CN104192145B - A kind of limited speed change cruise method of vehicle - Google Patents
A kind of limited speed change cruise method of vehicle Download PDFInfo
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- CN104192145B CN104192145B CN201410347617.0A CN201410347617A CN104192145B CN 104192145 B CN104192145 B CN 104192145B CN 201410347617 A CN201410347617 A CN 201410347617A CN 104192145 B CN104192145 B CN 104192145B
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- 230000006855 networking Effects 0.000 claims abstract description 38
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- 239000003921 oil Substances 0.000 claims description 25
- 230000033001 locomotion Effects 0.000 claims description 13
- 239000000203 mixture Substances 0.000 claims description 11
- 238000013480 data collection Methods 0.000 claims description 10
- 239000000446 fuel Substances 0.000 claims description 10
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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
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/14—Adaptive cruise control
- B60W30/143—Speed control
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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
- B60W10/00—Conjoint control of vehicle sub-units of different type or different function
- B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
- B60W10/06—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of combustion engines
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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
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/18—Propelling the vehicle
- B60W30/188—Controlling power parameters of the driveline, e.g. determining the required power
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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
- B60W2510/00—Input parameters relating to a particular sub-units
- B60W2510/06—Combustion engines, Gas turbines
- B60W2510/0666—Engine power
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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
- B60W2510/00—Input parameters relating to a particular sub-units
- B60W2510/10—Change speed gearings
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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
- 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
- B60W2710/00—Output or target parameters relating to a particular sub-units
- B60W2710/06—Combustion engines, Gas turbines
- B60W2710/0677—Engine power
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- Mechanical Engineering (AREA)
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Abstract
The present invention provides a kind of limited speed change cruise method of vehicle, utilize speed of the car networking acquisition vehicle in cruise, power data, power data Gauss is turned into the gaussian distribution data using load factor as mathematic expectaion, different loads coefficient is clustered out from gaussian distribution data；Then " speed-power " characteristic curve is fitted using cubic polynomial from revolving speed belonging to different load factors and power historical data；The speed and power data of this vehicle of real-time sampling are uploaded to car networking center, and are matched with the characteristic curve that cluster center fits, the characteristic curve after obtaining current matching；Using, with the oil consumption of each speed cruise, the past economic section of engine in finite interval is finely tuned by cruising speed according to prediction result in the characteristic curve law forecasting finite interval after matching, reach the target of oil consumption economy when improving vehicle cruise.The present invention can guarantee vehicle oil saving during entire cruise, be automatically performed energy-saving function.
Description
Technical field
The present invention relates to vehicle production technical field more particularly to a kind of limited speed change cruise methods of vehicle.
Background technique
Cruise can make automobile on the advanced roads such as highway or city expressway by pre-set velocity at the uniform velocity
Traveling reduces driver fatigue, drives to bring very big convenience to driver.But existing cruise system is all concerned with how root substantially
According to the different automatic setting cruising speeds for maintaining vehicle of external condition, the fewer economy in view of cruising.It is sent out according to automobile
The whole performance map of motivation can know automobile engine, and there are most economical revolving speed sections, in this revolving speed section, engine
Fuel economy is better than other revolving speeds.When automobile is with speed V cruise, the lesser speed for not influencing driving experience is taken
Change threshold ε enables cruising speed carry out dynamic change in a finite interval [V- ε, V+ ε], keeps engine speed real-time
It is close to economic section, it will be able under the premise of not influencing driver and driving to experience while to reach better fuel economy.But
Most economical revolving speed section with load-carrying, condition of road surface, gear difference and be varied, therefore speed is in finite interval
Changing value needs to carry out real-time estimation according to oil consumption prediction result.
A kind of " system and method for vehicle cruise control " are disclosed in the prior art, see Publication No.
