Vehicle longitudinal and lateral layered cooperative control method, system, device and storage medium

Abstract

The embodiment of the application provides a vehicle longitudinal and lateral layered cooperative control method, system, device and storage medium, and belongs to the technical field of vehicle control. The method is based on a zero centroid side slip angle strategy, determines expected driving state quantities according to actual state quantities and an expected trajectory, and the expected driving state quantities include axle reference angles. The zero centroid side slip angle strategy has a preset proportional relationship for the angles of the axles. Then, longitudinal and lateral cooperative control is performed according to the expected driving state quantities, global longitudinal generalized forces, global generalized lateral forces and global generalized yaw moments are obtained, tire forces of each wheel are obtained by performing optimal distribution of the moments, and the tire forces of each wheel are converted into driving space to obtain wheel angles and motor torques of each wheel of the bottom-layer driving vehicle. The application can flexibly track and control the vehicle, and improve the trajectory tracking accuracy and attitude stability of the vehicle in a complex environment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle control, in particular to a vehicle transverse and longitudinal layered cooperative control method, system, device and storage medium. BACKGROUND

[0002] With the acceleration of the automobile industry towards electrification and intelligentization, the chassis, as the key to vehicle driving performance, is undergoing a transformation from traditional mechanical to "drive-by-wire chassis". Drive-by-wire chassis controls actuators through electrical signals, replacing traditional mechanical connection methods, greatly reducing parts and costs. Especially in the field of heavy-duty transportation, traditional chassis faces the bottleneck of low transmission efficiency and complex structure, and cannot meet the modern demand for high mobility. Heavy-duty intelligent full-vector drive-by-wire chassis refers to the use of full-vector driving angle module technology and intelligent networking technology, and its drive-steering integrated electric wheel structure covers the maximum independent input set of the vehicle, enabling independent control of all wheel longitudinal and transverse forces. At the same time, it has the ability to freely combine and reconfigure intelligent cooperation, which can fully expand the driving and use boundaries of the vehicle and has very wide applications.

[0003] In the field of trajectory tracking algorithms for multi-axle heavy-duty vehicles, although there have been some research and exploration, due to the influence of complex multi-axle vehicle models and extreme working conditions, related technologies still cannot achieve high precision and robustness. In addition, due to the large volume of goods and limited space in the work site, there is an urgent need for omnidirectional mobility of vehicles and multi-vehicle cooperative reconfiguration docking, which requires chassis control to effectively combine expected path information to meet key tasks such as full-vector drive-by-wire vehicle reconfiguration docking and formation cooperation.

[0004] In the trajectory tracking control of vehicles, the longitudinal and lateral forces generated by the tires are crucial to the vehicle's attitude and dynamic performance, especially when approaching the control limit, the nonlinear characteristics of tire forces will make the vehicle dynamics highly complex. In addition, influenced by road adhesion, nonlinear saturation characteristics of tires, external characteristics of in-wheel motors and steering mechanism restrictions, the full-vector drive-by-wire system of multi-axle unmanned heavy-duty vehicles becomes a complex system with over-actuation, under-determination and multiple constraints. Currently, there are problems such as poor flexibility and weak fault tolerance in the tracking control of such complex systems, resulting in low trajectory tracking accuracy and attitude stability of vehicles in complex environments. SUMMARY

[0005] The main purpose of the embodiments of the present application is to propose a vehicle transverse and longitudinal layered cooperative control method, system, device and storage medium, which aims to flexibly track control the vehicle and improve the trajectory tracking accuracy and attitude stability of the vehicle in complex environments.

