CN105857312A - Method for optimizing speed running of highway heavy truck - Google Patents

Abstract

The invention discloses a method for optimizing speed of a highway heavy truck. The method comprises the following steps: establishing a longitudinal kinetic model of a vehicle, establishing an engine model of the vehicle, and designing a nonlinear model predication controller. A model predication control strategy is adopted, the running fuel economy of the highway heavy truck and restraint of a physical execution mechanism are taken into consideration, a nonlinear model predication control method is applied for optimization so as to obtain the optimal engine torque under current-stage road information, so that the vehicle speed with optimal fuel economy is obtained; according to the requirement of a driver on freight timeliness, the efficiency coefficient of the nonlinear model predication controller is set, so that the relation between the freight timeliness and the fuel economy is balanced, not only can the fuel consumption of the highway heavy truck be effectively reduced, but also the freight timeliness can be ensured, energy consumption is reduced, and emission of greenhouse gases is reduced.

Description

A kind of highway heavy truck speed travels optimization method

Technical field

The present invention relates to a kind of method improving highway heavy truck fuel economy, a kind of highway weight Type card vehicle speed travels optimization method.

Background technology

Automobile is bringing conveniently with simultaneously efficiently, brings huge also to countries in the world energy supply and environmental conservation Pressure.Goods transport is the core of global economy operating, and the demand of highway goods transportation increases year by year.But road traffic Transport account for the consumption of global energy and the discharge significant proportion of greenhouse gases, constitute about that global energy consumes 26%, and high The goods transport of speed highway is again the principal mode of Road Transportation.Therefore, substantial amounts of correlational study is devoted to reduce public affairs at a high speed The fuel oil consumption of road heavy truck, to improve the fuel economy of Road Transportation.Heavy in order to reduce highway further The fuel oil consumption of truck, the present invention carries out speed and travels optimization the heavy truck of highway driving.

Speed-optimization control strategy currently for vehicle mainly has cruise and adaptive learning algorithms both at home and abroad.Constant speed is patrolled Although the speed of vehicle can be fixed on particular value by boat, make vehicle remain a constant speed traveling, reduce fuel oil to a certain extent The effect consumed, the optimal fuel-economy speed being set in the case of present road but speed but differs, and the merit of cruise The most single can there is also certain limitation.Adaptive learning algorithms is to grow up on the basis of conventional truck cruise A kind of driver assistance system, can by detection vehicle status information (information such as gear, speed) adjust speed automatically, Thus ensure safe distance.But highway driving vehicle is relatively fewer, and high capacity waggon should travel at right side low speed carriage way, Relate to the situation of car, gearshift is less relative to urban road.Adaptive learning algorithms is more suitable for the most intensive riding of traffic flow Vehicle, by the judgement of the transport condition of front truck comes the travel speed of decision-making vehicle, and highway heavy truck travels Time the most sparse front truck of wagon flow less, it can be more desirable to according to current road information come decision-making go out optimum fuel-economy speed. Carry out the speed of highway heavy truck travelling optimization, according to car so this paper presents a kind of method based on PREDICTIVE CONTROL Present road information and driver's demand ageing to shipping, during optimization optimal fuel economy motor torque with Reduce the fuel oil consumption of vehicle.

Summary of the invention

A kind of method that the invention provides highway heavy truck speed-optimization, uses the strategy of Model Predictive Control, it is considered to The fuel economy of highway heavy truck traveling and the constraint of physics actuator, the side of application Nonlinear Model Predictive Control Method optimization obtains the optimal engine torque under current generation road information, thus obtains the car speed that fuel economy is optimal, And according to driver's requirement ageing to shipping, the timeliness coefficient of Nonlinear Model Predictive Control device can be configured, And then balancing shipping timeliness and fuel-economy relation between the two, the fuel oil that both can effectively reduce highway heavy truck disappears Consumption can guarantee that again the ageing of shipping, and energy efficient reduces the discharge of greenhouse gases.

The purpose of the present invention is achieved through the following technical solutions:

A kind of method of highway heavy truck speed-optimization, comprises the following steps:

Step one, set up the Longitudinal Dynamic Model of vehicle: ignore the axle load transfer of antero posterior axis, with the one degree of freedom modeling simplified Characterize the longitudinal dynamics of vehicle；

Step 2, set up the engine mockup of vehicle: gathering lot of experimental data, the fuel oil setting up electromotor consumes numerical model, In order to represent the relation between fuel consumption and motor torque, the engine speed in the electromotor unit interval；

Step 3, Nonlinear Model Predictive Control device design: based on described step one set up longitudinal vehicle dynamic model and The engine mockup that step 2 is set up, the design Nonlinear Model Predictive Control device with constrained consideration Diesel Engine Fuel Economy, Current road information and vehicle self speed are input in gamma controller, utilize model predictive control method prognoses system Following be dynamically optimized simultaneously, decision-making goes out the current optimum torque of electromotor, and exports to Vehicular system, makes vehicle with Excellent fuel-economy speed travels.

