CN112373459A - Method for controlling upper-layer motion state of four-hub motor-driven vehicle - Google Patents

Method for controlling upper-layer motion state of four-hub motor-driven vehicle Download PDF

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CN112373459A
CN112373459A CN202011132443.8A CN202011132443A CN112373459A CN 112373459 A CN112373459 A CN 112373459A CN 202011132443 A CN202011132443 A CN 202011132443A CN 112373459 A CN112373459 A CN 112373459A
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CN112373459B (en
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翟丽
张雪莹
侯宇涵
莫昱明
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Beijing Institute of Technology BIT
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/02—Control of vehicle driving stability
    • 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
    • B60L15/32—Control or regulation of multiple-unit electrically-propelled vehicles
    • 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
    • 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
    • B60L2240/42—Drive Train control parameters related to electric machines
    • B60L2240/423—Torque
    • 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
    • B60W2050/0028—Mathematical models, e.g. for simulation
    • B60W2050/0031—Mathematical model of the vehicle
    • 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
    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/08—Electric propulsion units
    • B60W2710/083—Torque
    • 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
    • B60W2720/00—Output or target parameters relating to overall vehicle dynamics
    • B60W2720/40—Torque distribution

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  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Automation & Control Theory (AREA)
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  • Steering Control In Accordance With Driving Conditions (AREA)
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Abstract

A method for controlling the upper layer motion state of a four-hub motor-driven vehicle is characterized in that dynamic adjustment of a vehicle motion state reference value is realized based on fuzzy control, a comprehensive reference value is obtained by modifying a yaw angular velocity reference value, the design of self-adaptive combined control of a mass center side drift angle and a yaw angular velocity can be effectively simplified, and comprehensive coordination of the maneuverability and the stability of the vehicle under different attachment conditions is facilitated. The upper-layer motion controller based on the improved sliding mode control method, which is established in the method, can effectively realize the joint control of motion state quantities such as longitudinal vehicle speed, yaw velocity, mass center and side slip angle, has small buffeting and high response speed while ensuring the control precision, improves the adaptability of motion control to external disturbance and system parameter change to a certain extent, and ensures the good tracking effect of the vehicle on each reference motion state. The resulting torque distribution thus provided may ensure good handling stability of the vehicle under different attachment conditions.

Description

Method for controlling upper-layer motion state of four-hub motor-driven vehicle
Technical Field
The invention relates to the technical field of distributed drive vehicle control, in particular to a control method for realizing stable operation of a four-wheel-hub motor drive vehicle under different adhesion coefficients and variable adhesion coefficient road conditions.
Background
The driving/braking torques of the four driving wheels of the four-hub motor-driven vehicle can be independently controlled, and the control of the steering stability in the steering process can be more favorably realized. At present, direct yaw moment control (DYC) is mostly adopted for controlling the operation stability of the in-wheel motor driven vehicle, and the DYC can achieve good stability control effect in both linear and nonlinear working areas of a tire. The control strategy of the control stability based on the DYC mainly comprises two control structures of integrated control and layered control. The layered control mainly comprises upper-layer motion control and lower-layer torque distribution control, wherein the upper-layer motion controller generates target control force and torque according to a driver model command, and the lower-layer torque distribution controller generates torque commands of all driving wheels according to the target control force and torque. The upper layer motion control usually uses the motion state of the vehicle when turning as the controlled variable, and calculates the force and moment to be applied to the vehicle by a suitable control method according to the deviation between the state reference quantity given by the reference model and the fed back actual quantity. However, the existing upper layer motion control mainly has the following problems:
1. most upper-layer motion control only reflects control over the yaw rate of the vehicle, the influence of the centroid yaw angle on the operation stability is not considered, and joint control over the centroid yaw angle and the yaw rate is lacked;
2. most upper-layer motion control sets reference values for yaw angular velocity and centroid slip angle and controls the yaw angular velocity and centroid slip angle, only restricts dynamic parameters, and does not realize accurate control of the yaw angular velocity and centroid slip angle;
3. most upper-layer motion control has over-high requirements on centroid slip angle estimation and tire model precision, weight coefficients are difficult to determine, physical meanings are lacked, and system setting is inconvenient;
4. at present, the influence of a road adhesion coefficient on upper layer motion control is less considered in research, the influence of the response of a centroid yaw angle and a yaw angular velocity on vehicle operation stability control is different under different adhesion coefficients, and the self-adaptive control on the road adhesion is difficult to realize by the conventional method for jointly controlling the centroid yaw angle and the yaw angular velocity.
