CN118219899A - Charging pile management method, device, management system and medium - Google Patents
Charging pile management method, device, management system and medium Download PDFInfo
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Abstract
The application relates to the technical field of charging management, in particular to a charging pile management method, a device, a management system and a medium, wherein the method comprises the steps of obtaining actual charging data of a charging pile to be detected; the actual charging data and the corresponding preset charging pile model are subjected to data superposition to obtain an AR charging pile model; determining hidden danger components according to actual operation data and safety limit value data of each preset component in the AR charging pile model; according to historical power grid data, charging vehicle data and actual operation data of the hidden danger components, determining predicted operation data of the hidden danger components in a preset time period, and obtaining a simulated operation image according to the predicted operation data; determining a simulation window according to the AR hidden danger position, and displaying a simulation running image in the simulation window; and determining hidden danger feedback information according to the simulation running image. The application can reduce the influence of the fault of the charging pile on the related charging vehicles or pedestrians, thereby improving the safety of the charging pile in the working process.
Description
Technical Field
The present application relates to the field of charging management technologies, and in particular, to a method, an apparatus, a system, and a medium for managing a charging pile.
Background
Along with the increase of electric automobile quantity, people are also higher to the demand of car fills electric pile, because fill electric pile and be the infrastructure that electric automobile charges, its security directly relates to user's life and property safety, if fill electric pile and have the potential safety hazard, not only can cause the injury to the user, can also cause the threat to whole electric wire netting system, consequently fill electric pile and carry out fault detection especially critical.
In the related art, a charging pile with faults is generally overhauled in a regular overhauling or manual reporting mode, but the charging pile is overhauled after the faults are all caused no matter the charging pile is overhauled regularly or is overhauled after the faults are reported manually, and once the charging pile is overhauled untimely, certain safety threat can be caused to charging vehicles or pedestrians.
Disclosure of Invention
In order to reduce the influence of faults of the charging pile on related charging vehicles or pedestrians and improve the safety of the charging pile in the working process, the application provides a charging pile management method, a charging pile management device, a charging pile management system and a charging pile management medium.
In a first aspect, the present application provides a method for managing a charging pile, which adopts the following technical scheme:
A method of managing a charging pile, comprising:
acquiring actual charging data corresponding to a charging pile to be detected, wherein the actual charging data comprises actual power grid supply data and charging vehicle data;
the actual charging data and a preset charging pile model corresponding to the charging pile to be detected are subjected to data superposition to obtain an AR charging pile model, wherein the preset charging pile model comprises each preset component and safety limit value data corresponding to each preset component;
Identifying actual operation data corresponding to each preset component in the AR charging pile model, and determining hidden danger components in the AR charging pile model according to the actual operation data and the safety limit value data corresponding to each preset component;
according to historical power grid data, the charging vehicle data and actual operation data of the hidden danger assembly, determining predicted operation data of the hidden danger assembly in a preset time period, and performing simulated operation on the hidden danger assembly according to the predicted operation data to obtain a simulated operation image;
Determining an AR hidden danger position of the hidden danger component in the AR charging pile model, determining a simulation window according to the AR hidden danger position, and displaying the simulation running image in the simulation window;
And determining hidden danger feedback information according to the simulation running image.
Through adopting above-mentioned technical scheme, through stacking actual charge data and the pile model that charges, be convenient for know the change of every default subassembly in the pile that charges in a more directly perceivedly, thereby be convenient for discern the potential problem that the pile that charges probably exists to every default subassembly in the process that charges, through predict and simulate the hidden danger subassembly that probably breaks down, in order to judge the health status of this hidden danger subassembly in the default time period, through demonstrate analog image in the AR fills the pile model, so that relevant staff can further know the health status of every default subassembly in filling the pile, at last generate hidden danger feedback information through the simulated operation image, but feedback after waiting that hidden danger subassembly really breaks down, through simulating the working condition of hidden danger subassembly in a period in the future, can discover the potential problem that fills the pile in advance, and take timely measure and maintain, avoid hidden danger subassembly problem expansion or break down, thereby can reduce the influence that the relevant vehicle or pedestrian that breaks down caused because of filling the pile breaks down, and then the security of being convenient for filling pile working process.
In one possible implementation, when there are multiple hidden danger components, the method further includes:
Acquiring an association component of each hidden danger component, and determining an association type of each association component and a corresponding hidden danger component according to actual operation data of each association component, wherein the association type comprises active association and passive association;
determining hidden danger component grades corresponding to each hidden danger component based on the number of the associated components of each hidden danger component and the associated type of each associated component;
According to the level of each hidden danger component and the window display mapping relation, window display information corresponding to each hidden danger component is determined, a corresponding simulation window is adjusted based on the window display information corresponding to each hidden danger component, and the window display mapping relation is the corresponding relation between the level of the hidden danger component and the window size and the lighting color.
Through adopting above-mentioned technical scheme, when having a plurality of hidden danger subassemblies, through the association subassembly quantity and the association type of every association subassembly of every hidden danger subassembly pair to confirm the scope of influence that causes after the trouble of different hidden danger subassemblies, confirm the wound show information of every hidden danger subassembly according to the scope of influence, demonstrate the simulation operation image of different hidden danger subassemblies through different window sizes and bright lamp colour, the important degree of different hidden danger subassemblies is confirmed fast to the relevant maintainer of being convenient for, thereby is convenient for promote the maintenance rate of relevant maintainer.
In one possible implementation manner, the determining the hidden danger component level corresponding to each hidden danger component based on the number of the associated components of each hidden danger component and the association type of each associated component includes:
acquiring component linkage information of the charging pile to be detected, and determining the degree of association between each associated component and the corresponding hidden danger component according to the component linkage information;
Determining an association node diagram of each hidden danger component according to each hidden danger component, the association type of the corresponding association component of each hidden danger component and the association degree between each association component and the corresponding hidden danger component;
Determining a preset association region in each association node diagram, and identifying the number of final association components and each final association type in the corresponding preset association region of each hidden danger component;
Determining the influence score corresponding to each hidden danger component according to the number of the final association components corresponding to each hidden danger component, each final association type and a score mapping relation, wherein the score mapping relation is the corresponding relation between the number of the final association components, the final association type and the influence score;
And determining the grade of the hidden danger component corresponding to each hidden danger component according to the influence score and the grade mapping relation of each hidden danger component, wherein the grade mapping relation is the corresponding relation between the influence score and the grade of the hidden danger component.
Through adopting above-mentioned technical scheme, can demonstrate the association between different hidden danger subassemblies and the corresponding association subassembly directly perceivedly through the association node diagram, the rethread sets for and presets the regional association subassembly of carrying out the screening to every hidden danger subassembly to the association subassembly that the association is lower is removed in the ease, thereby is convenient for promote the accuracy when confirming hidden danger subassembly level.
In one possible implementation, the method further includes:
judging whether the number of final association components in the corresponding preset association region of each hidden danger component and each final association type meet preset conditions or not;
when the preset condition is not met, adjusting the range of the preset association area until the number of final association components and each final association type in the adjusted preset association area meet the preset condition;
Wherein, the preset conditions include:
The number of the final association components is lower than a preset threshold; and, in addition, the method comprises the steps of,
The ratio of the final association components of different final association types does not exceed a preset scale range.
