CN113280830B - Data-driven specific driving scene vehicle screening and mileage checking method - Google Patents
Data-driven specific driving scene vehicle screening and mileage checking method Download PDFInfo
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C22/00—Measuring distance traversed on the ground by vehicles, persons, animals or other moving solid bodies, e.g. using odometers, using pedometers
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Abstract
The invention provides a data-driven method for screening and checking mileage of vehicles in a specific driving scene, which is characterized in that vehicle-mounted big data of a new energy automobile are considered from running states and information of various vehicles, hierarchical accurate screening of the specific driving scene (such as new energy vehicles specially used for training backing in driving schools) from the big data containing mass non-teaching vehicles is realized, and comprehensive and accurate checking of the mileage of the screened vehicles is realized by combining the vehicle speed and mileage information displayed by a vehicle instrument and the vehicle speed and mileage calculated from other angles, so that the method has a plurality of beneficial effects which are not possessed in the prior art.
Description
Technical Field
The invention belongs to the technical field of new energy automobile big data, and particularly relates to a method for screening driving school reversing vehicles and checking mileage based on new energy automobile big data.
Background
In some specific driving scenes (for example, new energy vehicles specially used for backyard training in teaching scenes such as driving schools) due to the small motion range and the existence of GPS accuracy errors, the existing method for calculating the driving mileage based on GPS positioning information is not suitable. The inverse warehouse occupies a quite high proportion in a use scene and is one of important consideration factors influencing the performance and the service life of the vehicle, so that the real-time monitoring and statistics of the accumulated mileage of the teaching vehicle are necessary to ensure normal teaching training. Compared with the traditional fuel vehicle, the new energy automobile has remarkable advantages in the aspects of vehicle-mounted data collection and processing, is more favorable for batch processing of vehicle screening and mileage checking of the garage-reversing vehicle, and avoids the heavy work of periodically and repeatedly screening vehicles from all vehicles for the garage-reversing training and checking mileage of a single vehicle. However, most of the existing new energy automobile mileage checking methods remove abnormal data through online mileage (such as meter panel mileage) and compare the abnormal data with GPS mileage of vehicle positioning information to obtain effective mileage of the vehicle. However, for the new energy automobile which is trained and returned to the garage in the driving school, the screening and checking work cannot be accurately finished due to the limitation of the relatively small effective movement range and the relatively large GPS error precision.
Disclosure of Invention
In view of this, the present invention is directed to solve the technical problem that there is no screening and mileage checking means for new energy vehicles in a specific driving scenario in the field, and provides a data-driven vehicle screening and mileage checking method in a specific driving scenario, in which steps S1 to S5 are performed to complete screening of vehicles in a backyard, and steps S6 to S8 are performed to check mileage of the screened vehicles, and the method is specifically based on the following steps:
s1, a database platform collects the following new energy vehicle data including new energy vehicles in a special driving scene: motor rotational speed, motor torque, instrument panel speed, battery pack current, vehicle position information (longitude, latitude), and forms a vehicle data set Q1;
s2, primarily selecting the data in the Q1, and screening the vehicles according to the proportion of the number of reversing frames in the data frames to obtain a vehicle data set Q2;
s3, screening a vehicle data set Q3 in a running state from the Q2 according to the current of the battery pack, and screening a vehicle data set Q4 based on the speed of an instrument panel;
s4, selecting data corresponding to the vehicle in a special driving scene from the Q4 based on the motor torque to obtain a vehicle data set Q5;
s5, screening a vehicle data set Q6 from the Q5 based on the vehicle activity range
S6, collecting relevant data of the vehicle corresponding to the Q6 by the database platform, calculating mileage according to the motor rotating speed and the motor torque, and determining initial accounting mileage by considering the result and the instrument panel mileage;
s7, calculating mileage change caused by abnormality according to abnormal conditions in vehicle running;
and S8, removing the mileage change caused by the abnormality from the initial accounting mileage, and finishing the final mileage check.
Further, the process of obtaining the vehicle data set Q2 in step S2 specifically includes:
determining the historical frame number n of each vehicle in the reverse state from the Q1 Go backwards N number of historical total frames Backward motion Ratio i between n ：
Screening out i n The data corresponding to vehicles greater than the predetermined value constitutes Q2.
