Vehicle mileage fuel consumption integral compensation longitude and latitude compensation method

Abstract

The invention provides a vehicle mileage fuel consumption integral compensation and longitude and latitude compensation method. A vehicle-mounted terminal, a cloud end and a map navigation system are included. Comprising the following steps: S1, data acquisition: collecting the running state and environment information of a vehicle; s2, the vehicle-mounted terminal uploads the collected data to a cloud end at a fixed frequency; s3, performing cloud analysis; s4, performing off-line statistical analysis, and correcting the acquired data; whether abnormal data points exist in the collected data or not is judged, averaging or interpolation is conducted on the abnormal data points through data of a plurality of moments before and after the abnormal data points, reasonable values of the abnormal data points at the moments are estimated, and the collected data are updated and corrected; according to the method, abnormal conditions in T-Box uploading data can be effectively processed, and the accuracy and reliability of mileage and fuel consumption data are ensured by using an integral method and a latitude and longitude compensation method. The method is of great significance to applications such as vehicle remote monitoring, motorcade management and driving behavior analysis.

Description

Technical Field

[0001] The present invention relates to the technical field of mileage fuel consumption compensation, and in particular to a method for compensating for latitude and longitude of vehicle mileage fuel consumption integral compensation. Background Art

[0002] In the field of vehicle telematics, location information and vehicle status data uploaded through vehicle terminals (such as T-Box) are the basis for vehicle monitoring, management and data analysis. Currently, many vehicles are equipped with T-Box to collect and transmit various vehicle data, including instrument mileage and ECU (Electronic Control Unit) fuel consumption. These data can be processed and analyzed in the cloud to calculate the vehicle's mileage and fuel consumption.

[0003] However, in the actual operation of the vehicle, various indicators collected and reported to the cloud may have jump points. For example, in the 808-2013 standard protocol, the 0200 position information is fixedly collected by the terminal and reported to the cloud at a transmission frequency of 30s, which includes mileage and fuel consumption information. Due to abnormal scenarios such as network signals, collection errors, and terminal errors, indicators such as mileage or fuel consumption may have jump points, resulting in the reported mileage of point A being 10,000km, the mileage of point B reported 30s later being 20,000km, and the mileage of point C reported 30s later being 5,000km. The value of the mileage increase far exceeds the actual 30s driving time, and this situation can be regarded as one of the jump points. Or the mileage decreases and jumps to some data that does not conform to the actual mileage, resulting in abnormal conditions in the data uploaded by the T-Box, affecting the calculation of mileage and fuel consumption in the cloud, and the accuracy and reliability of mileage and fuel consumption data cannot be guaranteed. In order to deal with the possible jump points or abnormal conditions in the instrument mileage and ECU fuel consumption data reported by the T-Box, a compensation method is urgently needed. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a method for compensating for latitude and longitude of vehicle mileage fuel consumption integral compensation.

[0005] To achieve the above object, the present invention adopts the following technical solutions: A method for compensating vehicle mileage fuel consumption points and longitude and latitude, comprising a vehicle terminal, a cloud and a map navigation system; The custom configurations in the cloud include the average mileage threshold, the average fuel consumption threshold, and the jump threshold; the jump threshold includes the jump mileage threshold and the jump fuel consumption threshold; The following steps are involved: S1: Data collection; The vehicle-mounted terminal collects data, including the vehicle's operating status and environmental information; The vehicle's operating status includes speed, mileage, and fuel consumption; The environmental information includes GPS location information; the GPS location information includes longitude, latitude, GPS time and altitude; S2: The vehicle terminal uploads the collected data to the cloud at a fixed frequency; The collected GPS location information, speed, mileage, and fuel consumption are transmitted to the cloud at a fixed transmission frequency; S3: Cloud analysis; After receiving the collected data uploaded by the vehicle terminal, the cloud analyzes it, obtains GPS location information, speed, mileage, fuel consumption and stores it in the order of GPS time; S4: Perform offline statistical analysis and correct the collected data; Perform historical backtracking in days, query the data of the entire vehicle history, obtain the GPS location information, speed, mileage, fuel consumption in the collected data, and determine whether there are abnormal data points in the collected data. For the abnormal data points, average or interpolate the data of several moments before and after to estimate the reasonable value of the abnormal data point, update and correct the collected data, output the mileage data and fuel consumption data for statistics, sort the output mileage data and fuel consumption data according to GPS time, form a vehicle trajectory playback, perform statistical analysis in the cloud, and calculate the vehicle fuel consumption statistics; S5: data fusion and final retransmission; Add the corrected mileage and fuel consumption to the instrument mileage and ECU total fuel consumption of the abnormal data point.

[0006] Further, step S4 includes: S41: Determine whether there is any abnormality in the collected data; Determine whether there is an abnormality based on two consecutive data points of the collected data: First, the difference between the mileage and fuel consumption of two consecutive data points is cyclically compared to see if it exceeds the jump threshold. If so, it is judged that an abnormality has occurred. If not, there is no abnormality. The difference between the mileage of the data point with a later GPS time and the mileage of the data point with an earlier GPS time is used. If the difference exceeds the jump mileage threshold, the mileage of the data point with a later GPS time is abnormal. The difference between the fuel consumption of the data point with a later GPS time and the fuel consumption of the data point with an earlier GPS time is used. If the difference exceeds the jump fuel consumption threshold, the fuel consumption of the data point with a later GPS time is abnormal. Secondly, the mileage difference between two consecutive data points is compared cyclically. The mileage of the data point with later GPS time is subtracted from the mileage of the data point with earlier GPS time to get the mileage difference. It is determined whether the mileage difference is less than 0. If so, it is determined that the mileage of the data point with later GPS time is abnormal. S42: The abnormal data point data is corrected by integral compensation, and the corrected data is output for cloud statistical analysis; When an abnormal data point is determined to exist, the data collected at several times before and after the abnormal data point is averaged or interpolated to estimate the reasonable value of the abnormal data point at that moment, and the reasonable value is output for cloud-based statistical analysis; S43: Correction mileage of abnormal data point longitude and latitude compensation; Through GPS location information, the map matching algorithm is used to match the actual driving trajectory of the vehicle with the road network and correct the mileage data; Obtain GPS location information of the benchmark points and abnormal data points. The GPS location information includes longitude and latitude. Use the map matching algorithm to match the actual driving trajectory of the vehicle with the road network. Combined with the road network, obtain the actual road mileage. Use the benchmark points plus the actual road mileage to correct the mileage data. S44: Output the compensated mileage and fuel consumption for cloud-based statistical analysis.