[0006] To achieve the above-mentioned purpose, one aspect of the embodiments of the present application proposes a vehicle transverse and longitudinal layered cooperative control method, comprising the following steps:

[0007] acquiring actual state quantities in a driving process of the vehicle;

[0008] determining desired driving state quantities according to the actual state quantities and a desired trajectory based on a zero-center side-slip angle strategy, wherein the desired driving state quantities include a desired longitudinal velocity and reference angles of each axle, and the zero-center side-slip angle strategy has a preset proportional relationship for the angles of each axle;

[0009] performing longitudinal-lateral collaborative control according to the desired driving state quantities to obtain a global longitudinal generalized force, a global generalized side force, and a global generalized yaw moment;

[0010] performing optimal distribution of tire forces according to the global longitudinal generalized force, the global generalized side force, and the global generalized yaw moment to obtain tire forces of each wheel, wherein the tire forces include longitudinal forces and lateral forces;

[0011] converting the tire forces of each wheel to a driving space to obtain wheel angles and motor torques of each wheel for a bottom-layer driving vehicle.

[0012] In some embodiments, the determining of the desired driving state quantities according to the actual state quantities and the desired trajectory based on the zero-center side-slip angle strategy includes the following steps:

[0013] determining the desired longitudinal velocity according to a pedal state quantity in the actual state quantities;

[0014] determining an error dynamics model according to a vehicle longitudinal velocity, a vehicle lateral velocity, a vehicle lateral acceleration, a yaw velocity, and a yaw angular acceleration in the actual state quantities based on a vehicle single-track model;

[0015] solving a minimum performance index problem based on the error dynamics model based on the zero-center side-slip angle strategy to obtain the reference angles of each axle.

[0016] In some embodiments, the longitudinal-lateral collaborative control according to the desired driving state quantities to obtain the global longitudinal generalized force, the global generalized side force, and the global generalized yaw moment includes the following steps:

[0017] determining a longitudinal velocity error according to the desired longitudinal velocity and an actual longitudinal velocity, and feeding back the longitudinal velocity error to a PID controller to determine the global longitudinal generalized force by using a PID control algorithm;

[0018] determining an ideal yaw angular velocity and an ideal center side-slip angle according to the vehicle single-track model, the zero-center side-slip angle strategy, and the reference angles by using a two-degree-of-freedom linear vehicle model as a reference model;

[0019] determining a yaw rate deviation according to the ideal yaw rate and the actual yaw rate, and determining a mass center side slip angle deviation according to the ideal mass center side slip angle and the actual mass center side slip angle;

[0020] determining a global generalized side force and a global generalized yaw moment according to the yaw rate deviation and the mass center side slip angle deviation by using a lateral stability sliding mode controller.

[0021] In some embodiments, the step of determining a global generalized side force and a global generalized yaw moment according to the yaw rate deviation and the mass center side slip angle deviation by using a lateral stability sliding mode controller comprises the following steps:

[0022] determining a mass center side slip angle sliding mode surface according to the mass center side slip angle deviation, and determining a yaw rate sliding mode surface according to the yaw rate deviation and an integral term of the yaw rate deviation;

[0023] determining a sliding mode approaching rate according to the mass center side slip angle sliding mode surface and the yaw rate sliding mode surface;

[0024] determining a global generalized side force and a global generalized yaw moment for making the vehicle reach the ideal yaw rate and the ideal mass center side slip angle according to the sliding mode approaching rate.

[0025] In some embodiments, the step of performing tire force optimal distribution according to the global longitudinal generalized force, the global generalized side force and the global generalized yaw moment to obtain tire forces of each wheel comprises the following steps:

[0026] determining dynamic vertical loads of each wheel by using a dynamic vertical load calculation model of each wheel;

[0027] determining adhesion forces of each wheel according to the dynamic vertical loads of each wheel and road adhesion coefficients;

[0028] determining polyhedral friction constraints on longitudinal and lateral forces of each tire according to the adhesion forces, and determining actuator constraints on changes of longitudinal and lateral forces of each tire according to maximum torques, maximum change rates of the torques and tire radii of each tire;

[0029] obtaining a tire force distribution target function, and solving an optimal solution of the tire force distribution target function according to the polyhedral friction constraints, the actuator constraints and expected generalized forces to obtain tire forces of each wheel, wherein the expected generalized forces include the global longitudinal generalized force, the global generalized side force and the global generalized yaw moment.

