CN116989817A - Energy equipment safety detection data transmission system and method based on data analysis - Google Patents
Energy equipment safety detection data transmission system and method based on data analysis Download PDFInfo
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- G—PHYSICS
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3492—Special cost functions, i.e. other than distance or default speed limit of road segments employing speed data or traffic data, e.g. real-time or historical
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3469—Fuel consumption; Energy use; Emission aspects
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- G—PHYSICS
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
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- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
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Abstract
The invention discloses a data analysis-based energy equipment safety detection data transmission system and a data analysis-based energy equipment safety detection data transmission method, which belong to the field of energy monitoring transmission. According to the invention, the energy loss caused by the driving behavior of the user is analyzed by analyzing the energy loss caused by the road conditions corresponding to each navigation route, the vehicle energy prediction model is constructed, the navigation route is comprehensively selected, the energy safety management of the electric automobile is realized, and the driving safety of the user is ensured.
Description
Technical Field
The invention relates to the field of energy monitoring and transmission, in particular to an energy equipment safety detection data transmission system and method based on data analysis.
Background
Along with the development of science and technology, electric vehicles are gradually popularized in daily life of people, and the electric vehicles are vehicles which use vehicle-mounted power supplies as power and drive wheels by motors to run and meet various requirements of road traffic and safety regulations, and have a relatively small influence on environment compared with the traditional vehicles, so that the electric vehicles have a wide prospect. The influence of the lithium battery on the electric automobile is of great importance. As a core component of an electric automobile, the performance of the lithium battery directly affects the performance of the electric automobile, including endurance mileage, safety, service life, charging time and the like.
In the running process of the electric automobile, people often use the existing navigation software to carry out route navigation, the existing navigation technology carries out route planning through a route planning algorithm according to the current position and the destination position of a user, however, the navigation mode has the defect of neglecting the energy consumption of the electric automobile, different road conditions can cause the situation that the user still has difficulty in reaching the destination even though the road conditions are shortest, the automobile is stopped in a road, and the situation that the automobile can leave after being refueled is different from the situation that the fuel automobile can leave, the electric automobile needs to use a specific charging pile for charging, and the charging time is long; meanwhile, because the driving behavior habits of users are different, the electric quantity loss conditions of the vehicle are also different, and the situation that the users are difficult to reach the destination and the energy use safety of the electric automobile and the driving safety of the users are threatened possibly caused by improper operation behaviors of the users.
It is necessary to analyze the energy loss caused by the road conditions of different navigation routes, reduce the energy loss, and reasonably arrange the routes according to the user behavior loss. Therefore, there is a need for a system and method for securely detecting data transmissions in an energy device for data analysis.
Disclosure of Invention
The invention aims to provide a data transmission system and a data transmission method for safety detection of energy equipment based on data analysis, so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: the energy equipment safety detection data transmission method based on data analysis comprises the following steps:
s1, acquiring an urban electronic map, acquiring a vehicle navigation route of a user, acquiring historical road condition information of the navigation route, and numbering each path node in the navigation route;
s2, road traffic condition information in the vehicle navigation routes is obtained in real time, and real-time road condition information corresponding to different vehicle navigation routes is analyzed to influence the energy consumption of the vehicle by combining the driving data of the user passing through the path nodes;
s3, analyzing behavior influence indexes of behavior habits of the user on energy loss of the vehicle under the condition of different navigation routes by combining behavior habit information of the user driving the vehicle under different road conditions, and constructing a vehicle energy prediction model by combining the analysis results in the step S2 to obtain energy loss driving schemes corresponding to different routes of the vehicle and energy loss comprehensive prediction indexes corresponding to the driving schemes;
and S4, arranging and displaying the scheme according to the comprehensive index of the energy loss from large to small, displaying the user through display equipment, and broadcasting the route through language.