Further, the process of obtaining the vehicle data sets Q3 and Q4 in step S3 specifically includes:
a) Screening out a data set Q3 in a normal operation state, namely a discharge state according to the current information i of the battery pack; wherein i <0 is a charged state, i >0 is a discharged state, and i =0 is a quiescent state;
b) Calculating a data frame V smaller than a preset value in historical instrument panel speed information of the vehicle corresponding to the Q3 Predetermined value Total number of frames V Total frame number The proportion of (A):
will i V The data corresponding to vehicles greater than the predetermined value constitutes Q4.
Further, the process of obtaining the vehicle data set Q5 in step S4 specifically includes:
for each vehicle corresponding to the data set Q4, an average value T in the data that the motor torque T is not equal to 0 in one day is calculated Average Screening of T Average >The data corresponding to the vehicle of T1 form Q5;
wherein T1 can be used for n different time periods T according to a sample vehicle which normally runs 1 ，t 2 ，…，t n The motor torque calculation of (a) yields:
further, the process of obtaining the vehicle data set Q6 in step S5 specifically includes:
calculating the central longitude and latitude of the moving range of each vehicle corresponding to the Q5 in a certain period:
where n represents the number of time periods in the period, t 1 ，t 2 ，…，t n Representing different time periods;
setting a range with a preset radius for each vehicle by taking the longitude and latitude of the center as the center of a circle, and setting the number X of frames with positioning information in the range in one day in historical data frames Number of frames in range The ratio is greater than a predetermined value:
the data corresponding to the vehicle of (b) constitutes Q6.
Further, the process of determining the initial accounting mileage in step S6 specifically includes:
the database platform collects the tire radius r and the transmission ratio i of the vehicle corresponding to the Q6 g Calculating the speed u of the vehicle by combining the motor speed omega a ：
Calculating the mileage of the vehicle per second:
summing to obtain the total calculated mileage:
S calculating mileage ＝S Calculating mileage (t 1) +S Calculating mileage (t 2) +…+S Calculating mileage (tn)
And taking the smaller value of the total calculated mileage and the instrument panel mileage as the initial calculated mileage.
Further, the process of calculating the change in mileage caused by the abnormality in step S7 specifically includes:
a) Calculating the mileage change caused by the abnormal rotating speed:
judging whether the rotating speed of the motor in the data has the condition that the continuous multi-frame numerical value is not changed and is not equal to 0, and recording the continuous frame number: from t 1 To t x Frame, computing from t 1 To t x Meter Panel mileage Change information of a vehicle during frame number, let t 1 Frame odometer reading S ω1 ，t x Frame odometer reading S ωx And the change of the mileage between two frames is recorded as S Abnormal rotational speed 1 ：
S Abnormal rotational speed 1 ＝S ωx -S ω1
The total abnormal revolution speed mileage including n times of abnormal revolution speeds is recorded as S Abnormal rotational speed ：
S Abnormal rotational speed ＝S Abnormal rotational speed 1 +S Abnormal rotational speed 2 +…+S Abnormal speed of rotation n ；
b) Calculating the change of mileage caused by current abnormality:
judging whether the current data in the data has the condition that the continuous multi-frame numerical value is unchanged and is not equal to 0, and recording the continuous frame number: from t 1 To t x Frame, computing from t 1 To t x Meter Panel mileage Change information of a vehicle during frame number, let t 1 Frame odometer reading S I1 ，t x Frame odometer reading S Ix And the change of the mileage between two frames is recorded as S Current anomaly 1 ：
S Current anomaly 1 ＝S tx —S I1
Then the total including n current anomaliesThe mileage with abnormal rotating speed is recorded as S Abnormality of current ：
S Abnormality of current ＝S Current anomaly 1 +S Current anomaly 2 +…+S Current anomaly n ；
c) Calculating mileage jump:
judging whether the range change in the data exceeds the preset distance between 2 continuous frames, and recording the range between two frames of data as W n (n =1, 2, 3, \ 8230;), then the total mileage jump is noted as W:
W＝W 1 +W 2 +…+W n 。
further, the mileage change caused by the exclusion of the abnormality in step S7 results in an effective calculated mileage:
S effectively calculating mileage ＝S Initial accounted mileage -S Abnormal rotational speed -S Abnormality of current -W
Effective calculated mileage S Effectively calculating mileage And S Mileage of instrument panel The smaller the two is as the final mileage check result.