103786724A, publication date are the Chinese patent of 2014-05-14, vehicle cruise control system, comprising: alignment sensor, it is described
Alignment sensor is configured to obtain along one group of position of road；Range sensor, the range sensor are configured to measure
Away from one or more close to the distance of vehicle；Velocity sensor, the velocity sensor are configured to measurement one or more and connect
The speed of nearly vehicle；Processor；And memory, by various sensor signals be used for enter bend, come off the curve, bend is led
Speed is limited under boat and experience vehicle case, guarantees safety and vehicle stability；But the invention has used multiple sensors real
Existing, it is not identical as the technical solution of present specification.
For another example a kind of " SCM Based cooperating type adaptive cruise petroleum economizer " is shown in Publication No.: 203047252U,
Publication date is the Chinese patent of 2013-07-10, is realized using single-chip microcontroller and fuel flow transducer etc. and shows driving on display
Member needs the movement and current oil consumption carried out, ultimately produces oil consumption consumption composite diagram, belongs to offline scheme, realize driver behavior
Prompt and oil consumption statistics；But the patent is all right without estimation road and car weight factor (i.e. present specification define load factor)
The influence of oil consumption.
Summary of the invention
The technical problem to be solved in the present invention is to provide a kind of limited speed change cruise method of vehicle, can entirely cruise
It can guarantee vehicle oil saving in the process, be automatically performed energy-saving function.
The present invention is implemented as follows: a kind of limited speed change cruise method of vehicle, the method are as follows: acquired using car networking
Speed of the vehicle in cruise, power data, turn to the Gauss using load factor as mathematic expectaion for power data Gauss
Distributed data clusters out different loads coefficient from gaussian distribution data；Then revolving speed and function belonging to the different load factors
" speed-power " characteristic curve is fitted using cubic polynomial in rate historical data；Opening finite region speed change cruise function
After energy, the speed and power data of this vehicle of real-time sampling are uploaded to car networking center, and the characteristic song fitted with cluster center
Line is matched, the characteristic curve after obtaining current matching；Using in the characteristic curve law forecasting finite interval after matching with
Cruising speed is finely tuned in finite interval toward the economic section of engine according to prediction result, is reached by the oil consumption of each speed cruise
The target of oil consumption economy when raising vehicle cruise.
Further, the method specifically: need to acquire the constant speed of the vehicle in advance to a certain vehicle using car networking
Cruise feature, uses car-mounted terminal constantly to acquire reality of the vehicle in cruise with a time interval by vehicle CAN bus
Shi Sudu u, gear n, engine real-time output power data P, composition data frame Di{ui,ni,Pi, i=1,2,3 ..., I,
Upload to car networking center；Load factor cluster result is carried out to power data P obtained in car networking center, by power data
Gauss turns to the gaussian distribution data using load factor as mathematic expectaion, and different loads system is clustered out from gaussian distribution data
Number；All load factor a clustered according to load factoriValue, calculating in current load factor is aiIn the case where, power
" speed-power " curve changed with speed；Since the power output under identical speed is influenced and different by gear n,
Curve also needs to distinguish according to different gears；It that is is multinomial three times in the relation nature of automobile output power P and speed u
Formula relationship, therefore set:
P=β1u3+β2u2+β3u+β4Wherein β1,β2,β3,β4For the parameter of curve to regression estimates, similar load number is utilized
According to collection CkThe data of middle different stalls n return the parameter value to regression estimates found out under different stalls using least square method,
Different stalls are obtained, " speed-power " characteristic curve under different loads coefficient；It returns to obtain difference in characteristic curve
Gear after " speed-power " characteristic curve under different loads coefficient, can open limited speed change cruise function for vehicle；
After vehicle opens limited speed change cruise function, car speed u and performance number P and gear value are acquired from CAN bus in real time
N is uploaded to car networking center, and is matched with the characteristic curve that cluster center fits, the characteristic after obtaining current matching
Curve；Using in the characteristic curve law forecasting finite interval after matching with the oil consumption of each speed cruise, will according to prediction result
Cruising speed, toward the economic section fine tuning of engine, reaches the mesh of oil consumption economy when improving vehicle cruise in finite interval
Mark.
