CN103791961A - Method for estimating vehicle range - Google Patents
Method for estimating vehicle range Download PDFInfo
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- CN103791961A CN103791961A CN201410019341.3A CN201410019341A CN103791961A CN 103791961 A CN103791961 A CN 103791961A CN 201410019341 A CN201410019341 A CN 201410019341A CN 103791961 A CN103791961 A CN 103791961A
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Abstract
The invention provides a method for estimating a vehicle range. The method includes the steps that S101, position information and navigation information of a vehicle of a user are received; S102, road sections are classified according to the current position of the vehicle of a user and road information of a navigation path; S103, real-time oil consumption values of vehicles, matched with the vehicle of a user, on the classified road sections are collected, and the average value of the real-time oil consumption values of the vehicles, matched with the vehicle of a user, on all the classified road sections is worked out; S104, the real-time oil consumption average value of the whole path is worked out; S105, the value of a remaining vehicle range is estimated according to the amount of remaining fuel oil and the real-time oil consumption average value worked out in the S104 and is sent to the vehicle.
Description
Technical field
The present invention relates to automotive field, relate in particular to a kind of method of predicting vehicle Fuel Remained amount mileage number.
Background technology
In prior art, vehicle can be according to predicting the remaining mileage number of vehicle when the Fuel Remained amount in average fuel consumption and the oil tank of vehicle of vehicle in front.Prediction residual running mileage number is not only conducive to vehicle user and adds fuel oil to vehicle timely, and is conducive to vehicle user understanding vehicle fuel situation and selects different driving paths or select filling-up area etc.Further, based on the destination information of vehicle user input, guider can generate many bar navigations path automatically, comprising: shortest time, bee-line and consumption minimization etc.Vehicle user can, according to those parameters, be selected suitable guidance path.
But the vehicle residual running mileage number doping according to the average fuel consumption of vehicle is inaccurate, because being history based on vehicle, average fuel consumption of the prior art travels record and the historical average fuel consumption that calculates.What but in fact, vehicle user needed is according to the pratical and feasible mileage number of sailing of the vehicle in current driving procedure.Discreet value based on historical behavior can only reflecting history situation, cannot make prediction relatively accurately based on current road conditions.For example: the fuel consumption values that vehicle travels in Shanghai City is 11L/100KM.If Fuel Oil Remaining is 22L, what panel board provided so estimates distance travelled number is 200 kilometers.If but current car owner intends to drive to Nanjing by highway from Shanghai, and the oil consumption (such as 9L/100KM) on highway is lower than incity oil consumption, and the mileage number in high speed should be 22/9 to be multiplied by 100 and to equal 244 kilometers so.Obviously,, under different road environments, the numerical value of prediction has very large discrepancy.Further, run into extreme case, such as traffic jam etc., discrepancy may be larger.Therefore, there are problems in the residual running mileage number doping based on historical behavior in prior art, for example: if user judges according to this residual running mileage number, select filling-up area or oiling opportunity, can exist and miss refuelling station or wrongly estimate residual running mileage number and cause vehicle cannot arrive the generation of the situations such as destination.
Summary of the invention
In view of this, the invention provides a kind of method of predicting vehicle mileage number, comprising:
Step S101, positional information and the navigation information of reception user vehicle;
Step S102, according to the road information on the current location of user's vehicle and navigation way, carries out section classification;
Step S103, collects on sorted section and user's vehicle real-time fuel consumption of vehicle that matches, and calculates the mean value of the current real-time fuel consumption of vehicle that matches on each sorted section;
Step S104, calculates the real-time fuel consumption mean value on whole route; And
Step S105, according to the real-time fuel consumption mean value calculating in vehicle Fuel Remained amount and step S104, dopes vehicle residual running mileage number, and sends to vehicle.
Further, in step S101, described navigation information comprises destination information and route.
Further, in step S102, described road information refers to the geographical location information of road; According to the different names of road on route, carry out section classification.
