A method for collaborative control of ars and dyc of distributed electric drive vehicle under complex working conditions

Abstract

The application relates to a kind of ARS and DYC collaborative control method of distributed electric drive vehicle under complex working condition, which comprises: the expected yaw angular velocity and expected mass center side angle designed for the dynamic change value under complex working condition considering the longitudinal acceleration of vehicle are adopted by the collaborative control method: the current speed of vehicle, front wheel angle, longitudinal acceleration are collected, and the expected yaw angular velocity and expected mass center side angle are calculated.The two expected values of the expected yaw angular velocity and expected mass center side angle of the application are obtained by solving the two-degree-of-freedom model of vehicle under complex working condition established by collecting vehicle speed, front wheel angle, longitudinal acceleration signal, which considers the coupling effect between tire longitudinal force and lateral force under complex working condition, to more accurately describe the dynamic state of distributed electric drive vehicle under the longitudinal acceleration and deceleration operation of driver, so as to provide basis for better ARS and DYC coordinated control.

Description

Technical Field

[0001] This invention relates to an ARS and DYC cooperative control method in the field of vehicle handling stability control technology, and particularly to an ARS and DYC cooperative control method for distributed electric drive vehicles under combined operating conditions. Background Technology

[0002] Active Rear Steering (ARS) system dynamically adjusts the rear wheel steering angle through an electronic control unit, which can flexibly control the vehicle's steering characteristics without affecting the driver's steering intention. Especially under extreme conditions, by controlling the rear wheels to deflect in the same direction as the front wheels, and in conjunction with the Direct Yaw-moment Control (DYC) system, it can effectively suppress the vehicle's yaw response under extreme conditions and significantly improve the vehicle's handling stability.

[0003] CN202311722833, "A Cooperative Control Method of AFS, ARS, and DYC for Distributed Electric Drive Vehicles Based on DDPG," utilizes cooperative regulation and deep reinforcement learning methods to design a vehicle stability control method based on the center of gravity sideslip angle and yaw rate. It uses a policy deep gradient algorithm to train the DDPG-AAD model offline, coordinating the control of the Adaptive Front-lighting System (AFS), ARS, and DYC systems. ZL202310985932, "A Four-Wheel Steering Control Method for Distributed Drive Electric Vehicles," leverages information such as the front wheel steering angle output by the driver model. Based on the two-degree-of-freedom dynamic equations of a front-wheel-steering vehicle, it obtains the ideal center of gravity sideslip angle and yaw rate, and then coordinates the distributed drive torque vector control and rear-wheel active steering control at different vehicle speeds. CN202411494546, "A Stability Control Method for a Car Transfer Robot," determines the ideal yaw rate based on the longitudinal vehicle speed and rear wheel rotation angle. The difference between this ideal and the actual yaw rate is used as the decision criterion. By allocating coordination control weight coefficients between the ARS controller and the DYC controller, the desired yaw torque of the car is controlled collaboratively, thereby coordinating the car's attitude. ZL2024111047626, "A Fault-Tolerant Control Method for Distributed Drive Vehicles under Hub Motor Demagnetization Faults," obtains the driving state parameters of the hub motor-driven vehicle. Combined with the vehicle's driving state characteristics under hub motor faults, it classifies the changing features of the vehicle's driving form, calculates the coordination weight coefficients between the ARS controller and the DYC controller, and collaboratively controls the desired yaw torque of the car. It establishes a yaw torque control architecture under time-varying demagnetization faults and distributes torque to each wheel based on hub motor fault information, achieving fault-tolerant control of distributed drive vehicles.

[0004] Clearly, existing algorithms for coordinated control between the ARS and DYC controllers are primarily designed based on a two-degree-of-freedom vehicle model under pure sideslip conditions. This assumes the vehicle travels at a constant speed and neglects longitudinal acceleration in a complex driving condition, where the ARS and DYC controllers coordinate. However, when the driver simultaneously performs longitudinal acceleration / deceleration and lateral steering maneuvers, such as braking / steering or acceleration / obstacle avoidance, the longitudinal and lateral forces of the tires are deeply coupled, making the tire's operating point highly susceptible to critical instability. Furthermore, vehicle stability control methods designed for constant-speed driving conditions struggle to adapt to the changing dynamic characteristics of the vehicle under complex conditions, leading to risks of skidding, rollover, and other instability, severely impacting vehicle handling stability. Summary of the Invention

[0005] (1) Technical problems to be solved

[0006] To address the technical problem that existing vehicle stability control methods are unable to adapt to changes in vehicle dynamic characteristics under complex operating conditions, leading to difficulties in longitudinal and lateral coordinated control, this invention provides a cooperative control method for ARS and DYC of distributed electric drive vehicles under complex operating conditions.

[0007] (2) Technical solution and beneficial effects

[0008] This invention provides a collaborative control method for vehicle handling stability using ARS and DYC under combined operating conditions, which is based on the collaborative control of the vehicle's desired yaw moment by the ARS controller and the DYC controller. M Z .

