CN113310647A - Method and device for detecting leakage of battery pack, electronic equipment and storage medium - Google Patents

Method and device for detecting leakage of battery pack, electronic equipment and storage medium Download PDF

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CN113310647A
CN113310647A CN202110734553.XA CN202110734553A CN113310647A CN 113310647 A CN113310647 A CN 113310647A CN 202110734553 A CN202110734553 A CN 202110734553A CN 113310647 A CN113310647 A CN 113310647A
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battery pack
fault
data
vehicle
insulation
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CN113310647B (en
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潘垂宇
张志�
李雪
于春洋
许立超
于鹏
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FAW Group Corp
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FAW Group Corp
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M3/00—Investigating fluid-tightness of structures
    • G01M3/40—Investigating fluid-tightness of structures by using electric means, e.g. by observing electric discharges
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/10—Energy storage using batteries
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries

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Abstract

The embodiment of the application discloses a method and a device for detecting leakage of a battery pack, electronic equipment and a storage medium. Which comprises the following steps: performing characteristic analysis on the battery pack data, and determining whether the battery pack data is fault data according to a characteristic analysis result; under the condition of being fault data, determining the fault category of the battery pack data, and determining the frequency of the fault category appearing in a preset diagnosis period; determining the insulation abnormal ratio of the battery pack according to the insulation value of the battery pack in the current diagnosis period and the insulation value of the battery pack in at least one historical diagnosis period; and performing fault evaluation on the battery pack data according to the fault category, the frequency of the fault category appearing in the preset diagnosis period and the insulation abnormity ratio of the battery pack, and determining whether the battery pack leaks according to the fault evaluation result. This application can be on the basis that does not increase hardware whether real-time supervision battery package takes place to leak the risk, has promoted the security of battery package, has protected driver's the security of the lives and property.

Description

Method and device for detecting leakage of battery pack, electronic equipment and storage medium
Technical Field
The embodiment of the application relates to the technical field of automobiles, in particular to a method and a device for detecting leakage of a battery pack, electronic equipment and a storage medium.
Background
The lithium ion power battery pack is a sealed structure, and if the sealed structure of the battery pack is damaged to enable water vapor to enter the battery pack, the lithium metal of the negative electrode and water undergo violent chemical reaction to cause the battery pack to burn at a very high speed. Therefore, there is a great safety risk in driving the electric vehicle.
In the prior art, the battery pack mainly detects whether water leaks into the battery pack or not by means of IP67 experiments during design and air tightness detection during production, but cannot ensure that water vapor enters air caused by damage of an outer shell or damage of a vent valve in the use process of the battery pack. In order to solve the problem, the prior art detects whether the battery pack leaks water by adding a humidity sensor and other methods, but the method not only increases the hardware cost, but also increases the burden of the originally tense CAN communication. Therefore, it is desirable to design a method for detecting leakage of a battery pack, which can improve the safety of the battery pack without increasing the cost.
Disclosure of Invention
The embodiment of the application provides a method and a device for detecting leakage of a battery pack, electronic equipment and a storage medium, which can monitor whether the battery pack has a leakage risk or not in real time and improve the safety of the battery pack.
In a first aspect, an embodiment of the present application provides a method for detecting leakage of a battery pack, where the method includes:
acquiring battery pack data of a vehicle;
performing characteristic analysis on the battery pack data, and determining whether the battery pack data is fault data according to a characteristic analysis result;
determining the fault category of the battery pack data under the condition of fault data, and determining the frequency of the fault category appearing in a preset diagnosis period;
determining an insulation abnormal ratio of the battery pack according to the insulation value of the battery pack in the current diagnosis period and the insulation value of the battery pack in at least one historical diagnosis period;
and performing fault evaluation on the battery pack data according to the fault category, the frequency of the fault category appearing in a preset diagnosis period and the insulation abnormal ratio of the battery pack, and determining whether the battery pack leaks according to a fault evaluation result.
In a second aspect, an embodiment of the present application provides an apparatus for detecting leakage of a battery pack, where the apparatus includes:
the data acquisition module is used for acquiring battery pack data of the vehicle;
the characteristic analysis module is used for carrying out characteristic analysis on the battery pack data and determining whether the battery pack data is fault data or not according to a characteristic analysis result;
the first determining module is used for determining the fault category of the battery pack data under the condition of fault data and determining the frequency of the fault category appearing in a preset diagnosis period;
the second determination module is used for determining the insulation abnormal ratio of the battery pack according to the insulation value of the battery pack in the current diagnosis period and the insulation value of the battery pack in at least one historical diagnosis period;
and the fault determining module is used for performing fault evaluation on the battery pack data according to the fault type, the frequency of the fault type occurring in a preset diagnosis period and the insulation abnormity ratio of the battery pack, and determining whether the battery pack leaks according to a fault evaluation result.
