CN110228470A - A kind of rate of economizing gasoline real-time computing technique based on the prediction of hiding auto model - Google Patents
A kind of rate of economizing gasoline real-time computing technique based on the prediction of hiding auto model Download PDFInfo
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Abstract
The invention belongs to vehicle information technologies field, specifically a kind of rate of economizing gasoline real-time computing technique based on the prediction of hiding auto model.The calculation method is the following steps are included: Step 1: calculate the real vehicles oil consumption of optimization cruise control system control；Step 2: benchmark cruise control system oil consumption is calculated by virtually hiding model, wherein virtually hiding auto model parameter carries out resetting by real vehicle data according to the switching of follow the bus target to reduce model error as far as possible；Rate of economizing gasoline is obtained Step 3: being compared with the oil consumption of step 1 and the calculated two systems of step 2.The present invention is using hiding oil consumption model method, oil consumption calculated result is set preferably to reflect influence of the traffic conditions to cruise system, the error of oil consumption comparing result is reduced, so as to find out real-time rate of economizing gasoline, solves the problems, such as that existing cruise system real-time fuel consumption calculating exists.
Description
Technical field
The invention belongs to vehicle information technologies field, specifically a kind of rate of economizing gasoline based on the prediction of hiding auto model
Real-time computing technique.
Background technique
With the development of the V2X mechanics of communication such as 5G, cartographic information, ambient condition information etc. can be used for the control of vehicle
System, this interconnects for smart city and realizes that target for energy-saving and emission-reduction provides with control by multilevel programming, optimization under information environment
It may.Countries in the world propose the development plan of State-level for the energy-saving and emission-reduction under intelligent network connection.
Big data information is made full use of in the intelligent network connection epoch to realize that energy-saving and emission-reduction will become domestic and international vehicle enterprise future
Research direction.Ford Motor Company applied utilizing Nonlinear Model Predictive Control design prediction cruise section in 2017
It can control system patent, the world such as general, daily output, continent, ZF vehicle enterprise has also all carried out corresponding research with supplier.
Domestic patent of invention CN 201710291137.0 authorizes a kind of real-time prediction cruise control system driven based on economy,
Include: information acquisition module: for acquiring current vehicle and front vehicles running condition information, including velocity information, working as front truck
And front truck distance and Prediction distance in road traffic speed limiting information；The information of acquisition is passed into vehicle power
Learn model building module；Vehicle dynamic model establishes module, according to the traffic speed restricted information and front truck of acquisition and this
The running condition information of vehicle establishes vehicle dynamic model, while establishing control problem, determines the target of optimization and is met
Constraint condition；Rolling time horizon optimizes computing module: the control problem peace treaty of module proposition is established based on vehicle dynamic model
Beam condition, the method combined by huge Baudrillard gold minimal principle and dichotomy, optimization obtain optimal gear sequence, most
The display solution of excellent motor torque and brake force, determines optimal control law.
It is general using prediction cruise system but in the real-time fuel consumption of computing system and when testing the oil-saving effect of such system
System carries out test of many times with to mark baseline system respectively on same route, and the fuel consumption per hundred kilometers for seeking each system is average
Value calculates rate of economizing gasoline.This method is as conventional real train test fuel consumption calculation method, though simple and practical, there is also many
Disadvantage, such as the traffic environment operating condition that two comparison systems work when real train test have differences, and accurately can not objectively arrange
Except effect of the proof control system to oil-saving effect under the influence of external environment.In addition, in the development task of the system mass production
In, in open system oil-saving effect will in the form of increasing course continuation mileage real-time exhibition to rider.Then fuel-economizing benchmark
Definition and the real-time display of oil-saving effect become for urgent problem.
Domestic patent CN 201810783843.1 discloses a kind of automobile fuel consumption real-time estimation side based on mobile terminal
Method, comprising: obtain the X-axis data of acceleration transducer and the X-axis data of Y-axis data and gyroscope, pass through acceleration sensing
The X-axis data of device obtain the vehicle driving acceleration with weight component；It is obtained by the Y-axis data of acceleration transducer
The road gradient obtains road grade by the X-axis data of gyroscope；To acceleration transducer and the collected data of gyroscope into
Row fusion, acceleration and optimal gradient estimated value after being corrected obtain the true of automobile according to the acceleration after correction and add
Speed；The true acceleration of automobile is integrated, the travel speed of automobile is obtained.The invention utilizes the embedded of mobile terminal
Sensor is realized to vehicle driving acceleration, speed and oil consumption real-time estimation, for assessing the green of driver's driving behavior
Degree reduces fuel consumption so that driver be helped to form the driving habit of green.This method may be implemented to vehicle oil consumption
Real-time estimation, have good reference.
Domestic patent CN 201410816008.5 discloses a kind of oil consumption prediction technique and device, method are as follows: according to electronics
Map determines at least one target traffic information that road to be predicted is included, for every kind of target traffic information, from preset
In traffic information and oil consumption model corresponding relationship, call with target traffic information for oil consumption model, and according to target road conditions
Information and corresponding oil consumption model calculate oil consumption of the road to be predicted under each target road conditions, finally road to be predicted exist
Oil consumption and value under each target road conditions are determined as total oil consumption of road to be predicted.The scheme of this application, it is contemplated that be predicted
Road may include a variety of different target traffic informations, call preset correspondence oil consumption model to carry out oil consumption prediction, so that most
The total oil consumption obtained eventually is more close to actual conditions namely accuracy is higher.
A kind of effective method for calculating vehicle oil consumption is both provided in the above patent of invention, but is seeking a control
When the rate of economizing gasoline of system, frequently with the method that benchmark oil consumption is set as to constant value, two comparison systems when lacking for real train test
It the considerations of difference existing for the traffic environment operating condition of work of uniting, can not accurately objectively be proved under the influence of excluding external environment
Effect of the control system to oil-saving effect.