[0007] The corrected mileage and fuel consumption are obtained and merged with the output mileage data and fuel consumption data, sorted according to GPS time, forming a vehicle trajectory playback, and statistical analysis is performed in the cloud to calculate vehicle fuel consumption statistics.

[0008] Furthermore, the speed includes instrument speed and GPS speed; The mileage includes meter mileage, total meter mileage, and integral mileage; The fuel consumption includes: ECU total fuel consumption and integrated fuel consumption; When judging an abnormality, the priority judgment method is used for analysis, including: S411: Determine whether the meter mileage is abnormal, and determine whether to output the meter mileage; The instrument mileage is given the first priority, and the mileage data for statistical analysis of cloud mileage is output. The instrument mileage in the stored collected data is obtained, and the difference of the instrument mileage of two consecutive data points is cyclically compared. First, the instrument mileage difference is compared with the jump mileage threshold to determine whether it exceeds the jump mileage threshold. If it exceeds, it is determined that the mileage of the data point with the later GPS time is abnormal, and S412 is executed. Otherwise, it is determined whether the instrument mileage difference is less than 0. If so, it is determined that the mileage of the data point with the later GPS time is abnormal, and S412 is executed. If not, the instrument mileage is normally output for cloud statistical analysis; S412: Determine whether there is an abnormality in the accumulated mileage, and determine whether to output the accumulated mileage; The integral mileage is taken as the second priority, and the integral mileage of the abnormal data point is obtained. The difference between the meter mileage of the two data points before and after the abnormal data point and the integral mileage of the abnormal data point is compared respectively, and the difference is compared with the jump mileage threshold to determine whether it exceeds the jump mileage threshold. If so, it is determined that the integral total mileage of the abnormal data point is abnormal, and S413 is executed. Otherwise, it is determined whether the difference is less than 0. If so, it is determined that the instrument total mileage of the abnormal data point is abnormal, and S413 is executed. If not, the instrument mileage of the data point after the abnormal data point is subtracted from the integral mileage of the abnormal data point to obtain the difference, and the difference is compared with the jump mileage threshold to determine whether it exceeds the jump mileage threshold. If so, it is determined that the integral mileage of the abnormal data point is abnormal, and S413 is executed. Otherwise, it is determined whether the difference is less than 0. If so, it is determined that the integral mileage of the abnormal data point is abnormal, and S413 is executed. If not, the integral mileage is normally output for cloud statistical analysis; S413: Determine whether there is an abnormality in the total mileage of the instrument, and determine whether to output the total mileage of the instrument; The total mileage of the instrument is the third priority, and the judgment method is the same as S412; if the total mileage of the instrument of the abnormal data point is abnormal, S42 is executed, if not, the total mileage of the instrument is normally output for cloud statistical analysis; S414: Determine whether there is an abnormality in the total fuel consumption of the ECU, and determine whether to output the total fuel consumption of the ECU; ECU total fuel consumption is the first priority, and the judgment method is the same as S411. The ECU total fuel consumption in the stored collected data is obtained, and the difference of the ECU total fuel consumption of two consecutive data points is cyclically compared. First, the ECU total fuel consumption difference is compared with the jump fuel consumption threshold to determine whether it exceeds the jump fuel consumption threshold. If it exceeds, it is determined that the ECU total fuel consumption of the data point with the GPS time later is abnormal, and S412 is executed. Otherwise, it is determined whether the ECU total fuel consumption difference is less than 0. If so, it is determined that the ECU total fuel consumption of the data point with the GPS time later is abnormal, and S415 is executed. If not, the ECU total fuel consumption is normally output for cloud statistical analysis; S415: Determine whether there is an abnormality in the integrated fuel consumption, and determine whether to output the integrated fuel consumption; The integral fuel consumption is taken as the second priority, and the integral fuel consumption of the abnormal data point is obtained. The difference between the ECU total fuel consumption of the two data points before and after the abnormal data point and the integral fuel consumption of the abnormal data point is compared respectively. The integral fuel consumption of the abnormal data point is subtracted from the ECU total fuel consumption of the data point before the abnormal data point to obtain the difference, and the difference is compared with the jump fuel consumption threshold to determine whether it exceeds the jump fuel consumption threshold. If it exceeds, it is determined that the integral total fuel consumption of the abnormal data point is abnormal, and S42 is executed. Otherwise, it is determined whether the difference is less than 0. If so, it is determined that the instrument total fuel consumption of the abnormal data point is abnormal, and S42 is executed. If not, the ECU total fuel consumption of the data point after the abnormal data point is subtracted from the integral fuel consumption of the abnormal data point to obtain the difference, and the difference is compared with the jump fuel consumption threshold to determine whether it exceeds the jump fuel consumption threshold. If it exceeds, it is determined that the integral fuel consumption of the abnormal data point is abnormal, and S42 is executed. Otherwise, it is determined whether the difference is less than 0. If so, it is determined that the integral fuel consumption of the abnormal data point is abnormal, and S42 is executed. If not, the integral fuel consumption is output normally for cloud statistical analysis.

[0009] Further, step S42 includes: S421: Calculate the average value using multiple data points before and after the abnormal point; Define a reference point in the collected data, compare the data point with the reference point in turn, set the data point currently being compared as the current point, record the mileage, fuel consumption and GPS time of the current point and the reference point of the collected data, use the mileage, fuel consumption and GPS time of the current point to subtract the mileage, fuel consumption and GPS time of the reference point respectively, obtain the mileage difference, fuel consumption difference and time difference, calculate the average speed by dividing the mileage difference by the time difference, and calculate the average fuel consumption by dividing the fuel consumption difference by the time difference; give priority to using the instrument mileage and ECU total fuel consumption to calculate the average speed and average fuel consumption; S422: performing integral calculation according to the average value; S4221: Determine whether it is a valid difference, compare the calculated average speed with the mileage average threshold, and compare the average fuel consumption with the fuel consumption average threshold. If the difference is > 0 and the average value is <= the threshold, the difference at the current point is considered valid, the average value is recorded, and the reference point is updated to the value of the current point and the GPS time; otherwise, the difference is invalid, the reference point is not updated, the current point is updated to the next data point, and S421 is executed to recalculate the average value and determine whether the difference is valid, until all the selected data points are compared; S4222: If the difference is invalid, the average speed is calculated based on the total mileage and the integrated mileage of the instrument in order of priority, and the fuel consumption difference is recalculated based on the integrated fuel consumption; S4223: For the valid difference, calculate the reasonable values ​​of mileage and fuel consumption of the abnormal data point based on GPS time and average value.

