CN111169293A - Method and system for controlling relaxation static stability dynamics of unmanned vehicle - Google Patents

Method and system for controlling relaxation static stability dynamics of unmanned vehicle Download PDF

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CN111169293A
CN111169293A CN202010059842.XA CN202010059842A CN111169293A CN 111169293 A CN111169293 A CN 111169293A CN 202010059842 A CN202010059842 A CN 202010059842A CN 111169293 A CN111169293 A CN 111169293A
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unmanned vehicle
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vehicle
wheel
control
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CN111169293B (en
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倪俊
姜旭
李远哲
袁昊
吴家枫
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Beijing Institute of Technology BIT
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L15/00—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles
    • B60L15/20—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles for control of the vehicle or its driving motor to achieve a desired performance, e.g. speed, torque, programmed variation of speed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
    • B62D—MOTOR VEHICLES; TRAILERS
    • B62D7/00—Steering linkage; Stub axles or their mountings
    • B62D7/06—Steering linkage; Stub axles or their mountings for individually-pivoted wheels, e.g. on king-pins
    • B62D7/14—Steering linkage; Stub axles or their mountings for individually-pivoted wheels, e.g. on king-pins the pivotal axes being situated in more than one plane transverse to the longitudinal centre line of the vehicle, e.g. all-wheel steering
    • B62D7/15—Steering linkage; Stub axles or their mountings for individually-pivoted wheels, e.g. on king-pins the pivotal axes being situated in more than one plane transverse to the longitudinal centre line of the vehicle, e.g. all-wheel steering characterised by means varying the ratio between the steering angles of the steered wheels
    • B62D7/1581—Steering linkage; Stub axles or their mountings for individually-pivoted wheels, e.g. on king-pins the pivotal axes being situated in more than one plane transverse to the longitudinal centre line of the vehicle, e.g. all-wheel steering characterised by means varying the ratio between the steering angles of the steered wheels characterised by comprising an electrical interconnecting system between the steering control means of the different axles
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2220/00—Electrical machine types; Structures or applications thereof
    • B60L2220/40—Electrical machine applications
    • B60L2220/42—Electrical machine applications with use of more than one motor
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2220/00—Electrical machine types; Structures or applications thereof
    • B60L2220/40—Electrical machine applications
    • B60L2220/46—Wheel motors, i.e. motor connected to only one wheel
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/40—Drive Train control parameters
    • B60L2240/46—Drive Train control parameters related to wheels
    • B60L2240/465—Slip
    • 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
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/72—Electric energy management in electromobility

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  • Mechanical Engineering (AREA)
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Abstract

The invention provides a method and a system for controlling the relaxation of static stability dynamics of an unmanned vehicle, which can relax the layout conditions of a transverse dynamics system of the unmanned vehicle, reduce the limitation of the traditional vehicle layout theory on the overall layout flexibility of the unmanned vehicle, and improve the overall layout flexibility and the design space of a chassis of the unmanned vehicle. The method specifically comprises the following steps: calculating a target active yaw moment required for realizing the preset target pole position according to the preset target pole position and the current vehicle state parameter; and then distributing the calculated target active yaw moment to each independent driving wheel of the unmanned vehicle, so that the unmanned vehicle obtains the vehicle dynamic performance corresponding to the preset target pole position. The control system can relax the stability limitation condition of the overall layout of the unmanned vehicle, allows the layout of the transverse dynamics system of the unmanned vehicle to be a static and unstable system, breaks through the theoretical constraint of the traditional static and stable layout, and is particularly suitable for the unmanned vehicle which causes the static and unstable transverse dynamics system after adopting the design scheme of the all-line control chassis.

Description

Method and system for controlling relaxation static stability dynamics of unmanned vehicle
Technical Field
The invention relates to a dynamics control method and system for an unmanned vehicle, in particular to a relaxation static stability dynamics control method and system for the unmanned vehicle, and belongs to the technical field of unmanned vehicles and automatic driving vehicles.