Summary of the invention
The present invention changes oil consumption comparing result according to the change of traffic environment using oil consumption model method is hidden
Become, reduces the error of oil consumption comparing result, solve the above problem existing for existing prediction oil consumption.
Technical solution of the present invention is described with reference to the drawings as follows:
It is a kind of based on hiding auto model prediction rate of economizing gasoline real-time computing technique, the calculation method the following steps are included:
Step 1: calculating the real vehicles oil consumption of optimization cruise control system control；
Step 2: calculating benchmark cruise control system oil consumption by virtually hiding model；
Rate of economizing gasoline is obtained Step 3: being compared with the oil consumption of step 1 and the calculated two systems of step 2.
The specific method is as follows for the step 1:
From the power CAN message module of heat transfer agent module and vehicle obtain optimization cruise control system calculated needed for
The relative distance for the target lead object wanted, relative velocity, status information i.e. this vehicle speed of vehicle, engine turn
Speed, motor torque, current shift, the gradient curvature information of road ahead, after obtaining these information, by optimization cruise control
System performance model PREDICTIVE CONTROL carries out rolling optimization, then combines with huge Baudrillard gold minimal principle and dichotomy
Braking deceleration required for being calculated and driving moment；By optimization cruise control system, calculated braking subtracts in real time
Speed and driving moment instruction are exported by vehicle power CAN to EMS and the ESC execution of vehicle, to control real vehicles
Carry out follow the bus or cruise traveling；The motor torque Yu revolving speed of real vehicles are input to oil after obtaining by CAN communication at this time
Computing module is consumed, instantaneous oil consumption is obtained by the lookup to oil consumption MAP table, then calculates optimal control by dynamic corrections
The oil consumption of algorithm.
The specific method is as follows for the step 2:
It is obtained required for benchmark cruise system calculated from the power CAN message module of heat transfer agent module and vehicle
The relative distance of target lead object, relative velocity, vehicle status information i.e. this vehicle speed, engine speed, hair
Motivation torque, current shift, later, by benchmark cruise control system by pid algorithm be calculated in instantly opposite away from
I.e. relative distance carries out braking deceleration and driving moment required for cruise travels divided by vehicle is controlled under this vehicle speed；Meter
It calculates desired braking deceleration and driving moment enters virtual hide in auto model and controls vehicle driving, when follow the bus target has
When variation, with true this vehicle parameter i.e. this vehicle speed, engine speed, motor torque, current shift and front vehicles
The relative distance of parameter, that is, front vehicles and this vehicle and relative velocity by virtual vehicle model parameter and follow the bus object parameter into
Row resetting, to eliminate due to the speed cumulative errors in model error bring virtual vehicle model, by environmental perception module
Obtained front vehicles information will be sent to real vehicles and virtual vehicle simultaneously, realize and hide vehicle under true traffic scene
The operation of model.
The construction method of the virtual vehicle model is as follows:
The auto model built with Simulink, including torque and throttle opening conversion module, engine block, transmission
System module and longitudinal dynamics module；The input of the auto model is engine demand torque and braking deceleration, output
For engine speed and the true torque of engine.
In the throttle opening conversion module, what is provided due to control algolithm is demand engine moment order, is needed
Demand engine torque command is converted to throttle opening order to execute to engine mockup；Engine is used in this module
Actual revolution and demand motor torque table look-up to obtain throttle opening, and then adjusting throttle opening by PID makes really to send out
Motivation torque keeps up with demand motor torque；When demand engine moment is less than zero, throttle opening zero；Lookup data
It is obtained by actual engine rack data, but lacks the data of full throttle in tables of data, full throttle operating condition exists
Seldom exist under truth, so being assumed to be maximum throttle opening data with 84% throttle opening in table, deposits here
In error；
Building for the engine block is the throttle opening that will be previously obtained multiplied by starting under present engine revolving speed
Machine maximum output torque obtains the effective output torque of engine at this time, makees ratio with constant engine maximum output torque later
It is relatively minimized to obtain engine output torque at this time, the engine maximum output torque under present engine revolving speed is also
The maximum mean effective pressure BMEP for obtaining current time by providing data in engine bed rack data, is obtaining engine most
By formula after big mean effective pressure
T (Nm)=BMEP (bar) * V (L)/(4*pi*0.01)
The effective output torque of the engine under current rotating speed of vehicle is calculated, wherein V indicates engine displacement,
He is substituted into parameter by real vehicle parameter；
Building for the train module is that the throttle opening obtained by engine block and speed are entered shift
The gear at module decision current time exports true torque and transmission ratio, hydraulic moment changeable with corresponding transmission ratio, engine block
Device efficiency is multiplied, and obtains transmission shaft driving moment divided by radius of wheel later, and transmission shaft driving moment is added with braking moment,
It obtains transmission shaft torque to export to longitudinal vehicle dynamic model, and engine speed is obtained by speed backstepping and carries out bending moment
The lookup of device efficiency；Using state machine model, upshifts and downshift based on speed and the determination of the two parameters of throttle opening
Instruction.
The prime formula of the longitudinal vehicle dynamic model are as follows:
Ft=Ff+Fw+Fj+Fi。
Wherein, FtFor driving force, unit N, since automobile is that neutral gear slides so it is zero, FfIt is single for frictional resistance
Position is N, and the form that embodies is Ff=Mg·f；Wherein, MgFor car weight, unit N, f are coefficient of friction, FwFor running car
Air drag, unit N, the form of embodying areWherein CAFor coefficient of air resistance, v0Start for automobile
Speed when sliding, unit m/s, FjFor the inertia force of vehicle, expression Fj=Map, wherein M is vehicle matter
Amount, unit kg, apFor the acceleration that slides under neutral gear, unit m/s2, FiFor the gradient resistance of vehicle, unit N；It is described
Longitudinal dynamics module is traditional longitudinal direction of car kinetics equation, but complete vehicle quality M and gradient α are parameter to be identified, right
Longitudinal direction of car dynamics has an impact.