Further, in step S102, described road information refers to the type information of road; Dissimilar according to road on route, carries out section classification.
Further, in step S102, described road information refers to the jam situation information of road; According to the different jam situations of road on route, carry out section classification.
Further, in step S103, described user's vehicle vehicle that vehicle refers to that discharge capacity is identical that matches, or all identical vehicles of discharge capacity brand and model.
Further, in step S104, the real-time fuel consumption mean value on described whole route is the mean value of each section real-time fuel consumption mean value on route.
Further, in step S104, the real-time fuel consumption mean value on described whole route is the oil consumption sum/road section length sum on section.
Further, the average real-time fuel consumption that the oil consumption on section is this section is multiplied by road section length.
In view of this, the present invention also provides a kind of method of predicting vehicle mileage number, comprising:
Step S201, the positional information of reception user vehicle;
Step S202, according in user's vehicle current location setting range road information, carry out section classification;
Step S203, collects on sorted section and user's vehicle real-time fuel consumption of vehicle that matches, and calculates the mean value of the current real-time fuel consumption of vehicle that matches on each sorted section;
Step S204, calculates the real-time fuel consumption mean value in setting range; And
Step S205, according to the real-time fuel consumption mean value in the described setting range calculating in vehicle Fuel Remained amount and step S204, dopes vehicle residual running mileage number, and sends to vehicle.
Further, described setting range refers to take vehicle current location as the center of circle, the scope that certain milimeter number is radius.
Further, described setting range refers to the scope that the certain milimeter number extra bus of vehicle headstock direction rear is diameter to certain milimeter number, and wherein the certain milimeter number of headstock direction is greater than car rear to certain milimeter number.
Further, in step S202, described road information refers to the geographical location information of road; According to the different names of road in setting range, carry out section classification.
Further, in step S202, described road information refers to the type information of road; Dissimilar according to road in setting range, carries out section classification.
Further, in step S202, described road information refers to the jam situation information of road; According to the different jam situations of road in setting range, carry out section classification.
Further, in step S203, described user's vehicle vehicle that vehicle refers to that discharge capacity is identical that matches, or all identical vehicles of discharge capacity brand and model.
Further, in step S204, the real-time fuel consumption mean value in described setting range is the mean value of each section real-time fuel consumption mean value on route.
Further, in step S204, the real-time fuel consumption mean value in described setting range is the oil consumption sum/road section length sum on section.
Further, the average real-time fuel consumption that the oil consumption on section is this section is multiplied by road section length.
The present invention predicts the method for vehicle mileage number, according to current road information, classified in section, calculate the average fuel consumption of the vehicle matching with user's vehicle on each section, and finally draw an average fuel consumption, thereby dope vehicle mileage number.Compared with prior art, more accurately, reliable.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet in a preferred embodiment of method that the present invention predicts vehicle mileage number;
Fig. 2 is the schematic flow sheet in another embodiment of method that the present invention predicts vehicle mileage number.
Embodiment
As shown in Figure 1, in the present invention one preferred embodiment, the present invention predicts the method for vehicle mileage number, comprising:
Step S101, positional information and the navigation information of reception user vehicle.Navigation information comprises destination information, or navigation information comprises destination information and route.
Step S102, according to the road information on the current location of user's vehicle and navigation way, carries out section classification.
Step S103, collects on sorted section and user's vehicle real-time fuel consumption of vehicle that matches, and calculates the mean value of the current real-time fuel consumption of vehicle that matches on each sorted section.
Step S104, calculates the real-time fuel consumption mean value on whole route.
Step S105, according to the real-time fuel consumption mean value on the described route calculating in vehicle Fuel Remained amount and step S104, dopes vehicle residual running mileage number, and sends to vehicle.
Wherein, in described step S101, user arranges navigation information on vehicle.After setting completes, navigation information is issued server by wireless network by vehicle.