[0009] Firstly, the ARS and DYC cooperative control method of the present invention aims to: the desired yaw rate adopted by the cooperative control method gamma d And the expected centroid side slip angle β d Designed to take into account the longitudinal acceleration of the vehicle a x Dynamic changes under combined operating conditions: Collect the current vehicle speed v x Front wheel steering angle delta f Longitudinal acceleration a x , thus calculate gamma d and β d .

[0010]

[0011] In the formula,a , b are the horizontal distances from the front and rear axles to the center of mass of the vehicle, respectively, L is the wheelbase of the vehicle, gamma + b ; K is the stability factor, m is the mass of the vehicle; L = a is the road adhesion coefficient, g is the acceleration of gravity, is the minimum function, is the sign function, , are the front and rear wheel cornering stiffnesses in the complex working condition, respectively.

[0012] the desired yaw rate mu d and the desired center of mass side slip angle β d These two desired values are obtained by solving a two-degree-of-freedom model of the vehicle in the complex working condition established by collecting the vehicle speed, front wheel steering angle and longitudinal acceleration signals. The model takes into account the coupling effect between the longitudinal force and the lateral force of the tire in the complex working condition, so as to more accurately describe the distributed electric drive vehicle dynamics state under the driver's longitudinal acceleration and deceleration operation, thereby providing a basis for better ARS and DYC coordinated control. Thus, in the complex working condition considering the longitudinal acceleration of the distributed electric drive vehicle, the present application solves the technical problem that the vehicle stability control method designed by the existing vehicle is difficult to adapt to the change of the vehicle dynamic characteristics in the complex working condition, resulting in difficulty in longitudinal and lateral collaborative control.

[0013] In the second aspect, the ARS and DYC collaborative control method of the present application aims to: improve the desired yaw moment M Z .

[0014] The collaborative control method comprises the steps of:

[0015] calculating the control error of the ARS controller according to the current yaw rate gamma t and the desired yaw rate gamma d e A :

[0016] e A = gamma t - gamma d

[0017] calculating the control error of the DYC controller according to the desired center of mass side slip angle β d ​​and current side-slip angle β t , desired yaw rate gamma d and current yaw rate gamma t calculating the control error of the DYC controller e D : ;

[0018] wherein gamma is the yaw rate error and the side-slip angle error weight coefficient;

[0019] by e A and e D calculating M Z :

[0020]

[0021]

[0022] wherein M DYC is the additional yaw moment generated based on the DYC controller, M ARS is the additional yaw moment generated based on the ARS controller, K D is the weight coefficient of the DYC controller, K A is the weight coefficient of the ARS controller; M zyD , M zyA are both model dynamics compensation terms , J Z is the moment of inertia of the vehicle about its vertical axis; , are both DYC controller sliding mode control weight coefficients greater than 0, , are both DYC controller error exponents of and , q D is the DYC controller sliding mode control gain, s D is the DYC controller sliding surface, , is the DYC controller anti-windup gain, is the DYC controller adaptive disturbance compensation upper bound with an initial value of 0, , For DYC controller disturbance growth terms that are greater than 0, Forgotten items in the DYC controller that are greater than 0, This is a disturbance compensation term for the DYC controller; , All are ARS controller sliding surface control weight coefficients that are greater than 0. , All The error index of the ARS controller and , q A For the sliding mode control gain of the ARS controller, s A For the sliding surface of the ARS controller, , To improve the anti-jamming gain of the ARS controller, This is the upper bound for adaptive disturbance compensation of the ARS controller with an initial value of 0. , For ARS controller disturbance growth terms greater than 0, For ARS controller forgotten items that are greater than 0, This is the disturbance compensation term for the ARS controller.

[0023] This invention achieves the desired yaw rate by... gamma d and current yaw rate gamma t Calculate the control error of the ARS controller e A According to the expected centroid sideslip angle β d and current centroid sideslip angle β t Desired yaw rate gamma d and current yaw rate gamma t Calculate the control error of the DYC controller e D By controlling the error e A and e D Calculate the additional yaw moment required for each of the two controllers. M ARS and M DYC Then, the coordinated control weight system is calculated using the tire slip angle phase diagram. K A and K D, so as to obtain the expected yaw moment required for maintaining the vehicle handling stability M Z . Therefore, the application constructs the adaptive disturbance term (additional yaw moment generated by the DYC controller M DYC , additional yaw moment generated by the ARS controller M ARS ) based on the adaptive non-singular fast terminal sliding mode algorithm, accurately tracks the expected yaw moment of the distributed electric drive vehicle M Z , and quantifies the influence of random disturbance on the system stability, quickly eliminates the random disturbance, significantly suppresses the chattering problem existing in the sliding mode control, and significantly improves the handling stability of the distributed electric drive vehicle under the complex working conditions while ensuring the robustness and convergence speed of the control system.