Disclosure of Invention
In view of the above, in order to solve the above technical problems in the upper layer motion state control method of the existing four-hub motor driven vehicle, the present invention provides an upper layer motion state control method of a four-hub motor driven vehicle, which specifically includes the following steps:
the method comprises the steps that firstly, a seven-degree-of-freedom vehicle dynamic model comprising longitudinal, lateral, transverse and four wheel rotational degrees of freedom is established for a four-hub motor driven vehicle;
step two, determining state variables reflecting vehicle motion characteristics: setting constraint conditions according to different road attachment conditions, determining reference values of the longitudinal vehicle speed and the centroid slip angle, and determining a reference value of the yaw rate by combining a one-dimensional fuzzy control rule;
step three, aiming at classical sliding mode control, introducing an error accumulation term and establishing an improved sliding mode control method;
fourthly, determining a longitudinal force equation and a yaw moment equation required by the steering motion based on the vehicle dynamic model established in the first step;
step five, obtaining an upper layer motion controller of the target longitudinal force based on the improved sliding mode control method in the step three and the longitudinal force equation determined in the step four, and realizing the following control of the longitudinal speed of the vehicle on the longitudinal speed reference value;
and step six, obtaining an upper layer motion controller of the target yaw moment based on the improved sliding mode control method established in the step three and the yaw moment equation determined in the step four, and realizing the tracking control of the yaw rate on the yaw rate reference value.
And step seven, distributing lower-layer moment, obtaining expected four-wheel torque according to the target longitudinal force and the target yaw moment, and distributing the command to the four motor controllers to realize direct control of the four-wheel hub motor-driven vehicle.
Further, the seven-degree-of-freedom vehicle dynamics model established in the first step can be expressed as the following equation:
Figure BDA0002735581190000021
wherein, Vx、VyAnd gamma respectively represent the longitudinal vehicle speed, lateral vehicle speed and yaw rate of the vehicle,
Figure BDA0002735581190000022
and
Figure BDA0002735581190000023
respectively corresponding derivatives of each parameter; fxijAnd FyijRepresents the longitudinal and lateral forces to which each tire is subjected, wherein i ∈ { f, r } represents front and back, and j ∈ { l, r } represents left and right;
wherein, the coefficient matrix Bx、ByRespectively as follows:
Figure BDA0002735581190000024
Figure BDA0002735581190000025
where m is the vehicle mass, δfFor the front wheel turning angle, a and b represent the front and rear wheelbase of the vehicle, respectively, d is half of the wheelbase, IzRepresenting the yaw moment of inertia.