By adopting the technical scheme, the number and the type of the final association components in the preset association region are analyzed to judge whether the range of the preset association region needs to be adjusted, and the accuracy in determining the hidden danger component level is convenient to improve by adjusting the preset association region because the hidden danger component level is related to the number and the type of the association components.
In one possible implementation manner, the data superposition of the actual charging data and the preset charging pile model corresponding to the charging pile to be detected to obtain an AR charging pile model includes:
Identifying the charging pile characteristics of the charging pile to be detected, and determining a preset charging pile model corresponding to the charging pile to be detected according to the charging pile characteristics and a model mapping relation, wherein the model mapping relation is the corresponding relation between the charging pile characteristics and the preset charging pile model;
Identifying each preset component in the preset charging pile model and operation support information corresponding to each preset component;
Determining the actual operation data corresponding to each preset component according to the operation support information corresponding to each preset component and the actual charging data;
And the actual operation data corresponding to each preset component are overlapped to the corresponding position in the preset charging pile model to obtain an AR charging pile model.
Through adopting above-mentioned technical scheme, through the operation support information of every preset subassembly in the electric pile that fills, and the actual data of charging confirm the actual operation data of every preset subassembly, be convenient for promote the accuracy of confirming every preset subassembly and corresponding actual operation data, demonstrate the actual operation data of every preset subassembly in the AR electric pile model through the mode of data stack, be convenient for demonstrate the operating condition of each preset subassembly directly perceivedly.
In one possible implementation manner, the determining the predicted operation data of the hidden danger component in the preset time period according to the historical power grid data, the charging vehicle data and the actual operation data of the hidden danger component includes:
determining a required charging time period and required charging power according to the charging vehicle data;
determining historical power of the power grid corresponding to the required time period according to the historical power grid data, and adjusting the required charging power according to the historical power of the power grid to obtain adjusted charging power;
And determining the predicted operation data of the hidden danger component in a preset time period according to the charging time period, the charging power adjustment and the actual operation data of the hidden danger component.
By adopting the technical scheme, because the power grid load is in a change state, the power grid load is not charged by adopting the same charging power all the time in the prediction stage, but the historical power grid power corresponding to the required time period of the hidden danger component is predicted through the historical power grid data, so that the actual charging power in a future period of time is adjusted, and the accuracy of a prediction result is improved conveniently.
In one possible implementation, the method further includes:
Acquiring the charging site image, and acquiring definition and integrity of the preset features in different associated images when the features of the articles in the charging vehicle are determined to be the preset features according to the charging site image, wherein the associated images are images corresponding to the charging piles to be detected and acquisition equipment at other charging piles;
Determining a target image according to the definition and the integrity of the preset features in different associated images, and determining acquisition equipment corresponding to the target image as target equipment;
Identifying charging scene characteristics contained in the charging scene image, and determining corresponding charging scene scores according to scene characteristic mapping relations, wherein the scene characteristic mapping relations are corresponding relations between the charging scene characteristics and the charging scene scores;
Acquiring the current charging time, and determining a corresponding charging time score according to a mapping relation between the charging time and the charging time, wherein the charging time mapping relation is a corresponding relation between the charging time and the charging time score;
And determining the target acquisition frequency of the target equipment according to the charging scene score, the charging moment score and the acquisition frequency mapping relation.
Through adopting above-mentioned technical scheme, in charging process, except monitoring the operating condition of each subassembly in the charging pile inside, also need monitor the charging vehicle in charging to promote charging vehicle's security, through definition and the integrality when the correlation image promotes to predetermineeing the characteristic and monitor, thereby be convenient for monitor the predetermined characteristic in the charging vehicle more directly perceivedly, the rethread charges scene and charges moment adjustment image acquisition frequency, is convenient for further promote charging vehicle and the security of the inside predetermined characteristic of vehicle.
In a second aspect, the present application provides a charging pile management device, which adopts the following technical scheme:
a charging pile management device, comprising:
The charging data acquisition module is used for acquiring actual charging data corresponding to the charging pile to be detected, wherein the actual charging data comprises actual power grid supply data and charging vehicle data;
Determining an AR charging pile model module, wherein the AR charging pile model module is used for carrying out data superposition on the actual charging data and a preset charging pile model corresponding to the charging pile to be detected to obtain an AR charging pile model, and the preset charging pile model comprises each preset component and safety limit value data corresponding to each preset component;
The hidden danger component determining module is used for identifying actual operation data corresponding to each preset component in the AR charging pile model and determining hidden danger components in the AR charging pile model according to the actual operation data and the safety limit value data corresponding to each preset component;
The simulation operation image determining module is used for determining prediction operation data of the hidden danger component in a preset time period according to historical power grid data, the charging vehicle data and actual operation data of the hidden danger component, and performing simulation operation on the hidden danger component according to the prediction operation data to obtain a simulation operation image;
the image display module is used for determining the AR hidden danger position of the hidden danger component in the AR charging pile model, determining a simulation window according to the AR hidden danger position and displaying the simulation running image in the simulation window;
And the hidden danger feedback information determining module is used for determining hidden danger feedback information according to the simulation running image.
Through adopting above-mentioned technical scheme, through stacking actual charge data and the pile model that charges, be convenient for know the change of every default subassembly in the pile that charges in a more directly perceivedly, thereby be convenient for discern the potential problem that the pile that charges probably exists to every default subassembly in the process that charges, through predict and simulate the hidden danger subassembly that probably breaks down, in order to judge the health status of this hidden danger subassembly in the default time period, through demonstrate analog image in the AR fills the pile model, so that relevant staff can further know the health status of every default subassembly in filling the pile, at last generate hidden danger feedback information through the simulated operation image, but feedback after waiting that hidden danger subassembly really breaks down, through simulating the working condition of hidden danger subassembly in a period in the future, can discover the potential problem that fills the pile in advance, and take timely measure and maintain, avoid hidden danger subassembly problem expansion or break down, thereby can reduce the influence that the relevant vehicle or pedestrian that breaks down caused because of filling the pile breaks down, and then the security of being convenient for filling pile working process.
In one possible implementation, when there are multiple hidden danger components, the apparatus further includes:
The system comprises an acquisition association component module, a hidden danger component acquisition module and a hidden danger component generation module, wherein the acquisition association component module is used for acquiring association components of each hidden danger component and determining association types of each association component and the corresponding hidden danger component according to actual operation data of each association component, and the association types comprise active association and passive association;
the hidden danger component grade determining module is used for determining hidden danger component grades corresponding to each hidden danger component based on the number of the associated components of each hidden danger component and the associated type of each associated component;
The window display information determining module is used for determining window display information corresponding to each hidden danger component according to the level of each hidden danger component and window display mapping relation, and adjusting a corresponding simulation window based on the window display information corresponding to each hidden danger component, wherein the window display mapping relation is the corresponding relation between the level of the hidden danger component and the window size and the lighting color.
In one possible implementation manner, the hidden danger component level determining module is specifically configured to, when determining the hidden danger component level corresponding to each hidden danger component based on the number of associated components of each hidden danger component and the association type of each associated component:
acquiring component linkage information of the charging pile to be detected, and determining the degree of association between each associated component and the corresponding hidden danger component according to the component linkage information;
Determining an association node diagram of each hidden danger component according to each hidden danger component, the association type of the corresponding association component of each hidden danger component and the association degree between the corresponding hidden danger component and the corresponding hidden danger component;
Determining a preset association region in each association node diagram, and identifying the number of final association components and each final association type in the corresponding preset association region of each hidden danger component;
Determining the influence score corresponding to each hidden danger component according to the number of the final association components corresponding to each hidden danger component, each final association type and a score mapping relation, wherein the score mapping relation is the corresponding relation between the number of the final association components, the final association type and the influence score;
And determining the grade of the hidden danger component corresponding to each hidden danger component according to the influence score and the grade mapping relation of each hidden danger component, wherein the grade mapping relation is the corresponding relation between the influence score and the grade of the hidden danger component.