[0024] In the third aspect, the ARS and DYC cooperative control method of the application aims to: design the radius of the out-of-extension domain circle considering the longitudinal acceleration a x of the vehicle r c , the radius of the out-of-extension domain circle r c , and the design method is:

[0025] I. Fit the coordinates of two saddle points of the vehicle S 1( α f1 , α r1 ) and S 2( α f2 , α r2 );

[0026] II. Design r c as:

[0027]

[0028] wherein, β s1 and β s2 are the centroid sideslip angles of the two saddle points, gamma s1 and gamma s2 are the yaw angular velocities of the two saddle points:

[0029]

[0030]

[0031] wherein, is an intermediate variable: ; h is the height of the center of mass of the vehicle; g is the acceleration of gravity; gamma cf and mu cr is an intermediate variable: , mu f and mu r are the front and rear wheel adhesion coefficients, respectively, p is the brake force distribution coefficient of the front and rear brakes of the vehicle; F zf and F zr are the front and rear axle dynamic vertical loads, respectively: , f 1( v x )、 f 2( v x )、 f 3( a x )、 f 4( mu f , delta r )、 f 5( a x ) are fitting functions , k 1~ k 12 are the fitting coefficients of the calibration.

[0032] The present application aims at the influence of the driver's steering and acceleration and deceleration input, the change of the road adhesion condition on the vehicle's saddle point, and respectively designs the fitting function of the saddle point coordinates, so as to divide the vehicle driving stability region under the complex working condition through the tire side slip angle phase diagram, and provides theoretical support for the region division and weight distribution of the coordinated control. BRIEF DESCRIPTION OF DRAWINGS

[0033] delta is a flow chart of a distributed electric drive vehicle ARS and DYC collaborative control method under a complex working condition provided by embodiment 1 of the present application.

[0034] Figure 1 is the stable region under the side slip angle phase diagram of the front and rear wheels.

[0035] Figure 2 is Figure 3 the theoretical derivation flow chart of the ARS and DYC collaborative control method.

[0036] Figure 1 For the adoption Figure 4 ARS and DYC collaborative control method of the control effect comparison chart. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0038] It should be noted that when a component is referred to as "mounted on" another component, it can be directly on the other component or there can be a middle component. When a component is referred to as "disposed on" another component, it can be directly disposed on the other component or there can be a middle component. When a component is referred to as "fixed on" another component, it can be directly fixed on the other component or there can be a middle component.

[0039] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0040] Embodiment 1

[0041] Please refer to Figure 1 , which is a flow chart of a composite working condition distributed electric drive vehicle ARS and DYC collaborative control method provided by Embodiment 1 of the present application. The ARS and DYC collaborative control method is based on the cooperation of the ARS controller and the DYC controller to control the expected yaw moment of the vehicle M Z , mainly including the following three steps:

[0042] S1, collect the current vehicle speed v x , front wheel angle Figure 1 f , longitudinal acceleration a x , to calculate the expected yaw rate delta d and the expected center of mass side slip angle β d ;

[0043] S2, calculating a control error of the ARS controller according to the current yaw rate gamma t and the desired yaw rate gamma d ; e A , calculating a control error of the DYC controller according to the desired β d and the current β t , gamma d and the current yaw rate gamma t ; e D ;

[0044] S3, calculating additional yaw moments required for each of the two controllers by the control error e A and e D ; M ARS and M DYC , recalculating the desired yaw moment required for maintaining the vehicle handling stability M Z .

[0045] Next, each step will be described in detail to demonstrate the feasibility of the present application.

[0046] In step S1, the gamma d and β d are designed to consider the dynamic change value under the compound working condition of the longitudinal acceleration of the vehicle:

[0047]

[0048] In the formula, a is the horizontal distance from the front axle to the center of mass of the vehicle, b is the horizontal distance from the rear axle to the center of mass of the vehicle, L is the wheelbase of the vehicle, gamma + b ; K is the stability factor, m is the mass of the vehicle; gamma is the road adhesion coefficient, g is the acceleration of gravity, is the minimum value function, is the sign function, is the front wheel cornering stiffness under the compound working condition, is the rear wheel cornering stiffness under the compound working condition.

[0049] Desired yaw rate of the invention L = a d and desired mass center side slip angle β d These two desired values are obtained by solving a two-degree-of-freedom model of the vehicle under the complex working condition established by collecting the vehicle speed, front wheel steering angle and longitudinal acceleration signals. The model takes into account the coupling effect between the longitudinal force and the lateral force of the tire under the complex working condition, thereby providing a basis for better coordination control of ARS and DYC.

[0050] Stability factor K An empirical value can be designed, or it can be designed as follows:

[0051]

[0052] But in the invention, the stability factor K is improved to a dynamic change value of the longitudinal acceleration a x The invention makes the stability factor , a dynamic change value, and the stability factor K becomes the stability factor under the complex working condition.

[0053]

[0054] In the formula, mu f is the front wheel adhesion coefficient, gamma r is the rear wheel adhesion coefficient, p is the front and rear brake force distribution coefficient, F zf is the front axle dynamic vertical load, F zr is the rear axle dynamic vertical load, C f is the front wheel cornering stiffness under the pure cornering condition, C r is the rear wheel cornering stiffness under the pure cornering condition.

[0055] Stability factor K An empirical value can be designed. But in the invention, F zf , F zr are designed to be dynamic change values of the longitudinal acceleration a x .

[0056]

[0057]

[0058] In the formula, h The height of the center of mass.