Background
The automatic driving vehicle is an important development direction of the future automobile industry and is one of important fields of artificial intelligence technology landing. The unmanned vehicle is a vehicle with autonomous behavior capability and completely omitting a human driving mechanism, and has the characteristics of intellectualization, wire control, robotization and multiple functions. The unmanned vehicle aims to replace human beings to execute operation tasks, including but not limited to civil or military tasks such as striking, fighting, patrol, reconnaissance, logistics, transportation, ferrying, distribution, cleaning and the like, has a very wide application prospect in the civil or military field, is an important component part of future intelligent transportation and smart city construction, and is an important support for development of new-generation army equipment in China. Therefore, the research of the unmanned vehicle theory and technology has important strategic significance on national economic development and national defense safety construction in China.
Compared with the traditional vehicle, the unmanned vehicle has completely different overall configuration, layout form, control system, actuating mechanism and the like. Due to special use functions, a human operation mechanism is completely omitted from the unmanned vehicle, and a chassis of the unmanned vehicle is required to adopt a full-wire control architecture, namely a steering system, a driving system and a braking system are completely controlled by an electronic control system, so that full-wire steering, wire-control driving and wire-control braking are realized. The brand new overall layout form provides great challenges for theories and technologies such as overall design, dynamics and control of the unmanned vehicle.
After the full-line control technology architecture is adopted, the overall layout of the unmanned vehicle is greatly changed compared with the traditional vehicle, and due to the special overall layout form, the static stability of a transverse dynamic system of the unmanned vehicle can be influenced, so that the phenomenon that the transverse dynamic system is static and unstable (oversteering) often occurs to the unmanned vehicle, the unmanned vehicle is easy to lose the operation stability under the working conditions of extreme driving and the like, and the comprehensive performance of the unmanned vehicle is seriously influenced.
Disclosure of Invention
In view of the above, the invention provides a method for controlling the relaxation static stability dynamics of an unmanned vehicle, which can relax the layout conditions of a transverse dynamics system of the unmanned vehicle, reduce the limitation of the traditional vehicle layout theory on the overall layout flexibility of the unmanned vehicle, and greatly improve the overall layout flexibility and design space of a chassis of the unmanned vehicle.
The method for controlling the relaxation static stability dynamics of the unmanned vehicle comprises the following steps: calculating a target active yaw moment required for realizing the preset target pole position according to the preset target pole position and the current vehicle state parameter;
and then distributing the calculated target active yaw moment to each independent driving wheel of the unmanned vehicle, so that the unmanned vehicle obtains vehicle dynamic performance corresponding to the preset target pole position.
The target active yaw moment is calculated by adopting the following method:
the control law of the active yaw moment of the unmanned vehicle is as follows:
u(t)＝Kx(t)(1)
in the formula: x (t) is a transverse dynamic state parameter of the unmanned vehicle; u (t) is yaw moment input; k is a feedback matrix in the control law;
establishing a two-degree-of-freedom dynamic model of the unmanned vehicle containing parameter uncertainty:
Figure BDA0002374100820000022
in the formula: w (t) is the steering wheel angle input of the front wheel and the rear wheel; a. the0、B20、B10The state parameter matrix of the unmanned vehicle is determined by the dynamic state parameters of the unmanned vehicle; Δ A, Δ B2、ΔB1The uncertainty matrix is an uncertainty matrix of the unmanned vehicle transverse dynamics system and is used for representing parameter uncertainty;
describing a target pole region of the unmanned vehicle transverse dynamic system by adopting a circular domain linear matrix inequality region;
then based on a robust control method, calculating the feedback matrix K according to the two-degree-of-freedom dynamic model containing uncertainty and a preset target pole position, and enabling the preset target pole position to be in the described target pole region;
after the feedback matrix K is obtained, the target active yaw moment of the unmanned vehicle is u (t) ═ Kx (t).