Further, the step two of determining the reference values of the longitudinal vehicle speed, the centroid slip angle and the yaw rate specifically includes:
assuming a linear relationship between the longitudinal acceleration of the vehicle and the angular displacement of the pedals, the reference longitudinal speed V of the vehiclex-desCan be expressed in the following form:
Figure BDA0002735581190000031
wherein, Vx0At an initial speed, axdLongitudinal acceleration, t time;
let the steering angle of the front wheel be deltafThe steady-state gain of yaw rate is GγYaw rate steady state response gamma of the vehiclessHas the following forms:
Figure BDA0002735581190000032
wherein, KfAnd KrRespectively representing the cornering stiffness of the front and rear tires, and L representing the distance from a front axle to a rear axle of the vehicle; for steady-state steering processes, there are
Figure BDA0002735581190000033
Vehicle lateral acceleration may be expressed as
Figure BDA0002735581190000034
Considering the constraints from the road adhesion conditions, there is | ay| ≦ μ g, thus:
Figure BDA0002735581190000035
wherein mu is a road surface adhesion coefficient, and g is a gravity acceleration;
integrating the above-mentioned driver input and road surface adhesion influence, and reserving a certain adhesion margin, vehicle yaw angular velocity gamma-desThe reference values of (a) have the following form:
Figure BDA0002735581190000036
similarly, the centroid offset angle beta is referred todesThe solution can also be obtained by the method;
taking into account the yaw moment MzThe influence on the state control is introduced into a two-degree-of-freedom dynamic model as a control quantity, and the following can be obtained:
Figure BDA0002735581190000037
when yaw moment MzWhen the centroid side slip angle is 0, the good stability of the vehicle can be ensured, and the steady-state response gamma of the yaw angular velocity is realized at the moment'ssHas the following forms:
Figure BDA0002735581190000038
thus, the corresponding reference yaw angular velocity γ -desHas the following forms:
Figure BDA0002735581190000041
introducing a weight factor k (beta) epsilon [0,1]For two reference yaw rates gamma-desAnd gamma'-desCarrying out balance to obtain a reference comprehensive yaw velocity
Figure BDA0002735581190000042
Has the following forms:
Figure BDA0002735581190000043
wherein k (beta) is calculated by a one-dimensional fuzzy controller, and the fuzzy rule is as follows:
TABLE 1 one-dimensional fuzzy control rule
Figure BDA0002735581190000044
Wherein, the 5-type fuzzy subsets are respectively small (ES), small (S), medium (M), large (B) and large (EB). The main design principles of the fuzzy rule are: when β is small, k (β) should be large to preferentially control γ, improving the drivability of the vehicle; when β is large, k (β) should be small to suppress β mainly, ensuring the stability of the vehicle.
Further, the step three of establishing an improved sliding mode control method specifically includes:
take a single-input single-output nonlinear system as an example:
Figure BDA0002735581190000045
wherein u is the control input and b is a coefficient associated with the system model;
the slip form was constructed as follows:
Figure BDA0002735581190000046
for a classical sliding mode control method, the constant velocity approach rate is taken (the saturation function is not considered temporarily), and the following steps are provided:
Figure BDA0002735581190000047
the control law can be derived as follows:
Figure BDA0002735581190000048
wherein, x and x-desRespectively, the state variable and its expected value, e represents the error of the two,
Figure BDA0002735581190000049
a derivative of the expected value; λ is a constant coefficient; epsilon is a constant velocity approach rate coefficient;
the error accumulation term k ^ edt is introduced into a control law, and the control law of the improved sliding mode method has the following forms:
Figure BDA00027355811900000410
wherein ε, λ, k need to satisfy the following relationship:
ε≥χ-k∫edt·sgns
k＝κ·sgn(∫edt·sgns)
sgns＝sgn(e+λ∫edt)≈sgn(∫edt)
wherein, k is more than 00, x is more than 0, and k is more than 0; thus, sgn (≈ edt · sgns) ═ 1, and k ═ κ > 0.
Further, the equations for the longitudinal force and yaw moment required for the steering motion in the fourth step are of the form:
Figure BDA0002735581190000051
wherein ξx、ξyAnd xizUncertainty terms for external interference, model simplification, etc., FRRepresenting the sum of external forces acting on the center of mass, such as slope resistance, air resistance, etc., Fxd、FydAnd MzdThe vehicle longitudinal force, the lateral force, and the yaw moment generated by the tire longitudinal force are respectively shown.
