CN104002816B - A kind of vehicle geographical environment, which excavates, perceives fuel saving method - Google Patents
A kind of vehicle geographical environment, which excavates, perceives fuel saving method Download PDFInfo
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- 230000006855 networking Effects 0.000 claims abstract description 44
- 238000005070 sampling Methods 0.000 claims abstract description 40
- 230000004927 fusion Effects 0.000 claims abstract description 13
- 238000004140 cleaning Methods 0.000 claims abstract 2
- 238000010606 normalization Methods 0.000 claims description 21
- 230000008859 change Effects 0.000 claims description 12
- 230000004087 circulation Effects 0.000 claims description 12
- 238000013500 data storage Methods 0.000 claims description 9
- 238000013507 mapping Methods 0.000 claims description 8
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
- B60W40/06—Road conditions
- B60W40/076—Slope angle of the road
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
- B60W40/06—Road conditions
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
- B60W40/105—Speed
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/12—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to parameters of the vehicle itself, e.g. tyre models
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/10—Longitudinal speed
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2530/00—Input parameters relating to vehicle conditions or values, not covered by groups B60W2510/00 or B60W2520/00
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2552/00—Input parameters relating to infrastructure
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2552/00—Input parameters relating to infrastructure
- B60W2552/15—Road slope, i.e. the inclination of a road segment in the longitudinal direction
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Abstract
The present invention provides a kind of vehicle geographical environment and excavates perception fuel saving method, and this method comprises the following steps：Step 1, by start vehicle position data and running data be fused into data frame and be transmitted to car networking center；Step 2, the data frame for calling and cleaning storage, obtain all at the uniform velocity fragments of vehicle；Step 3, carry out centre data fusion at the uniform velocity fragment, obtains section Gradient and is transmitted to car networking center；The position that step 4, car networking center are transmitted according to driving vehicle, driving vehicle is handed down to by Gradient；Step 5, driving vehicle calculate the distance between satellite positioning coordinate and the front gradient E initial positions of driving vehicle D, and carry out decision-making according to gradient E and distance D using the Gradient returned.It is an advantage of the invention that：Accurate Gradient can not only be obtained, and without specially carrying out substantial amounts of sampling operation to road, is also not required to that extra sensor is installed, this greatly reduces input cost.
Description
Technical field
Excavated the present invention relates to a kind of vehicle geographical environment and perceive fuel saving method.
Background technology
The important directions that automobile fuel ecomomy is development of automobile technology are improved, except load-carrying, contour structures, transmission
Outside the factors such as efficiency, geographical environment also has significant impact to fuel economy.When the geographical ring that can find out road ahead in advance
During border, we can start to control the suitable acceleration of vehicle or engine turbine pressure etc. in position, and then
Improve fuel consumption performance when vehicle crosses slope.Therefore, the problem of geographical environment of vehicle traveling is one critically important how is perceived.
Tradition perceives the vehicle gradient and mainly uses sensor, such as obliquity sensor (patent of invention number：
201210076260.8), acceleration transducer (patent of invention number：200910088125.3 with 201210272414.0) or
GPS surveys high.The defects of conventional method is：When sensor measures the gradient, automobile is on slope, thus miss in advance
The opportunity of motivation of adjustment；According to prior measurement grade information, and then road grade information database method is built, then need to throw
Enter special measurement vehicle, and each measurement vehicle is required for installing extra sensor device, each sensor also needs to locate
Respective error is managed, this considerably increases input cost；High method is surveyed according to GPS, then is highly susceptible in measurement process
The influence of satellite-signal, particularly in the case of tunnel, cannot often use completely.
The content of the invention
The technical problem to be solved in the present invention, is that providing a kind of vehicle geographical environment excavates perception fuel saving method, passes through
The position data for starting vehicle is acquired and merged with running data, and the data frame of fusion is transmitted to car networking center,
Data cleansing is carried out to the data frame of all vehicles again and centre data merges, and obtained Gradient is stored in car networking
Center, the Gradient that driving vehicle is then issued according to car networking center carries out Vehicle Decision Method, so as to reach oil-saving effect.