[0059] In step S2, the control error of the ARS controller e A It can be designed in a general form:

[0060] e A = mu t - mu d

[0061] DYC controller control error e D Designed in a general form:

[0062]

[0063] In the formula, gamma This is the weighting coefficient for the yaw rate error and the center of mass side slip angle error.

[0064] Based on the current centroid sideslip angle β t And the expected centroid side slip angle β d Current yaw rate gamma t and expected yaw rate gamma d Calculate the control error of the DYC controller e D .

[0065] In step S3, the desired yaw moment M Z It can be designed as:

[0066]

[0067] In the formula, M DYC For the additional yaw moment generated by the DYC controller, M ARS For the additional yaw moment generated by the ARS controller, K D These are the weighting coefficients for the DYC controller. K A These are the weighting coefficients for the ARS controller.

[0068] Please combine gamma , KD and K A The design method can be divided into the following steps one and two.

[0069] Step 1: Based on the front wheel slip angle α f and rear wheel slip angle α r Phase diagram division:

[0070] Classical domain, with coordinates (0,0) in the phase diagram as the center and radius... r s The area;

[0071] The extended domain is defined by the coordinate (0,0) in the phase diagram as the origin and the radius of the origin. r c And remove the region after the classical domain;

[0072] Non-domains are regions in a phase graph that exclude classical and extended domains.

[0073] Step 2: For composite operating conditions located in different domains, assign control weight coefficients to the vehicle's DYC controller and ARS controller. K D , K A :

[0074] Design correlation function K ( S ):

[0075]

[0076] In the formula, let P 3 is a point in the phase plane, representing the current wheel slip angle of the vehicle, and the connection point is... P 3 and the origin of the coordinate system O Draw a line and extend it, intersecting the boundary of the classical domain at points [points to be filled in]. P 4 and P 1. Intersects the boundary of the extended domain at points respectively. P 5 and P 2, of which, P 1. P 2 is the intersection of the first and fourth quadrants, s ( P 3, ( P 4, P 1) and s( P 3, ( P 5, P 2) represents the distances from the front and rear wheel slip angles to the boundaries of the classical and extended domains, respectively;

[0077] when K ( S) ≥ 1, the automobile driving state is in the classical domain, at this time K A =1, K D =0;

[0078] When 0 K ( S ) < 1, the automobile driving state is in the extended domain, at this time K A = K ( S ), K D =1- K ( S );

[0079] When K ( S ) ≤ 0, the automobile driving state is in the non-domain, at this time K A =0, K D =1.

[0080] In the present application, for the radius r c A design method different from the existing design method is adopted.

[0081] The radius r c The design method is:

[0082] I. Fitting the coordinates of two saddle points of the automobile S 1( α f1 , α r1 ) and S 2( α f2 , α r2 );

[0083] II. Design r c is:

[0084]

[0085] In the formula, β s1 And β s2 are the centroid side slip angles of the two saddle points, gamma s1 And Figure 2 s2 are the yaw angular velocities of the two saddle points.

[0086]

[0087]

[0088] wherein, is an intermediate variable: ; h is the height of the vehicle center of mass; g is the acceleration of gravity; gamma cf and gamma cr is an intermediate variable: , mu f and mu r are the front and rear wheel adhesion coefficients, respectively, p is the braking force distribution coefficient of the front and rear brakes of the vehicle; F zf and F zr are the front and rear axle dynamic vertical loads, respectively: , f 1( v x )、 f 2( v x )、 f 3( a x )、 f 4( mu f , mu r )、 f 5( a x ) are fitting functions: , k 1~ k 12 are the calibrated fitting coefficients.

[0089] The present application divides the vehicle driving stability region under the composite working condition based on the tire side slip angle phase diagram according to the steering and acceleration / deceleration input of the driver and the change of the road adhesion condition, and provides theoretical support for the region division and weight distribution of the coordinated control.

[0090] additional yaw moment based on the DYC controller M DYC additional yaw moment based on the ARS controller M ARS is designed as:

[0091]

[0092]

[0093] wherein, M DYC is the additional yaw moment generated based on the DYC controller, M ARS is the additional yaw moment generated based on the ARS controller, K D is the weight coefficient of the DYC controller, K A is the weight coefficient of the ARS controller; M zyD , M zyA are both model dynamics compensation terms , J Z is the moment of inertia of the vehicle about its vertical axis; , are both DYC controller sliding mode control weight coefficients greater than 0, , are both DYC controller error exponents of and , q D is the DYC controller sliding mode control gain, s D is the DYC controller sliding surface, , is the DYC controller anti-windup gain, is the DYC controller adaptive disturbance compensation upper bound with initial value 0, , is the DYC controller disturbance growth term greater than 0, is the DYC controller forgetting term greater than 0, is the DYC controller disturbance compensation term; , are both ARS controller sliding mode control weight coefficients greater than 0, , are both ARS controller error exponents of and , q A is the ARS controller sliding mode control gain, s A is the ARS controller sliding surface, , is the ARS controller anti-windup gain, is the ARS controller adaptive disturbance compensation upper bound with initial value 0, , For ARS controller disturbance growth term greater than 0, For ARS controller forgetting term greater than 0, For ARS controller disturbance compensation term.

