CN110375757A - Intelligently auxiliary roadway line gauge draws method to new-energy automobile based on big data - Google Patents
Intelligently auxiliary roadway line gauge draws method to new-energy automobile based on big data Download PDFInfo
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- CN110375757A CN110375757A CN201910566692.9A CN201910566692A CN110375757A CN 110375757 A CN110375757 A CN 110375757A CN 201910566692 A CN201910566692 A CN 201910566692A CN 110375757 A CN110375757 A CN 110375757A
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- 238000000034 method Methods 0.000 title claims abstract description 27
- 230000005611 electricity Effects 0.000 claims abstract description 46
- 238000012545 processing Methods 0.000 claims abstract description 9
- 230000008569 process Effects 0.000 claims description 10
- 238000005265 energy consumption Methods 0.000 description 6
- 238000005457 optimization Methods 0.000 description 3
- 230000006855 networking Effects 0.000 description 2
- 230000002265 prevention Effects 0.000 description 2
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- 230000003044 adaptive effect Effects 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3469—Fuel consumption; Energy use; Emission aspects
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/36—Input/output arrangements for on-board computers
- G01C21/3697—Output of additional, non-guidance related information, e.g. low fuel level
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Abstract
The invention discloses a kind of, and the new-energy automobile based on big data intelligently assists roadway line gauge to draw method, include: that different operating conditions is divided according to the region of vehicle driving, time, road information and situation of turning on the aircondition, different power consumption values basic parameters are arranged to different operating conditions；Traveling traffic information is obtained according to the route of planning based on big data, obtains milimeter number or the time that destination in programme path includes each operating condition section；It calculates by milimeter number or time by programme path institute's electricity demand and route power demand；Institute's electricity demand is compared with battery remaining power, and judges the priority of setting；If the event of processing is preferential or electricity consumption is at least preferential, battery remaining power is more than or equal to institute's electricity demand, then agrees to the programme path；If battery remaining power is less than institute's electricity demand, according to the priority of setting again programme path, by charging pile planning in route.The travel distance of prediction more rationally, accurately, can obtain optimal driving scheme from several dimensions.
Description
Technical field
The invention belongs to new-energy automobile intelligence ancillary technique fields, more particularly to a kind of new energy based on big data
Automobile intelligent assists roadway line gauge to draw method.
Background technique
New-energy automobile (pure electric automobile and hybrid vehicle) generally comprises Vidacare corp, has quickly dynamic
Therefore the characteristic of response is suitable for the intelligence auxiliary such as adaptive cruise, driving correction and quick navigation and drives and unpiloted
Using.
Although also occurring so-called intelligent navigation in terms of navigation, usually only when the route appearance originally planned seriously is gathered around
After stifled, just inform that driver selects other route, therefore, this navigation all belongs to post property, lacks pre-
Opinion property does not have help to advance preventing congestion.New-energy automobile is often equipped with estimation battery remaining power and can travel at present
Mileage algorithm, but existing prediction mileage algorithm is calculated according to the average energy consumption value being stored in vehicle, this makes
The mileage of prediction is often inaccuracy.
Chinese patent literature CN 108592930 discloses a kind of new-energy automobile based on Large system optimization and car networking
Real-time road condition information is mapped to the current path weight between path node by intelligent auxiliary driving method, by towards big system
The multiobjective Dynamic Optimization of system determines the travel route of each car in real time, carries out real-time navigation, makes entire city integrated oil consumption
(converting electric energy to nominal oil consumption) is minimum, carbon emission is minimum.It is to adjust route with energy consumption, predicts that the algorithm of mileage is also
It is calculated according to the stored average energy consumption value of vehicle.
Summary of the invention
For the above technical problems, the new-energy automobile intelligence based on big data that the object of the present invention is to provide a kind of
Roadway line gauge can be assisted to draw method, input road conditions big data in real time in conjunction with big data, according to traffic information, vehicle demand electricity
Amount and the information such as battery dump energy, and most short preferential, energy consumption preferential with event, time-consuming it is minimum it is preferential, mileage travelled is most short excellent
First etc. several dimensions obtain optimal driving scheme.