Further, in step S1, the historical road condition information of the navigation route includes historical traffic flow data and environmental temperature information of the passing nodes;
the number of the a-th path node in the user navigation route is recorded as。
Further, in step S2, the following steps are included:
s201, acquiring the current position and the target position of a user, and acquiring a vehicle navigation route of the user for vehicle driving through a path planning algorithm, wherein the path planning algorithm is an important link in robot navigation and mainly means that the robot automatically plans a path from a starting point to a target point in a corresponding area, in the process, collision needs to be avoided, the path searching cost is low, and a set is formedWhere n is represented as the number of acquired vehicle navigation routes,denoted as the nth vehicle navigation route;
s202, when a user starts the vehicle, the vehicle is monitored in real time, a preset time interval is t, and the real-time position of the vehicle is acquired through positioning equipment to form a history position setWherein m is expressed as the number of position acquisitions, < >>Denoted as the mth position of the vehicle, the altitudes form the set +.>, wherein ,Indicated as vehicle in position->Corresponding elevation;
when the collected vehicle positions are on the same road, namely the user drives the vehicle to turn, the running parameter f is calculated through the following formula:
；
wherein G is represented as a decision function,
when (when)If the vehicle is indicated to be traveling straight, the determination is made +.>And->；
When (when)When the vehicle is represented as ascending, the method determines +.>And is also provided with；
When (when)When the vehicle is represented as a downhill, the determination of +.>And is also provided with；
Represented as a standard height difference, the value size is preset by the relevant technician,
represented as j-th position of the vehicle, < >>Expressed as position->Corresponding vehicle electric quantity remaining quantity,/">Expressed as position->A corresponding altitude;
denoted as (j-1) th position of the vehicle,>expressed as position->The remaining power of the corresponding vehicle is calculated,expressed as position->The corresponding altitude is set to be at the same level,
expressed as position->And position->The distance of travel between the two is j E (1, m]；
The elements in the set P are classified into three categories according to the altitude difference conditions of the corresponding positions, the first category is that the altitude difference values of the adjacent positions belong to the interval (0,) The second type is that the elevation difference between adjacent positions is greater than +.>The third type is that the altitude difference value of adjacent positions is smaller than 0, the running parameters are judged, and the predicted running parameters corresponding to three conditions are obtained through a clustering algorithm respectively>, wherein ,Expressed as altitude difference interval (0,/o>) The result after clustering of the driving parameters obtained at that time, < + >>Expressed as altitude difference greater than +.>The result after clustering of the driving parameters obtained at that time, < + >>And the result is expressed as a result after the running parameters obtained when the altitude difference is smaller than 0 are clustered. Clustering is a machine learning technique that involves grouping of data points. Given a set of data points, we can use a clustering algorithm to divide each data point into a particular set. Theoretically, data points in the same group should have similar attributes and/or characteristics, while data points in different groups should have highly different attributes and/or characteristics. Clustering is an unsupervised learning method, and is a common statistical data analysis technique in many fields.
Further, S203, regarding the ith vehicle navigation routeAcquiring a vehicle navigation route by combining a city electronic map and historical data>The elevation of the route node is obtained by the road traffic information in the road, and the elevation of the a-th route node is marked as +.>，
When the adjacent nodes are judged to be positioned on the same road by combining the electronic map, the elevation between the adjacent nodes is compared, and the energy loss is calculated by the following formulaAnd (3) performing calculation:
；
wherein ,represented as a loss decision function,
when (when)When it is, then determine->And->；
When (when)When it is, then determine->And->；
When (when)When it is, then determine->And->；
Route to routeAll the energy losses between adjacent nodes of the same road are calculated and summed to obtain the total loss of straight running as +.>，Expressed as the distance travelled between the a-1 th pathway node to the a-th pathway node;
s204, obtaining energy loss forming set of turning of the user driving vehicle according to the historical driving data of the userWherein r is denoted as number of turns, +.>The energy loss is expressed as the energy loss of the r-th turn, and the energy loss value is the difference value between the residual quantity of the electric quantity of the vehicle before the turn and the residual quantity of the electric quantity of the vehicle after the turn; for the ith vehicle navigation route +.>The number of turns required is obtained as w, the total loss of the form of turns is +.>And (3) performing calculation:
；
wherein k is represented as a variable;
the user passes through the vehicle navigation routeRoad total loss->The method comprises the following steps:；
S205, repeating the steps S201-S204 for all the vehicle navigation routes in the set X to obtain the total road loss corresponding to each vehicle navigation route.