In one possible implementation, the apparatus further includes:
the condition judging module is used for judging whether the number of the final association components in the corresponding preset association area of each hidden danger component and each final association type meet preset conditions or not;
The adjusting range module is used for adjusting the range of the preset association area until the number of final association components and each final association type in the adjusted preset association area meet the preset condition when the preset condition is not met;
Wherein, the preset conditions include:
The number of the final association components is lower than a preset threshold; and, in addition, the method comprises the steps of,
The ratio of the final association components of different final association types does not exceed a preset scale range.
In one possible implementation manner, determining that the AR charging pile model module performs data superposition on the actual charging data and a preset charging pile model corresponding to the charging pile to be detected, so as to obtain an AR charging pile model, where the AR charging pile model module is specifically configured to:
Identifying the charging pile characteristics of the charging pile to be detected, and determining a preset charging pile model corresponding to the charging pile to be detected according to the charging pile characteristics and a model mapping relation, wherein the model mapping relation is the corresponding relation between the charging pile characteristics and the preset charging pile model;
Identifying each preset component in the preset charging pile model and operation support information corresponding to each preset component;
Determining the actual operation data corresponding to each preset component according to the operation support information corresponding to each preset component and the actual charging data;
And the actual operation data corresponding to each preset component are overlapped to the corresponding position in the preset charging pile model to obtain an AR charging pile model.
In one possible implementation manner, the determining the simulated operation image module is specifically configured to, when determining the predicted operation data of the hidden danger component in the preset time period according to the historical power grid data, the charging vehicle data and the actual operation data of the hidden danger component:
determining a required charging time period and required charging power according to the charging vehicle data;
determining historical power of the power grid corresponding to the required time period according to the historical power grid data, and adjusting the required charging power according to the historical power of the power grid to obtain adjusted charging power;
And determining the predicted operation data of the hidden danger component in a preset time period according to the charging time period, the charging power adjustment and the actual operation data of the hidden danger component.
In one possible implementation, the apparatus further includes:
The charging system comprises an on-site image acquisition module, a charging pile detection module and a charging pile detection module, wherein the on-site image acquisition module is used for acquiring the charging on-site image, and acquiring definition and integrity of preset features in different associated images when the features of articles in a charging vehicle are determined to be the preset features according to the charging on-site image, wherein the associated images are images corresponding to acquisition equipment at the charging pile to be detected and other charging piles;
The target image determining module is used for determining a target image according to the definition and the integrity of the preset features in different associated images and determining acquisition equipment corresponding to the target image as target equipment;
The charging scene score determining module is used for identifying charging scene features contained in the charging scene image, and determining corresponding charging scene scores according to scene feature mapping relations, wherein the scene feature mapping relations are corresponding relations between charging scene features and charging scene scores;
The charging time score determining module is used for obtaining the current charging time and determining a corresponding charging time score according to the mapping relation between the charging time and the charging time, wherein the charging time mapping relation is the corresponding relation between the charging time and the charging time score;
the target acquisition frequency determining module is used for determining the target acquisition frequency of the target equipment according to the charging scene score, the charging moment score and the acquisition frequency mapping relation.
In a third aspect, the present application provides a management system, which adopts the following technical scheme:
A management system, the management system comprising:
at least one processor;
A memory;
At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application configured to: and executing the method for managing the charging pile.
In a fourth aspect, the present application provides a computer readable storage medium, which adopts the following technical scheme:
A computer-readable storage medium, comprising: a computer program capable of being loaded by a processor and executing the above-described charging pile management method is stored.
In summary, the present application includes at least one of the following beneficial technical effects:
Through stacking actual charging data and the charging pile model, change of each preset component in the charging pile in the charging process is more intuitively known, potential safety hazards possibly existing in the charging pile can be conveniently identified, potential safety hazards possibly existing in the charging pile can be conveniently found in advance through predicting and simulating the potential safety hazards in the charging process, the health state of the potential safety hazards in the preset time period can be judged, a simulation image is displayed in the AR charging pile model, so that relevant staff can further know the health state of each preset component in the charging pile, potential safety hazard feedback information is finally generated through simulating operation images, feedback is not performed after the potential safety hazards in the charging pile really occur, potential safety hazards in the charging pile possibly exist can be conveniently found through working states of the simulated potential safety hazards in a future time, maintenance measures can be timely taken, potential safety hazards in the charging pile can be avoided, influences on relevant charging vehicles or pedestrians caused by the potential safety hazards in the charging pile are reduced, and safety in the working process of the charging pile is conveniently improved.
The association node diagram can intuitively display the association relation between different hidden danger components and corresponding association components, and the association components of each hidden danger component are screened by setting a preset area so as to remove the association components with lower association, thereby being convenient for improving the accuracy in determining the level of the hidden danger component.
Drawings
FIG. 1 is a schematic diagram of an application scenario in an embodiment of the present application;
Fig. 2 is a schematic flow chart of a method for managing a charging pile according to an embodiment of the present application;
FIG. 3 is a schematic illustration of an embodiment of the present application
Fig. 4 is a schematic structural diagram of a charging pile management device according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of a management system according to an embodiment of the present application.
Detailed Description
The application is described in further detail below with reference to fig. 1-5.
Modifications of the embodiments which do not creatively contribute to the application may be made by those skilled in the art after reading the present specification, but are protected by patent laws within the scope of the claims of the present application.
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. 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 order to facilitate understanding, please refer to fig. 1, fig. 1 is a schematic diagram of an applicable scenario of the present application, which includes a management system, a charging pile, a power grid and a user terminal, wherein when the charging pile contacts a charging vehicle, the charging pile can directly acquire charging vehicle data, a user can also directly upload the charging vehicle data to the management system, after detecting charging vehicle data uploaded by a relevant user, the management system feeds back the charging vehicle data to the corresponding charging pile, when information needing to be fed back exists in the charging process, the charging pile can directly feed back the information needing to be fed back to the relevant user, or the charging pile can upload the information needing to be fed back to the management system, and then the management system feeds back the information to the client terminal.
Specifically, the embodiment of the application provides a charging pile management method, which is executed by a management system, wherein the management system can be a server or a terminal device, 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, etc., 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, which is not limited herein.
Referring to fig. 2, fig. 2 is a flow chart of a method for managing a charging pile according to an embodiment of the present application, the method includes steps S210 to S260, wherein:
Step S210: and acquiring actual charging data corresponding to the charging pile to be detected, wherein the actual charging data comprises actual power grid supply data and charging vehicle data.
Specifically, the charging pile to be detected may be a charging pile in a cell or a charging pile in a parking lot, and the specific application scenario is not limited in the embodiment of the present application, so long as the safety detection requirement exists. The actual charging data corresponding to the charging pile to be detected comprises actual power grid supply data and charging vehicle data, wherein the actual power grid supply data is used for representing the power grid load condition at the charging moment and can comprise power grid voltage, power grid current, power grid power and the like; the charge vehicle data is used to characterize the charge demand of the charge vehicle and may include a demand voltage, a demand current, a demand power, etc. of the charge vehicle when charged.
