CN109484407A - A kind of adaptive follow the bus method that electric car auxiliary drives - Google Patents
A kind of adaptive follow the bus method that electric car auxiliary drives Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/14—Adaptive cruise control
- B60W30/16—Control of distance between vehicles, e.g. keeping a distance to preceding vehicle
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W2050/0001—Details of the control system
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Abstract
The present invention provides a kind of adaptive follow the bus method that electric car auxiliary drives, and can be realized the collaboration optimization of multiple target.The described method includes: establishing according to the stability requirement of following distance and becoming headway strategy；The change headway strategy established is combined according to kinematics character of vehicle during follow the bus, it establishes using following distance error, opposite speed, this vehicle acceleration and rate of acceleration change as state variable and output variable, it is expected acceleration as control variable, adaptive follow the bus kinetic model of the front truck acceleration as interference volume；According to the adaptive follow the bus kinetic model of foundation, determine that the prediction model based on Model Predictive Control, the prediction model optimize for realizing the collaboration of multiple target indicators, the target indicator includes: economy, safety and comfort.The present invention relates to automobile technical fields.
Description
Technical field
The present invention relates to automobile technical fields, particularly relate to a kind of adaptive follow the bus method that electric car auxiliary drives.
Background technique
In recent years, it before carrying out the Study on Adaptive Control that electric car auxiliary drives, needs to solve since vehicle is expert at
During sailing the problem of vehicle security caused by the quality of vehicle-following behavior, comfort and economy.
Adaptive follow the bus is that automatic driving vehicle is most basic and most important driving scene, the quality of vehicle-following behavior are direct
Influence safety, comfort and the economy of vehicle.Although adaptive follow the bus has been carried out as the unpiloted primary stage
Commercialization, however still can not achieve multiple indexs (for example, economy, safety, comfort) in existing solution
Collaboration optimization.
Summary of the invention
The technical problem to be solved in the present invention is to provide the adaptive follow the bus methods that a kind of electric car auxiliary drives, with solution
The problem of certainly can not achieve the collaboration optimization of multiple indexs present in the prior art.
In order to solve the above technical problems, the embodiment of the present invention provides a kind of adaptive follow the bus side that electric car auxiliary drives
Method, comprising:
According to the stability requirement of following distance, establishes and become headway strategy；
The change headway strategy established is combined according to kinematics character of vehicle during follow the bus, is established with following distance
Error, opposite speed, this vehicle acceleration and rate of acceleration change are as state variable and output variable, it is expected that acceleration is made
To control variable, adaptive follow the bus kinetic model of the front truck acceleration as interference volume；
According to the adaptive follow the bus kinetic model of foundation, the prediction model based on Model Predictive Control is determined, it is described pre-
It surveys model to optimize for realizing the collaboration of multiple target indicators, the target indicator includes: economy, safety and comfort.
Further, the stability requirement according to following distance, establishing change headway strategy includes:
According to the relative velocity of this vehicle speed, Ben Che and front truck, front truck acceleration, this vehicle battery pack state-of-charge, build
It is vertical to become headway strategy.
Further, the change headway strategy is expressed as:
ddes=th·vh+d0
Wherein, ddesIndicate desired vehicle headway, vhIndicate this vehicle speed, d0The minimum safe distance of two vehicles when being static
From thIndicate headway, h1、h2、h3、h4Indicate constant coefficient, th_max、th_minRespectively indicate headway the upper limit, under
Limit, vrelIndicate the relative velocity of this vehicle and front truck, apIndicate that front truck acceleration, SOC indicate the state-of-charge of this vehicle battery pack.