Further, in step S3, the following steps are included:
s301, acquiring the foot brake change distance and the accelerator change distance through a distance sensor according to the real-time acquired user vehicle running data, presetting a time interval as T,
the foot brake change distances in the time interval form a setWherein u is denoted as the number of foot brake changes, < >>The change distance of the foot brake is expressed as the change distance of the user stepping on the foot brake for the u th time, and the change distance of the foot brake is expressed as the maximum descent distance of the foot brake stepping on once; braking energy loss forming set->, wherein ,The difference value is expressed as the difference value between the residual quantity of the electric quantity of the vehicle before the foot brake is stepped on for the u th time and the residual quantity of the electric quantity of the vehicle after the foot brake is stepped on;
the throttle change distances in the time interval form a setWherein v is expressed as the number of throttle changes, < >>The change distance of the accelerator is expressed as the change distance of the user when stepping on the accelerator for the v time, and the change distance of the accelerator is expressed as the maximum descent distance of the foot brake when stepping on the foot brake once; the energy loss of the accelerator forms a set ∈ ->, wherein ,The difference value is expressed as the difference value between the residual quantity of the electric quantity of the vehicle before the v-th accelerator pedal and the residual quantity of the electric quantity of the vehicle after the accelerator pedal;
s302, influencing the index of the behavior of the user through the following formulaAnd (3) performing calculation:
；
wherein ,expressed as a variable +.>E is expressed as Euler number, which is the base of natural logarithm, also known as Napi number,>denoted as the mean value of the brake energy losses in set B,/->Expressed as the set->Average value of energy loss of middle throttle;
s303, constructing an energy prediction model, and comprehensively predicting the energy loss of the vehicle driven by the user through the following formulaAnd (3) performing calculation:
；
wherein ,expressed as the remaining capacity of the current user vehicle, +.>Expressed as deriving a vehicle navigation route according to a path planning algorithm>Route length of>Expressed as a passing route->The time required to reach the destination;
when (when)When the navigation route is reserved, the current navigation route is reserved; when->When the current navigation route is screened out;
s304, repeating the steps S301-S303 on all the vehicle navigation routes to obtain the comprehensive prediction index of the energy loss of each corresponding route.
Further, in step S4, according to the analysis result of step S3, the schemes corresponding to the routes are arranged according to the order of the energy loss comprehensive indexes from large to small, and the schemes are displayed to the user through the display device and are broadcasted through the language.
The driving safety of the electric automobile is guaranteed, the situation that the electric automobile runs along the shortest route but cannot reach the electric automobile finally is avoided, the using efficiency of the energy of the electric automobile is improved, the reliability and the safety of the lithium battery for supplying energy to the electric automobile are guaranteed, and the using experience of the user is improved.
An energy device security detection data transmission system based on data analysis, the security detection data transmission system comprising: an energy safety analysis module is arranged on the device,
the energy safety analysis module is used for analyzing the energy loss prediction index of the electric automobile after the electric automobile runs through the navigation routes and comprises a road condition analysis unit and a behavior analysis unit, wherein the road condition analysis unit is used for analyzing the energy loss conditions caused by different road conditions corresponding to each navigation route according to historical data, and the behavior analysis unit is used for analyzing the conditions of energy loss caused by user behaviors in the running process of different navigation routes according to the historical behaviors of the user, constructing an energy prediction model and analyzing the comprehensive prediction index of the energy loss.
Further, the security detection data transmission system further includes: a data acquisition module of the vehicle is provided,
the output end of the vehicle data acquisition module is connected with the input end of the energy safety analysis module;
the vehicle data acquisition module is used for acquiring running data of the electric vehicle in real time and comprises a route navigation unit, a road condition acquisition unit and a running acquisition unit, wherein the route navigation unit is used for carrying out route navigation planning according to the current position and the destination of a user, the road condition acquisition unit is used for acquiring road conditions of a navigation route in combination with an electronic map, and the running acquisition unit is used for acquiring foot brake change distance and accelerator change distance through a distance sensor and carrying out data acquisition on the running condition of the user.
