CN112732452A - Electric vehicle internet of things management and control method and system based on edge calculation - Google Patents
Electric vehicle internet of things management and control method and system based on edge calculation Download PDFInfo
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Abstract
The invention discloses an electric vehicle internet of things management and control method and a system based on edge calculation, which comprises edge node processing and background processing; the edge node processing comprises acquiring vehicle body information; judging whether the vehicle body information meets a preset abnormal condition, if so, summarizing related information, generally referring the summarized information as a problem information set, and sending the problem information set to a preset supervision platform for background processing; the background processing comprises the following steps: acquiring a problem information set; judging whether an information node corresponding to the identification information exists in a preset GIS map, and if so, storing a problem information set to the corresponding information node; if not, an information node is newly built and used for storing the problem information set; and judging whether the integrity of the vehicle body is lower than a preset threshold value, if so, judging that the accident problem occurs to the vehicle body corresponding to the problem information set. The electric vehicle control system has the effects of assisting relevant units to control electric vehicle groups and reducing traffic safety hidden dangers and economic losses.
Description
Technical Field
The application relates to the field of Internet of things, in particular to an electric vehicle Internet of things management and control method and system based on edge computing.
Background
The electric bicycle, also called electric moped and battery car, is a relatively environment-friendly and convenient trip choice because the electric bicycle is simple to ride and does not need to be refueled, and is widely popularized in China.
As the population of electric vehicle users increases, the various problems associated therewith also increase year by year. Besides the general theft problem, the related units and groups face more important traffic safety hidden trouble caused by electric vehicles, which is mainly caused by the following points: firstly, the user group is relatively complex, and has a plurality of underage and old users, so that the safety consciousness is relatively weak; secondly, partial workers who ride the electric vehicle to take away and sell the electric vehicle run the red light at high speed due to time driving and violation of traffic rules; and thirdly, the quality of the electric vehicle is not controlled due to the abnormity of a power system and a brake system.
In view of the troubles and economic losses caused by frequent accidents of the electric vehicles to relevant units and groups, the application provides a new technical scheme.
Disclosure of Invention
In order to assist relevant units to control electric vehicle groups and reduce potential traffic safety hazards and economic losses, the application provides an electric vehicle internet of things control method and system based on edge calculation.
In a first aspect, the application provides an electric vehicle internet of things management and control method based on edge calculation, which adopts the following technical scheme:
an electric vehicle internet of things management and control method based on edge calculation comprises edge node processing and background processing;
the edge node processing includes:
acquiring vehicle body information; the vehicle body information comprises identity information, position information, speed information, battery information, brake information and vehicle body integrity information; the identity information comprises a vehicle body sequence and a brand to which the vehicle body belongs; judging whether the vehicle body information meets a preset abnormal condition, if so, summarizing the vehicle body information, the abnormal judgment result and the identification information of the node, and collectively referring the summarized information as a problem information set, and sending the problem information set to a preset supervision platform for background processing; wherein the identification information comprises an identification sequence and position information;
the background processing comprises the following steps:
acquiring a problem information set;
judging whether an information node corresponding to the identification information exists in a preset GIS map, and if so, storing a problem information set to the corresponding information node; if not, an information node is newly established and used for storing the problem information set;
judging whether the integrity of the vehicle body is lower than a preset threshold value, if so, judging that the accident problem occurs to the vehicle body corresponding to the problem information set; if not, judging that the vehicle body corresponding to the problem information set has a non-accident problem;
respectively counting the number of non-accident and accident vehicle bodies in each information node within a time period T1;
counting the number of the accident car bodies by taking T1 as unit time according to a time axis and generating a chart;
counting the number of the accident car bodies of each information node, and generating a ranking chart according to the number of the accident car bodies;
acquiring the weather type of the edge node when the problem information set is obtained; and determining weather types when the vehicle body information corresponding to each brand accords with abnormal conditions, counting the number according to the weather types respectively, and generating an environmental interference chart.
Optionally, the background processing further includes:
counting the number of non-accident and accident vehicle bodies of each brand in a time period T2, and generating a comparison chart of each brand; and carrying out classified statistics on the non-accident vehicle bodies in the brand comparison chart according to the abnormal judgment result to obtain the number of the non-accident vehicle bodies of each brand under each abnormal condition.