Further, the kinematics character according to vehicle during follow the bus combines the change headway plan established
Slightly, it establishes and becomes using following distance error, opposite speed, this vehicle acceleration and rate of acceleration change as state variable and output
Amount, it is expected acceleration as control variable, front truck acceleration includes: as the adaptive follow the bus kinetic model of interference volume
According to kinematics character of vehicle during follow the bus, the discrete models of vehicle headway are determined:
Wherein, d indicates that practical front and back vehicle headway, k indicate k moment, TsIndicate the sampling period of discrete models, ah
Indicate the acceleration of this vehicle；
According to following distance error formula and the discrete models of the vehicle headway of determination, the discrete of following distance error is determined
Mathematical model:
Wherein, △ d indicates front and back vehicle headway error；
According to kinematics character of vehicle during follow the bus, the discrete models of relative velocity are determined:
vrel(k+1)=vrel(k)+ap(k)·Ts-ah(k)·Ts
Determine the discrete models of this vehicle acceleration:
Wherein, τ indicates that adaptive follow the bus system time constant, u indicate control variable, using the expectation acceleration of this vehicle as
Control variable；
According to the relationship between acceleration and rate of acceleration change, the discrete models of rate of acceleration change are determined:
Wherein, jhIndicate the rate of acceleration change of this vehicle；
According to the determining discrete models of following distance error, the discrete models of relative velocity, this vehicle acceleration
Discrete models, rate of acceleration change discrete models, establish and accelerated with following distance error, opposite speed, this vehicle
Degree and rate of acceleration change are as state variable and output variable, it is expected that acceleration as control variable, is accelerated with front truck
Spend as interference volume adaptive follow the bus vehicle during follow the bus kinetic model.
Further, the following distance error formula indicates are as follows:
△ d (k)=d (k)-ddes(k)
Wherein, d (k) indicates front and back vehicle headway error, and d indicates practical front and back vehicle headway, ddesIndicate desired workshop
Distance.
Further, state variable indicates are as follows: x (k)=[△ d (k), vrel(k),ah(k),jh(k)]T；
Output variable indicates are as follows: y (k)=[△ d (k), vrel(k),ah(k),jh(k)]T；
The form of the state equation of the kinetic model are as follows:
Wherein, A, B, G, C indicate coefficient matrix.
Further, coefficient matrices A, B, G, C are respectively indicated are as follows:
Further, the adaptive follow the bus kinetic model according to foundation is determined based on the pre- of Model Predictive Control
Model is surveyed, the prediction model includes: for realizing the collaboration optimization of multiple target indicators
Introduce amendment error term ex(k), according to the state equation of kinetic model, adaptive follow the bus system will be obtained in future
The predicted state at p moment:
Wherein,Indicate the state vector of prediction, U (k+m) indicates that control variable vector, m indicate that control becomes
The number of amount, W (k+p) indicate interference volume vector,Indicate coefficient matrix,U(k+m)、W
(k+p)、It respectively indicates are as follows:
Wherein,H indicates State Equation Coefficients；
Introduce amendment error term ex(k), according to the state equation of kinetic model, adaptive follow the bus system will be obtained in future
System in p moment exports predicted value:
Wherein,Indicate the system output vector of prediction,Indicate coefficient matrix,It respectively indicates are as follows:
Predicted state and system according to obtained adaptive follow the bus system at the following p moment export predicted value, determine
Performance indicator evaluation function based on Model Predictive Control, the performance indicator evaluation function as prediction model, for realizing
The collaboration of multiple target indicators optimizes.
Further, the performance indicator evaluation function based on Model Predictive Control indicates are as follows:
Wherein,Indicate that the performance indicator evaluation function based on Model Predictive Control, T representing matrix transposition, ρ indicate feature
Value matrix, Φ, R, Q indicate the coefficient of performance metrics evaluation function.
Further, the constraint condition of the performance indicator evaluation function are as follows:
Wherein, ε1、ε2、ε3、ε4、ε5For relaxation factor, v# min、v# maxFor on the constraint lower bound and constraint of each relevant variable
The coefficient of relaxation on boundary, the value of # are △ d, vrel、ah、jh, u, △ dmax、△dminRespectively indicate the maximum value, most of following distance error
Small value, vrel-max、vrel-minRespectively indicate maximum value, the minimum value of opposite speed, ah-max、ah-minRespectively indicate this vehicle acceleration
Maximum value, minimum value, jh-max、jh-minRespectively indicate maximum value, the minimum value of rate of acceleration change, umax、uminIt respectively indicates
Control maximum value, the minimum value of variable.