A kind of vehicle geographical environment of the present invention, which excavates, perceives fuel saving method, includes the following steps：
After step 1, vehicle launch, just start to gather the satellite positioning coordinate of the vehicle, and by satellite positioning coordinate and road
Road mapping matching obtains the position data of the vehicle, while gathers the running data of the vehicle, afterwards by the traveling number of the vehicle
Data frame is fused into according to position data, and is uploaded to car networking center；
Step 2, calling are stored in the data frame of all vehicles at car networking center, and the data frame of all vehicles is carried out
Data cleansing, obtains all at the uniform velocity fragments；
Step 3, carry out centre data fusion to above-mentioned all at the uniform velocity fragments, obtains the Gradient in whole section, and will
Gradient is uploaded to car networking center；
The data frame or satellite positioning coordinate that step 4, car networking center are transmitted according to driving vehicle, by the gradient in front
Data distributing gives the driving vehicle；
The Gradient that step 5, driving vehicle are returned by car networking center, calculates the satellite positioning of the driving vehicle
The distance between coordinate and the front gradient E initial positions D, and decision-making is carried out according to gradient E and distance D.
Further, the step 1 specifically comprises the following steps：
Step 11, after vehicle is started, just according to the time interval △ T of sampling, to the satellite positioning coordinate of the vehicle into
Row collection；If satellite positioning is in effective status, sampling instant t is write downsAnd the satellite positioning coordinate p of the vehicles, it is laggard
Enter step 12；If satellite positioning is in failure state, 13 are entered step；
Step 12, using minimum vertical projector distance method combination vehicle heading, by the satellite positioning coordinate of the vehicle
psMapping matching is carried out with road, obtains the position data of the vehicle, and by the matched position p in the vehicle position datas' with
Sampling instant tsIt recorded in active position caching；The running data of the vehicle, then the running data by the vehicle are gathered at the same time
A data frame is formed with position data, and data frame is sent to by car networking center by wireless communication, is entered step afterwards
14；
Step 13, when above-mentioned active position caching in have record when, just from active position cache in take out the vehicle storage
Previous sampling instant tsMatched position ps', and with matched position ps' it is starting point, pass through the mileometer data and road of the vehicle
Road map calculates the position data of the vehicle, while the position data of the vehicle and the running data of collection are formed a data
Frame, and data frame is sent to by car networking center by wireless communication, 14 are entered step afterwards；When in above-mentioned active position caching
When not recording, step 14 is just directly entered；
If step 14, the vehicle stop traveling, its active position caching is emptied；If the vehicle continues to travel, return
Step 11 circulation performs.
Further, the step 2 specifically comprises the following steps：
Step 21, all data frames for taking out from the vehicle data storage table at car networking center wherein one car；
Step 22, the feature according to the time interval △ t between the neighbouring sample moment, stop the vehicle is all from starting to
Only the continuous data frame of process separates paragraph by paragraph, and each section of continuous data frame is pressed sampling instant tsOrder arranges；
Step 23, one section of continuous data frame for taking out above-mentioned vehicle, by engine speed n and automobile gear level d, converse
This section of continuous data frame is in each sampling instant tsSpeed vs, and derivation is carried out to the speed of each adjacent moment, accelerated
Spend as；According to the threshold epsilon of selection, a is judgedsWhether threshold epsilon is less than, if then the vehicle is in sampling instant tsLocate at the uniform velocity to travel,
Mark sampling instant tsData frame be 1；If otherwise the vehicle is in sampling instant tsLocate at the uniform velocity to travel to be non-, mark the sampling
Moment tsData frame be 0, continue to compare asValue, until having marked this section of continuous data frame；
Step 24, by sampling instant tsThe order of arrangement, scans the continuous data frame marked, will wherein continued labelling be
1 data frame all takes out, and is deposited into as at the uniform velocity fragment at the uniform velocity fragment buffer；
If all continuous data frames of step 25, the untreated complete vehicle, the circulation of return to step 23 performs；It is if processed
All continuous data frames of the complete vehicle, then enter step 26；
If the data frame of all vehicles, enters step 3 in step 26, the complete vehicle data storage table of executed；If do not hold
The data frames of all vehicles in vehicle data storage table is gone, then the circulation of return to step 21 performs.
