CN114475244B - Constant-speed cruise control method, vehicle control unit and constant-speed cruise control system - Google Patents

Constant-speed cruise control method, vehicle control unit and constant-speed cruise control system Download PDF

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CN114475244B
CN114475244B CN202210386862.7A CN202210386862A CN114475244B CN 114475244 B CN114475244 B CN 114475244B CN 202210386862 A CN202210386862 A CN 202210386862A CN 114475244 B CN114475244 B CN 114475244B
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vehicle
speed
time domain
control
constant
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CN114475244A (en
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郭祥靖
陶冰冰
李�浩
胡阳
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Heduo Technology Guangzhou Co ltd
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HoloMatic Technology Beijing Co Ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60K—ARRANGEMENT OR MOUNTING OF PROPULSION UNITS OR OF TRANSMISSIONS IN VEHICLES; ARRANGEMENT OR MOUNTING OF PLURAL DIVERSE PRIME-MOVERS IN VEHICLES; AUXILIARY DRIVES FOR VEHICLES; INSTRUMENTATION OR DASHBOARDS FOR VEHICLES; ARRANGEMENTS IN CONNECTION WITH COOLING, AIR INTAKE, GAS EXHAUST OR FUEL SUPPLY OF PROPULSION UNITS IN VEHICLES
    • B60K31/00—Vehicle fittings, acting on a single sub-unit only, for automatically controlling vehicle speed, i.e. preventing speed from exceeding an arbitrarily established velocity or maintaining speed at a particular velocity, as selected by the vehicle operator
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60K—ARRANGEMENT OR MOUNTING OF PROPULSION UNITS OR OF TRANSMISSIONS IN VEHICLES; ARRANGEMENT OR MOUNTING OF PLURAL DIVERSE PRIME-MOVERS IN VEHICLES; AUXILIARY DRIVES FOR VEHICLES; INSTRUMENTATION OR DASHBOARDS FOR VEHICLES; ARRANGEMENTS IN CONNECTION WITH COOLING, AIR INTAKE, GAS EXHAUST OR FUEL SUPPLY OF PROPULSION UNITS IN VEHICLES
    • B60K31/00—Vehicle fittings, acting on a single sub-unit only, for automatically controlling vehicle speed, i.e. preventing speed from exceeding an arbitrarily established velocity or maintaining speed at a particular velocity, as selected by the vehicle operator
    • B60K2031/0091—Speed limiters or speed cutters
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/10—Internal combustion engine [ICE] based vehicles
    • Y02T10/40—Engine management systems

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  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)

Abstract

The invention discloses a constant-speed cruise control method, a vehicle control unit and a constant-speed cruise control system. The method comprises the following steps: acquiring the speed of a vehicle at the current moment and gradient data in a prediction time domain of a driving road section; determining a driving torque for enabling the vehicle to reach a target speed for constant-speed cruising based on an MPC algorithm according to the speed at the current moment, the gradient data and a discrete time domain equation; and generating a driving control signal according to the driving torque. According to the technical scheme, the influence of the gradient on the vehicle speed is considered by utilizing the gradient data of the driving road section and combining the discrete time domain equation, the driving torque can be accurately determined, the vehicle can maintain the target speed of constant-speed cruising on a slope, and the reliability of the constant-speed cruising is improved.

Description

Constant-speed cruise control method, vehicle control unit and constant-speed cruise control system
Technical Field
The embodiment of the invention relates to the technical field of vehicle control, in particular to a constant-speed cruise control method, a vehicle control unit and a constant-speed cruise control system.
Background
At present, feedback control is generally adopted in constant-speed cruising of a vehicle, for example, real-time feedback control is performed through a proportional-Integral-derivative (PID), a fuzzy control, or a table look-up of a certain control algorithm calibration term based on an error between a target vehicle speed and an actual vehicle speed. The control method is widely applied to passenger vehicles and commercial vehicles. However, such control methods have significant disadvantages for vehicles traveling on large slope roads (including passenger vehicles and commercial vehicles) and heavy commercial vehicles traveling on a large slope. Under the influence of a ramp, the ramp resistance of the vehicle in the longitudinal direction is correspondingly increased or reduced along with the change of the ramp angle, so that a certain degree of external interference is brought to the control of the vehicle, the cruising speed of the vehicle deviates from the target speed along with the ramp, and the constant-speed cruising reliability is low.