[0010] Furthermore, the invalid difference includes the invalid mileage difference and / or the invalid fuel consumption difference. Step S4222 is specifically as follows: 1) If the mileage difference is invalid, record the integrated mileage of the current point and the reference point, continue to calculate the average speed, and determine whether the newly calculated mileage difference is a valid difference. If so, execute S4223. If not, record the total instrument mileage of the current point and the reference point and recalculate the mileage difference. Continue to calculate the average speed and determine whether the newly calculated mileage difference is a valid difference. If so, execute S4223. If not, execute S43. 2) If the fuel consumption difference is invalid, record the integrated fuel consumption of the current point and the reference point, recalculate the fuel consumption difference, and continue to calculate the average fuel consumption based on the time difference, and determine whether the newly calculated fuel consumption difference is a valid difference. If so, execute S4223. If not, reselect multiple data points before and after the abnormal data point and recalculate based on the ECU total fuel consumption until the difference is valid; 3) If both the mileage difference and the fuel consumption difference are invalid, execute steps 1) and 2) to continue calculating the average speed and average fuel consumption respectively, and determine whether the difference is valid.

[0011] Furthermore, the cloud also sets an integral compensation calculation interval. When the time interval between the reference point and the current point exceeds the integral compensation calculation interval, the integral mileage / integral fuel consumption is used to calculate the difference, and the difference between the next data point and the reference point is no longer compared.

[0012] Furthermore, the cloud contains recorded T+1 data and T+7 data; T+1 data is the GPS location information, speed, mileage, and fuel consumption obtained within the current day; T+7 data is the daily GPS location information, speed, mileage, and fuel consumption from 7 days before the current day to the current day; Use T+7 data to trace back history on a daily basis, and eventually upload the compensated and corrected data to the T+7 data.

[0013] Furthermore, it also includes new logic to perform T+7 data backtracking every day. When the instrument mileage / ECU fuel consumption has normal values, it is determined whether points have been used to compensate before. If points have been compensated, points compensation will be used in this data backtracking, and the next data backtracking will continue to use normal logic for direct output.

[0014] Furthermore, the transmission frequency is 30s; the mileage average value threshold is 0.04km / s; the fuel consumption average value threshold is 0.04 L / s; the jump mileage threshold is 5km, and the jump fuel consumption threshold is 0.5L.

[0015] Furthermore, the first point of each day's data is taken as the base point by default.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention can effectively handle abnormal situations in the data uploaded by T-Box, and ensure the accuracy and reliability of mileage and fuel consumption data by using the integral method and the latitude and longitude compensation method. This is of great significance for applications such as vehicle remote monitoring, fleet management and driving behavior analysis. (2) The present invention can effectively improve the accuracy and reliability of mileage correction by combining the integral method and the latitude and longitude compensation method. The combination of the two methods can more effectively manage and process data, avoiding the degradation of data quality caused by a single method. The longitude and latitude compensation method can timely correct the errors gradually accumulated by the integral method to ensure data consistency. It can adapt to a variety of driving scenarios, enhance the fault tolerance of the system, and provide a solid foundation for data analysis and decision-making. (3) The present invention selects and outputs abnormal data points according to the priority method, gives priority to high-quality and highly relevant data, significantly reduces the number of noise data and abnormal points, and thus improves the quality of the overall data set. It makes subsequent data analysis, modeling and decision-making more accurate and avoids deviations caused by abnormal points. Reducing the number of abnormal data points and the amount of data to be analyzed can reduce the consumption of computing resources and improve the overall efficiency of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 The present invention is a flowchart of the steps of the method for compensating for latitude and longitude of vehicle mileage and fuel consumption integral compensation. DETAILED DESCRIPTION

[0018] In order to provide a further understanding of the purpose, structure, features, and functions of the present invention, the following detailed description is given in conjunction with the embodiments.

[0019] A method for compensating vehicle mileage fuel consumption points and longitude and latitude, comprising a vehicle terminal T-Box device, a cloud and a map navigation system; The cloud is an online service platform that analyzes mileage, fuel consumption, driving behavior, etc. based on data from vehicle terminals.

[0020] The custom configurations in the cloud include the mileage average threshold, fuel consumption average threshold, and jump threshold; Mileage average threshold: 0.04km / s (144km / h, 30-second value difference maximum 1200m); Fuel consumption average value threshold: 0.04 L / s (144 L / h, maximum value difference of 30 seconds is 1200 ml); The jump threshold includes a jump mileage threshold and a jump fuel consumption threshold; For example, the jump mileage threshold is 5km, and the jump fuel consumption threshold is 0.5L; The following steps are involved: S1: Data collection; The on-board terminal collects data and collects the vehicle's operating status and environmental information.

[0021] The vehicle's operating status includes speed, mileage, fuel consumption, etc. The speed includes instrument speed and GPS speed; The instrument speed is the speed displayed on the vehicle's dashboard, which is usually provided by the vehicle's speed sensor; GPS speed is the vehicle speed measured by the Global Positioning System (GPS).

[0022] The mileage includes instrument mileage, instrument total mileage, ECU total mileage, and integral mileage; The mileage meter is used to record the mileage of a vehicle during a specific journey or period of use.

[0023] The instrument mileage records the total mileage of the vehicle since it was manufactured or last reset.

[0024] Point mileage refers to the accumulated mileage of a vehicle within a certain period of time or under specific conditions.

[0025] The fuel consumption includes: ECU total fuel consumption and integrated fuel consumption; ECU total fuel consumption is the total fuel consumption recorded by the vehicle ECU.

[0026] Integrated fuel consumption refers to the accumulated fuel consumption over a specific time period, trip or conditions.

[0027] The environmental information includes GPS location information, etc. GPS location information is the geographical location information obtained through the Global Positioning System (GPS), including longitude, latitude, GPS time and altitude.

[0028] The ECU (Electronic Control Unit) records the operating status of the engine and fuel system, and can provide relatively accurate mileage and fuel consumption data. These data are transmitted to the vehicle terminal T-Box device through the in-vehicle network (such as CAN bus).