Step S220: and carrying out data superposition on the actual charging data and a preset charging pile model corresponding to the charging pile to be detected to obtain an AR charging pile model, wherein the preset charging pile model comprises each preset component and safety limit value data corresponding to each preset component.
Specifically, the preset charging pile model can be uploaded to the management system by a related technician, and as internal components of different charging piles to be detected may be different, the related technician uploads a plurality of charging pile models when uploading the preset charging pile model, and when a related user needs to charge a charging vehicle by using the charging pile to be detected, the charging pile to be detected is selected from a plurality of preset charging pile models according to the actual charging pile to be detected. In order to intuitively understand the working state of each component in the charging pile to be detected, data superposition is performed on actual charging data and a preset charging pile model corresponding to the charging pile to be detected, so as to obtain an AR charging pile model, which specifically comprises the following steps:
Identifying charging pile characteristics of a charging pile to be detected, and determining a preset charging pile model corresponding to the charging pile to be detected according to the charging pile characteristics and a model mapping relation, wherein the model mapping relation is a corresponding relation between the charging pile characteristics and the preset charging pile model; identifying each preset component in a preset charging pile model and operation support information corresponding to each preset component; determining the actual operation data corresponding to each preset component according to the operation support information and the actual charging data corresponding to each preset component; and (3) superposing the actual operation data corresponding to each preset assembly to the corresponding position in the preset charging pile model to obtain the AR charging pile model.
Specifically, the charging pile features can be charging pile numbers, charging pile models, charging pile factory numbers and the like, and only the internal component assembly condition of the charging pile to be detected can be determined through the charging pile features. The model mapping relation comprises preset charging pile modularity corresponding to different charging characteristics, the model mapping relation can be uploaded to a management system in advance by related technicians, specific contents are not limited in the embodiment of the application, and the model mapping relation can be modified by the related technicians according to actual conditions. The charging pile to be detected and the corresponding preset charging pile model to be detected are provided with preset components which are consistent with each other, wherein the preset components comprise the number of the preset components and the assembly position of each preset component in the charging pile. The preset components included in the preset charging pile model may be a direct current output component, an insulation detection component, a charging gun component, a direct current meter component, a CCU control component, a TCU control component, a lightning protection idle-open component, etc., the preset components corresponding to different charging pile features may be different, and the operation support information of each preset component is used to characterize the operation responsibility of each preset component, for example, the operation support information of the CCU component is used to monitor the charging vehicle in the charging pile in real time, and automatically transmit the obtained data, and in some cases, the operation support information of the CCU component may also be used to receive and process various sensor information. According to the operation support information and the actual charging data corresponding to each preset component, the actual operation data corresponding to each preset component is determined, that is, when the charging pile to be detected is charging the charging vehicle, the actual operation data of different preset components are obtained in real time, and because the operation support information of different preset components is different, that is, the working responsibilities are different, the actual operation data corresponding to different preset components are also different, for example, the actual operation data displayed by the CCU component may be the data transmission rate, and the actual operation data displayed by the direct current output component may be the output current.
The management system comprises actual operation data generated in the charging process of each component in the charging pile to be detected, the actual operation data generated by each component in the same charging pile to be detected is stored in the same data warehouse for convenience of management, when data superposition is needed, the target data warehouse is determined by traversing the management system according to the charging pile characteristics corresponding to the charging pile to be detected, corresponding actual operation data is determined from the target data warehouse according to preset components in the preset charging pile model, and the actual operation data is added to corresponding positions in the preset charging pile model. The AR charging pile model comprises a preset charging pile model and actual operation data of each preset component in the preset charging pile model in the charging process. If data fluctuation occurs in a certain component in the charging pile to be detected in the charging process, data fluctuation also occurs in a corresponding preset component in the AR charging pile model.
In addition, the preset charging pile model also comprises safety limit data of each preset component, the safety limit data corresponding to different preset components are different, the safety limit data of the preset components are not required to be set by related technicians according to historical fault data, and when the actual operation data of the preset components are higher than or lower than the safety limit data and are inconsistent, the probability of faults of the preset components is represented.
Step S230: and identifying actual operation data corresponding to each preset component in the AR charging pile model, and determining hidden danger components in the AR charging pile model according to the actual operation data and the safety limit value data corresponding to each preset component.
Specifically, because actual operation data of each preset component in the AR charging pile model may change in real time, when judging whether a hidden danger component exists, the actual operation data corresponding to the current moment needs to be acquired. Because the corresponding working responsibilities of different preset components are different, when judging whether the different preset components are hidden danger components, the abnormal type needs to be determined according to the corresponding working responsibilities of the preset components, the abnormal type comprises higher or lower than, for example, the abnormal type of the preset component 1 is higher than, the abnormal type of the preset component 2 is lower than, when judging whether the preset component 1 and the preset component 2 are hidden danger components, the actual operation data of the preset component 1 can be compared with the corresponding safety limit data, when the actual operation data of the preset component 1 is higher than the corresponding safety limit data, the preset component 1 is determined to be a hidden danger component, and similarly, when the actual operation data of the preset component 2 is lower than the corresponding safety limit data, the actual operation data of the preset component 2 is determined to be a hidden danger component. The abnormal type corresponding to each preset component can be determined according to the type mapping relation, wherein the type mapping relation comprises abnormal types corresponding to different preset components, the specific content of the type mapping relation is not particularly limited in the embodiment of the application, and the abnormal type can be set by related technicians. In the embodiment of the application, the hidden danger component is a component which can possibly fail in the charging process and is not a component which has failed.
Step S240: according to the historical power grid data, the charging vehicle data and the actual operation data of the hidden danger assembly, the predicted operation data of the hidden danger assembly in a preset time period is determined, and the hidden danger assembly is simulated according to the predicted operation data to obtain a simulated operation image.
Specifically, the historical power grid data includes power grid voltages, power grid currents and the like corresponding to different historical periods, power grid supply data in a future period can be predicted according to the historical power grid data, and in order to improve accuracy of a prediction result, predicted operation data of the hidden danger component in a preset period is determined according to the historical power grid data, charging vehicle data and actual operation data of the hidden danger component, and the method specifically includes the steps of:
determining a required charging period and a required charging power according to the charging vehicle data; determining historical power grid power corresponding to the required time period according to the historical power grid data, and adjusting required charging power according to the historical power grid power to obtain adjusted charging power; and according to the required charging time period, the charging power and the actual operation data of the hidden danger component, determining the predicted operation data of the hidden danger component in the preset time period.
Specifically, the charging vehicle data includes not only a required voltage, a required current and a required power of the charging vehicle during charging, but also a remaining capacity, a charging duration for fully charging the charging vehicle can be determined according to the remaining capacity, the required voltage, the required current and the required power, a required charging time period corresponding to the charging vehicle is used for representing the duration required for fully charging the remaining capacity of the charging vehicle, for example, 5 hours required for fully charging the charging vehicle is determined according to the charging vehicle data, charging is completed for 3 hours when the charging vehicle is 20:00-22:00, and the required charging time period of the charging vehicle is 20:00-22:00. The required charging power of the charging vehicle is the lowest charging power that can be satisfied by the charging vehicle, and may be lower than the charging power in the charging vehicle data in step S110, and since the hidden danger component appears at this time, in order to reduce the probability of the hidden danger component malfunctioning, the charging power of the charging vehicle may be adjusted in a future period of time at this time.