In a third aspect, an embodiment of the present application provides an electronic device, including:
one or more processors;
storage means for storing one or more programs;
when executed by the one or more processors, the one or more programs cause the one or more processors to implement the method for battery pack leak detection described in any embodiment of the present application.
In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, where the program, when executed by a processor, implements the method for detecting battery pack leakage according to any embodiment of the present application.
The embodiment of the application provides a method and a device for detecting leakage of a battery pack, electronic equipment and a storage medium, and the method comprises the steps of obtaining battery pack data of a vehicle; performing characteristic analysis on the battery pack data, and determining whether the battery pack data is fault data according to a characteristic analysis result; under the condition of being fault data, determining the fault category of the battery pack data, and determining the frequency of the fault category appearing in a preset diagnosis period; determining the insulation abnormal ratio of the battery pack according to the insulation value of the battery pack in the current diagnosis period and the insulation value of the battery pack in at least one historical diagnosis period; and performing fault evaluation on the battery pack data according to the fault category, the frequency of the fault category appearing in the preset diagnosis period and the insulation abnormity ratio of the battery pack, and determining whether the battery pack leaks according to the fault evaluation result. This application is on the basis that does not increase hardware, can whether real-time supervision battery package takes place to leak the risk, has promoted the security of battery package, has protected driver's the security of the lives and property.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present application, nor do they limit the scope of the present application. Other features of the present application will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not intended to limit the present application. Wherein:
fig. 1A is a schematic diagram of a battery pack leakage detection system according to an embodiment of the present disclosure;
fig. 1B is a first flowchart of a method for detecting leakage of a battery pack according to an embodiment of the present disclosure;
fig. 2 is a second flowchart of a method for detecting leakage of a battery pack according to an embodiment of the present disclosure;
fig. 3 is a third flowchart of a method for detecting leakage of a battery pack according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of an apparatus for detecting leakage of a battery pack according to an embodiment of the present disclosure;
fig. 5 is a block diagram of an electronic device for implementing a method of battery pack leak detection according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all 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 application.
Example one
Fig. 1A is a schematic diagram of a battery pack leakage detection system according to an embodiment of the present disclosure; fig. 1B is a first flowchart of a method for detecting leakage of a battery pack according to an embodiment of the present disclosure. The embodiment is applicable to the condition of detecting whether the battery pack leaks water or not. The method for detecting the leakage of the battery pack provided by the embodiment of the present application may be performed by the apparatus for detecting the leakage of the battery pack provided by the embodiment of the present application, and the apparatus may be implemented by software and/or hardware and integrated in an electronic device executing the method. The electronic device in the embodiment of the present application is carried by a battery pack leakage detection system.
Referring to fig. 1A, a schematic diagram of a battery pack leakage detection system provided in an embodiment of the present application is shown, where the battery pack leakage detection system includes: the system comprises a vehicle-mounted terminal 11, a cloud server 12 and a background server 13. The vehicle is provided with a vehicle-mounted terminal (such as a vehicle-mounted Telematics-BOX) which can upload data of the vehicle to a cloud server. The background server can download the data of the vehicle from the cloud server and detect the leakage of the battery pack. And if the monitoring result shows that the battery pack leakage exists in the vehicle, sending a leakage information notification to the vehicle-mounted terminal.
Referring to fig. 1B, the method of the present embodiment includes, but is not limited to, the following steps:
and S110, acquiring battery pack data of the vehicle.
The vehicle is provided with a battery sampler and a battery pack, and the battery pack is provided with a voltage sensor and a temperature sensor which are respectively used for monitoring voltage data and temperature data of the battery pack. The battery sampler is used for collecting battery pack data of the battery pack, such as voltage data and temperature data; in addition, the battery pack data further includes at least one of an insulation value of a high voltage circuit of the vehicle, historical driving data of the vehicle, charging data of the vehicle, voltage data of the battery pack, temperature data of the battery pack, a number of the vehicle, and a collection time of the battery pack data.
In the embodiment of the application, the vehicle terminal uploads the battery pack data of the vehicle and stores the battery pack data to the cloud server. When the background server is performing battery pack leakage detection analysis on the vehicle, the background server can acquire the battery pack data from the cloud server. Optionally, the vehicle-mounted terminal may further directly upload the battery pack data of the vehicle to the background server, so that the background server performs battery pack leakage detection analysis on the battery pack data.
