CN111739194B - New energy automobile driving behavior analysis system and method - Google Patents
New energy automobile driving behavior analysis system and method Download PDFInfo
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- CN111739194B CN111739194B CN202010574107.2A CN202010574107A CN111739194B CN 111739194 B CN111739194 B CN 111739194B CN 202010574107 A CN202010574107 A CN 202010574107A CN 111739194 B CN111739194 B CN 111739194B
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Abstract
The invention discloses a system and a method for analyzing the running behavior of a new energy automobile, wherein the system comprises a plurality of cameras, a vehicle real-time distance measuring module, a vehicle electric quantity consumption real-time analyzing module, a vehicle running behavior judging unit, an external scene recording and identifying module and an intelligent processing platform, the plurality of cameras are arranged outside the vehicle and shoot the external environment of the vehicle, the vehicle real-time distance measuring module is used for measuring the distance between people and the vehicle and between the vehicles, the vehicle electric quantity consumption real-time analyzing module is used for analyzing the electric quantity consumption condition of the vehicle, the vehicle running behavior judging unit is used for analyzing the running habit of the vehicle, the external scene recording and identifying module is used for identifying different scenes of the vehicle and analyzing the same scene after marking, the intelligent processing platform is used for obtaining and backing up the real-time monitored data and aims at monitoring the electric quantity consumption of the new energy automobile in real time, and analyzing the vehicle power consumption by referring to the external factors.
Description
Technical Field
The invention relates to the field of driving behaviors, in particular to a system and a method for analyzing the driving behavior of a new energy automobile.
Background
The new energy automobile adopts unconventional automobile fuel as a power source (or adopts conventional automobile fuel and a novel vehicle-mounted power device), integrates advanced technologies in the aspects of power control and driving of the automobile, and forms an automobile with advanced technical principle, new technology and new structure.
The new energy automobile is also called as an alternative fuel automobile, and comprises a pure electric automobile, a fuel electric automobile and other automobiles which all use non-petroleum fuel, and also comprises a hybrid electric automobile, an ethanol gasoline automobile and other automobiles which partially use non-petroleum fuel. All new energy automobiles existing at present are included in the concept, and are specifically divided into six categories: hybrid electric vehicles, pure electric vehicles, fuel-electric vehicles, alcohol ether fuel vehicles, natural gas vehicles and the like.
The pure electric vehicle adopts single electric capacity as an energy storage power source, and the electric capacity is used as the energy storage power source to provide electric energy for the motor through electric quantity so as to drive the motor to run, thereby pushing the vehicle to run. The chargeable electric quantity of the pure electric vehicle mainly comprises lead-acid electric quantity, nickel-cadmium electric quantity, nickel-hydrogen electric quantity, lithium ion electric quantity and the like, and the electric quantities can provide power for the pure electric vehicle. Meanwhile, the pure electric vehicle stores electric energy through electric quantity, and the driving motor operates to enable the vehicle to normally run.
The hybrid electric vehicle has a vehicle whose main drive system is composed of at least two single drive systems that can be operated simultaneously, and the driving power of the hybrid electric vehicle depends mainly on the vehicle driving state of the hybrid electric vehicle: one is provided by a single drive system alone; the second is provided by a plurality of drive systems in common.
At present, new energy automobile is most electronic, and the electric quantity consumption of vehicle driving in-process mainly is to leaning on the manual work to go discernment electric quantity consumption unusual, but the difficult initiative discernment of electric quantity consumption abnormal data leads to the vehicle to have the battery loss unable to learn, and this application aims at carrying out real-time supervision to new energy automobile's electric quantity consumption, refers to external factor and carries out the analysis to vehicle electric quantity consumption.
Disclosure of Invention
The invention aims to provide a system and a method for analyzing the running behavior of a new energy automobile, so as to solve the problems in the prior art.
In order to achieve the purpose, the invention provides the following technical scheme:
a new energy automobile driving behavior analysis system comprises a plurality of cameras, a vehicle real-time distance measurement module, a vehicle electric quantity consumption real-time analysis module, a vehicle driving behavior judgment unit, an external scene recording and recognition module and an intelligent processing platform, wherein the vehicle real-time distance measurement module, the vehicle electric quantity consumption real-time analysis module, the vehicle driving behavior judgment unit and the external scene recording and recognition module are respectively connected with the intelligent processing platform through an intranet, and the vehicle real-time distance measurement module and the external scene recording and recognition module are respectively connected with the cameras through the intranet;
the vehicle driving behavior determination unit is used for analyzing driving habits of the vehicle, the external scene recording and recognition module is used for recognizing different scenes of the vehicle, the same scene is marked and analyzed, and the intelligent processing platform is used for acquiring and backing up data monitored in real time.