Because the power grid load states corresponding to different time periods are different, when the power grid load corresponding to the required time period is too high or too low, the charging power of the charging vehicle may be affected, so that in order to characterize the charging safety of the charging vehicle, after the charging power of the charging vehicle is determined, the charging power of the charging vehicle needs to be adjusted according to the historical power grid power to obtain the adjusted charging power, and the charging of the charging vehicle according to the required charging power in the required time period is ensured to the greatest extent, wherein the adjusted charging power may be the same as or different from the required charging power, but the power difference between the adjusted charging power and the required charging power is lower than the preset power difference, and the specific preset power difference is not particularly limited in the embodiment of the application. Because the power grid load is in a change state, the power grid load is not charged by adopting the same charging power all the time in a prediction stage, but the historical power grid power corresponding to the required time period of the hidden danger component is predicted through the historical power grid data, the actual charging power in a future period of time is adjusted, and the accuracy of a prediction result is convenient to improve.
The method for determining the predicted operation data according to the charging power and the actual operation data of the hidden danger component may refer to the implementation method for determining the actual operation data corresponding to each preset component according to the operation support information and the actual charging data corresponding to each preset component in the above embodiment, which is not described herein.
And performing simulation operation on the hidden danger component according to the predicted operation data, namely driving the hidden danger component in the AR charging pile model to work according to the predicted operation data, wherein the simulation operation image is a simulation working condition of the hidden danger component in a required charging time period.
Step S250: and determining the AR hidden danger position of the hidden danger component in the AR charging pile model, determining a simulation window according to the AR hidden danger position, and displaying the simulation running image in the simulation window.
Step S260: and determining hidden danger feedback information according to the simulation running image.
Specifically, the position of the hidden danger AR is the position of the hidden danger component in the AR charging pile model, and may be determined by means of component feature comparison, where the specific manner is not specifically limited in the embodiment of the present application, and may be set by a related technician. The simulation window is used for displaying the simulation running image, and the simulation window can be positioned at the left side of the AR hidden danger position or at the right side of the AR hidden danger component, so long as other components are not shielded, and the specific position is not specifically limited in the embodiment of the application.
When the hidden danger component in the simulated operation image does not have a fault, namely, the simulated charging work is performed based on the predicted operation data corresponding to the hidden danger component, the hidden danger component does not have a behavior of being higher or lower than the corresponding safety limit value data, and the generated feedback information is null; when the predicted operation data corresponding to the hidden danger component fails, namely, the charging work is simulated based on the predicted operation data corresponding to the hidden danger component, the hidden danger component generates the feedback information based on the behavior higher or lower than the corresponding safety limit value data.
The charging pile to be detected can directly feed back the generated feedback information to the user side of the corresponding user and related maintenance personnel, and the management system can also forward the generated feedback information.
According to the embodiment of the application, the actual charging data and the charging pile model are overlapped, so that the change of each preset component in the charging pile in the charging process can be more intuitively known, potential problems possibly existing in the charging pile can be conveniently found in advance, potential hazards possibly existing in the charging pile can be timely maintained by adopting measures, the potential hazards are prevented from being expanded or failed due to the occurrence of the faults of the charging pile, the influence of the potential hazards on related charging vehicles or pedestrians can be reduced, and the safety in the working process of the charging pile is conveniently improved.
Further, when there are multiple hidden trouble components, the method further comprises:
Acquiring an association component of each hidden danger component, and determining an association type of each association component and a corresponding hidden danger component according to actual operation data of each association component, wherein the association type comprises active association and passive association; determining hidden danger component grades corresponding to each hidden danger component based on the number of the associated components of each hidden danger component and the associated type of each associated component; according to the level of each hidden danger component and the window display mapping relation, window display information corresponding to each hidden danger component is determined, a corresponding simulation window is adjusted based on the window display information corresponding to each hidden danger component, and the window display mapping relation is the corresponding relation between the level of the hidden danger component and the window size and the lighting color.
Specifically, the association component of the hidden danger component is a component directly associated with the hidden danger component, as shown in fig. 3, and the association component of the hidden danger component X includes an association component A1, an association component A2, an association component B1, an association component B2 and an association component B3. According to the actual operation data of each association component, the association type, namely the communication relation between each association component and the hidden danger component can be determined, for example, after the charging interface component is communicated, the charging control component can start to operate, so that the upper and lower association relation exists between the components in the charging pile. The association type comprises active association and passive association, and when the association component of the hidden danger component is an upper component of the hidden danger component, the association type of the association component is determined to be the active association; when the association component of the hidden trouble component is a subordinate component of the hidden trouble component, the association type of the association component is determined to be passive association.
The number of the association components contained in different hidden danger components may be different, and correspondingly, the association types contained in the association components are also different, so that in order to divide the importance degrees of different hidden danger components, the hidden danger component grade of each hidden danger component can be determined through the number of the association components contained in the hidden danger components and the association type of each association component. And then determining the display window effect of different hidden danger components in the AR charging pile model according to the different hidden danger component grades, wherein the display window effect comprises a window size and a lighting color of the window, and displaying the simulation running images of the different hidden danger components through the different window sizes and the lighting colors, so that the related maintainers can conveniently and quickly determine the importance degree of the different hidden danger components, and the maintenance rate of the related maintainers can be conveniently improved. The window display mapping relation comprises window sizes and lighting colors corresponding to different hidden danger component grades, wherein the higher the hidden danger component grade is, the larger the probability of the hidden danger component to fail is represented, the larger the window size of the corresponding simulation window is, the higher the brightness of the lighting color is, the specific content of the window display mapping relation is not specifically limited in the embodiment of the application, and the specific content can be set by related technicians.
Further, in order to improve accuracy in determining the hidden danger component level, determining the hidden danger component level corresponding to each hidden danger component based on the number of associated components of each hidden danger component and the association type of each associated component specifically includes:
And acquiring component linkage information of the charging pile to be detected, and determining the degree of association between each associated component and the corresponding hidden danger component according to the component linkage information.
Specifically, the linkage condition between each component is recorded in the component linkage information, and the higher the degree of association between the associated component and the hidden danger component is, the larger the influence on the associated component is after the hidden danger component is represented to be faulty.
And determining an association node diagram of each hidden danger component according to each hidden danger component, the association type of the corresponding association component of each hidden danger component and the association degree between each association component and the corresponding hidden danger component.
Specifically, when determining the association node diagram corresponding to each hidden danger component, the hidden danger component and each corresponding association component can be used as nodes, the side length between the nodes can be determined according to the association degree between the hidden danger component and each association component, and then the direction between the hidden danger component and the association component can be determined according to the association type of each hidden danger component and the corresponding association component, so as to generate the association node diagram corresponding to each hidden danger component, as shown in fig. 3, wherein the side length corresponding to the association degree can be determined according to the side length mapping relation, the side length corresponding to each association degree is contained in the side length mapping relation, the specific content of the side length mapping relation is not specifically limited in the embodiment of the application, and can be set by related technicians.
And determining a preset association region in each association node diagram, and identifying the number of final association components and each final association type in the corresponding preset association region of each hidden danger component.