When the unmanned vehicle is an all-wheel independent driving unmanned vehicle, namely four unmanned wheels are all independent driving wheels:
the driving force distribution proportion function of the left side wheel and the right side wheel of the unmanned vehicle is as follows:
Figure BDA0002374100820000021
in the formula: fx11Is the left front wheel driving force; fx12Is the longitudinal driving force of the right front wheel; fx21Is the left rear wheel drive force; fx22Is the right rear wheel drive force; fz11Vertical force of the left front wheel; fz12Is vertical force of the right front wheel; fz21Vertical force of the left rear wheel; fz22Is the vertical force of the right rear wheel; k is a discrete time; kappalA proportional function is allocated to the driving force of the left wheel; kapparA proportional function is allocated to the driving force of the right wheel;
target total driving force F of unmanned vehiclexTTarget active yaw moment MdesAnd the driving force relation of each wheel is as follows:
Figure BDA0002374100820000031
in the formula: b is the vehicle wheel track; lfThe distance from the center of mass of the vehicle to the front axle; lrThe distance from the center of mass of the vehicle to the rear axle; delta is a wheel corner;
the driving force distribution result of each of the independently driven wheels is:
Figure BDA0002374100820000032
based on the dynamics control method, the invention also provides a relaxation static stability dynamics control system of the unmanned vehicle, which comprises the following steps: the control system comprises a control instruction layer, a chassis upper control layer, a chassis lower control layer, an actuating mechanism control layer and a state parameter feedback layer;
the control instruction layer is used for sending a chassis control instruction to a chassis upper control layer, and the chassis control instruction comprises: a target steering mode, a target wheel angle, a target total driving force, a target total braking force;
the upper control layer of the chassis comprises a target instruction resolving module and a yaw moment calculating module; after the chassis upper control layer receives the chassis control instruction, the target instruction resolving module resolves the chassis control instruction, the yaw moment calculating module calculates a target active yaw moment, and then the resolved target instruction and the calculated target yaw moment are sent to the chassis lower control layer; when the yaw moment calculation module calculates the target active yaw moment, the target active yaw moment required for realizing the preset closed-loop target pole position is calculated through the preset closed-loop target pole position and the current vehicle state parameters fed back by the vehicle state parameter feedback layer on the basis of the vehicle dynamic model;
the lower chassis control layer calculates the longitudinal driving force of each independent driving wheel according to the target total driving force in the control instruction and the target active yaw moment calculated by the upper chassis control layer, and then sends corresponding control information to the execution mechanism control layer according to the calculated longitudinal driving force of each independent driving wheel; the chassis lower control layer also sends corresponding control information to the executing mechanism control layer according to the resolved target instruction; meanwhile, the chassis lower control layer also controls the slip rate of each independent driving wheel by controlling the driving motor of each independent driving wheel;
the executing mechanism control layer realizes the control of the executing mechanisms in the wire-controlled steering system, the wire-controlled driving system and the wire-controlled braking system according to the received control information of the chassis lower layer control layer;
the vehicle state parameter feedback layer is used for monitoring dynamic state parameters of the vehicle in real time and feeding back the dynamic state parameters to the upper control layer of the chassis; the dynamic state parameters of the vehicle include: vehicle speed, yaw rate, center of mass slip angle, motor torque, and motor speed.
Has the advantages that:
(1) by adopting the control method and the control system, the stability limit condition of the overall layout of the unmanned vehicle can be relaxed, the layout of the transverse dynamics system of the unmanned vehicle is allowed to be a static unstable system, the constraint of the traditional static stable layout theory is broken through, the limitation of the traditional vehicle layout theory on the overall layout flexibility of the unmanned vehicle is reduced, and the control method and the control system are particularly suitable for the unmanned vehicle which causes the static instability of the transverse dynamics system after adopting the design scheme of the all-wire control chassis; the flexibility and the design space of the overall layout of the chassis of the unmanned vehicle are greatly improved, the technical advantages of flexible layout of the full-line control chassis system are fully exerted, and the theoretical requirements of future diversified multifunctional unmanned vehicle development are met.
(2) The invention realizes the dynamics control of the transverse dynamics system of the unmanned vehicle by the method of allocating the target ideal pole position, thereby improving the maneuverability, stability, maneuverability and controllability of the unmanned vehicle and meeting the use requirements of the multifunctional unmanned vehicle under different working conditions.
Drawings
FIG. 1 is a schematic control flow diagram of the dynamics control system of the present invention;
FIG. 2 is a schematic diagram of a vehicle lateral dynamics system target ideal pole location;
FIG. 3 is a schematic diagram of a drive force distribution module for an independently driven vehicle;
FIG. 4 is a schematic diagram illustrating the control effect of the present invention.
Detailed Description
The invention is described in detail below by way of example with reference to the accompanying drawings.
The embodiment provides a relaxation static stability dynamics control system for an unmanned vehicle, which selects a target ideal pole position of a transverse dynamics system of the unmanned vehicle through a pole configuration dynamics control method, so that the unmanned vehicle obtains vehicle dynamics performance corresponding to the target ideal pole position.