The present invention has the advantage that cruising speed of the invention carries out dynamic change in a finite interval, make to send out
Motivation revolving speed is close to economic section in real time, and vehicle power data Gaussian is obtained difference using clustering method by the present invention
Load factor under the influence of road, and the speed in the case of characteristic curve returns out different loads coefficient is carried out with least square method
Power changing rule is finally accurately calculated in real time using Curve Matching method and predicts there is speed limit under different roads and loading condition
Oil consumption in section is spent, the adjustment of scanning frequency of going forward side by side degree drives to experience, together because speed changes in finite interval therefore do not influence driver
When reach better fuel economy.The present invention predicts engine and load factor using car networking scheme Online statistics and in real time
Relevant oil consumption rule, finds fine tuning of the most economical revolving speed section for speed during entire cruise, is entirely cruising
It can guarantee vehicle oil saving in the process, be automatically performed energy-saving function.
Detailed description of the invention
Fig. 1 is logical construction schematic diagram of the invention.
Specific embodiment
Refering to Figure 1, a kind of limited speed change cruise method of vehicle of the invention, the method are as follows: utilize car networking
Speed of the vehicle in cruise, power data are acquired, power data Gauss is turned to using load factor as mathematic expectaion
Gaussian distribution data clusters out different loads coefficient from gaussian distribution data；Then the revolving speed belonging to the different load factors
Cubic polynomial is used to fit " speed-power " characteristic curve with power historical data；It is patrolled opening finite region speed change
After function of navigating, the speed and power data of this vehicle of real-time sampling are uploaded to car networking center, and the spy fitted with cluster center
Linearity curve is matched, the characteristic curve after obtaining current matching；Utilize the characteristic curve law forecasting finite interval after matching
The interior oil consumption with each speed cruise finely tunes cruising speed according to prediction result in finite interval toward the economic section of engine,
Reach the target of oil consumption economy when improving vehicle cruise.
Wherein the method for the invention is specifically include the following steps: 1, constant speed parameter acquisition；2, load factor clusters；3, special
Linearity curve returns；4, oil consumption prediction speed change adjustment:
Constant speed parameter acquisition: it needs to acquire the cruise feature of the vehicle in advance to a certain vehicle using car networking, adopts
Existed with car-mounted terminal by vehicle CAN bus with a time interval (interval takes 100ms when this project is implemented) constantly acquisition vehicle
Real-time speed u, gear n, engine real-time output power data P, composition data frame D when cruisei{ui,ni,Pi, i=
1,2,3 ..., I upload to car networking center；
Load factor cluster: load factor cluster result is carried out to power data P obtained in car networking center, by power
Data Gauss turns to the gaussian distribution data using load factor as mathematic expectaion, and different loads are clustered out from gaussian distribution data
Coefficient；
Characteristic curve returns: all load factor a clustered according to load factoriValue is calculated in present load system
Number is aiIn the case where, " speed-power " curve that power changes with speed；Since the power output under identical speed is by shelves
The position influence of n and it is different, therefore curve also needs to distinguish according to different gears；That is automobile output power P's and speed u
It is cubic polynomial relationship in relation nature, therefore sets: P=β1u3+β2u2+β3u+β4Wherein β1,β2,β3,β4For to regression estimates
Parameter of curve, utilize similar load data collection CkThe data of middle different stalls n find out different shelves using least square method recurrence
For the parameter value to regression estimates under position to get different stalls have been arrived, " speed-power " characteristic under different loads coefficient is bent
Line；
Oil consumption prediction speed change adjustment: it returns to obtain different stalls in characteristic curve, " the speed-function under different loads coefficient
After rate " characteristic curve, limited speed change cruise function can be opened for vehicle；When vehicle open limited speed change cruise function it
Afterwards, car speed u and performance number P and gear value n are acquired from CAN bus in real time, is uploaded to car networking center, and in networking
The characteristic curve that the heart fits is matched, the characteristic curve after obtaining current matching；Utilize the characteristic curve rule after matching
It predicts the oil consumption in finite interval with each speed cruise, is passed through cruising speed toward engine in finite interval according to prediction result
The fine tuning of Ji section, reaches the target of oil consumption economy when improving vehicle cruise.