Further, the step 3 specifically comprises the following steps：
Step 31, take from the uniform velocity fragment buffer the at the uniform velocity fragment a of load-carrying vehicle A known to one as initial segment, if should
In initial segment, the position data of vehicle is { pa1,pa2,…pan,pd1,pd2,…pdk, and by engine torque T and engine
Rotating speed n calculates each point power P；If adjacent position data pa2With pa1Power variation be Δ Pa2,a1, then this at the uniform velocity fragment is adjacent
The changed power sequence of position is：
Step 32, by initial segment a as current reference fragment, and according to its position data, from the uniform velocity fragment buffer
Find out with the at the uniform velocity fragment a at the uniform velocity fragment b that to have position data overlapping, and set this at the uniform velocity fragment b belong to vehicle B, position data
For { pd1,pd2,…pdk,pb1,pb2,…pbm, each point power P is calculated by engine torque T and engine speed n, then this is at the uniform velocity
The changed power sequence of fragment adjacent position is:
Step 33, in overlapping position data { pd1,pd2,…pdk-1Place, calculate B vehicle speeds and quality product feature phase
For the normalization coefficient { C of A vehicle speeds and quality product featured1,Cd2,…Cdk-1}；
Step 34, the value C by obtained normalization coefficientd1,Cd2,…Cdk-1It is averaging, obtains overall normalization coefficient C；
Step 35, using overall normalization coefficient C, by B cars at the uniform velocity on fragment b with load-carrying GBAnd the work(of at the uniform velocity uB travelings
Rate change sequenceA cars are normalized at the uniform velocity fragment b
On with load-carrying GAAnd at the uniform velocity uAThe changed power sequence of traveling, the changed power sequence after normalization are：
Step 36, by A cars at the uniform velocity fragment a with the uniform velocity on fragment b with load-carrying GAAnd at the uniform velocity uAThe changed power sequence of traveling
Splicing fusion is carried out, obtaining the changed power sequence after splicing fusion is：
{ΔPa2,a1,ΔPa3,a2,…,ΔPan,an-1,
CΔPb2,b1,CΔPb3,b2,…,CΔPbm,bm-1}；
If step 37, do not find out also with the uniform velocity fragment a all at the uniform velocity fragments that to have position data overlapping, by what is spliced
At the uniform velocity fragment is as current reference fragment, and the circulation of return to step 32 performs；If found out has position data weight with the uniform velocity fragment a
Folded all at the uniform velocity fragments, and all at the uniform velocity fragment assemblies are obtained into the changed power sequence in whole section, then enter step 38；
Step 38, utilize slope change amountIt is the gradient by the changed power sequence transitions in whole section
Change sequence, and send obtained Gradient to car networking center, wherein u is speed, and G is quality, and Δ P is changed power
Amount, ηTFor machinery driving efficiency.
Further, the step 4 specifically comprises the following steps：
The Gradient transmitted is stored in Gradient storage table by step 41, car networking center；
Satellite positioning coordinate and travel direction are uploaded to car networking center by step 42, driving vehicle；
Step 43, car networking center receive data frame or satellite positioning coordinate and the travel direction that driving vehicle transmits,
If what is received is the data frame of the driving vehicle, the matched position p in data frame is taken outs' and road section ID rs, enter step afterwards
Rapid 44；If what is received is the satellite positioning coordinate and travel direction of the driving vehicle, using minimum vertical projector distance method simultaneously
With reference to travel direction, the satellite positioning coordinate of the driving vehicle and road are subjected to mapping matching, obtain of the driving vehicle
With position ps" and road section ID rs', 44 are entered step afterwards；
Step 44, according to matched position ps' and road section ID rsOr matched position ps" and road section ID rs', by front
Gradient is handed down to the driving vehicle.
Further, the position data includes matched position ps' and road section ID rs；The running data includes engine
Rotating speed n, engine torque T and automobile gear level d.
Further, the data frame is { n, T, d, ps’,ts,rs}。
Further, the feature of the time interval △ t between the neighbouring sample moment is：If in same continuous data frame
In, then time interval △ t are equal to the time interval △ T of sampling；If in two sections of continuous data frames, time interval △ t
More than the time interval △ T of sampling.
Further, the specific calculating process of the step 33 is：First by engine torque T and engine speed n, difference
Calculate lap position data pd2、pd1Locate the engine output P of A carsad2And Pad1；Further according to gradient i's and power of vehicle P
RelationObtain in position data pd2With pd1Between, the actual grade that A cars are run into changesThe actual grade change that B cars are run into
Wherein u is speed, and G is quality, and η T are machinery driving efficiency；Then according to Δ iB=Δ iA, obtain
OrderThen B vehicle speeds uBWith quality GBProduct relative to A vehicle speeds uAWith quality GAThe normalization coefficient of productContinue selection lap position data to be calculated, until obtaining all normalization coefficients of the lap position data
Cd2,Cd3,…Cdk-1, 34 are entered step afterwards.