[0029] The vehicle terminal T-Box device is a vehicle-mounted telematics terminal that can collect various status data of the vehicle, including GPS location information, speed, mileage, fuel consumption, etc., and then transmit the data to the cloud via wireless communication (such as 4G / 5G).

[0030] S2: The vehicle terminal uploads the collected data to the cloud at a fixed frequency; According to the 808-2013 departmental standard protocol 0200, the collected GPS location information, speed, mileage, fuel consumption, etc. can be transmitted to the cloud through wireless communication (such as 4G / 5G) at a fixed transmission frequency of 30s.

[0031] S3: Cloud analysis; After receiving the collected data uploaded by the vehicle terminal T-box, the cloud parses it based on the 808-2013 departmental standard protocol document to obtain GPS location information, speed, mileage, fuel consumption and other data and stores them in chronological order according to GPS time.

[0032] The cloud contains records of T+1 data and T+7 data; T+1 data refers to the GPS location information, speed, mileage, fuel consumption and other data obtained within the current day. It is used for statistical analysis of real-time fuel consumption and mileage. It does not include compensated mileage and fuel consumption. It directly outputs the collected instrument mileage and ECU total fuel consumption for statistical analysis to meet the needs of real-time analysis.

[0033] T+7 data is the daily GPS location information, speed, mileage, fuel consumption and other data from 7 days before the current day to the current day. It is used for re-tracing and considering the supplementary transmission in combination with the actual situation. For example, in the actual situation of passing through a tunnel or poor network, the data cannot be reported on time. There is a situation where the data uploaded today contains the data from the previous day or the previous seven days. Through the historical backtracking of T+7, the mileage energy consumption or driving behavior of the vehicle can be analyzed more accurately. T+7 data backtracking is performed every day, which is compatible with the scenario of terminal reporting data supplementation. The vehicle mileage and fuel consumption data from up to 7 days ago can be re-counted and calculated.

[0034] S4: Perform offline statistical analysis and correct the collected data; The system conducts historical backtracking in days, queries the data of the entire vehicle history, obtains GPS location information, speed, mileage, fuel consumption and other data in the collected data, and determines whether there are abnormal data points in the collected data. The system averages or interpolates the data of several moments before and after the abnormal data point to estimate the reasonable value of the abnormal data point, updates and corrects the collected data, outputs mileage data and fuel consumption data for statistics, sorts the output mileage data and fuel consumption data according to GPS time, forms vehicle trajectory playback, performs statistical analysis on the cloud, and calculates vehicle fuel consumption statistics.

[0035] S41: Determine whether there is any abnormality in the collected data; Determine whether there is an abnormality based on two consecutive data points of the collected data: First, the difference between the mileage and fuel consumption of two consecutive data points is cyclically compared to see if it exceeds the jump threshold. If so, it is judged that an abnormality has occurred. If not, there is no abnormality. The difference between the mileage of the data point with a later GPS time and the mileage of the data point with an earlier GPS time is used. If the difference exceeds the jump mileage threshold, the mileage of the data point with a later GPS time is abnormal. The difference between the fuel consumption of the data point with a later GPS time and the fuel consumption of the data point with an earlier GPS time is used. If the difference exceeds the jump fuel consumption threshold, the fuel consumption of the data point with a later GPS time is abnormal. Secondly, the mileage difference between two consecutive data points is compared cyclically. The mileage of the data point with later GPS time is subtracted from the mileage of the data point with earlier GPS time to get the mileage difference. It is determined whether the mileage difference is less than 0. If so, it is determined that the mileage of the data point with later GPS time is abnormal. Furthermore, when judging an abnormality, the priority judgment method is used for analysis step by step, including: S411: Determine whether the meter mileage is abnormal, and determine whether to output the meter mileage; The instrument mileage is given the first priority, and the mileage data used for statistical analysis of cloud mileage is output. The instrument mileage in the stored collected data is obtained, and the difference in the instrument mileage of two consecutive data points is compared cyclically. The instrument mileage of the data point with a later GPS time is subtracted from the instrument mileage of the data point with an earlier GPS time to obtain the instrument mileage difference. First, the instrument mileage difference is compared with the jump mileage threshold to determine whether it exceeds the jump mileage threshold. If it exceeds, it is determined that the mileage of the data point with a later GPS time is abnormal, and S412 is executed. Otherwise, it is determined whether the instrument mileage difference is less than 0. If so, it is determined that the mileage of the data point with a later GPS time is abnormal, and S412 is executed. If not, the instrument mileage is output normally for cloud statistical analysis. S412: Determine whether there is an abnormality in the accumulated mileage, and determine whether to output the accumulated mileage; The integral mileage is the second priority. When the instrument mileage is judged to be abnormal, the integral mileage of the abnormal data point is output for statistical analysis of cloud mileage.

[0036] Obtain the integral mileage of the abnormal data point, compare the difference between the meter mileage of the two data points before and after the abnormal data point and the integral mileage of the abnormal data point, use the integral mileage of the abnormal data point to subtract the meter mileage of the data point before the abnormal data point to obtain the difference, compare the difference with the jump mileage threshold, and determine whether it exceeds the jump mileage threshold. If so, it is determined that the integral total mileage of the abnormal data point is abnormal, and S413 is executed. Otherwise, determine whether the difference is less than 0. If so, it is determined that the instrument total mileage of the abnormal data point is abnormal, and S413 is executed. If not, use the meter mileage of the data point after the abnormal data point to subtract the integral mileage of the abnormal data point to obtain the difference, compare the difference with the jump mileage threshold, and determine whether it exceeds the jump mileage threshold. If so, it is determined that the integral mileage of the abnormal data point is abnormal, and S413 is executed. Otherwise, determine whether the difference is less than 0. If so, it is determined that the integral mileage of the abnormal data point is abnormal, and S413 is executed. If not, output the integral mileage normally for cloud statistical analysis; S413: Determine whether there is an abnormality in the total mileage of the instrument, and determine whether to output the total mileage of the instrument; The total mileage of the instrument is the third priority. When the integral mileage is judged to be abnormal, the total mileage of the instrument with abnormal data points is output for statistical analysis of cloud mileage.