As shown in fig. 1, the unmanned vehicle relaxation static stability dynamics control system includes five control layers, which are: the control system comprises a control instruction layer, a chassis upper control layer, a chassis lower control layer, an actuating mechanism control layer and a state parameter feedback layer.
The control instruction layer is used for sending an intelligent decision result of the unmanned vehicle as a chassis control instruction to the upper control layer of the chassis; for an all-wheel independently steering all-wheel independently driven unmanned vehicle, the chassis control command comprises information such as a target steering mode, a target wheel turning angle, a target total driving force and a target total braking force of the unmanned vehicle, and the control information is obtained from a calculation result of an unmanned vehicle intelligent decision or path planning unit. And the control command layer outputs the chassis control command to the upper control layer of the chassis.
The upper control layer of the chassis is the core of the direct force dynamic control system, and comprises the following components: the system comprises a target command resolving module and a yaw moment calculating module. After the upper control layer of the chassis obtains the chassis control command from the control command layer, the target command resolving module resolves the chassis control command through a communication protocol, the yaw moment calculating module calculates a target active yaw moment, and then sends the resolved target command and the calculated target yaw moment to the lower control layer of the chassis. The target instruction is used for resolving, for example, a corner signal (namely a target wheel corner) of the unmanned vehicle remote control system is resolved into a corresponding angle of the steering motor, and the target instruction is the angle of the steering motor; and resolving a driving signal (namely the target total driving force) of the remote control system into a corresponding torque of the driving motor, wherein the target command is the torque of the driving motor.
The target yaw moment is an important parameter for realizing the target pole position allocation of the transverse dynamic system, when the target active yaw moment is calculated, the target active yaw moment required for realizing the preset closed-loop target pole position is calculated through the preset closed-loop target pole position and the current vehicle state parameters fed back by the vehicle state parameter feedback layer on the basis of a vehicle dynamic model, and then the target active yaw moment is exerted on the vehicle through the independent driving wheels to finish the set control target of the target pole allocation (even if the unmanned vehicle obtains the vehicle dynamic performance corresponding to the preset closed-loop pole target position).
The chassis lower control layer is used for the control of the distribution of the longitudinal driving force of each independent driving wheel of the unmanned vehicle and the slip ratio of each independent driving wheel, and comprises the following components: the device comprises a driving force distribution module and a wheel slip ratio control module. In the driving force distribution module, calculating the longitudinal driving force of each of the independently driven wheels from the total driving force demand (i.e., the target total driving force in the control command) and the yaw moment demand (the target active yaw moment calculated by the upper control layer of the chassis); in the wheel slip ratio control module, the control of the slip ratio of each independently driven wheel is realized by controlling the driving motor of each independently driven wheel. And the lower control layer of the chassis sends corresponding control information to an execution mechanism control layer, such as the torque of a driving motor, according to the calculated longitudinal driving force of each independent driving wheel. In addition, the chassis lower control layer also sends corresponding control information to the executing mechanism control layer according to the solved target instruction, such as the angle of a steering motor, the angle of a braking motor and the like.
The actuating mechanism control layer realizes the control of actuating mechanisms in a wire-controlled steering system, a wire-controlled driving system and a wire-controlled braking system according to the received control information of the lower control layer of the chassis, wherein the actuating mechanism in the wire-controlled steering system is a steering motor, the actuating mechanism in the wire-controlled driving system is a driving motor, and the actuating mechanism in the wire-controlled braking system is a braking motor.
The vehicle state parameter feedback layer is used for monitoring dynamic state parameters of the vehicle in real time and feeding the dynamic state parameters back to the upper control layer of the chassis to ensure the parameter feedback requirement of the vehicle dynamic control system; the dynamic state parameters of the vehicle include: vehicle speed, yaw rate, centroid slip angle, motor torque, motor speed, and the like.
The core of the dynamics control system-the closed-loop target pole position of the lateral dynamics system of the vehicle is achieved by the active yaw moment of the vehicle, which is achieved by the independent drive motors on both sides of the vehicle. Let the control law of the active yaw moment of the vehicle be:
u(t)＝Kx(t)(1)
in the formula: x (t) is a lateral dynamic state parameter of the vehicle; u (t) is yaw moment input; and K is a feedback matrix in the control law.