The invention have the benefit that

1. the present invention is by road information and the collection of self speed, the motor torque that reasonably optimization fuel-economy is optimum, Significantly reduce the fuel oil consumption of the heavy truck of running on expressway.

Alleviate the most to a certain extent driver driving burden, directly motor torque is controlled due to controller thus Changing the speed of vehicle, so driver is not required to operate throttle and brake pedal in the process, and highway is big Part road conditions are straight line, and steering wheel only need to carry out the rectification in current direction.But when emergency occurs, driver still may be used Vehicle is controlled by brake pedal.

3. according to three-dimensional map and the engine air throttle of engine air throttle aperture, engine output torque and engine speed The three-dimensional map of aperture, engine speed and fuel consumption carries out interpolation fitting to data, draw engine output torque, Numerical relation between engine output torque and fuel consumption three, sets up the perfect number that heavy duty truck engine fuel oil consumes Value model and the universal characteristic curve of electromotor.

Accompanying drawing explanation

Fig. 1 is vehicle force analysis schematic diagram；

Fig. 2 is engine torque vs. engine rotating speed-throttle opening map；

Fig. 3 is fuel consumption-engine speed-throttle opening map；

Fig. 4 is fuel consumption-engine speed-engine torque matching map；

Fig. 5 is universal characteristic curve of engine；

Fig. 6 is fuel oil total amount consumed simulation comparison figure；

Fig. 7 is Vehicle Speed simulation comparison figure；

Fig. 8 is vehicle engine torque simulation comparison figure.

Detailed description of the invention

The invention provides a kind of highway heavy truck speed and travel the method optimized, the method includes following step:

Step one, for the ease of to the analysis of Vehicular system and control, setting up longitudinal direction of car kinetic simulation according to Newton's second law Type, ignores the axle load transfer of antero posterior axis, characterizes the longitudinal dynamics of vehicle with the one degree of freedom modeling simplified, and such as Fig. 1, it moves Mechanical equation is:

$m\stackrel{\·}{v}=F_{engine}-F_{grad}-F_{rolling}-F_{air}---\left(1\right)$

Wherein, m is vehicle mass, units/kg；V is vehicular longitudinal velocity, unit m/s；F_engine、F_grad、F_rolling、 F_airBeing the engine traction of vehicle, road grade resistance, resistance to rolling and air drag respectively, unit is all N.

$F_{engine}=\frac{T_t{i}_g{i}_0{\mathrm{\η}}_t}{r}---\left(2\right)$

Wherein, T_tFor motor torque, unit Nm；i_gFor transmission for vehicles gear ratio；i₀For vehicle main retarder gear ratio； η_tIt it is the transmission efficiency of car load power train；R is the radius of wheel, and unit is m.

F_grad=mg sin (θ) (3)

Wherein, g is acceleration of gravity, unit m/s²；θ is road grade, unit rad.

F_rolling=mgC_r cos(θ) (4)

Wherein, C_rRepresent coefficient of rolling resistance.

$F_{air}=\frac{1}{2}{\mathrm{\ρAC}}_D{v}^2---\left(5\right)$

Wherein, C_DFor coefficient of air resistance；ρ is atmospheric density, units/kg/m³；A is vehicle front face area, unit m²； V is vehicular longitudinal velocity, unit m/s.

In sum, the longitudinal dynamics equation of vehicle can be to be expressed as form:

$m\stackrel{\·}{v}=\frac{T_t{i}_g{i}_0{\mathrm{\η}}_t}{r}-mgsin\left(\mathrm{\θ}\right)-{\mathrm{mgC}}_{r}cos\left(\mathrm{\θ}\right)-\frac{1}{2}{\mathrm{\ρAC}}_D{v}^2---\left(6\right)$

Step 2, set up the engine mockup of vehicle: gathering lot of experimental data, the fuel oil setting up electromotor consumes numerical model, In order to represent the relation between fuel consumption and motor torque, the engine speed in the electromotor unit interval；

For the fuel oil consumption of Accurate Analysis vehicle, the precise fuel setting up heavy truck diesel engine consumes numerical model.Extract certain The motor torque of money heavy truck diesel engine, engine speed and throttle opening three-dimensional map, such as Fig. 2, and fuel oil consumption The three-dimensional map of rate, engine speed and throttle opening, such as Fig. 3.What the numerical model of engine fuel consumption represented is diesel oil The relation between fuel consumption and motor torque, engine speed in the machine unit interval.