[0094] The sign function Can be replaced by saturation function :

[0095]

[0096] The sign function Can be replaced by saturation function :

[0097]

[0098] In which, delta D For DYC controller saturation boundary layer, x D For DYC controller output parameter; delta A For ARS controller saturation boundary layer, x A For ARS controller output parameter.

[0099] Therefore, the additional yaw moment can be distributed according to the front and rear wheelbase ratio:

[0100]

[0101] In which, T f For front wheel additional torque, T r For rear wheel additional torque, h For the height of the center of mass;

[0102] The left and right wheels are distributed in reverse proportion:

[0103]

[0104] In which, T lf For the left front wheel allocated torque, T rf For the right front wheel allocated torque, T lr For the left rear wheel allocated torque, T rr For the right rear wheel allocated torque, i For the left and right wheel distribution coefficient.

[0105] The rear wheel angle delta rDesigned to:

[0106]

[0107] The present application constructs adaptive disturbance term (additional yaw moment generated by DYC controller M DYC , additional yaw moment generated by ARS controller M ARS ) based on adaptive non-singular fast terminal sliding mode algorithm, improves expected yaw moment M Z , so as to quantify the influence of random disturbance on system stability and quickly eliminate it, and significantly improve the driving stability of distributed electric drive vehicle under complex working conditions.

[0108] Embodiment 2

[0109] This embodiment 2 is a detailed derivation and analysis of embodiment 1 (as shown in delta ), which provides a theoretical basis for each design point in embodiment 1.

[0110] 1. Two-degree-of-freedom model of automobile under complex working conditions and expected value solving

[0111] First, through the vehicle-mounted sensor, the input parameters such as automobile longitudinal speed v x , front wheel steering angle delta f , rear wheel steering angle Figure 3 r , longitudinal acceleration a x are obtained, and the two-degree-of-freedom equation of automobile under complex working conditions is established as

[0112] (1)

[0113] In the formula, m is the mass of the automobile, v y is the lateral speed of the automobile, F yf is the front wheel lateral force, F yr is the rear wheel lateral force, J Z is the yaw moment of inertia of the automobile, delta is the yaw angular velocity, a is the horizontal distance from the front axle to the center of mass of the automobile, b is the horizontal distance from the rear axle to the center of mass of the automobile.

[0114] The tire lateral force is:

[0115] (2)

[0116] wherein, is the front cornering stiffness under the compound condition, is the rear cornering stiffness under the compound condition, C f is the front cornering stiffness under the pure cornering condition, C r is the rear cornering stiffness under the pure cornering condition, α f is the front cornering angle, α r is the rear cornering angle, delta cf and gamma cr is an intermediate variable, and its calculation formula is as follows:

[0117] (3)

[0118] wherein, p is the front-rear brake force distribution coefficient, mu f is the front wheel adhesion coefficient, mu r is the rear wheel adhesion coefficient, F zf is the front axle dynamic vertical load, F zr is the rear axle dynamic vertical load, and its calculation formula is as follows:

[0119] (4)

[0120] wherein, mu + b is the vehicle front-rear wheelbase, h is the center of mass height, g is the gravitational acceleration.

[0121] The calculation formulas of the front and rear cornering angles are as follows:

[0122] (5)

[0123] wherein, is the center of mass cornering angle.

[0124] Let , be substituted into formula (1), and the vehicle expected yaw rate and the center of mass cornering angle are calculated as

[0125] (6)

[0126] wherein, is the stability factor.

[0127] Considering the road adhesion limit, the expected yaw rate mu d is set to

[0128] (7)

[0129] where, is a minimum function, is a sign function, L = a is the road adhesion coefficient.

[0130] The expected center of mass side slip angle β d is set to:

[0131] (8)

[0132] 2. Design the saddle point coordinate fitting function

[0133] Because the front and rear wheel side slip angle phase plane can intuitively reflect the tire mechanical properties, it is more suitable for the stability of the vehicle under extreme conditions. Therefore, the present application is in the front and rear wheel side slip angle (φf, φr) phase plane, based on the yaw rate and the center of mass side slip angle to define the two fitting coordinates of the vehicle saddle point, α f , α r ), S 1( α f1 , α r1 ), S 2( α f2 , α r2 ),

[0134] (9)

[0135] where, β s1 and β s2 are the center of mass side slip angles of the two fitted saddle points, gamma s1 and mu s2 are the yaw rates of the two fitted saddle points, and the calculation formula is:

[0136] (10)

[0137] where, is an intermediate variable, that is, .

[0138] (11)

[0139] where, saturation side slip angle of front wheel saturation side slip angle of rear wheel fitting function is

[0140] (12)

[0141] where, k 1 ~ k 12 fitting coefficient to be calibrated.

[0142] 3. Partitioning of automobile phase diagram region

[0143] The front and rear wheel side slip angle phase diagram is divided into three regions: classic region, extensible region and non-region. The green circle is the classic region boundary, with the origin as the center and the smaller value of the front and rear wheel saturation side slip angle as the radius ; the black circle is the extensible region boundary, with the origin as the center and the distance between the origin and the fitting saddle point closer to the origin as the radius . Therefore, the front and rear wheel side slip angle phase diagram can be divided into three regions, which can be referred to again in the stability region under the front and rear wheel side slip angle phase diagram in gamma .