The invention has the advantages that：Satellite positioning coordinate is matched, and it is clear to the data frame progress data of fusion
Wash, so as to get Gradient it is more accurate, reliability is high；Runed using existing car networking in net, be automatically performed information
Collecting function, it is not necessary to put into a large amount of vehicles and go to complete road sampling operation, it is not required that installation additional sensors, obtain cost
Reduction is arrived；Gradient order after processing is stored in special Gradient storage table, it is convenient and efficient when making lookup.
Brief description of the drawings
The present invention is further illustrated in conjunction with the embodiments with reference to the accompanying drawings.
Fig. 1 is that a kind of vehicle geographical environment of the present invention excavates the FB(flow block) for perceiving fuel saving method.
Embodiment
It refer to shown in Fig. 1, a kind of vehicle geographical environment, which excavates, perceives fuel saving method, includes the following steps：
After step 1, vehicle launch, just start to gather the satellite positioning coordinate of the vehicle, and by satellite positioning coordinate and road
Road mapping matching obtains the position data of the vehicle, while gathers the running data of the vehicle, afterwards by the traveling number of the vehicle
Data frame is fused into according to position data, and is uploaded to car networking center；Comprise the following steps that：
After step 11, vehicle launch, just start the time interval △ T according to sampling, to the satellite positioning coordinate of the vehicle
It is acquired, the time interval usually sampled is smaller, and the Gradient of end reaction is more accurate, so we generally take sampling
Time interval △ T be 100ms；If satellite positioning is in effective status, sampling instant t is write downsAnd the satellite of the vehicle
Position coordinate ps, 12 are entered step afterwards；If satellite positioning is in failure state (such as when vehicle enters tunnel), enter step
Rapid 13；
Step 12, using minimum vertical projector distance method and combine vehicle heading, and the satellite positioning of the vehicle is sat
Mark psMapping matching is carried out with road, obtains position data (including the matched position p of the vehicles' and road section ID rs), and general
With position ps' and sampling instant tsIt recorded in active position caching, taken when being in disarmed state for satellite positioning；At the same time
From automobile CAN-bus gather the vehicle running data (including engine speed n, engine torque T and automobile gear level d), and
The position data of the vehicle and running data are formed into data frame { n, T, d, a ps’,ts,rs, and by wireless communication by number
Car networking center is sent to according to frame, enters step 14 afterwards；
Step 13, when above-mentioned active position caching in have record when, just from active position cache in take out the vehicle storage
Previous sampling instant tsMatched position ps', and with matched position ps' it is starting point, pass through the mileometer data and road of the vehicle
Road map calculates the position data of the vehicle, while the position data of the vehicle and the running data of collection are formed a data
Frame, and data frame is sent to by car networking center by wireless communication, 14 are entered step afterwards；When in above-mentioned active position caching
When not recording, then illustrate that satellite positioning is constantly in disarmed state, be directly entered step 14 at this time；
If step 14, the vehicle stop traveling, its active position caching is emptied, for being used during vehicle startup next time；
If the vehicle continues to travel, the circulation of return to step 11 performs.
Step 2, calling are stored in the data frame of all vehicles at car networking center, and the data frame of all vehicles is carried out
Data cleansing, obtains all at the uniform velocity fragments；Comprise the following steps that：
Step 21, all data frames for taking out from the vehicle data storage table at car networking center wherein one car；
Step 22, according to the feature of the time interval △ t between the neighbouring sample moment (if in same continuous data frame,
Then time interval △ t are 100ms；If in two sections of continuous data frames, time interval △ t are more than 100ms), by the car
It is all to be separated paragraph by paragraph from the continuous data frame for starting to stopped process, and each section of continuous data frame is pressed into sampling instant tsIt is suitable
Sequence arranges；
Step 23, one section of continuous data frame for taking out above-mentioned vehicle, by engine speed n and automobile gear level d, converse
This section of continuous data frame is in each sampling instant tsSpeed vs, and derivation is carried out to the speed of each adjacent moment, accelerated
Spend as；According to the threshold epsilon of selection (ε level off to 0), a is judgedsWhether threshold epsilon is less than, if then the vehicle is in sampling instant tsPlace
At the uniform velocity to travel, sampling instant t is markedsData frame be 1；If otherwise the vehicle is in sampling instant tsLocate at the uniform velocity to travel to be non-,
Mark sampling instant tsData frame be 0, continue to compare asValue, until having marked this section of continuous data frame；
Step 24, by sampling instant tsThe order of arrangement, scans the continuous data frame marked, will wherein continued labelling be
1 data frame all takes out, and is deposited into as at the uniform velocity fragment at the uniform velocity fragment buffer；
If all continuous data frames of step 25, the untreated complete vehicle, the circulation of return to step 23 performs；It is if processed
All continuous data frames of the complete vehicle, then enter step 26；
If the data frame of all vehicles, enters step 3 in step 26, the complete vehicle data storage table of executed；If do not hold
The data frames of all vehicles in vehicle data storage table is gone, then the circulation of return to step 21 performs.