By adopting the technical scheme: the vehicle real-time ranging module comprises a man-vehicle distance ranging submodule, an adjacent vehicle distance ranging submodule and a vehicle passing near early warning submodule, wherein the man-vehicle distance ranging submodule and the adjacent vehicle distance ranging submodule comprise a range finder used for carrying out distance measurement inside, the man-vehicle distance ranging submodule is used for measuring the distance between a pedestrian and a vehicle, the adjacent vehicle distance ranging submodule is used for measuring the distance between the vehicle and the vehicle, the vehicle passing near early warning submodule is used for monitoring the distance between the vehicle and the person, the distance between the vehicle and the vehicle is smaller than a set threshold value, and the vehicle passing near early warning submodule carries out early warning on the distance broadcast between the vehicle and the person or the vehicle.
By adopting the technical scheme: the vehicle electric quantity consumption real-time analysis module comprises a driving road condition real-time monitoring submodule and an electric quantity use condition comparison analysis submodule, the driving road condition real-time monitoring submodule is used for detecting and judging the road condition of vehicle driving, the judging road condition comprises a normal road, a rugged road, a ramp road and a muddy road, the electric quantity use condition comparison analysis submodule is used for comparing the electric quantity rated use condition with the electric quantity actual condition, and the electric quantity consumption condition is analyzed.
By adopting the technical scheme: the electric quantity use condition comparison and analysis submodule sets the electric quantity consumption of a normal road condition to be a rated electric quantity use condition, sets the influence rate of a rugged road condition to the electric quantity consumption every 50 kilometers to be 3%, the influence rate of a ramp road condition to the electric quantity consumption to be 5%, the influence rate of a muddy road condition to the electric quantity consumption to be 5%, sets the driving distance of a current vehicle to be L0 kilometers, sets the battery capacity of the current vehicle to be M (unit: kwh), sets the road condition of the current driving to comprise a normal road, a rugged road, a ramp road and a muddy road, wherein the electric quantity consumption is not additionally increased under the normal road condition, sets the estimated battery consumption of each 50 kilometers of the vehicle to be C0, sets the estimated electric quantity consumption after the current driving to be C, and according to a formula:
C0＝M-[M*(1-3％)*(1-5％)*(1-5％)]
calculating to obtain the estimated power consumption of the current vehicle running as C, sending the estimated power consumption of the vehicle obtained by analysis to a power use condition comparison and analysis submodule, setting the current actual power consumption as Rc by the power use condition comparison and analysis submodule, and when the actual power consumption is Rc
Judging that the actual electric quantity consumption of the current vehicle is within a reasonable range, and when the actual electric quantity consumption is
And judging that the actual electric quantity consumption of the current vehicle is abnormal, and sending the monitored actual electric quantity consumption data of the current vehicle to the intelligent processing platform.
By adopting the technical scheme: the vehicle driving behavior judgment unit comprises a vehicle driving internal behavior analysis submodule and a driving process intelligent selection submodule, the vehicle driving internal behavior analysis submodule is used for monitoring and marking the temperature commonly used in the vehicle, the played song style and the driving speed interval which are adjusted by a vehicle owner during vehicle driving, the marked data are sent to the intelligent processing platform, the driving process intelligent selection submodule is used for deriving the data monitored by the vehicle driving internal behavior analysis submodule in the intelligent processing platform, and when the vehicle owner carries out the next driving behavior, the temperature, the humidity and the played song style inside the vehicle are intelligently adjusted.
By adopting the technical scheme: the external scene recording and identifying module comprises a vehicle scene route marking submodule and a vehicle map route searching submodule at the same time, wherein the vehicle scene route marking submodule at the same time is used for marking different scenes where a vehicle is parked and running routes, the scenes where the vehicle is parked most are screened out for different scenes, the screened scenes are subjected to time matching, the times of parking the vehicle in the same scene at the same time are marked, when the times are larger than a set threshold value, the place is sent to the vehicle map route searching submodule, and the vehicle map route searching submodule is used for planning the route of the scene parked most frequently at the next time for the vehicle owner to recommend when the vehicle is parked on the marked place after the vehicle owner restarts and starts the vehicle.