Further, the security detection data transmission system further includes: the data transmission module is used for transmitting the data,
the input end of the data transmission module is connected with the output end of the vehicle data acquisition module, the output end of the data transmission module is connected with the input end of the energy safety analysis module, and the output end of the energy safety analysis module is connected with the input end of the data transmission module;
the data transmission module is used for carrying out encryption transmission and storage on collected data and analysis results, and comprises an encryption transmission unit and an intelligent storage unit, wherein the encryption transmission unit carries out encryption transmission on the collected data and analysis results through an asymmetric encryption algorithm, so that the safety in the data transmission process is ensured, the threat of economic safety and personal safety of a user caused by user information leakage is avoided, the asymmetric encryption is also called public key encryption, and two keys are used: a public key and a private key. The public key may be public and can be used by anyone to encrypt a message, but only the holder of the private key can decrypt it. In asymmetric encryption, the public key and the private key are a pair of keys that are generated by a mathematical algorithm. Public keys can be widely distributed, while private keys must be kept secret; the intelligent storage unit stores the data in a cloud storage mode, so that the safety of the data is guaranteed, and the cloud storage is an online storage mode, namely, the data is stored on a plurality of virtual servers usually hosted by a third party, but not on a dedicated server. The service mode for storing the data in the cloud can avoid the risk of data loss caused by local equipment hardware faults, natural disasters and the like. Cloud storage may be provided by a large internet data center with back-end ready storage virtualized resources and provided in a storage resource pool that customers can use to store files or objects.
Further, the security detection data transmission system further includes: a user feedback module is provided for receiving the user feedback information,
the user feedback module is used for intelligently displaying the user according to the analysis result, and comprises a route display unit and a language broadcasting unit, wherein the route display unit is used for displaying the user through display equipment after arranging schemes corresponding to each navigation route according to the analysis result and the order of the energy loss comprehensive indexes from large to small, and the language broadcasting unit is used for broadcasting the route to the user through in-vehicle voice.
Compared with the prior art, the invention has the following beneficial effects:
according to the invention, route navigation planning is carried out according to the current position and the destination of the user, road conditions of the navigation routes are collected by combining with an electronic map, and the energy loss condition caused by the road conditions corresponding to each navigation route is analyzed to obtain the road total loss predicted value of each navigation route. The foot brake change distance and the accelerator change distance are acquired through the distance sensor, data acquisition is carried out on the running condition of the user, the behavior influence index caused by the driving behavior of the user is analyzed, the vehicle energy prediction model is constructed, the comprehensive energy loss prediction index is analyzed, the navigation route is comprehensively selected, the situation that the user follows the navigation route form but the energy of the final electric vehicle is insufficient to support the user to arrive at the destination is avoided, the energy safety management of the electric vehicle is carried out, and the running safety of the user is ensured.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of the steps of the method for transmitting safety detection data of an energy device based on data analysis of the present invention;
fig. 2 is a schematic diagram of the module composition of the safety detection data transmission system of the energy equipment based on data analysis.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-2, the present invention provides the following technical solutions: fig. 1 is a flowchart of the steps of the present invention, which includes the following steps:
s1, acquiring an urban electronic map, acquiring a vehicle navigation route of a user, acquiring historical road condition information of the navigation route, and numbering each path node in the navigation route;
in step S1, the historical road condition information of the navigation route includes historical traffic flow data and environmental temperature information of the passing nodes;
the number of the a-th path node in the user navigation route is recorded asThe route nodes are preset reference nodes in the electronic map, such as road intersections, urban landmark buildings and the like.
