries;
calculating the difference value of the open circuit voltage of each single battery at each data sampling point compared with the average battery according to the charging current and the voltage of the single battery;
calculating an open-circuit voltage difference characteristic value matrix according to the open-circuit voltage difference value of each single battery at each data sampling point;
and generating battery short-circuit fault early warning information in the charging process according to the open-circuit voltage difference characteristic value matrix.
2. The method according to claim 1, wherein calculating the difference value of the open circuit voltage of each single battery at each data sampling point compared with the average battery according to the charging current and the voltage of the single battery comprises:
calculating to obtain a first open-circuit voltage of the single battery at the data sampling point and a second open-circuit voltage of the average battery at the data sampling point according to the charging current, the voltage and a preset internal resistance;
and calculating the difference value of the open circuit voltage of the single battery at the data sampling point according to the first open circuit voltage and the second open circuit voltage.
3. The method according to claim 2, wherein the calculating a first open-circuit voltage of the single battery at the data sampling point and a second open-circuit voltage of the average battery at the data sampling point according to the charging current, the voltage and a preset internal resistance comprises:
identifying a charging current mutation point according to the mutation value of the charging current;
calculating the preset internal resistance according to the charging current at the charging current sudden change point and the voltage at the charging current sudden change point;
and calculating to obtain a first open-circuit voltage of the single battery at the data sampling point and a second open-circuit voltage of the average battery at the data sampling point according to the charging current at the data sampling point, the voltage at the data sampling point and the preset internal resistance.
4. The method according to claim 1, wherein the calculating an open circuit voltage difference eigenvalue matrix according to the open circuit voltage difference value of each single battery at each data sampling point comprises:
dividing a use voltage interval of the single battery into at least two subintervals, wherein the use voltage interval is an interval from a discharge cut-off voltage to a charge cut-off voltage;
classifying each data sampling point into a plurality of subintervals according to the open-circuit voltage value of the average battery at each data sampling point;
calculating to obtain an open-circuit voltage difference characteristic value of the single battery in the subinterval according to the open-circuit voltage difference value of the single battery in the data sampling point of the subinterval;
and calculating to obtain the open-circuit voltage difference characteristic value matrix according to the open-circuit voltage difference characteristic values of the single batteries in the subintervals.
5. The method according to claim 1, wherein the generating of the battery short-circuit fault early warning information in the charging process according to the open-circuit voltage difference eigenvalue matrix comprises:
acquiring an open-circuit voltage difference characteristic value reference matrix;
and generating the battery short-circuit fault early warning information according to the open-circuit voltage difference characteristic value matrix and the open-circuit voltage difference characteristic value reference matrix.
6. The method of claim 5, wherein the battery short-circuit fault pre-warning information comprises first fault pre-warning information, and wherein the generating the battery short-circuit fault pre-warning information according to the open-circuit voltage difference eigenvalue matrix and the open-circuit voltage difference eigenvalue benchmark matrix comprises:
obtaining a first test result according to the open-circuit voltage difference characteristic value matrix and the open-circuit voltage difference characteristic value reference matrix; the first check result comprises that none of the elements of the corresponding position are null values;
obtaining a second test result according to the open-circuit voltage difference characteristic value matrix and the open-circuit voltage difference characteristic value reference matrix; the second detection result comprises that the element difference value of the corresponding position is smaller than a preset threshold value;
and generating first fault early warning information according to the first detection result and the second detection result.
7. The method of claim 1, wherein the battery short-circuit fault pre-warning information includes second fault pre-warning information, and wherein the generating of the battery short-circuit fault pre-warning information during the charging process according to the open-circuit voltage difference eigenvalue matrix further comprises:
calculating to obtain a long-term evolution matrix of the difference characteristic value of the open-circuit voltage according to the matrix of the difference characteristic value of the open-circuit voltage;
calculating the evolution speed of the single battery open-circuit voltage difference characteristic value according to the open-circuit voltage difference characteristic value long-term evolution matrix;
and generating the second fault early warning information according to the evolution speed.
8. The utility model provides a battery short-circuit fault early warning information generation device, is applied to the charging process, its characterized in that includes:
the first acquisition module is used for acquiring charging data of a charging process, wherein the charging data comprises sampling time, charging current and voltages of at least two single batteries;
the first calculation module is used for calculating the difference value of the open-circuit voltage of each single battery at each data sampling point compared with the average battery according to the charging current and the voltage of the single battery;
the second calculation module is used for calculating an open-circuit voltage difference characteristic value matrix according to the open-circuit voltage difference value of each single battery at each data sampling point;
and the fault early warning information generating module is used for generating battery short circuit fault early warning information in the charging process according to the open-circuit voltage difference characteristic value matrix.
9. A computer device comprising a memory and a processor, wherein the memory has stored therein a program, and wherein the processor is configured to perform, when the program is executed by the processor:
the method of any one of claims 1 to 7.
10. A storage medium which is a computer-readable storage medium, wherein the computer-readable storage stores a computer program, and when the computer program is executed by a computer, the computer is configured to perform:
the method of any one of claims 1 to 7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115144765A (en) * | 2022-07-05 | 2022-10-04 | 东莞新能安科技有限公司 | Method and device for detecting short-circuit fault in battery |
| CN117829097A (en) * | 2024-02-29 | 2024-04-05 | 双一力(宁波)电池有限公司 | Battery data processing method and device, electronic equipment and readable storage medium |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115144765A (en) * | 2022-07-05 | 2022-10-04 | 东莞新能安科技有限公司 | Method and device for detecting short-circuit fault in battery |
| CN117829097A (en) * | 2024-02-29 | 2024-04-05 | 双一力(宁波)电池有限公司 | Battery data processing method and device, electronic equipment and readable storage medium |
| CN117829097B (en) * | 2024-02-29 | 2024-05-28 | 双一力(宁波)电池有限公司 | Battery data processing method and device, electronic equipment and readable storage medium |
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