CN110414860A - Loss of Oil Products at Gas Station analysis method and system - Google Patents
Loss of Oil Products at Gas Station analysis method and system Download PDFInfo
- Publication number
- CN110414860A CN110414860A CN201910716153.9A CN201910716153A CN110414860A CN 110414860 A CN110414860 A CN 110414860A CN 201910716153 A CN201910716153 A CN 201910716153A CN 110414860 A CN110414860 A CN 110414860A
- Authority
- CN
- China
- Prior art keywords
- oil
- data
- per hundred
- current
- driving
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000004458 analytical method Methods 0.000 title claims abstract description 35
- 238000012545 processing Methods 0.000 claims abstract description 21
- 239000000446 fuel Substances 0.000 claims abstract description 20
- 230000008859 change Effects 0.000 claims abstract description 6
- 238000004891 communication Methods 0.000 claims abstract description 5
- 238000000034 method Methods 0.000 claims description 9
- 239000003921 oil Substances 0.000 abstract description 106
- 239000000295 fuel oil Substances 0.000 abstract description 8
- 230000002411 adverse Effects 0.000 abstract description 3
- 230000000694 effects Effects 0.000 abstract description 2
- 238000011897 real-time detection Methods 0.000 abstract 1
- 230000008569 process Effects 0.000 description 3
- 238000001514 detection method Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 238000005192 partition Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000001960 triggered effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06395—Quality analysis or management
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0808—Diagnosing performance data
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Strategic Management (AREA)
- Educational Administration (AREA)
- General Physics & Mathematics (AREA)
- Economics (AREA)
- Physics & Mathematics (AREA)
- Development Economics (AREA)
- Game Theory and Decision Science (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Measuring Volume Flow (AREA)
Abstract
The present invention relates to the present invention relates to analysis of oil technical fields, especially a kind of Loss of Oil Products at Gas Station analysis method and system, Loss of Oil Products at Gas Station analysis method includes: S1, the mileage information for obtaining vehicle, interior appliance information and geography information, the oil mass situation of change of real-time detection vehicle；If S2, fresh oil accounting are greater than predetermined ratio, nearest fuel station information is obtained, an analysis of oil period is started；S21, per 100 km fuel consumption is calculated；S22, current driving habit data are recorded, analyzes driving style；S23, judge influence of this kind of driving style to the secondary oil consumption, analyze current fuel quality under identical driving style；Loss of Oil Products at Gas Station analysis system includes acquisition module, processing module, locating module, backstage cloud and communication module.Oil consumption after the analysis of present invention combination driving style and oiling carries out Quantitative marking to fuel oil, gives the more objective fuel oil oil product reference of car owner and bad fuel oil is avoided to cause adverse effect to car owner's economic expenditure and vehicle itself.
Description
Technical Field
The invention relates to the technical field of oil product analysis, in particular to a method and a system for analyzing oil products of a gas station.
Background
In recent years, the number of automobiles is increasing continuously, so that not only is the domestic fuel demand increased rapidly, but also the fuel price is increased rapidly, and a plurality of private fuel stations appear in the fuel market. Compared with the fuel of national gas stations, the private gas stations are cheap, but the oil products are not uniform, the names of some private gas stations are even very similar to those of national gas stations, many owners are difficult to distinguish one from another, the fuel with poor quality is added for a long time to be discovered, and the driving experience of the owners and the vehicles are all adversely affected.
Disclosure of Invention
The invention aims to overcome the defect that the fuel oil of a gas station cannot be comprehensively analyzed in the prior art so as to prompt a vehicle owner.