S2, road traffic condition information in the vehicle navigation routes is obtained in real time, and real-time road condition information corresponding to different vehicle navigation routes is analyzed to influence the energy consumption of the vehicle by combining the driving data of the user passing through the path nodes;
in step S2, the following steps are included:
s201, acquiring the current position and the target position of a user, and acquiring a vehicle navigation route of the user for vehicle driving through a path planning algorithm, wherein the path planning algorithm is an important link in robot navigation and is a main linkThe robot automatically plans a path from a starting point to a target point in a corresponding area, in the process, collision needs to be avoided, and the path searching cost is low, for example, dijkstra algorithm, A-x algorithm, PRM path planning algorithm and the like, so as to form a setWherein n is represented as the number of acquired vehicle navigation routes, < >>Denoted as the nth vehicle navigation route;
s202, when a user starts the vehicle, the vehicle is monitored in real time, a preset time interval is t, and the real-time position of the vehicle is acquired through positioning equipment, such as GPS or Beidou satellite navigation, and the like, so as to form a history position setWherein m is expressed as the number of position acquisitions, < >>Denoted as the mth position of the vehicle, the altitudes form the set +.>, wherein ,Indicated as vehicle in position->Corresponding elevation;
when the collected vehicle positions are on the same road, namely the user drives the vehicle to turn, the running parameter f is calculated through the following formula:
；
wherein G is represented as a decision function,
when (when)If the vehicle is indicated to be traveling straight, the determination is made +.>And->；
When (when)When the vehicle is represented as ascending, the method determines +.>And is also provided with；
When (when)When the vehicle is represented as a downhill, the determination of +.>And is also provided with；
Represented as a standard height difference, the value size is preset by the relevant technician,
represented as j-th position of the vehicle, < >>Expressed as position->Corresponding vehicle electric quantity remaining quantity,/">Expressed as position->A corresponding altitude;
denoted as (j-1) th position of the vehicle,>expressed as position->The remaining power of the corresponding vehicle is calculated,expressed as position->The corresponding altitude is set to be at the same level,
expressed as position->And position->The distance of travel between the two is j E (1, m]；
The elements in the set P are classified into three categories according to the altitude difference conditions of the corresponding positions, the first category is that the altitude difference values of the adjacent positions belong to the interval (0,) The second type is that the elevation difference between adjacent positions is greater than +.>The third type is that the altitude difference value of adjacent positions is smaller than 0, the running parameters are judged, and the predicted running parameters corresponding to three conditions are obtained through a clustering algorithm respectively>, wherein ,Expressed as altitude difference interval (0,/o>) The result after clustering of the driving parameters obtained at that time, < + >>Expressed as altitude difference greater than +.>The result after clustering of the driving parameters obtained at that time, < + >>And the result is expressed as a result after the running parameters obtained when the altitude difference is smaller than 0 are clustered. Clustering is a machine learning technique that involves grouping of data points. Given a set of data points, we can use a clustering algorithm to divide each data point into a particular set. Theoretically, data points in the same group should have similar attributes and/or characteristics, while data points in different groups should have highly different attributes and/or characteristics. Clustering is an unsupervised learning method, and is a common statistical data analysis technology in many fields, such as K-MEANS clustering algorithm, mean shift clustering algorithm, DBSCAN clustering algorithm and the like.
S203, regarding the ith vehicle navigation routeAcquiring a vehicle navigation route by combining a city electronic map and historical data>The elevation of the route node is obtained by the road traffic information in the road, and the elevation of the a-th route node is marked as +.>，
When the adjacent nodes are judged to be positioned on the same road by combining the electronic map, the elevation between the adjacent nodes is compared, and the energy loss is calculated by the following formulaAnd (3) performing calculation:
；
wherein ,represented as a loss decision function,
when (when)When it is, then determine->And->；
When (when)When it is, then determine->And->；
When (when)When it is, then determine->And->；
Route to routeAll the judgments in (1) are locatedCalculating the energy loss between adjacent nodes of the same road, and summing to obtain the total loss of straight running as +.>，Expressed as the distance travelled between the a-1 th pathway node to the a-th pathway node;
s204, obtaining energy loss forming set of turning of the user driving vehicle according to the historical driving data of the userWherein r is denoted as number of turns, +.>The energy loss is expressed as the energy loss of the r-th turn, and the energy loss value is the difference value between the residual quantity of the electric quantity of the vehicle before the turn and the residual quantity of the electric quantity of the vehicle after the turn; for the ith vehicle navigation route +.>The number of turns required is obtained as w, the total loss of the form of turns is +.>And (3) performing calculation:
；
wherein k is represented as a variable;
the user passes through the vehicle navigation routeRoad total loss->The method comprises the following steps:；
S205, repeating the steps S201-S204 for all the vehicle navigation routes in the set X to obtain the total road loss corresponding to each vehicle navigation route.