Further, the upper layer motion controller for obtaining the target longitudinal force in the fifth step specifically includes the following steps:
based on an improved sliding mode control method, the sliding mode is taken as follows:
Figure BDA0002735581190000052
wherein the subscript vx represents a parameter relating to the vehicle speed in the longitudinal direction, and x represents the longitudinal direction;
and the longitudinal force equation established in the fourth step is combined to obtain:
Figure BDA0002735581190000053
wherein the superscript "·" represents the derivative of the corresponding parameter;
taking the constant velocity approach rate and introducing an error accumulation control termThen the target longitudinal force FxdHas the following forms:
Figure BDA0002735581190000054
further, the upper layer motion controller for obtaining the target yaw moment in the sixth step specifically includes the following steps:
taking the following slip form surface:
Figure BDA0002735581190000055
wherein the subscript γ represents a parameter relating to yaw moment;
and the yaw moment equation established in the fourth step is combined to obtain the following result:
Figure BDA0002735581190000061
taking the constant velocity approach rate, introducing an error accumulation control term and a target yaw moment MzdHas the following forms:
Figure BDA0002735581190000062
further, the lower layer moment distribution in the seventh step specifically includes the following steps:
taking the tire adhesion utilization rate as a stability optimization target, selecting the square sum of the adhesion utilization rate of each tire to construct an optimization target function, wherein the specific form is as follows:
Figure BDA0002735581190000063
considering the constraints from ground adhesion, the tire longitudinal force also needs to satisfy the friction circle constraint:
Figure BDA0002735581190000064
wherein, muijAnd FzijRespectively representing the road surface adhesion coefficient and the vertical load borne by each tire;
substituting the target longitudinal force and the target yaw moment obtained in the fifth step and the sixth step into a target function, and eliminating any two variables to obtain:
Figure BDA0002735581190000065
the optimal solution of the tire force can be obtained by an analytical method
Figure BDA0002735581190000066
The electric wheel output torque is optimally demodulated based on the tire force, the final torque distribution is completed, and the control on the operation stability of the vehicle is realized.
Compared with the prior art, the method provided by the invention at least has the following beneficial effects:
(1) the method provided by the invention realizes dynamic adjustment of the reference value of the vehicle motion state based on fuzzy control, obtains the comprehensive reference quantity by modifying the reference value of the yaw angular velocity, can effectively simplify the design of self-adaptive combined control of the centroid side drift angle and the yaw angular velocity, and is beneficial to comprehensively coordinating the maneuverability and the stability of the vehicle under different attachment conditions.
(2) The upper-layer motion controller based on the improved sliding mode control method can effectively realize the combined control of motion state quantities such as longitudinal vehicle speed, yaw angular velocity, mass center and side slip angle, has small buffeting and high response speed while ensuring the control precision, improves the adaptability of motion control to external disturbance and system parameter change to a certain extent, and ensures the good tracking effect of a vehicle on each reference motion state.
(3) The force and the moment obtained by the previous stage are distributed to the four hub motors through the single-stage optimal distribution controller, so that the final torque distribution is completed, and the good operation stability of the vehicle under different attachment conditions can be ensured.
Drawings
FIG. 1 is a block flow diagram of a method provided by the present invention;
FIG. 2 is a schematic diagram of a seven-degree-of-freedom dynamic model of a four-hub motor-driven vehicle;
FIG. 3 is a schematic diagram of a two-degree-of-freedom dynamic model of a four-hub motor-driven vehicle;
FIG. 4 is a diagram of a double travel path setup;
FIG. 5 is a simulation result of a double-shift line working condition under a high adhesion road surface;
FIG. 6 is a simulation result of a double-shift line working condition under a low adhesion road surface;
FIG. 7 is a sinusoidal input plot of steering wheel angle;
FIG. 8 is a simulation result of a sine input condition of a steering wheel corner of a high-adhesion road surface;
FIG. 9 is a simulation result of a low-adhesion road surface steering wheel corner sine input condition.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a method for controlling the upper layer motion state of a four-hub motor-driven vehicle, which specifically comprises the following steps as shown in figure 1:
the method comprises the steps that firstly, a seven-degree-of-freedom vehicle dynamic model comprising longitudinal, lateral, transverse and four wheel rotational degrees of freedom is established for a four-hub motor driven vehicle; the concrete form of the model is shown in FIG. 2;
step two, determining state variables reflecting vehicle motion characteristics: setting constraint conditions according to different road attachment conditions, and determining reference values of longitudinal vehicle speed, centroid slip angle and yaw angular speed(ii) a Taking into account the yaw moment MzThe influence on the state control can be introduced into a two-degree-of-freedom dynamic model shown in fig. 3 as a control quantity, and a reference value of the yaw rate is determined by combining a one-dimensional fuzzy control rule;
step three, aiming at classical sliding mode control, introducing an error accumulation term and establishing an improved sliding mode control method;
fourthly, determining a longitudinal force equation and a yaw moment equation required by the steering motion based on the vehicle dynamic model established in the first step;
step five, obtaining an upper layer motion controller of the target longitudinal force based on the improved sliding mode control method in the step three and the longitudinal force equation determined in the step four, and realizing the following control of the longitudinal speed of the vehicle on the longitudinal speed reference value;
and step six, obtaining an upper layer motion controller of the target yaw moment based on the improved sliding mode control method established in the step three and the yaw moment equation determined in the step four, and realizing the tracking control of the yaw rate on the yaw rate reference value.