In order to achieve the purpose, the invention discloses an oil analysis method of a gas station, which comprises the following steps:
s1, acquiring mileage information, in-vehicle electrical appliance information and geographic information of the vehicle, and detecting the oil quantity change condition of the vehicle in real time;
s2, if the oil quantity of the vehicle is increased and the new oil quantity ratio is larger than a preset ratio, obtaining the information of a gas station nearest to the current position of the vehicle, and starting an oil analysis period;
the oil analysis cycle comprises the following steps:
s21, calculating the oil consumption per hundred kilometers;
s22, recording driving habit data of a current driver, and identifying the driving style of the driver through the driving habit data, wherein the driving habit data comprises brake data, accelerator data, steering wheel data, vehicle speed data and gear data;
and S23, feeding back the current oil consumption per hundred kilometers in real time, uploading the current oil consumption per hundred kilometers, the information of the gas station and the historical oil consumption per hundred kilometers of the driving style to a background cloud, comparing the current oil consumption per hundred kilometers and the historical oil consumption per hundred kilometers of the driving style by the background cloud, and analyzing the current fuel quality under the same driving style.
Preferably, the method further comprises the following steps:
and S3, uploading the driving habit data to a background cloud end, comparing the influence of the difference of brake data, accelerator data, steering wheel data, vehicle speed data and gear data in each group of driving habit data on the fuel consumption per hundred kilometers, and sending one or more driving habit data with the minimum average fuel consumption to the driver.
Preferably, the predetermined ratio in step S2 is four times the amount of fresh oil as compared to the amount of raw oil.
Preferably, the driving style recognized by the driver habit in step S22 is specifically: and comparing the acquired driving habit data with historical driving habit data, and judging the driving habit data to be the same driving style if at least three groups of brake data, accelerator data, steering wheel data, vehicle speed data or gear data in the two groups of driving habit data are the same, or judging the driving habit data to be different driving styles.
Preferably, the step S23 further includes the steps of:
acquiring road characteristic information and the historical refueling times of the vehicle at a current refueling station;
establishing an oil product quantitative scoring model for quantitatively scoring an oil product, wherein the oil product quantitative scoring model is as follows:
wherein x is1～xnIncluding but not limited to current oil consumption per hundred kilometers, driving style score, in-vehicle electrical information, road characteristic information and historical fueling times, f1～fnThe weight corresponding to each parameter.
The invention also discloses a gas station oil analysis system, which is used for implementing the gas station oil analysis method of any one of claims 1 to 5, and comprises the following steps:
the acquisition module is used for acquiring oil mass information, in-vehicle electrical appliance information, road characteristic information, odometer reading and current driving habit data;
the processing module is used for acquiring the acquired data of the acquisition module, identifying the current driving style by comparing the current driving habit data with the historical driving habit data stored in the processing module, calculating the oil consumption per hundred kilometers after the new oil quantity reaches a preset proportion, and uploading the current oil consumption per hundred kilometers and the historical oil consumption per hundred kilometers;
the positioning module is used for acquiring and uploading the information of a gas station closest to the vehicle after the new oil quantity reaches a preset proportion;
the background cloud end is used for acquiring the information uploaded by the processing module and the information uploaded by the positioning module of the gas station, and comparing the current oil consumption per hundred kilometers and the historical oil consumption per hundred kilometers in the driving style, so that the oil consumption of the gas station at the current time is quantitatively scored;
and the communication module is used for establishing signal connection between the processing module and the background cloud end and between the positioning module and the background cloud end.
Preferably, the processing module is further configured to upload the current driving habit data and the historical driving habit data to a background cloud; the background cloud is further used for analyzing the influence of the difference of each group of driving habit data on the oil consumption per hundred kilometers, and sending one or more driving habit data with the minimum oil consumption per hundred kilometers to the processing module.
The invention has the beneficial effects that: the fuel oil added at a filling station each time is quantitatively graded by detecting the oil consumption per hundred kilometers after the vehicle is filled with the oil and analyzing the driving style of a driver, so that a vehicle owner is provided with more objective fuel oil product reference, the fuel oil quality of the vehicle owner is timely reminded, and adverse effects on the economic expenditure of the vehicle owner and the vehicle are avoided due to poor oil products; meanwhile, the driving styles of various drivers are compared and an oil-saving driving reference is provided, so that the fuel oil expenditure cost of the vehicle owner is saved.
Drawings
FIG. 1: the steps of the method for analyzing the oil of the gas station are shown schematically.