Optionally, data can be uploaded to the cloud server or the backend server according to data uploading standards (such as data uploading frequency and data fields) specified in the national standard GBT32960, so that the battery pack data uploaded to the cloud server or the backend server is more universal. For example, a battery collector in the vehicle collects temperature data and voltage data of a battery pack once every 10 seconds, and the vehicle-mounted terminal aggregates the temperature data and the voltage data of the battery pack with historical driving data of the vehicle, charging data of the vehicle, voltage data of the battery pack, temperature data of the battery pack, the number of the vehicle and collection time of the battery pack data into battery pack data and uploads the battery pack data to a cloud server or a background server.
And S120, performing characteristic analysis on the battery pack data, and determining whether the battery pack data is fault data according to a characteristic analysis result.
In the embodiment of the application, after the background server acquires the battery pack data of the vehicle, the characteristic analysis is performed on the battery pack data. Specifically, if the battery pack data of the vehicle is fault data, various characteristics are shown, a preset diagnosis period (for example, 1 day) is set, and all the battery pack data of the vehicle in the preset diagnosis period are analyzed. If the battery pack data without the characteristics is normal data; if the battery pack data with the characteristics is the fault data, it is further determined whether the battery pack sends a leak in the case of the fault data, and a specific leak determination process will be explained in the following embodiments.
In the embodiment of the application, characteristic analysis is mainly performed on indexes such as temperature data of the battery pack, voltage data of the battery pack and insulation value of the pure battery pack state, and whether the battery pack data is fault data or not is judged according to a characteristic analysis result.
It should be noted that, in the existing design of an electric vehicle, the insulation value feeds back the insulation resistance value of the whole high-voltage loop, and the insulation value of a pure battery pack state is needed for judging the leakage of the battery pack. The whole loop in the charging state comprises a part of the charging pile, and the driving state comprises all high-voltage loop states of a battery pack system, a motor control system comprising an inverter and the like. The present application treats this state, in which the vehicle is just powered on and the relay is not connected to the motor controller, as the battery only state. That is, the pure battery pack state needs to satisfy three conditions simultaneously: the vehicle state is a running state, the charging state is a non-charging state, and the motor controller voltage of the vehicle does not reach the battery voltage.
The mode of determining the insulation value of the pure battery pack state is as follows: as a system of the electric vehicle, an insulation value of a high voltage circuit of the vehicle is stored in the battery pack data. When the vehicle is powered on, if the voltage data of the motor controller is far smaller than the voltage data of the battery pack, the insulation value of the high-voltage loop of the vehicle can be regarded as the insulation value of the pure battery pack state, and the insulation value can be used for battery pack leakage analysis.
In the embodiment of the application, due to the leakage of the battery pack, the moisture entering can cause the abnormality (namely fault data) of the battery pack data, such as temperature data abnormality, voltage data abnormality and insulation value abnormality inside the vehicle. The fault data identification and characteristics described in table 1 are specific examples, and other battery pack conditions need to be adjusted accordingly according to specific states. The fault data signature is shown in table 1 below:
TABLE 1 Fault data feature identification Table
Figure BDA0003141108500000071
And S130, under the condition of the fault data, determining the fault type of the battery pack data, and determining the frequency of the fault type in a preset diagnosis period.
In the embodiment of the present application, after determining that the battery pack data is the failure data through the above steps, it is further determined whether the battery pack transmits a leak through S130 to S150. In this step, when the battery pack data is fault data, the battery pack data is specifically analyzed in a preset diagnosis period to determine a fault category to which the battery pack data belongs, and a ratio of the number of frame data corresponding to the fault category to the total number of the frame data in the preset diagnosis period, that is, a frequency of occurrence of the fault category in the preset diagnosis period is determined. Alternatively, the fault category may be for one battery cell, such as whether only temperature data is abnormal, only voltage data is abnormal, or both temperature data and voltage data are abnormal for one battery cell; the fault category may also be for a circuit abnormal condition, such as whether a circuit abnormal condition in a battery pack is an open circuit or a short circuit.
And S140, determining the insulation abnormal ratio of the battery pack according to the insulation value of the battery pack in the current diagnosis period and the insulation value of the battery pack in at least one historical diagnosis period.
In the embodiment of the present application, whether the battery pack leaks or not needs to be analyzed, and optionally, the insulation abnormal condition of the battery pack may be represented by an insulation abnormal ratio of the battery pack. Specifically, one battery pack data corresponds to one frame data, so that all battery pack data in a preset diagnosis period comprises a plurality of frame data, each battery pack data packet has an insulation value of the battery pack, a characteristic value (such as an average number or a median number) of the insulation value of the battery pack in the current diagnosis period is calculated, a characteristic value of the insulation value of the battery pack in the previous diagnosis period is calculated, a difference value (namely a difference between the insulation values of the battery packs) of the battery packs is calculated, and finally the difference value of the insulation values of the battery packs is divided by the characteristic value of the insulation value of the battery pack in the current diagnosis period to obtain an insulation abnormal ratio of the battery pack.