The technical scheme is that
A kind of new-energy automobile intelligence auxiliary roadway line gauge stroke method based on big data, comprising the following steps:
S01: different operating conditions is divided according to the region of vehicle driving, time, road information and situation of turning on the aircondition, to different works
Different power consumption values basic parameters are arranged in condition；
S02: traveling traffic information is obtained according to the route of planning based on big data, obtaining destination in programme path includes each work
The milimeter number in condition section or time；
S03: including the milimeter number in each operating condition section according to destination in the power consumption values basic parameter and programme path of different operating conditions
Or the time calculates and travels by programme path to electricity needed for destination and route power demand；
S04: traveling destination institute's electricity demand is compared with battery remaining power, and judges the priority of setting；
S05: if processing event is preferential or electricity consumption is at least preferential, battery remaining power is more than or equal to institute's electricity demand, then agreeing to should
Programme path；Charging pile is planned according to the priority of setting again programme path if battery remaining power is less than institute's electricity demand
In route.
In preferred technical solution, the power consumption values basic parameter in the step S01 is distributed according to national temperature band to be divided
Region, using month as frame, and energy needed for calculating separately the non-flameout state of parking per minute according to situation of turning on the aircondition, township road is every
Average energy needed for kilometer, average energy needed for every kilometer of town way, average energy needed for every kilometer of highway and special
Average energy needed for every kilometer of operating condition.
In preferred technical solution, the power consumption values basic parameter in the step S01 is adjusted according to big data.
In preferred technical solution, after being arrived at the destination in the step S05, charging pile near search destination, if place
Reason location of incident nearby has charging pile, then handles event and carry out simultaneously with Vehicular charging, otherwise after the completion of processing event, according to filling
The jam situation selection charging pile charging of electric stake.
In preferred technical solution, in the step S02, if destination is multistage destination, according to multistage destination point
Other programme path, and priority is respectively set to multistage destination, it obtains multistage destination in programme path and separately includes each work
The milimeter number in condition section.
In preferred technical solution, real-time judge battery dump energy in the process of moving, if battery in the process of moving
Remaining capacity reminds driver lower than when reaching nearest charging pile institute electricity demand.
Compared with prior art, the beneficial effects of the present invention are:
Present invention combination big data and car networking input road conditions big data in real time, according to traffic information, vehicle demand electricity with
The information such as battery dump energy, the travel distance of prediction more rationally, accurately, can determine whether before vehicle electricity is used up
Can arrive at the destination, and most short preferential, energy consumption preferential with event, time-consuming it is minimum it is preferential, the most short priority scheduling of mileage travelled is several
Dimension obtains optimal driving scheme.
Detailed description of the invention
The invention will be further described with reference to the accompanying drawings and embodiments:
Fig. 1 divides institute's electricity demand schematic diagram according to different operating conditions for the present invention；
Fig. 2 is the flow chart for intelligently assisting roadway line gauge to draw method the present invention is based on the new-energy automobile of big data.
Specific embodiment
In order to make the objectives, technical solutions and advantages of the present invention clearer, With reference to embodiment and join
According to attached drawing, the present invention is described in more detail.It should be understood that these descriptions are merely illustrative, and it is not intended to limit this hair
Bright range.In addition, in the following description, descriptions of well-known structures and technologies are omitted, to avoid this is unnecessarily obscured
The concept of invention.
Embodiment:
As shown in Figure 1, intelligently auxiliary roadway line gauge draws method to the new-energy automobile of the invention based on big data, including following
Step:
S01: different operating conditions is divided according to the region of vehicle driving, time, road information and situation of turning on the aircondition, to different works
Different power consumption values basic parameters are arranged in condition；
S02: traveling traffic information is obtained according to the route of planning based on big data, obtaining destination in programme path includes each work
The milimeter number in condition section or time；
S03: including the milimeter number in each operating condition section according to destination in the power consumption values basic parameter and programme path of different operating conditions
Or the time calculates and travels by programme path to electricity needed for destination and route power demand；
S04: traveling destination institute's electricity demand is compared with battery remaining power, and judges the priority of setting；
S05: if processing event is preferential or electricity consumption is at least preferential, battery remaining power is more than or equal to institute's electricity demand, then agreeing to should
Programme path；Charging pile is planned according to the priority of setting again programme path if battery remaining power is less than institute's electricity demand
In route.
