CN116424353B - Distributed automobile-based coordination control strategy for drive-by-wire chassis subsystem - Google Patents
Distributed automobile-based coordination control strategy for drive-by-wire chassis subsystem 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
- 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
- B60W10/00—Conjoint control of vehicle sub-units of different type or different function
- B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
- B60W10/08—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of electric propulsion units, e.g. motors or generators
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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
- B60W10/00—Conjoint control of vehicle sub-units of different type or different function
- B60W10/20—Conjoint control of vehicle sub-units of different type or different function including control of steering systems
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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
- B60W10/00—Conjoint control of vehicle sub-units of different type or different function
- B60W10/22—Conjoint control of vehicle sub-units of different type or different function including control of suspension systems
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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
- B60W50/0098—Details of control systems ensuring comfort, safety or stability not otherwise provided for
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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
- B60W2050/0002—Automatic control, details of type of controller or control system architecture
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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
- B60W2050/0002—Automatic control, details of type of controller or control system architecture
- B60W2050/0013—Optimal controllers
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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
- B60W2050/0019—Control system elements or transfer functions
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- 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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- 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
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- B60W2050/0028—Mathematical models, e.g. for simulation
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- 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
- B60W2540/00—Input parameters relating to occupants
- B60W2540/18—Steering angle
Abstract
The invention discloses a drive-by-wire chassis subsystem coordination control strategy based on a distributed automobile, which comprises the steps of firstly judging the running condition of the automobile by utilizing a self-adaptive steering wheel rotation angle threshold value, and when the automobile is in straight running, controlling the strategy to be an ASS independent control mode; when the vehicle enters steering, two sections representing the stable state of the vehicle are obtained based on bifurcation theory, state judgment is carried out by combining critical front wheel corner values, and a control strategy is adjusted in real time according to judgment results: if the vehicle is in a stable zone, the control strategy is an ASS+AFS composite control mode so as to improve stability and smoothness; if the vehicle is in an unstable zone, the control strategy is switched to an ASS+DYC composite control mode. Considering the influence of ASS on DYC and the optimization degree of four-wheel torque distribution under the limit working condition, the two are coordinated and controlled by adopting a game idea, so that the safety, stability and energy conservation of the vehicle under the dangerous condition are ensured, the functional conflict of subsystems is avoided, and the optimal control effect is achieved.
Description
Technical Field
The invention relates to the technical field, in particular to a drive-by-wire chassis subsystem coordination control strategy based on a distributed automobile.
Background
Distributed driving has great development potential as a novel electric automobile driving configuration. The configuration is characterized in that the hub motor is used as an actuator to independently drive a single wheel, so that the centralized distribution of the total required torque of the power system and the accurate control of the torque of the single wheel can be realized, the dynamic control is flexible, the active safety is high, and the control requirement under multiple working conditions is met. Active safety technologies currently applied to a chassis of a distributed driving electric automobile mainly comprise an Active Suspension Subsystem (ASS), a front wheel active steering subsystem (AFS), a direct yaw moment control subsystem (DYC) and the like. Because the coupling mechanism among all the subsystems is complex, the improper control strategy can cause functional conflict among the subsystems, and the performance of the whole vehicle is weakened. For example, AFS uses tire lateral forces to generate additional yaw moment to control vehicle yaw stability, but when DYC suddenly mediates, it can cause a large change in each tire longitudinal force, thereby affecting lateral force margin and further weakening control effect of AFS; for another example, when the DYC is operated, if a large additional yaw moment is generated, the roll stability of the vehicle body is instantaneously affected, and the control effect of the ASS is disturbed. Therefore, a reasonable coordination control strategy is very important, and can effectively reduce or even eliminate interference and conflict among subsystems, so that the performance of the whole chassis is optimal. Some existing patents are based on 8-wheel distributed electric drive vehicles, and AFS and DYC are coordinated and controlled through a layered framework of a decision layer, a coordination control layer and a torque distribution layer, so that the running stability of the vehicle can be effectively improved, but under a limit dangerous working condition, the coupling effect and the functional conflict between DYC and ASS are not considered, and the stability performance of the whole vehicle under the limit working condition cannot be ensured.