The method provided by the invention considers the vehicle-mounted big data of the new energy automobile from various vehicle running states and information, realizes hierarchical accurate screening of the driving school dump vehicle from the big data containing mass non-teaching vehicles, and realizes comprehensive and accurate checking of the screened vehicle mileage by combining the vehicle speed and mileage information displayed by a vehicle instrument and the vehicle speed and mileage obtained by calculation from other angles, thereby having a plurality of beneficial effects which are not possessed by the prior art.
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FIG. 1 is a schematic flow chart of the method of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. 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.
The data-driven vehicle screening and mileage checking method for the specific driving scene, as shown in fig. 1, is specifically based on the following steps:
s1, a database platform collects the following new energy vehicle data including new energy vehicles in a special driving scene: motor speed, motor torque, instrument panel speed, battery pack current, vehicle position information (longitude, latitude), and forms a vehicle data set Q1;
s2, primarily selecting the data in the Q1, and screening the vehicles according to the proportion of the number of reversing frames in the data frames to obtain a vehicle data set Q2;
s3, screening a vehicle data set Q3 in a running state from the Q2 according to the current of the battery pack, and screening a vehicle data set Q4 based on the speed of the instrument panel;
s4, selecting a vehicle data set Q5 under a special driving scene from the Q4 based on the motor torque;
s5, screening a vehicle data set Q6 from the Q5 based on the vehicle activity range
S6, collecting relevant data of the vehicle corresponding to the Q6 by the database platform, calculating mileage according to the motor rotating speed and the motor torque, and determining initial accounting mileage by considering the result and the instrument panel mileage;
s7, calculating mileage change caused by abnormality according to abnormal conditions in vehicle running;
and S8, removing the mileage change caused by the abnormality from the initial accounting mileage, and finishing the final mileage check.
In a preferred embodiment of the present invention, the process of obtaining the vehicle data set Q2 in step S2 specifically includes:
determining the historical frame number n of each vehicle in the reverse state from the Q1 Go backwards Ratio i to historical frame number n n ：
For driving school vehicles, on the premise of large sample data, the proportion of the number of frames in a forward state to the number of frames in a reverse state in the data is obviously different from the proportion of other vehicles in normal running, so that i can be screened out n >Data corresponding to 40% of the vehicles constitutes Q2.
The process of obtaining the vehicle data sets Q3 and Q4 in step S3 specifically includes:
a) Screening out a data set Q3 in a normal operation state, namely a discharge state according to the current information i of the battery pack; wherein i <0 is a charging state, i >0 is a discharging state, and i =0 is a static state;
b) Calculating a data frame v less than 30km/h in historical instrument panel speed information of a vehicle corresponding to the Q3 Predetermined value Total number of frames v Total frame number The proportion of (A):
will i V Data for > 70% of vehicles constitutes Q4.
The process of obtaining the vehicle data set Q5 in step S4 specifically includes:
for the driving school vehicle, because the driving school vehicle is in a low-speed running state for a long time and is frequently started and stopped, the torque of the driving school vehicle is larger than the average value of other vehicles, and therefore, for each vehicle corresponding to the data set Q4, the average value T in the data that the motor torque T is not equal to 0 in one day is calculated Average Screening of T Average The data corresponding to the vehicle with the speed more than T1 form Q5;
wherein T1 can be used for n different time periods T according to a sample vehicle which normally runs 1 ，t 2 ，…，t n The motor torque of (a) is calculated to obtain:
further, the process of obtaining the vehicle data set Q6 in step S5 specifically includes:
and (3) calculating the central longitude and latitude of each vehicle corresponding to the Q5 in the moving range in a certain period:
where n represents the number of time periods in the period, t 1 ，t 2 ，…，t n Representing different time periods;
setting a range with the radius of 20 meters by taking the longitude and latitude of the center as the center of a circle for each vehicle, and setting the number X of frames with positioning information in the range within one day in historical data frames Number of frames in range The ratio being greater than a predetermined value, i.e.
The data corresponding to the vehicle of (1) constitutes Q6.
The process of determining the initial mileage accounting in step S6 specifically includes:
the database platform collects the tire radius r and the transmission ratio i of the vehicle corresponding to the Q6 g Calculating the speed u of the vehicle by combining the motor speed omega a ：
Calculating the mileage per second of the vehicle:
summing to obtain the total calculated mileage:
S calculating mileage ＝S Calculating mileage (t 1) +S Calculating mileage (t 2) +…+S Calculating mileage (tn)
And taking the smaller value of the total calculated mileage and the instrument panel mileage as the initial calculated mileage.