By adopting the technical scheme: the same-time vehicle scene route marking submodule marks different routes of vehicle driving, and the marked route is set to be L1、 L2、L3、…、Ln-1、LnSetting the number of driving times of different routes marked currently as A1、 A2、A3、…、An-1、AnSetting the number of driving times of a certain current driving route as B, and according to a formula:
when the calculated running times of a certain current running route meet the formula, the data of the route are sent to a vehicle map route searching submodule, the vehicle map route searching submodule limits the time of the running route, the time range of the starting time of the running route is set to be T1-T2, when the vehicle is at the time of T1-2-T2-2 (unit: h), the route of the most common parking scene is planned for the vehicle owner to be recommended, and when the calculated running times of the certain current running route do not meet the formula, the vehicle scene route marking submodule does not process at the same time.
By adopting the technical scheme: the intelligent processing platform comprises an intelligent voice broadcasting submodule and a monitoring data real-time backup uploading submodule, the intelligent voice broadcasting submodule is used for carrying out voice broadcasting when all modules need broadcasting, the monitoring data real-time backup uploading submodule is used for backing up data monitored by all the modules and uploading the backed-up data in real time.
A new energy automobile driving behavior analysis method comprises the following steps:
s1: the method comprises the following steps of utilizing a plurality of cameras to be arranged outside a vehicle to shoot an environment outside the vehicle;
s2: the vehicle real-time distance measurement module is used for measuring the distance between people and a vehicle and the distance between the vehicles;
s3: analyzing the electric quantity consumption condition of the vehicle by using a vehicle electric quantity consumption real-time analysis module;
s4: analyzing the driving habits of the vehicle by using a vehicle driving behavior determination unit;
s5: the method comprises the following steps of identifying different scenes of a vehicle by using an external scene recording and identifying module, and analyzing the same scene after marking;
s6: and acquiring and backing up the data monitored in real time by using an intelligent processing platform.
By adopting the technical scheme: the analysis method further comprises the following steps:
s1-1: the pedestrian-vehicle distance measuring submodule and the adjacent vehicle distance measuring submodule internally comprise distance measuring instruments for measuring distances, the pedestrian-vehicle distance measuring submodule is used for measuring the distance between a pedestrian and a vehicle, the adjacent vehicle distance measuring submodule is used for measuring the distance between the vehicle and the vehicle, and the vehicle passing-near early warning submodule broadcasts the distance between the vehicle and the person or the vehicle for early warning when the distance between the vehicle and the person is monitored and the distance between the vehicle and the vehicle is smaller than a set threshold value;
s2-1: the real-time monitoring submodule for the driving road conditions is used for detecting and judging the driving road conditions of the vehicle, wherein the judged road conditions comprise normal roads, rugged roads, ramp roads and muddy roads, and the electric quantity use condition comparison and analysis submodule compares the rated use condition of the electric quantity with the actual condition of the electric quantity and analyzes the electric quantity consumption condition;
s3-1: monitoring and marking the commonly used temperature, the played song style and the running speed interval in the vehicle, which are regulated by a vehicle owner during vehicle driving, by using a vehicle driving internal behavior analysis submodule, sending the marked data to an intelligent processing platform, leading out the data monitored by the vehicle driving internal behavior analysis submodule in the intelligent processing platform by using a running process intelligent selection submodule, and intelligently regulating the internal temperature, the internal humidity and the played song style of the vehicle when the vehicle owner carries out the next driving behavior;
s4-1: marking different scenes in which the vehicle is parked by using the vehicle scene route marking submodule at the same time, screening the scenes in which the vehicle is parked most in the different scenes, carrying out time matching on the screened scenes, marking the times of parking the vehicle in the same scene at the same time, sending the place to the vehicle map route searching submodule when the times are greater than a set threshold value, and planning the route of the most frequently parked scene at the next moment for the vehicle owner to recommend when the vehicle is parked at the marked place by the vehicle map route searching submodule and the vehicle owner restarts to start the vehicle;
s5-1: the intelligent voice broadcasting submodule is used for carrying out voice broadcasting when all the modules need broadcasting, the monitoring data real-time backup uploading submodule carries out backup on data monitored by all the modules, and the backup data is uploaded in real time.
Compared with the prior art, the invention has the beneficial effects that: the invention aims to monitor the electric quantity consumption of a new energy automobile in real time and analyze the electric quantity consumption of the automobile by referring to external factors;
utilize a plurality of cameras to set up in the vehicle outside, shoot vehicle external environment, vehicle real-time ranging module is used for people and car, the distance is carried out between the car and the car to the car, vehicle electric quantity consumption real-time analysis module is used for the electric quantity consumption condition of analysis vehicle, vehicle action of going decision unit is used for carrying out the analysis to the driving habit of vehicle, outside scene record identification module is used for discerning the different scenes of vehicle, carry out the analysis after the mark to same scene, intelligent processing platform is used for obtaining the back-up to real-time supervision's data.