And step seven, distributing lower-layer moment, obtaining expected four-wheel torque according to the target longitudinal force and the target yaw moment, and distributing the command to the four motor controllers to realize direct control of the four-wheel hub motor-driven vehicle. Fig. 4-9 show a specific example of the method provided by the present invention, using Matlab/Simulink simulation experiments, and table 2 shows the set vehicle and motor parameters:
TABLE 2 vehicle and Motor parameters
Figure BDA0002735581190000081
In order to integrally evaluate the effectiveness of the control stability adaptive control strategy, closed-loop and open-loop working condition simulation of a driver is performed under different vehicle speeds and road attachment conditions, and the control effect and reliability of the proposed adaptive control strategy (called adaptive control for short) are analyzed compared with other stability control strategies. The comparison strategy comprises the following steps: 1) the strategy is called as 'speed control' for short, an upper-level motion control layer only controls longitudinal speed without controlling lateral motion, and a lower-level torque control layer adopts a torque average distribution method without controlling slip ratio; 2) the control method is characterized in that the control strategy is a 'general control' strategy, the upper-level motion control layer adopts a classical sliding mode control method to realize the control of the yaw velocity, the mass center slip angle and the vehicle speed, but the self-adaptive adjustment of the attachment coefficient such as a motion state reference value, a weight coefficient and the like is not considered, and the lower-level torque control layer adopts a torque average distribution method and does not control the slip ratio.
Fig. 4 shows a double shift line condition path data set.
Fig. 5(a) - (b) depict the driving trajectory and speed response of a vehicle under different handling stability control strategies, respectively. It can be seen that the three control strategies under the high-adhesion road surface can ensure the good tracking effect of the vehicle on the expected track and the target speed. Among them, the vehicle running speed is most stable under adaptive control, and the influence of steering operation is least, reflecting the best speed control effect.
Fig. 5(c) - (d) show the response of the yaw rate and the centroid slip angle of the vehicle, respectively. In which the actual response of the adaptive control and the general control have a small deviation from the desired value. In the speed control, however, the deviation between the desired value and the both values is large, but the deviation is within the acceptable range as a whole.
FIG. 5(e) is a phase diagram of the vehicle centroid slip angle and its rate of change for different control strategies. The control effect of the control stability of the speed control, general control and self-adaptive control strategies is better and better as can be seen from the concentration degree of the lower plane curve relative to the origin in each control strategy in the figure.
Fig. 5(f) - (g) show the output torque of each electric wheel under the speed control, general control and adaptive control strategies, respectively. The speed control strategy does not consider the control of the lateral and yaw movement of the vehicle, the torque output does not form an additional yaw moment, and the driving torque is minimum; adaptive control and general control strategies use wheel reversal to create a large additional yaw moment, with the maximum value of the adaptive control output torque being relatively small.
Fig. 6(a) depicts the driving trajectory of a vehicle under different steering stability control strategies, wherein the vehicle under speed control starts to run with gradually diverging side-to-side oscillations after a second lane change (at about 9 s), when the driver almost loses steering and the vehicle is unstable. In contrast, the vehicle track deviation error under the adaptive control is minimum, and the best track tracking control effect is presented.
Fig. 6(b) - (d) show the vehicle speed, yaw rate and centroid slip response for each control strategy, respectively. It can be seen that the deviation amount of each motion state quantity from the expected value under the adaptive control is minimum, which indicates that the effect of the adaptive control on the motion state quantity is the best. The divergence phenomenon of each motion state quantity starts to appear at the later stage of the working condition under the speed control, and the stability of the vehicle cannot be ensured at the moment. The control effect of the general control is between the two controls.
