CN117805663B - Battery testing method, device, equipment and medium based on running state - Google Patents
Battery testing method, device, equipment and medium based on running state Download PDFInfo
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Abstract
The application relates to the field of battery fault detection, in particular to a battery test method, device, equipment and medium based on an operation state, wherein the method comprises the following steps: when a fault signal corresponding to a preset running state is detected, determining a plurality of first running data corresponding to the fault signal; acquiring second operation data corresponding to the fault signal, and determining a second operation data difference value based on the second operation data and standard second operation data; determining a plurality of associated first operational data from all the first operational data based on the second operational data difference and all the first operational data; acquiring time sequence attribute values corresponding to all the associated first operation data respectively, wherein the time sequence attribute values represent the change of the amplitude values of the associated first operation data; and determining fault information of the battery in a preset running state based on the second running data, all the related first running data and the corresponding time sequence attribute values. The application has the effect of improving the fault detection accuracy.
Description
Technical Field
The present application relates to the field of battery fault detection technology, and in particular, to a method, an apparatus, a device, and a medium for testing a battery based on an operating state.
Background
Solid Oxide Fuel Cells (SOFCs) are a new energy power supply material, which is generated as the operation of the solid oxide fuel cells is carried out with the advent of environmental friendly slogans; the SOFC not only has the characteristic of environmental friendliness, but also has different working states, namely a reverse running state and a forward running state, and when the SOFC is in the forward running state, the SOFC has the function of converting chemical energy into electric energy; when the SOFC is in a reverse running state, the SOFC functions as an electrolytic cell of the water electrolysis hydrogen production device; in the SOFC operation process, in order to ensure the SOFC operation stability, the SOFC needs to be subjected to fault detection in real time so as to reduce the fault occurrence rate.
The related art acquires voltage data or current data of the SOFC cell, and determines that the cell has a fault when the current data or the voltage data of the SOFC changes, however, when a fault exists in a detection line, for example, a problem that noise interference exists in the circuit or a transient error exists in a sensor may also cause the current data or the voltage data to change, at this time, the SOFC without the fault is determined to have the fault, and therefore, in the related art, the accuracy of determining that the SOFC has the fault is poor only according to a certain item of data.
Disclosure of Invention
In order to improve fault detection accuracy, the application provides a battery test method, device, equipment and medium based on an operation state.
In a first aspect, the present application provides a battery testing method based on an operating state, which adopts the following technical scheme:
a battery testing method based on operating conditions, comprising:
When a fault signal corresponding to a preset operation state is detected, determining a plurality of first operation data corresponding to the fault signal, wherein the preset operation state represents the operation state of a battery;
Acquiring second operation data corresponding to the fault signal, and determining a second operation data difference value based on the second operation data and standard second operation data, wherein the second operation data difference value represents an abnormality degree;
Determining a plurality of associated first operational data from all the first operational data based on the second operational data difference and all the first operational data;
Acquiring time sequence attribute values corresponding to all the associated first operation data, wherein the time sequence attribute values represent the change of the amplitude values of the associated first operation data;
determining fault information of the battery in the preset operation state based on the second operation data, all the associated first operation data and the time sequence attribute values corresponding to the second operation data, wherein the fault information comprises: there is a fault or no fault.
The present application may be further configured in a preferred example to determine fault information of the battery in the preset operation state based on the second operation data, all the associated first operation data, and the respective corresponding time sequence attribute values, including:
Acquiring environment information, and determining initial associated first operation data according to the environment information and time sequence attribute values corresponding to all the associated first operation data;
determining first components corresponding to the second operation data based on the second operation data, and determining respective second components based on all the initial association first operation data;
Determining a plurality of target associated first operation data based on the first assembly, all the initial associated first operation data and the corresponding second assemblies;
And acquiring first historical data corresponding to all the target associated first operation data, and determining fault information of the battery in the preset operation state according to all the first historical data.
The present application may be further configured in a preferred example, wherein the determining a plurality of target associated first operation data based on the first component, all the initial associated first operation data, and the respective corresponding second components includes:
Acquiring first position and first function information of the first component, and acquiring second positions and second function information corresponding to all second components;
determining, for each of the second components, an association value from the first location, the first function information, the second location, and the second function information;
Determining a plurality of target associated first operation data based on all the initial associated first operation data, the associated values corresponding to the initial associated first operation data and a preset associated value threshold value,
And the association value of the target associated first operation data is larger than the preset association value threshold.
The present application may be further configured in a preferred example, wherein the determining the association value according to the first location, the first function information, the second location, and the second function information includes:
Determining a structural association value based on the first location and the second location;
Determining a function association value based on the first function information and the second function information;
Acquiring a first weight value corresponding to the structural association value and a second weight value corresponding to the functional association value;
The association value is determined based on the structural association value, the first weight value, the functional association value, and the second weight value.
The present application may be further configured in a preferred example, wherein the determining, based on the second operation data difference value and all the first operation data, a plurality of associated first operation data from all the first operation data includes:
Obtaining second historical data of the second operation data difference value, wherein the second historical data comprises: historical first operational data and first frequency of occurrence;
Determining target historical first operation data from all the historical first operation data based on a preset minimum occurrence frequency and the first occurrence frequency, wherein the first occurrence frequency of the target historical first operation data is not greater than the preset minimum occurrence frequency;
and matching all the first operation data with the target historical first operation data to determine initial first operation data, wherein the initial first operation data represents the same data as the target historical first operation data.