Further, the process of calculating the mileage change caused by the abnormality in step S7 specifically includes:
a) Calculating the mileage change caused by the abnormal rotating speed:
judging whether the rotating speed of the motor in the data has the condition that the value of continuous 20 frames (20 seconds) is not changed and is not equal to 0, and recording the continuous frame number: from t 1 To t x Frame, computing from t 1 To t x Meter gauge change information for a vehicle during a frame number, let t 1 Frame odometer reading is S ω1 ，t x Frame odometer reading S ωx And the change of the mileage between two frames is recorded as S Abnormal rotational speed 1 ：
S Abnormal rotational speed 1 ＝S ωx -S ω1
The total abnormal revolution speed mileage including the n times of abnormal revolution speed is recorded as S Abnormality of rotational speed ：
S Abnormality of rotational speed ＝S Abnormal rotational speed 1 +S Abnormal rotational speed 2 +…+S Abnormal speed n ；
b) Calculating the change of mileage caused by current abnormality:
judging whether the current data in the data has the condition that the value of continuous 20 frames (20 seconds) is unchanged and is not equal to 0, and recording the continuous frame number: from t 1 To t x Frame, computing from t 1 To t x Meter gauge change information for a vehicle during a frame number, let t 1 Frame odometer reading S I1 ，t x Frame odometer reading is S Ix If the mileage change between two frames is recorded as S Current anomaly 1 ：
S Current anomaly 1 ＝S lx -S I1
The total abnormal rotating speed mileage including n times of current abnormality is marked as S Abnormality of current ：
S Abnormality of current ＝S Current anomaly 1 +S Current anomaly 2 +…+S Abnormal current n ；
c) Calculating mileage jump:
judging the existence of mileage variation in the dataIn the case of the change exceeding 0.01km between the continuous 2 frames, the mileage between two frames of data is recorded as W n (n =1, 2, 3, \ 8230;), then the total mileage jump is noted as W:
W＝W 1 +W 2 +…+W n 。
further, the mileage change caused by the exclusion of the abnormality in step S7 results in an effective calculated mileage:
S effectively calculating mileage ＝S Initial accounted mileage -S Abnormal rotational speed -S Abnormality of current -W
Effective calculated mileage S Effectively calculating mileage And S Mileage of instrument panel The smaller the two is as the final mileage check result.
For the instrument panel mileage information, the mileage information corresponding to the first frame can be recorded as S t1 The mileage information corresponding to the nth frame is S tn And calculating the instrument panel mileage of the vehicle as S Mileage of instrument panel ＝S tn -S t1 。
It should be understood that, the sequence numbers of the steps in the embodiments of the present invention do not mean the execution sequence, and the execution sequence of each process should be determined by the function and the inherent logic of the process, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (7)
1. The data-driven method for screening and checking the mileage of the vehicle in the specific driving scene is characterized in that: the method is specifically based on the following steps:
s1, a database platform collects the following new energy vehicle data including new energy vehicles in a special driving scene: the method comprises the following steps of (1) forming a vehicle data set Q1 by motor rotating speed, motor torque, instrument panel speed, battery pack current and longitude and latitude position information of a vehicle;
s2, initially selecting data in the Q1, and screening out data corresponding to vehicles with the ratio between the number of the historical frames in the reverse state and the total number of the historical frames larger than a preset value to obtain a vehicle data set Q2;
s3, screening a vehicle data set Q3 in a running state from the Q2 according to the current of the battery pack, and screening to obtain a vehicle data set Q4 based on the speed of an instrument panel;
s4, selecting a vehicle data set Q5 under a special driving scene from the Q4 based on the motor torque;
s5, screening a vehicle data set Q6 from the Q5 based on the vehicle activity range;
s6, collecting relevant data of the vehicle corresponding to the Q6 by the database platform, calculating mileage according to the motor rotating speed and the motor torque, and determining initial accounting mileage by considering the calculated mileage and instrument panel mileage;
s7, calculating mileage change caused by abnormality according to the abnormal condition of the running vehicle;
and S8, removing the mileage change caused by the abnormality from the initial accounting mileage, and finishing the final mileage check.