The identification process of the gradient α are as follows:
By the working principle of acceleration transducer it is found that vehicle in upward slope or descending, is measured by acceleration transducer
Acceleration be actually longitudinal acceleration of the vehicle and acceleration of gravity along the sum of ramp component；
The calculation formula of the gradient are as follows:
Wherein, avFor the vehicle acceleration that speed derivation obtains, asenThe acceleration measured for the acceleration transducer of vehicle
Degree, can be obtained current road grade divided by acceleration g after making the difference；Since there are transmission system buffeting, speed signal exists
The shake of fixed frequency, and the period shaken reduces with the increase of speed, so being wanted when carrying out differential to speed
A cycle is selected to carry out differential, clipping is carried out after differential and is filtered with low-pass filter, vehicle
Acceleration signal is also required to carry out clipping and is filtered with low-pass filter.
The identification process of the complete vehicle quality M are as follows:
Complete vehicle quality M is recognized using recursive least squares；
Conventional truck longitudinal dynamics equation are as follows:
Ft=Fw+mgf+mgi+ma
Wherein, FtFor the driving force of vehicle, since vehicle traction force data can not be directly obtained, so we need to pass through
The driving force of engine output, passes through the true driving force for being converted to vehicle of transmission system, FwFor the air of vehicle driving
Resistance, mgf are the rolling resistance of vehicle driving, and f is the coefficient of rolling resistance of vehicle, and mgi is the grade resistance of vehicle, and i is
The sine value of the gradient, ma are the acceleration resistance of vehicle；
It is changed into recurrence least square format, can obtains:
γ (k)=P (k-1) a_e (k) [a_e (k) P (k-1) a_e (k)+μ (k)]-1
Wherein, e is process white noise, and above formula is re-started transformation, can be obtained:
Ftw=θ a_e+e
Wherein,System output quantity is represented, θ=m represents parameter to be identified, a_e=gf+
Gi+a represents observable data vector；
According to the principle of least square, the least square recursive formula of system can be obtained are as follows:
γ (k)=P (k-1) a_e (k) [a_e (k) P (k-1) a_e (k)+μ (k)]-1
P (k)=μ (k)-1[I-γ(k)a_e(k)]P(k-1)
Wherein, μ (k) is the forgetting factor at kth moment, and γ (k) is the gain matrix at k moment, Ftw(k) the k moment is indicated
System input quantity,The quality that the expression k moment recognizes, in Multistage Recursive Least-Squares identification,It is needed with γ (k) preparatory
Initialization, I indicate that unit matrix, P (k) indicate the excessive matrix at k moment.
Using the oil consumption model oil consumption calculate detailed process is as follows:
The method that oil consumption model tables look-up to engine consumption MAP using engine speed and torque, but MAP table is
Into engine rig test static demarcating is crossed, needs to be modified it by the true fuel consumption data of fuel consumption meter and reach dynamic
Compensation.
Wherein FinsFor accumulative oil before the real vehicle amendment under optimization cruise control system or the control of benchmark cruise control system
Consumption,It indicates the instantaneous oil consumption found out by engine speed and torque, integrates available accumulative oil consumption, later
Revised oil consumption is obtained by amendment；
Ffinal=aFins 2+b·Fins+c
Formula is correction function, FfinalIndicate the reality under optimization cruise control system or the control of benchmark cruise control system
Add up oil consumption, a, b after vehicle amendment, c is correction formula parameter.
Detailed process is as follows for the step 3:
Compared with calculated benchmark cruise control system oil consumption carries out once with the every 1km of optimization cruise control system oil consumption,
Available optimization cruise control system compares the rate of economizing gasoline of benchmark cruise control system；
Wherein, φ is rate of economizing gasoline, FoptFor the real vehicle oil consumption under optimization cruise control system control, FbenchmarkOn the basis of patrol
Virtual vehicle model oil consumption under control system of navigating control；Further, since the oil consumption of optimization cruise control system is also in accumulative meter
It calculates and does not reset, so as to obtain the fuel consumption per hundred kilometers of optimization cruise control system；Finally obtained rate of economizing gasoline and hundred kilometers
Oil consumption is input to human-computer interaction interface by CAN communication and is shown.
The invention has the benefit that
1, the present invention constructs accurate longitudinal vehicle dynamic model by reasonable model buildings method, and by model
The inspiration of PREDICTIVE CONTROL is reset with real vehicle parameter when follow the bus target changes and hides model and front truck state parameter,
The oil consumption of vehicle cruise control is calculated, multiple follow the bus stages are divided into according to follow the bus object, with based on follow the bus object
Switch carry out vehicle parameter with new, portray this vehicle speed wave caused by the follow the bus object in the case of true follow the bus switches
It is dynamic, the follow the bus for the base controllers algorithm for each making virtual vehicle model can be very good to react under identical traffic scene
Control effect, so as to maximumlly embody the follow the bus driving style of benchmark control algolithm.
2, the present invention estimates road grade using CAN bus information and equation, carries out with recurrent least square method
Complete vehicle quality recognizes to solve auto model precision problem；
3, the present invention searches oil consumption MAP table to traditional revolving speed using engine and torque by actual fuel consumption data
Method to calculate engine consumption has carried out improvement amendment, keeps calculated engine consumption more accurate.