In a preferred example, the method may further include, if there is a fault, determining fault information of the battery in the preset operation state based on the second operation data, all the associated first operation data, and the respective corresponding time sequence attributes, and then further including:
Determining the fault type of the battery in the preset running state, and acquiring a second occurrence frequency of the fault type in a first preset duration;
Determining a target maintenance waiting time length corresponding to the fault type according to the fault type and the second occurrence frequency;
acquiring an idle maintenance period of a maintenance person, and determining a target maintenance person according to the idle maintenance period and the target maintenance waiting time;
And generating a maintenance signal based on the fault type and the target maintenance personnel, and sending the maintenance signal to the target maintenance personnel equipment so as to carry out maintenance reminding.
The present application may be further configured in a preferred example, where the determining, based on the fault type and the second occurrence frequency, a target maintenance waiting duration corresponding to the fault type includes:
Acquiring an influence attribute of the fault type, and determining a first sub-target maintenance waiting time length according to the influence attribute, wherein the influence attribute characterizes the influence degree generated by the fault type;
determining a second sub-target maintenance waiting time length corresponding to the second occurrence frequency according to a preset corresponding relation between the occurrence frequency and the maintenance waiting time length and the second occurrence frequency;
And determining the target maintenance waiting time corresponding to the fault type according to the first sub-target maintenance waiting time and the second sub-target maintenance waiting time.
In a second aspect, the present application provides a battery testing device based on an operating state, which adopts the following technical scheme:
a battery testing device based on an operating state, comprising:
The first operation data determining module is used for determining a plurality of first operation data corresponding to a fault signal when the fault signal corresponding to a preset operation state is detected, wherein the preset operation state represents the operation state of the battery;
The second operation data acquisition module is used for acquiring second operation data corresponding to the fault signal, determining a second operation data difference value based on the second operation data and standard second operation data, and representing the degree of abnormality;
The first operation data correlation determination module is used for determining a plurality of first operation data correlation from all the first operation data based on the second operation data difference value and all the first operation data;
the time sequence attribute value acquisition module is used for acquiring time sequence attribute values corresponding to all the associated first operation data respectively, and the time sequence attribute values represent the change of the amplitude values of the associated first operation data;
The fault information determining module is configured to determine fault information of the battery in the preset operation state based on the second operation data, all the associated first operation data, and the corresponding time sequence attribute values, where the fault information includes: there is a fault or no fault.
In a third aspect, the present application provides an electronic device, which adopts the following technical scheme:
At least one processor;
A memory;
At least one application program, wherein the at least one application program is stored in the memory and configured to be executed by the at least one processor, the at least one application program configured to: performing the run state based battery test method of any one of the first aspects.
In a fourth aspect, the present application provides a computer readable storage medium, which adopts the following technical scheme:
A computer readable storage medium having stored thereon a computer program which, when executed in a computer, causes the computer to perform the run state based battery testing method according to any of the first aspects.
In summary, the application has the following beneficial technical effects:
When a fault signal is detected, determining a plurality of corresponding first operation data directly according to the fault signal so as to combine the first operation data for common judgment; acquiring second operation data corresponding to the fault signal, and determining second operation data difference values, wherein different second operation data difference values correspond to batteries with different abnormal degrees, and the batteries with different abnormal degrees may correspond to different first operation data, so that associated first operation data are determined according to the second operation data difference values and all the first operation data, and the accuracy of the associated first operation data is effectively improved; acquiring time sequence attribute values corresponding to all the associated first operation data respectively so as to determine the change condition of the associated first operation data; determining fault information of the battery in a preset state by combining the related first operation data and the change condition of the related first operation data; compared with the prior art that the battery fault information is determined only according to a certain item of data, the application combines the running state of the battery, the related first running data under the running state, the change condition of the related first running data and the like to achieve the purpose of determining the battery fault information, so that the technical effect of determining the battery fault information accuracy is effectively improved, and the technical problem of poor battery fault information accuracy in the prior art is solved.
Drawings
Fig. 1 is a schematic flow chart of a battery testing method based on an operation state according to an embodiment of the present application.
Fig. 2 is a flowchart of a method for determining battery fault information according to an embodiment of the present application.
Fig. 3 is a schematic structural diagram of a battery detection device based on an operation state according to an embodiment of the present application.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to fig. 1 to 4.
The present embodiment is merely illustrative of the present application and is not intended to limit the present application, and those skilled in the art, after having read the present specification, may make modifications to the present embodiment without creative contribution as necessary, but are protected by patent laws within the scope of the present application.
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application are clearly and completely described, 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 made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In addition, the term "and/or" herein is merely an association relationship describing an association object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone. In this context, unless otherwise specified, the term "/" generally indicates that the associated object is an "or" relationship.
Embodiments of the application are described in further detail below with reference to the drawings.
The embodiment of the application provides a battery testing method based on an operation state, which is executed by electronic equipment, wherein the electronic equipment can be a server or terminal equipment, and the server can be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server for providing cloud computing service. The terminal device may be a smart phone, a tablet computer, a notebook computer, a desktop computer, or the like, but is not limited thereto, and the terminal device and the server may be directly or indirectly connected through a wired or wireless communication manner, as shown in fig. 1, the method includes steps S101, S102, S103, S104, and S105, where:
step S101: when a fault signal corresponding to a preset operation state is detected, determining a plurality of first operation data corresponding to the fault signal, wherein the preset operation state represents the operation state of the battery.