Drawings
In order that the present invention may be more readily and clearly understood, a more particular description of the invention briefly described above will be rendered by reference to specific embodiments that are illustrated in the appended drawings.
Fig. 1 is a schematic block diagram of a new energy vehicle driving behavior analysis system according to the present invention;
FIG. 2 is a schematic step diagram of a new energy vehicle driving behavior analysis method according to the invention;
FIG. 3 is a schematic diagram illustrating specific steps of a new energy vehicle driving behavior analysis method according to the present invention;
fig. 4 is a schematic diagram of an implementation process of the new energy vehicle driving behavior analysis method of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1 to 4, in the embodiment of the invention, a system and a method for analyzing driving behaviors of a new energy automobile include a plurality of cameras, a vehicle real-time distance measurement module, a vehicle electric quantity consumption real-time analysis module, a vehicle driving behavior determination unit, an external scene recording and recognition module and an intelligent processing platform, wherein the vehicle real-time distance measurement module, the vehicle electric quantity consumption real-time analysis module, the vehicle driving behavior determination unit and the external scene recording and recognition module are respectively connected with the intelligent processing platform through an intranet, and the vehicle real-time distance measurement module and the external scene recording and recognition module are respectively connected with the plurality of cameras through the intranet;
the vehicle driving behavior determination unit is used for analyzing driving habits of the vehicle, the external scene recording and recognition module is used for recognizing different scenes of the vehicle, the same scene is marked and analyzed, and the intelligent processing platform is used for acquiring and backing up data monitored in real time.
By adopting the technical scheme: the vehicle real-time ranging module comprises a man-vehicle distance ranging submodule, an adjacent vehicle distance ranging submodule and a vehicle passing near early warning submodule, wherein the man-vehicle distance ranging submodule and the adjacent vehicle distance ranging submodule comprise a range finder used for carrying out distance measurement inside, the man-vehicle distance ranging submodule is used for measuring the distance between a pedestrian and a vehicle, the adjacent vehicle distance ranging submodule is used for measuring the distance between the vehicle and the vehicle, the vehicle passing near early warning submodule is used for monitoring the distance between the vehicle and the person, the distance between the vehicle and the vehicle is smaller than a set threshold value, and the vehicle passing near early warning submodule carries out early warning on the distance broadcast between the vehicle and the person or the vehicle.
By adopting the technical scheme: the vehicle electric quantity consumption real-time analysis module comprises a driving road condition real-time monitoring submodule and an electric quantity use condition comparison analysis submodule, the driving road condition real-time monitoring submodule is used for detecting and judging the road condition of vehicle driving, the judging road condition comprises a normal road, a rugged road, a ramp road and a muddy road, the electric quantity use condition comparison analysis submodule is used for comparing the electric quantity rated use condition with the electric quantity actual condition, and the electric quantity consumption condition is analyzed.
By adopting the technical scheme: the electric quantity use condition comparison and analysis submodule sets the electric quantity consumption of a normal road condition to be a rated electric quantity use condition, sets the influence rate of a rugged road condition to the electric quantity consumption every 50 kilometers to be 3%, the influence rate of a ramp road condition to the electric quantity consumption to be 5%, the influence rate of a muddy road condition to the electric quantity consumption to be 5%, sets the driving distance of a current vehicle to be L0 kilometers, sets the battery capacity of the current vehicle to be M (unit: kwh), sets the road condition of the current driving to comprise a normal road, a rugged road, a ramp road and a muddy road, wherein the electric quantity consumption is not additionally increased under the normal road condition, sets the estimated battery consumption of each 50 kilometers of the vehicle to be C0, sets the estimated electric quantity consumption after the current driving to be C, and according to a formula:
C0＝M-[M*(1-3％)*(1-5％)*(1-5％)]
calculating to obtain the estimated electric quantity consumption of the current vehicle running as C, sending the estimated electric quantity consumption of the vehicle obtained by analysis to an electric quantity use condition comparison and analysis submoduleSetting the current actual power consumption to Rc, when the actual power consumption is
Judging that the actual electric quantity consumption of the current vehicle is within a reasonable range, and when the actual electric quantity consumption is
And judging that the actual electric quantity consumption of the current vehicle is abnormal, and sending the monitored actual electric quantity consumption data of the current vehicle to the intelligent processing platform.
By adopting the technical scheme: the vehicle driving behavior judgment unit comprises a vehicle driving internal behavior analysis submodule and a driving process intelligent selection submodule, the vehicle driving internal behavior analysis submodule is used for monitoring and marking the temperature commonly used in the vehicle, the played song style and the driving speed interval which are adjusted by a vehicle owner during vehicle driving, the marked data are sent to the intelligent processing platform, the driving process intelligent selection submodule is used for deriving the data monitored by the vehicle driving internal behavior analysis submodule in the intelligent processing platform, and when the vehicle owner carries out the next driving behavior, the temperature, the humidity and the played song style inside the vehicle are intelligently adjusted.