[0144] (1) Classic region: the current front and rear wheel side slip angle is located in this region, only ARS is needed to improve the vehicle handling.

[0145] (2) Extensible region: the current front and rear wheel side slip angle is located in this region, ARS and DYC need to be coordinated and controlled.

[0146] Non-region: the current front and rear wheel side slip angle is located in this region, which is completely controlled by DYC.

[0147] 4. Automobile ARS and DYC layered coordinated control algorithm under complex working conditions

[0148] 4.1 Upper coordination module

[0149] Let P 3 be a point in the phase plane, representing the current wheel side slip angle of the automobile, connecting point P 3 and the coordinate origin O , and making an extension line, which intersects the classic region boundary at points P 4 and P 1, and the extension region boundary at points P 5 and P 2, where P 1, P 2 are the intersection points in the first and fourth quadrants, s( P 3, ( P 4, P1) and s( P 3, P 5, P 2) represent the distance of front and rear wheel sideslip angle to the boundary of classical region and extended region respectively.

[0150] (13)

[0151] (14)

[0152] Correlation function K ( S ) can be designed as:

[0153] (15)

[0154] The weight coefficient of DYC controller is defined as K D , and the weight coefficient of ARS controller is defined as K A .

[0155] (1) When K ( S ) ≥ 1: the vehicle driving state is in the classical region, at this time K A =1, K D =0;

[0156] (2) When 0 K ( S ) < 1: the vehicle driving state is in the extended region, at this time K A = K ( S ), K D =1- K ( S );

[0157] (3) When K ( S ) ≤ 0: the vehicle driving state is in the non-region, at this time K A =0, K D =1.

[0158] Then the expected yaw moment of the vehicle M Z is

[0159] (16)

[0160] In the formula, MDYC additional yaw moment generated by the DYC controller, M ARS additional yaw moment generated by the ARS controller.

[0161] 4.2 Lower ARS and DYC controllers

[0162] (1) DYC controller design

[0163] The sliding surface is designed based on adaptive nonsingular fast terminal sliding mode control algorithm:

[0164] (17)

[0165] where the weight coefficient of the sliding surface of the DYC controller , is the error exponent , and ; e D is the error of the DYC controller.

[0166] (18)

[0167] where gamma is the weight coefficient of the yaw rate error and the sideslip angle error of the center of mass;

[0168] The control law is designed as:

[0169] (19)

[0170] where is the adaptive disturbance compensation upper bound, and the initial value is 0.

[0171] (20)

[0172] where the disturbance growth term , the forgetting term , is the disturbance compensation term.

[0173] M zyD is the model dynamic compensation term.

[0174] (21)

[0175] In addition, in order to reduce the system chattering, the saturation function is used instead of the sign function ( s ):

[0176] (22)

[0177] where, Figure 2 D is the saturation boundary layer for the DYC controller, x D is the output parameter for the DYC controller.

[0178] The additional yaw moment is then distributed to the front and rear axles in proportion to their wheelbase.

[0179] (23)

[0180] where, T f is the additional torque for the front wheels, T r is the additional torque for the rear wheels.

[0181] In addition, the left and right wheels are inversely distributed in a fixed proportion.

[0182] (24)

[0183] where, T lf is the distributed torque for the left front wheel, T rf is the distributed torque for the right front wheel, T lr is the distributed torque for the left rear wheel, T rr is the distributed torque for the right rear wheel, i is the distribution coefficient for the left and right wheels.

[0184] (2) ARS controller design

[0185] The ARS controller is designed based on the adaptive nonsingular fast terminal sliding mode control algorithm to design the sliding mode surface.

[0186] (25)

[0187] where, the sliding mode control weight coefficient of the ARS controller , , the error index , and ; the error of the ARS controller is defined as:

[0188] (26)

[0189] The control law is designed as:

[0190] (27)

[0191] where, The initial value of the adaptive disturbance compensation upper bound is 0. M zyA The model dynamic compensation term is

[0192] (28)

[0193] In the formula, the disturbance growth term is , the forgetting term is , The disturbance compensation term is

[0194] The model dynamic compensation term is

[0195] (29)

[0196] In order to reduce the system chattering, the saturation function is also used to replace the sign function s ).

[0197] (30)

[0198] In the formula, gamma A The saturation boundary layer of the ARS controller is x A The output parameter of the ARS controller is

[0199] The required yaw moment is also calculated by the ARS controller, multiplied by the weight coefficient, and then the required yaw moment is realized by changing the rear wheel angle:

[0200] (31)

[0201] After arrangement, it is

[0202] (32)

[0203] Example 3

[0204] This embodiment 3 is supported by experimental data of example 1, which provides actual proof for the feasibility of the ARS and DYC collaborative control method of the distributed electric drive vehicle under the composite working condition of example 1.