Optionally, the edge node processing further includes judging a sequence that the vehicle integrity information, the speed information, the battery information and the brake information meet the abnormal condition, and if the vehicle integrity information meets the abnormal condition and the sequence is the last, adding a quality accident mark in the problem information set;
the background processing further comprises:
determining the vehicle body with the quality accident mark as an accident vehicle body;
counting the number of vehicle bodies with quality accident marks of each brand according to the identity information, and generating a ranking table of quality accidents of each brand; and counting the number of the vehicles with the same brand quality according to the sequence that the vehicle integrity information accords with the abnormal conditions, and obtaining the number of the vehicles corresponding to each sequence.
Optionally, the background processing further includes:
calculating the probability of accidents of each brand of vehicle body of each weather type according to the environmental interference back chart every time period T3, generating environmental interference accident probability information, and sending the information to an edge node or an electric vehicle user for edge calculation;
the edge node processing further comprises the step of sending the information to the electric vehicle user when the information of the probability of the environmental interference accident is obtained.
Optionally, the background processing further includes:
determining a landmark building within X kilometers of the periphery of the node generating the problem information set; wherein X is a value other than 0;
counting problem information of buildings with the same sign, and accumulating the number of accident vehicles to obtain the ranking of the number of accidents near each sign building; and sending a ranking of the number of accidents occurring in the vicinity of each landmark building to the user at intervals of time T4.
In a second aspect, the application provides an electric vehicle internet of things management and control system based on edge computing, which adopts the following technical scheme:
the utility model provides an electric motor car thing allies oneself with management and control system based on edge calculation, includes on-vehicle module, edge node, supervision backstage and user terminal, its characterized in that: the vehicle-mounted module comprises an OBU unit and a plurality of sensors used for acquiring vehicle body information, the sensors are connected to the OBU unit, edge nodes are connected to the OBU unit and configured to be used for achieving edge node processing of the method as above, a supervision background is connected to the edge nodes and configured to be used for achieving background processing of the method as above, the user terminal is connected to the supervision background, and the user terminal comprises any one or more of a mobile phone, a tablet and a computer.
In summary, the present application includes at least one of the following beneficial technical effects:
1. the system can assist related personnel such as traffic polices and the like to know when, where and under what conditions traffic accidents are easy to occur in the supervision area, so as to reasonably distribute police force and the like, and reduce the occurrence probability and economic loss of the traffic accidents;
2. the method can facilitate each brand manufacturer to know the product defects of the manufacturer and guide the improvement direction of subsequent products;
3. the convenience of customers knows the probability and the quality condition of each brand electric motor car accident, for buying the electric motor car and making reference, still can improve the safety consciousness to its accident suggestion simultaneously in the use.
Drawings
FIG. 1 is a block diagram of the system architecture of the present application;
FIG. 2 is a block flow diagram of the edge node processing of the present application;
FIG. 3 is a block flow diagram of a background process of the present application.
Detailed Description
The present application is described in further detail below with reference to figures 1-3.
The embodiment of the application discloses an electric vehicle internet of things management and control method based on edge calculation. Referring to fig. 1-3, the electric vehicle internet of things management and control method based on edge calculation includes edge node processing and background processing, wherein the edge node processing is realized by a road side unit RUS, the road side unit RUS communicates with an OBU unit installed on an electric vehicle through a DSRC protocol, and the OBU unit connects a plurality of sensing modules installed on the electric vehicle to send vehicle body information to the road side unit RUS for edge calculation; and then, the road side unit RUS sends the information processed by the edge node to a supervision platform (such as a cloud deck) through a wireless network for background processing.
The edge node processing includes:
acquiring vehicle body information; and judging whether the vehicle body information meets a preset abnormal condition, if so, summarizing the vehicle body information, the abnormal judgment result and the identification information of the node, and collectively referring the summarized information as a problem information set, and sending the problem information set to a preset supervision platform for background processing.
The vehicle body information comprises identity information, position information, speed information, battery information, brake information and vehicle body integrity information of the electric vehicle. The identity information comprises an OBU unit written in the electric vehicle by a manufacturer before the electric vehicle leaves the factory, and is used for distinguishing the serial number and the brand of each electric vehicle; the position information is acquired by a GPRS module installed on the electric vehicle, the speed information is acquired by a vehicle speed sensor, and the battery information is acquired by a battery of the electric vehicle which is monitored by a storage battery electric quantity sensor and a voltage/current transducer in a combined mode; the brake information is obtained by the potentiometer connected and linked with the brake through an integrated board and matched with the speed information judgment, if: the potentiometer outputs 1, the speed is reduced by 10, and the brake degree is 5 percent; the integrity of the vehicle body is determined according to the pressure values of a plurality of pressure sensors installed inside the vehicle shell, such as: 1, if a non-key node sensor is pressed by 10 percent, the sensor is damaged by 5 percent; 1, if the key node sensor is pressed by 10 percent, the damage is 20 percent; and each sensor acquires corresponding information and then outputs the information to the OBU unit so as to ensure that subsequent edge calculation is smoothly executed.