Specifically, the preset operating state includes: the SOFC is in a forward running state or a reverse running state, wherein when the SOFC is in the forward running state, the SOFC has the function of converting chemical energy into electric energy, and a corresponding fault signal can be generated when the electric energy conversion efficiency is abnormal, namely the electric energy conversion efficiency is lower; when the SOFC is in a reverse running state, the SOFC bears the function of the solid oxide electrolytic cell, converts the surplus electric energy into hydrogen, and the fault signal corresponds to the occurrence of abnormal hydrogen conversion quantity, namely insufficient hydrogen conversion quantity. The plurality of first operation data can be determined according to the corresponding relation, the fault model is matched with the corresponding relation, and then the plurality of first operation data can be determined, wherein the corresponding relation is set by a technician according to working experience and is input into the electronic equipment in advance. It will be appreciated that the above-mentioned low power conversion efficiency or abnormal hydrogen conversion may be caused by detection by a sensor, or may be caused by failure of the SOFC itself. It may be understood that the first operation data may be voltage data, current data, or internal resistance data of the battery, etc., which is not limited in the embodiment of the present application; and the first operation data can be the same or different in different operation states, and the first operation data corresponding to the fault signal in the operation state is determined, so that the data calculation amount is reduced through targeted analysis, and the accuracy of the calculation result is further improved. If the preset operation state is a forward operation state, the corresponding first operation data may be voltage data, current data or oxidant flow data; when the preset operation state is a reverse operation state, the corresponding first operation data may be battery temperature data, voltage data, current data, charge and discharge data, or the like.
Step S102: and acquiring second operation data corresponding to the fault signal, and determining a second operation data difference value based on the second operation data and the standard second operation data, wherein the second operation data difference value represents the degree of abnormality.
Specifically, when the fault signal is generated when the electric energy conversion efficiency is abnormal, the corresponding second operation data is the electric energy conversion efficiency; when the fault signal is generated when the hydrogen conversion amount is abnormal, the corresponding second operation data is the hydrogen conversion amount; the second operation data is monitored in real time by the corresponding sensor and is uploaded to the electronic equipment. Standard second operation data is empirically set by a technician and is input into the electronic device in advance, and the second operation data difference value=. The degree of abnormality of the SOFC is greater as the difference in the second operation data increases.
Step S103: based on the second operational data difference and all of the first operational data, a number of associated first operational data is determined from all of the first operational data.
In particular, a number of associated first operational data may be determined from the second historical data of the second operational data differences and all of the first operational data, and reference may be made to the following embodiments for specific implementation. It can be appreciated that the first historical data has a higher referenceable degree, so that a plurality of associated first operation data are determined according to the first historical data, so that the accuracy of the associated first operation data is effectively improved.
Step S104, acquiring time sequence attribute values corresponding to all the associated first operation data, wherein the time sequence attribute values represent the change of the amplitude values of the associated first operation data.
Specifically, the method can be obtained from an operation database, wherein the operation database comprises a plurality of associated first operation data and time sequence attribute values corresponding to the first operation data; the determining of each timing attribute value associated with the first operational data includes: acquiring amplitude change frequency and amplitude change value of associated first operation data, determining a first sub-time attribute value according to the corresponding relation between the amplitude change frequency and the first sub-time attribute value, determining a second sub-time attribute value according to the corresponding relation between the amplitude change value and the second sub-time attribute value, determining the sum of time sequence attribute values of the first sub-time attribute value and the second sub-time attribute value, and taking the sum as the time sequence attribute value corresponding to the associated first operation data. The corresponding relation between the amplitude change frequency and the first sub-time attribute value, and the corresponding relation between the amplitude change value and the second sub-time attribute value are all set by a technician according to working experience and are input into the electronic equipment in advance. The amplitude change value is determined based on the amplitude corresponding to the current moment and the preset amplitude, and the preset amplitude is not limited in the embodiment of the application.
Step S105, determining fault information of the battery in a preset operation state based on the second operation data, all the related first operation data and the corresponding time sequence attribute values, wherein the fault information comprises: there is a fault or no fault.
In particular, the specific implementation of determining fault information from the second operational data, the associated first operational data and the timing attribute value may be referred to the following embodiments. It can be understood that in the process of determining the fault information, the related first operation data is taken as a reference, and the fault information of the battery in the preset operation state is determined by combining the time sequence attribute value related to the first operation data, so that the accuracy of determining the fault information is effectively improved.
In the embodiment of the application, when the fault signal is detected, a plurality of corresponding first operation data are directly determined according to the fault signal so as to be judged together with the first operation data; acquiring second operation data corresponding to the fault signal, and determining second operation data difference values, wherein different second operation data difference values correspond to batteries with different abnormal degrees, and the batteries with different abnormal degrees may correspond to different first operation data, so that associated first operation data are determined according to the second operation data difference values and all the first operation data, and the accuracy of the associated first operation data is effectively improved; acquiring time sequence attribute values corresponding to all the associated first operation data respectively so as to determine the change condition of the associated first operation data; determining fault information of the battery in a preset state by combining the related first operation data and the change condition of the related first operation data; compared with the prior art that the battery fault information is determined only according to a certain item of data, the application combines the running state of the battery, the related first running data under the running state, the change condition of the related first running data and the like to achieve the purpose of determining the battery fault information, so that the technical effect of determining the battery fault information accuracy is effectively improved, and the technical problem of poor battery fault information accuracy in the prior art is solved.
As shown in fig. 2, a possible implementation manner of the embodiment of the present application is a flowchart of a method for determining battery fault information provided by the embodiment of the present application, step S105 determines fault information of a battery in a preset operation state based on second operation data, all associated first operation data and respective corresponding time sequence attribute values, and includes steps S1051-S1054:
Step S1051: acquiring environment information, and determining initial associated first operation data according to the environment information and time sequence attribute values corresponding to all the associated first operation data;
Step S1052: determining first components corresponding to the second operation data based on the second operation data, and determining respective second components based on all initial associated first operation data;
step S1053: determining a plurality of target associated first operation data based on the first assembly, all initial associated first operation data and the corresponding second assemblies;
Step S1054: and acquiring first historical data corresponding to each of the first operation data associated with all the targets, and determining fault information of the battery in a preset operation state according to all the first historical data.