In addition, the heretofore described cruise for needing to acquire the vehicle in advance to a certain vehicle using car networking is special
Sign uses car-mounted terminal constantly to acquire real-time speed of the vehicle in cruise with a time interval by vehicle CAN bus
U, the real-time output power data P of gear n, engine, composition data frame Di{ui,ni,Pi, i=1,2,3 ..., I are uploaded to
Car networking center；Specifically:
Step 11, vehicle, which enter after cruise to start to be spaced at regular intervals, to be sampled, and sampling time interval takes
90ms~120ms obtains the car speed u of sampling instant ii, gear ni, the real-time output power P of enginei, composition data frame Di
{ui,ni,Pi, i=1,2,3 ..., I upload to car networking center；Enter step 12；
Step 12: judging whether vehicle is in cruise state, if it is return step one continues to sample, if not
It is then to stop sampling；
Cruise sampling can be completed jointly by same type of more vehicles, when sampled data cover substantially the various gradients with
When surface conditions, sampled data is complete, carries out load factor cluster.
In the present invention, load factor cluster result is carried out to power data P obtained in car networking center, by power data
Gauss turns to the gaussian distribution data using load factor as mathematic expectaion, and different loads system is clustered out from gaussian distribution data
Number；Specifically:
Step 21, to each sampled data Di{ui,ni,Pi, wherein the road friction resistance as caused by vehicle load
Consumed power are as follows:
Wherein G is load-carrying quality, and f is road friction coefficient, and u is car speed；
The power that vehicle load causes grade resistance to consume are as follows:
Wherein θ is road grade
η in two formulas aboveTFor system of vehicle transmission efficiency, same vehicle transmission efficiency is mutually all known quantity, by load friction
Resistance and grade resistance factor are uniformly classified as load factor a, thenStart as caused by loading
Machine power consumption is expressed as Pg=au；Load factor a is different with load-carrying with road conditions and changes, for determining speed cruise sampling
Data Di{ui,ni,Pi, i=1,2,3 ..., I is handled；The P in each data frameiIt is by load power consumption
P is consumed with air-resistance powerwiComposition, it may be assumed that
Pi=aiui+Pwi (1)
Wherein aiFor unknown quantity, will be obtained by subsequent cluster；Windage consumes power PwiPower P is consumed by movement windagesiWith
Natural windage consumes power PniComposition:
Pwi=Psi+Pni (2)
Wherein movement windage is calculation method caused by the counter blow generated as Velicle motion velocity are as follows:
Wherein uiAs car speed, A are that the front face area of vehicle is determined that same vehicle A value is identical, C by vehicle external formDFor
Coefficient of air resistance is taken as approximately constant constant, PsiIt is the known quantity calculated according to vehicle speed and front face area；Natural wind
Resistance consumption power long-time sampling big data in its meet zero-mean normal distribution, Pni~μ (0, σ2)；
Utilize its speed uiIts corresponding movement windage consumption power is calculated according to formula (3)；
Step 22, by all P for determining speed cruise sampled dataiGaussian processing is carried out, is converted into and meets Gaussian Profile
Data Gi, processing method is by PiSubtract movement windage consumption power PsiAnd divided by speed ui:
By formula (1) and (2) it is found that formula (4) can also be expressed asDue to PniIt is σ for zero-mean variance2
Gaussian Profile, thereforeThat is GiIt is a to obey mean valuei, variance isGaussian Profile, pass through public affairs
Cruise sampled data is converted gaussian distribution data by the conversion of formula (4)；
Power is consumed by the movement windage that formula (4) subtracts step 21 calculating, and divided by speed ui, final conversion meet for
The data G of Gaussian Profilei, then sampled data is extended to
Step 23, using K mean cluster method to all GiIt is clustered, obtained cluster centre is different bears
Carry coefficient value ak(k=1,2,3 ..., K), for each akEstablish a load data collection Ck；
Step 24, forCalculate wherein GiWith each akThe distance of (k=1,2,3 ..., K), takes apart from the smallest
akFor GiGeneric, by GiAffiliatedIn Di{ui,ni,PiA is addedkCorresponding load data collection CkIn；Repeat step
24, until allIt is disposed, is included into corresponding load data and concentrates.