In the chassis coordination control strategy, the vehicle stability needs to be judged in real time so as to switch the control strategy in time. Most researches only aim at the vehicle stability under the steering working condition to carry out subsystem coordination control, neglect the condition that the vehicle is in straight line running for most of the time, and fail to give an accurate working condition switching mechanism, so that the sub-controller is not required to be started frequently, and the economic benefit and the driving experience are reduced. In addition, in the vehicle stability determination process, most studies have conducted coordinated control based on the vehicle body motion state as a determination basis, such asStable levelingThe vehicle longitudinal speed v which has great influence on subsystem working performance and changes in real time is seldom considered by the surface, the characteristic vehicle speed and the like x And road adhesion coefficient mu. The existing patent judges the current vehicle stable state based on the phase plane and combining the centroid slip angle and the derivative thereof, and utilizes fuzzy control to drive the front wheel rotation angle delta f And road adhesion coefficient mu is used as input to obtain a boundary function of a stable domain, and a coordination control strategy is further designed for the AFS and the DYC. Although the method improves the effect of controlling the vehicle stability under different working conditions, the vehicle speed v is lacked in the process of judging the stability x In (3) the control accuracy of the vehicle cannot be ensured.
For this reason, a drive-by-wire chassis subsystem coordination control strategy based on a distributed automobile is proposed.
Disclosure of Invention
The invention aims to provide a drive-by-wire chassis subsystem coordination control strategy based on a distributed automobile so as to solve the problems in the background art.
In order to achieve the above purpose, the present invention provides the following technical solutions: a drive-by-wire chassis subsystem coordination control strategy based on a distributed automobile comprises the following steps:
step one: judging whether the vehicle enters steering according to the self-adaptive steering wheel turning angle threshold delta;
step two: when the vehicle turns, the bifurcation saddle node position and critical front wheel corner value delta under different vehicle speeds are developed by utilizing bifurcation theory based on phase plane s And quantitatively analyzing the mapping relation of the road adhesion coefficient mu, and determining critical front wheel corner delta under different vehicle speeds and different road adhesion coefficients by utilizing a parameter bifurcation method and an MATCT tool box s And is composed of delta s Obtaining two control intervals which represent the transverse stable state of the vehicle during steering, wherein the two control intervals are respectively a stable interval and an unstable interval;
step three: when the vehicle is in a stable section, the control strategy is an ASS plus AFS composite control mode, and when the vehicle is in an unstable section, the control function is gradually disabled when the lateral force of the tire tends to be saturated by the AFS subsystem, so that the control strategy is switched to the ASS plus DYC composite control mode;
step four: carrying out coordinated control on the ASS and the DYC subsystem by adopting a Nash equilibrium game theory, and obtaining the optimal control quantity by solving a coupled algebraic Li-Ka equation set;
step five: based on the controller of the DYC subsystem in the step four, a layered control architecture is adopted, and the obtained expected additional yaw moment is reasonably and optimally distributed to four independently driven wheels through constraint.
Preferably, the calculation formula of the adaptive steering wheel angle threshold Δδ in the first step is as follows:
wherein: delta is the adaptive steering wheel angle threshold; k is a proportionality coefficient; mu is the road adhesion coefficient; v x Is the vehicle longitudinal speed.
Preferably, in the first step, whether the vehicle enters the steering is judged according to the adaptive steering wheel angle threshold Δδ, and the judging mode is as follows: when the driver manipulates the steering wheel angle delta under the preset speed and road adhesion coefficient of the vehicle w When the control strategy is smaller than the threshold delta, judging that the vehicle does not enter a steering state, and determining that the vehicle is in a straight running state, wherein the control strategy is an ASS single control mode; when the driver manipulates the steering wheel angle delta w And when the vehicle steering speed is greater than the threshold delta, judging that the vehicle enters a steering working condition.
Preferably, the bifurcation theory of the phase plane in the second step is to quantitatively analyze system parameters through a phase plane graph drawn by a nonlinear differential equation and bifurcation phenomena thereof, and the parameter bifurcation method is to calculate bifurcation by adopting bifurcation analysis software MATCT, wherein MATCT is a MATLAB software package for interactive bifurcation analysis of a power system, and an ODE solver of all standards of MATLAB can be accessed.
Preferably, in the second step, the stable section and the unstable section are judged as follows: by calculating the front wheel angle delta f Contrast front wheel angle delta f And critical front wheel angle delta s If the front wheel steering angle delta f Is smaller than the critical front wheel rotation angle delta s When the time is short, the time is a stable interval; if the front wheel rotates by delta f Is larger than the critical front wheel angle delta s In this case, the non-stable section is defined.
Front wheel corner delta f The calculation mode of the vehicle speed v is that the parameters such as the rotation angle of the rear wheel, the moment of inertia and the like are assumed to be unchanged, the rotation angle of the front wheel is taken as a bifurcation parameter for research, and different vehicle speeds v are selected x Determining corresponding critical front wheel steering angle values according to different road surface adhesion coefficients mu, obtaining a three-dimensional curved surface relation diagram of the three, and performing polynomial fitting, wherein the critical front wheel steering angle, the road surface adhesion coefficient mu and the longitudinal vehicle speed v x Is fitted to:
wherein: p is p i Fitting coefficients are respectively used.