FIG. 2: the invention discloses a structural schematic diagram of a gas station oil product analysis system.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments and the accompanying drawings.
Referring to fig. 1, an implementation process of the oil analysis method of the gas station of the present invention includes the following steps:
s1, acquiring mileage information, in-vehicle electrical appliance information and geographic information of the vehicle, and detecting the oil quantity change condition of the vehicle in real time;
s2, if the oil quantity of the vehicle is increased and the new oil quantity ratio is larger than a preset ratio, obtaining the information of a gas station nearest to the current position of the vehicle, and starting an oil analysis period;
in the above steps S1 to S2, the change of the oil amount in the oil cylinder is an important variable for triggering the oil analysis period, generally, the vehicle owner will refuel to the gas station after the oil amount is consumed to a certain extent, the oil amount difference before and after refuel is the new oil amount, and when the new oil amount ratio exceeds the predetermined ratio, an oil analysis period will be triggered to perform quality analysis on the new oil. When an oil product analysis period begins, the recorded mileage information is a zero reference value, and the information of a gas station nearest to the vehicle, including the name of the gas station and the address of the gas station, is obtained by positioning the current geographic information of the vehicle. In this embodiment, the predetermined ratio is four times the amount of fresh oil as compared to the amount of raw oil.
The oil analysis cycle comprises the following steps:
s21, calculating the oil consumption per hundred kilometers;
s22, recording driving habit data of a current driver, and identifying the driving style of the driver through the driving habit data, wherein the driving habit data comprises brake data, accelerator data, steering wheel data, vehicle speed data and gear data;
the driving habit of a driver can influence the oil consumption speed to a great extent, wherein, the brake data and the accelerator data detect the torque angle and the torque duration of a brake and an accelerator respectively, according to the torque angle and the torque duration, whether the driver is used to 'sudden braking' or 'hard stepping on oil' is judged, the angle of a steering wheel is detected by a steering wheel angle detection device, the gear is detected by a gear detection device, and the speed data of a vehicle is obtained by reading a speedometer. While the brake data, the throttle data, the steering wheel data, the vehicle speed data and the gear data are respectively detected, the generation sequence of the data is recorded, such as the alternate use condition of the throttle and the brake or the alternate use condition of the throttle and the brake combined with gear change.
The specific principle of identifying the driving style through the habit of the driver is as follows: and comparing the acquired driving habit data with historical driving habit data, wherein each group of data is provided with a reasonable deviation range, and the difference between the current driving habit data and the historical driving habit data is within the reasonable deviation range and is judged to be the same as the two groups of data. In this embodiment, if at least three groups of brake data, accelerator data, steering wheel data, vehicle speed data, or gear data in the two groups of driving habit data are the same, it is determined as the same driving style, otherwise, it is determined as different driving styles.
S23, feeding back the current oil consumption per hundred kilometers in real time, uploading the current oil consumption per hundred kilometers, the information of a gas station and the historical oil consumption per hundred kilometers of the driving style to a background cloud, comparing the current oil consumption per hundred kilometers and the historical oil consumption per hundred kilometers of the driving style by the background cloud, and analyzing the current fuel quality under the same driving style;
after the driving styles are judged, the background cloud end carries out quantitative scoring on the new oil, wherein one scoring standard is that the oil consumption per hundred kilometers of the same driving style (the same driving style of the vehicle or the same vehicle type is preferably selected) is compared with the oil consumption per hundred kilometers of the same driving style, the oil consumption per hundred kilometers of the same driving style is lower, and the oil quality is higher;
more specific criteria are: acquiring road characteristic information and the historical refueling times of the vehicle at the refueling station;
establishing an oil product quantitative scoring model to carry out quantitative scoring on the oil product,
the oil product quantitative scoring model comprises the following components:
in this example, x1～xnIncluding the current oil consumption per hundred kilometers, driving style score, in-vehicle electrical equipment information, road characteristic information and historical refueling times, f1～fnThe weight corresponding to each parameter; the driving style is scored by comparing oil consumption per hundred kilometers of different driving styles after the same gas station is filled with oil, the road characteristic information is the evaluation of the road condition by detecting the bumping condition and the inclination angle of a vehicle body when the vehicle runs, and the in-vehicle electric appliance information is the service time condition of in-vehicle electric appliances in an oil product analysis period; the historical refueling frequency score is the number of car owners refueling at least 10 times at the station; and after various data are obtained, the weights are preset, and the data are respectively substituted into the oil product quantitative scoring model to obtain the total score, and the total score is transmitted to a user to be used as the fuel quality reference of the gas station.