Specifically, the environmental information includes: ambient temperature data or humidity data may be monitored by corresponding sensors and uploaded to the electronic device. The specific process of determining the initial association first operational data according to the environmental information and the time sequence attribute value comprises the following steps: judging whether the change environment data exists, if so, acquiring a change period corresponding to the change environment data, acquiring associated first operation data without data change in the change period, and determining the associated first operation data without data change as initial associated first operation data. It will be appreciated that during operation of the battery, an excessively high ambient temperature, an excessively low ambient temperature, an excessively high humidity or an excessively low humidity may affect the initial associated first operation data, i.e. there is a change in a part of the associated first operation data due to an environmental factor rather than a fault factor, and determining the fault information of the battery according to the above-mentioned associated first operation data that changes due to the environmental factor may result in determining erroneous fault information, so that the associated first operation data that is not changed due to the environmental factor, i.e. the self-fault factor, is determined as the initial associated first operation data. The first component may be determined according to the first correspondence and the second component may be determined according to the second correspondence; the first corresponding relation is the corresponding relation between the second operation data and the first component, and the second corresponding relation is the corresponding relation of the first operation data and the second component which are initially associated. The first corresponding relation and the second corresponding relation are determined by a technician according to a plurality of historical data, wherein the establishing process of the first corresponding relation comprises the following steps: acquiring a plurality of historical second operation data in the same operation state as the preset operation state, matching the second operation data with the plurality of historical second operation data to determine target historical second operation data, acquiring historical first components corresponding to all the target historical second operation data, determining third occurrence frequencies corresponding to all the historical first components, and taking the historical first component with the highest third occurrence frequency as the first component of the second operation data. The process of establishing the second corresponding relationship is the same as the process of establishing the first corresponding relationship, and the embodiment of the application is not repeated, and the first component and the second component are respectively corresponding component names. For a specific implementation of determining the target associated first operational data from the first component, the initial associated first operational data and the second component, reference may be made to the following embodiments. The first history data may be obtained from a preset history database, where the first history data includes: the method comprises the steps of determining an abnormal interval period according to historical abnormal frequency and corresponding abnormal period, comparing the abnormal interval period with a preset abnormal interval period to determine the quantity of target associated first operation data of which the abnormal interval period is smaller than the preset abnormal interval period, and determining that fault information of a battery is fault if the quantity is larger than a preset quantity threshold; otherwise, determining that no fault exists, and limiting the preset abnormal interval period and the preset quantity threshold value according to the embodiment of the application. It will be appreciated that when the target-associated first operational data is frequently abnormal, the SOFC has a high probability of abnormality and is therefore determined to be faulty at this time. And the historical abnormal frequency represents the frequency corresponding to the first operation data associated with the target when the first operation data is not the standard value.
In the embodiment of the application, environment information is acquired, and initial associated first operation data is determined according to the environment information and a time sequence attribute value, so that the associated first operation data which is not influenced by environmental factors is taken as a reference; determining a first component of second operation data and a second component of initial association first operation data, and determining target association first operation data according to the first component, the initial association first operation data and the second component; and then acquiring the first historical data corresponding to the target associated first operation data, and taking the first historical data as a reference to effectively improve the accuracy of determining the fault information.
In one possible implementation manner of the embodiment of the present application, step S105 determines, based on the first component, all the initial associated first operation data and the respective corresponding second components, a plurality of target associated first operation data, including:
acquiring first position and first function information of a first component, and acquiring second positions and second function information corresponding to all second components;
determining, for each second component, an association value according to the first location, the first function information, the second location, and the second function information;
And determining a plurality of targets to be associated with the first operation data based on all the initial associated first operation data, the corresponding associated values and the preset associated value threshold, wherein the associated value of the targets to be associated with the first operation data is larger than the preset associated value threshold.
Specifically, the first location, the second location, the first function information, and the second function information may be acquired from a location information base and a function information base, respectively. For a specific implementation of determining the association value according to the first location, the first function, the second location and the second function information, reference may be made to the following embodiments. It can be appreciated that the closer the location between the components, the higher the degree of association between the second operational data and the initially associated first operational data, and the higher the degree of association between the first function and the second function, the higher the degree of association between the second operational data and the initially associated first operational data, and thus the association value is determined from the location dimension and the function dimension, so as to effectively improve the accuracy of the association value determination. The preset association value threshold is set by a technician according to working experience and is input into the electronic equipment in advance. And comparing the association value with a preset association value threshold value, further determining a target association value larger than the preset association value threshold value, and determining initial association first operation data corresponding to the target association value as target association first operation data. It can be understood that the association degree of the initial association first operation data and the second operation data corresponding to the target association value is higher, at this time, the initial association first operation data with the higher association degree is taken as a reference, and the fault information is determined, so that the accuracy of determining the fault information can be effectively improved.
In the embodiment of the application, the first position, the first function information, the second position and the second function information are acquired, the association value is determined, and then the target association first operation data is determined according to the association value, the initial association first operation data and the preset association value threshold value, so that the target association first operation data with higher association degree with the second operation data is used for effectively improving the accuracy of determining the target association first operation data.
In one possible implementation manner of the embodiment of the present application, step S105 determines an association value according to the first location, the first function information, the second location and the second function information, including:
Determining a structural association value based on the first location and the second location;
Determining a function association value based on the first function information and the second function information;
Acquiring a first weight value corresponding to the structural association value and a second weight value corresponding to the functional association value;
the association value is determined based on the structural association value, the first weight value, the functional association value, and the second weight value.