When the difference between the insulation values of the battery packs is negative, indicating that the insulation value of the battery pack is increased, the difference between the insulation values of the battery packs is written as zero. The smaller the characteristic value of the insulation value of the battery pack in the current diagnosis period is, the larger the insulation abnormality ratio of the battery pack is.
S150, fault evaluation is carried out on the battery pack data according to the fault type, the frequency of the fault type occurring in the preset diagnosis period and the insulation abnormal ratio of the battery pack, and whether the battery pack leaks or not is determined according to the fault evaluation result.
In the embodiment of the application, after the frequency of the fault type in the preset diagnosis period and the insulation abnormal ratio of the battery pack are calculated through the steps, the fault evaluation is performed on the battery pack data. The specific method of fault evaluation may be: and adopting a pre-trained fault evaluation model, taking the fault type, the frequency of the fault type in a preset diagnosis period and the insulation abnormity ratio of the battery pack as characteristic values, and inputting the characteristic values into the fault evaluation model to obtain a fault evaluation result. And judging whether the battery pack leaks or not according to the fault evaluation result.
Optionally, the battery pack data of the vehicle may further include a maintenance log of the battery pack, where the maintenance log includes a maintenance condition and time of the battery pack. Therefore, the method and the device can also determine the latest time for the battery maintenance of the vehicle according to the battery pack data of the vehicle; and if the time interval between the latest time of the battery maintenance and the current time is greater than the preset time interval, sending a reminding message of the battery maintenance to a vehicle-mounted terminal of the vehicle.
According to the technical scheme provided by the embodiment, the battery pack data of the vehicle is acquired; performing characteristic analysis on the battery pack data, and determining whether the battery pack data is fault data according to a characteristic analysis result; under the condition of being fault data, determining the fault category of the battery pack data, and determining the frequency of the fault category appearing in a preset diagnosis period; determining the insulation abnormal ratio of the battery pack according to the insulation value of the battery pack in the current diagnosis period and the insulation value of the battery pack in at least one historical diagnosis period; and performing fault evaluation on the battery pack data according to the fault category, the frequency of the fault category appearing in the preset diagnosis period and the insulation abnormity ratio of the battery pack, and determining whether the battery pack leaks according to the fault evaluation result. This application is through carrying out characteristic analysis to battery package data and confirming whether to be fault data, if for fault data, whether this battery package data of continuous analysis takes place to leak, and this application can real-time supervision battery package take place to leak the risk on the basis that does not increase hardware, has greatly promoted the security of battery package, has protected driver's the security of the lives and property.
Example two
Fig. 2 is a second flowchart of a method for detecting leakage of a battery pack according to an embodiment of the present disclosure. The embodiment of the application is optimized on the basis of the embodiment, and specifically optimized as follows: a detailed explanation of the judgment process of the leakage of the battery pack is added.
Referring to fig. 2, the method of the present embodiment includes, but is not limited to, the following steps:
s210, acquiring battery pack data of the vehicle.
And S220, performing characteristic analysis on the battery pack data, and determining whether the battery pack data is fault data according to a characteristic analysis result.
And S230, under the condition of the fault data, determining the fault type of the battery pack data, and determining the frequency of the fault type in a preset diagnosis period.
S240, determining the insulation abnormal ratio of the battery pack according to the insulation value of the battery pack in the current diagnosis period and the insulation value of the battery pack in at least one historical diagnosis period.
And S250, carrying out cumulative summation according to the fault type, the frequency of the fault type in a preset diagnosis period and the number of the single batteries corresponding to the fault type, and determining a fault value corresponding to the battery pack.
Wherein, the battery package includes at least one battery monomer.
In the embodiment of the application, after the fault type of the battery pack data, the frequency of the fault type in the preset diagnosis period and the insulation abnormal ratio of the battery pack are determined through the steps, the fault value corresponding to the battery pack is determined according to the fault type, the frequency of the fault type in the preset diagnosis period and the insulation abnormal ratio of the battery pack. Specifically, for example, the fault category is for one battery cell, that is, the fault category includes three cases, namely, abnormal temperature data only, abnormal voltage data only, and abnormal temperature data and abnormal voltage data. Respectively calculating the product of the frequency of the fault category appearing in the preset diagnosis period and the number of the battery monomers corresponding to the fault category under the three conditions to obtain three fault sub-numerical values; and adding the three fault sub-values to obtain a fault value corresponding to the battery pack. The formula for determining the fault value is as follows:
Figure BDA0003141108500000101
wherein, P represents the corresponding failure numerical value of the battery pack; c represents the weight corresponding to the fault category, the value of the weight is 1 or 0, the value of 1 represents that the battery pack data in the preset diagnosis period has the fault category, and the value of 0 represents that the battery pack data in the preset diagnosis period does not have the fault category; n represents the number of the single batteries corresponding to the fault category; f represents the frequency of the fault category in a preset diagnosis period; n represents the number of the types of the fault categories, and correspondingly, the value of i is a natural integer between 1 and n.