Specifically, the preset association area of the association node diagram is an area with hidden danger components as emphasis and the preset distance as radius, after the preset association area is determined, the preset association area can be subjected to screenshot, and the number of final association components in the preset association area and the final association type of each final association component are identified in a feature identification manner, so that the number of final association components may be smaller than the number of all association components corresponding to the hidden danger components due to the limited preset association area, namely, the association components of the hidden danger components may be located outside the preset association area, such as nodes corresponding to association component B4 in fig. 3.
Further, in order to improve accuracy in determining the level of the hidden danger component, the method further includes:
Judging whether the number of final association components in the corresponding preset association region of each hidden danger component and each final association type meet preset conditions or not; when the preset condition is not met, adjusting the range of the preset association area until the number of final association components and each final association type in the adjusted preset association area meet the preset condition; the preset conditions comprise: the number of the final association components is lower than a preset threshold; and the ratio of the final association components of different final association types does not exceed a preset ratio range.
Specifically, since the level of the hidden danger component is related to the number and the type of the association component, whether the range of the preset association region needs to be adjusted can be judged by analyzing the number and the type of the final association component in the preset association region, when the number of the final association component in each preset association region is not lower than a preset threshold value and the ratio of the final association components among different final association types is within a preset proportion range, namely, the number of the final association components in the corresponding preset association region of the hidden danger component and each final association type are determined to meet preset conditions, namely, the preset association region corresponding to the hidden danger component does not need to be adjusted; when the number of the final association components in each preset association region is lower than a preset threshold value, or the ratio of the final association components between different final association types exceeds a preset proportion range, determining that the number of the final association components in the corresponding preset association region of the hidden danger component and each final association type do not meet preset conditions, namely, the preset association region corresponding to the hidden danger component needs to be adjusted. The specific preset threshold and preset ratio range are not specifically limited in the embodiment of the present application, and may be set by a related technician.
When the preset association area corresponding to the hidden trouble component needs to be adjusted, the hidden trouble component can be adjusted in a mode of gradually increasing the corresponding radius of the preset association area until the number of final association components and each final association type in the preset association area meet preset conditions. When the corresponding radius of the preset association area is gradually increased, the radius of the preset association area can be increased in a mode of increasing the length of the fixed radius each time, or in a mode of gradually increasing the radius, and the specific increasing mode is not limited in the embodiment of the application.
And determining the influence score corresponding to each hidden danger component according to the number of the final association components corresponding to each hidden danger component, each final association type and the score mapping relation, wherein the score mapping relation is the corresponding relation between the number of the final association components, the final association type and the influence score.
Specifically, a first sub-impact score may be determined according to a first sub-mapping relationship and the number of final association components, where the first sub-mapping relationship includes first sub-impact scores corresponding to different numbers of final association components. The second sub-influence score may be determined according to a type ratio between the second sub-mapping relationship and each final association type in the final association component, where the second sub-mapping relationship includes second sub-influence scores corresponding to different types of ratios, and specific contents of the first sub-mapping relationship and the second sub-mapping relationship are not specifically limited in the embodiment of the present application, and may be set by related technicians.
And determining the hidden danger component grade corresponding to each hidden danger component according to the influence score and grade mapping relation of each hidden danger component, wherein the grade mapping relation is the corresponding relation between the influence score and the hidden danger component grade.
Specifically, the level mapping relationships include level mapping relationships corresponding to different impact scores, and specific contents are not specifically limited in the embodiment of the present application, and may be set by related technicians. The association node diagram can intuitively display the association relation between different hidden danger components and corresponding association components, and the association components of each hidden danger component are screened by setting a preset area so as to remove the association components with lower association, thereby being convenient for improving the accuracy in determining the level of the hidden danger component.
Further, in order to improve the safety of the charging vehicle and the preset features inside the vehicle, the method provided by the embodiment of the application further includes:
acquiring charging site images, and acquiring definition and integrity of preset features in different associated images when the features of articles in a charging vehicle are determined to be preset features according to the charging site images, wherein the associated images are images corresponding to acquisition equipment at a charging pile to be detected and other charging piles; determining a target image according to the definition and the integrity of preset features in different associated images, and determining acquisition equipment corresponding to the target image as target equipment; identifying charging scene characteristics contained in the charging scene image, and determining corresponding charging scene scores according to scene characteristic mapping relations, wherein the scene characteristic mapping relations are corresponding relations between the charging scene characteristics and the charging scene scores; acquiring a current charging time, and determining a corresponding charging time score according to a mapping relation between the charging time and the charging time, wherein the charging time mapping relation is a corresponding relation between the charging time and the charging time score; and determining the target acquisition frequency of the target equipment according to the charging scene score, the charging moment score and the acquisition frequency mapping relation.
Specifically, the charging site image can be collected by the image collecting device arranged in the surrounding environment of charging to be detected and then uploaded to the management system, and can also be collected by the image collecting device corresponding to the charging pile to be detected or the adjacent charging pile of the charging pile to be detected and then uploaded to the management system. The image feature recognition model is obtained by training a large amount of sample data, wherein the large amount of sample data is pictures containing various preset features and corresponding feature labels. The preset features may be important properties, etc., and specific preset features are not specifically limited in the embodiment of the present application, and may be set by a related person.
After the preset features in the charge site image are identified, the Laplace operator can be used for edge detection, the definition of the preset features in different associated images is evaluated by calculating the gradient or variance of the preset features in the image, and the gradient or variance value of the clearer image is higher; the integrity of the preset features in the different associated images can be determined by means of contour recognition. And determining all charging field images containing preset features as associated images, and determining the associated images with the preset features of the associated images with the definition higher than the preset definition and the integrity higher than the preset integrity as target images, wherein the image acquisition equipment for acquiring the target images is determined as target equipment, and the target equipment can be the image acquisition equipment corresponding to the charging pile to be detected or the image acquisition equipment corresponding to the adjacent charging pile of the charging pile to be detected because the vehicle posture of the charging vehicle is not fixed during charging.
By identifying scene features in the charging scene image, a charging scene where the charging pile to be detected is located can be determined, the scene features can be guideboards, roadbeds, buildings and the like, the scene feature mapping relationship contains charging scene scores corresponding to different scene features, and the charging moment mapping relationship contains charging moment scores corresponding to different charging moments. Determining a total charge score according to the charge scene score and the charge moment score, and determining the collection frequency corresponding to the total charge score by utilizing a collection frequency mapping relation, wherein specific scene identification, scene feature mapping relation, charge moment mapping relation and collection frequency mapping relation are not particularly limited in the embodiment of the application and can be set by related technicians.
In the charging process, besides monitoring the working state of each component in the charging pile, the charging vehicle in charging is required to be monitored so as to improve the safety of the charging vehicle, and the definition and the integrity of the charging vehicle in monitoring the preset features are improved through the associated images, so that the preset features in the charging vehicle are monitored more intuitively, the image acquisition frequency is adjusted through the charging scene and the charging moment, and the charging vehicle and the safety of the preset features in the vehicle are further improved.
The foregoing embodiments describe a method for managing a charging pile from the viewpoint of a method flow, and the following embodiments describe a device for managing a charging pile from the viewpoint of a virtual module or a virtual unit, which will be described in detail below.