[0037] The judgment method is the same as S412; the total mileage of the instrument of the abnormal data point is obtained, and the difference between the instrument mileage of the two data points before and after the abnormal data point and the total mileage of the instrument of the abnormal data point is compared respectively, and the difference is obtained by subtracting the instrument mileage of the data point before the abnormal data point from the total mileage of the instrument of the abnormal data point, and the difference is compared with the jump mileage threshold to determine whether it exceeds the jump mileage threshold. If it exceeds, it is determined that the total mileage of the instrument of the abnormal data point is abnormal, and S42 is executed. Otherwise, it is determined whether the difference is less than 0. If so, it is determined that the total mileage of the instrument of the abnormal data point is abnormal, and S42 is executed. If not, the instrument mileage of the data point after the abnormal data point is subtracted from the total mileage of the instrument of the abnormal data point to obtain the difference, and the difference is compared with the jump mileage threshold to determine whether it exceeds the jump mileage threshold. If it exceeds, it is determined that the total mileage of the instrument of the abnormal data point is abnormal, and S42 is executed. Otherwise, it is determined whether the difference is less than 0. If so, it is determined that the total mileage of the instrument of the abnormal data point is abnormal, and S42 is executed. If not, the total mileage of the instrument is output normally for cloud statistical analysis; S414: Determine whether there is an abnormality in the total fuel consumption of the ECU, and determine whether to output the total fuel consumption of the ECU; The ECU total fuel consumption is taken as the first priority and output for statistical analysis of cloud mileage. The judgment method is the same as S411, obtaining the ECU total fuel consumption in the stored collected data, cyclically comparing the difference of the ECU total fuel consumption of two consecutive data points, using the ECU total fuel consumption of the data point with later GPS time minus the ECU total fuel consumption of the data point with earlier GPS time to obtain the ECU total fuel consumption difference, firstly comparing the ECU total fuel consumption difference with the jump fuel consumption threshold to determine whether it exceeds the jump fuel consumption threshold, if it exceeds, it is determined that the ECU total fuel consumption of the data point with later GPS time is abnormal, and S412 is executed, otherwise it is determined whether the ECU total fuel consumption difference is less than 0, if so, it is determined that the ECU total fuel consumption of the data point with later GPS time is abnormal, and S415 is executed, if not, the ECU total fuel consumption is normally output for cloud statistical analysis; S415: Determine whether there is an abnormality in the integrated fuel consumption, and determine whether to output the integrated fuel consumption; The integrated fuel consumption is the second priority and is output for statistical analysis of mileage in the cloud.

[0038] Obtain the integral fuel consumption of the abnormal data point, compare the difference between the ECU total fuel consumption of the two data points before and after the abnormal data point and the integral fuel consumption of the abnormal data point, use the integral fuel consumption of the abnormal data point to subtract the ECU total fuel consumption of the data point before the abnormal data point to obtain the difference, compare the difference with the jump fuel consumption threshold, and determine whether it exceeds the jump fuel consumption threshold. If so, it is determined that the integral total fuel consumption of the abnormal data point is abnormal, and S42 is executed. Otherwise, it is determined whether the difference is less than 0. If so, it is determined that the total fuel consumption of the instrument of the abnormal data point is abnormal, and S42 is executed. If not, subtract the integral fuel consumption of the abnormal data point from the ECU total fuel consumption of the data point after the abnormal data point to obtain the difference, and compare the difference with the jump fuel consumption threshold to determine whether it exceeds the jump fuel consumption threshold. If so, it is determined that the integral fuel consumption of the abnormal data point is abnormal, and S42 is executed. Otherwise, it is determined whether the difference is less than 0. If so, it is determined that the integral fuel consumption of the abnormal data point is abnormal, and S42 is executed. If not, the integral fuel consumption is normally output for cloud statistical analysis; The present invention uses a priority method to select and output abnormal data points according to priority, giving priority to high-quality, highly relevant data, significantly reducing the number of noise data and abnormal points, thereby improving the quality of the overall data set. This makes subsequent data analysis, modeling, and decision-making more accurate, avoiding deviations caused by abnormal points. Reducing the number of abnormal data points reduces the amount of data that needs to be analyzed, and processing a small amount of data can reduce the consumption of computing resources and improve the overall efficiency of the system.

[0039] S42: The abnormal data point data is corrected by integral compensation, and the corrected data is output for cloud statistical analysis; When it is determined that there is an abnormal data point, the collected data at several times before and after the abnormal data point is averaged or interpolated to estimate the reasonable value of the abnormal data point at that moment, and the reasonable value is output for cloud-based statistical analysis.

[0040] S421: Calculate the average value using multiple data points before and after the abnormal point; Define a reference point in the collected data, record the value to be calculated at this point (meter mileage, ECU total fuel consumption) and GPS time, compare the data point with the reference point in turn, make the difference between the current point and the reference point (mileage difference, fuel consumption difference), divide it by the time difference with the reference point, and calculate the average value (average speed, average fuel consumption).

[0041] Record the instrument mileage, ECU total fuel consumption and GPS time of the current point and the reference point of data collection, and use the instrument mileage, ECU total fuel consumption and GPS time of the current point to subtract the instrument mileage, ECU total fuel consumption and GPS time of the reference point to obtain the mileage difference, fuel consumption difference and time difference, and calculate the average speed by dividing the mileage difference by the time difference, and calculate the average fuel consumption by dividing the fuel consumption difference by the time difference; The difference is calculated by subtracting the values ​​of two points, and the point being subtracted is called the reference point. Usually, the first point of the data day is the reference point by default. The reference point is mainly used to calculate the instrument mileage and ECU total fuel consumption, which requires special attention. The current point refers to the data point currently being compared.

[0042] S422: performing integral calculation according to the average value; S4221: Determine whether it is a valid difference, compare the calculated average speed with the mileage average threshold, and compare the average fuel consumption with the fuel consumption average threshold. If the difference > 0 and the average value <= the threshold, the difference at the current point is considered valid, the average value is recorded, and the reference point is updated to the value of the current point and GPS time; otherwise, the difference is invalid, the reference point is not updated, the current point is updated to the next data point, and S421 is executed to recalculate the average value and determine whether the difference is valid, until all selected data points are compared.

[0043] S4222: If the difference is invalid, the average speed is calculated according to the total mileage and the integrated mileage of the instrument in order of priority, and the fuel consumption difference is recalculated according to the integrated fuel consumption; the invalid difference includes the invalid mileage difference and / or the invalid fuel consumption difference.