The advantageous effects of the above technical solutions of the present invention are as follows:
In above scheme, according to the stability requirement of following distance, establishes and become headway strategy, to guarantee S-EATC system
Stability；The change headway strategy established is combined according to kinematics character of vehicle during follow the bus, is established with workshop
Away from error, opposite speed, this vehicle acceleration and rate of acceleration change as state variable and output variable, it is expected acceleration
As control variable, adaptive follow the bus kinetic model of the front truck acceleration as interference volume；According to the adaptive follow the bus of foundation
Kinetic model, determine the prediction model based on Model Predictive Control, the prediction model for realizing economy, safety and
The collaboration of comfort index optimizes；In this way, improving vehicle on the basis of guaranteeing passenger comfort and traveling economy
Safety and follow the bus realize the collaboration optimization of multiple target.
Detailed description of the invention
Fig. 1 is the flow diagram for the adaptive follow the bus method that electric car provided in an embodiment of the present invention auxiliary drives；
Fig. 2 is provided in an embodiment of the present invention special based on the S-EATC system longitudinal dynamics that headway strategy is built are become
Property schematic diagram；
Fig. 3 (a) is vehicle acceleration change curve synoptic diagram in front and back provided in an embodiment of the present invention；
Fig. 3 (b) is vehicle speed change curve schematic diagram in front and back provided in an embodiment of the present invention；
Fig. 3 (c) is expectation vehicle headway curve synoptic diagram provided in an embodiment of the present invention；
Fig. 3 (d) is the change curve schematic diagram of rate of acceleration change provided in an embodiment of the present invention；
Fig. 3 (e) is the schematic diagram of practical following distance provided in an embodiment of the present invention；
Fig. 3 (f) be the MPC algorithm provided in an embodiment of the present invention based on VTH go to the workshop away from schematic diagram.
Specific embodiment
To keep the technical problem to be solved in the present invention, technical solution and advantage clearer, below in conjunction with attached drawing and tool
Body embodiment is described in detail.
The present invention is directed to the existing collaboration optimization problem that can not achieve multiple indexs, provides a kind of electric car auxiliary and drives
Adaptive follow the bus (Self-driving Electric Adaptive Tracking Control, the S-EATC) method sailed.
As shown in Figure 1, the adaptive follow the bus method that electric car auxiliary provided in an embodiment of the present invention drives, comprising:
S101 is established according to the stability requirement of following distance and is become headway (Variable Time Headway, VTH)
Strategy；
S102 combines the change headway strategy established according to kinematics character of vehicle during follow the bus, establish with
Following distance error, opposite speed, this vehicle acceleration and rate of acceleration change are added as state variable and output variable with expectation
Speed as control variable, front truck acceleration as interference volume adaptive follow the bus (Adaptive Tracking Control,
ATC) kinetic model；
S103 is determined according to the adaptive follow the bus kinetic model of foundation and is based on Model Predictive Control (Model
Predictive Control, MPC) prediction model, the prediction model for realizing multiple target indicators collaboration optimize,
The target indicator includes: economy, safety and comfort.
The adaptive follow the bus method that the auxiliary of electric car described in the embodiment of the present invention drives, according to the stability of following distance
Become headway strategy it is required that establishing, to guarantee the stability of S-EATC system；According to kinematics of vehicle during follow the bus
Feature combines the change headway strategy established, and establishes and is become with following distance error, opposite speed, this vehicle acceleration and acceleration
Rate is as state variable and output variable, and it is expected acceleration as control variable, front truck acceleration is used as oneself of interference volume
Adapt to follow the bus kinetic model；According to the adaptive follow the bus kinetic model of foundation, the prediction based on Model Predictive Control is determined
Model, the prediction model optimize for realizing the collaboration of economy, safety and comfort index；In this way, guaranteeing passenger
The safety and follow the bus of vehicle are improved on the basis of comfort and traveling economy, the collaboration for realizing multiple target is excellent
Change.