Specifically, a position difference value is determined according to a first position and a second position, a structure association value corresponding to the position difference value is determined according to a corresponding relation between the position difference value and the structure association value, the corresponding relation between the position difference value and the structure association value is set by a technician according to working experience, and in the corresponding relation, the structure association value is increased along with the decrease of the position difference value. The specific process of determining the function association value according to the first function information and the second function information comprises the following steps: and acquiring a plurality of preset second functions of the first function information, and matching the second functions with the plurality of preset second functions to determine a target second function, namely a second function with an association relation with the first function. Acquiring the number of the second functions, and determining a function association value according to the corresponding relation between the number and the function association value; with the increase of the number of the second functions, the function association value is increased, and the method and the device do not limit the establishment process of the corresponding relation between the number and the function association value, so that the user can set the device and the method. The first weight value and the second weight value may be set by a technician according to working experience, and the embodiment of the present application is not limited. It can be understood that in the SOFC operation process, the operation data with the structural association relationship and the operation data with the functional association relationship have different effects on the SOFC, so that the first weight value and the second weight value need to be acquired to perform targeted calculation. The correlation value can be determined according to a calculation formula of the correlation value, wherein the calculation formula is as follows: association value = structure association value x first weight value + function association value x second weight value.
In the embodiment of the application, the structural association value is determined according to the first position and the second position to determine the association value from the structural dimension, and the functional association value is determined according to the first functional information and the second functional information to determine the association value from the functional dimension.
In one possible implementation manner of the embodiment of the present application, step S103 determines, based on the second operation data difference value and all the first operation data, a plurality of associated first operation data from all the first operation data, including:
Obtaining second historical data of a second operation data difference value, wherein the second historical data comprises: historical first operational data and first frequency of occurrence;
Determining target historical first operation data from all the historical first operation data based on a preset minimum occurrence frequency and a first occurrence frequency, wherein the first occurrence frequency of the target historical first operation data is not greater than the preset minimum occurrence frequency;
and matching all the first operation data with the target historical first operation data, and determining initial first operation data, wherein the initial first operation data represents the same data as the target historical first operation data.
Specifically, second historical data for the second operational data difference may be obtained from a historical database. The preset minimum occurrence frequency is set by a technician according to working experience, in the embodiment of the application, the preset minimum occurrence frequency is preferably 1, and then the first occurrence frequency of the historical first operation data is compared with the preset minimum occurrence frequency to determine the target historical first operation data. It is understood that when the first occurrence frequency of any one of the historical first operation data is not greater than the preset minimum occurrence frequency, it indicates that the occurrence of the historical first operation data may be accidental, and thus the historical first operation data greater than the preset minimum occurrence frequency is determined as the target historical first operation data. And determining initial first operation data through a matching algorithm, wherein the embodiment of the application does not limit the specific implementation process of the initial first operation data, and the user can set the initial first operation data by himself.
In the embodiment of the application, the historical data of the second operation data difference value is obtained, and then the first operation data of the target history is determined according to the preset minimum occurrence frequency and the first occurrence frequency so as to reduce accidental data; and the first operation data and the target historical first operation data are matched so as to determine the initial first operation data with the association relation with the second operation data, so that the accuracy of determining the initial first operation data is effectively improved.
In one possible implementation manner of the embodiment of the present application, if there is a fault, step S105 further includes, after determining fault information of the battery in the preset state based on the second operation data, all the associated first operation data, and the corresponding time sequence attribute values:
Determining the fault type of the battery in a preset state, and acquiring a second occurrence frequency of the fault type in a first preset time period;
Determining a target maintenance waiting time length corresponding to the fault type according to the fault type and the second occurrence frequency;
Acquiring an idle maintenance period of maintenance personnel, and determining a target maintenance personnel according to the idle maintenance period and the target maintenance waiting time;
and generating a maintenance signal based on the fault type and the target maintenance personnel and sending the maintenance signal to the target maintenance personnel equipment to carry out maintenance reminding.
Specifically, the fault type can be determined according to a preset corresponding relation between the fault signal and the fault type, wherein the corresponding relation is set by a technician according to working experience; the embodiment of the application does not limit the first preset time length and can be set by oneself; and each time the fault type occurs, the electronic equipment correspondingly records so as to obtain a second occurrence frequency corresponding to the fault type. Matching the fault type with a plurality of preset corresponding relations to obtain a corresponding relation of the fault type, wherein the corresponding relation is a corresponding relation of a second occurrence frequency and a waiting maintenance duration under the fault type, and the corresponding relation is set by a technician according to working experience. It will be appreciated that the impact of different fault types on SOFCs in different operating conditions is different, and that the negative impact on SOFCs increases with increasing repair waiting time, so that it is necessary to determine a target repair waiting time corresponding to the fault type to reduce the impact on SOFCs. The specific implementation manner of determining the target maintenance waiting time according to the fault type and the second occurrence frequency can refer to the following embodiments. The idle repair period may be determined from a repair person information repository in which a plurality of repair person identifications and respective corresponding idle repair periods are stored. The current time is obtained, the latest maintenance period is determined according to the current time and the target maintenance waiting time, all the idle maintenance periods and the latest maintenance period are matched, and maintenance personnel corresponding to the idle maintenance period earlier than the latest maintenance period are determined and used as target maintenance personnel. The number of the target maintenance personnel can be one or a plurality of the target maintenance personnel, and the embodiment of the application is not limited. The maintenance signal can be in a text form or a voice form and then is sent, and when the number of the target maintenance personnel is multiple, the selection signal of the target maintenance personnel is received, namely whether the target maintenance personnel automatically select to maintain or not is determined, so that the unique target maintenance personnel are determined.