[0044] 1) If the mileage difference is invalid, record the integrated mileage of the current point and the reference point, continue to calculate the average speed, and determine whether the newly calculated mileage difference is a valid difference. If so, execute S4223. If not, record the total instrument mileage of the current point and the reference point and recalculate the mileage difference. Continue to calculate the average speed and determine whether the newly calculated mileage difference is a valid difference. If so, execute S4223. If not, execute S43.

[0045] 2) If the fuel consumption difference is invalid, record the integrated fuel consumption of the current point and the reference point, recalculate the fuel consumption difference, and continue to calculate the average fuel consumption based on the time difference. Determine whether the newly calculated fuel consumption difference is a valid difference. If so, execute S4223. If not, reselect multiple data points before and after the abnormal data point and recalculate based on the ECU total fuel consumption until the difference is valid.

[0046] 3) If both the mileage difference and the fuel consumption difference are invalid, execute steps 1) and 2) to continue calculating the average speed and average fuel consumption respectively, and determine whether the difference is valid.

[0047] Furthermore, the cloud also sets a point compensation calculation interval of 300s. When the time interval between the reference point and the current point is too long, exceeding the point compensation calculation interval, the point mileage / point fuel consumption is used to compensate this data. The difference between the next data point and the reference point is no longer compared, ensuring that the point compensation calculation speed of the present invention is fast and the calculation is terminated in time. In addition, by limiting the compensation calculation interval, the calculation deviation is reduced, ensuring the accuracy and reliability of the compensation.

[0048] S4223: For the valid difference, calculate the reasonable values ​​of mileage and fuel consumption of the abnormal data point according to the GPS time and the average value; Calculate the mileage of the abnormal point according to the reasonable mileage value = instrument mileage of the current point + average speed * (GPS time of the abnormal data point + GPS time of the current point); Calculate the fuel consumption of the abnormal point based on the reasonable fuel consumption value = total ECU fuel consumption at the current point + average speed * (GPS time of the abnormal data point + GPS time of the current point); The mileage calculated by the integration method can more accurately reflect the actual driving distance based on the accumulation of real-time speed and time. This method can adapt to different speed changes and provide detailed mileage estimation. It is suitable for a variety of driving scenarios such as urban roads, highways, and complex terrain. In particular, the integration method can provide important compensation when the vehicle encounters signal interference or navigation system failure during driving. In the case of unstable GPS signal, the integration method can still provide mileage data, thereby ensuring the continuity and reliability of the system.

[0049] Furthermore, historical backtracking of T+7 data is performed every day. A new logic can be added. When the instrument mileage / ECU fuel consumption has normal values, it is determined whether points have been used for compensation before. If compensation has been made, points compensation will be used for this data backtracking, and normal logic output will continue to be used for the next data backtracking.

[0050] This mechanism ensures the consistency of data, is compatible with scenarios where terminals report data retransmission, corrects change trends, optimizes the integral compensation method, reduces the long-term accumulated calculation errors of the integral compensation method, ensures the accuracy and reliability of the data corrected by the integral compensation method, can flexibly respond to changes in driving behavior, meet complex scenario applications, and is highly practical.

[0051] S43: Correction mileage of abnormal data point longitude and latitude compensation; Through GPS location information and map matching algorithm, the actual driving trajectory of the vehicle is matched with the road network to correct the mileage data.

[0052] Get the GPS location information of the benchmark and abnormal data points. The GPS location information includes longitude and latitude. Use the map matching algorithm to match the actual driving trajectory of the vehicle with the road network. Combined with the road network, get the actual road mileage. Use the benchmark plus the actual road mileage to correct the mileage data. The longitude and latitude data obtained by GPS or other positioning systems can effectively correct the mileage deviation caused by equipment error or signal loss.

[0053] The combination of the integral method and the longitude and latitude compensation method can effectively improve the accuracy and reliability of mileage correction. The combination of the two methods can more effectively manage and process data, avoiding the degradation of data quality caused by a single method. The longitude and latitude compensation method can timely correct the gradually accumulated errors of the integral method to ensure data consistency. It can adapt to a variety of driving scenarios, enhance the system's fault tolerance, and provide a solid foundation for data analysis and decision-making.

[0054] S44: Output the compensated mileage and fuel consumption for cloud-based statistical analysis.

[0055] The corrected mileage and fuel consumption are obtained and merged with the output mileage data and fuel consumption data, sorted according to GPS time, forming a vehicle trajectory playback, and statistical analysis is performed in the cloud to calculate vehicle fuel consumption statistics.

[0056] S5: data fusion and final retransmission; After data processing and correction in the cloud, the corrected mileage and fuel consumption data will be updated to the T+7 data in the cloud through the supplementary transmission mechanism, and the corrected mileage and fuel consumption will be added to the instrument mileage and ECU total fuel consumption of the abnormal data points.

[0057] After updating the cloud data and correcting the data through supplementary transmission, the storage space can be used more reasonably to avoid storing unnecessary redundant data. It ensures that the data stored in the cloud is more accurate and reliable when used for actual analysis, which is helpful for subsequent data analysis and decision-making, and avoids decision-making errors caused by data errors. The present invention only saves data for a maximum of 7 days, which is convenient for tracing back historical data, meets the analysis requirements of data supplementary transmission and reporting, conforms to complex data reporting situations, has a high fault tolerance rate, and is suitable for complex scene applications.

[0058] The present invention has been described by the above-mentioned relevant embodiments, however, the above-mentioned embodiments are only examples for implementing the present invention. It must be pointed out that the disclosed embodiments do not limit the scope of the present invention. On the contrary, changes and modifications made without departing from the spirit and scope of the present invention are all within the scope of patent protection of the present invention.