After data above is cleaned and is filtered, the data frame of reservation is all the fragment that vehicle approximation at the uniform velocity travels,
The purpose for the arrangement is that influence of the acceleration to changed power is excluded, and at the uniform velocity in fragment, the speed and quality of vehicle are all
It is constant, therefore the power of road friction resistance consumption is equal, the power also approximately equal of windage consumption, thus makes power of vehicle
The influence factor of change mostlys come from Gradient.
Step 3, carry out centre data fusion to above-mentioned all at the uniform velocity fragments, obtains the Gradient in whole section, and will
Gradient is uploaded to car networking center；Comprise the following steps that：
Step 31, take from the uniform velocity fragment buffer the at the uniform velocity fragment a of load-carrying vehicle A known to one as initial segment, if should
In initial segment, the position data of vehicle is { pa1,pa2,…pan,pd1,pd2,…pdk, and by engine torque T and engine
Rotating speed n calculates each point power P；If adjacent position data pa2With pa1Power variation be Δ Pa2,a1, then this at the uniform velocity fragment is adjacent
The changed power sequence of position is：
Step 32, by initial segment a as current reference fragment, and according to its position data, from the uniform velocity fragment buffer
Find out with the at the uniform velocity fragment a at the uniform velocity fragment b that to have position data overlapping, and set this at the uniform velocity fragment b belong to vehicle B, position data
For { pd1,pd2,…pdk,pb1,pb2,…pbm, each point power P is calculated by engine torque T and engine speed n, then this is at the uniform velocity
The changed power sequence of fragment adjacent position is:
Step 33, in overlapping position data { pd1,pd2,…pdk-1Place, calculate B vehicle speeds and quality product feature phase
For the normalization coefficient { C of A vehicle speeds and quality product featured1,Cd2,…Cdk-1}；Specifically calculating process is：
First by engine torque T and engine speed n, lap position data p is calculated respectivelyd2、pd1Locate the engine of A cars
Output power Pad2And Pad1；Further according to the relation of gradient i and power of vehicle PObtain in position data pd2With
pd1Between, the actual grade that A cars are run into changesThe reality that B cars are run into
Slope changeWherein u is speed, and G is quality, ηTImitated for machine driving
Rate；Then according to Δ iB=Δ iA, obtain(expression of formula for convenience here, we set vehicle
A and vehicle B is same model car, then the η in molecule denominatorTIt can divide out, if in practice, the model of vehicle A and vehicle B is not
Together, we are only needed corresponding ηTValue substitutes into formula), orderThen B vehicle speeds uBWith quality GBProduct phase
For A vehicle speeds uAWith quality GAThe normalization coefficient of productContinue selection lap position data to be calculated, directly
To obtaining all normalization coefficient C of the lap position datad2,Cd3,…Cdk-1, 34 are entered step afterwards；
Step 34, the value C by obtained normalization coefficientd1,Cd2,…Cdk-1It is averaging, obtains overall normalization coefficient C；
Step 35, using overall normalization coefficient C, by B cars at the uniform velocity on fragment b with load-carrying GBAnd at the uniform velocity uBThe work(of traveling
Rate change sequenceA cars are normalized at the uniform velocity fragment b
On with load-carrying GAAnd at the uniform velocity uAThe changed power sequence of traveling, the changed power sequence after normalization are：
Step 36, by A cars at the uniform velocity fragment a with the uniform velocity on fragment b with load-carrying GAAt the uniform velocity uAThe changed power sequence of traveling
Splicing fusion is carried out, obtaining the changed power sequence after splicing fusion is：
{ΔPa2,a1,ΔPa3,a2,…,ΔPan,an-1,
CΔPb2,b1,CΔPb3,b2,…,CΔPbm,bm-1}；
If step 37, do not find out also with the uniform velocity fragment a all at the uniform velocity fragments that to have position data overlapping, by what is spliced
At the uniform velocity fragment is as current reference fragment, and the circulation of return to step 32 performs；If found out has position data weight with the uniform velocity fragment a
Folded all at the uniform velocity fragments, and all at the uniform velocity fragment assemblies are obtained into the changed power sequence in whole section, then enter step 38；
Step 38, utilize slope change amountIt is the gradient by the changed power sequence transitions in whole section
Change sequence, and send obtained Gradient to car networking center, wherein u is speed, and G is quality, and Δ P is changed power
Amount, ηTFor machinery driving efficiency.