Mainly there are two parts for realization process, first is that energy needed for prediction vehicle, drives a vehicle second is that being realized according to calculated result
Strategic planning.
As shown in Figure 1, energy needed for prediction vehicle, divides region by temperature band distribution according to the whole nation, using month as frame,
The non-flameout state of parking required energy per minute is calculated separately according to situation of turning on the aircondition, is averaged needed for general every kilometer of the operating condition in township road
Energy, average energy needed for general every kilometer of the operating condition of town way, average energy needed for every kilometer of highway, special operation condition are every
Average energy needed for kilometer increases part Redundancy Design, obtains mean value needed for every kilometer under different work condition environments.The temperature in China
Band includes 6 kinds, and situation of turning on the aircondition, which can be divided into, does not turn on the aircondition, opens three kinds of warm wind of refrigeration and unlatching, by dividing in month 12 months.
Each operating condition of vehicle, as basic parameter, furthermore can also be used the time to distinguish as unit, such as often using as unit of every kilometer
Average energy needed for ten minutes etc..
In addition, adding artificial intelligence learning algorithm, energy consumption precision under the real-time various operating conditions of optimization of collection adjusts different operating conditions
Lower basic parameter improves precision of prediction.
As shown in Fig. 2, driving strategic planning, inputs multistage destination, various operating condition sections in route are presented in programme path
Milimeter number calculates and travels destination institute's electricity demands at different levels and route power demand, by event is preferential or a minimum of elder generation of electricity consumption, if
It is fully able to meet, then agrees to this programme path.If being unable to satisfy, rational routes are planned again, arrive each classification destination row
Electricity is mended by charging pile during sailing；If in the process of moving battery capacity lower than being needed when reaching nearest charging pile institute electricity demand and
When remind driving personnel note that charge as early as possible, the risk that prevention electricity is used up.
It is illustrated below with specific example:
Step 1: travelling road conditions essential information needed for collecting during vehicle is reached home based on big data, new energy vehicle is surplus
Remaining 80 degree of electricity, Chinese Suzhou District travels summer August part, and driving process whole process is turned on the aircondition, and level-one destination is positioned, need by
60 kilometers of highway, 80 kilometers of town road, 40 kilometers of farm-to-market road, the non-flameout state of parking 1 hour；Second level destination,
Need to be 60 kilometers by cities and towns, 20 kilometers of small towns；Three-level destination is that terminal is also starting point, need to be 60 kilometers through highway, cities and towns
140 kilometers, 60 kilometers of township road, night the coast is clear is without the non-flameout state of parking.
Step 2: collecting data according to different operating conditions and demarcated, the related road conditions power consumption values basic parameter of setting, i.e., and every kind
Average kilometer energy demand value, this basic parameter will be optimized by later period practical vehicular behavior under work condition environment.
Step 3: each road conditions are by month and whether open air-conditioning, and electricity needed for carrying out calculates, by this route running, from
It sets out and needs about 74 degree of electricity of electricity to level-one destination；Level-one is to 30 degree of electricity of second level electricity demand；Second level is to terminal three-level destination
Need 100 degree of electricity.
Step 4: this driving backhaul is set out, backhaul second level to three-level purpose preferential with event to level-one, second level destination
Ground is at least preferential with electricity consumption.
Step 5: electricity meets level-one destination, does not support second level destination.Then starting point to level-one destination can be direct
Traveling is travelled to level-one destination, handles event, if processing location of incident nearby has charging pile, handles event and vehicle
It charges while carrying out.Otherwise it selects the charging of idle state charging pile preferential after the completion of processing event, reduces queue time.
Step 6: after charging, 120 degree of battery dump energy, meet second level destination, but do not support three-level destination.Directly
It connects by planning traveling to second level destination locations, it is preferential to handle thing.Second level needs 100 degree of electricity to three-level destination, electric at this time
The remaining 90 degree of electricity in pond, do not support directly to return, should mend electricity in the process of moving, since backhaul is at least preferential with electricity consumption, then advise
It draws the charged stake of the shortest distance in backhaul route and mends circuit line.