In step S102, server, according to the road information on the current location of user's vehicle and navigation way, carries out section classification.In the present invention one preferred embodiment, described road information refers to the geographical location information of road.According to the different names of road on route, carry out section classification.For instance, the route of vehicle need to pass through Long Yanglu, Golden Bridge road and make widely known road, and this route is just divided into three sections so: imperial positive section, Golden Bridge section and make widely known section.
The present invention another preferred embodiment, described road information refers to the type information of road.Dissimilar according to road on route, carries out section classification.For instance, need to be through Wuning road (urban road), 312 national highways and expressway, Shanghai and Nanjing as the route of vehicle, this route is just divided into three sections so: urban road section, state's road segment segment and fastlink.
The present invention another preferred embodiment in, described road information refers to the jam situation information of road.According to the different jam situations of road on route, carry out section classification.For instance, the route of vehicle need to be through 3 sections of unimpeded sections, 2 sections of block up section and 1 section of obstruction, and this route is just divided into three sections so: unimpeded section, block up section and stop up section.Certainly, in other embodiments, described jam situation also can be divided into 1 grade of road conditions, 2 grades of road conditions, 3 grades of road conditions etc.
In step S103, server is collected on above-mentioned different sections of highway and user's vehicle real-time fuel consumption information of vehicle that matches, and calculates the average real-time fuel consumption on each section.Wherein, described user's vehicle vehicle that vehicle refers to that discharge capacity is identical that matches, or all identical vehicles of discharge capacity brand and model.For example user's vehicle is the A brand vehicle of 1.6 liters of discharge capacities, and whois lookup discharge capacity on different sections of highway is all the A brand vehicle of 1.6 liters so, and collects the real-time fuel consumption of those vehicles, calculates average real-time fuel consumption.In further example, because certain road section traffic volume situation is for stopping up, and server receives the vehicle mating with user and has 3, and oil consumption is respectively 7.5L/100KM, 7.3L/100KM and 7.7L/100KM, the average real-time fuel consumption in so final this section is: 7.5L/100KM.
In step S104, according to the average real-time fuel consumption in the each section having calculated, can calculate the real-time fuel consumption mean value on whole route.One preferred embodiment in, the real-time fuel consumption mean value on described whole route can be the mean value of each section real-time fuel consumption mean value on route.For example, have two different sections of highways on whole route, average real-time fuel consumption is respectively 7.4L/100KM and 8.0L/100KM, and the real-time fuel consumption mean value of so whole route is 7.7L/100KM.Another preferred embodiment in, the real-time fuel consumption mean value on described whole route is the oil consumption sum/road section length sum on section.Wherein, the average real-time fuel consumption that the oil consumption on section is this section is multiplied by this road section length.For example, have three different sections of highways on whole route, length is respectively 10KM, 30KM and 50KM, and on these three sections, average real-time fuel consumption is respectively 8.0L/100KM, 7.5L/100KM and 6.5/100KM.Real-time fuel consumption mean value on so whole route is (8*10+7.5*30+6.5*50)/(10+30+50), i.e. 7.0L/100KM.
In step S105, the real-time fuel consumption mean value on the described route calculating according to vehicle Fuel Remained amount and step S104, dopes vehicle residual running mileage number, and sends to vehicle.Specifically, the real-time fuel consumption mean value calculating according to step S104 is as the oil consumption of vehicle, then in conjunction with the current Fuel Remained amount of vehicle receiving from vehicle, can calculate when vehicle in front mileage number.For example: the real-time fuel consumption mean value calculating on navigation way is 7.0L/100KM, and fuel tank shows that Fuel Oil Remaining is 5L, and vehicle mileage number is about 71KM so.
The present invention, by arranging like this, predicts vehicle mileage number according to current road information, obviously than in prior art only the current oil consumption according to vehicle historical record come that estimating vehicle mileage number comes more accurately, reliable.
As shown in Figure 2, in another embodiment of the present invention, user not necessarily can arrange navigation information.The present invention predicts the method for vehicle mileage number, comprising:
Step S201, the positional information of reception user vehicle.