Disclosure of Invention
The invention provides a constant-speed cruise control method, a vehicle control unit and a constant-speed cruise control system, which are used for improving the reliability of constant-speed cruise.
In a first aspect, an embodiment of the present invention provides a cruise control method, including:
acquiring the speed of a vehicle at the current moment and gradient data in a prediction time domain of a driving road section;
determining a driving torque for bringing the vehicle to a target speed for constant-speed cruising based on a Model Predictive Control (MPC) algorithm according to the speed at the current time, the gradient data and a discrete time domain equation;
a drive control signal is generated based on the drive torque.
In a second aspect, an embodiment of the present invention provides a Vehicle Control Unit (VCU), including:
one or more processors;
storage means for storing one or more programs;
when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the constant-speed-cruise control method according to the first aspect.
In a third aspect, an embodiment of the present invention further provides a constant-speed cruise control system, including: the vehicle control unit of the second aspect; further comprising:
the high-precision map module is used for acquiring gradient data of the vehicle in a prediction time domain;
the signal measurement module is used for measuring the real-time speed of the vehicle through a vehicle speed sensor;
the vehicle control system comprises an engine control module and a vehicle control module, wherein the engine control module is used for controlling a vehicle according to a drive control signal, and the drive control signal is transmitted by the vehicle control unit through a Controller Area Network (CAN) bus.
The embodiment of the invention provides a constant-speed cruise control method, a vehicle control unit and a constant-speed cruise control system, wherein the method comprises the steps of obtaining the speed of a vehicle at the current moment and gradient data in a prediction time domain of a driving road section; determining a driving moment for enabling the vehicle to reach a target speed of constant-speed cruising based on an MPC algorithm according to the speed at the current moment, the gradient data and a discrete time domain equation; and generating a driving control signal according to the driving torque. According to the technical scheme, the influence of the gradient on the vehicle speed is considered by utilizing the gradient data of the running road section and combining the discrete time domain equation, the driving torque can be accurately determined, the vehicle can maintain the target speed of constant-speed cruising on the ramp, and the reliability of the constant-speed cruising is improved.
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The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and features are not necessarily drawn to scale.
FIG. 1 is a flow chart of a cruise control method according to an embodiment of the present invention;
FIG. 2 is a flow chart of a cruise control method according to another embodiment of the present invention;
fig. 3 is a schematic structural diagram of a vehicle control unit according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a constant-speed cruise control system according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. In addition, the embodiments and features of the embodiments in the present invention may be combined with each other without conflict. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the steps as a sequential process, many of the steps can be performed in parallel, concurrently or simultaneously. In addition, the order of the steps may be rearranged. The process may be terminated when its operations are completed, but could have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, subprograms, and the like.
Fig. 1 is a flowchart of a cruise control method according to an embodiment of the present invention, where the embodiment is applicable to control of a cruise function of a vehicle. Specifically, the constant-speed cruise control method may be executed by a constant-speed cruise control device, which may be implemented by software and/or hardware and integrated in the vehicle control unit. The vehicle control unit can be contained in a constant-speed cruise control system, and the constant-speed cruise control system also comprises a high-precision map module for acquiring gradient data, a signal measuring module for measuring the real-time speed of the vehicle and an engine control module for driving the vehicle.
As shown in fig. 1, the method specifically includes the following steps:
and S110, acquiring the speed of the vehicle at the current moment and gradient data in a prediction time domain of the driving road section.