Step 7: safety measures, if battery dump energy is lower than reaching nearest charging pile institute electricity demand in the process of moving
When need to remind driver in time note that charging as early as possible, the risk that prevention electricity is used up.
It should be understood that above-mentioned specific embodiment of the invention is used only for exemplary illustration or explains of the invention
Principle, but not to limit the present invention.Therefore, that is done without departing from the spirit and scope of the present invention is any
Modification, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.In addition, appended claims purport of the present invention
Covering the whole variations fallen into attached claim scope and boundary or this range and the equivalent form on boundary and is repairing
Change example.
Claims (6)
1. intelligently auxiliary roadway line gauge draws method to a kind of new-energy automobile based on big data, which is characterized in that including following
Step:
S01: different operating conditions is divided according to the region of vehicle driving, time, road information and situation of turning on the aircondition, to different works
Different power consumption values basic parameters are arranged in condition；
S02: traveling traffic information is obtained according to the route of planning based on big data, obtaining destination in programme path includes each work
The milimeter number in condition section or time；
S03: including the milimeter number in each operating condition section according to destination in the power consumption values basic parameter and programme path of different operating conditions
Or the time calculates and travels by programme path to electricity needed for destination and route power demand；
S04: traveling destination institute's electricity demand is compared with battery remaining power, and judges the priority of setting；
S05: if processing event is preferential or electricity consumption is at least preferential, battery remaining power is more than or equal to institute's electricity demand, then agreeing to should
Programme path；Charging pile is planned according to the priority of setting again programme path if battery remaining power is less than institute's electricity demand
In route.
2. intelligently auxiliary roadway line gauge draws method to the new-energy automobile according to claim 1 based on big data, special
Sign is that the power consumption values basic parameter in the step S01 is distributed according to national temperature band divides region, using month as frame,
And energy needed for according to situation of turning on the aircondition calculating separately the non-flameout state of parking per minute, average energy needed for every kilometer of township road,
Average energy needed for every kilometer of town way, it is average needed for every kilometer of average energy and special operation condition needed for every kilometer of highway
Energy.
3. intelligently auxiliary roadway line gauge draws method to the new-energy automobile according to claim 2 based on big data, special
Sign is that the power consumption values basic parameter in the step S01 is adjusted according to big data.
4. intelligently auxiliary roadway line gauge draws method to the new-energy automobile according to claim 1 based on big data, special
Sign is, after arriving at the destination in the step S05, charging pile near search destination fills if processing location of incident nearby has
Electric stake then handles event and carries out simultaneously with Vehicular charging, otherwise after the completion of processing event, is selected according to the jam situation of charging pile
Charging pile charging.
5. intelligently auxiliary roadway line gauge draws method to the new-energy automobile according to claim 1 based on big data, special
Sign is, in the step S02, if destination is multistage destination, distinguishes programme path according to multistage destination, and to multistage
Priority is respectively set in destination, obtains the milimeter number that multistage destination in programme path separately includes each operating condition section.
6. intelligently auxiliary roadway line gauge draws method to the new-energy automobile according to claim 1 based on big data, special
Sign is, in the process of moving real-time judge battery dump energy, if battery dump energy is lower than reaching most in the process of moving
When nearly charging pile institute electricity demand, driver is reminded.
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Cited By (5)
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| CN110758177A (en) * | 2019-12-24 | 2020-02-07 | 宁波洁程汽车科技有限公司 | Power supply management method applied to extended-range cold storage vehicle |
| CN112217280A (en) * | 2020-09-28 | 2021-01-12 | 廖志玻 | New energy automobile charging prediction reminding system based on big data |
| CN113071474A (en) * | 2021-04-08 | 2021-07-06 | 浙江吉利控股集团有限公司 | Energy management method and system of vehicle and vehicle |
| CN113335126A (en) * | 2021-07-08 | 2021-09-03 | 恒大恒驰新能源汽车研究院(上海)有限公司 | Intelligent charging control method for new energy automobile, storage medium and electronic equipment |
| CN113741490A (en) * | 2020-05-29 | 2021-12-03 | 广州极飞科技股份有限公司 | Inspection method, inspection device, aircraft and storage medium |
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