By adopting the technical scheme: the external scene recording and identifying module comprises a vehicle scene route marking submodule and a vehicle map route searching submodule at the same time, wherein the vehicle scene route marking submodule at the same time is used for marking different scenes where a vehicle is parked and running routes, the scenes where the vehicle is parked most are screened out for different scenes, the screened scenes are subjected to time matching, the times of parking the vehicle in the same scene at the same time are marked, when the times are larger than a set threshold value, the place is sent to the vehicle map route searching submodule, and the vehicle map route searching submodule is used for planning the route of the scene parked most frequently at the next time for the vehicle owner to recommend when the vehicle is parked on the marked place after the vehicle owner restarts and starts the vehicle.
By adopting the technical scheme: the same-time vehicle scene route marking submodule pairMarking the vehicle on different routes, and setting the marked route as L1、 L2、L3、…、Ln-1、LnSetting the number of driving times of different routes marked currently as A1、 A2、A3、…、An-1、AnSetting the number of driving times of a certain current driving route as B, and according to a formula:
when the calculated running times of a certain current running route meet the formula, the data of the route are sent to a vehicle map route searching submodule, the vehicle map route searching submodule limits the time of the running route, the time range of the starting time of the running route is set to be T1-T2, when the vehicle is at the time of T1-2-T2-2 (unit: h), the route of the most common parking scene is planned for the vehicle owner to be recommended, and when the calculated running times of the certain current running route do not meet the formula, the vehicle scene route marking submodule does not process at the same time.
By adopting the technical scheme: the intelligent processing platform comprises an intelligent voice broadcasting submodule and a monitoring data real-time backup uploading submodule, the intelligent voice broadcasting submodule is used for carrying out voice broadcasting when all modules need broadcasting, the monitoring data real-time backup uploading submodule is used for backing up data monitored by all the modules and uploading the backed-up data in real time.
A new energy automobile driving behavior analysis method comprises the following steps:
s1: the method comprises the following steps of utilizing a plurality of cameras to be arranged outside a vehicle to shoot an environment outside the vehicle;
s2: the vehicle real-time distance measurement module is used for measuring the distance between people and a vehicle and the distance between the vehicles;
s3: analyzing the electric quantity consumption condition of the vehicle by using a vehicle electric quantity consumption real-time analysis module;
s4: analyzing the driving habits of the vehicle by using a vehicle driving behavior determination unit;
s5: the method comprises the following steps of identifying different scenes of a vehicle by using an external scene recording and identifying module, and analyzing the same scene after marking;
s6: and acquiring and backing up the data monitored in real time by using an intelligent processing platform.
By adopting the technical scheme: the analysis method further comprises the following steps:
s1-1: the pedestrian-vehicle distance measuring submodule and the adjacent vehicle distance measuring submodule internally comprise distance measuring instruments for measuring distances, the pedestrian-vehicle distance measuring submodule is used for measuring the distance between a pedestrian and a vehicle, the adjacent vehicle distance measuring submodule is used for measuring the distance between the vehicle and the vehicle, and the vehicle passing-near early warning submodule broadcasts the distance between the vehicle and the person or the vehicle for early warning when the distance between the vehicle and the person is monitored and the distance between the vehicle and the vehicle is smaller than a set threshold value;
s2-1: the real-time monitoring submodule for the driving road conditions is used for detecting and judging the driving road conditions of the vehicle, wherein the judged road conditions comprise normal roads, rugged roads, ramp roads and muddy roads, and the electric quantity use condition comparison and analysis submodule compares the rated use condition of the electric quantity with the actual condition of the electric quantity and analyzes the electric quantity consumption condition;
s3-1: monitoring and marking the commonly used temperature, the played song style and the running speed interval in the vehicle, which are regulated by a vehicle owner during vehicle driving, by using a vehicle driving internal behavior analysis submodule, sending the marked data to an intelligent processing platform, leading out the data monitored by the vehicle driving internal behavior analysis submodule in the intelligent processing platform by using a running process intelligent selection submodule, and intelligently regulating the internal temperature, the internal humidity and the played song style of the vehicle when the vehicle owner carries out the next driving behavior;
s4-1: marking different scenes in which the vehicle is parked by using the vehicle scene route marking submodule at the same time, screening the scenes in which the vehicle is parked most in the different scenes, carrying out time matching on the screened scenes, marking the times of parking the vehicle in the same scene at the same time, sending the place to the vehicle map route searching submodule when the times are greater than a set threshold value, and planning the route of the most frequently parked scene at the next moment for the vehicle owner to recommend when the vehicle is parked at the marked place by the vehicle map route searching submodule and the vehicle owner restarts to start the vehicle;
s5-1: the intelligent voice broadcasting submodule is used for carrying out voice broadcasting when all the modules need broadcasting, the monitoring data real-time backup uploading submodule carries out backup on data monitored by all the modules, and the backup data is uploaded in real time.