[0030] In some embodiments, the tire force distribution target function includes a first target function approximating a top layer generalized moment error and a second target function minimizing a tire load rate.

[0031] The first target function is expressed as:

[0032]

[0033] wherein W v is a diagonal weighting matrix about each generalized lateral force moment, B is a gain efficiency matrix, u is a tire force distribution matrix, and A is an expected generalized longitudinal force;

[0034] The second target function is expressed as:

[0035]

[0036] wherein W u is an angular weighting matrix about each wheel load rate, and u is a tire force distribution matrix.

[0037] In some embodiments, the converting the tire force of each wheel into a driving space to obtain a wheel rotation angle and a motor torque for each wheel of the underlying driving vehicle comprises the following steps:

[0038] calculating the side slip angle of the wheel according to the tire force of the wheel by using a Dugoff tire inverse model;

[0039] determining the wheel rotation angle of the wheel according to the side slip angle, a vehicle longitudinal speed, a vehicle lateral speed, and a vehicle yaw speed;

[0040] determining the motor torque of the wheel according to the longitudinal force of the wheel based on a torque balance equation.

[0041] To achieve the above object, another aspect of the embodiment of the present application proposes a vehicle longitudinal and lateral layered collaborative control system, comprising:

[0042] a first module configured to acquire actual state quantities in a vehicle driving process;

[0043] a second module configured to determine expected driving state quantities according to the actual state quantities and an expected trajectory based on a zero center of mass side slip angle strategy, wherein the expected driving state quantities comprise an expected longitudinal speed and reference rotation angles of each axle, and the zero center of mass side slip angle strategy has a preset proportional relationship between the rotation angles of each axle;

[0044] a third module configured to perform longitudinal and lateral collaborative control according to the expected driving state quantities to obtain a global longitudinal generalized force, a global generalized lateral force, and a global generalized yaw moment;

[0045] a fourth module configured to perform tire force optimal distribution according to the global longitudinal generalized force, the global generalized lateral force, and the global generalized yaw moment to obtain tire forces of each wheel, wherein the tire forces comprise longitudinal forces and lateral forces;

[0046] A fifth module is configured to convert the tire forces of each wheel into a drive space to obtain wheel rotation angles and motor torques for each wheel of the bottom-layer driven vehicle.

[0047] To achieve the above object, another aspect of the embodiments of the present application provides an electronic device, which comprises a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for realizing connection communication between the processor and the memory, and the program is executed by the processor to realize the method described in the above embodiments.

[0048] To achieve the above object, another aspect of the embodiments of the present application provides a storage medium, which is a computer-readable storage medium for computer-readable storage, and the storage medium stores one or more programs, and the one or more programs are executable by one or more processors to realize the method described in the above embodiments.

[0049] The vehicle longitudinal-lateral layered collaborative control method, system, device and storage medium provided by the present application are based on a zero-center side slip angle strategy, and an expected driving state quantity is determined according to an actual state quantity and an expected trajectory, the expected driving state quantity includes an expected longitudinal speed and a reference rotation angle of each axle, the zero-center side slip angle strategy has a preset proportional relationship between the rotation angles of the axles, then longitudinal-lateral collaborative control is performed according to the expected driving state quantity to obtain a global longitudinal generalized force, a global generalized lateral force and a global generalized yaw moment, then tire forces are optimally distributed according to the global longitudinal generalized force, the global generalized lateral force and the global generalized yaw moment to obtain tire forces of each wheel, the tire forces of each wheel are converted into a drive space to obtain wheel rotation angles and motor torques for each wheel of the bottom-layer driven vehicle. The present application constructs a vehicle dynamics model in view of the complexity of driving behaviors of a vehicle with multiple driving and steering axles, and combines a zero-center side slip angle control strategy to make the equivalent rotation angles of the other axles and the equivalent rotation angle of the reference axle have a proportional relationship, thereby improving the accuracy and efficiency of path tracking. BRIEF DESCRIPTION OF DRAWINGS