In the present embodiment, following distance error and opposite speed can embody follow the bus security performance, this vehicle acceleration with
And rate of acceleration change can reflect out follow the bus comfort and economic performance index, therefore, the prediction model passes through optimization
Parameter: following distance error, opposite speed, this vehicle acceleration and rate of acceleration change, Lai Shixian economy, safety and comfortable
The optimization of the multiple indexs of property, wherein characterize the opposite speed v of vehicle-following behaviorrelAbsolute value mean value reduce 19.81%, characterization
The rate of acceleration change j of comfort level by bushAbsolute value mean value reduce 30.4%.
It is further, described in the specific embodiment for the adaptive follow the bus method that aforementioned electric car auxiliary drives
According to the stability requirement of following distance, establishing change headway strategy includes:
According to the relative velocity of this vehicle speed, Ben Che and front truck, front truck acceleration, this vehicle battery pack state-of-charge
(State Of Charge, SOC) is established and is become headway strategy.
In the present embodiment, safe vehicle headway is determined in order to establish change headway strategy first according to this vehicle speed
ddes:
ddes=th·vh+d0
Wherein, ddesIndicate desired vehicle headway；thIt indicates headway, generally takes 1.4~3s；vhIndicate Ben Cheche
Speed；d0The minimum safe distance of two vehicles when being static generally comprises a length of wagon and workshop minimum range.
Then, according to determining safe vehicle headway, the relative velocity of Ben Che and front truck, front truck acceleration, this vehicle battery
The state-of-charge of group determines and becomes headway strategy are as follows:
ddes=th·vh+d0
Wherein, h4Constant coefficient is indicated, for example, h1、h2、h3、h41.5,0.05,0.3,0.2 can be taken respectively；th_max、
th_minThe upper limit, the lower limit of headway are respectively indicated, for example, 0.5s, 2.2s can be taken respectively；vrelIndicate this vehicle and front truck
Relative velocity；apIndicate front truck acceleration；SOC indicates the state-of-charge of this vehicle battery pack.
Finally, it is verified that becoming the stability of headway strategy
According to front and back following distance error formula: △ d (k)=d (k)-ddes(k), wherein d (k) indicates front and back vehicle headway
Error, d indicate practical front and back vehicle headway, ddesIndicate desired vehicle headway；By determining safe vehicle headway ddesFormula
It brings into the formula, and the derivation of peer-to-peer both sides can obtainBy system stability condition vrelWhen → 0,
Known to Δ d → 0: vrel+ k Δ d=0, wherein k is constant term, k > 0；It can be obtained by arrangementIt enables: k1=h2·k·vh+thK+1 >=1,Wherein, k1For
Constant term；Due toWith Δ d always contrary sign, i.e., as Δ d < 0,As Δ d > 0,So no matter workshop
Away from error delta d be it is just or negative, interval error can all converge on 0, i.e., this changes headway strategy is to restrain and stable.