During centre data merges, we only need to know the load-carrying as initial reference fragment A cars, it is possible to
By carrying out centre data fusion at the uniform velocity fragment, the Gradient in whole section is obtained, without knowing other vehicles
Load-carrying data, this is easily achieved in actual car networking business.
The data frame or satellite positioning coordinate that step 4, car networking center are transmitted according to driving vehicle, by the gradient in front
Data distributing gives the driving vehicle；Comprise the following steps that：
The Gradient transmitted is stored in Gradient storage table by step 41, car networking center；
Satellite positioning coordinate and travel direction are uploaded to car networking center by step 42, driving vehicle；
Step 43, car networking center receive data frame or satellite positioning coordinate and the travel direction that driving vehicle transmits,
If what is received is the data frame of the driving vehicle, the matched position p in data frame is taken outs' and road section ID rs, enter step afterwards
Rapid 44；If what is received is the satellite positioning coordinate and travel direction of the driving vehicle, using minimum vertical projector distance method simultaneously
With reference to travel direction, the satellite positioning coordinate of the driving vehicle and road are subjected to mapping matching, obtain of the driving vehicle
With position ps" and road section ID rs', 44 are entered step afterwards；
Step 44, according to matched position ps' and road section ID rsOr matched position ps" and road section ID rs', by front
Gradient is handed down to the driving vehicle.
The Gradient that step 5, driving vehicle are returned by car networking center, calculates the satellite positioning of the driving vehicle
The distance between coordinate and the front gradient E initial positions D, and decision-making is carried out according to gradient E and distance D, vehicle is reached preferable
Oil-saving effect.
Although the foregoing describing the embodiment of the present invention, those familiar with the art should manage
Solution, we are merely exemplary described specific embodiment, rather than for the restriction to the scope of the present invention, are familiar with this
The equivalent modification and change that the technical staff in field is made in the spirit according to the present invention, should all cover the present invention's
In scope of the claimed protection.
Claims (9)
1. a kind of vehicle geographical environment, which excavates, perceives fuel saving method, it is characterised in that：Described method includes following steps：
After step 1, vehicle launch, just start to gather the satellite positioning coordinate of the vehicle, and satellite positioning coordinate and road are reflected
Penetrate matching and obtain the position data of the vehicle, while gather the running data of the vehicle, afterwards by the running data of the vehicle with
Position data is fused into data frame, and is uploaded to car networking center；
Step 2, calling are stored in the data frame of all vehicles at car networking center, and carry out data to the data frame of all vehicles
Cleaning, obtains all at the uniform velocity fragments；
Step 3, carry out centre data fusions to above-mentioned all at the uniform velocity fragments, obtains the Gradient in whole section, and by the gradient
Data are uploaded to car networking center；
The data frame or satellite positioning coordinate that step 4, car networking center are transmitted according to driving vehicle, by the Gradient in front
It is handed down to the driving vehicle；
The Gradient that step 5, driving vehicle are returned by car networking center, calculates the satellite positioning coordinate of the driving vehicle
The distance between front gradient E initial positions D, and decision-making is carried out according to gradient E and distance D.