Preferably, the subsystem of the ASS in the third step adopts random linear optimal control, the subsystem of the AFS adopts a synovial variable structure control decision to obtain the desired additional front wheel corner, and the subsystem of the DYC adopts a synovial variable structure control decision to obtain the desired additional yaw moment.
Preferably, in the fourth step, the performing coordinated control on the ASS and DYC subsystems by adopting a nash equilibrium game theory is to consider the ASS subsystem and DYC subsystem as two game players, obtain an optimal equilibrium solution by a game control nash equilibrium method, and establish the following quadratic cost function for each participant, where the formula of the quadratic cost function is as follows:
in the weighting matrix Q i ≥0，R ii > 0 and are all real symmetric matrices.
Preferably, the Nash equilibrium game theory in the fourth step is the optimal solution of both game partiesFor all possible solutions (U D ,U A ) The following conditions must be satisfied:
in the superscript * Nash equilibrium solution representing the corresponding participant;
a unique open loop optimal control solution can be solved for the linear quadratic differential game problem:
wherein: p (P) i For the solution of the licarpa's equation,optimal additional yaw moment control amount ΔM corresponding to DYC subsystem z ，/>Optimal additional roll moment control amount Δm corresponding to the ASS subsystem x ；
The equation in step four is shown as:
preferably, in the fifth step, the specific control manner is to reasonably distribute four-wheel torque based on the relation between the total vehicle driving torque and the driving wheel driving torque according to the optimal additional yaw moment control quantity solved by the DYC subsystem through the Nash equilibrium game theory, with the minimum sum of the tire utilization rates as an optimization target J, with the peak torque of the wheel hub motor and the road surface attachment condition as constraints, and the specified vehicle yaw rate is positive in the anticlockwise direction; wherein, considering the influence of the road adhesion coefficient μ, the optimization target J expression formula is as follows:
wherein: f (F) xi 、F yi Longitudinal force and lateral force of each wheel respectively;
the constraint expression formula is as follows:
0≤T xi ≤min(T m_max ,μF zi R)
-μRF zi ≤T xi ≤μRF zi
wherein: t (T) xi For each wheel torque, R is the wheel rolling radius, F zi Mu is the road adhesion coefficient, T, for each wheel vertical load m_max Is the peak torque of the hub motor.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention designs the self-adaptive steering wheel corner threshold value for judging the working condition, which can judge whether the vehicle is in a straight running working condition under the changing vehicle speed and road surface adhesion coefficient, provides a basis for switching the control strategy, and improves the triggering precision and economic benefit of the controller.
2. According to the invention, by utilizing the bifurcation theory, the vehicle stability judging method under the conditions of different limits such as low adhesion of a road surface, high vehicle speed and the like in the steering process is unified, the switching mechanism of the control mode is formulated based on the fitted critical front wheel corner value, the instability trend of the system is prejudged, all subsystems of the chassis are effectively coordinated, and the transverse stability of the vehicle can be fully improved.
3. In the invention, the ASS subsystem and the DYC subsystem are controlled in a layered and coordinated manner by utilizing the game theory, so that the functional conflict and interference between the two subsystems under dangerous working conditions are avoided, and the safety and stability performance of the whole vehicle are ensured to the greatest extent.