In the embodiment of the application, the fault type of the battery is determined, the second occurrence frequency of the fault type is obtained, the influence degree of different fault types on the battery is different, the damage degree of the battery is more serious as the second occurrence frequency increases, and the corresponding maintenance waiting time period is shortened, so that the target maintenance waiting time period is determined according to the fault type and the second occurrence frequency, and the accuracy of determining the target maintenance waiting time period is effectively improved; and acquiring an idle maintenance period of the maintenance personnel, and determining a target maintenance personnel according to the idle maintenance period and the target maintenance waiting time so that the target maintenance personnel can maintain the battery in time, and generating a maintenance signal according to the fault type and the target maintenance personnel to remind the battery, thereby effectively reducing the maintenance waiting time of the battery and avoiding the serious damage of the battery.
In one possible implementation manner of the embodiment of the present application, step S105 determines, based on the fault type and the second occurrence frequency, a target maintenance waiting duration corresponding to the fault type, including:
Acquiring an influence attribute of the fault type, determining a first sub-target maintenance waiting time according to the influence attribute, and representing the influence degree generated by the fault type by the influence attribute;
Determining a second sub-target maintenance waiting time length corresponding to the second occurrence frequency according to the corresponding relation between the preset occurrence frequency and the maintenance waiting time length and the second occurrence frequency;
and determining the target maintenance waiting time corresponding to the fault type according to the first sub-target maintenance waiting time and the second sub-target maintenance waiting time.
Specifically, it can be understood that when the SOFC fails, normal operation of other associated devices may be affected, and different failure types of the SOFC affect different numbers of associated devices, so that in the embodiment of the present application, the extent of the influence is increased as the number increases. The influence attribute of each fault type is set by a technician according to working experience and is input into the electronic equipment in advance. The first sub-target maintenance waiting time length corresponding to the influence attribute can be determined according to the corresponding relation between the influence attribute and the maintenance waiting time length, and the corresponding relation is set by a technician according to working experience and is input into the electronic equipment; as the degree of influence increases, the first sub-target maintenance waiting period gradually decreases. The preset correspondence between the occurrence frequency and the maintenance waiting time is set by a technician according to working experience and is input into the electronic equipment in advance. Target maintenance waiting time = first sub-target maintenance waiting time + second sub-target maintenance waiting time.
In the embodiment of the application, the influence of different fault types on the battery-associated device is different, so that the first sub-target maintenance waiting time length is determined according to the influence attribute, and the accuracy of the first sub-target maintenance waiting time length is effectively improved; the increase of the occurrence frequency shows that the fault of the battery is more serious, so that the second sub-target maintenance waiting time is determined according to the preset occurrence frequency and the second occurrence frequency, and the accuracy of the second sub-target maintenance waiting time is effectively improved; and obtaining the target maintenance waiting time with higher accuracy according to the accurate first sub-target maintenance waiting time and the accurate second sub-target maintenance waiting time.
The above embodiments describe a battery testing method based on an operation state from the viewpoint of a method flow, and the following embodiments describe a battery testing device based on an operation state from the viewpoint of a virtual module or a virtual unit, specifically the following embodiments.
The embodiment of the application provides a battery testing device based on an operation state, as shown in fig. 3, the battery testing device based on the operation state specifically may include:
a first operation data determining module 201, configured to determine, when a fault signal corresponding to a preset operation state is detected, a plurality of first operation data corresponding to the fault signal, where the preset operation state represents an operation state of the battery;
A second operation data obtaining module 202, configured to obtain second operation data corresponding to the fault signal, and determine a second operation data difference value based on the second operation data and the standard second operation data, where the second operation data difference value represents an abnormality degree;
an associated first operation data determining module 203, configured to determine a number of associated first operation data from all the first operation data based on the second operation data difference value and all the first operation data;
a time sequence attribute value obtaining module 204, configured to obtain time sequence attribute values corresponding to all the associated first operation data, where the time sequence attribute values characterize a change of the amplitude of the associated first operation data;
The fault information determining module 205 is configured to determine, based on the second operation data, all the associated first operation data, and the respective corresponding time sequence attribute values, fault information of the battery in the preset operation state, where the fault information includes: there is a fault or no fault.
In one possible implementation manner of the embodiment of the present application, when the fault information determining module 205 determines the fault information of the battery in the preset operation state based on the second operation data, all the associated first operation data and the corresponding time sequence attribute values, the fault information determining module is specifically configured to:
acquiring environment information, and determining initial associated first operation data according to the environment information and time sequence attribute values corresponding to all the associated first operation data;
Determining first components corresponding to the second operation data based on the second operation data, and determining respective second components based on all initial associated first operation data;
Determining a plurality of target associated first operation data based on the first assembly, all initial associated first operation data and the corresponding second assemblies;
and acquiring historical abnormal information corresponding to each of the first operation data associated with all the targets, and determining fault information of the battery in a preset operation state according to all the historical abnormal information.
In one possible implementation manner of the embodiment of the present application, when the fault information determining module 205 determines that a plurality of targets are associated with the first operation data based on the first component, all initial associated first operation data and the respective corresponding second components, the fault information determining module is specifically configured to:
acquiring first position and first function information of a first component, and acquiring second positions and second function information corresponding to all second components;
determining, for each second component, an association value according to the first location, the first function information, the second location, and the second function information;
Determining a plurality of targets associated with the first operation data based on all the initial associated first operation data, the corresponding association values and the preset association value threshold value,
The association value of the target associated first operation data is larger than a preset association value threshold value.