Specifically, the speed of the vehicle at the current moment can be measured by the signal measurement module, and specifically can be measured by a vehicle speed sensor in the signal measurement module. The prediction time domain may be understood as a period of time after the current time, for example, 30 seconds after the current time, or a period of time corresponding to 500 meters ahead of the position of the vehicle at the current time. The control horizon may be understood as how many sets of control quantities are solved, but the MPC algorithm only acts on the control system with the first element of the control increment. The slope data can be obtained through a high-precision map module, and the high-precision map (also called an automatic driving map and a high-resolution map) can accurately reflect the road characteristics of the vehicle in front of the position of the driving road section in real time, wherein the road characteristics include the slope data, and the front part of the driving road section can be an ascending road section or a descending road section. In general, for an uphill road section, the speed of the vehicle may be reduced to deviate from the target speed for constant-speed cruising, and a certain driving torque needs to be applied; for downhill sections, the speed of the vehicle may increase and deviate from the target speed, requiring a certain braking torque to be applied.
S120, determining the driving torque for enabling the vehicle to reach the target speed of constant-speed cruising based on an MPC algorithm according to the speed and gradient data at the current moment and a discrete time domain equation
Specifically, vehicle dynamics primarily involve three directions: the driving torque or the braking torque is predictively determined by considering gradient data and combining a discrete time domain equation to predict the change of the speed of the vehicle in a prediction time domain, wherein the discrete time domain equation is obtained by a vehicle longitudinal dynamic balance equation.
The MPC algorithm is an advanced process control method that can predict an output (e.g., a driving torque) for a period of time in the future based on a speed at a current time, and the following elements are determined when using the MPC algorithm: state quantities (such as the speed and acceleration of the vehicle, etc.), control quantities (i.e., output quantities such as the drive torque), objective functions (as optimization criteria for solving the control quantities), and constraints (limits on the ranges of values of the state quantities and the control quantities). In this embodiment, based on the MPC algorithm, according to the speed at the current time, the gradient data and the discrete time domain equation, the driving torque may be solved for the case where the uphill road segment exists, so that the deviation of the vehicle that may occur in the prediction time domain is effectively compensated and controlled, and the vehicle is maintained at the target speed.
And S130, generating a driving control signal according to the driving torque.
Specifically, a drive control signal generated by the vehicle control unit may be transmitted to the engine control module through the CAN bus to implement control of the vehicle.
In one embodiment, the prediction time domain and the control time domain corresponding to the prediction time domain are variable. Specifically, the prediction time domain may be changed according to the length of the front slope and the size of the slope angle, for example, for a road section on an uphill slope, when the slope angle is smaller than a certain threshold, a smaller prediction time domain and a smaller control time domain may be used; when the slope angle is larger than a certain threshold value, predicting a time period of the time domain needing to cover the distance from the starting point of the threshold value of the slope to the highest point of the slope, and adopting a smaller control time domain; for a section of a downhill slope, the time domain is predicted to include a time period from the highest point of the slope to the lowest point of the slope, and the time domain is controlled to take a larger value. The embodiment does not limit the variation strategy of the prediction time domain and the control time domain, for example, the prediction time domain and the control time domain can be determined along with the change of a ramp, so as to achieve the purpose of better maintaining the constant-speed cruising speed of the vehicle.
According to the constant-speed cruise control method provided by the embodiment, the influence of the gradient on the vehicle speed is considered by utilizing the gradient data of the driving road section and combining a discrete time domain equation, the driving torque can be accurately determined, the vehicle can maintain the target speed of constant-speed cruise on the slope, and the reliability of constant-speed cruise is improved. The MPC algorithm is adopted, the MPC algorithm has predictive feedforward control and rolling optimization feedback control effects, and corresponding control can be performed in advance for the condition that the vehicle has an uphill and downhill road section in front, namely, certain degree of slope rushing is performed before uphill and speed reduction is performed before downhill, so that the control effect that the cruising speed fluctuation range is very small is achieved, certain degree of upshifting, downshifting, speed reduction and the like are avoided, and the driving stability and riding comfort of the vehicle are ensured.
Fig. 2 is a flowchart of a constant-speed cruise control method according to another embodiment of the present invention, which is optimized based on the above embodiment, and a process of solving a driving torque is described in detail. It should be noted that technical details that are not described in detail in the present embodiment may be referred to any of the above embodiments.