Claims

1. A method for compensating vehicle mileage fuel consumption integral compensation latitude and longitude, characterized in that: Including vehicle terminal, cloud and map navigation system; The custom configuration in the cloud includes the mileage average threshold, fuel consumption average threshold and jump threshold; the jump threshold includes the jump mileage threshold and the jump fuel consumption threshold; The following steps are involved: S1: Data collection; The vehicle-mounted terminal collects data, including the vehicle's operating status and environmental information; The vehicle's operating status includes speed, mileage, and fuel consumption; The environmental information includes GPS location information; the GPS location information includes longitude, latitude, GPS time and altitude; S2: The vehicle terminal uploads the collected data to the cloud at a fixed frequency; The collected GPS location information, speed, mileage, and fuel consumption are transmitted to the cloud at a fixed transmission frequency; S3: Cloud analysis; After receiving the collected data uploaded by the vehicle terminal, the cloud analyzes it, obtains GPS location information, speed, mileage, fuel consumption and stores it in the order of GPS time; S4: Perform offline statistical analysis and correct the collected data; Perform historical backtracking in days, query the data of the entire vehicle history, obtain the GPS location information, speed, mileage, fuel consumption in the collected data, and determine whether there are abnormal data points in the collected data. For the abnormal data points, average or interpolate the data of several moments before and after to estimate the reasonable value of the abnormal data point, update and correct the collected data, output the mileage data and fuel consumption data for statistics, sort the output mileage data and fuel consumption data according to GPS time, form a vehicle trajectory playback, perform statistical analysis in the cloud, and calculate the vehicle fuel consumption statistics; S5: data fusion and final retransmission; Add the corrected mileage and fuel consumption to the instrument mileage and ECU total fuel consumption of the abnormal data point.

2. The method for compensating for latitude and longitude of vehicle mileage fuel consumption integral compensation as claimed in claim 1, characterized in that: Step S4 includes: S41: Determine whether there is any abnormality in the collected data; Determine whether there is an abnormality based on two consecutive data points of the collected data: First, the difference between the mileage and fuel consumption of two consecutive data points is cyclically compared to see if it exceeds the jump threshold. If so, it is judged that an abnormality has occurred. If not, there is no abnormality. The difference between the mileage of the data point with a later GPS time and the mileage of the data point with an earlier GPS time is used. If the difference exceeds the jump mileage threshold, the mileage of the data point with a later GPS time is abnormal. The difference between the fuel consumption of the data point with a later GPS time and the fuel consumption of the data point with an earlier GPS time is used. If the difference exceeds the jump fuel consumption threshold, the fuel consumption of the data point with a later GPS time is abnormal. Secondly, the mileage difference between two consecutive data points is compared cyclically. The mileage of the data point with later GPS time is subtracted from the mileage of the data point with earlier GPS time to get the mileage difference. It is determined whether the mileage difference is less than 0. If so, it is determined that the mileage of the data point with later GPS time is abnormal. S42: The abnormal data point data is corrected by integral compensation, and the corrected data is output for cloud statistical analysis; When an abnormal data point is determined to exist, the data collected at several times before and after the abnormal data point is averaged or interpolated to estimate the reasonable value of the abnormal data point at that moment, and the reasonable value is output for cloud-based statistical analysis; S43: Correction mileage of abnormal data point longitude and latitude compensation; Through GPS location information, the map matching algorithm is used to match the actual driving trajectory of the vehicle with the road network and correct the mileage data; Obtain GPS location information of the benchmark points and abnormal data points. The GPS location information includes longitude and latitude. Use the map matching algorithm to match the actual driving trajectory of the vehicle with the road network. Combined with the road network, obtain the actual road mileage. Use the benchmark points plus the actual road mileage to correct the mileage data. S44: Output the mileage and fuel consumption after compensation for cloud statistical analysis; The corrected mileage and fuel consumption are obtained and merged with the output mileage data and fuel consumption data, sorted according to GPS time, forming a vehicle trajectory playback, and statistical analysis is performed in the cloud to calculate vehicle fuel consumption statistics.

3. The method for compensating for latitude and longitude of vehicle mileage fuel consumption integral compensation as claimed in claim 1, characterized in that: The speed includes instrument speed and GPS speed; The mileage includes meter mileage, total meter mileage, and integral mileage; The fuel consumption includes: ECU total fuel consumption and integrated fuel consumption; When judging an abnormality, the priority judgment method is used for analysis, including: S411: Determine whether the meter mileage is abnormal, and determine whether to output the meter mileage; The instrument mileage is given the first priority, and the mileage data for statistical analysis of cloud mileage is output. The instrument mileage in the stored collected data is obtained, and the difference of the instrument mileage of two consecutive data points is cyclically compared. First, the instrument mileage difference is compared with the jump mileage threshold to determine whether it exceeds the jump mileage threshold. If it exceeds, it is determined that the mileage of the data point with the later GPS time is abnormal, and S412 is executed. Otherwise, it is determined whether the instrument mileage difference is less than 0. If so, it is determined that the mileage of the data point with the later GPS time is abnormal, and S412 is executed. If not, the instrument mileage is normally output for cloud statistical analysis; S412: Determine whether there is an abnormality in the accumulated mileage, and determine whether to output the accumulated mileage; The integral mileage is taken as the second priority, and the integral mileage of the abnormal data point is obtained. The difference between the meter mileage of the two data points before and after the abnormal data point and the integral mileage of the abnormal data point is compared respectively, and the difference is compared with the jump mileage threshold to determine whether it exceeds the jump mileage threshold. If so, it is determined that the integral total mileage of the abnormal data point is abnormal, and S413 is executed. Otherwise, it is determined whether the difference is less than 0. If so, it is determined that the instrument total mileage of the abnormal data point is abnormal, and S413 is executed. If not, the instrument mileage of the data point after the abnormal data point is subtracted from the integral mileage of the abnormal data point to obtain the difference, and the difference is compared with the jump mileage threshold to determine whether it exceeds the jump mileage threshold. If so, it is determined that the integral mileage of the abnormal data point is abnormal, and S413 is executed. Otherwise, it is determined whether the difference is less than 0. If so, it is determined that the integral mileage of the abnormal data point is abnormal, and S413 is executed. If not, the integral mileage is normally output for cloud statistical analysis; S413: Determine whether there is an abnormality in the total mileage of the instrument, and determine whether to output the total mileage of the instrument; The total mileage of the instrument is the third priority, and the judgment method is the same as S412; if the total mileage of the instrument of the abnormal data point is abnormal, S42 is executed, if not, the total mileage of the instrument is normally output for cloud statistical analysis; S414: Determine whether there is an abnormality in the total fuel consumption of the ECU, and determine whether to output the total fuel consumption of the ECU; ECU total fuel consumption is the first priority, and the judgment method is the same as S411. The ECU total fuel consumption in the stored collected data is obtained, and the difference of the ECU total fuel consumption of two consecutive data points is cyclically compared. First, the ECU total fuel consumption difference is compared with the jump fuel consumption threshold to determine whether it exceeds the jump fuel consumption threshold. If it exceeds, it is determined that the ECU total fuel consumption of the data point with the GPS time later is abnormal, and S412 is executed. Otherwise, it is determined whether the ECU total fuel consumption difference is less than 0. If so, it is determined that the ECU total fuel consumption of the data point with the GPS time later is abnormal, and S415 is executed. If not, the ECU total fuel consumption is normally output for cloud statistical analysis; S415: Determine whether there is an abnormality in the integrated fuel consumption, and determine whether to output the integrated fuel consumption; The integral fuel consumption is taken as the second priority, and the integral fuel consumption of the abnormal data point is obtained. The difference between the ECU total fuel consumption of the two data points before and after the abnormal data point and the integral fuel consumption of the abnormal data point is compared respectively. The integral fuel consumption of the abnormal data point is subtracted from the ECU total fuel consumption of the data point before the abnormal data point to obtain the difference, and the difference is compared with the jump fuel consumption threshold to determine whether it exceeds the jump fuel consumption threshold. If it exceeds, it is determined that the integral total fuel consumption of the abnormal data point is abnormal, and S42 is executed. Otherwise, it is determined whether the difference is less than 0. If so, it is determined that the instrument total fuel consumption of the abnormal data point is abnormal, and S42 is executed. If not, the ECU total fuel consumption of the data point after the abnormal data point is subtracted from the integral fuel consumption of the abnormal data point to obtain the difference, and the difference is compared with the jump fuel consumption threshold to determine whether it exceeds the jump fuel consumption threshold. If it exceeds, it is determined that the integral fuel consumption of the abnormal data point is abnormal, and S42 is executed. Otherwise, it is determined whether the difference is less than 0. If so, it is determined that the integral fuel consumption of the abnormal data point is abnormal, and S42 is executed. If not, the integral fuel consumption is output normally for cloud statistical analysis.