In one possible implementation manner of the embodiment of the present application, the fault information determining module 205 is specifically configured to, when determining the association value according to the first location, the first function information, the second location, and the second function information:
Determining a structural association value based on the first location and the second location;
Determining a function association value based on the first function information and the second function information;
Acquiring a first weight value corresponding to the structural association value and a second weight value corresponding to the functional association value;
the association value is determined based on the structural association value, the first weight value, the functional association value, and the second weight value.
In one possible implementation manner of the embodiment of the present application, when the associated first operation data determining module 203 determines a plurality of associated first operation data from all the first operation data based on the second operation data difference value and all the first operation data, the associated first operation data determining module is specifically configured to:
Acquiring historical data of the second operation data difference value, wherein the historical data comprises: historical first operational data and first frequency of occurrence;
Determining target historical first operation data from all the historical first operation data based on a preset minimum occurrence frequency and a first occurrence frequency, wherein the first occurrence frequency of the target historical first operation data is not greater than the preset minimum occurrence frequency;
and matching all the first operation data with the target historical first operation data, and determining initial first operation data, wherein the initial first operation data represents the same data as the target historical first operation data.
In one possible implementation manner of the embodiment of the present application, the battery testing device based on the running state further includes:
the maintenance reminding module is used for:
determining the fault type of the battery in a preset running state, and acquiring a second occurrence frequency of the fault type in a first preset duration;
Determining a target maintenance waiting time length corresponding to the fault type according to the fault type and the second occurrence frequency;
Acquiring an idle maintenance period of maintenance personnel, and determining a target maintenance personnel according to the idle maintenance period and the target maintenance waiting time;
and generating a maintenance signal based on the fault type and the target maintenance personnel and sending the maintenance signal to the target maintenance personnel equipment to carry out maintenance reminding.
In one possible implementation manner of the embodiment of the present application, when the maintenance reminding module determines, based on the fault type and the second occurrence frequency, a target maintenance waiting duration corresponding to the fault type, the maintenance reminding module is specifically configured to:
Acquiring an influence attribute of the fault type, determining a first sub-target maintenance waiting time according to the influence attribute, and representing the influence degree generated by the fault type by the influence attribute;
Determining a second sub-target maintenance waiting time length corresponding to the second occurrence frequency according to the corresponding relation between the preset occurrence frequency and the maintenance waiting time length and the second occurrence frequency;
and determining the target maintenance waiting time corresponding to the fault type according to the first sub-target maintenance waiting time and the second sub-target maintenance waiting time.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, a specific working process of the battery testing device based on an operating state described above may refer to a corresponding process in the foregoing method embodiment, which is not described herein again.
In an embodiment of the present application, as shown in fig. 4, an electronic device shown in fig. 4 includes: a processor 301 and a memory 303. Wherein the processor 301 is coupled to the memory 303, such as via a bus 302. Optionally, the electronic device may also include a transceiver 304. It should be noted that, in practical applications, the transceiver 304 is not limited to one, and the structure of the electronic device is not limited to the embodiment of the present application.
The Processor 301 may be a CPU (Central Processing Unit ), general purpose Processor, DSP (DIGITAL SIGNAL Processor, data signal Processor), ASIC (Application SPECIFIC INTEGRATED Circuit), FPGA (Field Programmable GATE ARRAY ) or other programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various exemplary logic blocks, modules and circuits described in connection with this disclosure. Processor 301 may also be a combination that implements computing functionality, e.g., comprising one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.
Bus 302 may include a path to transfer information between the components. Bus 302 may be a PCI (PERIPHERAL COMPONENT INTERCONNECT, peripheral component interconnect standard) bus or an EISA (Extended Industry Standard Architecture ) bus, or the like. Bus 302 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in fig. 4, but not only one bus or type of bus.
The Memory 303 may be, but is not limited to, a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory ) or other type of dynamic storage device that can store information and instructions, an EEPROM (ELECTRICALLY ERASABLE PROGRAMMABLE READ ONLY MEMORY ), a CD-ROM (Compact Disc Read Only Memory, compact disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
The memory 303 is used for storing application program codes for executing the inventive arrangements and is controlled to be executed by the processor 301. The processor 301 is configured to execute the application code stored in the memory 303 to implement what is shown in the foregoing method embodiments.
Among them, electronic devices include, but are not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and stationary terminals such as digital TVs, desktop computers, and the like. But may also be a server or the like. The electronic device shown in fig. 4 is only an example and should not be construed as limiting the functionality and scope of use of the embodiments of the application.
Embodiments of the present application provide a computer-readable storage medium having a computer program stored thereon, which when run on a computer, causes the computer to perform the corresponding method embodiments described above.
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited in order and may be performed in other orders, unless explicitly stated herein. Moreover, at least some of the steps in the flowcharts of the figures may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, the order of their execution not necessarily being sequential, but may be performed in turn or alternately with other steps or at least a portion of the other steps or stages.
The foregoing is only a partial embodiment of the present application, and it should be noted that it will be apparent to those skilled in the art that modifications and adaptations can be made without departing from the principles of the present application, and such modifications and adaptations are intended to be comprehended within the scope of the present application.
Claims (9)
1. A battery testing method based on an operating state, comprising:
When a fault signal corresponding to a preset operation state is detected, determining a plurality of first operation data corresponding to the fault signal, wherein the preset operation state represents the operation state of a battery;
Acquiring second operation data corresponding to the fault signal, and determining a second operation data difference value based on the second operation data and standard second operation data, wherein the second operation data difference value represents an abnormality degree;
Determining a plurality of associated first operational data from all the first operational data based on the second operational data difference and all the first operational data;
Acquiring time sequence attribute values corresponding to all the associated first operation data, wherein the time sequence attribute values represent the change of the amplitude values of the associated first operation data;
Determining fault information of the battery in the preset operation state based on the second operation data, all the associated first operation data and the time sequence attribute values corresponding to the second operation data, wherein the fault information comprises: with or without a fault;
The determining the fault information of the battery in the preset operation state based on the second operation data, all the associated first operation data and the corresponding time sequence attribute values includes:
Acquiring environment information, and determining initial associated first operation data according to the environment information and time sequence attribute values corresponding to all the associated first operation data;
determining first components corresponding to the second operation data based on the second operation data, and determining respective second components based on all the initial association first operation data;
Determining a plurality of target associated first operation data based on the first assembly, all the initial associated first operation data and the corresponding second assemblies;
And acquiring first historical data corresponding to all the target associated first operation data, and determining fault information of the battery in the preset operation state according to all the first historical data.