As shown in fig. 2, the method specifically includes the following steps:
s210, taking the vehicle speed, the acceleration and the acceleration derivative as state quantities, taking the driving moment as a control quantity, and constructing the discrete time domain equation.
The discrete time domain equation can be obtained according to a vehicle longitudinal dynamic equilibrium equation. The vehicle longitudinal dynamic equilibrium equation is as follows:
Figure 916866DEST_PATH_IMAGE001
wherein, the first and the second end of the pipe are connected with each other,
Figure 224220DEST_PATH_IMAGE002
the weight (Kg) of the whole vehicle is provided;
Figure 738378DEST_PATH_IMAGE003
is the acceleration of gravity (m/s) 2 )；
Figure 602429DEST_PATH_IMAGE004
Is rolling resistance coefficient (-);
Figure 885642DEST_PATH_IMAGE005
grade (°) for the road location of the current vehicle;
Figure 160635DEST_PATH_IMAGE006
is the air resistance coefficient (-);
Figure 896510DEST_PATH_IMAGE007
is the frontal area (m) of the vehicle 2 )；
Figure 564251DEST_PATH_IMAGE008
Is the density of air (N.m) 2 ·m -4 )；
Figure 701972DEST_PATH_IMAGE009
Real-time vehicle speed (m/s) for the host vehicle;
Figure 413445DEST_PATH_IMAGE010
is a vehicle rotating mass conversion coefficient (-);
Figure 636616DEST_PATH_IMAGE011
is the variator drive ratio (-);
Figure 639207DEST_PATH_IMAGE012
is the main transmission ratio (-) of the main speed reducer;
Figure 365854DEST_PATH_IMAGE013
is the mechanical efficiency (-) of the drive train,
Figure 264540DEST_PATH_IMAGE014
is the effective radius (m) of the wheel,
Figure 771745DEST_PATH_IMAGE015
for the driving moment (N · m),
Figure 499398DEST_PATH_IMAGE016
is the acceleration (m/s) 2 )。
Specifically, the vehicle speed is selected
Figure 611711DEST_PATH_IMAGE009
(m/s), acceleration
Figure 212456DEST_PATH_IMAGE016
(m/s 2 ) Derivative of acceleration
Figure 410219DEST_PATH_IMAGE017
(m/s 3 ) Is a state quantity, driving torque
Figure 692296DEST_PATH_IMAGE015
(N.m) is a controlled variable, and a discrete time domain equation is constructed by a vehicle longitudinal dynamics balance equation and a first-order inertia system by using a forward Euler method:
Figure 455853DEST_PATH_IMAGE018
Figure 945609DEST_PATH_IMAGE019
Figure 99510DEST_PATH_IMAGE020
wherein the content of the first and second substances,
Figure 247594DEST_PATH_IMAGE021
a desired vehicle speed (m/s);
Figure 68920DEST_PATH_IMAGE022
gradient (°) for a current vehicle travel position;
Figure 214730DEST_PATH_IMAGE023
is the sampling time(s);
Figure 370774DEST_PATH_IMAGE024
is the time constant (-);
Figure 56970DEST_PATH_IMAGE025
the current time is the vehicle speed (m/s);
Figure 732802DEST_PATH_IMAGE026
the vehicle speed (m/s) at the next moment;
Figure 111831DEST_PATH_IMAGE027
and
Figure 505903DEST_PATH_IMAGE028
acceleration (m/s) of the current time and the next time 2 )；
Figure 933474DEST_PATH_IMAGE029
Is the desired acceleration (m/s) at the current moment 2 )；
Figure 260550DEST_PATH_IMAGE030
The derivative (m/s) of the acceleration at the next moment 3 )，
Figure 263010DEST_PATH_IMAGE014
Is the effective radius (m) of the wheel.
In this embodiment, the forward eulerian method is used to linearly discretize the vehicle longitudinal dynamics balance equation, and a discrete time domain equation related to time can be obtained based on the vehicle longitudinal dynamics balance equation, so that the MPC algorithm is used to solve the control quantity in the prediction time domain.