Step S202, according to the road information in user's vehicle current location setting range, carries out section classification.
Step S203, collects on sorted section and user's vehicle real-time fuel consumption of vehicle that matches, and calculates the mean value of the current real-time fuel consumption of vehicle that matches on each sorted section;
Step S204, calculates the real-time fuel consumption mean value in setting range; And
Step S205, according to the real-time fuel consumption mean value in the described setting range calculating in vehicle Fuel Remained amount and step S204, dopes vehicle residual running mileage number, and sends to vehicle.
Wherein, in step S201, server only receives the positional information of user's vehicle.
In step S202, one preferred embodiment in, described user's vehicle current location setting range refers to take vehicle current location as the center of circle, the scope that certain milimeter number is radius, for example certain milimeter number is 20KM.In another embodiment, described user's vehicle current location setting range refers to the scope that the certain milimeter number extra bus of vehicle headstock direction rear is diameter to certain milimeter number, and wherein the certain milimeter number of headstock direction is greater than car rear to certain milimeter number.For example: the certain milimeter number of headstock direction is 30KM, car rear is 10KM to certain milimeter number, and therefore described preset range is the scope of the circle of formation take 40KM as diameter.In another embodiment, described user's vehicle current location setting range is the scope that the certain milimeter number of headstock direction is diameter, or within the scope of the sector region of the certain milimeter number of headstock direction and certain angle.
In step S202, according to the road information in this setting range, carry out section classification.Described road information can be the geographical location information of road, also can refer to the dissimilar of road, can also be the different jam situations of road.Specifically please refer in above-mentioned embodiment described in step S102, repeat no more herein.
Step S203, with reference to the step S103 in above-mentioned embodiment.Described user's vehicle vehicle that vehicle refers to that discharge capacity is identical that matches, or all identical vehicles of discharge capacity brand and model.Repeat no more herein.
Step S204, with reference to the step S104 in above-mentioned embodiment.To " calculate the real-time fuel consumption mean value on whole route ", change to " calculating the real-time fuel consumption mean value in setting range ", calculate the real-time fuel consumption mean value in all sections in setting range.
Step S205, with reference to the step S105 in above-mentioned embodiment.By " according to the real-time fuel consumption mean value on the described route calculating in vehicle Fuel Remained amount and step S104 ", change to " according to the real-time fuel consumption mean value in the described setting range calculating in vehicle Fuel Remained amount and step S204 ".
Arrange like this, in the situation that user does not arrange navigation way, by said method also estimating vehicle mileage number comparatively accurately.
The present invention predicts that the method for vehicle mileage number is real-time.For example, calculate once at interval of a period of time (2 minutes or 5 minutes), more accurate with the vehicle mileage number of guaranteeing to dope.
The foregoing is only preferred embodiment of the present invention, in order to limit the present invention, within the spirit and principles in the present invention not all, any modification of making, be equal to replacement, improvement etc., within all should being included in the scope of protection of the invention.
Claims (19)
1. a method of predicting vehicle mileage number, is characterized in that, the method comprises:
Step S101, positional information and the navigation information of reception user vehicle;
Step S102, according to the road information on the current location of user's vehicle and navigation way, carries out section classification;
Step S103, collects on sorted section and user's vehicle real-time fuel consumption of vehicle that matches, and calculates the mean value of the current real-time fuel consumption of vehicle that matches on each sorted section;
Step S104, calculates the real-time fuel consumption mean value on whole route; And
Step S105, according to the real-time fuel consumption mean value calculating in vehicle Fuel Remained amount and step S104, dopes vehicle residual running mileage number, and sends to vehicle.
2. the method for claim 1, is characterized in that: in step S101, described navigation information comprises destination information and route.
3. the method for claim 1, is characterized in that: in step S102, described road information refers to the geographical location information of road; According to the different names of road on route, carry out section classification.
4. the method for claim 1, is characterized in that: in step S102, described road information refers to the type information of road; Dissimilar according to road on route, carries out section classification.
