CN105857312B - A kind of highway heavy truck speed travels optimization method - Google Patents

A kind of highway heavy truck speed travels optimization method Download PDF

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Publication number
CN105857312B
CN105857312B CN201610356264.XA CN201610356264A CN105857312B CN 105857312 B CN105857312 B CN 105857312B CN 201610356264 A CN201610356264 A CN 201610356264A CN 105857312 B CN105857312 B CN 105857312B
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engine
speed
vehicle
heavy truck
optimization
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CN201610356264.XA
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CN105857312A (en
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郭洪艳
郝宁峰
王秋
陈虹
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吉林大学
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    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W30/00Purposes 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, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/18Propelling the vehicle
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W10/00Conjoint control of vehicle sub-units of different type or different function
    • B60W10/04Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
    • B60W10/06Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of combustion engines
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/02Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
    • B60W40/06Road conditions
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/10Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
    • B60W40/105Speed
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W2520/00Input parameters relating to overall vehicle dynamics
    • B60W2520/10Longitudinal speed
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2552/00Input parameters relating to infrastructure
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W2710/00Output or target parameters relating to a particular sub-units
    • B60W2710/06Combustion engines, Gas turbines
    • B60W2710/0666Engine torque
    • Y02T10/52

Abstract

The invention discloses a kind of methods of highway heavy truck speed-optimization, include the following steps:The Longitudinal Dynamic Model for establishing vehicle, engine mockup, the Nonlinear Model Predictive Control device of establishing vehicle design.The present invention uses the strategy of Model Predictive Control, consider the fuel economy of highway heavy truck traveling and the constraint of physics executing agency, optimize to obtain the optimal engine torque under current generation road information using the method for Nonlinear Model Predictive Control, so as to obtain the best car speed of fuel economy, it and can be according to requirement of the driver to shipping timeliness, the timeliness coefficient of Nonlinear Model Predictive Control device is configured, and then balance the relationship of shipping timeliness and fuel-economy between the two, not only it can effectively reduce the fuel consumption of highway heavy truck but also can guarantee the timeliness of shipping, saving energy consumption reduces the discharge of greenhouse gases.

Description

A kind of highway heavy truck speed travels optimization method

Technical field

The present invention relates to a kind of method for improving highway heavy truck fuel economy, specifically a kind of high speeds Highway heavy truck speed travels optimization method.

Background technology

Automobile is also brought while bringing convenient and quick to countries in the world energy supply and environmental protection Huge pressure.Cargo transport is the core of global economy operating, and the demand of highway goods transportation increases year by year.However road The transport of road traffic accounts for the consumption of global energy and the discharge significant proportion of greenhouse gases, accounts about global energy consumption 26%, and the cargo transport of highway is the principal mode of Road Transportation.Therefore, a large amount of correlative study is dedicated to The fuel consumption of highway heavy truck is reduced, to improve the fuel economy of Road Transportation.In order to further reduce The fuel consumption of highway heavy truck, the present invention carry out the heavy truck of highway driving speed traveling optimization.

Mainly there are cruise and adaptive learning algorithms currently for the speed-optimization control strategy of vehicle both at home and abroad. Although the speed of vehicle can be fixed on particular value by cruise, vehicle is made to remain a constant speed traveling, is reached to a certain extent The effect of fuel consumption, the best fuel-economy speed being set in the case of present road but speed but differs are reduced, and is determined The fast function of cruising is excessively single, and there is also certain limitations.Adaptive learning algorithms are the bases in conventional truck cruise A kind of driver assistance system to grow up on plinth, can be by detecting the status information (information such as gear, speed) of vehicle Automatically adjustment speed, so as to ensure safe distance.However highway driving vehicle is relatively fewer, and high capacity waggon should go Sail in right side low speed carriage way, be related to vehicle, gearshift situation with respect to urban road it is less.Adaptive learning algorithms are more suitable for handing over Through-flow relatively intensive passenger vehicle, by the judgement of the transport condition to front truck come the travel speed of decision vehicle, and The relatively sparse front truck of wagon flow is less when driving for highway heavy truck, it can be more desirable to according to current road information come decision Go out optimal fuel-economy speed.So this paper presents it is a kind of based on the method for PREDICTIVE CONTROL to highway heavy truck Speed carries out traveling optimization, and according to the demand of vehicle present road information and driver to shipping timeliness, optimization is best Fuel economy when motor torque to reduce the fuel consumption of vehicle.