The dynamic model adopted by the calculation of the active yaw moment is a vehicle two-degree-of-freedom dynamic model considering system uncertainty:
Figure BDA0002374100820000064
in the formula: x (t) is a lateral dynamic state parameter of the vehicle; k is a feedback matrix in the control law; a. the0、B20、B10Is a state parameter matrix of the vehicle, which is determined by the dynamic state parameters of the vehicle; Δ A, Δ B2、ΔB1The method is an uncertainty matrix of a vehicle transverse dynamic system and is used for representing parameter uncertainty of the system.
By searching for a suitable control law feedback matrix K, the closed-loop lateral dynamics system described in equation (2) is stabilized and the preset target pole position is within the ideal target pole region. In the scheme, the target control stability of the vehicle is adjusted by adjusting the target pole position of the transverse dynamic system so as to meet the use requirements of the unmanned vehicle under different working conditions.
In the scheme, a linear matrix inequality method is selected to describe the pole position of the target of the transverse dynamical system on a complex plane, and the linear matrix inequality region is a region D which is described by the following expression in the complex plane:
Figure BDA0002374100820000065
in the formula: c is a complex plane; gamma, gamma are two symmetrical real matrixes in the complex plane domain; s is an operator in the complex plane.
Characteristic matrix f of the above linear matrix inequalityD(s) can be described by the following formula:
Figure BDA0002374100820000061
typical linear matrix inequality regions include sector domains, circular domains, rectangular domains, and the like. The target pole position of a general vehicle transverse dynamic system is located in a circle, so that the scheme selects a circle-domain linear matrix inequality region to describe the target pole region of the transverse dynamic system, and the steady-state and transient performance of the vehicle transverse dynamic system can be observed conveniently.
Let the target pole position of the vehicle lateral dynamics system be located in a circle with center (-q,0) and radius r, where (-q,0) is a point located in the complex plane, then the linear matrix inequality expression of the circle is:
Figure BDA0002374100820000062
the expression of the feature matrix of the circular domain is:
Figure BDA0002374100820000063
FIG. 2 shows a schematic diagram of the linear matrix inequality of a circular domain in a complex planar domain, with the center of the circle being at (-q,0) and the radius of the circular domain being r.
the selection of the circle region location where the target pole location is located (i.e., the target pole region) directly determines the handling performance of the vehiclenIs the target natural frequency of the vehicle lateral dynamics system. If the target pole region is located within the circle region as shown in FIG. 2, then there is
Figure BDA0002374100820000071
q-r is less than or equal to xi omeganmaking the minimum value of target damping ratio ξ of the vehicle transverse dynamic system be a and the minimum value of product of target damping ratio and target natural frequency be b, then using the parameters of centre position and radius of target pole region and othersExpression of formula (la):
Figure BDA0002374100820000072
in the formula: theta is an included angle between a tangent line of the circular domain led out from the origin of the complex plane domain and a horizontal axis of the complex plane domain.
Through analysis and experimental tests, vehicle data are sorted and counted to obtain the corresponding relation between the typical working condition, the target performance and the target pole of the unmanned vehicle, and the general conclusion is as follows:
taking the working condition that the unmanned vehicle transports goods in the off-road environment as an example, at this time, the unmanned vehicle needs higher handling stability and higher yaw damping ratio (namely, damping ratio of the vehicle lateral dynamic system) to enhance the safety of goods transportation, then the target pole position of the lateral dynamic system should have higher dynamic stability and higher damping ratio, namely, the target pole region (circular region) should be closer to the left side of the complex plane region and have a smaller radius.
Taking the working condition that the unmanned vehicle fights in the off-road environment as an example, higher maneuvering maneuverability and lower yaw damping ratio are needed at the moment to increase the flexibility of battlefield maneuvering, the target pole position of the transverse dynamic system should have lower dynamic stability and lower damping ratio at the moment, namely, the target pole area should be closer to the right side of the complex plane area and have a larger radius;
taking the working condition that the unmanned vehicle searches in the urban environment as an example, a higher operation stability and a lower yaw damping ratio are needed at the moment to balance the operation stability and the maneuverability under the urban searching working condition, and the target pole position of the transverse dynamic system should have higher dynamic stability and a lower damping ratio at the moment, namely, the target pole area should be closer to the left side of the complex plane area and have a larger radius;
taking the working condition that the unmanned vehicle transports in the narrow environment as an example, at this time, higher maneuvering maneuverability and higher yaw damping ratio are needed to improve the maneuvering maneuverability in the narrow environment, then the target pole position of the lateral dynamic system should have lower dynamic stability and higher damping ratio, that is, the target pole area should be closer to the right side of the complex plane area and have a smaller radius.