Example 1: the method comprises the following steps of defining conditions, setting the electricity consumption of normal road conditions as rated electricity consumption by the electricity usage comparison and analysis submodule, setting the influence rate of rugged road conditions on electricity consumption every 50 kilometers to be 3%, setting the influence rate of ramp road conditions on electricity consumption to be 5%, setting the influence rate of muddy road conditions on electricity consumption to be 5%, setting the driving distance of a current vehicle to be 210 kilometers, setting the battery capacity of the current vehicle to be 33kwh, setting the road conditions of the current driving to comprise normal roads, rugged roads, ramp roads and muddy roads, wherein the electricity consumption is not additionally increased by the normal road conditions, setting the estimated battery consumption of the vehicle to be C0 every 50 kilometers, setting the estimated electricity consumption after the current driving to be C, and according to a formula:
C0＝33-[33*(1-3％)*(1-5％)*(1-5％)]＝4.2kwh
and calculating to obtain the estimated power consumption of the current vehicle running as 17.64kwh, and sending the estimated power consumption of the vehicle obtained by analysis to the power use condition comparison and analysis submodule.
The electric quantity use condition comparison and analysis submodule sets the current actual electric quantity consumption to be 18.9kwh, and when the actual electric quantity consumption is
And judging that the actual electric quantity consumption of the current vehicle is within a reasonable range.
Example 2: the method comprises the following steps of defining conditions, setting the electricity consumption of normal road conditions as rated electricity consumption by the electricity usage comparison and analysis submodule, setting the influence rate of rugged road conditions on electricity consumption every 50 kilometers to be 3%, setting the influence rate of ramp road conditions on electricity consumption to be 5%, setting the influence rate of muddy road conditions on electricity consumption to be 5%, setting the driving distance of a current vehicle to be 128 kilometers, setting the battery capacity of the current vehicle to be 43kwh, setting the road conditions of the current driving to include normal roads, rugged roads and ramp roads, wherein electricity consumption is not additionally increased in the normal road conditions, setting the battery consumption of the vehicle every 50 kilometers to be C0, setting the estimated electricity consumption after the current driving to be C, and according to a formula:
C0＝43-[43*(1-3％)*(1-5％)]＝3.4kwh
and calculating to obtain the estimated power consumption of the current vehicle running as 8.7kwh, and sending the estimated power consumption of the vehicle obtained by analysis to the power use condition comparison and analysis submodule.
The electric quantity use condition comparison and analysis submodule sets the current actual electric quantity consumption to be 13.2kwh, and the actual electric quantity consumption is
And judging that the actual electric quantity consumption of the current vehicle is abnormal, and sending the monitored actual electric quantity consumption data of the current vehicle to the intelligent processing platform.