It is further, described in the specific embodiment for the adaptive follow the bus method that aforementioned electric car auxiliary drives
The change headway strategy established is combined according to kinematics character of vehicle during follow the bus, is established with following distance error, phase
To speed, this vehicle acceleration and rate of acceleration change as state variable and output variable, it is expected acceleration as control
Variable, front truck acceleration include: as the adaptive follow the bus kinetic model of interference volume
A1, as shown in Fig. 2, Host vehicle indicates that this vehicle, Preceeding vehicle indicate front fortune in Fig. 2
Vehicle in row establishes the kinetic model of adaptive follow the bus system according to kinematics character of vehicle during follow the bus:
A11 determines the discrete models of vehicle headway according to kinematics character of vehicle during follow the bus:
Wherein, d indicates that practical front and back vehicle headway, k indicate k moment, TsIndicate the sampling period of discrete models, ah
Indicate the acceleration of this vehicle；
A12 determines following distance error according to following distance error formula and the discrete models of the vehicle headway of determination
Discrete models:
Wherein, △ d indicates front and back vehicle headway error；
A13 determines the discrete models of relative velocity according to kinematics character of vehicle during follow the bus:
vrel(k+1)=vrel(k)+ap(k)·Ts-ah(k)·Ts
A14 determines the discrete models of this vehicle acceleration according to contacting between lower layer's control and top level control:
Wherein, τ indicates adaptive follow the bus system time constant, and u indicates control variable, in the present embodiment, with the phase of this vehicle
Hope acceleration as control variable；
The application in order to better understand controls lower layer and is briefly described with top level control: controlling and leads in ACC system
Be divided into direct-type and layer-stepping control two ways, at present in vehicle using it is more be multi-layer controller, layer-stepping control
Device is mainly made of upper controller and lower layer's controller, wherein upper controller collects speed spacing by sensor
Information calculates the expectation acceleration that automobile realizes adaptive cruise function, inputs to lower layer's controller；Lower layer's controller is often
It is the inversion model of an automobile dynamics, it is expected that acceleration value is input with the output of upper controller, to be calculated
The opening information of accelerator pedal aperture or brake pedal.
A15 determines rate of acceleration change (that is: shock extent) according to the relationship between acceleration and rate of acceleration change
Discrete models:
Wherein, jhIndicate the rate of acceleration change of this vehicle；
A16, to sum up, the kinetic model that arrangement obtains adaptive follow the bus system (are referred to as: longitudinal dynamics mould
Type):
A2 determines the state equation of the kinetic model of obtained adaptive follow the bus system:
The selection of state variable often has ignored the stability of state equation and often with output distracter；Based on upper
Problem is stated, the state variable that following state variable is kinetic model is chosen:
X (k)=[△ d (k), vrel(k),ah(k),jh(k)]T
Choose control variable of the expectation acceleration of this vehicle as kinetic model, front truck acceleration apIt is as input dry
Disturb variable；The main performance indicator for considering follow the bus of the selection of output variable, following distance error and opposite speed can embody
Follow the bus security performance, acceleration and rate of acceleration change can reflect out follow the bus comfort and economic performance index, therefore select
Pick-up interval error, the opposite output variable of speed, this vehicle acceleration and rate of acceleration change as kinetic model:
Y (k)=[△ d (k), vrel(k),ah(k),jh(k)]TTherefore the shape of adaptive follow the bus system dynamics model can be obtained
State equation form is as follows:
Wherein, A, B, G, C indicate that coefficient matrix, A, B, G, C respectively indicate are as follows:
To sum up, the present embodiment is according to the discrete models of determining following distance error, the discrete mathematics mould of relative velocity
Type, the discrete models of this vehicle acceleration, rate of acceleration change discrete models, establish with following distance error, opposite
Speed, this vehicle acceleration and rate of acceleration change are as state variable and output variable, it is expected that acceleration becomes as control
It measures, kinetic model during follow the bus of the adaptive follow the bus vehicle using front truck acceleration as interference volume.