Detailed description of the invention
Fig. 1 is to calculate comparison system schematic diagram in real time using the vehicle oil consumption for hiding auto model；
Fig. 2 is virtually to hide model oil consumption computing architecture figure；
Fig. 3 is auto model Simulink illustraton of model；
Fig. 4 is that the gradient estimates schematic diagram；
Fig. 5 is that the gradient estimates design frame chart；
Fig. 6 is recurrence least square quality identification structure schematic diagram；
Fig. 7 is oil consumption model data correction module schematic diagram.
Specific embodiment
Under the premise of not changing system software architecture, the invention proposes a kind of using the vehicle oil for hiding auto model
Consumption calculates comparison system in real time.System principle such as Fig. 1, true vehicle by optimization algorithm system control run in the case where,
The fuel consumption of optimization algorithm system, the fuel consumption are obtained by the engine speed and torque interpolation calculation of real vehicles
Amount is updated primary and is not reset every 1km.Simultaneously, also operation has and is controlled by bench-marking algorithm in the controller
Virtual vehicle model.Since virtual vehicle model is used, then model error problem just becomes to avoid.In order to solve
This problem is inspired by Model Predictive Control principle, when follow the bus target changes, with true this vehicle parameter and front
Vehicle parameter resets virtual auto model parameter and follow the bus object parameter, to eliminate due to model error band
The speed cumulative errors in virtual vehicle model come, the front vehicles information obtained by environmental perception module will be sent simultaneously
To real vehicles and virtual vehicle, the above-mentioned difference due to traffic environment can be effectively avoided to cause oil consumption in this way
The problem of comparing result confidence level declines.The engine speed and torque interpolation calculation of virtual vehicle model obtain bench-marking
The fuel consumption of algorithm, the fuel consumption also will update primary and accumulate every 1km.Real vehicles in this way
The fuel consumption of fuel consumption and virtual vehicle compares, it can be deduced that the real-time fuel consumption rate of optimization algorithm system,
To which increase course continuation mileage be calculated.
This method high degree allows bench-marking algorithm simulation to operate under the same traffic environment of optimization algorithm system,
And the thought of Model Predictive Control is borrowed, has predicted fuel consumption of the bench-marking algorithm under same follow the bus target, currently
The follow the bus target of side mediates two vehicle speeds by force when changing, and so rolls the calculating comparison for being carried forward oil consumption, can be with
Be effectively prevented from measurement optimize cruise control algorithm when, due to traffic environment can not repdocutbility bring oil consumption comparison knot
The error of fruit.
Specific virtually hiding model oil consumption Computational frame is as shown in Figure 2.Information of vehicles and environmental information enter benchmark pair
Virtual vehicle model is given than output engine requirement drive torque after algorithm and braking deceleration order, virtual vehicle model
The true torque of engine and engine speed export the accumulative oil consumption that virtual vehicle is calculated to oil consumption computing module, every 1km to
It is outer to send once, rate of economizing gasoline is calculated with real vehicles oil consumption.
But another problem is also brought using auto model --- the precision of model.Auto model and real vehicles
Mismatch will cause the misalignment of travel condition of vehicle, so as to cause the distortion of bench-marking algorithmic system real-time fuel consumption, to understand
Certainly this problem carries out Accurate Model on the basis of real vehicles parameter.
For hiding auto model, accurately longitudinal vehicle dynamic model is built in Simulink comprising start
Machine model, actuation system models and longitudinal vehicle dynamic model, wherein the gradient and complete vehicle quality in vehicle operation
The influence changed to vehicle oil consumption is also very big, and then we estimate road grade using CAN bus information and equation,
Complete vehicle quality identification is carried out with recurrent least square method to solve auto model precision problem.
A specific embodiment of the invention can be divided into three steps:
Step 1: calculating the real vehicles oil consumption of optimization cruise control system control；It is specific as follows:
From the power CAN message module of heat transfer agent module and vehicle obtain optimization cruise control system calculated needed for
The information such as relative distance, the relative velocity of the target lead object wanted, the status information of vehicle i.e. this vehicle speed, engine
Revolving speed, motor torque, current shift, the information such as gradient curvature of road ahead after obtaining these information, are cruised by optimization
Control system performance model PREDICTIVE CONTROL carries out rolling optimization, then with huge Baudrillard gold minimal principle and dichotomy phase
The braking deceleration in conjunction with required for being calculated and driving moment；By optimization cruise control system calculated system in real time
Dynamic deceleration and driving moment instruction are exported by vehicle power CAN to EMS and the ESC execution of vehicle, so that control is true
Vehicle carries out follow the bus or cruise traveling；The motor torque of real vehicles inputs after being obtained with revolving speed by CAN communication at this time
To oil consumption computing module, instantaneous oil consumption is obtained by the lookup to oil consumption MAP table, then calculates optimization by dynamic corrections
The oil consumption of control algolithm.
Detailed process is as follows for the oil consumption calculating of the oil consumption model:
The method that oil consumption model tables look-up to engine consumption MAP using engine speed and torque, but MAP table is
Into engine rig test static demarcating is crossed, needs to be modified it by the true fuel consumption data of fuel consumption meter and reach dynamic
Compensation, structural framing figure are as shown in Figure 7.Fitting formula are as follows:
Wherein, FinsIt is accumulative before the real vehicle amendment under optimization cruise control system or the control of benchmark cruise control system
Oil consumption,It indicates the instantaneous oil consumption found out by engine speed and torque, integrates available accumulative oil consumption, it
Revised oil consumption is obtained by amendment afterwards；
Ffinal=aFins 2+b·Fins+c
Formula is correction function, FfinalIndicate the reality under optimization cruise control system or the control of benchmark cruise control system
Add up oil consumption, a, b after vehicle amendment, c is correction formula parameter.