The oil analysis method of the gas station further comprises the following steps:
s3, uploading the driving habit data to a background cloud, comparing the influence of the difference of brake data, accelerator data, steering wheel data, vehicle speed data and gear data in each group of driving habit data on fuel consumption per hundred kilometers by the background cloud, and sending one or more driving habit data with the minimum average fuel consumption to a driver;
in order to reduce the oil consumption speed, the background cloud end can recommend a plurality of driving schemes for saving the oil amount to the vehicle owner, for example, the driving scheme can keep constant-speed driving and emergency braking can be reduced as much as possible.
In order to implement the oil analysis method of the gas station, the invention also discloses an oil analysis system of the gas station, which refers to fig. 2 and comprises an acquisition module, a processing module, a positioning module, a background cloud and a communication module; wherein,
the system is used for acquiring data such as oil mass information, in-vehicle electrical appliance information, road characteristic information, odometer reading and current driving habit data; the acquisition modules are distributed on the whole vehicle to acquire analog signals or are associated with a control system of the vehicle so as to acquire various required data.
The processing module is used for acquiring the acquired data of the acquisition module, identifying the current driving style by comparing the current driving habit data with the historical driving habit data stored in the processing module, calculating the oil consumption per hundred kilometers after the new oil quantity reaches a preset proportion, and uploading the current oil consumption per hundred kilometers and the historical oil consumption per hundred kilometers; the processing module, in addition to analyzing and transmitting the collected data, stores all the data generated for each oil analysis cycle. And the positioning module is used for acquiring and uploading the information of the gas station closest to the vehicle after the new fuel quantity reaches a preset proportion.
The processing module and the positioning module are respectively associated with the background cloud end through the communication module, the background cloud end is used for acquiring information uploaded by the processing module and information uploaded by the positioning module of the gas station, and the current oil consumption per hundred kilometers and the historical oil consumption per hundred kilometers of the driving style are compared, so that the oil consumption of the gas station at the current time is quantitatively scored.
When a user wants to acquire driving habit information for saving oil, the processing module uploads current driving habit data and historical driving habit data to a background cloud end, the background cloud end compares oil consumption per hundred kilometers corresponding to each group of driving habit data, and sends a plurality of driving habit data with the minimum oil consumption per hundred kilometers to the processing module, and the processor transmits the driving habit data to the user in a display screen display or voice broadcast mode.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system and the module described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In addition, each module in the present invention is only a logical function partition, and there may be another partition manner in actual implementation, for example, all the modules may exist as a physical entity integrated together, or each unit exists as a single physical entity, or two or more units are integrated together, and the integrated unit may be implemented in a form of hardware, or may be implemented in a form of a software functional unit.
Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art will understand that various changes, modifications and substitutions can be made without departing from the spirit and scope of the invention as defined by the appended claims. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
1. A method for analyzing oil products of a gas station is characterized by comprising the following steps:
s1, acquiring mileage information, in-vehicle electrical appliance information and geographic information of the vehicle, and detecting the oil quantity change condition of the vehicle in real time;
s2, if the oil quantity of the vehicle is increased and the new oil quantity ratio is larger than a preset ratio, obtaining the information of a gas station nearest to the current position of the vehicle, and starting an oil analysis period;
the oil analysis cycle comprises the following steps:
s21, calculating the oil consumption per hundred kilometers;
s22, recording driving habit data of a current driver, and identifying the driving style of the driver through the driving habit data, wherein the driving habit data comprises brake data, accelerator data, steering wheel data, vehicle speed data and gear data;
and S23, feeding back the current oil consumption per hundred kilometers in real time, uploading the current oil consumption per hundred kilometers, the information of the gas station and the historical oil consumption per hundred kilometers of the driving style to a background cloud, comparing the current oil consumption per hundred kilometers and the historical oil consumption per hundred kilometers of the driving style by the background cloud, and analyzing the current fuel quality under the same driving style.