Optionally, the vehicle longitudinal dynamics balance equation and the discrete time domain equation contain disturbance terms of ramp resistance, acceleration resistance, air resistance, and rolling resistance.
Predicting a ramp angle in a time domain in the vehicle longitudinal dynamics balance equation and the discrete time domain equation
Figure 878799DEST_PATH_IMAGE022
The current moment can be obtained in advance through the high-precision map module
Figure 172377DEST_PATH_IMAGE031
Up to the point where
Figure 822801DEST_PATH_IMAGE032
Respective slope value of time, wherein
Figure 215736DEST_PATH_IMAGE033
Is a prediction time domain; as the ramp changes, the desired acceleration also changes. Wherein the disturbance term of the ramp resistance is
Figure 381138DEST_PATH_IMAGE034
(ii) a The disturbance term of air resistance is
Figure 665358DEST_PATH_IMAGE035
(ii) a The interference term of the rolling resistance is
Figure 170289DEST_PATH_IMAGE036
。
The embodiment realizes the prediction of the front slope by introducing a high-precision map, and realizes the predictive constant-speed cruise control by adding interference items of slope resistance, air resistance and rolling resistance brought to the vehicle by slope change into an MPC algorithm.
And S220, determining the expected acceleration at the current moment according to the speed and gradient data at the current moment and a vehicle longitudinal dynamic balance equation.
In this embodiment, solving the expected acceleration at the current time may provide a basis for linear discretization of the vehicle longitudinal dynamic equilibrium equation. Solving for expected acceleration
Figure 999704DEST_PATH_IMAGE029
The principle of (1) is as follows:
Figure 652403DEST_PATH_IMAGE037
Figure 225466DEST_PATH_IMAGE038
Figure 834171DEST_PATH_IMAGE039
wherein the content of the first and second substances,
Figure 896805DEST_PATH_IMAGE040
predicting the vehicle speed at each moment in the time domain;
Figure 708903DEST_PATH_IMAGE041
predicting the expected vehicle speed at each moment in the time domain;
Figure 351237DEST_PATH_IMAGE042
to predict the desired acceleration at various times in the time domain.
In this embodiment, the discrete time domain equation constructed in S210 can be expressed as an equation of the following form:
Figure 627498DEST_PATH_IMAGE043
wherein, the first and the second end of the pipe are connected with each other,
Figure 798716DEST_PATH_IMAGE044
Figure 612957DEST_PATH_IMAGE045
Figure 590141DEST_PATH_IMAGE046
wherein the content of the first and second substances,
Figure 924170DEST_PATH_IMAGE047
in the case of a status item,
Figure 266290DEST_PATH_IMAGE048
in order to control the items of the game,
Figure 115297DEST_PATH_IMAGE049
for the amount of interference associated with the state term,
Figure 833854DEST_PATH_IMAGE050
for the amount of disturbance associated with the output item, and assuming
Figure 271658DEST_PATH_IMAGE050
Is 0.
Based on discrete time domain equations, one can obtain
Figure 50258DEST_PATH_IMAGE051
Time of day and
Figure 386561DEST_PATH_IMAGE031
and on the basis of the relation between the vehicle speeds at the moment, the prediction matrix can be solved according to the discrete time domain equation.
Optionally, after the vehicle longitudinal dynamic equilibrium equation is discretized linearly according to the forward eulerian method to obtain a discrete time domain equation, the method further includes: the discrete time domain equation is converted to a form that contains control increments.
In this embodiment, in order to avoid the phenomenon of sudden change of the controlled system control quantity, the control increment may be embodied in the above equation after linear discretization
Figure 643230DEST_PATH_IMAGE052
And thus, the control increments within each sampling period are constrained. Specifically, after the control increment is added to the discrete time domain equation, the discrete time domain equation can be expressed as:
Figure 951852DEST_PATH_IMAGE053
wherein, the first and the second end of the pipe are connected with each other,
Figure 698091DEST_PATH_IMAGE054
wherein the content of the first and second substances,mthe number of the control variables;nthe number of state variables.