Step 2: calculating benchmark cruise control system oil consumption by virtually hiding model；It is specific as follows:
It is obtained required for benchmark cruise system calculated from the power CAN message module of heat transfer agent module and vehicle
The information such as relative distance, the relative velocity of target lead object, the status information of vehicle i.e. this vehicle speed, engine speed,
Motor torque, current shift are calculated by pid algorithm in instantly opposite by benchmark cruise control system later
Braking deceleration and driving moment required for cruise travels are carried out divided by vehicle is controlled under this vehicle speed away from i.e. relative distance；
It calculates desired braking deceleration and driving moment enters virtual hide in auto model and controls vehicle driving, when follow the bus target
When changing, with true this vehicle parameter i.e. this vehicle speed, engine speed, motor torque, current shift and front vehicle
The relative distance and relative velocity of parameter, that is, front vehicles and this vehicle are by virtual vehicle model parameter and follow the bus object parameter
It is reset, to eliminate due to the speed cumulative errors in model error bring virtual vehicle model, by environment sensing mould
The front vehicles information that block obtains will be sent to real vehicles and virtual vehicle simultaneously, realize and hide under true traffic scene
The operation of auto model.
The construction method of the virtual vehicle model is as follows:
Refering to Fig. 3, the auto model built with Simulink, including torque and throttle opening conversion module, engine
Module, train module and longitudinal dynamics module；The input of the auto model is that engine demand torque subtracts with braking
Speed exports as engine speed and the true torque of engine.
In the throttle opening conversion module, what is provided due to control algolithm is demand engine moment order, is needed
Demand engine torque command is converted to throttle opening order to execute to engine mockup；Engine is used in this module
Actual revolution and demand motor torque table look-up to obtain throttle opening, and then adjusting throttle opening by PID makes really to send out
Motivation torque keeps up with demand motor torque；When demand engine moment is less than zero, throttle opening zero；Lookup data
Obtained by actual engine rack data, but in tables of data lack full throttle data (full throttle operating condition exists
Seldom exist under truth), so being assumed to be maximum throttle opening data with 84% throttle opening in table, here
There are unavoidable some errors.
Building for the engine block is the throttle opening that will be previously obtained multiplied by starting under present engine revolving speed
Machine maximum output torque obtains the effective output torque of engine at this time, makees ratio with constant engine maximum output torque later
It is relatively minimized to obtain engine output torque at this time, the engine maximum output torque under present engine revolving speed is also
The maximum mean effective pressure BMEP for obtaining current time by providing data in engine bed rack data, is obtaining engine most
By formula after big mean effective pressure
T (Nm)=BMEP (bar) * V (L)/(4*pi*0.01)
The effective output torque of the engine under current rotating speed of vehicle is calculated, wherein V indicates engine displacement, east
Its numerical value of wind G29_EW10 engine is 1.997L, and other parameters are substituted by real vehicle parameter.
Building for the train module is that the throttle opening obtained by engine block and speed are entered shift
The gear at module decision current time exports true torque and transmission ratio, hydraulic moment changeable with corresponding transmission ratio, engine block
Device efficiency is multiplied, and obtains transmission shaft driving moment divided by radius of wheel later, and transmission shaft driving moment is added with braking moment,
It obtains transmission shaft torque to export to longitudinal vehicle dynamic model, and engine speed is obtained by speed backstepping and carries out bending moment
The lookup of device efficiency；Using state machine model, upshifts and downshift based on speed and the determination of the two parameters of throttle opening
Instruction.
The prime formula of the longitudinal vehicle dynamic model are as follows:
Ft=Ff+Fw+Fj+Fi。
Wherein, FtFor driving force, unit N, since automobile is that neutral gear slides so it is zero, FfIt is single for frictional resistance
Position is N, and the form that embodies is Ff=Mg·f；Wherein, MgFor car weight, unit N, f are coefficient of friction, FwFor running car
Air drag, unit N, the form of embodying areWherein GAFor coefficient of air resistance, v0Start for automobile
Speed when sliding, unit m/s, FjFor the inertia force of vehicle, expression Fj=Map, wherein M is vehicle matter
Amount, unit kg, apFor the acceleration that slides under neutral gear, unit m/s2, FiFor the gradient resistance of vehicle, unit N；It is described
Longitudinal dynamics module is traditional longitudinal direction of car kinetics equation, but complete vehicle quality M and gradient α are parameter to be identified, right
Longitudinal direction of car dynamics has an impact.
The identification process of the gradient α are as follows:
The gradient is very big to longitudinal direction of car kinetic effect, and then influences the tracking effect of following distance or speed；Accurately
Longitudinal Dynamic Model can effectively reduce the steady-state error of model, to reduce the integral gain in controller.At present
The method that can be estimated in real time road grade mainly has 3 kinds: estimating road grade using GPS elevation information；It utilizes
CAN bus message and equation estimate road grade；It is additional to add acceleration transducer to estimate road grade.Due to examination
Validate the car has acceleration sensor outputs signals in itself, and this method does not wait identified parameters to couple with complete vehicle quality, so adopting
The gradient of vehicle is calculated with the third method.
By the working principle of acceleration transducer it is found that vehicle in upward slope or descending, is measured by acceleration transducer
Acceleration be actually longitudinal acceleration of the vehicle and acceleration of gravity along the sum of ramp component, as shown in Figure 4.
The calculation formula of the gradient can so be obtained are as follows:
Wherein, avFor the vehicle acceleration that speed derivation obtains, asenThe acceleration measured for the acceleration transducer of vehicle
Degree, can be obtained current road grade divided by acceleration g after making the difference；Since there are transmission system buffeting, speed signal exists
The shake of fixed frequency, and the period shaken reduces with the increase of speed, so being wanted when carrying out differential to speed
A cycle is selected to carry out differential, clipping is carried out after differential and is filtered with low-pass filter, vehicle
Acceleration signal is also required to carry out clipping and is filtered with low-pass filter, specific design frame chart such as Fig. 5 institute
Show.