Example 3: and limiting conditions, wherein the vehicle scene route marking submodule marks different routes for the vehicle to run at the same time, and the marked route is set to be L1、L2、 L3、…、Ln-1、LnSetting the running times of different routes marked currently to be 4, 3, 2, 7, 3 and 1, setting the running times of the route driven currently to be 7, and according to a formula:
and when the calculated running times of a certain current running route meet the formula, sending the data of the route to a vehicle map route searching submodule, limiting the time of the running route by the vehicle map route searching submodule, setting the time range of the starting time of the running route to be 16: 00-19: 00, planning the route of the most frequent parking scene for the vehicle owner to recommend when the vehicle is at the moment of 14: 00-17: 00 (unit: h), and not processing by the vehicle scene route marking submodule at the same time when the calculated running times of the certain current running route do not meet the formula.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (1)
1. The utility model provides a new energy automobile action analysis system that traveles which characterized in that: the system comprises a plurality of cameras, a vehicle real-time distance measuring module, a vehicle electric quantity consumption real-time analysis module, a vehicle driving behavior judging unit, an external scene recording and identifying module and an intelligent processing platform, wherein the vehicle real-time distance measuring module, the vehicle electric quantity consumption real-time analysis module, the vehicle driving behavior judging unit and the external scene recording and identifying module are respectively connected with the intelligent processing platform through an intranet;
the system comprises a plurality of cameras, a vehicle real-time distance measuring module, an external scene recording and identifying module, an intelligent processing platform, a vehicle electric quantity consumption real-time analysis module, a vehicle driving behavior judgment unit, a driving road condition real-time monitoring submodule and an electric quantity use condition comparison and analysis submodule, wherein the plurality of cameras are arranged outside the vehicle and used for shooting the external environment of the vehicle, the vehicle real-time distance measuring module is used for measuring the distance between a person and the vehicle and between the person and the vehicle, the vehicle electric quantity consumption real-time analysis module is used for analyzing the electric quantity consumption condition of the vehicle, the external scene recording and identifying module is used for identifying different scenes of the vehicle, the same scene is marked and analyzed, the intelligent processing platform is used for obtaining and backing up the data monitored in real time, the vehicle electric quantity consumption real-time analysis module comprises the driving road condition real-time monitoring submodule and the electric quantity use condition comparison and analysis submodule, the driving road condition real-time monitoring submodule is used for detecting and judging the road conditions of the driving of the vehicle, and the road conditions comprise a normal road, a rugged road, a ramp road, a road, Muddy road, electric quantity situation of use contrastive analysis submodule is used for contrasting electric quantity rated service condition and electric quantity actual conditions, analyzes the electric quantity consumption condition, electric quantity consumption that electric quantity situation of use contrastive analysis submodule set for normal road conditions is rated electric quantity situation of use, sets for every 50 kilometers rugged road conditions and is 3% to the influence rate of electric quantity consumption, and the influence rate of ramp road conditions to electric quantity consumption is 5%, and muddy road conditions is 5% to the influence rate of electric quantity consumption, sets for current vehicle driving distance and is L0 kilometers, sets for the battery capacity of current vehicle and is M, the unit: kwh, set for the road conditions of current driving to contain normal road, rugged road, ramp road, muddy road, wherein normal road conditions do not additionally increase electric quantity consumption, set for every 50 kilometers vehicle to predict battery consumption as C0, set for the current driving end to predict electric quantity consumption as C, according to the formula:
C0=M-[M*（1-3%）*（1-5%）*（1-5%）]
C= C0* 
calculating to obtain the estimated power consumption of the current vehicle running as C, analyzing to obtain the estimated power consumption of the vehicle, sending the estimated power consumption to a power use condition comparison and analysis submodule, setting the current actual power consumption as Rc by the power use condition comparison and analysis submodule, and when the actual power consumption is equal to or less than Rc
Judging that the actual electric quantity consumption of the current vehicle is in a reasonable range, and judging that the actual electric quantity consumption is Rc >, when the actual electric quantity consumption is Rc >, the electric quantity consumption is in a reasonable range
Judging that the current actual electric quantity of the vehicle is abnormal in consumption, and sending the monitored current actual electric quantity consumption data of the vehicle to an intelligent processing platform;
the vehicle real-time distance measuring module comprises a man-vehicle distance measuring submodule, an adjacent vehicle distance measuring submodule and a vehicle passing-near early warning submodule, wherein the man-vehicle distance measuring submodule and the adjacent vehicle distance measuring submodule internally comprise a distance measuring instrument for measuring distances, the man-vehicle distance measuring submodule is used for measuring the distances between pedestrians and vehicles, the adjacent vehicle distance measuring submodule is used for measuring the distances between vehicles, the vehicle passing-near early warning submodule is used for early warning the distances between vehicles and people or vehicles when the distances between vehicles and people are monitored and the distances between vehicles are smaller than a set threshold value;
the vehicle driving behavior judgment unit comprises a vehicle driving internal behavior analysis submodule and a driving process intelligent selection submodule, wherein the vehicle driving internal behavior analysis submodule is used for monitoring and marking a frequently-used temperature, a played song style and a driving speed interval which are regulated by a vehicle owner during vehicle driving and sending marking data to an intelligent processing platform, the driving process intelligent selection submodule is used for deriving data monitored by the vehicle driving internal behavior analysis submodule in the intelligent processing platform, and intelligently regulating the internal temperature, humidity and played song style of a vehicle volume when the vehicle owner performs the next driving behavior;