4. The method for compensating for latitude and longitude of vehicle mileage fuel consumption integral compensation as claimed in claim 3, characterized in that: Step S42 includes: S421: Calculate the average value using multiple data points before and after the abnormal point; Define a reference point in the collected data, compare the data point with the reference point in turn, set the data point currently being compared as the current point, record the mileage, fuel consumption and GPS time of the current point and the reference point of the collected data, use the mileage, fuel consumption and GPS time of the current point to subtract the mileage, fuel consumption and GPS time of the reference point respectively, obtain the mileage difference, fuel consumption difference and time difference, calculate the average speed by dividing the mileage difference by the time difference, and calculate the average fuel consumption by dividing the fuel consumption difference by the time difference; give priority to using the instrument mileage and ECU total fuel consumption to calculate the average speed and average fuel consumption; S422: performing integral calculation according to the average value; S4221: Determine whether it is a valid difference, compare the calculated average speed with the mileage average threshold, and compare the average fuel consumption with the fuel consumption average threshold. If the difference > 0, and the average value <= the threshold, the difference at the current point is considered valid, the average value is recorded, and the reference point is updated to the value of the current point and the GPS time; otherwise, the difference is invalid, the reference point is not updated, the current point is updated to the next data point, and S421 is executed to recalculate the average value and determine whether the difference is valid, until all the selected data points are compared; S4222: If the difference is invalid, the average speed is calculated based on the total mileage and the integrated mileage of the instrument in order of priority, and the fuel consumption difference is recalculated based on the integrated fuel consumption; S4223: For the valid difference, calculate the reasonable values ​​of mileage and fuel consumption of the abnormal data point based on GPS time and average value.

5. The method for compensating for latitude and longitude of vehicle mileage fuel consumption integral compensation as claimed in claim 4, characterized in that: The invalid difference includes the invalid mileage difference and / or the invalid fuel consumption difference. Step S4222 is specifically as follows: 1) If the mileage difference is invalid, record the integrated mileage of the current point and the reference point, continue to calculate the average speed, and determine whether the newly calculated mileage difference is a valid difference. If so, execute S4223. If not, record the total instrument mileage of the current point and the reference point and recalculate the mileage difference. Continue to calculate the average speed and determine whether the newly calculated mileage difference is a valid difference. If so, execute S4223. If not, execute S43. 2) If the fuel consumption difference is invalid, record the integrated fuel consumption of the current point and the reference point, recalculate the fuel consumption difference, and continue to calculate the average fuel consumption based on the time difference, and determine whether the newly calculated fuel consumption difference is a valid difference. If so, execute S4223. If not, reselect multiple data points before and after the abnormal data point and recalculate based on the ECU total fuel consumption until the difference is valid; 3) If both the mileage difference and the fuel consumption difference are invalid, execute steps 1) and 2) to continue calculating the average speed and average fuel consumption respectively, and determine whether the difference is valid.

6. The method for compensating for latitude and longitude of vehicle mileage fuel consumption integral compensation as claimed in claim 4, characterized in that: The cloud also sets an integral compensation calculation interval. When the time interval between the reference point and the current point exceeds the integral compensation calculation interval, the integral mileage / integral fuel consumption is used to calculate the difference, and the difference between the next data point and the reference point is no longer compared.

7. The method for compensating for latitude and longitude of vehicle mileage fuel consumption integral compensation as claimed in claim 1, characterized in that: The cloud contains records of T+1 data and T+7 data; T+1 data is the GPS location information, speed, mileage, and fuel consumption obtained within the current day; T+7 data is the daily GPS location information, speed, mileage, and fuel consumption from 7 days before the current day to the current day; Use T+7 data to trace back history on a daily basis, and eventually upload the compensated and corrected data to the T+7 data.

8. The method for compensating for latitude and longitude of vehicle mileage fuel consumption integral compensation as claimed in claim 7, characterized in that: It also includes new logic to perform T+7 data backtracking every day. When the instrument mileage / ECU fuel consumption has normal values, it determines whether points have been used to compensate before. If points have been compensated, points compensation will be used in this data backtracking, and the next data backtracking will continue to use normal logic for direct output.

9. The method for compensating for latitude and longitude of vehicle mileage fuel consumption integral compensation as claimed in claim 1, characterized in that: The transmission frequency is 30s; the average mileage threshold is 0.04km / s; the average fuel consumption threshold is 0.04 L / s; the jump mileage threshold is 5km, and the jump fuel consumption threshold is 0.5L.

10. The method for compensating for latitude and longitude of vehicle mileage fuel consumption integral compensation as claimed in claim 4, characterized in that: By default, the first point of each day’s data is taken as the base point.

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