2. The method of claim 1, wherein determining a number of target-associated first operational data based on the first component, all of the initial-associated first operational data, and the respective second components comprises:
Acquiring first position and first function information of the first component, and acquiring second positions and second function information corresponding to all second components;
determining, for each of the second components, an association value from the first location, the first function information, the second location, and the second function information;
And determining a plurality of target associated first operation data based on all the initial associated first operation data, the associated values and preset associated value thresholds, wherein the associated values of the target associated first operation data are larger than the preset associated value thresholds.
3. The battery testing method based on an operation state according to claim 2, wherein the determining an association value according to the first location, the first function information, the second location, and the second function information comprises:
Determining a structural association value based on the first location and the second location;
Determining a function association value based on the first function information and the second function information;
Acquiring a first weight value corresponding to the structural association value and a second weight value corresponding to the functional association value;
The association value is determined based on the structural association value, the first weight value, the functional association value, and the second weight value.
4. The battery testing method based on the operation state of claim 1, wherein the determining a number of associated first operation data from all the first operation data based on the second operation data difference value and all the first operation data includes:
Obtaining second historical data of the second operation data difference value, wherein the second historical data comprises: historical first operational data and first frequency of occurrence;
Determining target historical first operation data from all the historical first operation data based on a preset minimum occurrence frequency and the first occurrence frequency, wherein the first occurrence frequency of the target historical first operation data is not greater than the preset minimum occurrence frequency;
and matching all the first operation data with the target historical first operation data to determine initial first operation data, wherein the initial first operation data represents the same data as the target historical first operation data.
5. The method for testing a battery according to claim 1, wherein if there is a fault, after determining fault information of the battery in the preset operation state based on the second operation data, all the associated first operation data, and the respective corresponding time sequence attribute values, the method further comprises:
Determining the fault type of the battery in the preset running state, and acquiring a second occurrence frequency of the fault type in a first preset duration;
Determining a target maintenance waiting time length corresponding to the fault type according to the fault type and the second occurrence frequency;
acquiring an idle maintenance period of a maintenance person, and determining a target maintenance person according to the idle maintenance period and the target maintenance waiting time;
And generating a maintenance signal based on the fault type and the target maintenance personnel, and sending the maintenance signal to the target maintenance personnel equipment so as to carry out maintenance reminding.
6. The method for testing a battery based on an operation state according to claim 5, wherein the determining a target maintenance waiting period corresponding to the fault type based on the fault type and the second occurrence frequency includes:
Acquiring an influence attribute of the fault type, and determining a first sub-target maintenance waiting time length according to the influence attribute, wherein the influence attribute characterizes the influence degree generated by the fault type;
determining a second sub-target maintenance waiting time length corresponding to the second occurrence frequency according to a preset corresponding relation between the occurrence frequency and the maintenance waiting time length and the second occurrence frequency;
And determining the target maintenance waiting time corresponding to the fault type according to the first sub-target maintenance waiting time and the second sub-target maintenance waiting time.
7. A battery testing device based on an operating state, comprising:
The first operation data determining module is used for determining a plurality of first operation data corresponding to a fault signal when the fault signal corresponding to a preset operation state is detected, wherein the preset operation state represents the operation state of the battery;
The second operation data acquisition module is used for acquiring second operation data corresponding to the fault signal, determining a second operation data difference value based on the second operation data and standard second operation data, and representing the degree of abnormality;
The first operation data correlation determination module is used for determining a plurality of first operation data correlation from all the first operation data based on the second operation data difference value and all the first operation data;
the time sequence attribute value acquisition module is used for acquiring time sequence attribute values corresponding to all the associated first operation data respectively, and the time sequence attribute values represent the change of the amplitude values of the associated first operation data;
The fault information determining module is configured to determine fault information of the battery in the preset operation state based on the second operation data, all the associated first operation data, and the corresponding time sequence attribute values, where the fault information includes: with or without a fault;
the fault information determining module is configured to, when executing the fault information of the battery in the preset operation state, determine the fault information of the battery based on the second operation data, all the associated first operation data, and the corresponding time sequence attribute values, and:
Acquiring environment information, and determining initial associated first operation data according to the environment information and time sequence attribute values corresponding to all the associated first operation data;
determining first components corresponding to the second operation data based on the second operation data, and determining respective second components based on all the initial association first operation data;
Determining a plurality of target associated first operation data based on the first assembly, all the initial associated first operation data and the corresponding second assemblies;
And acquiring first historical data corresponding to all the target associated first operation data, and determining fault information of the battery in the preset operation state according to all the first historical data.
8. An electronic device, comprising:
At least one processor;
A memory;
At least one application program, wherein the at least one application program is stored in the memory and configured to be executed by the at least one processor, the at least one application program configured to: performing the operating state-based battery testing method of any one of claims 1 to 6.
9. A computer-readable storage medium, having stored thereon a computer program which, when executed in a computer, causes the computer to perform the run state based battery testing method of any one of claims 1 to 6.
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