FIG. 6(e) is a phase plane diagram of the vehicle centroid slip angle and its rate of change. It can be seen from the figure that the adaptive control and the general control are gradually far away from the original point compared with the phase plane curves under the speed control, which shows that the control stability control effect of the three control strategies is sequentially worse.
Fig. 6(f) - (h) show the output torque of the electric wheels under each control strategy. Under the speed control, the output torque begins to gradually diverge at the later stage of the working condition and tends to be unstable. Compared with a general control strategy, the self-adaptive control can self-adaptively adjust the motion control reference value and the torque distribution weight, and the maximum value of the output torque is slightly smaller.
Fig. 7 is a steering wheel angle sine input diagram.
Fig. 8(a) depicts the driving trajectory of the vehicle under different steering stability control strategies, and fig. 8(b) - (d) show the vehicle's speed, yaw rate, and centroid slip angle responses, respectively. It can be seen that the offset of each quantity from the expected value is the smallest under the adaptive control, the offset is the largest under the speed control, and the control result shows that the motion control layer adopting the improved sliding mode control method has the best control effect.
As can be seen from the phase plane of the centroid slip angle and the change rate thereof of the vehicle shown in fig. 8(e), the phase plane curve under the adaptive control and the general control is gradually far from the origin in comparison with the phase plane curve under the speed control, which indicates that the control effects of the three kinds of control stability are sequentially deteriorated, and the adaptive control stability control effect is optimal.
Fig. 8(f) - (g) show the output torque of the electric wheels under each control strategy. The speed control output torque peak value is small, but the control accuracy of the motion state quantity is sacrificed to some extent. Compared with a common control strategy, the self-adaptive control can self-adaptively adjust the torque distribution weight, the distributed torque of each wheel is relatively average, and the peak value and the average value of the output torque are relatively small.
FIGS. 9(a) and (b) depict the trajectory and speed of the vehicle under different handling stability control strategies, respectively, wherein the lateral displacement of the vehicle is minimized and the speed of the vehicle is most stable under adaptive control; the lateral displacement is maximized under speed control, and the vehicle speed, although somewhat affected by steering, can be maintained substantially at the target value.
Fig. 9(c) and (d) show the response of the yaw rate and the centroid slip angle of the vehicle, respectively. It can be seen that the amount of deviation between the yaw-rate response and the desired value under adaptive control is small, and the value of the vehicle's centroid slip angle is always kept within a small region. In contrast, the general control strategy has a slightly inferior motion control effect and a least inferior speed control effect, but since the lateral force requirement of the vehicle on the tire only just reaches the adhesion limit, as can be seen from the phase plane of the vehicle mass center slip angle and the change rate thereof shown in fig. 9(e), each control strategy can still better ensure the steering stability of the vehicle. The phase plane curve of the self-adaptive control is more concentrated on the origin, and the control effect of the self-adaptive control is optimal.
Fig. 9(f) - (h) show the output torque of the electric wheels under each control strategy. It can be seen that the peak value and the average value of the speed control output torque are minimum, but the speed control output torque sacrifices the motion control effect to a certain extent, and an additional yaw moment cannot be formed to control the lateral and yaw motion of the vehicle. By adjusting the torque distribution weight coefficient, the self-adaptive control has smaller integral output torque peak value and fluctuation compared with a common control strategy.
It should be understood that, the sequence numbers of the steps in the embodiments of the present invention do not mean the execution sequence, and the execution sequence of each process should be determined by the function and the inherent logic of the process, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.