It is further, described in the specific embodiment for the adaptive follow the bus method that aforementioned electric car auxiliary drives
According to the adaptive follow the bus kinetic model of foundation, determine that the prediction model based on Model Predictive Control, the prediction model are used
Optimize in the collaboration for realizing multiple target indicators and includes:
B1, determine that predicted state and system of the adaptive follow the bus system at the following p moment export predicted value
B11, amendment error term e is introducedx(k), it according to the state equation of kinetic model, obtains adaptive follow the bus system and exists
The predicted state at the following p moment:
Wherein,Indicate the state vector of prediction, U (k+m) indicates that control variable vector, m indicate that control becomes
The number of amount, W (k+p) indicate interference volume vector,Indicate coefficient matrix,U(k+m)、W
(k+p)、It respectively indicates are as follows:
Wherein,H indicates State Equation Coefficients；
B12, amendment error term e is introducedx(k), it according to the state equation of kinetic model, obtains adaptive follow the bus system and exists
System in the following p moment exports predicted value:
Wherein,Indicate the system output vector of prediction,Indicate coefficient matrix,It respectively indicates are as follows:
B2, predicted state and system according to obtained adaptive follow the bus system at the following p moment export predicted value, really
The fixed performance indicator evaluation function based on Model Predictive Control, the performance indicator evaluation function is as prediction model, for real
The collaboration optimization of existing multiple target indicators, specific steps may include:
B21, the Performance Evaluating Indexes function J for primarily determining adaptive follow the bus system:
Wherein,Indicate the system output value of prediction, yref(k+i) desired system output value is indicated, R, Q are
Indicate the coefficient of performance metrics evaluation function；
In the present embodiment, Performance Evaluating Indexes are established according to practical significance, and system optimization is the optimization based on output
Problem should determine that the m control amount from the k moment makes output predicted value of the controll plant within the following p momentAs close as desired system output value yref(k+i), while being not intended to control variable that violent change occurs
Change.
The constraint condition of Performance Evaluating Indexes function J are as follows:
Corresponding sofening treatment is carried out to above-mentioned constraint condition and obtains following new constraint condition:
Wherein, ε1、ε2、ε3、ε4、ε5For relaxation factor, v# min、v# maxFor on the constraint lower bound and constraint of each relevant variable
The coefficient of relaxation on boundary, the value of # are △ d, vrel、ah、jh, u, △ dmax、△dminRespectively indicate the maximum value, most of following distance error
Small value, vrel-max、vrel-minRespectively indicate maximum value, the minimum value of opposite speed, ah-max、ah-minRespectively indicate this vehicle acceleration
Maximum value, minimum value, jh-max、jh-minRespectively indicate maximum value, the minimum value of rate of acceleration change, umax、uminIt respectively indicates
Control maximum value, the minimum value of variable.
In the present embodiment, v# min≤0、v# max>=0, coefficient of relaxation reflects relaxation factor to different variables and different changes
The relaxation degree of each component of amount.Due to not making at softening to tracking range error and rate of acceleration change (shock extent)
Reason, therefore enable ε1=ε4=0；εi>=0, i=2,3,5.
B22, the performance indicator evaluation function for having relaxation factor penalty term is determined
Infinitely expand in order to avoid constraint bound is relaxed the factor, loses constraint inequality to the limit of system input and output
Production is used, and a square of penalty term is added in the performance indicator evaluation function primarily determined, obtains punishing with relaxation factor
The performance indicator evaluation goal function of item
Wherein, ρ indicates eigenvalue matrix；
B23, ignore the item unrelated with control variable u, obtain the performance indicator evaluation function new based on Model Predictive Control:
It enables:
Wherein, Q indicates that the coefficient of performance metrics evaluation function, Ω indicate that coefficient, T indicate adopting for performance metrics evaluation function
The sample period；
B24, quadratic programming problem will be converted into based on the new performance indicator evaluation function of Model Predictive Control and solves,
Realize the collaboration optimization of multiple target indicators:
Wherein:
K1For 1 × m rank matrix, K2For m × m rank matrix.
In the present embodiment, after carrying out collaboration optimization to economy, safety and comfort index, it can also utilize dynamic
The associative simulation of Mechanics Simulation software CRUISE and Simulink complete economical, comfort during adaptive follow the bus,
The verifying of safety and follow the bus (and: power performance), it is specific: ATC system research pair used by the embodiment of the present invention
As if the electric car that auxiliary drives, using variable headway strategy, Comparing method when simulating, verifying is based on solid
Determine the ATC algorithm of headway (Constant Time Headway, CTH)；Partial simulation parameter setting is as follows: timeconstantτ
=0.5s, the sampling period T of discrete modelss=0.2s, p=16, m=5, the minimum safe distance d of two vehicles when static0=
15, the initial velocity v of diplomatic copy vehicleh-0=15m/s, the front truck initial velocity v that when emulation is arrangedp-0=17m/s, when emulation, are arranged
Initial front and back vehicle headway dstart=40m.