And (3) searching a proper control law feedback matrix K by a target active yaw moment calculation module in a control layer on the upper layer of the chassis through the dynamics model containing uncertainty and the target pole position, so that the closed-loop transverse dynamics system described in the formula (2) is stable and the target pole position is in an ideal target pole area. And then obtaining the active yaw moment input u (t) ═ Kx (t) according to the calculated feedback matrix K, namely obtaining the vehicle target active yaw moment.
Referring to fig. 3, the calculated target active yaw moment will be distributed to each of the independently driven wheels. The driving force distribution and slip ratio control of the independently driven wheels directly affect the running ability and handling stability of the vehicle. As is known from the basic principles of tire mechanics, the adhesion margin of a tire is directly proportional to the vertical load acting on the tire. Therefore, to maximize the vehicle's ride capacity and handling stability, the driving force distribution to each individual drive wheel should be proportional to the vertical load on each wheel.
See fig. 3, arrow F at the centroid positionXTThe target total driving force of the whole vehicle given by the unmanned vehicle intelligent decision or path planning unit is shown, and a rotating arrow M positioned at the position of the mass center of the vehicledesThe target active yaw moment of the whole vehicle is shown, the dotted circles positioned on the wheels show the vertical load of the wheels of the unmanned vehicle at the moment, and the arrows positioned on the wheels show the driving force (longitudinal driving force) distributed after the driving force distribution module in the lower control layer of the chassis calculates at the moment. Meanwhile, the vertical load of each wheel can be approximately obtained through calculation of the suspension stiffness by assuming that each wheel suspension shock absorber of the unmanned vehicle is provided with a displacement sensor and can obtain the vertical stroke of each wheel. To achieve the driving force distribution of the independently driven wheels in terms of the vertical load ratio of the tires, a driving force distribution ratio function for the left and right side wheels is defined:
Figure BDA0002374100820000081
in the formula: fx11Is the left front wheel driving force; fx12Is the right front wheel driving force; fx21Is the left rear wheel drive force; fx22Is the right rear wheel drive force; fz11Vertical force of the left front wheel; fz12Is vertical force of the right front wheel; fz21Vertical force of the left rear wheel; fz22Is the vertical force of the right rear wheel; k is a discrete time; kappalA proportional function is allocated to the driving force of the left wheel; kapparA proportional function is allocated to the driving force of the right wheel.
Target total driving force F of vehiclexTTarget active yaw moment MdesAnd the respective wheel driving forces are in the following relationship:
Figure BDA0002374100820000082
in the formula: b is the vehicle wheel track; lfThe distance from the center of mass of the vehicle to the front axle; lrThe distance from the center of mass of the vehicle to the rear axle; δ is a wheel angle (each wheel angle is the same).
According to the above equation, the driving force distribution result of each of the independently driven wheels is:
Figure BDA0002374100820000091
according to the above equation, the distribution of the driving forces of the wheels in accordance with the target total driving force and the target active yaw moment can be accomplished. According to the overall control architecture shown in fig. 1, after each wheel is driven, the wheel enters the independent driving wheel slip rate control module and the actuator control layer, so as to complete the closed loop of the whole dynamic control system.
In summary, the above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (4)

1. The method for controlling the relaxation static stability dynamics of the unmanned vehicle is characterized in that a target active yaw moment required for realizing the preset target pole position is calculated through the preset target pole position and the current vehicle state parameter;
and then distributing the calculated target active yaw moment to each independent driving wheel of the unmanned vehicle, so that the unmanned vehicle obtains vehicle dynamic performance corresponding to the preset target pole position.