the external scene recording and identifying module comprises a vehicle scene route marking submodule and a vehicle map route searching submodule at the same time, wherein the vehicle scene route marking submodule at the same time is used for marking different scenes where a vehicle is parked and a driving route, the scene where the vehicle is parked most is screened out of different scenes, the screened scenes are subjected to time matching, the times of parking the vehicle in the same scene at the same time are marked, when the times are larger than a set threshold value, the scenes with the marking times larger than the set threshold value are sent to the vehicle map route searching submodule, and the vehicle map route searching submodule is used for planning the route of the most frequently parked scene at the next time for a vehicle owner to recommend when the vehicle is parked on the scene with the marking times larger than the set threshold value after the vehicle owner restarts the vehicle;
the same-time vehicle scene route marking submodule marks different routes of vehicle driving, and the marked route is set to be L1、L2、L3、…、Ln-1、LnSetting the number of driving times of different routes marked currently as A1、A2、A3、…、An-1、AnSetting the number of driving times of a certain current driving route as B, and according to a formula:
B≥
（A1+A2+A3+…+An-1+An）
when the calculated running times of a certain current running route meet the formula, the data of the route are sent to a vehicle map route searching submodule, the vehicle map route searching submodule limits the time of the running route, the time range of the starting time of the running route is set to be T1-T2, when the vehicle is at the time of T1-2-T2-2, the route of the most frequent parking scene is planned for the vehicle owner to be recommended, and when the calculated running times of the certain current running route do not meet the formula, the vehicle scene route marking submodule does not process at the same time;
the intelligent processing platform comprises an intelligent voice broadcasting submodule and a monitoring data real-time backup uploading submodule, wherein the intelligent voice broadcasting submodule is used for carrying out voice broadcasting when all modules need to be broadcasted, and the monitoring data real-time backup uploading submodule is used for backing up data monitored by all modules and uploading the backed-up data in real time;
a new energy automobile driving behavior analysis method comprises the following steps:
s1: the method comprises the following steps of utilizing a plurality of cameras to be arranged outside a vehicle to shoot an environment outside the vehicle;
s2: the vehicle real-time distance measurement module is used for measuring the distance between people and a vehicle and the distance between the vehicles;
s3: analyzing the electric quantity consumption condition of the vehicle by using a vehicle electric quantity consumption real-time analysis module;
s4: analyzing the driving habits of the vehicle by using a vehicle driving behavior determination unit;
s5: the method comprises the following steps of identifying different scenes of a vehicle by using an external scene recording and identifying module, and analyzing the same scene after marking;
s6: acquiring and backing up real-time monitored data by using an intelligent processing platform;
the analysis method further comprises the following steps:
s1-1: the vehicle real-time distance measuring module comprises a pedestrian-vehicle distance measuring submodule and an adjacent vehicle distance measuring submodule, wherein a distance meter for measuring distance is arranged in the pedestrian-vehicle distance measuring submodule and the adjacent vehicle distance measuring submodule;
s2-1: the vehicle electric quantity consumption real-time analysis module comprises a driving road condition real-time monitoring submodule and an electric quantity use condition comparison analysis submodule, and the driving road condition real-time monitoring submodule is used for detecting and judging the driving road condition of the vehicle, wherein the judged road condition comprises a normal road, a rugged road, a ramp road and a muddy road, and the electric quantity use condition comparison analysis submodule compares the rated use condition of the electric quantity with the actual condition of the electric quantity and analyzes the electric quantity consumption condition;
s3-1: the vehicle driving behavior judgment unit comprises a vehicle driving internal behavior analysis submodule and a driving process intelligent selection submodule, the vehicle driving internal behavior analysis submodule is used for monitoring and marking the commonly used temperature, the played song style and the driving speed interval in the vehicle, which are adjusted by a vehicle owner during vehicle driving, and sending the marked data to the intelligent processing platform, the driving process intelligent selection submodule derives the data monitored by the vehicle driving internal behavior analysis submodule in the intelligent processing platform, and the vehicle volume internal temperature, humidity and the played song style are intelligently adjusted when the vehicle owner performs the next driving behavior;
s4-1: the external scene recording and identifying module comprises a vehicle scene route marking submodule and a vehicle map route searching submodule at the same time, different scenes where the vehicle is parked are marked by using the vehicle scene route marking submodule at the same time, the scene where the vehicle is parked most is screened out for different scenes, the screened scenes are subjected to time matching, the number of times that the vehicle is parked in the same scene at the same time is marked, when the number of times is larger than a set threshold value, the scene is sent to the vehicle map route searching submodule, and when the vehicle is parked on the marked scene, the vehicle map route searching submodule plans a route of the most frequently parked scene at the next time for the vehicle owner to recommend after the vehicle owner restarts the vehicle;
s5-1: the intelligent processing platform comprises an intelligent voice broadcasting submodule and a monitoring data real-time backup uploading submodule, voice broadcasting is carried out when all modules need broadcasting by using the intelligent voice broadcasting submodule, the monitoring data real-time backup uploading submodule backs up data monitored by all the modules, and the backed-up data is uploaded in real time.
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