Invention content

The present invention provides a kind of method of highway heavy truck speed-optimization, using the plan of Model Predictive Control Slightly, consider the fuel economy of highway heavy truck traveling and the constraint of physics executing agency, it is pre- using nonlinear model The method of observing and controlling optimizes to obtain the optimal engine torque under current generation road information, best so as to obtain fuel economy Car speed, and can be according to requirement of the driver to shipping timeliness, to the timeliness of Nonlinear Model Predictive Control device Coefficient is configured, and then balances the relationship of shipping timeliness and fuel-economy between the two, both can effectively reduce highway The fuel consumption of heavy truck can guarantee the timeliness of shipping again, and saving energy consumption 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, includes the following steps:

Step 1: establish the Longitudinal Dynamic Model of vehicle:Ignore the axle load transfer of antero posterior axis, with simplified single-degree-of-freedom Model characterizes the longitudinal dynamics of vehicle;

Step 2: establish the engine mockup of vehicle:Lot of experimental data is acquired, establishes the fuel consumption numerical value of engine Model, to represent the relationship between fuel consumption rate and motor torque, engine speed in the engine unit interval;

Step 3: Nonlinear Model Predictive Control device designs:The longitudinal direction of car kinetic simulation established based on the step 1 The engine mockup that type and step 2 are established, the nonlinear model for designing Diesel Engine Fuel Economy the considerations of with Constrained are pre- Controller is surveyed, current road information and vehicle itself speed is input in gamma controller, utilizes Model Predictive Control The following dynamic of method forecasting system is carried out at the same time optimization, and decision goes out the current optimum torque of engine, and exports to vehicle system System, makes vehicle be travelled with optimal fuel-economy speed.

Beneficial effects of the present invention are:

By the acquisition to road information and itself speed, 1. reasonably optimization fuel-economy is optimal starts the present invention Machine torque significantly reduces the fuel consumption of the heavy truck of running on expressway.

2. the driving burden of driver is alleviated to a certain extent, since controller directly controls motor torque The speed so as to change vehicle is made, so driver is not required to operate throttle and brake pedal in the process, and high Fast highway major part road conditions are straight line, and the correction when front direction need to be only carried out to steering wheel.But it when emergency occurs, drives The person of sailing still can brake pedal vehicle is controlled.

3. according to the three-dimensional map of engine air throttle aperture, engine output torque and engine speed and engine machine The three-dimensional map of throttle opening, engine speed and fuel consumption rate carries out interpolation fitting to data, show that engine exports Numerical relation between torque, engine output torque and fuel consumption rate three, establishes heavy duty truck engine fuel consumption Exact numerical model and engine universal characteristic curve.

Description of the drawings

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 rate-engine speed-throttle opening map;

Fig. 4 is fitted map for fuel consumption rate-engine speed-engine torque;

Fig. 5 is universal characteristic curve of engine;

Fig. 6 is fuel consumption total amount simulation comparison figure;

Fig. 7 is Vehicle Speed simulation comparison figure;

Fig. 8 is vehicle engine torque simulation comparison figure.

Specific embodiment

The present invention provides a kind of method of highway heavy truck speed traveling optimization, this method includes following Step:

Step 1: for the ease of analysis and control to Vehicular system, longitudinal direction of car is established according to Newton's second law and is moved Mechanical model ignores the axle load transfer of antero posterior axis, with the longitudinal dynamics of simplified one degree of freedom modeling characterization vehicle, such as Fig. 1, Its kinetics equation is:

Wherein, m is vehicle mass, units/kg;V is vehicular longitudinal velocity, unit m/s;Fengine、Fgrad、Frolling、Fair It is engine traction, road grade resistance, rolling resistance and the air drag of vehicle respectively, unit is all N.

Wherein, TtFor motor torque, unit Nm;igFor transmission for vehicles gearratio;i0It is driven for vehicle main retarder Than;ηtIt is the transmission efficiency of vehicle power train;R is the radius of wheel, unit m.