Optionally, the weight C corresponding to the fault category may also be adjusted in time by taking a value between 0 and 1 according to the actual situation.
And S260, summing the fault value and the insulation abnormal ratio of the battery pack, and then carrying out normalization processing on the sum to obtain a fault evaluation result.
In the embodiment of the application, the fault value and the insulation abnormal ratio of the battery pack obtained in the above steps are summed, and then normalized to obtain a fault evaluation result.
Specifically, the fault evaluation result is determined by the following risk evaluation formula:
Figure BDA0003141108500000111
wherein score represents the failure evaluation result; p represents a fault value corresponding to the battery pack; dmedianA difference value representing an insulation value of the battery pack for a current diagnostic period and an insulation value of the battery pack for at least one historical diagnostic period; a. themedianAn insulation value of the battery pack representing a current diagnostic period; k is an adjusting factor used for adjusting the insulation abnormal ratio of the battery pack; m is a theoretical fault value corresponding to the faults of all the battery monomers in the battery pack; q is a constant; the 100 to the right of the equal sign indicates that score is better with higher score evaluation values as a risk assessment scheme.
Determining a battery pack leakage risk grade of the vehicle according to a risk evaluation formula, wherein if score is 100, the battery pack has no leakage risk; if score is 0, it means that the leakage risk of the battery pack is the highest. Alternatively, 3 risk levels may be set, such as a low level, a medium level, or a high level. If score > 80, the risk level is low; if 80> score > -60, the risk level risk is medium; if score <60, the risk level risk is high.
And S270, determining whether the battery pack leaks according to the fault evaluation result.
In the embodiment of the present application, a leakage risk criterion is set, such as score 60 of risk assessment formula. If score of the risk assessment formula is less than 60, indicating that the battery pack leaks, sending a leakage early warning; if the score of the risk assessment formula is >60, it indicates that there is no leakage from the battery pack.
Optionally, the risk level in S260 and the leakage risk criterion in S270 may be modified according to actual situations. The specific modified scheme may be: when the driver returns the faulty vehicle to the factory for maintenance, the battery pack is disassembled, whether the phenomenon corresponding to the fault category exists in the embodiment is analyzed, and the risk level in the step S260 and the risk early warning standard in the step S270 are corrected according to the fault phenomenon; the method can also be as follows: and making a fault data sample, and correcting the evaluation of the risk level corresponding to the fault category by using a machine learning model.
According to the technical scheme provided by the embodiment, the battery pack data of the vehicle is acquired; performing characteristic analysis on the battery pack data, and determining whether the battery pack data is fault data according to a characteristic analysis result; under the condition of being fault data, determining the fault category of the battery pack data, and determining the frequency of the fault category appearing in a preset diagnosis period; determining the insulation abnormal ratio of the battery pack according to the insulation value of the battery pack in the current diagnosis period and the insulation value of the battery pack in at least one historical diagnosis period; carrying out cumulative summation according to the fault category, the frequency of the fault category appearing in a preset diagnosis period and the number of the single batteries corresponding to the fault category, and determining a fault value corresponding to the battery pack; summing the fault value and the insulation abnormal ratio of the battery pack, and then carrying out normalization processing on the sum to obtain a fault evaluation result; and determining whether the battery pack leaks according to the fault evaluation result. This application is through carrying out fault assessment to battery package data, whether the analysis battery package leaks, and this application can real-time supervision battery package whether take place to leak the risk on the basis that does not increase hardware, has greatly promoted the security of battery package, has protected driver's the security of the lives and property.
EXAMPLE III
Fig. 3 is a third flowchart of a method for detecting leakage of a battery pack according to an embodiment of the present disclosure. The embodiment of the application is optimized on the basis of the embodiment, and specifically optimized as follows: a detailed explanation of the judgment process of the accuracy of the battery pack data and the analysis process of the leakage cause is added.
Referring to fig. 3, the method of the present embodiment includes, but is not limited to, the following steps:
and S310, acquiring battery pack data of the vehicle.
And S320, judging whether the battery pack data is accurate according to a preset judgment rule, and deleting the battery pack data if the battery pack data is not accurate.
In the embodiment of the application, after receiving the battery pack data, the background server can analyze the accuracy of the battery pack data according to the judgment rule of the accuracy of the battery pack data and delete the false alarm data. For example, taking a single battery as an example, the voltage value range of the battery pack that can be collected by the battery sampler is 0-5V, and when the voltage value is 5.3V, it is certain that the voltage value is caused by signal transmission, and the battery pack data should be excluded.