Owing to two diesel engine characteristics map of Fig. 2 and Fig. 3 all comprise engine air throttle aperture, so can be to the number of two map Carry out linear interpolation according in MATLAB by interp1 function, eliminate total throttle opening, recycle MATLAB work The data of tool case cftool motor torque, engine speed and fuel consumption to integrating out are fitted, and obtaining precision is 10-⁶ Normalization fuel consumption and motor torque, the polynomial function of engine speed:

f_fuelrate(n, T)=p₀₀+p₁₀n+p₀₁T+p₂₀n²+p₁₁nT+p₀₂T²+p₂₁n²T+p₁₂nT²+p₀₃T³ (7)

The fitting parameter that wherein MATLAB workbox cftool draws is as shown in table 1:

Table 1 engine fuel consumes numerical model fitting parameter

Fitting parameter	Numerical value
		p00	0.002892
p10	0.00209
		p01	0.001245
p20	0.0005709
		p11	0.0009704
p02	-0.0004742
		p21	0.0002821
p12	-0.0002978
		p03	-7.293e-005

According to the data of the motor torque integrated out, engine speed and fuel consumption, draw fuel consumption and turn with electromotor Square, the three-dimensional map of engine speed, as shown in Figure 4.The engine fuel obtained is consumed map and carries out the projection of x-y plane, I.e. can get the universal characteristic curve of engine of heavy truck diesel engine, as shown in Figure 5.

Show that the fuel oil of electromotor consumes numerical model, in the case of the engine speed and motor torque of known any time, The fuel consumption of current time and the fuel oil total amount consumed in the unit interval can be tried to achieve easily.

Step 3, Nonlinear Model Predictive Control device design: based on the longitudinal vehicle dynamic model set up in step one and step The fuel oil set up in two consumes numerical model, the design non-linear mould predictive with the constrained actual driving situation of consideration highway Controller, according to self speed of current road information and vehicle, utilizes the following dynamic of model predictive control method prognoses system, Being optimized, decision-making goes out the motor torque of optimum, and exports to Vehicular system, so that vehicle obtains current optimal combustion simultaneously Oil economic pace.

The design of the Nonlinear Model Predictive Control device in above-mentioned steps three comprises the following steps:

(1) control problem describes:

When carrying out highway heavy truck travel speed and optimizing, the present invention chooses the torque Tt of electromotor as control variable, i.e. U=T_t, choose longitudinal speed of vehicle as quantity of state, i.e. x=v.In order to meet the fuel-economy of vehicle during speed-optimization Property and ageing, the present invention uses the method for Model Predictive Control to be optimized vehicle engine torque, thus reach to vehicle speed The purpose that degree is optimized.Longitudinal dynamics equation according to vehicle, arranges the forecast model used during drawing optimization, as follows Shown in:

$\stackrel{\·}{v}=\frac{T_t{i}_g{i}_0{\mathrm{\η}}_t}{mr}-gsin\left(\mathrm{\θ}\right)-{\mathrm{gC}}_{r}cos\left(\mathrm{\θ}\right)-\frac{{\mathrm{\ρAC}}_D}{2m}{v}^2---\left(8\right)$

The concrete meaning of the parameters in formula is described by step 2, is not repeating at this.According to starting Machine fuel oil consumption models, and the parameter after normalization is substituted into, arrangement draws the energy consumption model during optimization, as follows:

f_fuelrate(n, T)=0.002892+0.00209n+0.001245T+0.0005709n²+0.0009704nT- 0.0004742T²+0.0002978n²T-0.0002978nT²+7.293e^-5T³ (9)

Owing to engine speed and car speed also exist following relation:

$\left\{\begin{array}{c}n=\frac{{\mathrm{\ω}}_e}{2\mathrm{\π}}\×60\\ {\mathrm{\ω}}_e=\frac{i_g{i}_0}{r}v\end{array}\right.---\left(10\right)$

Wherein, n is engine speed, unit r/min, ω_eFor electromotor angular velocity unit, rad/s.

So fuel consumption and engine speed, the functional relation of motor torque, fuel consumption and vehicle can be changed into Speed, the functional relation of engine speed.

Highway heavy truck speed-optimization so far can be organized into following form:

$\begin{array}{cc}\underset{u}{min}& J=\underset{i=1}{\overset{N}{\Σ}}(f_{fuelrate}\·\mathrm{\Δ}t)\end{array}---\left(11\right)$

s.t.