Based on the vehicle body information, the abnormal condition includes:
1. the battery electric quantity loss rate exceeds a preset threshold, the electric quantity index drops, and the voltage/current rapidly increases and exceeds a normal threshold;
2. battery information is normal, but speed is 0;
3. the brake information changes in a non-preset digital relation and exceeds a maximum allowable value;
4. the vehicle body integrity is broken beyond a threshold and a multi-point sensor is triggered, or a designated key sensor is triggered beyond a threshold.
The abnormal condition is that related workers are preset in the RUS through the cradle head, so that the RUS can preliminarily process partial information, uploading of a large amount of unnecessary data is reduced, and pressure of the server for supporting the background is reduced. In order to distinguish each RUS unit, the node identification information is preset, the identification information comprises the identification serial number and the position information of the node, and the position information can be acquired by the extended GPRS module and can also be manually written by a worker according to the installation position of the node.
After the abnormal conditions of all nodes are judged, if the vehicle body information does not conform to the abnormal conditions, keeping the set frequency and an OBU unit on the vehicle body to perform data interaction, and releasing connection after the set frequency and the OBU unit are separated from the communication distance; and if the exception is met, handing over to the background for processing according to the above.
The background processing comprises the following steps:
acquiring a problem information set; judging whether an information node corresponding to the identification information exists in a preset GIS map (determined according to map coordinates and node positions), and if so, storing a problem information set to the corresponding information node; if not, the inode is newly created and used to store the problem information set.
In order to save background cost, the cleaning time of the information nodes is set, such as: and cleaning data for more than 1 year.
The background (supervision platform) needs to analyze data besides filing data according to coordinates, so background processing further comprises:
judging whether the integrity of the vehicle body is lower than a preset threshold value, if so, judging that the accident problem occurs to the vehicle body corresponding to the problem information set; if not, judging that the vehicle body corresponding to the problem information set has a non-accident problem;
respectively counting the number of non-accident and accident vehicle bodies of each information node in a time period T1 (such as 1 calendar day);
counting the number of the accident car bodies by taking T1 as unit time according to a time axis and generating a chart; and counting the number of the accident car bodies of each information node, and generating a ranking chart according to the number.
And if the problem information is concentrated with the information that the integrity of the vehicle body conforms to the abnormity, the vehicle body is directly determined to be the accident problem vehicle body.
The relevant staff, such as: after the traffic police combines the GIS map, the traffic police can relatively clearly know which time in the supervision area is more prone to accidents through the chart of the number of accident vehicles obtained according to the time axis; and the accident multi-occurrence positions of the supervision areas can be more intuitively known through the ranking chart, the assigned areas are managed by properly distributing related police strength, and traffic accidents and economic losses are reduced.
For better assisting relevant personnel such as traffic police, the background processing further comprises:
determining the landmark buildings (schools, hospitals and the like) within X kilometers of the nodes generating the problem information sets; wherein X is a value other than 0, such as: 0.5;
counting problem information of buildings with the same sign, and accumulating the number of accident vehicles to obtain the ranking of the number of accidents near each sign building; and sending the ranking of the number of accidents happening nearby each sign building to the user at intervals of a time period T4 (such as 1 month); the step generally requires the binding of the identity information of the user mobile phone and the electric vehicle, so that the background can send the relevant information.
According to the content, the method and the system can better assist the traffic police to know the accident frequently-occurring area and can also be used for prompting the user, so that the effect is relatively better.
Further, the background processing further includes:
acquiring the weather type of the edge node when the problem information set is obtained; and determining weather types when the vehicle body information corresponding to each brand accords with abnormal conditions, counting the number according to the weather types respectively, and generating an environmental interference chart.
On one hand, the chart can be supplied to each electric vehicle brand after environmental interference, so that the problem size of the product per se under various weathers can be conveniently summarized, and the work improvement direction can be guided; on the other hand, it can be provided for users and related persons as a reference for paying attention to the use of the electric vehicle in various weather.
Thus, the background process further comprises:
calculating the probability of accidents of each brand of vehicle body of each weather type according to the chart after environmental interference every time period T3 (such as one quarter), generating environmental interference accident probability information, and sending the information to an edge node or an electric vehicle user for performing edge calculation;
and the corresponding edge node processing also comprises the step of sending the information to the electric vehicle user when the information of the environmental interference accident probability is obtained.