As shown in table 2 below, the rule for determining the accuracy of the battery pack data in the present embodiment is shown, the accuracy of the battery pack data in the present embodiment is determined as a specific example, and the methods for determining the accuracy of the remaining battery pack data are also within the protection range.
TABLE 2 Battery pack data accuracy judgment rules
Figure BDA0003141108500000131
And S330, performing characteristic analysis on the battery pack data, and determining whether the battery pack data is fault data according to a characteristic analysis result.
S340, under the condition of being fault data, determining the fault type of the battery pack data, and determining the frequency of the fault type in a preset diagnosis period;
s350, determining an insulation abnormal ratio of the battery pack according to the insulation value of the battery pack in the current diagnosis period and the insulation value of the battery pack in at least one historical diagnosis period;
and S360, performing fault evaluation on the battery pack data according to the fault type, the frequency of the fault type in a preset diagnosis period and the insulation abnormal ratio of the battery pack, and determining whether the battery pack leaks according to a fault evaluation result.
S370, under the condition that the battery pack leaks, determining the leakage reason of the battery pack according to the historical driving data of the vehicle; and transmitting the failure evaluation result of the vehicle and the leakage cause to a vehicle-mounted terminal of the vehicle.
The historical driving data of the vehicle comprises a vehicle driving track route, vehicle speed information, weather information and the like.
In the embodiment of the application, a leakage reason analysis module is configured in the battery pack leakage detection system, and when it is determined that the battery pack leaks and a leakage early warning is sent out through S360, the leakage reason analysis module is started to analyze the reason for the battery pack leaking. After the leakage reason of the battery pack is determined, the fault evaluation result and the leakage reason of the vehicle are sent to the vehicle-mounted terminal of the vehicle so as to warn a driver that the current vehicle is at a high risk. The specific execution process of the leakage reason analysis module is as follows: firstly, a leakage reason analysis module acquires the time of leakage occurrence, and searches a vehicle driving track route, vehicle speed information and weather information according to the time of leakage occurrence; then, by drawing a vehicle driving track route and matching with vehicle speed information, analyzing the driving habits of a driver, such as highway driving or urban low-lying road section driving; and finally, correlating weather information, analyzing local humidity and rainfall, analyzing whether the vehicle is involved in water or not and analyzing the leakage reason.
According to the technical scheme provided by the embodiment, the battery pack data of the vehicle is acquired; judging whether the battery pack data is accurate according to a preset judgment rule, and deleting the battery pack data if the battery pack data is not accurate; performing characteristic analysis on the battery pack data, and determining whether the battery pack data is fault data according to a characteristic analysis result; under the condition of being fault data, determining the fault category of the battery pack data, and determining the frequency of the fault category appearing in a preset diagnosis period; determining the insulation abnormal ratio of the battery pack according to the insulation value of the battery pack in the current diagnosis period and the insulation value of the battery pack in at least one historical diagnosis period; according to the fault type, the frequency of the fault type in a preset diagnosis period and the insulation abnormal ratio of the battery pack, carrying out fault evaluation on the battery pack data, and determining whether the battery pack leaks according to a fault evaluation result; under the condition that the battery pack leaks, determining the leakage reason of the battery pack according to the historical driving data of the vehicle; and transmitting the failure evaluation result of the vehicle and the leakage cause to a vehicle-mounted terminal of the vehicle. The battery pack data is subjected to accuracy judgment and leakage analysis, the leakage reason analysis is carried out on the battery pack after the battery pack is determined to leak, the leakage reason is sent to a driver, whether the battery pack of a vehicle leaks or not can be monitored, and risk early warning is carried out when the battery pack leaks.
Example four
Fig. 4 is a schematic structural diagram of an apparatus for detecting leakage of a battery pack according to an embodiment of the present disclosure, and as shown in fig. 4, the apparatus 400 may include:
the data acquisition module 410 is used for acquiring battery pack data of a vehicle.
And the characteristic analysis module 420 is configured to perform characteristic analysis on the battery pack data and determine whether the battery pack data is fault data according to a characteristic analysis result.
The first determining module 430 is configured to determine a fault category of the battery pack data if the battery pack data is fault data, and determine a frequency of occurrence of the fault category within a preset diagnosis period.
The second determining module 440 is configured to determine an insulation abnormality ratio of the battery pack according to the insulation value of the battery pack in the current diagnosis period and the insulation value of the battery pack in at least one historical diagnosis period.
And the fault determining module 450 is configured to perform fault evaluation on the battery pack data according to the fault category, the frequency of the fault category occurring in a preset diagnosis period, and the insulation abnormal ratio of the battery pack, and determine whether the battery pack leaks according to a fault evaluation result.