2. The gasoline station oil analysis method of claim 1, further comprising the steps of:
and S3, uploading the driving habit data to a background cloud end, comparing the influence of the difference of brake data, accelerator data, steering wheel data, vehicle speed data and gear data in each group of driving habit data on the fuel consumption per hundred kilometers, and sending one or more driving habit data with the minimum average fuel consumption to the driver.
3. The method for analyzing the gasoline station oil of claim 1, wherein the predetermined ratio in step S2 is four times the amount of fresh oil.
4. The gasoline station oil analysis method of claim 1, wherein the driving style recognition through the driver habit in the step S22 is specifically as follows: and comparing the acquired driving habit data with historical driving habit data, and judging the driving habit data to be the same driving style if at least three groups of brake data, accelerator data, steering wheel data, vehicle speed data or gear data in the two groups of driving habit data are the same, or judging the driving habit data to be different driving styles.
5. The gasoline station oil analysis method of claim 1, wherein the step S23 further comprises the steps of:
acquiring road characteristic information, engine speed and historical refueling times of the vehicle at a current refueling station;
establishing an oil product quantitative scoring model for quantitatively scoring an oil product, wherein the oil product quantitative scoring model is as follows:
wherein x is1～xnIncluding the current oil consumption per hundred kilometers, driving style score, in-vehicle electrical equipment information, road characteristic information, engine speed and historical refueling times, f1～fnThe weight corresponding to each parameter.
6. A gasoline station oil analysis system for implementing the gasoline station oil analysis method of any one of claims 1 to 5, comprising:
the acquisition module is used for acquiring oil mass information, in-vehicle electrical appliance information, road characteristic information, odometer reading and current driving habit data;
the processing module is used for acquiring the acquired data of the acquisition module, identifying the current driving style by comparing the current driving habit data with the historical driving habit data stored in the processing module, calculating the oil consumption per hundred kilometers after the new oil quantity reaches a preset proportion, and uploading the current oil consumption per hundred kilometers and the historical oil consumption per hundred kilometers;
the positioning module is used for acquiring and uploading the information of a gas station closest to the vehicle after the new oil quantity reaches a preset proportion;
the background cloud end is used for acquiring the information uploaded by the processing module and the information uploaded by the positioning module of the gas station, and comparing the current oil consumption per hundred kilometers and the historical oil consumption per hundred kilometers of the driving style, so that the oil consumption of the gas station at the current time is quantitatively scored;
and the communication module is used for establishing signal connection between the processing module and the background cloud end and between the positioning module and the background cloud end.