Drawings
FIG. 1 is a flow chart of a distributed drive based chassis subsystem coordination control strategy switching mechanism;
FIG. 2 is a graph of fitting results of critical front wheel corner values under different road adhesion coefficients at different vehicle speeds;
FIG. 3 is a seven degree of freedom automotive suspension model;
FIG. 4 is a schematic diagram of an AFS subsystem controller;
FIG. 5 is a schematic diagram of a DYC subsystem controller;
fig. 6 is a diagram of a game theory-based ASS and DYC hierarchical coordination control architecture.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one:
referring to fig. 1 to 6, a distributed automobile-based coordination control strategy for a drive-by-wire chassis subsystem includes the following steps:
step one: judging whether the vehicle enters steering according to the self-adaptive steering wheel turning angle threshold delta;
step two: when the vehicle turns, the bifurcation saddle node position and critical front wheel corner value delta under different vehicle speeds are developed by utilizing bifurcation theory based on phase plane s And quantitatively analyzing the mapping relation of the road adhesion coefficient mu, and determining critical front wheel corner delta under different vehicle speeds and different road adhesion coefficients by utilizing a parameter bifurcation method and an MATCT tool box s And is composed of delta s Obtaining two control intervals which represent the transverse stable state of the vehicle during steering, wherein the two control intervals are respectively a stable interval and an unstable interval;
step three: when the vehicle is in a stable section, the control strategy is an ASS-AFS composite control mode, stability and smoothness in the running process of the vehicle are improved, and when the vehicle is in an unstable section, the control function is gradually disabled when the lateral force of the tire tends to be saturated by the AFS subsystem, so that the control strategy is switched to the ASS-DYC composite control mode, and the safety and stability of the vehicle are further ensured;
step four: in order to cope with the extreme dangerous conditions under the unsteady state and consider the influence of an ASS subsystem on a DYC subsystem, the ASS and the DYC subsystem are coordinated and controlled by adopting a Nash equilibrium game theory, and the optimal control quantity is obtained by solving a coupled algebraic Li-Card equation set, so that the functional conflict among the subsystems is avoided, and the safety and stability of the vehicle under the extreme state are improved;
step five: based on the controller of the DYC subsystem in the step four, a layered control architecture is adopted, and the obtained expected additional yaw moment is reasonably and optimally distributed to four independently driven wheels through constraint.
Active Suspension System is an active suspension system, ASS for short.
Active Front Steering it is the active front wheel steering, abbreviated as AFS.
DirectYaw-movement Control is direct yaw Moment Control, abbreviated as DYC.
Embodiment two:
as shown in fig. 1 and fig. 2, the present embodiment provides a technical solution based on the first embodiment: the calculation formula of the self-adaptive steering wheel angle threshold delta in the first step is as follows:
wherein: delta is the adaptive steering wheel angle threshold; k is a proportionality coefficient; mu is the road adhesion coefficient; v x Considering the great danger that the road adhesion coefficient is in the range of 0-1 and the high-speed working condition under most conditions, the self-adaptive steering wheel angle threshold is inversely related to the square term of the vehicle speed and positively related to the road adhesion coefficient;
in the first step, whether the vehicle turns is judged according to the self-adaptive steering wheel turning angle threshold delta, and the judging mode is as follows: at a predetermined speed of a vehicle and on a road surfaceUnder the coefficient, when the driver manipulates the steering wheel to turn delta w When the control strategy is smaller than the threshold delta, judging that the vehicle does not enter a steering state, and determining that the vehicle is in a straight running state, wherein the control strategy is an ASS single control mode, so that the vertical dynamics performance of the vehicle is improved; when the driver manipulates the steering wheel angle delta w And when the vehicle steering speed is greater than the threshold delta, judging that the vehicle enters a steering working condition.
Embodiment III:
as shown in fig. 4 to 6, the present embodiment provides a technical solution based on the first embodiment: the bifurcation theory of the phase plane in the second step is to quantitatively analyze system parameters through a phase plane graph drawn by a nonlinear differential equation and bifurcation phenomena thereof, the parameter bifurcation method is to calculate bifurcation by adopting bifurcation analysis software MATCT, MATCT is a MATLAB software package for interactive bifurcation analysis of a power system, ODE solvers of all standards of MATLAB can be accessed, and the judging mode between the stable section and the unstable section in the second step is as follows: by calculating the front wheel angle delta f Contrast front wheel angle delta f And critical front wheel angle delta s If the front wheel steering angle delta f Is smaller than the critical front wheel rotation angle delta s When the time is short, the time is a stable interval; if the front wheel rotates by delta f Is larger than the critical front wheel angle delta s In this case, the non-stable section is defined.
Front wheel corner delta f The calculation mode of the vehicle speed v is that the parameters such as the rotation angle of the rear wheel, the moment of inertia and the like are assumed to be unchanged, the rotation angle of the front wheel is taken as a bifurcation parameter for research, and different vehicle speeds v are selected x Determining corresponding critical front wheel steering angle values according to different road surface adhesion coefficients mu, obtaining a three-dimensional curved surface relation diagram of the three, and performing polynomial fitting, wherein the critical front wheel steering angle, the road surface adhesion coefficient mu and the longitudinal vehicle speed v x Is fitted to:
wherein: p is p i Fitting coefficients are respectively adopted;
when the vehicle enters a steering working condition, quantitative analysis is carried out on system parameters by utilizing a phase plane graph and bifurcation thereof which are drawn by a nonlinear differential equation: before the saddle fork appears, the vehicle system is in an approximately linear stage, and after the saddle fork appears, the system is in a critical stable state; as the front wheel steering angle continues to be increased, the limit ring is further increased until the same-dormitory bifurcation occurs, the wheels are in an approximate saturated state, at the moment, the vehicle is extremely easy to be unstable and has accidents, and the state when the saddle bifurcation occurs, namely the corresponding front wheel steering angle is used as a critical threshold value to pre-judge the transverse stability change of the vehicle system;
obtaining two control sections representing the lateral stability of the vehicle during steering by using the critical front wheel steering angle value, namely a stable section and an unstable section respectively, according to delta s And switching the control strategy.