Further, the failure determining module 450 is specifically configured to: carrying out accumulation summation according to the fault category, the frequency of the fault category appearing in a preset diagnosis period and the number of the single batteries corresponding to the fault category, and determining a fault value corresponding to the battery pack; the battery pack comprises at least one battery cell; and summing the fault numerical value and the insulation abnormal ratio of the battery pack, and then carrying out normalization processing on the fault numerical value and the insulation abnormal ratio to obtain a fault evaluation result.
Optionally, the fault evaluation result is determined by the following formula:
Figure BDA0003141108500000161
wherein score represents the failure evaluation result; c represents the weight corresponding to the fault category; n represents the number of the single batteries corresponding to the fault category; f represents the frequency of the fault category in a preset diagnosis period; n represents the number of the types of the fault categories, and correspondingly, the value of i is a natural integer between 1 and n; dmedianA difference value representing an insulation value of the battery pack for a current diagnostic period and an insulation value of the battery pack for at least one historical diagnostic period; a. themedianAn insulation value of the battery pack representing a current diagnostic period; k is an adjusting factor used for adjusting the insulation abnormal ratio of the battery pack; m is a theoretical fault value corresponding to the faults of all the battery monomers in the battery pack; q is a constant.
Further, the apparatus for detecting leakage of a battery pack may further include: a fault notification module;
the fault notification module is used for determining the leakage reason of the battery pack according to the historical driving data of the vehicle under the condition that the battery pack leaks; and sending the fault evaluation result of the vehicle and the leakage reason to a vehicle-mounted terminal of the vehicle.
Further, the apparatus for detecting leakage of a battery pack may further include: a maintenance reminding module;
the maintenance reminding module is used for determining the latest time of battery maintenance of the vehicle according to the battery pack data of the vehicle; and if the time interval between the latest time of the battery maintenance and the current time is greater than the preset time interval, sending a reminding message of the battery maintenance to a vehicle-mounted terminal of the vehicle.
Further, the apparatus for detecting leakage of a battery pack may further include: a data judgment module;
and the data judgment module is used for judging whether the battery pack data is accurate or not according to a preset judgment rule before performing characteristic analysis on the battery pack data, and deleting the battery pack data if the battery pack data is inaccurate.
Optionally, the battery pack data further includes at least one of historical driving data of the vehicle, charging data of the vehicle, voltage data of the battery pack, temperature data of the battery pack, a number of the vehicle, and acquisition time of the battery pack data.
The device for detecting the leakage of the battery pack provided by the embodiment can be applied to the method for detecting the leakage of the battery pack provided by any embodiment, and has corresponding functions and beneficial effects.
EXAMPLE five
Fig. 5 is a block diagram of an electronic device adapted to implement a method of battery pack leak detection of an embodiment of the present application, and fig. 5 shows a block diagram of an exemplary electronic device suitable for implementing an embodiment of the present application. The electronic device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application. The electronic device can be a smart phone, a tablet computer, a notebook computer, a vehicle-mounted terminal, a wearable device and the like.
As shown in fig. 5, the electronic device 500 is embodied in the form of a general purpose computing device. The components of the electronic device 500 may include, but are not limited to: one or more processors or processing units 516, a memory 528, and a bus 518 that couples the various system components including the memory 528 and the processing unit 516.
Bus 518 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, micro-channel architecture (MAC) bus, enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
Electronic device 500 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by electronic device 500 and includes both volatile and nonvolatile media, removable and non-removable media.
Memory 528 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)530 and/or cache memory 532. The electronic device 500 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 534 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 5, and commonly referred to as a "hard drive"). Although not shown in FIG. 5, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 518 through one or more data media interfaces. Memory 528 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the application.
A program/utility 540 having a set (at least one) of program modules 542, including but not limited to an operating system, one or more application programs, other program modules, and program data, may be stored in, for example, the memory 528, each of which examples or some combination may include an implementation of a network environment. Program modules 542 generally perform the functions and/or methods of the embodiments described herein.
The electronic device 500 may also communicate with one or more external devices 514 (e.g., keyboard, pointing device, display 524, etc.), with one or more devices that enable a user to interact with the electronic device 500, and/or with any devices (e.g., network card, modem, etc.) that enable the electronic device 500 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 522. Also, the electronic device 500 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via the network adapter 520. As shown in FIG. 5, the network adapter 520 communicates with the other modules of the electronic device 500 via the bus 518. It should be appreciated that although not shown in FIG. 5, other hardware and/or software modules may be used in conjunction with the electronic device 500, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 516 executes various functional applications and data processing by executing programs stored in the memory 528, for example, to implement the method for detecting battery pack leakage provided in any embodiment of the present application.
EXAMPLE six
A sixth embodiment of the present application further provides a computer-readable storage medium, on which a computer program (or referred to as computer-executable instructions) is stored, where the computer program, when executed by a processor, can be used to perform the method for detecting battery pack leakage provided in any of the above-mentioned embodiments of the present application.