S3, analyzing behavior influence indexes of behavior habits of the user on energy loss of the vehicle under the condition of different navigation routes by combining behavior habit information of the user driving the vehicle under different road conditions, and constructing a vehicle energy prediction model by combining the analysis results in the step S2 to obtain energy loss driving schemes corresponding to different routes of the vehicle and energy loss comprehensive prediction indexes corresponding to the driving schemes;
in step S3, the following steps are included:
s301, acquiring the foot brake change distance and the accelerator change distance through a distance sensor according to the real-time acquired user vehicle running data, presetting a time interval as T,
the foot brake change distances in the time interval form a setWherein u is denoted as the number of foot brake changes, < >>The change distance of the foot brake is expressed as the change distance of the user stepping on the foot brake for the u th time, and the change distance of the foot brake is expressed as the maximum descent distance of the foot brake stepping on once; braking energy loss forming set->, wherein ,The difference value is expressed as the difference value between the residual quantity of the electric quantity of the vehicle before the foot brake is stepped on for the u th time and the residual quantity of the electric quantity of the vehicle after the foot brake is stepped on;
the throttle change distances in the time interval form a setWherein v is expressed as the number of throttle changes, < >>Represented asThe change distance of the throttle is stepped on by the user v times, and the change distance of the throttle is expressed as the maximum descent distance of the foot brake when the foot brake is stepped on once; the energy loss of the accelerator forms a set ∈ ->, wherein ,The difference value is expressed as the difference value between the residual quantity of the electric quantity of the vehicle before the v-th accelerator pedal and the residual quantity of the electric quantity of the vehicle after the accelerator pedal;
s302, influencing the index of the behavior of the user through the following formulaAnd (3) performing calculation:
；
wherein ,expressed as a variable +.>E is expressed as Euler number, which is the base of natural logarithm, also known as Napi number,>denoted as the mean value of the brake energy losses in set B,/->Expressed as the set->Average value of energy loss of middle throttle;
s303, constructing an energy prediction model, and comprehensively predicting the energy loss of the vehicle driven by the user through the following formulaAnd (3) performing calculation:
；
wherein ,expressed as the remaining capacity of the current user vehicle, +.>Expressed as deriving a vehicle navigation route according to a path planning algorithm>Route length of>Expressed as a passing route->The time required to reach the destination;
when (when)When the navigation route is reserved, the current navigation route is reserved; when->When the current navigation route is screened out;
s304, repeating the steps S301-S303 on all the vehicle navigation routes to obtain the comprehensive prediction index of the energy loss of each corresponding route.
And S4, arranging and displaying the scheme according to the comprehensive index of the energy loss from large to small, displaying the user through display equipment, and broadcasting the route through language.
In step S4, according to the analysis result of step S3, the schemes corresponding to the routes are arranged according to the order of the energy loss comprehensive indexes from large to small, and the schemes are displayed to the user through a display device, such as a vehicle-mounted computer or a mobile phone, and route broadcasting is performed through a language.
The driving safety of the electric automobile is guaranteed, the situation that the electric automobile runs along the shortest route but cannot reach the electric automobile finally is avoided, the using efficiency of the energy of the electric automobile is improved, the reliability and the safety of the lithium battery for supplying energy to the electric automobile are guaranteed, and the using experience of the user is improved.
Fig. 2 is a schematic diagram of a module composition of the present invention, where the security detection data transmission system for an energy device based on data analysis includes: an energy safety analysis module is arranged on the device,
the energy safety analysis module is used for analyzing the energy loss prediction index of the electric automobile after the electric automobile runs through the navigation routes and comprises a road condition analysis unit and a behavior analysis unit, wherein the road condition analysis unit is used for analyzing the energy loss conditions caused by different road conditions corresponding to each navigation route according to historical data, and the behavior analysis unit is used for analyzing the conditions of energy loss caused by user behaviors in the running process of different navigation routes according to the historical behaviors of the user, constructing an energy prediction model and analyzing the comprehensive prediction index of the energy loss.