Current wheel rotation angle delta f Is smaller than the critical front wheel rotation angle delta s When the vehicle is in a stable zone, the control strategy is an ASS+AFS composite control mode, and the running stability and smoothness of the vehicle are improved;
current wheel rotation angle delta f Is larger than the critical front wheel angle delta s When the vehicle is in an unstable zone, the control strategy is switched to an ASS+DYC composite control mode in consideration of the fact that the control function of the AFS subsystem gradually fails and limit dangerous working conditions possibly occur when the lateral force of the tire tends to be saturated, so that the safety and stability of the vehicle are further ensured.
In addition, in order to prevent the vehicle control mode from being switched too frequently, the controller can judge that the vehicle has exited an unstable working condition only if the current wheel angle value is returned to the stable interval again and lasts for t seconds; wherein the magnitude of t is related to the type of vehicle and its use.
For each subsystem, ASS adopts random linear optimal control, a seven-degree-of-freedom automobile suspension model is shown in fig. 3, and the state space equation of the suspension system can be obtained as follows:
wherein: system state vectorW (t) is Gaussian white noise input matrix; control input matrix U (t) = (U) ai (t))，U ai (t) is the active suspension actuator force; m is m si For suspension mass, m wi For the wheel mass, c si K is the suspension damping coefficient si For suspension stiffness, k ti For tyre stiffness, x si 、x wi 、x gi Displacements of suspension, wheel and road surface, G 0 F is the road surface unevenness coefficient 0 For lower cut-off frequency, F 0 The matrix is input for the road surface.
Wherein the method comprises the steps of
Taking state variablesGet output variable +.>The state equation and the output equation can be written as follows:
wherein: a is that s 、B s 、C s 、D s For ASS augmentation system state matrix, U= (U) 1 U 2 ) T 、U 1 ＝(U ai (t)) T 、U 2 ＝(x gi ) T 。
Taking the smoothness and safety of the vehicle in running into consideration, taking the performance indexes of the suspension system as follows:
wherein: x is x wi For tyre displacement, (x) si -x wi ) For the dynamic travel of the suspension,for acceleration of the vehicle body->Is pitch angle rate, q 1 、q 2 、q 3 、ρ i Is the weight coefficient of each item.
Further, the above formula can be written as follows:
wherein: q, R, N is a weighted matrix of terms.
After the specific parameter value of the vehicle is determined, the optimal control feedback gain matrix K can be obtained by a Rika equation, and the form is as follows:
wherein: b (B) s1 Is ASS state matrix, B s2 A state matrix is input for the road surface.
Further, AFS adopts synovial membrane variable structure control to make real-time decision to obtain the expected additional front wheel corner.
Firstly, a linear two-degree-of-freedom vehicle model is established as a reference model, and a dynamics equation is expressed as follows:
wherein:
wherein: u=δ f Is the front wheel rotation angle, beta is the centroid side deflection angle, w r For yaw rate, k f 、k r Respectively the lateral deflection rigidity of the front shaft and the rear shaft, a is the distance from the mass center to the front shaft, b is the distance from the mass center to the rear shaft, I zz Is the moment of inertia about the Z-axis of the vehicle coordinate system.
As shown in the schematic diagram of the AFS subsystem controller in FIG. 4, the influence of the AFS subsystem on the slip angle of the mass center of the vehicle is remarkable, so that the control error of the slip angle of the mass center is selected as a slip form surface:
s＝β-β d
the derivation of the above is available:
substitution of formula (1) into formula (2) yields:
order theThe desired front wheel rotation angle is obtained as follows:
in order to prevent the disturbance and parameter uncertainty from affecting the above method, an index approach law is adopted to modify the equivalent control law into:
δ f_deal ＝δ f -k 1 s-k 2 sgn(s) (3)
wherein k is 1 、k 2 To control the gain and to be greater than 0, sgn () is a sign function.