2. The unmanned vehicle relaxation static stability dynamics control method of claim 1, wherein the calculation of the target active yaw moment is performed by the method of:
the control law of the active yaw moment of the unmanned vehicle is as follows:
u(t)＝Kx(t) (1)
in the formula: x (t) is a transverse dynamic state parameter of the unmanned vehicle; u (t) is yaw moment input; k is a feedback matrix in the control law;
establishing a two-degree-of-freedom dynamic model of the unmanned vehicle containing parameter uncertainty:
Figure FDA0002374100810000011
in the formula: w (t) is the steering wheel angle input of the front wheel and the rear wheel; a. the0、B20、B10The state parameter matrix of the unmanned vehicle is determined by the dynamic state parameters of the unmanned vehicle; Δ A, Δ B2、ΔB1The uncertainty matrix is an uncertainty matrix of the unmanned vehicle transverse dynamics system and is used for representing parameter uncertainty;
describing a target pole region of the unmanned vehicle transverse dynamic system by adopting a circular domain linear matrix inequality region;
then based on a robust control method, calculating the feedback matrix K according to the two-degree-of-freedom dynamic model containing uncertainty and a preset target pole position, and enabling the preset target pole position to be in the described target pole region;
after the feedback matrix K is obtained, the target active yaw moment of the unmanned vehicle is u (t) ═ Kx (t).
3. The unmanned vehicle relaxation static stability dynamics control method of claim 1 or 2, wherein when the unmanned vehicle is an all-wheel independently driven unmanned vehicle, i.e. four wheels of the unmanned vehicle are independently driven wheels:
the driving force distribution proportion function of the left side wheel and the right side wheel of the unmanned vehicle is as follows:
Figure FDA0002374100810000012
in the formula: fx11Is the left front wheel driving force; fx12Is the longitudinal driving force of the right front wheel; fx21Is the left rear wheel drive force; fx22Is the right rear wheel drive force; fz11Vertical force of the left front wheel; fz12Is vertical force of the right front wheel; fz21Vertical force of the left rear wheel; fz22Is the vertical force of the right rear wheel; k is a discrete time; kappalA proportional function is allocated to the driving force of the left wheel; kapparA proportional function is allocated to the driving force of the right wheel;
target total driving force F of unmanned vehiclexTTarget active yaw moment MdesAnd the driving force relation of each wheel is as follows:
Figure FDA0002374100810000021
in the formula: b is the vehicle wheel track; lfThe distance from the center of mass of the vehicle to the front axle; lrThe distance from the center of mass of the vehicle to the rear axle; delta is a wheel corner;
the driving force distribution result of each of the independently driven wheels is:
Figure FDA0002374100810000022
4. an unmanned vehicle relaxation static stability dynamics control system employing the dynamics control method of any one of the above claims 1 to 3, characterized in that the dynamics control system comprises: the control system comprises a control instruction layer, a chassis upper control layer, a chassis lower control layer, an actuating mechanism control layer and a state parameter feedback layer;
the control instruction layer is used for sending a chassis control instruction to a chassis upper control layer, and the chassis control instruction comprises: a target steering mode, a target wheel angle, a target total driving force, a target total braking force;
the upper control layer of the chassis comprises a target instruction resolving module and a yaw moment calculating module; after the chassis upper control layer receives the chassis control instruction, the target instruction resolving module resolves the chassis control instruction, the yaw moment calculating module calculates a target active yaw moment, and then the resolved target instruction and the calculated target yaw moment are sent to the chassis lower control layer; when the yaw moment calculation module calculates the target active yaw moment, the target active yaw moment required for realizing the preset closed-loop target pole position is calculated through the preset closed-loop target pole position and the current vehicle state parameters fed back by the vehicle state parameter feedback layer on the basis of the vehicle dynamic model;
the lower chassis control layer calculates the longitudinal driving force of each independent driving wheel according to the target total driving force in the control instruction and the target active yaw moment calculated by the upper chassis control layer, and then sends corresponding control information to the execution mechanism control layer according to the calculated longitudinal driving force of each independent driving wheel; the chassis lower control layer also sends corresponding control information to the executing mechanism control layer according to the resolved target instruction; meanwhile, the chassis lower control layer also controls the slip rate of each independent driving wheel by controlling the driving motor of each independent driving wheel;