Claims (8)

1. A method for controlling the upper motion state of a four-hub motor-driven vehicle is characterized by comprising the following steps: the method specifically comprises the following steps:
the method comprises the steps that firstly, a seven-degree-of-freedom vehicle dynamic model comprising longitudinal, lateral, transverse and four wheel rotational degrees of freedom is established for a four-hub motor driven vehicle;
step two, determining state variables reflecting vehicle motion characteristics: setting constraint conditions according to different road attachment conditions, determining reference values of the longitudinal vehicle speed and the centroid slip angle, and determining a reference value of the yaw rate by combining a one-dimensional fuzzy control rule;
step three, aiming at classical sliding mode control, introducing an error accumulation term and establishing an improved sliding mode control method;
fourthly, determining a longitudinal force equation and a yaw moment equation required by the steering motion based on the vehicle dynamic model established in the first step;
step five, obtaining an upper layer motion controller of the target longitudinal force based on the improved sliding mode control method in the step three and the longitudinal force equation determined in the step four, and realizing the following control of the longitudinal speed of the vehicle on the longitudinal speed reference value;
and step six, obtaining an upper layer motion controller of the target yaw moment based on the improved sliding mode control method established in the step three and the yaw moment equation determined in the step four, and realizing the tracking control of the yaw rate on the yaw rate reference value.
And step seven, distributing lower-layer moment, obtaining expected four-wheel torque according to the target longitudinal force and the target yaw moment, and distributing the command to the four motor controllers to realize direct control of the four-wheel hub motor-driven vehicle.
2. The method of claim 1, wherein: the seven-degree-of-freedom vehicle dynamics model established in the first step can be expressed as the following equation:
Figure FDA0002735581180000011
wherein, Vx、VyAnd gamma respectively represent the longitudinal vehicle speed, lateral vehicle speed and yaw rate of the vehicle,
Figure FDA0002735581180000012
and
Figure FDA0002735581180000013
respectively corresponding derivatives of each parameter; fxijAnd FyijRepresents the longitudinal and lateral forces to which each tire is subjected, wherein i ∈ { f, r } represents front and back, and j ∈ { l, r } represents left and right;
wherein, the coefficient matrix Bx、ByRespectively as follows:
Figure FDA0002735581180000021
Figure FDA0002735581180000022
where m is the vehicle mass, δfFor the front wheel turning angle, a and b represent the front and rear wheelbase of the vehicle, respectively, d is half of the wheelbase, IzRepresenting the yaw moment of inertia.
3. The method of claim 2, wherein: the step two of determining the reference values of the longitudinal vehicle speed, the centroid slip angle and the yaw rate specifically comprises the following steps:
assuming a linear relationship between the longitudinal acceleration of the vehicle and the angular displacement of the pedals, the longitudinal speed reference value V of the vehiclex-desCan be expressed in the following form:
Figure FDA0002735581180000023
wherein, Vx0At an initial speed, axdLongitudinal acceleration, t time;
let the steering angle of the front wheel be deltafThe steady-state gain of yaw rate is GγYaw rate steady state response gamma of the vehiclessHas the following forms:
Figure FDA0002735581180000024
wherein, KfAnd KrRespectively representing the cornering stiffness of the front and rear tires, and L representing the distance from a front axle to a rear axle of the vehicle;
for steady-state steering processes, there are
Figure FDA0002735581180000025
Vehicle lateral acceleration may be expressed as
Figure FDA0002735581180000026
Considering the constraints from the road adhesion conditions, there is | ay| ≦ μ g, thus:
Figure FDA0002735581180000027
wherein mu is a road surface adhesion coefficient, and g is a gravity acceleration;
integrating the above-mentioned driver input and road surface adhesion influence, and reserving a certain adhesion margin and vehicle yaw angular speed gamma-desThe reference values of (a) have the following form:
Figure FDA0002735581180000031
similarly, the centroid slip angle beta is referenced-desThe method is also used for solving;
taking into account the yaw moment MzThe influence on the state control is introduced into a two-degree-of-freedom dynamic model as a control quantity, and the following can be obtained:
Figure FDA0002735581180000032
when yaw moment MzWhen the centroid side slip angle is 0, the good stability of the vehicle can be ensured, and the steady-state response gamma of the yaw angular velocity is realized at the moment'ssHas the following forms:
Figure FDA0002735581180000033
thus, the corresponding reference yaw rate γ'-desHas the following forms:
Figure FDA0002735581180000034
introducing a weight factor k (beta) epsilon [0,1]For two reference yaw rates gamma-desAnd gamma'-desCarrying out balance to obtain a comprehensive yaw rate reference value
Figure FDA0002735581180000035
Has the following forms:
Figure FDA0002735581180000036
wherein k (beta) is calculated by a one-dimensional fuzzy controller, and whether to preferentially control gamma or inhibit beta for k (beta) is determined according to beta.