In the present invention, it is described then from revolving speed belonging to different load factors in power historical data using multinomial three times
Formula fits " speed-power " characteristic curve；Specifically:
Step 31, to each load data collection CkIn all data Di{ui,ni,Pi, according to gear niClassify,
Obtain the data set N under different stalls Kk{Di|ni=K }；The relationship of automobile output power P and speed u is that cubic polynomial is closed
System, the cubic polynomial relationship
P=β1u3+β2u2+β3u+β4 (5)
Wherein β1,β2,β3,β4For the parameter of curve to regression estimates；
Step 32: to data set Nk{Di|ni=K } least square method is utilized, it is bent to carry out " speed-power " cubic polynomial
Line returns, and obtains each β of the cubic polynomial curve of formula (5)1,β2,β3,β4Parameter；Step 32 is repeated, until all gears
Under cubic curve equation parameter return and finish；
Step 33: return step 31, until all load data collection CkAll it is disposed；
Step 34: by all parameters of curve, there are in car networking central database.
In the present invention, after finding out all " speed-power " curves, finite interval speed change cruise function is opened, if vehicle is set
Determining cruising speed is V, and the limited constant interval of cruising speed is [V- ε, V+ ε], adjusts cruising speed in real time as follows:
Step 41: the vehicle in speed change cruise acquires car speed u and performance number P and gear from CAN bus in real time
Value n, and upload car networking center；
Step 42: car networking center carries out Curve Matching calculating, is located under gear n and shares M characteristic curve, and coefficient is
{β1m,β2m,β3m,β4m, m=1,2 ..., M；Speed u is substituted into each curvilinear equation, calculated curve corresponds to performance number Pm
=β1mu3+β2mu2+β3mu+β4m；FromMiddle taking-up and the immediate value of P, are set asI.e.Then
Curve P=β1ju3+β2ju2+β3ju+β4jIt is matched, enters step 43；
Step 43: setting vehicle and set cruising speed as V, the limited constant interval of cruising speed is [V- ε, V+ ε], then will have
Limit all velocity amplitude v in constant intervalj∈ [V- ε, V+ ε], the ε of j=1,2 ..., 2 substitute into the curve being matched, and find out limited
The corresponding performance number P of each speed in constant intervalj, the ε of j=1,2 ..., 2；Utilize power PjWith speed vjPredict limited variation
Each speed v in sectionjCorresponding fuel consumption per hundred kilometers value Qj:
It is known quantity that wherein ρ, which is the density of fuel oil, and g is acceleration of gravity, bjFor according to PjWith vjLook into Engine Universal Characteristics
The fuel consumption rate that table obtains；
Step 44: according to the smallest QjIt is worth corresponding speed v, the optimal travel speed as in finite interval will patrol
Speed of a ship or plane degree, which is adjusted to v, can reach the purpose of the most economical fuel consumption per hundred kilometers in finite speed section；
Step 45: return step 41 constantly calculates in real time and adjusts best cost cruising speed.
In short, the present invention is using the oil consumption relevant with load factor to real-time prediction engine of car networking scheme Online statistics
Rule finds fine tuning of the most economical revolving speed section for speed during entire cruise, can during entire cruise
Guarantee vehicle oil saving, is automatically performed energy-saving function.
The foregoing is merely presently preferred embodiments of the present invention, all equivalent changes done according to scope of the present invention patent with
Modification, is all covered by the present invention.