Further, in order to attenuate the high frequency buffeting of the system, the saturation function is used to replace the sign function in equation (3), and the expected front wheel rotation angle is finally obtained as follows:
where p is the boundary slide film thickness, sat () is the saturation function and exists in the form:
thus, the additional front wheel angle is ultimately desired to be:
Δδ f ＝δ f_deal -δ sw /i
wherein delta sw For steering wheel angle input, i is steering mechanism transmission ratio.
Further, the DYC adopts a synovial variable structure control to make a real-time decision to obtain the desired additional yaw moment.
As shown in fig. 5, the DYC controller schematic diagram is that the DYC subsystem has a significant effect on the yaw rate of the vehicle and also has a certain effect on the centroid side offset angle, so that the difference between the actual yaw rate value and the ideal value and the difference between the actual centroid side offset angle value and the ideal value are selected as control errors based on the linear two-degree-of-freedom vehicle model, and the slip plane is defined as follows:
s＝(w r -w rd )+λ(β-β d )
the derivation of the above is available:
substitution of formula (1) into formula (4) yields:
order theThe desired additional yaw moment is:
in order to prevent the above formula from being influenced by disturbance and parameter uncertainty as much as possible, an exponential approach law is adopted:
ΔM z_deal ＝ΔM z -k 1 s-k 2 sgn(s)
wherein: k (k) 1 、k 2 To control the gain and to be greater than 0, sgn () is a sign function.
Further, in order to attenuate the high frequency buffeting of the system, the sign function in equation (27) is replaced with a saturation function, resulting in the desired additional yaw moment:
where p is the boundary slide film thickness, sat () is the saturation function and exists in the form:
the desired additional yaw moment, as determined by the DYC subsystem, is determined by reasonably optimizing the distribution to the four independently driven wheels, as will be described in more detail below.
Further, when the vehicle is in an unstable zone and the control strategy is switched to an ASS+DYC composite control mode, considering that functional conflict exists between ASS and DYC under the limit dangerous working condition, in order to avoid the reduction of the control performance of the whole vehicle, the Nash equilibrium game theory is adopted to carry out coordinated control on the ASS and the DYC, and the principle is shown in figure 6.
Embodiment four:
as shown in fig. 4 and fig. 6, the present embodiment provides a technical solution based on the first embodiment: and in the third step, the ASS subsystem adopts random linear optimal control, the AFS subsystem adopts a synovial membrane variable structure control decision to obtain the expected additional front wheel corner, and the DYC subsystem adopts a synovial membrane variable structure control decision to obtain the expected additional yaw moment.
Fifth embodiment:
as shown in fig. 5 and 6, the present embodiment provides a technical solution based on the first embodiment: in the fourth step, the coordinated control of the ASS and DYC subsystems by adopting the nash equilibrium game theory means that the ASS subsystem and DYC subsystem are regarded as two game players, and the optimal equilibrium solution is obtained by a game control nash equilibrium method, and the following quadratic cost function is established for each participant, wherein the quadratic cost function has the following formula:
in the weighting matrix Q i ≥0，R ii > 0 and are all real symmetric matrices;
the Nash equilibrium principle in the fourth step is the optimal solution of both game partiesFor all possible solutions (U D ,U A ) The following conditions must be satisfied:
in the superscript * Nash equilibrium solution representing the corresponding participant;
a unique open loop optimal control solution can be solved for the linear quadratic differential game problem:
wherein: p (P) i For the solution of the licarpa's equation,optimal additional yaw moment control amount ΔM corresponding to DYC subsystem z ，/>Optimal additional roll moment control amount Δm corresponding to the ASS subsystem x ；
The equation in step four is shown as:
example six:
as shown in fig. 1 and fig. 5, the present embodiment provides a technical solution based on the first embodiment: the specific control mode in the fifth step is to reasonably distribute four-wheel torque based on the relation between the total vehicle driving torque and the driving wheel driving torque according to the optimal additional yaw moment control quantity solved by the DYC subsystem through the Nash equilibrium game theory, with the minimum sum of the tire utilization rates as an optimization target J, with the peak torque of the wheel hub motor and the road surface attachment condition as constraints, and the anticlockwise direction of the yaw speed of the specified vehicle as positive; wherein, considering the influence of the road adhesion coefficient μ, the optimization target J expression formula is as follows:
wherein: f (F) xi 、F yi Longitudinal force and lateral force of each wheel respectively;
writing the above as a matrix norm form:
the constraint expression formula is as follows:
0≤T xi ≤min(T m_max ,μF zi R)
-μRF zi ≤T xi ≤μRF zi
wherein: t (T) xi For each wheel torque, R is the wheel rolling radius, F zi Mu is the road adhesion coefficient, T, for each wheel vertical load m_max Is the peak torque of the hub motor.