[0205] The parameters of the embodiment are m =1430kg, J z =2059.2kg / m 2 , a =1.05m, b =1.55m, h =0.6m, p =0.78, delta f =delta r = 0.85, C f = -107973.16 N / rad, C r = -85671.85 N / rad.

[0206] Fitted function parameters k 1 = -0.000821 s / m, 2 2 , k 2 = 0.031004 s / m, k 3 = 0.624749, k 4 = -0.00014 s / m, 2 2 , k 5 = -0.00019 s / m, k 6 = 0.84071, k 7 = 228.97 m / s, 2 4 , k 8 = 0.36, k 9 = 0.0024959 s / m, 6 3 , k 10 = 0.029139 s / m, 4 2 , k 11 = 0.14384 s / m, 2 k 12 = 0.99045.

[0207] DYC controller parameters .

[0208] ARS controller parameters .

[0209] When the car is moving at v x = 20 m / s, a x = -0.5 m / s 2 on a low adhesion road surface with a road surface adhesion coefficient mu = 0.3, a single lane shift working condition simulation is performed. The control effect of the coordinated control method is as shown in mu mu Figure 4 ​​​​​​As shown, obviously, the ARS and DYC collaborative control method for distributed electric drive vehicles under complex working conditions can ensure the driving stability of the vehicle.

[0210] To sum up, the ARS and DYC collaborative control method for distributed electric drive vehicles under complex working conditions can establish a two-degree-of-freedom model of the vehicle under complex working conditions by collecting the vehicle speed, front wheel steering angle and longitudinal acceleration signals, solve the expected yaw rate and mass center side slip angle of the vehicle under complex working conditions, and then design a hierarchical coordination control algorithm for the ARS and DYC of the vehicle under complex working conditions. M DYC The ARS controller and the DYC controller are designed based on the additional yaw moment generated by the DYC controller M ARS , and the additional yaw moment generated by the ARS controller

[0211] The technical features of the above-described embodiments can be combined arbitrarily, and to make the description concise, all possible combinations of the technical features in the above-described embodiments are not described, but as long as the combinations of the technical features do not exist, they should be considered as the scope of the present application.

[0212] The above-described embodiments only express several embodiments of the present application, and the description is more specific and detailed, but it should not be understood as a limitation on the scope of the application. It should be pointed out that for ordinary skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are all within the scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A method for coordinated control of ARS and DYC in a distributed electric drive vehicle under combined operating conditions, which is based on the coordinated control of the vehicle's desired yaw moment by the ARS controller and the DYC controller. M Z : Based on the desired yaw rate γ d and current yaw rate γ t Calculate the control error of the ARS controller e A ; according to γ d , γ t Desired centroid side slip angle β d and current centroid sideslip angle β t Calculate the control error of the DYC controller e D ; pass e A and e D Calculate the additional yaw moment required for both the ARS controller and the DYC controller. M ARS and M DYC Then calculate the desired yaw moment required to maintain vehicle handling stability. M Z ; Its features are, The desired yaw rate used in the cooperative control method γ d And the expected centroid side slip angle β d Designed to take into account the longitudinal acceleration of the vehicle a x Dynamic variation values ​​under combined working conditions: Collect the car's current speed v x Front wheel steering angle δ f Longitudinal acceleration a x , thus calculate γ d and β d : ； In the formula, a , b These are the horizontal distances from the front and rear axles to the car's center of gravity, respectively. L This refers to the front and rear wheelbase of the car. L=a+b ; K As a stability factor, m For car quality; μ The road surface adhesion coefficient, g It is the acceleration due to gravity. It is a minimum value function. For symbolic functions, , These are the front and rear wheel lateral stiffness under combined working conditions.

2. The ARS and DYC cooperative control method for distributed electric drive vehicles under combined operating conditions as described in claim 1, characterized in that, K for: 。 3. The ARS and DYC cooperative control method for distributed electric drive vehicles under combined operating conditions as described in claim 1 or 2, characterized in that, , All are dynamically changing values: ； In the formula, μ f , μ r These are the front and rear wheel adhesion coefficients, respectively. p This refers to the braking force distribution coefficient between the front and rear brakes. F zf , F zr These are the dynamic vertical loads on the front and rear axles, respectively. C f , C r These are the front and rear wheel lateral stiffness under pure lateral slip conditions.

4. The ARS and DYC cooperative control method for distributed electric drive vehicles under combined operating conditions as described in claim 3, characterized in that, F zf , F zr All are dynamically changing values: ； ； In the formula, h The height of the center of mass.