T_{t_min}≤T_t≤T_{t_max} (12)

v_min≤v≤v_max (13)

$s\≥s_{max}-\frac{\mathrm{\κ}}{100}(s_{max}-s_{\min })---\left(14\right)$

Formula (11) is the object function of highway heavy truck speed-optimization, pre-during wherein N is model predictive control method Surveying step-length, Δ t is the duration of prediction time domain each step forward prediction, and the product of fuel consumption step each with prediction step duration enters Row N step is cumulative, and makes accumulated value minimum by optimized algorithm, thus it is minimum, the most directly to reach to predict that time domain fuel oil consumes Reflect the fuel economy during speed-optimization；Formula (12) is to the constraint of motor torque during optimizing, owing to sending out The restriction of motivation build-in attribute is so there is the restriction of maximum and minima, wherein T in torque_minAnd T_maxIt is motor torque respectively The minima that can reach and maximum, unit N；Formula (13) is to heavy truck restriction of speed when highway driving, According to " freeway traffic regulation way ", goods stock should travel at slow lane, speed limit 60km/h 100km/h, wherein v_min And v_maxThe minimum and maximum travel speed of vehicle, unit m/s respectively；Formula (14) is the timeliness constraint travelling vehicle, balance Goods haulage time and fuel oil consume relation between the two, if merely vehicle can be allowed to travel in order to reduce fuel oil consumption Slow as far as possible, but this is the most irrational to goods transport, it is likely that the Late delivery of goods can be caused, so should drop The fuel oil consumption that low vehicle travels, ensures the ageing of goods transport again, and in formula (14), the expression formula of each variable is as follows:

S=v (N Δ t) (15)

Wherein, in s is prediction time domain, vehicle travels the distance travelled in prediction time domain, unit m with present speed；

s_min=v_min·(N·Δt) (16)

Wherein, s_minBe that in predicting time domain, vehicle travels the distance travelled in prediction time domain with the minimum speed limited, i.e. vehicle exists The minimum range that prediction time domain can travel, unit m；

s_max=v_max·(N·Δt) (17)

Wherein, s_maxBe that in predicting time domain, vehicle travels the distance travelled in prediction time domain with the maximal rate limited, i.e. vehicle exists The ultimate range that prediction time domain can travel, unit m；

The proportionality coefficient that κ is manual control in formula (14), can optimum fuel oil consumption and shortest time arrive appointed place it Between carry out manual control, the κ the biggest fuel oil consumption the lowest time arrived at is the longest, on the contrary fuel oil consume the high time short.

(2) control problem solves:

During highway heavy truck speed-optimization, the present invention utilizes in MATLAB fmincon function to designed Nonlinear Model Predictive Control device solves, and the parameter of controller is as shown in table 2:

Table 2 Nonlinear Model Predictive Control device parameter

Parameter	Tt_min,Tt_max	vmin,vmax	N
				Value	-50,650	(60/3.6,100/3.6)	16

Owing to inevitably there is the interference of external environment in actual driving conditions, it was predicted that model only only accounts for the vertical of vehicle To kinetics, do not account for the impact of external interference in driving conditions.Therefore, during optimizing, if directly will calculate To N number of velocity amplitude of optimum motor torque sequence all act on control vehicle, it will cause model mismatch phenomenon, excellent The speed effect changed is deteriorated.Therefore, in actual solution procedure, the thought of our combination model PREDICTIVE CONTROL, by each moment First value of the optimal engine torque sequence obtained acts on vehicle, it is achieved rolling optimization, thus reduces other interference factors Impact.

(3) control algolithm simulating, verifying

In order to verify the functional, in MATLAB/SIMULINK of designed highway heavy truck speed-optimization scheme Build Nonlinear Model Predictive Control device, and carry out associative simulation together with high accuracy truck simulation software TRUCKSIM, TRUCKSIM provides high-precision card vehicle model as controlled device, and farthest the truck in simulating reality situation travels shape State.

Under above-mentioned union simulation platform, being simulated highway operating mode emulation experiment, in the gradient 0.03753, highway is straight Line travels 300m, and to arrange vehicle initial velocity be 70km/h, and controller timeliness coefficient κ is chosen for 70；In order to verify intuitively The minimizing that when highway heavy truck travels under Nonlinear Model Predictive Control device effect, fuel oil consumes, in identical road work There is no the effect of controller under condition, allow heavy truck travel with constant speed 70km/h, will have controller action and there is no controller action Under simulation result contrast, such as Fig. 68.