2. The method of claim 1, wherein: the process of obtaining the vehicle data sets Q3 and Q4 in step S3 specifically includes:
a) Screening out a data set Q3 in a normal operation state, namely a discharge state according to the current information i of the battery pack; wherein i <0 is a charging state, i >0 is a discharging state, and i =0 is a rest state;
b) Calculating a data frame V smaller than a preset value in historical instrument panel speed information of the vehicle corresponding to the Q3 Predetermined value Total number of frames V Total frame number The proportion of (A):
will i V The data corresponding to vehicles greater than the predetermined value constitutes Q4.
3. The method of claim 1, wherein: the process of obtaining the vehicle data set Q5 in step S4 specifically includes:
for each vehicle corresponding to the data set Q4, an average value T in the data that the motor torque T is not equal to 0 in one day is calculated Average Screening of T Average >The data corresponding to the vehicle of T1 form Q5;
wherein T1 can be used for n different time periods T according to a sample vehicle which normally runs 1 ，t 2 ，…，t n The motor torque of (a) is calculated to obtain:
4. the method of claim 1, wherein: the process of obtaining the vehicle data set Q6 in step S5 specifically includes:
and (3) calculating the central longitude and latitude of each vehicle corresponding to the Q5 in the moving range in a certain period:
where n represents the number of time periods in the period, t 1 ，t 2 ，…，t n Representing different time periods;
setting a range with a preset radius for each vehicle by taking the longitude and latitude of the center as the center of the circle, and setting the number X of frames with the position information in one day in the range in the historical data frames Number of frames in range In proportion of
Data composition corresponding to vehicle larger than preset valueQ6。
5. The method of claim 1, wherein: the process of determining the initial mileage accounting in step S6 specifically includes:
the database platform collects the tire radius r and the transmission ratio i of the vehicle corresponding to the Q6 g Calculating the speed u of the vehicle by combining the motor speed omega a ：
Calculating the mileage per second of the vehicle:
summing to obtain the total calculated mileage:
S calculating mileage ＝S Calculating mileage (t 1) +S Calculating mileage (t 2) +…+S Calculating mileage (tn)
And taking the smaller value of the total calculated mileage and the instrument panel mileage as the initial calculated mileage.
6. The method of claim 1, wherein: the process of calculating the mileage change caused by the abnormality in step S7 specifically includes:
a) Calculating the total mileage change caused by the abnormal rotating speed:
judging whether the rotating speed of the motor in the data has the condition that the continuous multi-frame numerical value is not changed and is not equal to 0, and recording the continuous frame number: from t th 1 To t x Frame, computing from t 1 To t x Meter Panel mileage Change information of a vehicle during frame number, let t 1 Frame odometer reading is S ω1 ，t x Frame odometer reading is S ωx If the mileage change between two frames is recorded as S Abnormal rotational speed 1 ：
S Abnormal rotational speed 1 ＝S ωx -S ω1
The total abnormal revolution speed mileage including n times of abnormal revolution speeds is recorded as S Abnormal rotational speed ：
S Abnormal rotational speed ＝S Abnormal rotational speed 1 +S Abnormal rotational speed 2 +…+S Abnormal speed n ；
b) Calculating the total mileage change caused by the current abnormality:
judging whether the current data in the data has the condition that the continuous multi-frame numerical value is unchanged and is not equal to 0, and recording the continuous frame number: from t 1 To t th x Frame, computing from t 1 To t x Meter Panel mileage Change information of a vehicle during frame number, let t 1 Frame odometer reading S I1 ，t x Frame odometer reading is S Ix And the change of the mileage between two frames is recorded as S Current anomaly 1 ：
S Current anomaly 1 ＝S Ix -S I1
The total abnormal rotating speed mileage including n times of current abnormality is marked as S Abnormality of current ：
S Abnormality of current ＝S Current anomaly 1 +S Current anomaly 2 +…+S Abnormal current n ；
c) Calculating total mileage jump:
judging whether the range change in the data exceeds the preset distance between 2 continuous frames, and recording the range between two frames of data as W n N =1, 2, 3, \8230, then the total mileage jump is marked as W:
W＝W 1 +W 2 +…+W n 。
7. the method of claim 6, wherein: and step 7, removing the mileage change caused by the abnormality to obtain an effective calculated mileage:
S effectively calculating mileage ＝S Initial accounted mileage -S Abnormality of rotational speed -S Abnormality of current -W
Effective calculated mileage S Effectively calculating mileage And S Mileage of instrument panel The smaller the two is as the final mileage check result.
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