Using dynamics simulation software CRUISE and Simulink carry out associative simulation, obtain ATC vehicle adaptively with
The simulation result diagram of vehicle traveling, as shown in figure 3, LQR indicates linearquadratic regulator in Fig. 3.It can be sent out by simulation result
Existing: the designed S-EATC system based on VTH strategy and MPC algorithm can make vehicle that will relax during adaptive follow the bus
Adaptive, safety, economic index are controlled always within the scope of defined, realize the collaboration optimization of three indexs.
It should be noted that, in this document, relational terms such as first and second and the like are used merely to a reality
Body or operation are distinguished with another entity or operation, are deposited without necessarily requiring or implying between these entities or operation
In any actual relationship or order or sequence.
The above is a preferred embodiment of the present invention, it is noted that for those skilled in the art
For, without departing from the principles of the present invention, several improvements and modifications can also be made, these improvements and modifications
It should be regarded as protection scope of the present invention.
Claims (10)
1. a kind of adaptive follow the bus method that electric car auxiliary drives characterized by comprising
According to the stability requirement of following distance, establishes and become headway strategy；
The change headway strategy established is combined according to kinematics character of vehicle during follow the bus, foundation is missed with following distance
Difference, opposite speed, this vehicle acceleration and rate of acceleration change as state variable and output variable, using it is expected acceleration as
Control variable, adaptive follow the bus kinetic model of the front truck acceleration as interference volume；
According to the adaptive follow the bus kinetic model of foundation, the prediction model based on Model Predictive Control, the prediction mould are determined
Type optimizes for realizing the collaboration of multiple target indicators, and the target indicator includes: economy, safety and comfort.
2. the adaptive follow the bus method that electric car auxiliary according to claim 1 drives, which is characterized in that the basis
The stability requirement of following distance, establishing change headway strategy includes:
According to the relative velocity of this vehicle speed, Ben Che and front truck, front truck acceleration, this vehicle battery pack state-of-charge, establish become
Headway strategy.
3. the adaptive follow the bus method that electric car auxiliary according to claim 2 drives, which is characterized in that the change vehicle
Between when be expressed as away from strategy:
ddes=th·vh+d0
Wherein, ddesIndicate desired vehicle headway, vhIndicate this vehicle speed, d0The minimum safe distance of two vehicles, t when being statich
Indicate headway, h1、h2、h3、h4Indicate constant coefficient, th_max、th_minRespectively indicate the upper limit, the lower limit of headway, vrel
Indicate the relative velocity of this vehicle and front truck, apIndicate that front truck acceleration, SOC indicate the state-of-charge of this vehicle battery pack.
4. the adaptive follow the bus method that electric car auxiliary according to claim 3 drives, which is characterized in that the basis
Kinematics character of vehicle during follow the bus combines the change headway strategy established, and establishes with following distance error, opposite vehicle
Speed, this vehicle acceleration and rate of acceleration change are used as state variable and output variable, using it is expected acceleration as controlling variable,
Front truck acceleration includes: as the adaptive follow the bus kinetic model of interference volume
According to kinematics character of vehicle during follow the bus, the discrete models of vehicle headway are determined:
Wherein, d indicates that practical front and back vehicle headway, k indicate k moment, TsIndicate the sampling period of discrete models, ahIt indicates
The acceleration of this vehicle；
According to following distance error formula and the discrete models of the vehicle headway of determination, the discrete mathematics of following distance error is determined
Model:
Wherein, △ d indicates front and back vehicle headway error；
According to kinematics character of vehicle during follow the bus, the discrete models of relative velocity are determined:
vrel(k+1)=vrel(k)+ap(k)·Ts-ah(k)·Ts
Determine the discrete models of this vehicle acceleration:
Wherein, τ indicates that adaptive follow the bus system time constant, u indicate control variable, using the expectation acceleration of this vehicle as control
Variable；
According to the relationship between acceleration and rate of acceleration change, the discrete models of rate of acceleration change are determined:
Wherein, jhIndicate the rate of acceleration change of this vehicle；
According to the determining discrete models of following distance error, the discrete models of relative velocity, this vehicle acceleration from
Dissipate the discrete models of mathematical model, rate of acceleration change, establish with following distance error, opposite speed, this vehicle acceleration with
And rate of acceleration change is as state variable and output variable, it is expected acceleration as control variable, with front truck acceleration work
For interference volume adaptive follow the bus vehicle during follow the bus kinetic model.