The completion of gradient estimation can reduce the dependence to high-precision map, improve the precision of virtual vehicle model running,
To predict that the mass production scheme of cruise algorithm provides a kind of new thinking and possibility later.
The identification process of the complete vehicle quality M are as follows:
It is well known that complete vehicle quality M has a very big impact oil consumption, and during vehicle test, due to vehicle occupant
The difference of member's quantity and consumption with vehicle fuel oil, complete vehicle quality can be changed, if be given to complete vehicle quality as constant
In auto model, then being bound to that large effect will be caused to vehicle oil consumption.Since complete vehicle quality is the ginseng become slowly
Number, so not having extra high requirement to the real-time of identification algorithm.
Present invention employs most classical, most basic Identification of parameter, that is, recursive least squares, firstly, traditional
Longitudinal direction of car kinetics equation are as follows:
Ft=Fw+mgf+mgi+ma
Wherein, FtFor the driving force of vehicle, since vehicle traction force data can not be directly obtained, so we need to pass through
The driving force of engine output, passes through the true driving force for being converted to vehicle of transmission system, FwFor the air of vehicle driving
Resistance, mgf are the rolling resistance of vehicle driving, and f is the coefficient of rolling resistance of vehicle, and mgi is the grade resistance of vehicle, and i is
The sine value of the gradient, ma are the acceleration resistance of vehicle；
It is changed into recurrence least square format, can obtains:
γ (k)=P (k-1) a_e (k) [a_e (k) P (k-1) a_e (k)+μ (k)]-1
Wherein, e is process white noise, and above formula is re-started transformation, can be obtained:
Ftw=θ a_e+e
Wherein,System output quantity is represented, θ=m represents parameter to be identified, a_e=gf+
Gi+a represents observable data vector；
According to the principle of least square, the least square recursive formula of system can be obtained are as follows:
γ (k)=P (k-1) a_e (k) [a_e (k) P (k-1) a_e (k)+μ (k)]-1
P (k)=μ (k)-1[I-γ(k)a_e(k)]P(k-1)
Wherein, μ (k) is the forgetting factor at kth moment, and in calculating process, as recurrence is pushed ahead, γ (k) can be fast
The decaying of speed, while μ (k) can also decay rapidly, so that new data are smaller and smaller to the correction effect of parameter estimation until effect
Fruit loses, this phenomenon is referred to as " data saturation " phenomenon, in order to avoid the generation of this phenomenon, propose forgetting factor this
One concept, the new data obtained in identification process in this way can become by force the correction effect of parameter estimation, and legacy data is to parameter
The correction effect of valuation can die down, and " data saturation " this problem is just resolved.Forgetting factor is bigger, carries out to system
The precision of identification is higher, but the convergence time of System Discrimination result can be caused elongated simultaneously.Forgetting factor value is too small to be enabled
The precision of System Discrimination is lower, but the convergence time of System Discrimination result can be caused to shorten simultaneously.Herein, forgetting factor
It is chosen for 0.95.In Multistage Recursive Least-Squares identification,Need to preset initial value with γ (k), setting is first under normal conditions
Value is to enable there are two types of methodIn element be zero or lesser parameter, enable γ (k)=α I, wherein α be 105~
1010Real number.After the recurrence equation for obtaining the identification of recurrence least square quality, recurrence least square quality identification structure is such as
Fig. 6.
The completion of complete vehicle quality identification, can be improved the precision of virtual vehicle model running, makes the oil of virtual vehicle model
Consumption estimation is more accurate, is the basis of fuel-economizing benchmark formulation and oil-saving effect real-time display.
Rate of economizing gasoline is obtained Step 3: being compared with the oil consumption of step 1 and the calculated two systems of step 2；Specifically such as
Under:
The method that oil consumption model tables look-up to engine consumption MAP using engine speed and torque, but MAP table is
Into engine rig test static demarcating is crossed, needs to be modified it by the true fuel consumption data of fuel consumption meter and reach dynamic
Compensation.
Wherein FinsFor accumulative oil before the real vehicle amendment under optimization cruise control system or the control of benchmark cruise control system
Consumption,It indicates the instantaneous oil consumption found out by engine speed and torque, integrates available accumulative oil consumption, later
Revised oil consumption is obtained by amendment；
Ffinal=aFins 2+b·Fins+c
Formula is correction function, FfinalIndicate the reality under optimization cruise control system or the control of benchmark cruise control system
Add up oil consumption, a, b after vehicle amendment, c is correction formula parameter.
Compared with calculated benchmark cruise control system oil consumption carries out once with the every 1km of optimization cruise control system oil consumption,
Available optimization cruise control system compares the rate of economizing gasoline of benchmark cruise control system；
Wherein, φ is rate of economizing gasoline, FoptFor the real vehicle oil consumption under optimization cruise control system control, FbenchmarkOn the basis of patrol
Virtual vehicle model oil consumption under control system of navigating control；Further, since the oil consumption of optimization cruise control system is also in accumulative meter
It calculates and does not reset, so as to obtain the fuel consumption per hundred kilometers of optimization cruise control system；Finally obtained rate of economizing gasoline and hundred kilometers
Oil consumption is input to human-computer interaction interface by CAN communication and is shown.