The method for calculating the probability information of the environmental interference accident comprises the following steps:
the number of accidents occurring on a certain day type certain brand vehicle body/the total number of accidents occurring on the brand vehicle body.
If the environmental interference accident probability information is sent to the user from the background, the environmental interference accident probability information is directly sent to the mobile phone of the user through the short message, and therefore the mobile phone of the user needs to be bound with the identity information of the electric vehicle. If the environmental interference accident probability information is sent by the edge node, the RSU is in a broadcasting mode, the road side unit RSU is interacted with the OBU unit connected with the RSU, and therefore a small display connected with the OBU can be installed on the corresponding vehicle body to receive the prompt.
For making the product improvement better for the convenience of manufacturers, also provide more shopping reference bases for the electric vehicle user, the background processing further comprises:
counting the number of non-accident and accident car bodies of each brand in a time period T2 (such as one quarter), and generating a brand comparison chart; and carrying out classified statistics on the non-accident vehicle bodies in the brand comparison chart according to the abnormal judgment result to obtain the number of the non-accident vehicle bodies of each brand under each abnormal condition.
Accidents of electric vehicles are mainly divided into two categories according to responsibilities, wherein one category is caused by non-standard operation of users, such as: speeding and running red light; the other type is quality responsibility caused by production of each brand manufacturer, and in order to facilitate related personnel to know the cause of the accident vehicle body, the edge node processing is set to further comprise:
judging the sequence that the integrity information, the speed information, the battery information and the brake information of the vehicle body accord with the abnormal conditions, if the integrity information of the vehicle body accords with the abnormal conditions and the sequence is the last, adding a quality accident mark in the problem information set;
at this time, the background process further includes:
counting the number of vehicle bodies with quality accident marks of each brand according to the identity information, and generating a ranking table of quality accidents of each brand; counting the number of the vehicles with the quality of the same brand according to the sequence that the information of the integrity of the vehicles accords with the abnormal conditions, and obtaining the number of the vehicles respectively corresponding to each sequence, such as the sequence A, the brake abnormality in front and the integrity of the vehicle in the rear; and B, sequence, battery abnormality is in the front, and vehicle body integrity is in the back.
According to the content, related personnel can not only know the proportion of quality accidents of each brand, but also can more clearly know which quality problem causes the accidents.
For quality accident marking, the background processing also makes the following applications: and determining the vehicle body with the quality accident mark as an accident vehicle body to skip the background accident/non-accident judgment link, thereby saving calculation power.
The embodiment of the application discloses electric motor car thing allies oneself with management and control system based on edge calculation. Referring to fig. 1, the electric vehicle internet of things management and control system based on edge computing comprises a vehicle-mounted module, edge nodes, a supervision background and a user terminal.
The vehicle-mounted module comprises an OBU unit and a plurality of sensors (as described in the embodiment) for acquiring vehicle body information, wherein each sensor is connected with the OBU unit respectively so as to ensure smooth proceeding of edge calculation; the edge node comprises a plurality of Road Side Units (RSUs) which are respectively arranged beside the road, connected with the OBU units and configured to be used for realizing the edge node processing of the embodiment; the supervision background is connected to the edge node and configured for implementing the background processing as described in the above embodiments; the user terminal comprises any one or more of a mobile phone, a tablet and a computer.
In order to improve the management effect, the staff can also choose to improve the electric motor car, if: when the handle of the electric vehicle is a Hall handle, a speed-limiting unit is connected in parallel at the output side of the Hall handle, the speed-limiting unit comprises a speed-limiting resistor and an adaptive triode switch circuit, and the triode switch circuit is connected with the OBU unit; at the moment, related personnel with corresponding authority can send speed limit information to the background through a mobile phone and the like, the background sends the information to the edge node, and the information is sent to the corresponding OBU unit through the edge node so as to realize remote speed limit.
In summary, the method can assist traffic police and other related personnel to reasonably distribute police strength and the like, reduce the occurrence probability of traffic accidents and economic loss, and can also facilitate each brand manufacturer to know the defects of the product and guide the improvement direction of subsequent products; meanwhile, the shopping reference and the prompt in the using process can be provided for the user.
The above embodiments are preferred embodiments of the present application, and the protection scope of the present application is not limited by the above embodiments, so: all equivalent changes made according to the structure, shape and principle of the present application shall be covered by the protection scope of the present application.