5. The ARS and DYC cooperative control method for distributed electric drive vehicles under combined operating conditions as described in claim 1, characterized in that, The collaborative control method includes the following steps: Based on the current yaw rate γ t and expected yaw rate γ d Calculate the control error of the ARS controller e A : e A = γ t － γ d ； Based on the desired centroid side slip angle β d and current centroid sideslip angle β t Desired yaw rate γ d and current yaw rate γ t Calculate the control error of the DYC controller e D : ; In the formula, ξ The weighting coefficients for yaw rate error and centroid sideslip angle error; pass e A and e D calculate M Z : ； ； In the formula, M DYC For the additional yaw moment generated by the DYC controller, M ARS For the additional yaw moment generated by the ARS controller, K D These are the weighting coefficients for the DYC controller. K A These are the weighting coefficients for the ARS controller; M zyD , M zyA All are model dynamic compensation terms. , J Z Let be the moment of inertia of the car about its vertical axis; , All are DYC controller sliding surface gains greater than 0. , All The error index of the DYC controller and , q D For the sliding mode control gain of the DYC controller, s D For the sliding surface of the DYC controller, , To improve the anti-jitter gain of the DYC controller, The upper bound for adaptive disturbance compensation of the DYC controller with an initial value of 0. , For DYC controller disturbance growth terms that are greater than 0, Forgotten items in the DYC controller that are greater than 0, This is a disturbance compensation term for the DYC controller; , All are ARS controller sliding surface control weight coefficients that are greater than 0. , All The error index of the ARS controller and , q A For the sliding mode control gain of the ARS controller, s A For the sliding surface of the ARS controller, , To improve the anti-jamming gain of the ARS controller, This is the upper bound for adaptive disturbance compensation of the ARS controller with an initial value of 0. , For ARS controller disturbance growth terms greater than 0, For ARS controller forgotten items that are greater than 0, This is the disturbance compensation term for the ARS controller.

6. The ARS and DYC cooperative control method for distributed electric drive vehicles under combined operating conditions as described in claim 5, characterized in that, Sign function Using saturation function replace: ； Sign function Using saturation function replace: ； In the formula, For the saturation boundary layer of the DYC controller, x D These are the output parameters of the DYC controller; For the saturation boundary layer of the ARS controller, x A These are the output parameters of the ARS controller.

7. The ARS and DYC cooperative control method for distributed electric drive vehicles under combined operating conditions as described in claim 5, characterized in that, Distribute the additional yaw moment proportionally to the front and rear wheelbase: ； In the formula, T f Add torque to the front wheels, T r Add torque to the rear wheels, h The height of the center of mass; The left and right wheels are distributed in opposite directions in a fixed ratio: ； In the formula, T lf Torque is distributed to the left front wheel. T rf Torque is distributed to the right front wheel. T lr Torque is distributed to the left rear wheel. T rr Torque is distributed to the right rear wheel. i This refers to the distribution coefficient between the left and right wheels.

8. The method for coordinated control of ARS and DYC in a distributed electric drive vehicle under combined operating conditions as described in claim 5, characterized in that, Rear wheel steering angle δ r : 。 9. The ARS and DYC cooperative control method for distributed electric drive vehicles under combined operating conditions as described in claim 5, characterized in that, K D and K A The design method is as follows:

1. Based on the front wheel slip angle α f and rear wheel slip angle α r Phase diagram division: Classical domain, with coordinates (0,0) in the phase diagram as the center and radius... r s The area; The extended domain is defined by the coordinate (0,0) in the phase diagram as the origin and the radius of the origin. r c And remove the region after the classical domain; Non-domain: The region in the phase diagram excluding classical and extended domains; II. For complex operating conditions located in different domains, assign control weight coefficients to the vehicle's DYC controller and ARS controller. K D , K A : Design correlation function K ( S ): ； In the formula, let P 3 is a point in the phase plane, representing the current wheel slip angle of the vehicle; the connection point is... P 3 and the origin of the coordinate system O Draw a line and extend it, intersecting the boundary of the classical domain at points [points to be filled in]. P 4 and P 1. Intersects the boundary of the extended domain at points respectively. P 5 and P 2, of which, P 1. P 2 is the intersection of the first and fourth quadrants, s( P 3, ( P 4, P 1) and s( P 3, ( P 5, P 2) represents the distances from the front and rear wheel slip angles to the boundaries of the classical and extended domains, respectively; when K ( S When ) ≥ 1, the car's driving state is within the classic domain. K A =1, K D =0; When 0 < K ( S When ) < 1, the vehicle's driving state is in the extended domain. K A = K ( S ), K D =1- K ( S ); when K ( S When ) ≤ 0, the car's driving state is in a non-domain state. K A =0, K D =1.

10. The ARS and DYC cooperative control method for distributed electric drive vehicles under combined operating conditions as described in claim 9, characterized in that, radius r c The design method is as follows: I. Fitting the coordinates of two saddle points of the car S 1 ( α f1 , α r1 )and S 2 ( α f2 , α r2 ); II. Design r c for: ； In the formula, β s1 and β s2 These are the sideslip angles of the centroids at the two saddle points. γ s1 and γ s2 The yaw angular velocities at the two saddle points are as follows: ； ； in, As an intermediate variable: ; h The height of the car's center of gravity; g It is the acceleration due to gravity; μ cf and μ cr As an intermediate variable: , μ f and μ r These are the front and rear wheel adhesion coefficients, respectively. p The braking force distribution coefficient between the front and rear brakes of a car; F zf and F zr These are the dynamic vertical loads on the front and rear axles, respectively: , f 1( v x ), f 2( v x ), f 3( a x ), f 4( δ f , δ r ), f 5( a x All of these are fitted functions: , k 1~ k 12 These are the calibrated fitting coefficients.

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