5. the method for claim 1, is characterized in that: in step S102, described road information refers to the jam situation information of road; According to the different jam situations of road on route, carry out section classification.
6. the method for claim 1, is characterized in that: in step S103, and described user's vehicle vehicle that vehicle refers to that discharge capacity is identical that matches, or all identical vehicles of discharge capacity brand and model.
7. the method as described in any one in claim 1 to 6, is characterized in that: in step S104, the real-time fuel consumption mean value on described whole route is the mean value of each section real-time fuel consumption mean value on route.
8. the method as described in any one in claim 1 to 6, is characterized in that: in step S104, the real-time fuel consumption mean value on described whole route is the oil consumption sum/road section length sum on section.
9. method as claimed in claim 8, is characterized in that: the average real-time fuel consumption that the oil consumption on section is this section is multiplied by road section length.
10. a method of predicting vehicle mileage number, is characterized in that, the method comprises:
Step S201, the positional information of reception user vehicle;
Step S202, according in user's vehicle current location setting range road information, carry out section classification;
Step S203, collects on sorted section and user's vehicle real-time fuel consumption of vehicle that matches, and calculates the mean value of the current real-time fuel consumption of vehicle that matches on each sorted section;
Step S204, calculates the real-time fuel consumption mean value in setting range; And
Step S205, according to the real-time fuel consumption mean value in the described setting range calculating in vehicle Fuel Remained amount and step S204, dopes vehicle residual running mileage number, and sends to vehicle.
11. methods as claimed in claim 10, is characterized in that: described setting range refers to take vehicle current location as the center of circle, the scope that certain milimeter number is radius.
12. methods as claimed in claim 10, is characterized in that: described setting range refers to the scope that the certain milimeter number extra bus of vehicle headstock direction rear is diameter to certain milimeter number, and wherein the certain milimeter number of headstock direction is greater than car rear to certain milimeter number.
13. methods as claimed in claim 10, is characterized in that: in step S202, described road information refers to the geographical location information of road; According to the different names of road in setting range, carry out section classification.
14. methods as claimed in claim 10, is characterized in that: in step S202, described road information refers to the type information of road; Dissimilar according to road in setting range, carries out section classification.
15. methods as claimed in claim 10, is characterized in that: in step S202, described road information refers to the jam situation information of road; According to the different jam situations of road in setting range, carry out section classification.
16. methods as claimed in claim 10, is characterized in that: in step S203, and described user's vehicle vehicle that vehicle refers to that discharge capacity is identical that matches, or all identical vehicles of discharge capacity brand and model.
17. methods as described in any one in claim 10 to 16, is characterized in that: in step S204, the real-time fuel consumption mean value in described setting range is the mean value of each section real-time fuel consumption mean value on route.
18. methods as described in any one in claim 10 to 16, is characterized in that: in step S204, the real-time fuel consumption mean value in described setting range is the oil consumption sum/road section length sum on section.
19. methods as claimed in claim 18, is characterized in that: the average real-time fuel consumption that the oil consumption on section is this section is multiplied by road section length.