Claims (10)
1. a kind of rate of economizing gasoline real-time computing technique based on the prediction of hiding auto model, which is characterized in that the calculation method includes
Following steps:
Step 1: calculating the real vehicles oil consumption of optimization cruise control system control；
Step 2: calculating benchmark cruise control system oil consumption by virtually hiding model；
Rate of economizing gasoline is obtained Step 3: being compared with the oil consumption of step 1 and the calculated two systems of step 2.
2. a kind of rate of economizing gasoline real-time computing technique based on the prediction of hiding auto model according to claim 1, feature
It is, the specific method is as follows for the step 1:
From the power CAN message module of heat transfer agent module and vehicle obtain optimization cruise control system calculated required for
The relative distance of target lead object, relative velocity, vehicle status information i.e. this vehicle speed, engine speed, hair
Motivation torque, current shift, the gradient curvature of road ahead after obtaining these information, use mould by optimization cruise control system
Type PREDICTIVE CONTROL carries out rolling optimization, then combines needed for being calculated with huge Baudrillard gold minimal principle and dichotomy
The braking deceleration and driving moment wanted；By optimization cruise control system calculated braking deceleration and driving force in real time
Square instruction is exported by vehicle power CAN to EMS and the ESC execution of vehicle, is carried out follow the bus to control real vehicles or is patrolled
Navigation is sailed；The motor torque Yu revolving speed of real vehicles are input to oil consumption computing module after obtaining by CAN communication at this time, pass through
Instantaneous oil consumption is obtained to the lookup of oil consumption MAP table, the oil consumption of system optimizing control is then calculated by dynamic corrections.
3. a kind of rate of economizing gasoline real-time computing technique based on the prediction of hiding auto model according to claim 1, feature
It is, the specific method is as follows for the step 2:
Benchmark cruise system is obtained from the power CAN message module of heat transfer agent module and vehicle to carry out calculating required front
The relative distance of object, relative velocity, status information i.e. this vehicle speed of vehicle, engine speed, motor torque,
Current shift is calculated in instantly opposite by pid algorithm away from i.e. relative distance by benchmark cruise control system later
Braking deceleration and driving moment required for cruise travels are carried out divided by vehicle is controlled under this vehicle speed；It calculates desired
Braking deceleration and driving moment, which enter in virtually hiding auto model, controls vehicle driving, when follow the bus target changes, uses
True this vehicle parameter i.e. this vehicle speed, engine speed, motor torque, current shift and front vehicles parameter is front
The relative distance and relative velocity of vehicle and this vehicle reset virtual vehicle model parameter and follow the bus object parameter, thus
It eliminates due to the speed cumulative errors in model error bring virtual vehicle model, the front vehicle obtained by environmental perception module
Information will be sent to real vehicles and virtual vehicle simultaneously, realize the fortune that auto model is hidden under true traffic scene
Row.
4. a kind of rate of economizing gasoline real-time computing technique based on the prediction of hiding auto model according to claim 3, feature
It is, the construction method of the virtual vehicle model is as follows:
The auto model built with Simulink, including torque and throttle opening conversion module, engine block, transmission system
Module and longitudinal dynamics module；The input of the auto model is engine demand torque and braking deceleration, is exported as hair
Motivation revolving speed and the true torque of engine.
5. a kind of rate of economizing gasoline real-time computing technique based on the prediction of hiding auto model according to claim 4, feature
It is,
In the throttle opening conversion module, what is provided due to control algolithm is demand engine moment order, needs to need
It asks engine torque command to be converted to throttle opening order to execute to engine mockup；Really turned in this module using engine
Speed tables look-up to obtain throttle opening with demand motor torque, and then adjusting throttle opening by PID turns actual engine
Square keeps up with demand motor torque；When demand engine moment is less than zero, throttle opening zero；Lookup data is by really sending out
Motivation rack data obtain, but the data of full throttle are lacked in tables of data, and full throttle operating condition is in truth
It is lower seldom to exist, so being assumed to be maximum throttle opening data with 84% throttle opening in table, there is error here；
The engine block build be the throttle opening that will be previously obtained multiplied by engine under present engine revolving speed most
Big output torque obtains the effective output torque of engine at this time, makes comparisons take with constant engine maximum output torque later
Minimum value obtains engine output torque at this time, and the engine maximum output torque under present engine revolving speed is also by starting
The maximum mean effective pressure BMEP that data obtain current time is provided in board rack data, is had obtaining engine maximum averagely
Pressure is imitated later by formula
T (Nm)=BMEP (bar) * V (L)/(4*pi*0.01)
The effective output torque of the engine under current rotating speed of vehicle is calculated, wherein V indicates engine displacement, other ginsengs
Number is substituted by real vehicle parameter；
Building for the train module is that the throttle opening obtained by engine block and speed are entered shift module
Determine that the gear at current time is imitated with corresponding transmission ratio, the true torque of engine block output and transmission ratio, fluid torque-converter
Rate is multiplied, and obtains transmission shaft driving moment divided by radius of wheel later, transmission shaft driving moment is added with braking moment, is passed
Moving axis torque is exported to longitudinal vehicle dynamic model, and is obtained engine speed by speed backstepping and carried out torque converter
It searches；Using state machine model, the instruction of upshift and downshift is determined based on speed and the two parameters of throttle opening.
6. a kind of rate of economizing gasoline real-time computing technique based on the prediction of hiding auto model according to claim 5, feature
It is, the prime formula of the longitudinal vehicle dynamic model are as follows:
Ft=Ff+Fw+Fj+Fi。
Wherein, FtFor driving force, unit N, since automobile is that neutral gear slides so it is zero, FfFor frictional resistance, unit N,
Embodying form is Ff=Mg·f；Wherein, MgFor car weight, unit N, f are coefficient of friction, FwFor the resistance of running car air
Power, unit N, the form of embodying areWherein CAFor coefficient of air resistance, vOWhen starting to slide for automobile
Speed, unit m/s, FJFor the inertia force of vehicle, expression FJ=MaP, wherein M is complete vehicle quality, and unit is
Kg, aPFor the acceleration that slides under neutral gear, unit m/s2, FIFor the gradient resistance of vehicle, unit N；The longitudinal dynamics
Module is traditional longitudinal direction of car kinetics equation, but complete vehicle quality M and gradient α are parameter to be identified, dynamic to longitudinal direction of car
Mechanics has an impact.