Fgrad=mg sin (θ) (3)

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

Frolling=mgCr cos(θ) (4)

Wherein, CrRepresent coefficient of rolling resistance.

Wherein, CDFor 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 conclusion the longitudinal dynamics equation of vehicle can be expressed as form:

Step 2: establish the engine mockup of vehicle:Lot of experimental data is acquired, establishes the fuel consumption numerical value of engine Model, to represent the relationship between fuel consumption rate and motor torque, engine speed in the engine unit interval;

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

Since Fig. 2 and Fig. 3 two open diesel engine machine characteristic map comprising engine air throttle aperture, so can be to two map Data linear interpolation is carried out by interp1 functions in MATLAB, eliminate shared throttle opening, recycle MATLAB Tool box cftool is fitted the data of motor torque, engine speed and fuel consumption rate integrated out, obtains essence It spends for 10-6Normalization fuel consumption rate and motor torque, engine speed polynomial function:

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

The fitting parameter that wherein MATLAB tool boxes cftool is obtained is as shown in table 1:

1 engine fuel of table 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 motor torque, engine speed and fuel consumption rate integrated out, draw fuel consumption rate with The three-dimensional map of motor torque, engine speed, as shown in Figure 4.X-y plane is carried out to obtained engine fuel consumption map Projection, you can obtain the universal characteristic curve of engine of heavy truck diesel engine, as shown in Figure 5.

The fuel consumption numerical model of engine is obtained, in the engine speed and motor torque of known any time In the case of, you can easily acquire the fuel consumption total amount in the fuel consumption rate and unit interval at current time.

Step 3: Nonlinear Model Predictive Control device designs:Based on the longitudinal vehicle dynamic model established in step 1 And the fuel consumption numerical model established in step 2, design the non-of highway practical driving situation the considerations of with Constrained Linear Model for Prediction controller, it is pre- using model predictive control method according to itself speed of current road information and vehicle The following dynamic of examining system is carried out at the same time optimization, and decision goes out optimal motor torque, and exports to Vehicular system, so as to make Vehicle obtains current best fuel-economy speed.

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

(1) control problem describes:

When carrying out the optimization of highway heavy truck travel speed, the present invention chooses the torque Tt of engine as control Variable, i.e. u=Tt, longitudinal speed of vehicle is chosen as quantity of state, i.e. x=v.In order to meet vehicle during speed-optimization Fuel economy and timeliness, the present invention optimize vehicle engine torque using the method for Model Predictive Control, so as to Achieve the purpose that optimize car speed.According to the longitudinal dynamics equation of vehicle, arrangement, which is obtained in optimization process, to be used Prediction model, it is as follows:

The concrete meaning of the parameters in formula is described in step 2, is not just being repeated herein. It is substituted into according to engine fuel consumption models, and by the parameter after normalization, arranges the energy consumption model obtained in optimization process, such as Shown in lower:

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

Due to engine speed, there is following relationships with car speed:

Wherein, n is engine speed, unit r/min, ωeFor engine angular speed unit, rad/s.

So fuel consumption rate and engine speed, the functional relation of motor torque, can be converted to fuel consumption Rate and car speed, the functional relation of engine speed.

So far highway heavy truck speed-optimization can be organized into following form:

s.t.

Tt_min≤Tt≤Tt_max (12)

vmin≤v≤vmax (13)

Formula (11) is the object function of highway heavy truck speed-optimization, and wherein N is in model predictive control method Prediction step, Δ t is the duration for predicting each step forward prediction of time domain, fuel consumption rate and each step duration of prediction step Product carries out N steps and adds up, and passing through optimization algorithm makes accumulated value minimum, minimum so as to reach prediction time domain fuel consumption, also Directly reflect the fuel economy during speed-optimization;Formula (12) is the constraint to motor torque in optimization process, Due to engine build-in attribute limitation thus torque there are the limitation of maximum value and minimum value, wherein TminAnd TmaxIt is hair respectively The attainable minimum value of motivation torque and maximum value, unit N;Formula (13) be to heavy truck in highway driving speed Limitation, according to《Freeway traffic regulation method》, goods stock should travel in slow lane, speed limit 60km/h -100km/h, Middle vminAnd vmaxThe minimum and maximum travel speed of vehicle respectively, unit m/s;Formula (14) is that the timeliness that vehicle travels is constrained, Cargo transport time and fuel consumption relationship between the two are balanced, if merely in order to reduce fuel consumption vehicle can be allowed Traveling is slow as far as possible, but this is very unreasonable to cargo transport, it is likely that the Late delivery of cargo can be caused, so The fuel consumption of vehicle traveling should be reduced, ensures the timeliness of cargo transport again, the expression formula of each variable is such as in formula (14) Shown in lower:

S=v (N Δs t) (15)

Wherein, s is to predict that vehicle is predicting the distance travelled in time domain, unit m with present speed traveling in time domain;

smin=vmin·(N·Δt) (16)

Wherein, sminIt is to predict that vehicle is predicting the distance travelled in time domain with the minimum speed traveling limited in time domain, i.e., The minimum range that vehicle can be travelled in prediction time domain, unit m;

smax=vmax·(N·Δt) (17)

Wherein, smaxIt is to predict that vehicle is predicting the distance travelled in time domain with the maximum speed traveling limited in time domain, i.e., The maximum distance that vehicle can be travelled in prediction time domain, unit m;

κ in formula (14) is the proportionality coefficient of people in order to control, can be reached in optimal fuel consumption and shortest time specified It is artificially controlled between place, the bigger fuel consumptions of κ are lower, and the time arrived at is longer, otherwise the fuel consumption high time It is short.

(2) control problem solves:

During highway heavy truck speed-optimization, the present invention is using set by fmincon function pairs in MATLAB The Nonlinear Model Predictive Control device of meter is solved, and the parameter of controller is as shown in table 2:

2 Nonlinear Model Predictive Control device parameter of table

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

Since, inevitably there are the interference of external environment, prediction model only only accounts in practical driving conditions The longitudinal dynamics of vehicle do not account for the influence of external interference in driving conditions.Therefore, in optimization process, if directly The N number of velocity amplitude of optimal motor torque sequence being calculated all is acted on into control vehicle, it will model is caused to lose With phenomenon, the speed effect of optimization is deteriorated.Therefore in practical solution procedure, the thought of our binding model PREDICTIVE CONTROLs, First value of the optimal engine torque sequence that each moment obtains is acted on into vehicle, rolling optimization is realized, so as to reduce The influence of other disturbing factors.

(3) control algolithm simulating, verifying

In order to verify the functionality of designed highway heavy truck speed-optimization scheme, in MATLAB/ Nonlinear Model Predictive Control device is built in SIMULINK, and is combined together with high-precision truck simulation software TRUCKSIM Emulation, TRUCKSIM provide high-precision truck model as controlled device, utmostly the truck in simulation reality Transport condition.

Under above-mentioned union simulation platform, simulation highway operating mode emulation experiment is carried out, in the gradient 0.03753, high speed Highway straight-line travelling 300m, and it is 70km/h to set vehicle initial velocity, controller timeliness coefficient κ is chosen for 70;In order to intuitively The reduction of the highway heavy truck fuel consumption when driving under the effect of Nonlinear Model Predictive Control device is verified, identical There is no the effect of controller under road condition, heavy truck is allowed to be travelled with constant speed 70km/h, there will be controller action and do not control Simulation result under device effect processed is compared, such as Fig. 6-8.

From simulation result it can be seen that when significantly reducing heavy truck highway driving under the action of controller Fuel consumption, from fig. 6 it can be seen that fuel consumption total amount under control of the controller is less than the situation for not applying control, Oil consumption is respectively 0.035031kg and 0.038101kg, fuel-economizing about 7.35%, and has controller action under such operating mode Speed be consistently higher than the situation of controller useless, also demonstrate the timeliness of designed gamma controller, it was demonstrated that institute The controller of design is for the validity of highway heavy truck speed-optimization when driving.