7. The gas station oil analysis system of claim 6, wherein the processing module is further configured to upload current driving habit data and historical driving habit data to a background cloud; the background cloud is further used for analyzing the influence of the difference of each group of driving habit data on the oil consumption per hundred kilometers, and sending one or more driving habit data with the minimum oil consumption per hundred kilometers to the processing module.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910716153.9A CN110414860A (en) | 2019-08-02 | 2019-08-02 | Loss of Oil Products at Gas Station analysis method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910716153.9A CN110414860A (en) | 2019-08-02 | 2019-08-02 | Loss of Oil Products at Gas Station analysis method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110414860A true CN110414860A (en) | 2019-11-05 |
Family
ID=68365651
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910716153.9A Pending CN110414860A (en) | 2019-08-02 | 2019-08-02 | Loss of Oil Products at Gas Station analysis method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110414860A (en) |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111698298A (en) * | 2020-05-28 | 2020-09-22 | 北京百度网讯科技有限公司 | Method and device for determining newly added vehicle energy station |
| CN112730813A (en) * | 2020-12-25 | 2021-04-30 | 青岛无车承运服务中心有限公司 | Oil filling point oil product analysis method of remote monitoring platform based on OBD system |
| CN112817256A (en) * | 2020-12-31 | 2021-05-18 | 车主邦（北京）科技有限公司 | Method and device for monitoring oil for transport vehicle |
| CN113060130A (en) * | 2021-04-13 | 2021-07-02 | 龙岩学院 | Vehicle driving assistance control system, control method and storage medium |
| CN113156053A (en) * | 2020-12-23 | 2021-07-23 | 广州市云景信息科技有限公司 | Gas station identification method for unlicensed and unlicensed operation |
| CN113850015A (en) * | 2021-08-05 | 2021-12-28 | 北京蜂云科创信息技术有限公司 | Method and system for distinguishing type of gas station based on CAN data |
| CN114179739A (en) * | 2021-12-24 | 2022-03-15 | 无锡伟博汽车科技有限公司 | Algorithm system for evaluating quality of diesel oil product added to truck |
| CN114511226A (en) * | 2022-02-09 | 2022-05-17 | 浙江吉利控股集团有限公司 | A method for analyzing fuel oil products and a method for pushing the scores of gas stations |
| CN114954299A (en) * | 2022-05-19 | 2022-08-30 | 李诣坤 | Fuel consumption early warning method and system for reducing fuel consumption of automobile |
| CN116402409A (en) * | 2023-06-07 | 2023-07-07 | 北京英视睿达科技股份有限公司 | Oil quality identification method for gas station based on OBD system |
| CN116485266A (en) * | 2023-04-26 | 2023-07-25 | 车泊喜智能科技(山东)有限公司 | Internet of things-based intelligent management method and system for oiling oil |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104132704A (en) * | 2014-07-16 | 2014-11-05 | 深圳市凯伦圣科技有限公司 | Fuel consumption analysis method and system |
| CN104200267A (en) * | 2014-09-23 | 2014-12-10 | 清华大学 | Vehicle driving economy evaluation system and vehicle driving economy evaluation method |
| CN104240326A (en) * | 2013-06-06 | 2014-12-24 | 广州汽车集团股份有限公司 | Vehicle economical-driving evaluation server and vehicle driving management method |
| CN109100493A (en) * | 2018-08-21 | 2018-12-28 | 上海博泰悦臻网络技术服务有限公司 | oil quality monitoring method and server |
-
2019
- 2019-08-02 CN CN201910716153.9A patent/CN110414860A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104240326A (en) * | 2013-06-06 | 2014-12-24 | 广州汽车集团股份有限公司 | Vehicle economical-driving evaluation server and vehicle driving management method |
| CN104132704A (en) * | 2014-07-16 | 2014-11-05 | 深圳市凯伦圣科技有限公司 | Fuel consumption analysis method and system |
| CN104200267A (en) * | 2014-09-23 | 2014-12-10 | 清华大学 | Vehicle driving economy evaluation system and vehicle driving economy evaluation method |
| CN109100493A (en) * | 2018-08-21 | 2018-12-28 | 上海博泰悦臻网络技术服务有限公司 | oil quality monitoring method and server |
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111698298B (en) * | 2020-05-28 | 2023-02-17 | 阿波罗智联(北京)科技有限公司 | Method and device for determining newly added vehicle energy station |
| CN111698298A (en) * | 2020-05-28 | 2020-09-22 | 北京百度网讯科技有限公司 | Method and device for determining newly added vehicle energy station |
| CN113156053A (en) * | 2020-12-23 | 2021-07-23 | 广州市云景信息科技有限公司 | Gas station identification method for unlicensed and unlicensed operation |