Can be seen that fuel oil when significantly reducing heavy truck highway driving under the effect of controller disappears from simulation result Consumption, from fig. 6 it can be seen that fuel oil total amount consumed under control of the controller is less than the situation not applying to control, oil consumption is divided Not Wei 0.035031kg and 0.038101kg, fuel-economizing about 7.35%, and have the speed of controller action under this kind of operating mode all the time Higher than the situation of controller useless, also demonstrate the ageing of designed gamma controller, it was demonstrated that the controller designed by The effectiveness of speed-optimization when highway heavy truck is travelled.

Claims (5)

1. the method for a highway heavy truck speed-optimization, it is characterised in that comprise the following steps:

Step one, set up longitudinal vehicle dynamic model；

Step 2, set up the engine mockup of vehicle: gathering experimental data, the fuel oil setting up electromotor consumes numerical model, in order to represent the relation between fuel consumption and motor torque, the engine speed in the electromotor unit interval；

Step 3, Nonlinear Model Predictive Control device design: the engine mockup that the longitudinal vehicle dynamic model set up based on described step one and step 2 are set up, the design Nonlinear Model Predictive Control device with constrained consideration Diesel Engine Fuel Economy, current road information and vehicle self speed are input in gamma controller, utilize the following dynamic of model predictive control method prognoses system, it is optimized simultaneously, decision-making goes out the current optimum torque of electromotor, and export to Vehicular system, make vehicle travel with optimum fuel-economy speed.

The method of a kind of highway heavy truck speed-optimization the most as claimed in claim 1, it is characterised in that the longitudinal vehicle dynamic model that described step one is set up is:

Wherein, m is vehicle mass, units/kg；V is vehicular longitudinal velocity, unit m/s；T_tFor motor torque, unit Nm；i_gFor transmission for vehicles gear ratio；i₀For vehicle main retarder gear ratio；η_tIt it is the transmission efficiency of car load power train；R is the radius of wheel, and unit is m；G is acceleration of gravity, unit m/s²；θ is road grade, unit rad；C_rRepresent coefficient of rolling resistance；C_DFor coefficient of air resistance；ρ is atmospheric density, units/kg/m³；A is vehicle front face area, unit m²。

The method of a kind of highway heavy truck speed-optimization the most as claimed in claim 1, it is characterised in that described step 2 is set up the engine mockup of vehicle and is:

f_fuelrate(n, T)=0.002892+0.00209n+0.001245T+0.0005709n²+0.0009704nT-

0.0004742T²+0.0002978n²T-0.0002978nT²+7.293e^-5T³

The method of a kind of highway heavy truck speed-optimization the most as claimed in claim 3, it is characterised in that described step 2 is set up the detailed process of the engine mockup of vehicle and is:

Extract the motor torque of heavy truck diesel engine, engine speed and throttle opening three-dimensional map, and the three-dimensional map of fuel consumption, engine speed and throttle opening；

Two Zhang San are tieed up the data of map in MATLAB, carries out linear interpolation by interp1 function, eliminate total throttle opening, the data of recycling MATLAB workbox cftool motor torque, engine speed and fuel consumption to integrating out are fitted, and obtaining precision is 10^-6Normalization fuel consumption and motor torque, the polynomial function of engine speed；

Data according to the motor torque integrated out, engine speed and fuel consumption, draw fuel consumption and motor torque, the three-dimensional map of engine speed, the engine fuel obtained is consumed map and carries out the projection of x-y plane, i.e. can get the universal characteristic curve of engine of heavy truck diesel engine.

The method of a kind of highway heavy truck speed-optimization the most as claimed in claim 1, it is characterised in that the design of described step 3 Nonlinear Model Predictive Control device comprises the following steps:

(1) control problem describes:

Highway heavy truck speed-optimization is organized into following form:

s.t.

T_{t_min}≤T_t≤T_{t_max} (12)

v_min≤v≤v_max (13)

Described formula (11) is the object function of highway heavy truck speed-optimization, the prediction step during wherein N is model predictive control method, and Δ t is the duration of prediction time domain each step forward prediction；

Described formula (12) is to the constraint of motor torque, wherein T during optimizing_minAnd T_maxIt is the minima that can reach of motor torque and maximum, unit N respectively；

Described formula (13) is to the heavy truck restriction of speed, wherein v when highway driving_minAnd v_maxIt is respectively the minimum and maximum travel speed of vehicle, unit m/s；

Described formula (14) is the timeliness constraint travelling vehicle, in formula: s=v (N Δ t)；s_min=v_min·(N·Δt)；s_max=v_max·(N·Δt)；κ is the proportionality coefficient of manual control；

(2) control problem solves.