The security detection data transmission system further includes: a data acquisition module of the vehicle is provided,
the output end of the vehicle data acquisition module is connected with the input end of the energy safety analysis module;
the vehicle data acquisition module is used for acquiring running data of the electric vehicle in real time and comprises a route navigation unit, a road condition acquisition unit and a running acquisition unit, wherein the route navigation unit is used for carrying out route navigation planning according to the current position and the destination of a user, the road condition acquisition unit is used for acquiring road conditions of a navigation route in combination with an electronic map, and the running acquisition unit is used for acquiring foot brake change distance and accelerator change distance through a distance sensor and carrying out data acquisition on the running condition of the user.
The security detection data transmission system further includes: the data transmission module is used for transmitting the data,
the input end of the data transmission module is connected with the output end of the vehicle data acquisition module, the output end of the data transmission module is connected with the input end of the energy safety analysis module, and the output end of the energy safety analysis module is connected with the input end of the data transmission module;
the data transmission module is used for carrying out encryption transmission and storage on collected data and analysis results, and comprises an encryption transmission unit and an intelligent storage unit, wherein the encryption transmission unit carries out encryption transmission on the collected data and analysis results through an asymmetric encryption algorithm, so that the safety in the data transmission process is ensured, the threat of economic safety and personal safety of a user caused by user information leakage is avoided, the asymmetric encryption is also called public key encryption, and two keys are used: a public key and a private key. The public key may be public and can be used by anyone to encrypt a message, but only the holder of the private key can decrypt it. In asymmetric encryption, the public key and the private key are a pair of keys that are generated by a mathematical algorithm. Public keys can be widely distributed, while private keys must be kept secret, and common asymmetric encryption algorithms include RSA, ECC and the like; the intelligent storage unit stores the data in a cloud storage mode, so that the safety of the data is guaranteed, and the cloud storage is an online storage mode, namely, the data is stored on a plurality of virtual servers usually hosted by a third party, but not on a dedicated server. The service mode for storing the data in the cloud can avoid the risk of data loss caused by local equipment hardware faults, natural disasters and the like. Cloud storage may be provided by a large internet data center with back-end ready storage virtualized resources and provided in a storage resource pool that customers can use to store files or objects.
The security detection data transmission system further includes: a user feedback module is provided for receiving the user feedback information,
the user feedback module is used for intelligently displaying the user according to the analysis result, and comprises a route display unit and a language broadcasting unit, wherein the route display unit is used for arranging schemes corresponding to each navigation route according to the analysis result from high to low according to the energy consumption comprehensive index, displaying the user through display equipment such as a vehicle-mounted computer or a mobile phone, and the language broadcasting unit is used for broadcasting the route of the user through in-vehicle voice.
Example 1.
If 20% of electric quantity of a certain electric automobile is remained, according to historical data, the electric quantity of the electric automobile can travel at a constant speed of 0.6 km, and 3 routes a, b and c exist for a user to go to a charging pile through navigation; route a is 0.56 km, but there are 3 uphill segments; route b is 0.58 km, but there are 4 intersections that need to turn; route c is 0.59 km and is a straight road segment with no turns or uphill.
According to the existing route navigation scheme, the display modes of the users are a, b and c according to the shortest path algorithm; however, because a and b have the condition of ascending and turning, the electric automobile is easy to be insufficient in energy source and insufficient in electric power to enable a user to reach a charging pile, and most likely to be stagnated in the center of a road, meanwhile, the electric automobile is started again and needs longer charging time than the refueling time of the tanker, and timely remedial measures are difficult to be taken as if the tanker is directly refueled and can be started, so that the running safety of the user is threatened. By the analysis of the invention, the route c is preferentially selected to be displayed for the user, so that the user can reach the charging pile before the electric quantity is exhausted, the use efficiency of the power supply is improved, and the use safety of the energy source and the personal safety of the user are ensured.
Example 2.
If the user is locatedElevation of 20, position->Is 50%>ThenThen->And->；
If the user usesAltitude via node a-1 is 20 and altitude via node a-1 is 30, thenThen->And->。
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
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