Combining the constraint conditions, the solution T can be solved xi The problem of (2) is converted into a weighted least squares programming problem, and the solution is carried out by using an interior point method:
wherein: t (T) ximin 、T ximax And respectively outputting upper and lower limits of torque constraint conditions of the driving wheels, and finally, inputting the solved optimal control quantity to corresponding actuators of the vehicle.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (9)
1. A drive-by-wire chassis subsystem coordination control strategy based on distributed automobile is characterized in that: the method comprises the following steps:
step one: judging whether the vehicle enters steering according to the self-adaptive steering wheel turning angle threshold delta;
step two: when the vehicle turns, the bifurcation saddle node position and critical front wheel corner value delta under different vehicle speeds are developed by utilizing bifurcation theory based on phase plane s And quantitatively analyzing the mapping relation of the road adhesion coefficient mu, and determining critical front wheel corner delta under different vehicle speeds and different road adhesion coefficients by utilizing a parameter bifurcation method and an MATCT tool box s And is composed of delta s Obtaining two control intervals which represent the transverse stable state of the vehicle during steering, wherein the two control intervals are respectively a stable interval and an unstable interval;
step three: when the vehicle is in a stable section, the control strategy is an ASS plus AFS composite control mode, and when the vehicle is in an unstable section, the control function is gradually disabled when the lateral force of the tire tends to be saturated by the AFS subsystem, so that the control strategy is switched to the ASS plus DYC composite control mode;
step four: carrying out coordinated control on the ASS and the DYC subsystem by adopting a Nash equilibrium game theory, and obtaining the optimal control quantity by solving a coupled algebraic Li-Ka equation set;
step five: based on the controller of the DYC subsystem in the step four, a layered control architecture is adopted, and the obtained expected additional yaw moment is reasonably and optimally distributed to four independently driven wheels through constraint.
2. A distributed automotive-based drive-by-wire chassis subsystem coordination control strategy as claimed in claim 1, wherein: the calculation formula of the self-adaptive steering wheel angle threshold delta in the first step is as follows:
wherein: delta is the adaptive steering wheel angle threshold; k is a proportionality coefficient; mu is the road adhesion coefficient; v x Is the vehicle longitudinal speed.
3. A distributed automotive-based drive-by-wire chassis subsystem coordination control strategy as claimed in claim 2, wherein: in the first step, whether the vehicle turns is judged according to the self-adaptive steering wheel turning angle threshold delta, and the judging mode is as follows: when the driver manipulates the steering wheel angle delta under the preset speed and road adhesion coefficient of the vehicle w When the control strategy is smaller than the threshold delta, judging that the vehicle does not enter a steering state, and determining that the vehicle is in a straight running state, wherein the control strategy is an ASS single control mode; when the driver manipulates the steering wheel angle delta w And when the vehicle steering speed is greater than the threshold delta, judging that the vehicle enters a steering working condition.
4. A distributed automotive-based drive-by-wire chassis subsystem coordination control strategy as claimed in claim 1, wherein: the bifurcation theory of the phase plane in the second step is to quantitatively analyze system parameters through a phase plane graph drawn by a nonlinear differential equation and bifurcation phenomena thereof, and the parameter bifurcation method is to calculate bifurcation by adopting bifurcation analysis software MATCT, wherein MATCT is a MATLAB software package for interactive bifurcation analysis of a power system, and an ODE solver of all standards of MATLAB can be accessed.
5. A distributed automotive-based drive-by-wire chassis subsystem coordination control strategy as claimed in claim 1, wherein: in the second step, the stable section and the unstable section are judged as follows: by calculating the front wheel angle delta f Contrast front wheel angle delta f And critical front wheel angle delta s If the front wheel steering angle delta f Is smaller than the critical front wheel rotation angle delta s When the time is short, the time is a stable interval; if the front wheel rotates by delta f Is larger than the critical front wheel angle delta s When the time is short, the time is a non-stable section;
front wheel corner delta f The calculation mode of the vehicle speed v is that the parameters such as the rotation angle of the rear wheel, the moment of inertia and the like are assumed to be unchanged, the rotation angle of the front wheel is taken as a bifurcation parameter for research, and different vehicle speeds v are selected x Adhesion coefficient mu of different road surfacesDetermining corresponding critical front wheel steering angle values, obtaining three-dimensional curved surface relation diagrams of the three, and then performing polynomial fitting, wherein the critical front wheel steering angle, road surface adhesion coefficient mu and longitudinal vehicle speed v x Is fitted to:
wherein: p is p i Fitting coefficients are respectively used.