5. the adaptive follow the bus method that electric car auxiliary according to claim 4 drives, which is characterized in that the workshop
It is indicated away from error formula are as follows:
△ d (k)=d (k)-ddes(k)
Wherein, d (k) indicates front and back vehicle headway error, and d indicates practical front and back vehicle headway, ddesIndicate desired following distance
From.
6. the adaptive follow the bus method that electric car auxiliary according to claim 4 drives, which is characterized in that state variable
It indicates are as follows: x (k)=[△ d (k), vrel(k),ah(k),jh(k)]T；
Output variable indicates are as follows: y (k)=[△ d (k), vrel(k),ah(k),jh(k)]T；
The form of the state equation of the kinetic model are as follows:
Wherein, A, B, G, C indicate coefficient matrix.
7. the adaptive follow the bus method that electric car auxiliary according to claim 6 drives, which is characterized in that coefficient matrix
A, B, G, C are respectively indicated are as follows:
8. the adaptive follow the bus method that electric car auxiliary according to claim 1 drives, which is characterized in that the basis
The adaptive follow the bus kinetic model established determines the prediction model based on Model Predictive Control, and the prediction model is for real
The collaboration of existing multiple target indicators, which optimizes, includes:
Introduce amendment error term ex(k), according to the state equation of kinetic model, adaptive follow the bus system is obtained at following p
The predicted state at quarter:
Wherein,Indicate the state vector of prediction, U (k+m) indicates that control variable vector, m indicate the number of control variable
Mesh, W (k+p) indicate interference volume vector,Indicate coefficient matrix,U(k+m)、W(k+p)、It respectively indicates are as follows:
Wherein,H indicates State Equation Coefficients；
Introduce amendment error term ex(k), according to the state equation of kinetic model, adaptive follow the bus system is obtained at following p
System in quarter exports predicted value:
Wherein,Indicate the system output vector of prediction,Indicate coefficient matrix,It respectively indicates are as follows:
Predicted state and system according to obtained adaptive follow the bus system at the following p moment export predicted value, and determination is based on
The performance indicator evaluation function of Model Predictive Control, the performance indicator evaluation function is as prediction model, for realizing multiple
The collaboration of target indicator optimizes.
9. the adaptive follow the bus method that electric car auxiliary according to claim 8 drives, which is characterized in that described to be based on
The performance indicator evaluation function of Model Predictive Control indicates are as follows:
Wherein,Indicate that the performance indicator evaluation function based on Model Predictive Control, T representing matrix transposition, ρ indicate characteristic value square
Battle array, Φ, R, Q indicate the coefficient of performance metrics evaluation function.
10. the adaptive follow the bus method that electric car auxiliary according to claim 9 drives, which is characterized in that the property
The constraint condition of energy metrics evaluation function are as follows:
Wherein, ε1、ε2、ε3、ε4、ε5For relaxation factor, v# min、v# maxConstraint lower bound and the constraint upper bound for each relevant variable
Coefficient of relaxation, the value of # are △ d, vrel、ah、jh, u, △ dmax、△dminRespectively indicate maximum value, the minimum of following distance error
Value, vrel-max、vrel-minRespectively indicate maximum value, the minimum value of opposite speed, ah-max、ah-minRespectively indicate this vehicle acceleration
Maximum value, minimum value, jh-max、jh-minRespectively indicate maximum value, the minimum value of rate of acceleration change, umax、uminRespectively indicate control
Maximum value, the minimum value of variable processed.
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