The embodiment of the application provides a charging pile management device, as shown in fig. 4, which specifically may include a charging data acquisition module 410, an AR charging pile model determination module 420, a hidden danger determination module 430, a simulation operation image determination module 440, an image display module 450, and a hidden danger determination feedback information module 460, wherein:
The charging data acquisition module 410 is configured to acquire actual charging data corresponding to a charging pile to be detected, where the actual charging data includes actual power grid supply data and charging vehicle data;
The AR charging pile model determining module 420 is configured to perform data superposition on actual charging data and a preset charging pile model corresponding to a charging pile to be detected, so as to obtain an AR charging pile model, where the preset charging pile model includes each preset component and safety limit data corresponding to each preset component;
the hidden danger determining component module 430 is configured to identify actual operation data corresponding to each preset component in the AR charging pile model, and determine hidden danger components in the AR charging pile model according to the actual operation data and the safety limit data corresponding to each preset component;
The simulated operation image determining module 440 is configured to determine predicted operation data of the hidden danger component in a preset time period according to historical power grid data, charging vehicle data and actual operation data of the hidden danger component, and perform simulated operation on the hidden danger component according to the predicted operation data to obtain a simulated operation image;
The image display module 450 is used for determining an AR hidden danger position of the hidden danger component in the AR charging pile model, determining a simulation window according to the AR hidden danger position, and displaying a simulation running image in the simulation window;
the hidden danger feedback information determining module 460 is configured to determine hidden danger feedback information according to the simulated operation image.
In one possible implementation, when there are multiple hidden danger components, the apparatus further includes:
The system comprises an acquisition association component module, a hidden danger component acquisition module and a hidden danger component generation module, wherein the acquisition association component module is used for acquiring association components of each hidden danger component and determining association types of each association component and the corresponding hidden danger component according to actual operation data of each association component, wherein the association types comprise active association and passive association;
the hidden danger component grade determining module is used for determining hidden danger component grades corresponding to each hidden danger component based on the number of the associated components of each hidden danger component and the associated type of each associated component;
The window display information determining module is used for determining window display information corresponding to each hidden danger component according to the level of each hidden danger component and window display mapping relation, and adjusting a corresponding simulation window based on the window display information corresponding to each hidden danger component, wherein the window display mapping relation is the corresponding relation between the level of the hidden danger component and the window size and the lighting color.
In one possible implementation manner, the hidden danger component level determining module is specifically configured to, when determining the hidden danger component level corresponding to each hidden danger component based on the number of associated components of each hidden danger component and the association type of each associated component:
Acquiring component linkage information of a charging pile to be detected, and determining the degree of association between each associated component and a corresponding hidden danger component according to the component linkage information;
Determining an association node diagram of each hidden danger component according to each hidden danger component, the association type of the corresponding association component of each hidden danger component and the association degree between the corresponding hidden danger component and the corresponding hidden danger component;
Determining a preset association region in each association node diagram, and identifying the number of final association components and each final association type in the corresponding preset association region of each hidden danger component;
determining the influence score corresponding to each hidden danger component according to the number of the final association components corresponding to each hidden danger component, each final association type and the score mapping relation, wherein the score mapping relation is the corresponding relation between the number of the final association components, the final association type and the influence score;
And determining the hidden danger component grade corresponding to each hidden danger component according to the influence score and grade mapping relation of each hidden danger component, wherein the grade mapping relation is the corresponding relation between the influence score and the hidden danger component grade.
In one possible implementation, the apparatus further includes:
the condition judging module is used for judging whether the number of the final association components in the corresponding preset association area of each hidden danger component and each final association type meet preset conditions or not;
the adjusting range module is used for adjusting the range of the preset association area until the number of final association components and each final association type in the adjusted preset association area meet the preset condition when the preset condition is not met;
the preset conditions comprise:
The number of the final association components is lower than a preset threshold; and, in addition, the method comprises the steps of,
The ratio of the final association components of different final association types does not exceed a preset scale range.
In one possible implementation manner, the determining AR charging pile model module 420 is specifically configured to, when performing data superposition on actual charging data and a preset charging pile model corresponding to a charging pile to be detected to obtain an AR charging pile model:
Identifying charging pile characteristics of a charging pile to be detected, and determining a preset charging pile model corresponding to the charging pile to be detected according to the charging pile characteristics and a model mapping relation, wherein the model mapping relation is a corresponding relation between the charging pile characteristics and the preset charging pile model;
identifying each preset component in a preset charging pile model and operation support information corresponding to each preset component;
Determining the actual operation data corresponding to each preset component according to the operation support information and the actual charging data corresponding to each preset component;
and (3) superposing the actual operation data corresponding to each preset assembly to the corresponding position in the preset charging pile model to obtain the AR charging pile model.
In one possible implementation manner, the determining simulated operation image module 440 is specifically configured to, when determining the predicted operation data of the hidden danger component in the preset time period according to the historical grid data, the charging vehicle data, and the actual operation data of the hidden danger component:
determining a required charging period and a required charging power according to the charging vehicle data;
Determining historical power grid power corresponding to the required time period according to the historical power grid data, and adjusting required charging power according to the historical power grid power to obtain adjusted charging power;
And according to the charging time period, the charging power and the actual operation data of the hidden danger component, determining the predicted operation data of the hidden danger component in the preset time period.
In one possible implementation, the apparatus further includes:
The charging system comprises an on-site image acquisition module, a charging pile detection module and a charging pile detection module, wherein the on-site image acquisition module is used for acquiring a charging on-site image, and acquiring definition and integrity of preset features in different associated images when the features of articles in a charging vehicle are determined to be preset features according to the charging on-site image, wherein the associated images are images corresponding to acquisition equipment at the charging pile to be detected and other charging piles;
The target image determining module is used for determining a target image according to the definition and the integrity of preset features in different associated images and determining acquisition equipment corresponding to the target image as target equipment;
The charging scene score determining module is used for identifying charging scene features contained in the charging scene image, determining corresponding charging scene scores according to scene feature mapping relations, wherein the scene feature mapping relations are corresponding relations between charging scene features and the charging scene scores;
the charging time score determining module is used for obtaining the current charging time, determining a corresponding charging time score according to the mapping relation between the charging time and the charging time, wherein the charging time mapping relation is the corresponding relation between the charging time and the charging time score;
The target acquisition frequency determining module is used for determining the target acquisition frequency of the target equipment according to the charging scene score, the charging moment score and the acquisition frequency mapping relation.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the management system described above may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In an embodiment of the present application, as shown in fig. 5, a management system is provided, where a management system 500 shown in fig. 5 includes: a processor 501 and a memory 503. The processor 501 is coupled to a memory 503, such as via a bus 502. Optionally, the management system 500 may also include a transceiver 504. It should be noted that, in practical applications, the transceiver 504 is not limited to one, and the structure of the management system 500 is not limited to the embodiment of the present application.
The Processor 501 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. The processor 501 may also be a combination that implements computing functionality, such as a combination comprising one or more microprocessors, a combination of a DSP and a microprocessor, and the like.
Bus 502 may include a path to transfer information between the components. Bus 502 may be a PCI (PERIPHERAL COMPONENT INTERCONNECT, peripheral component interconnect standard) bus, or an EISA (Extended Industry Standard Architecture ) bus, or the like. The bus 502 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. 5, but not only one bus or one type of bus.
The Memory 503 may be, but is not limited to, ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, RAM (Random Access Memory ) or other type of dynamic storage device that can store information and instructions, EEPROM (ELECTRICALLY ERASABLE PROGRAMMABLE READ ONLY MEMORY ), 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 503 is used to store application code for performing the implementation of the present application and is controlled by the processor 501 for execution. The processor 501 is configured to execute the application code stored in the memory 503 to implement what is shown in the foregoing method embodiments.