6. A distributed automotive-based drive-by-wire chassis subsystem coordination control strategy as claimed in claim 1, wherein: and in the third step, the ASS subsystem adopts random linear optimal control, the AFS subsystem adopts a synovial membrane variable structure control decision to obtain the expected additional front wheel corner, and the DYC subsystem adopts a synovial membrane variable structure control decision to obtain the expected additional yaw moment.
7. A distributed automotive-based drive-by-wire chassis subsystem coordination control strategy as claimed in claim 1, wherein: in the fourth step, the coordination control of the ASS and DYC subsystems by adopting the nash equilibrium game theory is to consider the ASS subsystem and DYC subsystem as two game players, obtain an optimal equilibrium solution by controlling the nash equilibrium method through the game, and establish the following quadratic cost function for each participant, wherein the formula of the quadratic cost function is as follows:
in the weighting matrix Q i ≥0，R ii > 0 and are all real symmetric matrices.
8. The distributed automotive-based drive-by-wire chassis subsystem coordination control strategy of claim 7, wherein: the Nash equilibrium game theory in the fourth step is the optimal solution of both game partiesFor all possible solutions (U D ,U A ) The following conditions must be satisfied:
wherein superscript represents the nash equalization solution for the corresponding participant;
a unique open loop optimal control solution can be solved for the linear quadratic differential game problem:
wherein: p (P) i For the solution of the licarpa's equation,optimal additional yaw moment control amount ΔM corresponding to DYC subsystem z ，Optimal additional roll moment control amount Δm corresponding to the ASS subsystem x ；
The equation in step four is shown as:
9. a distributed automotive-based drive-by-wire chassis subsystem coordination control strategy as claimed in claim 1, wherein: the specific control mode in the fifth step is to reasonably distribute four-wheel torque based on the relation between the total vehicle driving torque and the driving wheel driving torque according to the optimal additional yaw moment control quantity solved by the DYC subsystem through the Nash equilibrium game theory, with the minimum sum of the tire utilization rates as an optimization target J, with the peak torque of the wheel hub motor and the road surface attachment condition as constraints, and the anticlockwise direction of the yaw speed of the specified vehicle as positive; wherein, considering the influence of the road adhesion coefficient μ, the optimization target J expression formula is as follows:
wherein: f (F) xi 、F yi Longitudinal force and lateral force of each wheel respectively;
the constraint expression formula is as follows:
0≤T xi ≤min(T m_max ,μF zi R)
-μRF zi ≤T xi ≤μRF zi
wherein: t (T) xi For each wheel torque, R is the wheel rolling radius, F zi Mu is the road adhesion coefficient, T, for each wheel vertical load m_max Is the peak torque of the hub motor.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109747434A (en) * | 2019-01-16 | 2019-05-14 | 浙江科技学院 | Distributed-driving electric automobile torque vector distributes control method |
| CN113911106A (en) * | 2021-10-11 | 2022-01-11 | 聊城大学 | Commercial vehicle transverse track following and stability cooperative control method based on game theory |
| CN114194202A (en) * | 2021-12-30 | 2022-03-18 | 江苏大学 | Vehicle stable state judgment method based on phase plane, chassis coordination control method and system |
| CN115179963A (en) * | 2022-07-18 | 2022-10-14 | 湖南大学 | Fault-tolerant control method, medium and system for lane changing of automatic driving vehicle and automobile |
Family Cites Families (1)
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109747434A (en) * | 2019-01-16 | 2019-05-14 | 浙江科技学院 | Distributed-driving electric automobile torque vector distributes control method |
| CN113911106A (en) * | 2021-10-11 | 2022-01-11 | 聊城大学 | Commercial vehicle transverse track following and stability cooperative control method based on game theory |
| CN114194202A (en) * | 2021-12-30 | 2022-03-18 | 江苏大学 | Vehicle stable state judgment method based on phase plane, chassis coordination control method and system |
| CN115179963A (en) * | 2022-07-18 | 2022-10-14 | 湖南大学 | Fault-tolerant control method, medium and system for lane changing of automatic driving vehicle and automobile |
Non-Patent Citations (3)
| Title |
|---|
| 基于AFS和DYC协调控制的车辆稳定性研究;田杰;高翔;陈宁;;机械设计(第10期);全文 * |
| 基于底盘多子系统协调控制的车辆稳定性控制;赵树恩;李玉玲;余强;;交通运输工程学报(第04期);全文 * |
| 考虑驾驶员特性的分布式驱动汽车合作博弈容错控制;张博涵;《工程科技Ⅱ辑》;第91-99页 * |
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