Claims (5)
1. a kind of limited speed change cruise method of vehicle, it is characterised in that: the method are as follows: using car networking acquisition vehicle in constant speed
Power data Gauss is turned to the gaussian distribution data using load factor as mathematic expectaion by speed, power data when cruise, from
Different loads coefficient is clustered out in gaussian distribution data；Then from revolving speed belonging to different load factors and power historical data
" speed-power " characteristic curve is fitted using cubic polynomial；After opening finite region speed change cruise function, adopt in real time
The speed and power data of sample vehicle are uploaded to car networking center, and the characteristic curve progress fitted with car networking center
Match, the characteristic curve after obtaining current matching；It is patrolled using in the characteristic curve law forecasting finite interval after matching with each speed
Cruising speed is finely tuned in finite interval toward the economic section of engine according to prediction result, reaches raising vehicle by the oil consumption of boat
The target of oil consumption economy when cruise；
The cruise feature for needing to acquire the vehicle in advance to a vehicle using car networking, passes through vehicle using car-mounted terminal
CAN bus is constantly acquired vehicle real-time speed u, gear n, vehicle of the vehicle in cruise with a time interval and exported in real time
Power P, composition data frame Di{ui,ni,Pi, i=1,2,3 ..., I upload to car networking center；
Output power P real-time to vehicle obtained in car networking center carries out load factor cluster result, by power data Gauss
The gaussian distribution data using load factor as mathematic expectaion is turned to, different loads coefficient is clustered out from gaussian distribution data；Tool
Body are as follows:
Step 21, to each sampled data Di{ui,ni,Pi, wherein the road friction resistance as caused by vehicle load is consumed
Power are as follows:
Wherein G is load-carrying quality, and f is road friction coefficient, and u is vehicle real-time speed；
The power that vehicle load causes grade resistance to consume are as follows:
Wherein θ is road grade
η in two formulas aboveTFor system of vehicle transmission efficiency, same vehicle transmission efficiency is mutually all known quantity, by load friction resistance with
Grade resistance factor is uniformly classified as load factor a, thenThe engine power caused by loading
Consumption is expressed as Pg=au；Load factor a is different with load-carrying with road conditions and changes, for determining the data of speed cruise sampling
Di{ui,ni,Pi, i=1,2,3 ..., I is handled；The P in each data frameiIt is by load power consumption and windage
Power consumption PwiComposition, it may be assumed that
Pi=aiui+Pwi (1)
Wherein aiFor unknown quantity, will be obtained by subsequent cluster；Windage consumes power PwiPower P is consumed by movement windagesiWith nature
Windage consumes power PniComposition:
Pwi=Psi+Pni (2)
Wherein movement windage is calculation method caused by the counter blow generated as Velicle motion velocity are as follows:
Wherein uiAs car speed, A are that the front face area of vehicle is determined that same vehicle A value is identical, C by vehicle external formDFor air
Resistance coefficient is taken as approximately constant constant, PsiIt is the known quantity calculated according to vehicle speed and front face area；Natural windage disappears
Wasted work rate long-time sampling big data in its meet zero-mean normal distribution, Pni~μ (0, σ2)；
Utilize its vehicle real-time speed uiIts corresponding movement windage consumption power is calculated according to formula (3)；
Step 22, by all P for determining speed cruise sampled dataiGaussian processing is carried out, the data for meeting Gaussian Profile are converted into
Gi, processing method is by PiSubtract movement windage consumption power PsiAnd divided by speed ui:
By formula (1) and (2) it is found that formula (4) is also expressed asDue to PniIt is σ for zero-mean variance2Gauss
Distribution, thereforeThat is GiIt is a to obey mean valuei, variance isGaussian Profile, pass through formula (4)
Cruise sampled data is converted gaussian distribution data by conversion；
Power is consumed by the movement windage that formula (4) subtracts step 21 calculating, and divided by vehicle real-time speed ui, final conversion symbol
It is combined into the data G of Gaussian Profilei, then sampled data is extended to
Step 23, using K mean cluster method to all GiIt is clustered, obtained cluster centre is different load system
Numerical value ak(k=1,2,3 ..., K), for each akEstablish a load data collection Ck；
Step 24, forCalculate wherein GiWith each akThe distance of (k=1,2,3 ..., K), takes apart from the smallest akFor
GiGeneric, by GiAffiliatedIn Di{ui,ni,PiA is addedkCorresponding load data collection CkIn；Step 24 is repeated, directly
To allIt is disposed, is included into corresponding load data and concentrates.