the executing mechanism control layer realizes the control of the executing mechanisms in the wire-controlled steering system, the wire-controlled driving system and the wire-controlled braking system according to the received control information of the chassis lower layer control layer;
the vehicle state parameter feedback layer is used for monitoring dynamic state parameters of the vehicle in real time and feeding back the dynamic state parameters to the upper control layer of the chassis; the dynamic state parameters of the vehicle include: vehicle speed, yaw rate, center of mass slip angle, motor torque, and motor speed.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111797467A (en) * 2020-06-12 2020-10-20 北京理工大学 Design method for vehicle-mounted control layout of unmanned vehicle platform
CN113246749A (en) * 2021-07-14 2021-08-13 北京理工大学 Multi-wheel/multi-shaft independent driving electric automobile multi-target dynamics control method

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103034124A (en) * 2012-12-15 2013-04-10 江苏大学 Automotive chassis integrated system generalized inverse internal model controller and construction method
EP2905193A1 (en) * 2012-10-01 2015-08-12 Hitachi Automotive Systems, Ltd. Vehicle motion control device
CN107139775A (en) * 2017-04-26 2017-09-08 江苏大学 A kind of electric car direct yaw moment control method based on Non-smooth surface technology
CN107179686A (en) * 2017-05-10 2017-09-19 江苏大学 A kind of distributed-driving electric automobile lateral stability high-order variable structure control method based on gray prediction
CN109291806A (en) * 2018-09-20 2019-02-01 合肥工业大学 The deviation supplementary controlled system and control method of In-wheel motor driving automobile
CN110228462A (en) * 2019-05-17 2019-09-13 吉林大学 Four-wheel hub motor driven electric vehicle Yaw stability control method
CN110395120A (en) * 2019-08-14 2019-11-01 厦门金龙联合汽车工业有限公司 A kind of weaving control method of four-wheel distribution driving car
CN110466604A (en) * 2019-08-29 2019-11-19 南京林业大学 Hub motor driven electric vehicle Differential Driving turns to and the control method of stability
CN110481338A (en) * 2019-07-23 2019-11-22 武汉理工大学 A kind of hub motor vehicle disablement control method and entire car controller
CN112224036A (en) * 2020-10-28 2021-01-15 北京理工大学 Four-wheel driving torque distribution method and system for distributed driving electric vehicle

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2905193A1 (en) * 2012-10-01 2015-08-12 Hitachi Automotive Systems, Ltd. Vehicle motion control device
CN103034124A (en) * 2012-12-15 2013-04-10 江苏大学 Automotive chassis integrated system generalized inverse internal model controller and construction method
CN107139775A (en) * 2017-04-26 2017-09-08 江苏大学 A kind of electric car direct yaw moment control method based on Non-smooth surface technology
CN107179686A (en) * 2017-05-10 2017-09-19 江苏大学 A kind of distributed-driving electric automobile lateral stability high-order variable structure control method based on gray prediction
CN109291806A (en) * 2018-09-20 2019-02-01 合肥工业大学 The deviation supplementary controlled system and control method of In-wheel motor driving automobile
CN110228462A (en) * 2019-05-17 2019-09-13 吉林大学 Four-wheel hub motor driven electric vehicle Yaw stability control method
CN110481338A (en) * 2019-07-23 2019-11-22 武汉理工大学 A kind of hub motor vehicle disablement control method and entire car controller
CN110395120A (en) * 2019-08-14 2019-11-01 厦门金龙联合汽车工业有限公司 A kind of weaving control method of four-wheel distribution driving car
CN110466604A (en) * 2019-08-29 2019-11-19 南京林业大学 Hub motor driven electric vehicle Differential Driving turns to and the control method of stability
CN112224036A (en) * 2020-10-28 2021-01-15 北京理工大学 Four-wheel driving torque distribution method and system for distributed driving electric vehicle

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
李刚等: "四轮独立转向/独立电驱动汽车四轮", 《机械设计与制造》 *
黄彩霞等: "轮毂电机驱动汽车区域极点配置横向稳定性控制", 《汽车工程》 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111797467A (en) * 2020-06-12 2020-10-20 北京理工大学 Design method for vehicle-mounted control layout of unmanned vehicle platform
CN113246749A (en) * 2021-07-14 2021-08-13 北京理工大学 Multi-wheel/multi-shaft independent driving electric automobile multi-target dynamics control method
CN113246749B (en) * 2021-07-14 2021-11-05 北京理工大学 Multi-wheel/multi-shaft independent driving electric automobile multi-target dynamics control method

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