230. And solving a prediction matrix according to the discrete time domain equation and the expected acceleration, wherein the prediction matrix is used for expressing the vehicle speed at each moment in the prediction time domain.
In this embodiment, taking the case that the discrete time domain equation includes the control increment as an example, the prediction matrix is solved according to the general form of the MPC algorithm
Figure 443062DEST_PATH_IMAGE055
（
Figure 769001DEST_PATH_IMAGE055
For representing vehicle speed at each time in the prediction horizon):
Figure 728867DEST_PATH_IMAGE056
wherein the content of the first and second substances,
Figure 583690DEST_PATH_IMAGE057
Figure 97848DEST_PATH_IMAGE058
Figure 758637DEST_PATH_IMAGE059
Figure 759960DEST_PATH_IMAGE060
the number of output quantities of the system;mthe number of the control variables;nis the number of state variables;
Figure 316843DEST_PATH_IMAGE033
is a prediction time domain;
Figure 849455DEST_PATH_IMAGE061
to control the time domain.
And S240, determining an objective function of quadratic programming.
In this embodiment, an objective function of the MPC algorithm is constructed, and a Quadratic Programming (QP) algorithm is used to solve a control quantity when the objective function reaches an optimal value. Wherein the objective function is used to minimize the deviation of the vehicle speed from the target speed at each time in the prediction horizon.
Illustratively, the objective function may be in the form of:
Figure 251618DEST_PATH_IMAGE062
wherein the content of the first and second substances,
Figure 123759DEST_PATH_IMAGE063
is composed of
Figure 648281DEST_PATH_IMAGE064
The predicted vehicle speed at the time of day,
Figure 855141DEST_PATH_IMAGE065
is composed of
Figure 857732DEST_PATH_IMAGE064
The target vehicle speed at the time of day,
Figure 849958DEST_PATH_IMAGE066
is a weight matrix of the desired reference quantity. Make it
Figure 483065DEST_PATH_IMAGE067
And (5) minimizing to obtain an optimal solution.
Optionally, the objective function is further used for at least one of: minimizing a control increment in a control time domain; minimizing a control amount in a control time domain; the relaxation factor is minimized.
For example, the objective function may be:
Figure 724690DEST_PATH_IMAGE068
the four terms on the right side of the equation are related to the deviation of the vehicle speed and the target speed at each moment, the control increment in the control time domain, the control quantity in the control time domain and the relaxation factor in turn;
Figure 734235DEST_PATH_IMAGE066
a weight matrix being a desired reference quantity;
Figure 830236DEST_PATH_IMAGE069
a weight matrix that is a control increment;
Figure 634244DEST_PATH_IMAGE070
a weight matrix which is a controlled variable;
Figure 628744DEST_PATH_IMAGE071
a weight matrix which is a relaxation factor;
Figure 910821DEST_PATH_IMAGE072
is a relaxation factor. Make it
Figure 877640DEST_PATH_IMAGE067
And (5) minimizing to obtain an optimal solution. Further, in the case where a relaxation factor is added, when there is no optimal solution, a suboptimal solution can be found.
Optionally, the constraint term of the quadratic programming includes at least one of the following:
constraint on acceleration:
Figure 649287DEST_PATH_IMAGE073
；
constraint on control amount:
Figure 318035DEST_PATH_IMAGE074
；
constraints on control increments:
Figure 466119DEST_PATH_IMAGE075
；
constraint on relaxation factor:
Figure 287445DEST_PATH_IMAGE076
；
soft constraints on the prediction values in the prediction matrix:
Figure 433255DEST_PATH_IMAGE077
；
hard constraints on the prediction values in the prediction matrix:
Figure 136769DEST_PATH_IMAGE078
。
the upper limit value and the lower limit value of each constraint item can be set according to actual requirements.
And S250, solving the objective function to obtain the driving torque.
And S260, generating a driving control signal according to the driving torque.