Wherein the management system includes, but is 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 management system shown in fig. 5 is only an example, and should not be construed as limiting the functionality and scope of use of the embodiments of the present 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 (10)
1. A method of managing a charging pile, comprising:
acquiring actual charging data corresponding to a charging pile to be detected, wherein the actual charging data comprises actual power grid supply data and charging vehicle data;
the actual charging data and a preset charging pile model corresponding to the charging pile to be detected are subjected to data superposition to obtain an AR charging pile model, wherein the preset charging pile model comprises each preset component and safety limit value data corresponding to each preset component;
Identifying actual operation data corresponding to each preset component in the AR charging pile model, and determining hidden danger components in the AR charging pile model according to the actual operation data and the safety limit value data corresponding to each preset component;
according to historical power grid data, the charging vehicle data and actual operation data of the hidden danger assembly, determining predicted operation data of the hidden danger assembly in a preset time period, and performing simulated operation on the hidden danger assembly according to the predicted operation data to obtain a simulated operation image;
Determining an AR hidden danger position of the hidden danger component in the AR charging pile model, determining a simulation window according to the AR hidden danger position, and displaying the simulation running image in the simulation window;
And determining hidden danger feedback information according to the simulation running image.
2. The method of claim 1, further comprising, when there are a plurality of hidden trouble components:
Acquiring an association component of each hidden danger component, and determining an association type of each association component and a corresponding hidden danger component according to actual operation data of each association component, wherein the association type comprises active association and passive association;
determining hidden danger component grades corresponding to each hidden danger component based on the number of the associated components of each hidden danger component and the associated type of each associated component;
According to the level of each hidden danger component and the window display mapping relation, window display information corresponding to each hidden danger component is determined, a corresponding simulation window is adjusted based on the window display information corresponding to each hidden danger component, and the window display mapping relation is the corresponding relation between the level of the hidden danger component and the window size and the lighting color.
3. The method for managing a charging pile according to claim 2, wherein the determining the hidden danger component level corresponding to each hidden danger component based on the number of associated components of each hidden danger component and the association type of each associated component comprises:
acquiring component linkage information of the charging pile to be detected, and determining the degree of association between each associated component and the corresponding hidden danger component according to the component linkage information;
Determining an association node diagram of each hidden danger component according to each hidden danger component, the association type of the corresponding association component of each hidden danger component and the association degree between the corresponding hidden danger component and the corresponding hidden danger component;
Determining a preset association region in each association node diagram, and identifying the number of final association components and each final association type in the corresponding preset association region of each hidden danger component;
Determining the influence score corresponding to each hidden danger component according to the number of the final association components corresponding to each hidden danger component, each final association type and a score mapping relation, wherein the score mapping relation is the corresponding relation between the number of the final association components, the final association type and the influence score;
And determining the grade of the hidden danger component corresponding to each hidden danger component according to the influence score and the grade mapping relation of each hidden danger component, wherein the grade mapping relation is the corresponding relation between the influence score and the grade of the hidden danger component.
4. A method of managing a charging pile according to claim 3, further comprising:
judging whether the number of final association components in the corresponding preset association region of each hidden danger component and each final association type meet preset conditions or not;
when the preset condition is not met, adjusting the range of the preset association area until the number of final association components and each final association type in the adjusted preset association area meet the preset condition;
Wherein, the preset conditions include:
The number of the final association components is lower than a preset threshold; and, in addition, the method comprises the steps of,
The ratio of the final association components of different final association types does not exceed a preset scale range.
5. The method for managing charging piles according to claim 1, wherein the step of performing data superposition on the actual charging data and a preset charging pile model corresponding to the charging pile to be detected to obtain an AR charging pile model includes:
Identifying the charging pile characteristics of the charging pile to be detected, and determining a preset charging pile model corresponding to the charging pile to be detected according to the charging pile characteristics and a model mapping relation, wherein the model mapping relation is the corresponding relation between the charging pile characteristics and the preset charging pile model;
Identifying each preset component in the preset charging pile model and operation support information corresponding to each preset component;
Determining the actual operation data corresponding to each preset component according to the operation support information corresponding to each preset component and the actual charging data;
And the actual operation data corresponding to each preset component are overlapped to the corresponding position in the preset charging pile model to obtain an AR charging pile model.
6. The method of claim 5, wherein determining predicted operational data of the hidden danger component within a preset time period based on historical grid data, the charging vehicle data, and actual operational data of the hidden danger component comprises:
determining a required charging time period and required charging power according to the charging vehicle data;
Determining historical power grid power corresponding to the required charging time period according to the historical power grid data, and adjusting the required charging power according to the historical power grid power to obtain adjusted charging power;
And determining the predicted operation data of the hidden danger component in a preset time period according to the required charging time period, the adjusted charging power and the actual operation data of the hidden danger component.
7. The method of managing a charging pile according to claim 1, further comprising:
Acquiring a charging site image, and acquiring definition and integrity of preset features in different associated images when the features of articles in a charging vehicle are determined to be the preset features according to the charging site image, wherein the associated images are images corresponding to acquisition equipment at the charging pile to be detected and other charging piles;
Determining a target image according to the definition and the integrity of the preset features in different associated images, and determining acquisition equipment corresponding to the target image as target equipment;
Identifying charging scene characteristics contained in the charging scene image, and determining corresponding charging scene scores according to scene characteristic mapping relations, wherein the scene characteristic mapping relations are corresponding relations between the charging scene characteristics and the charging scene scores;
Acquiring the current charging time, and determining a corresponding charging time score according to a mapping relation between the charging time and the charging time, wherein the charging time mapping relation is a corresponding relation between the charging time and the charging time score;
And determining the target acquisition frequency of the target equipment according to the charging scene score, the charging moment score and the acquisition frequency mapping relation.
8. A charging pile management device, characterized by comprising:
The charging data acquisition module is used for acquiring actual charging data corresponding to the charging pile to be detected, wherein the actual charging data comprises actual power grid supply data and charging vehicle data;
Determining an AR charging pile model module, wherein the AR charging pile model module is used for carrying out data superposition on the actual charging data and a preset charging pile model corresponding to the charging pile to be detected to obtain an AR charging pile model, and the preset charging pile model comprises each preset component and safety limit value data corresponding to each preset component;
The hidden danger component determining module is used for identifying actual operation data corresponding to each preset component in the AR charging pile model and determining hidden danger components in the AR charging pile model according to the actual operation data and the safety limit value data corresponding to each preset component;
The simulation operation image determining module is used for determining prediction operation data of the hidden danger component in a preset time period according to historical power grid data, the charging vehicle data and actual operation data of the hidden danger component, and performing simulation operation on the hidden danger component according to the prediction operation data to obtain a simulation operation image;
the image display module is used for determining the AR hidden danger position of the hidden danger component in the AR charging pile model, determining a simulation window according to the AR hidden danger position and displaying the simulation running image in the simulation window;
And the hidden danger feedback information determining module is used for determining hidden danger feedback information according to the simulation running image.
9. A management system, the management system comprising:
at least one processor;
A memory;
at least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application configured to: a charging pile management method as defined in any one of claims 1 to 7.
10. A computer-readable storage medium, comprising: a computer program that can be loaded by a processor and that performs a method of managing a charging pile according to any one of claims 1-7 is stored.
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