2. the limited speed change cruise method of a kind of vehicle according to claim 1, it is characterised in that: the method specifically:
Different loads coefficient is clustered out from gaussian distribution data；All load factor a clustered according to load factoriValue, meter
Calculating in current load factor is aiIn the case where, " speed-power " curve that power changes with speed；Due under identical speed
Power output influenced and different by gear n, therefore curve also needs to distinguish according to different gears；I.e. vehicle is real-time
It is cubic polynomial relationship in the relation nature of output power P and vehicle real-time speed u, therefore sets: P=β1u3+β2u2+β3u+β4
Wherein β1,β2,β3,β4For the parameter of curve to regression estimates, similar load data collection C is utilizedkThe data of middle different stalls n, are adopted
The parameter value to regression estimates under different stalls is found out with least square method recurrence to get different stalls, different loads have been arrived
" speed-power " characteristic curve under coefficient；It returns to obtain different stalls in characteristic curve, " the speed under different loads coefficient
After degree-power " characteristic curve, finite region speed change cruise function can be opened for vehicle；Finite region is opened when vehicle to become
After fast cruise function, vehicle real-time speed u and vehicle real-time output power P and gear n is acquired from CAN bus in real time, on
Car networking center is reached, and the characteristic curve fitted with car networking center is matched, the characteristic after obtaining current matching is bent
Line；Using, with the oil consumption of each speed cruise, being patrolled according to prediction result in the characteristic curve law forecasting finite interval after matching
Speed of a ship or plane degree, toward the economic section fine tuning of engine, reaches the target of oil consumption economy when improving vehicle cruise in finite interval.
3. the limited speed change cruise method of a kind of vehicle according to claim 2, it is characterised in that: described to utilize car networking pair
A certain vehicle needs to acquire the cruise feature of the vehicle in advance, uses car-mounted terminal by vehicle CAN bus with the time
Interval constantly vehicle real-time speed u, gear n, vehicle real-time output power P of the acquisition vehicle in cruise, composition data
Frame Di{ui,ni,Pi, i=1,2,3 ..., I upload to car networking center；Specifically:
Step 11, vehicle, which enter after cruise to start to be spaced at regular intervals, to be sampled, and sampling time interval takes 90ms
~120ms obtains the vehicle real-time speed u of sampling instant ii, gear ni, the real-time output power P of vehiclei, composition data frame Di
{ui,ni,Pi, i=1,2,3 ..., I upload to car networking center；Enter step 12；
Step 12: judge whether vehicle is in cruise state, if it is return step 11 continues to sample, if it is not,
Then stop sampling；
Cruise sampling can be completed jointly by same type of more vehicles, when sampled data covers the various gradients and road surface substantially
When situation, sampled data is complete, carries out load factor cluster.
4. the limited speed change cruise method of a kind of vehicle according to claim 2, it is characterised in that: described then negative from difference
It carries in revolving speed belonging to coefficient and power historical data and " speed-power " characteristic curve is fitted using cubic polynomial；Specifically
Are as follows:
Step 31, to each load data collection CkIn all data Di{ui,ni,Pi, according to gear niClassify, obtains
Data set N under different stalls Kk{Di|ni=K }；The relationship of the real-time output power P of vehicle and vehicle real-time speed u is more three times
Item formula relationship, the cubic polynomial relationship
P=β1u3+β2u2+β3u+β4 (5)
Wherein β1,β2,β3,β4For the parameter of curve to regression estimates；
Step 32: to data set Nk{Di|ni=K } least square method is utilized, it carries out " speed-power " cubic polynomial curve and returns
Return, obtains each β of the cubic polynomial curve of formula (5)1,β2,β3,β4Parameter；Step 32 is repeated, until under all gears
Cubic curve equation parameter is returned and is finished；
Step 33: return step 31, until all load data collection CkAll it is disposed；
Step 34: by all parameters of curve, there are in car networking central database.