In this embodiment, the QP algorithm is used to solve the control quantity when the objective function reaches the optimal value, that is, the driving torque required by the vehicle at the current time, and then the vehicle controller CAN generate a driving control signal according to the control quantity, and send the driving control signal to the engine control module through the CAN bus, thereby implementing driving control of the vehicle.
In an embodiment, the method further comprises:
and S270, if the gradient data comprise downhill road section data and the speed at the current moment is greater than the speed threshold, generating a brake control signal.
Specifically, the actual vehicle speed of the vehicle is normally required to be within ± 3 Km/h of the target vehicle speed during constant-speed cruising. The processes of determining the driving torque and generating the driving control signal are mainly aimed at an uphill road section; and for downhill sections, can be setWhen the vehicle speed is larger than a speed threshold value (for example, 5 Km/h), a certain braking torque is applied to the vehicleT b And the vehicle is braked, so that the vehicle speed is prevented from being increased excessively. The braking torque can also be determined based on an MPC algorithm based on the speed at the present moment, the gradient data and the vehicle longitudinal dynamic balance equation, in order to maintain the vehicle at the target speed also on a downhill road section, and the principle can refer to the solution process of the driving torque in any of the embodiments described above.
The constant-speed cruise control method can solve the problems that the constant-speed cruise function is poor when the vehicle runs on a road section with a slope, the vehicle speed is reduced too much when the vehicle ascends the slope, the vehicle speed is increased greatly when the vehicle descends the slope or the cruise vehicle speed is unstable. The method comprises the steps of introducing a high-precision map to a constant-speed cruise solution of an MPC control algorithm to realize the prediction of the gradient in a certain range in front and the prediction control of a vehicle; the discrete time domain equation is constructed according to the vehicle longitudinal dynamics balance equation, the error of the state item is solved, the target function is constructed by using the QP algorithm, the constraint condition is established, the optimal driving moment can be obtained, the vehicle is maintained at the target speed, and the stability of constant-speed cruising is improved.
The embodiment of the invention also provides a vehicle control unit. Fig. 3 shows a schematic structural diagram of a hybrid vehicle controller 10 that may be used to implement an embodiment of the invention.
As shown in fig. 3, the hybrid vehicle controller 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, and the like, wherein the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various suitable actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the hybrid vehicle controller 10 may also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to the bus 14.
Various components in the vehicle control unit 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, a microphone, and the like; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the hybrid vehicle controller 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks, wireless networks.
Processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, or the like. The processor 11 performs the various methods and processes described above, such as the cruise control method.
In some embodiments, the constant speed cruise control method may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed on the hybrid vehicle controller 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the cruise control method in any other suitable manner (e.g., by way of firmware).
To provide for interaction with a user, the systems and techniques described herein may be implemented on a vehicle control unit 10, the vehicle control unit 10 having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user may provide input to the hybrid vehicle controller 10. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
Fig. 4 is a schematic diagram of a constant-speed cruise control system according to an embodiment of the present invention. As shown in fig. 4, the system includes: the vehicle control unit 310 of any of the embodiments described above; the system further comprises:
the signal measuring module 320 is used for measuring the real-time speed of the vehicle through a vehicle speed sensor;
the high-precision map module 330 is used for acquiring gradient data of the vehicle in a prediction time domain;
and an engine control module 340 for controlling the vehicle according to the driving control signal, wherein the driving control signal is transmitted by the vehicle controller 310 through the CAN bus.
The vehicle control unit 310 has a constant-speed cruise control function and comprises a predictive control module, wherein the predictive control module utilizes a quadratic programming algorithm to solve by establishing a vehicle dynamics model, a model predictive control algorithm and corresponding constraint conditions to obtain the driving torque required by the vehicle.
The Engine Control module 340 may also be understood as an Engine Electronic Control Unit (EECU). The vehicle controller 310 may send a driving control signal to the engine control module 340 by using the CAN bus according to the driving torque to instruct the engine control module 340 to implement driving control of the vehicle, and may implement acceleration control of the vehicle on an uphill road.