Claims (6)
1. An electric vehicle internet of things management and control method based on edge calculation is characterized in that: the method comprises edge node processing and background processing;
the edge node processing includes:
acquiring vehicle body information; the vehicle body information comprises identity information, position information, speed information, battery information, brake information and vehicle body integrity information; the identity information comprises a vehicle body sequence and a brand to which the vehicle body belongs; judging whether the vehicle body information meets a preset abnormal condition, if so, summarizing the vehicle body information, the abnormal judgment result and the identification information of the node, and collectively referring the summarized information as a problem information set, and sending the problem information set to a preset supervision platform for background processing; wherein the identification information comprises an identification sequence and position information;
the background processing comprises the following steps:
acquiring a problem information set;
judging whether an information node corresponding to the identification information exists in a preset GIS map, and if so, storing a problem information set to the corresponding information node; if not, an information node is newly established and used for storing the problem information set;
judging whether the integrity of the vehicle body is lower than a preset threshold value, if so, judging that the accident problem occurs to the vehicle body corresponding to the problem information set; if not, judging that the vehicle body corresponding to the problem information set has a non-accident problem;
respectively counting the number of non-accident and accident vehicle bodies in each information node within a time period T1;
counting the number of the accident car bodies by taking T1 as unit time according to a time axis and generating a chart;
counting the number of the accident car bodies of each information node, and generating a ranking chart according to the number of the accident car bodies;
acquiring the weather type of the edge node when the problem information set is obtained; and determining weather types when the vehicle body information corresponding to each brand accords with abnormal conditions, counting the number according to the weather types respectively, and generating an environmental interference chart.
2. The electric vehicle internet of things management and control method based on edge calculation according to claim 1, characterized in that: the background processing further comprises:
counting the number of non-accident and accident vehicle bodies of each brand in a time period T2, and generating a comparison chart of each brand; and carrying out classified statistics on the non-accident vehicle bodies in the brand comparison chart according to the abnormal judgment result to obtain the number of the non-accident vehicle bodies of each brand under each abnormal condition.
3. The electric vehicle internet of things management and control method based on edge calculation according to claim 2, characterized in that: the edge node processing also comprises the step of judging the sequence that the vehicle body integrity information, the speed information, the battery information and the brake information accord with the abnormal conditions, if the vehicle body integrity information accords with the abnormal conditions and the sequence is the last, the quality accident mark is added in the problem information in a centralized way;
the background processing further comprises:
determining the vehicle body with the quality accident mark as an accident vehicle body;
counting the number of vehicle bodies with quality accident marks of each brand according to the identity information, and generating a ranking table of quality accidents of each brand; and counting the number of the vehicles with the same brand quality according to the sequence that the vehicle integrity information accords with the abnormal conditions, and obtaining the number of the vehicles corresponding to each sequence.
4. The electric vehicle internet of things management and control method based on edge calculation according to claim 1, characterized in that: the background processing further comprises:
calculating the probability of accidents of each brand of vehicle body of each weather type according to the environmental interference back chart every time period T3, generating environmental interference accident probability information, and sending the information to an edge node or an electric vehicle user for edge calculation;
the edge node processing further comprises the step of sending the information to the electric vehicle user when the information of the probability of the environmental interference accident is obtained.
5. The electric vehicle internet of things management and control method based on edge calculation according to claim 1, characterized in that: the background processing further comprises:
determining a landmark building within X kilometers of the periphery of the node generating the problem information set; wherein X is a value other than 0;
counting problem information of buildings with the same sign, and accumulating the number of accident vehicles to obtain the ranking of the number of accidents near each sign building; and sending a ranking of the number of accidents occurring in the vicinity of each landmark building to the user at intervals of time T4.
6. The utility model provides an electric motor car thing allies oneself with management and control system based on edge calculation, includes on-vehicle module, edge node, supervision backstage and user terminal, its characterized in that: the vehicle-mounted module comprises an OBU unit and a plurality of sensors for acquiring vehicle body information, the sensors are connected with the OBU unit, the edge nodes are connected with the OBU unit and are configured to be used for realizing edge node processing according to any one of the methods in claims 1-5, the supervision background is connected with the edge nodes and is configured to be used for realizing background processing according to any one of the methods in claims 1-5, the user terminal is connected with the supervision background, and the user terminal comprises any one or more of a mobile phone, a tablet and a computer.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110336958.8A CN112732452B (en) | 2021-03-30 | 2021-03-30 | Electric vehicle internet of things management and control method and system based on edge calculation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202110336958.8A CN112732452B (en) | 2021-03-30 | 2021-03-30 | Electric vehicle internet of things management and control method and system based on edge calculation |
Publications (2)
| Publication Number | Publication Date |
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| CN112732452A true CN112732452A (en) | 2021-04-30 |
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