5. the limited speed change cruise method of a kind of vehicle according to claim 2, it is characterised in that: find out all " speed-
After power " curve, finite region speed change cruise function is opened, if vehicle sets cruising speed as V, the limited variation of cruising speed
Section is [V- ε, V+ ε], adjusts cruising speed in real time as follows:
Step 41: the vehicle in speed change cruise acquires vehicle real-time speed u and the real-time output work of vehicle from CAN bus in real time
Rate P and gear n, and upload car networking center；
Step 42: car networking center carries out Curve Matching calculating, is located under gear n and shares M characteristic curve, and coefficient is { β1m,
β2m,β3m,β4m, m=1,2 ..., M；Vehicle real-time speed u is substituted into each curvilinear equation, calculated curve corresponds to power
ValueFromMiddle taking-up and the real-time immediate value of output power P of vehicle, are set asI.e.Then curve P=β1ju3+β2ju2+β3ju+β4jIt is matched, enters step 43；
Step 43: setting vehicle and set cruising speed as V, the limited constant interval of cruising speed is [V- ε, V+ ε], then by limited change
Change all velocity amplitude v in sectionj∈ [V- ε, V+ ε], the ε of j=1,2 ..., 2 substitute into the curve being matched, and find out limited variation
The corresponding performance number P of each speed in sectionj, the ε of j=1,2 ..., 2；Utilize power PjWith speed vjPredict limited constant interval
Interior each speed vjCorresponding fuel consumption per hundred kilometers value Qj:
It is known quantity that wherein ρ, which is the density of fuel oil, and g is acceleration of gravity, bjFor according to PjWith vjEngine Universal Characteristics table is looked into obtain
The fuel consumption rate arrived；
Step 44: according to the smallest QjIt is worth corresponding speed v, the optimal travel speed as in finite interval, by cruising speed
Being adjusted to v can reach the purpose of the most economical fuel consumption per hundred kilometers in finite speed section；
Step 45: return step 41 constantly calculates in real time and adjusts best cost cruising speed.
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| CN106677913B (en) * | 2015-11-10 | 2019-11-01 | 中联重科股份有限公司 | Power and load matching control method, device and system and transport vehicle |
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| CN108266278A (en) * | 2016-12-30 | 2018-07-10 | 中国移动通信集团公司 | Method, system, T platforms and the OBD terminals that a kind of automobile engine power is adjusted |
| CN107433942B (en) * | 2017-07-27 | 2019-08-09 | 清华大学 | Energy-saving longitudinal movement control method, device and the vehicle of motorized vehicle |
| CN109552329A (en) * | 2018-12-26 | 2019-04-02 | 与德科技有限公司 | Constant speed of vehicle cruise method, device and storage medium |
| CN110059289B (en) * | 2019-03-01 | 2022-08-26 | 吉林大学 | Engineering vehicle load power prediction method based on Kalman filtering neural network |
| CN110155051B (en) * | 2019-04-30 | 2020-11-13 | 吉林大学青岛汽车研究院 | Fuel-saving control method for truck speed change cruise |
| CN113239963B (en) * | 2021-04-13 | 2024-03-01 | 联合汽车电子有限公司 | Method, device, equipment, vehicle and storage medium for processing vehicle data |
| CN113232652B (en) * | 2021-06-16 | 2022-10-25 | 武汉光庭信息技术股份有限公司 | Vehicle cruise control method and system based on kinematics model |
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