The System also includes a wheel controller 350, which may function as an Antilock Brake System (ABS). The braking torque is used for braking the wheels according to the braking torque, and the deceleration control of the vehicle on the downhill section can be realized.
The high accuracy map module 330 may be used to obtain grade data for a vehicle within a distance in front of a travel segment, the grade data including a grade. The high accuracy map module 330 may include a high accuracy map controller, an antenna receiver.
The signal measurement module 320 includes a vehicle speed sensor.
The constant-speed cruise control system provided by the embodiment can be used for executing the constant-speed cruise control method provided by any embodiment, and has corresponding functions and beneficial effects.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present invention may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired results of the technical solution of the present invention can be achieved.
The above-described embodiments should not be construed as limiting the scope of the invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (7)

1. A constant-speed-cruise control method, characterized by comprising:
acquiring the speed of a vehicle at the current moment and gradient data of each moment in a prediction time domain of a driving road section;
constructing a discrete time domain equation by taking the vehicle speed, the acceleration and the acceleration derivative as state quantities and taking the driving moment as a control quantity;
determining a driving moment for enabling the vehicle to reach a target speed for constant-speed cruising based on a Model Predictive Control (MPC) algorithm according to the speed at the current moment, the gradient data and a discrete time domain equation at each moment in the prediction time domain;
generating a drive control signal according to the drive torque;
the prediction time domain and the control time domain corresponding to the prediction time domain are changed according to the ramp length and the ramp angle;
determining a driving torque to bring the vehicle to a target speed for cruise at a constant speed based on an MPC algorithm based on the speed at the present time, the gradient data, and a discrete time domain equation, comprising:
linearly discretizing a vehicle longitudinal dynamic equilibrium equation according to a forward Euler method to obtain a discrete time domain equation;
determining the expected acceleration of each moment in the prediction time domain according to the speed of the current moment, the gradient data of each moment in the prediction time domain and the discrete time domain equation;
solving a prediction matrix according to the discrete time domain equation and the expected acceleration, wherein the prediction matrix is used for representing the vehicle speed at each moment in the prediction time domain;
determining an objective function of quadratic programming, wherein the objective function is used for minimizing the deviation of the vehicle speed and the target speed at each moment in the prediction time domain;
solving the objective function to obtain the driving torque; the objective function is further for at least one of:
minimizing a control increment in a control time domain;
minimizing a control amount in a control time domain;
the relaxation factor is minimized.
2. The method of claim 1, further comprising, after linearly discretizing the vehicle longitudinal dynamical balance equation according to the forward euler method to obtain a discrete time domain equation:
converting the discrete time domain equation to a form that includes control increments.
3. The method of claim 1, wherein the constraint term of quadratic programming comprises at least one of:
constraints on acceleration; constraint on the control quantity; constraints on control increments; constraints on relaxation factors; soft constraints on the prediction values in the prediction matrix; hard constraints on the prediction values in the prediction matrix.
4. The method of claim 1, further comprising:
and if the gradient data comprise downhill road section data and the speed at the current moment is greater than a speed threshold value, generating a brake control signal.
5. The method of claim 1, wherein the discrete time domain equations contain interference terms of ramp resistance, acceleration resistance, air resistance, and rolling resistance.
6. A vehicle control unit is characterized by comprising:
one or more processors;
storage means for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the cruise control method according to any of claims 1-5.
7. A constant speed cruise control system, comprising: the vehicle control unit of claim 6;
further comprising:
the high-precision map module is used for acquiring gradient data of the vehicle in a prediction time domain;
the signal measurement module is used for measuring the real-time speed of the vehicle through a vehicle speed sensor;
the vehicle control system comprises an engine control module, a vehicle monitoring module and a vehicle monitoring module, wherein the engine control module is used for controlling a vehicle according to a driving control signal, and the driving control signal is transmitted by the vehicle control unit through a Controller Area Network (CAN) bus;
and the prediction time domain and the control time domain corresponding to the prediction time domain are changed according to the ramp length and the ramp angle.
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