2. a kind of vehicle geographical environment as claimed in claim 1, which excavates, perceives fuel saving method, it is characterised in that：The step 1
Specifically comprise the following steps：
Step 11, after vehicle is started, just according to the time interval △ T of sampling, the satellite positioning coordinate of the vehicle is adopted
Collection；If satellite positioning is in effective status, sampling instant t is write downsAnd the satellite positioning coordinate p of the vehicles, enter step afterwards
Rapid 12；If satellite positioning is in failure state, 13 are entered step；
Step 12, using minimum vertical projector distance method combination vehicle heading, by the satellite positioning coordinate p of the vehiclesWith road
Road carries out mapping matching, obtains the position data of the vehicle, and by the matched position p in the vehicle position datas' with sampling when
Carve tsIt recorded in active position caching；Gather the running data of the vehicle at the same time, then by the running data of the vehicle and position
Data form a data frame, and data frame is sent to car networking center by wireless communication, enter step 14 afterwards；
Step 13, when above-mentioned active position caching in have record when, just from active position cache in take out the vehicle storage before
One sampling instant tsMatched position ps', and with matched position ps' it is starting point, by the mileometer data of the vehicle and road
Graphic calculation goes out the position data of the vehicle, while the position data of the vehicle and the running data of collection are formed a data frame,
And data frame is sent to by car networking center by wireless communication, 14 are entered step afterwards；Do not have when in above-mentioned active position caching
When having record, step 14 is just directly entered；
If step 14, the vehicle stop traveling, its active position caching is emptied；If the vehicle continues to travel, return to step
11 circulations perform.
3. a kind of vehicle geographical environment as claimed in claim 1 or 2, which excavates, perceives fuel saving method, it is characterised in that：Institute's rheme
Putting data includes matched position ps' and road section ID rs；The running data includes engine speed n, engine torque T and vehicle
Gear d.
4. a kind of vehicle geographical environment as claimed in claim 2, which excavates, perceives fuel saving method, it is characterised in that：The data frame
For { n, T, d, ps’,ts,rs}。
5. a kind of vehicle geographical environment as claimed in claim 1, which excavates, perceives fuel saving method, it is characterised in that：The step 2
Specifically comprise the following steps：
Step 21, all data frames for taking out from the vehicle data storage table at car networking center wherein one car；
Step 22, the feature according to the time interval △ t between the neighbouring sample moment, stopped the vehicle is all from starting to
The continuous data frame of journey separates paragraph by paragraph, and each section of continuous data frame is pressed sampling instant tsOrder arranges；
Step 23, one section of continuous data frame for taking out above-mentioned vehicle, by engine speed n and automobile gear level d, converse the section
Continuous data frame is in each sampling instant tsSpeed vs, and derivation is carried out to the speed of each adjacent moment, obtain acceleration
as；According to the threshold epsilon of selection, a is judgedsWhether threshold epsilon is less than, if then the vehicle is in sampling instant tsLocate at the uniform velocity to travel, mark
Remember sampling instant tsData frame be 1；If otherwise the vehicle is in sampling instant tsLocate at the uniform velocity to travel to be non-, when marking the sampling
Carve tsData frame be 0, continue to compare asValue, until having marked this section of continuous data frame；
Step 24, by sampling instant tsThe order of arrangement, scans the continuous data frame marked, by the number that wherein continued labelling is 1
All take out according to frame, and be deposited into as at the uniform velocity fragment at the uniform velocity fragment buffer；
If all continuous data frames of step 25, the untreated complete vehicle, the circulation of return to step 23 performs；If processed should
All continuous data frames of vehicle, then enter step 26；
If the data frame of all vehicles, enters step 3 in step 26, the complete vehicle data storage table of executed；If it has been not carried out
The data frame of all vehicles in vehicle data storage table, the then circulation of return to step 21 perform.
6. a kind of vehicle geographical environment as claimed in claim 5, which excavates, perceives fuel saving method, it is characterised in that：It is described adjacent to adopt
The feature of time interval △ t between the sample moment is：If in same continuous data frame, time interval △ t are equal to sampling
Time interval △ T；If in two sections of continuous data frames, time interval △ t are more than the time interval △ T of sampling.