The computer storage media of the embodiments of the present application may take any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for embodiments of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present application and the technical principles employed. It will be understood by those skilled in the art that the present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the application. Therefore, although the embodiments of the present application have been described in more detail through the above embodiments, the embodiments of the present application are not limited to the above embodiments, and many other equivalent embodiments may be included without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the appended claims.

Claims (10)

1. A method of battery pack leak detection, the method comprising:
acquiring battery pack data of a vehicle;
performing characteristic analysis on the battery pack data, and determining whether the battery pack data is fault data according to a characteristic analysis result;
determining the fault category of the battery pack data under the condition of fault data, and determining the frequency of the fault category appearing in a preset diagnosis period;
determining the insulation abnormal ratio of the battery pack according to the insulation value of the battery pack in the current diagnosis period and the insulation value of the battery pack in at least one historical diagnosis period;
and performing fault evaluation on the battery pack data according to the fault category, the frequency of the fault category appearing in a preset diagnosis period and the insulation abnormal ratio of the battery pack, and determining whether the battery pack leaks according to a fault evaluation result.
2. The method according to claim 1, wherein the fault evaluation of the battery pack data according to the fault category, the frequency of occurrence of the fault category within a preset diagnosis period, and the insulation abnormality ratio of the battery pack comprises:
carrying out accumulation summation according to the fault category, the frequency of the fault category appearing in a preset diagnosis period and the number of the single batteries corresponding to the fault category, and determining a fault value corresponding to the battery pack; the battery pack comprises at least one battery cell;
and summing the fault numerical value and the insulation abnormal ratio of the battery pack, and then carrying out normalization processing on the fault numerical value and the insulation abnormal ratio to obtain a fault evaluation result.
3. The method of claim 2, wherein the fault assessment result is determined by the formula:
Figure FDA0003141108490000021
wherein score represents the failure evaluation result; c represents the weight corresponding to the fault category; n represents the number of the single batteries corresponding to the fault category; f represents the frequency of the fault category in a preset diagnosis period; n represents the number of the types of the fault categories, and correspondingly, the value of i is a natural integer between 1 and n; dmedianA difference value representing an insulation value of the battery pack for a current diagnostic period and an insulation value of the battery pack for at least one historical diagnostic period; a. themedianAn insulation value of the battery pack representing a current diagnostic period; k is an adjusting factor used for adjusting the insulation abnormal ratio of the battery pack; m is a theoretical fault value corresponding to the faults of all the battery monomers in the battery pack; q is a constant.
4. The method of claim 1, further comprising, after determining whether the battery pack is leaking according to the fault assessment result:
under the condition that the battery pack leaks, determining the leakage reason of the battery pack according to historical driving data of the vehicle;
and sending the fault evaluation result of the vehicle and the leakage reason to a vehicle-mounted terminal of the vehicle.
5. The method of claim 1, further comprising:
determining the latest time for battery maintenance of a vehicle according to battery pack data of the vehicle;
and if the time interval between the latest time of the battery maintenance and the current time is greater than the preset time interval, sending a reminding message of the battery maintenance to a vehicle-mounted terminal of the vehicle.
6. The method of claim 1, further comprising, prior to performing a characterization analysis on the battery pack data:
and judging whether the battery pack data is accurate or not according to a preset judgment rule, and deleting the battery pack data if the battery pack data is not accurate.
7. The method of claim 1, wherein the battery pack data further comprises at least one of historical driving data of a vehicle, charging data of a vehicle, voltage data of a battery pack, temperature data of a battery pack, a number of a vehicle, and a collection time of battery pack data.
8. An apparatus for battery pack leak detection, the apparatus comprising:
the data acquisition module is used for acquiring battery pack data of the vehicle;
the characteristic analysis module is used for carrying out characteristic analysis on the battery pack data and determining whether the battery pack data is fault data or not according to a characteristic analysis result;
the first determining module is used for determining the fault category of the battery pack data under the condition of fault data and determining the frequency of the fault category appearing in a preset diagnosis period;
the second determination module is used for determining the insulation abnormal ratio of the battery pack according to the insulation value of the battery pack in the current diagnosis period and the insulation value of the battery pack in at least one historical diagnosis period;
and the fault determining module is used for performing fault evaluation on the battery pack data according to the fault type, the frequency of the fault type occurring in a preset diagnosis period and the insulation abnormity ratio of the battery pack, and determining whether the battery pack leaks according to a fault evaluation result.
9. An electronic device, characterized in that the electronic device comprises:
one or more processors;
storage means for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement a method of battery pack leak detection as recited in any of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method of battery pack leak detection according to any one of claims 1 to 7.
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