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Cited By (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104236574A (en) * | 2014-08-26 | 2014-12-24 | 惠州市凯越电子有限公司 | Refueling reminding method |
| CN104848868A (en) * | 2015-05-21 | 2015-08-19 | 小米科技有限责任公司 | Vehicle energy supplementing reminding method and device |
| CN105957184A (en) * | 2016-04-27 | 2016-09-21 | 惠州市华阳多媒体电子有限公司 | Intelligent HUD data processing method and system |
| US9506775B2 (en) * | 2015-02-20 | 2016-11-29 | Qualcomm Incorporated | Smart fuel indicator |
| CN106323331A (en) * | 2016-08-22 | 2017-01-11 | 乐视控股（北京）有限公司 | Method and device of forecasting vehicle travel mileage |
| CN106846883A (en) * | 2017-01-25 | 2017-06-13 | 郑州云海信息技术有限公司 | A kind of vehicle location Forecasting Methodology and system |
| WO2017128798A1 (en) * | 2016-01-26 | 2017-08-03 | 京东方科技集团股份有限公司 | Smart fuel indication device and method |
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE19929426A1 (en) * | 1999-06-26 | 2000-12-28 | Bosch Gmbh Robert | Determining residual distance to be travelled involves computing distance from fuel quantity, current position, stored route, route-specific information using mean consumption figures |
| CN101645200A (en) * | 2009-08-19 | 2010-02-10 | 深圳华为通信技术有限公司 | Navigation path selecting method and device |
| CN102509470A (en) * | 2011-10-14 | 2012-06-20 | 北京掌城科技有限公司 | System and method for realizing energy conservation and emission reduction of vehicle based on dynamic path planning |
| CN102538890A (en) * | 2011-12-31 | 2012-07-04 | 北京中科微电子技术有限公司 | Method and device for obtaining course continuation mileage of motor vehicle |
| CN103324820A (en) * | 2012-03-20 | 2013-09-25 | 财团法人资讯工业策进会 | Driving oil consumption calculation method and driving oil consumption calculation system |
-
2014
- 2014-01-16 CN CN201410019341.3A patent/CN103791961B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE19929426A1 (en) * | 1999-06-26 | 2000-12-28 | Bosch Gmbh Robert | Determining residual distance to be travelled involves computing distance from fuel quantity, current position, stored route, route-specific information using mean consumption figures |
| CN101645200A (en) * | 2009-08-19 | 2010-02-10 | 深圳华为通信技术有限公司 | Navigation path selecting method and device |
| CN102509470A (en) * | 2011-10-14 | 2012-06-20 | 北京掌城科技有限公司 | System and method for realizing energy conservation and emission reduction of vehicle based on dynamic path planning |
| CN102538890A (en) * | 2011-12-31 | 2012-07-04 | 北京中科微电子技术有限公司 | Method and device for obtaining course continuation mileage of motor vehicle |
| CN103324820A (en) * | 2012-03-20 | 2013-09-25 | 财团法人资讯工业策进会 | Driving oil consumption calculation method and driving oil consumption calculation system |
Cited By (27)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104236574A (en) * | 2014-08-26 | 2014-12-24 | 惠州市凯越电子有限公司 | Refueling reminding method |
| US9506775B2 (en) * | 2015-02-20 | 2016-11-29 | Qualcomm Incorporated | Smart fuel indicator |
| CN104848868A (en) * | 2015-05-21 | 2015-08-19 | 小米科技有限责任公司 | Vehicle energy supplementing reminding method and device |
| WO2017128798A1 (en) * | 2016-01-26 | 2017-08-03 | 京东方科技集团股份有限公司 | Smart fuel indication device and method |
| US10429198B2 (en) | 2016-01-26 | 2019-10-01 | Boe Technology Group Co., Ltd. | Intelligent fuel prompt device and method |
| CN105957184A (en) * | 2016-04-27 | 2016-09-21 | 惠州市华阳多媒体电子有限公司 | Intelligent HUD data processing method and system |
| CN106323331A (en) * | 2016-08-22 | 2017-01-11 | 乐视控股（北京）有限公司 | Method and device of forecasting vehicle travel mileage |
| CN106846883A (en) * | 2017-01-25 | 2017-06-13 | 郑州云海信息技术有限公司 | A kind of vehicle location Forecasting Methodology and system |
| CN107089209A (en) * | 2017-05-25 | 2017-08-25 | 西安顺德电子科技有限公司 | A kind of method and apparatus for calculating electric automobile continual mileage |
| CN107351784A (en) * | 2017-06-30 | 2017-11-17 | 上海友衷科技有限公司 | A kind of information processing method and device |
| CN108759858A (en) * | 2018-06-29 | 2018-11-06 | 北京汽车股份有限公司 | A kind of course continuation mileage computational methods, computing device and automobile |
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