7. a kind of vehicle geographical environment as claimed in claim 1, which excavates, perceives fuel saving method, it is characterised in that：The step 3
Specifically comprise the following steps：
Step 31, take from the uniform velocity fragment buffer the at the uniform velocity fragment a of load-carrying vehicle A known to one as initial segment, if this is initial
In fragment, the position data of vehicle is { pa1,pa2,…pan,pd1,pd2,…pdk, and by engine torque T and engine speed n
Calculate each point power P；If adjacent position data pa2With pa1Power variation be Δ Pa2,a1, then the at the uniform velocity fragment adjacent position
Changed power sequence be：
Step 32, by initial segment a as current reference fragment, and according to its position data, found out from the uniform velocity fragment buffer
With the at the uniform velocity fragment a at the uniform velocity fragment b that to have position data overlapping, and set this at the uniform velocity fragment b belongs to vehicle B, position data is
{pd1,pd2,…pdk,pb1,pb2,…pbm, each point power P is calculated by engine torque T and engine speed n, then the at the uniform velocity piece
Section adjacent position changed power sequence be:
Step 33, in overlapping position data { pd1,pd2,…pdk-1Place, calculate B vehicle speeds and quality product feature relative to
A vehicle speeds and the normalization coefficient { C of quality product featured1,Cd2,…Cdk-1}；
Step 34, the value C by obtained normalization coefficientd1,Cd2,…Cdk-1It is averaging, obtains overall normalization coefficient C；
Step 35, using overall normalization coefficient C, by B cars at the uniform velocity on fragment b with load-carrying GBAnd at the uniform velocity uBThe power of traveling becomes
Change sequenceBe normalized to A cars at the uniform velocity on fragment b with
Load-carrying GAAnd at the uniform velocity uAThe changed power sequence of traveling, the changed power sequence after normalization are：
Step 36, by A cars at the uniform velocity fragment a with the uniform velocity on fragment b with load-carrying GAAnd at the uniform velocity uAThe changed power sequence of traveling carries out
Splicing fusion, obtaining the changed power sequence after splicing fusion is：
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<mn>3</mn>
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<mi>n</mi>
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<mn>1</mn>
</mrow>
</msub>
<mo>,</mo>
</mrow>
</mtd>
</mtr>
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If step 37, do not find out also with the uniform velocity fragment a all at the uniform velocity fragments that to have position data overlapping, will splice at the uniform velocity
Fragment is as current reference fragment, and the circulation of return to step 32 performs；If found out has the position data overlapping with the uniform velocity fragment a
All at the uniform velocity fragments, and all at the uniform velocity fragment assemblies are obtained into the changed power sequence in whole section, then enter step 38；
Step 38, utilize slope change amountIt is slope change by the changed power sequence transitions in whole section
Sequence, and send obtained Gradient to car networking center, wherein u is speed, and G is quality, and Δ P is power variation,
ηTFor machinery driving efficiency.
8. a kind of vehicle geographical environment as claimed in claim 7, which excavates, perceives fuel saving method, it is characterised in that：The step 33
Specific calculating process be：First by engine torque T and engine speed n, lap position data p is calculated respectivelyd2、pd1Locate A cars
Engine output Pad2And Pad1；Further according to the relation of gradient i and power of vehicle PObtain in position
Data pd2With pd1Between, the actual grade that A cars are run into changesB cars are run into
Actual grade changeWherein u is speed, and G is quality, ηTPassed for machinery
Efficiency of movement；Then according to Δ iB=Δ iA, obtainOrderThen B vehicle speeds uBWith quality
GBProduct relative to A vehicle speeds uAWith quality GAThe normalization coefficient of productContinue to choose lap position data
Calculated, until obtaining all normalization coefficient C of the lap position datad2,Cd3,…Cdk-1, 34 are entered step afterwards.
9. a kind of vehicle geographical environment as claimed in claim 1, which excavates, perceives fuel saving method, it is characterised in that：The step 4
Specifically comprise the following steps：
The Gradient transmitted is stored in Gradient storage table by step 41, car networking center；
Satellite positioning coordinate and travel direction are uploaded to car networking center by step 42, driving vehicle；
Step 43, car networking center receive data frame or satellite positioning coordinate and the travel direction that driving vehicle transmits, if connecing
What is received is the data frame of the driving vehicle, then takes out the matched position p in data frames' and road section ID rs, enter step afterwards
44；If what is received is the satellite positioning coordinate and travel direction of the driving vehicle, using minimum vertical projector distance method and tie
Travel direction is closed, the satellite positioning coordinate of the driving vehicle and road are subjected to mapping matching, obtain the matching of the driving vehicle
Position ps" and road section ID rs', 44 are entered step afterwards；
Step 44, according to matched position ps' and road section ID rsOr matched position ps" and road section ID rs', by the slope number in front
According to being handed down to the driving vehicle.
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| CN107222572A (en) * | 2017-07-11 | 2017-09-29 | 江苏大学 | In-vehicle networking Social ecological balance information interaction security design methods under a kind of intelligent network connection environment |
| CN109927708B (en) * | 2017-12-15 | 2021-05-14 | 宝沃汽车（中国）有限公司 | Vehicle torque control method and system, vehicle and Internet of vehicles system |
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