7. a kind of rate of economizing gasoline real-time computing technique based on the prediction of hiding auto model according to claim 6, feature
It is, the identification process of the gradient α are as follows:
By the working principle of acceleration transducer it is found that vehicle is in upward slope or descending, added by what acceleration transducer measured
Speed is actually longitudinal acceleration of the vehicle and acceleration of gravity along the sum of ramp component；
The calculation formula of the gradient are as follows:
Wherein, avFor the vehicle acceleration that speed derivation obtains, asenFor the acceleration that the acceleration transducer of vehicle measures, make the difference
Current road grade can be obtained divided by acceleration g afterwards；Since there are transmission system buffeting, there are fixed frequencies for speed signal
Shake, and shake period reduce with the increase of speed, so to speed carry out differential when, to select a week
Phase carries out differential, to carry out clipping after differential and is filtered with low-pass filter, the acceleration signal of vehicle
It is also required to carry out clipping and be filtered with low-pass filter.
8. a kind of rate of economizing gasoline real-time computing technique based on the prediction of hiding auto model according to claim 6, feature
It is, the identification process of the complete vehicle quality M are as follows:
Complete vehicle quality M is recognized using recursive least squares；
Conventional truck longitudinal dynamics equation are as follows:
Ft=Fw+mgf+mgi+ma
Wherein, FtStart since vehicle traction force data can not be directly obtained so we need to pass through for the driving force of vehicle
The driving force of machine output, passes through the true driving force for being converted to vehicle of transmission system, FwFor the air drag of vehicle driving,
Mgf be vehicle driving rolling resistance, f be vehicle coefficient of rolling resistance, mgi be vehicle grade resistance, i be the gradient just
String value, ma are the acceleration resistance of vehicle；
It is changed into recurrence least square format, can obtains:
γ (k)=P (k-1) a_e (k) [a_e (k) P (k-1) a_e (k)+μ (k)]-1
Wherein, e is process white noise, and above formula is re-started transformation, can be obtained:
Ftw=θ a_e+e
Wherein,Representing system output quantity, θ=m represents parameter to be identified, a_e=gf+gi+a,
Represent observable data vector；
According to the principle of least square, the least square recursive formula of system can be obtained are as follows:
γ (k)=P (k-1) a_e (k) [a_e (k) P (k-1) a_e (k)+μ (k)]-1
P (k)=μ (k)-1[I-γ(k)a_e(k)]P(k-1)
Wherein, μ (k) is the forgetting factor at kth moment, and γ (k) is the gain matrix at k moment, Ftw(k) system at k moment is indicated
Input quantity,The quality that the expression k moment recognizes, in Multistage Recursive Least-Squares identification,It is preset with γ (k) needs
Initial value, I indicate that unit matrix, P (k) indicate the excessive matrix at k moment.
9. a kind of rate of economizing gasoline real-time computing technique based on the prediction of hiding auto model according to claim 2, feature
Be, using the oil consumption model oil consumption calculate detailed process is as follows:
The method that oil consumption model tables look-up to engine consumption MAP using engine speed and torque, but MAP table is into mistake
Engine rig test static demarcating, need to be modified it by the true fuel consumption data of fuel consumption meter reach dynamic compensate.
Wherein FinsTo add up oil consumption before the real vehicle amendment under optimization cruise control system or the control of benchmark cruise control system,It indicates the instantaneous oil consumption found out by engine speed and torque, integrates available accumulative oil consumption, pass through later
Amendment obtains revised oil consumption；
Ffinal=aFins 2+b·Fins+c
Formula is correction function, FfinalIndicate that the real vehicle under optimization cruise control system or the control of benchmark cruise control system is repaired
Just add up oil consumption, a, b afterwards, c is correction formula parameter.
10. a kind of rate of economizing gasoline real-time computing technique based on the prediction of hiding auto model according to claim 1, feature
It is, detailed process is as follows for the step 3:
It, can be with compared with calculated benchmark cruise control system oil consumption carries out once with the every 1km of optimization cruise control system oil consumption
Optimization cruise control system is obtained to compare the rate of economizing gasoline of benchmark cruise control system；
Wherein, φ is rate of economizing gasoline, FoptFor the real vehicle oil consumption under optimization cruise control system control, FbenchmarkOn the basis of cruise control
Virtual vehicle model oil consumption under system control processed；Further, since the oil consumption of optimization cruise control system also in cumulative calculation and
It does not reset, so as to obtain the fuel consumption per hundred kilometers of optimization cruise control system；Finally obtained rate of economizing gasoline and fuel consumption per hundred kilometers
Human-computer interaction interface is input to by CAN communication to be shown.
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| CN116644865B (en) * | 2023-07-27 | 2023-10-20 | 中汽信息科技(天津)有限公司 | Commercial vehicle fuel consumption prediction method, electronic equipment and storage medium |
| CN117664601A (en) * | 2024-01-31 | 2024-03-08 | 中汽研汽车检验中心（天津）有限公司 | Method and system for testing and evaluating energy-saving effect of automobile predictive cruising technology |
| CN117664601B (en) * | 2024-01-31 | 2024-05-07 | 中汽研汽车检验中心（天津）有限公司 | Method and system for testing and evaluating energy-saving effect of automobile predictive cruising technology |
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