Claims (5)

  1. A kind of 1. method of highway heavy truck speed-optimization, which is characterized in that include the following steps:
    Step 1: establish longitudinal vehicle dynamic model;
    Step 2: establish the engine mockup of vehicle:Experimental data is acquired, establishes the fuel consumption numerical model of engine, is used To represent the relationship between fuel consumption rate and motor torque, engine speed in the engine unit interval;
    Step 3: Nonlinear Model Predictive Control device designs:Based on the step 1 establish longitudinal vehicle dynamic model with And the engine mockup that step 2 is established, design the non-linear mould predictive control of Diesel Engine Fuel Economy the considerations of with Constrained Current road information and vehicle itself speed is input in gamma controller, utilizes model predictive control method by device processed The following dynamic of forecasting system is carried out at the same time optimization, and decision goes out the current optimum torque of engine, and exports to Vehicular system, makes Vehicle is travelled with optimal fuel-economy speed.
  2. A kind of 2. method of highway heavy truck speed-optimization as described in claim 1, which is characterized in that the step It is rapid one establish longitudinal vehicle dynamic model be:
    Wherein, m is vehicle mass, units/kg;V is vehicular longitudinal velocity, unit m/s;TtFor motor torque, unit Nm;igFor Transmission for vehicles gearratio;i0For vehicle main retarder gearratio;ηtIt is the transmission efficiency of vehicle power train;R is the half of wheel Diameter, unit m;G is acceleration of gravity, unit m/s2;θ is road grade, unit rad;CrRepresent coefficient of rolling resistance;CDFor Coefficient of air resistance;ρ is atmospheric density, units/kg/m3;A is vehicle front face area, unit m2
  3. A kind of 3. method of highway heavy truck speed-optimization as described in claim 1, which is characterized in that the step Two engine mockups for establishing vehicle are:
    ffuelrate(n, T)=0.002892+0.00209n+0.001245T+0.0005709n2+0.0009704nT- 0.0004742T2+0.0002978n2T-0.0002978nT2+7.293e-5T3
    Wherein, T is engine output torque, unit Nm;N is engine speed, unit r/min.
  4. A kind of 4. method of highway heavy truck speed-optimization as claimed in claim 3, which is characterized in that the step Two detailed processes for establishing the engine mockup of vehicle are:
    Extract motor torque, engine speed and the throttle opening three-dimensional map and fuel consumption of heavy truck diesel engine The three-dimensional map of rate, engine speed and throttle opening;
    The data that two Zhang San are tieed up with map carry out linear interpolation in MATLAB by interp1 functions, eliminate shared air throttle Aperture recycles MATLAB tool box cftool to the number of motor torque, engine speed and fuel consumption rate integrated out According to being fitted, it is 10 to obtain precision-6Normalization fuel consumption rate and motor torque, engine speed multinomial letter Number;
    According to the data of motor torque, engine speed and fuel consumption rate integrated out, fuel consumption rate is drawn with starting Machine torque, the three-dimensional map of engine speed carry out obtained engine fuel consumption map the projection of x-y plane, you can To the universal characteristic curve of engine of heavy truck diesel engine.
  5. A kind of 5. method of highway heavy truck speed-optimization as described in claim 1, which is characterized in that the step The design of three Nonlinear Model Predictive Control devices includes the following steps:
    (1) control problem describes:
    Highway heavy truck speed-optimization is organized into following form:
    Tt_min≤Tt≤Tt_max (12)
    vmin≤v≤vmax (13)
    The formula (11) is the object function of highway heavy truck speed-optimization, and wherein N is in model predictive control method Prediction step, Δ t be predict each step forward prediction of time domain duration;
    The formula (12) is the constraint to motor torque in optimization process, wherein TminAnd TmaxIt is that motor torque can reach respectively The minimum value and maximum value arrived, unit N;
    The formula (13) is the limitation to heavy truck speed in highway driving, wherein vminAnd vmaxRespectively vehicle Minimum and maximum travel speed, unit m/s;
    The formula (14) is that the timeliness that vehicle travels is constrained, in formula:S=v (N Δs t);smin=vmin·(N·Δt); smax=vmax·(N·Δt);κ is the proportionality coefficient of people in order to control;
    (2) control problem solves.
CN201610356264.XA 2016-05-26 2016-05-26 A kind of highway heavy truck speed travels optimization method CN105857312B (en)

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CN108501955A (en) * 2018-04-20 2018-09-07 北京理工大学 A kind of distance increasing unit pressure point of maximum efficiency optimization method
CN109910890A (en) * 2019-03-19 2019-06-21 吉林大学 A kind of truck prediction energy conserving system and control method based on route topography information

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