| CN112730813A (en) * | 2020-12-25 | 2021-04-30 | 青岛无车承运服务中心有限公司 | Oil filling point oil product analysis method of remote monitoring platform based on OBD system |
| CN112817256A (en) * | 2020-12-31 | 2021-05-18 | 车主邦（北京）科技有限公司 | Method and device for monitoring oil for transport vehicle |
| CN113060130A (en) * | 2021-04-13 | 2021-07-02 | 龙岩学院 | Vehicle driving assistance control system, control method and storage medium |
| CN113060130B (en) * | 2021-04-13 | 2022-09-09 | 龙岩学院 | Vehicle driving assistance control method and storage medium |
| CN113850015A (en) * | 2021-08-05 | 2021-12-28 | 北京蜂云科创信息技术有限公司 | Method and system for distinguishing type of gas station based on CAN data |
| CN114179739A (en) * | 2021-12-24 | 2022-03-15 | 无锡伟博汽车科技有限公司 | Algorithm system for evaluating quality of diesel oil product added to truck |
| CN114511226A (en) * | 2022-02-09 | 2022-05-17 | 浙江吉利控股集团有限公司 | A method for analyzing fuel oil products and a method for pushing the scores of gas stations |
| CN114954299A (en) * | 2022-05-19 | 2022-08-30 | 李诣坤 | Fuel consumption early warning method and system for reducing fuel consumption of automobile |
| CN114954299B (en) * | 2022-05-19 | 2023-02-17 | 李诣坤 | Fuel consumption early warning method and system for reducing fuel consumption of automobile |
| CN116485266A (en) * | 2023-04-26 | 2023-07-25 | 车泊喜智能科技(山东)有限公司 | Internet of things-based intelligent management method and system for oiling oil |
| CN116485266B (en) * | 2023-04-26 | 2023-09-22 | 车泊喜智能科技(山东)有限公司 | Internet of things-based intelligent management method and system for oiling oil |
| CN116402409A (en) * | 2023-06-07 | 2023-07-07 | 北京英视睿达科技股份有限公司 | Oil quality identification method for gas station based on OBD system |
| CN116402409B (en) * | 2023-06-07 | 2023-10-24 | 北京英视睿达科技股份有限公司 | Oil quality identification method for gas station based on OBD system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110414860A (en) | Loss of Oil Products at Gas Station analysis method and system | |
| US8099207B2 (en) | Method for determining the performance of motor vehicle consumables | |
| CN111806239B (en) | Electric vehicle endurance mileage measuring method, electronic device, and storage medium | |
| US9747730B2 (en) | Driver measurement and incentive system for improving fuel-efficiency | |
| WO2017190595A1 (en) | Vehicle data processing method, apparatus, and terminal device | |
| EP2036777B1 (en) | Method and system of providing driving data to a driver of a vehicle | |
| EP2320387A1 (en) | A method and device for evaluating vehicle's fuel consumption efficiency | |
| CN108475358B (en) | Method and system for evaluating driver's trip performance | |
| CN108431837B (en) | Method and system for evaluating driver's trip performance | |
| CN108369682B (en) | Method and system for evaluating driver's trip performance | |
| CA2748797A1 (en) | Driving management system and method | |
| CN110853179A (en) | Internet of vehicles server, vehicle and vehicle oil consumption prompting method based on driving data | |
| CN108369683B (en) | Method and system for evaluating driver's trip performance | |
| EP3891512B1 (en) | System and method for providing an indication of driving performance | |
| CN115158345A (en) | Correction prompting method and device for high-oil-consumption driving of vehicle | |
| CN109115997A (en) | oil quality monitoring method and server | |
| US20200160407A1 (en) | Server apparatus and information providing method | |
| EP3154839A1 (en) | Driving assistance method for increasing the awareness of drivers of vehicles about fuel consumption and/or other consumption sources of the vehicle | |
| US20180297604A1 (en) | Method and system for assessing the trip performance of a driver | |
| CN110874873A (en) | Vehicle and vehicle information processing method and device | |
| US20200159199A1 (en) | Server apparatus and information providing method | |
| CN103890558A (en) | Vehicle diagnostic method, and external diagnostic device | |
| JP2010102699A (en) | Vehicle operation management system | |
| CN112445969A (en) | Man-machine interaction method and device based on Internet of vehicles | |
| CN119359139A (en) | Vehicle control multi-dimensional fusion-based scoring system and scoring method for various data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20191105 |