4. The method of claim 3, wherein: the step three of establishing the improved sliding mode control method specifically comprises the following steps:
the sliding mode is constructed based on the nonlinearity of single input and single output as follows:
Figure FDA0002735581180000037
the constant approach rate is:
Figure FDA0002735581180000038
the control law is obtained as follows:
Figure FDA0002735581180000039
wherein, x and x-desRespectively representing the state variable and the expected value thereof, e represents the error of the state variable and the expected value thereof, and the superscript "·" represents the derivative of the corresponding parameter; λ is a constant coefficient; epsilon is a constant velocity approach rate coefficient;
the error accumulation term k ^ edt is introduced into a control law, so that the control law of the improved sliding mode method has the following form:
Figure FDA0002735581180000041
wherein ε, λ, k need to satisfy the following relationship:
ε≥χ-k∫edt·sgns
k＝κ·sgn(∫edt·sgns)
sgns＝sgn(e+λ∫edt)≈sgn(∫edt)
wherein, k is more than 0, x is more than 0, and k is more than 0; thus, sgn (≈ edt · sgns) ═ 1, and k ═ κ > 0.
5. The method of claim 4, wherein: the equations for the longitudinal force and yaw moment required to determine the steering motion in step four are of the form:
Figure FDA0002735581180000042
wherein ξx、ξyAnd xizUncertainty terms for external interference, model simplification, etc., FRRepresenting the sum of external forces acting on the center of mass, such as slope resistance, air resistance, etc., Fxd、FydAnd MzdThe vehicle longitudinal force, the lateral force, and the yaw moment generated by the tire longitudinal force are respectively shown.
6. The method of claim 5, wherein: the upper layer motion controller for obtaining the target longitudinal force in the fifth step specifically comprises the following steps:
based on an improved sliding mode control method, the sliding mode is taken as follows:
Figure FDA0002735581180000043
wherein the subscript vxRepresents a parameter relating to the longitudinal vehicle speed, x represents the longitudinal direction;
and the longitudinal force equation established in the fourth step is combined to obtain:
Figure FDA0002735581180000044
wherein the superscript "·" represents the derivative of the corresponding parameter;
obtaining the equal speed approach rate, introducing an error accumulation control term, and obtaining the target longitudinal force FxdHas the following forms:
Figure FDA0002735581180000045
7. the method of claim 6, wherein: the upper layer motion controller for obtaining the target yaw moment in the sixth step specifically comprises the following steps:
taking the following slip form surface:
Figure FDA0002735581180000051
wherein the subscript γ represents a parameter relating to yaw moment;
and the yaw moment equation established in the fourth step is combined to obtain the following result:
Figure FDA0002735581180000052
taking the constant velocity approach rate, introducing an error accumulation control term and a target yaw moment MzdHas the following forms:
Figure FDA0002735581180000053
8. the method of claim 7, wherein: the lower layer moment distribution in the seventh step specifically comprises the following steps:
taking the tire adhesion utilization rate as a stability optimization target, selecting the square sum of the adhesion utilization rate of each tire to construct an optimization target function, wherein the specific form is as follows:
Figure FDA0002735581180000054
considering the constraints from ground adhesion, the tire longitudinal force also needs to satisfy the friction circle constraint:
Figure FDA0002735581180000055
wherein, muijAnd FzijRespectively representing the road surface adhesion coefficient and the vertical load borne by each tire;
substituting the target longitudinal force and the target yaw moment obtained in the fifth step and the sixth step into a target function, and eliminating any two variables to obtain:
Figure FDA0002735581180000056
the optimal solution of the tire force can be obtained by an analytical method
Figure FDA0002735581180000057
The electric wheel output torque is optimally demodulated based on the tire force, the final torque distribution is completed, and the control on the operation stability of the vehicle is realized.
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