[0050] Figure 1 is a flowchart of the vehicle longitudinal-lateral layered collaborative control method provided by the embodiments of the present application;

[0051] Figure 2 is a curve diagram of the steering ratio of each axle to the first axle varying with vehicle speed provided by the embodiments of the present application;

[0052] Figure 3 is a schematic diagram of a full-vector four-axle unmanned heavy-load vehicle 11DOF maneuvering dynamics model provided by the embodiments of the present application;

[0053] Figure 4 is a schematic diagram of a vehicle longitudinal-lateral layered collaborative control process provided by the embodiments of the present application;

[0054] Figure 5 FIG. 1 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application and not to limit the present application.

[0056] It should be noted that although the functional modules are divided in the system and the logical order is shown in the flowchart, in some cases, the steps shown or described can be performed in a manner different from the module division in the system or the order in the flowchart. The terms "first", "second", etc. in the specification and claims and the above drawings are used to distinguish similar objects and do not necessarily describe a specific order or sequence.

[0057] 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 the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

[0058] The embodiments of the present application provide a vehicle lateral and longitudinal layered collaborative control method, system, device and storage medium, which aims to flexibly track and control the vehicle and improve the trajectory tracking accuracy and attitude stability of the vehicle in a complex environment.

[0059] The vehicle lateral and longitudinal layered collaborative control method, system, device and storage medium provided by the embodiments of the present application are specifically described by the following embodiments. First, the vehicle lateral and longitudinal layered collaborative control method in the embodiments of the present application is described.

[0060] The vehicle lateral and longitudinal layered collaborative control method provided by the embodiments of the present application relates to the technical field of vehicle control. The vehicle lateral and longitudinal layered collaborative control method provided by the embodiments of the present application can be applied to a terminal, can be applied to a server end, and can also be software running in a terminal or a server end. In some embodiments, the terminal can be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc.; the server end can be configured as an independent physical server, can be configured as a server cluster or a distributed system composed of multiple physical servers, can also be configured as a cloud server providing basic cloud computing services such as cloud service, cloud database, cloud computing, cloud function, cloud storage, network service, cloud communication, middleware service, domain name service, security service, CDN, and big data and artificial intelligence platform; and the software can be an application that implements the vehicle lateral and longitudinal layered collaborative control method, etc., but is not limited to the above forms.

[0061] The application is operable in a variety of general purpose or special purpose computing system environments or configurations. Examples of computing systems, environments, and / or configurations that can be suitable for use with the application include personal computers, server computers, handheld or laptop devices, tablet-type devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like. The application can be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, and the like, that perform particular tasks or implement particular abstract data types. The application can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules can be located in local and remote computer storage media including memory storage devices.

[0062] Figure 1 is an optional flowchart of a vehicle longitudinal and lateral layered cooperative control method provided by an embodiment of the application, Figure 1 The method in the above embodiment can include, but is not limited to, steps S101 to S105.

[0063] In step S101, actual state quantities in a vehicle driving process are acquired.

[0064] In step S102, expected driving state quantities are determined according to the actual state quantities and an expected trajectory based on a zero-center side slip angle strategy, wherein the expected driving state quantities include expected longitudinal speed and reference rotation angles of each axle, and the zero-center side slip angle strategy has a preset proportional relationship between the rotation angles of each axle.

[0065] In step S103, longitudinal and lateral cooperative control is performed according to the expected driving state quantities, to obtain global longitudinal generalized force, global generalized lateral force, and global generalized yaw moment.

[0066] In step S104, tire force optimal distribution is performed according to the global longitudinal generalized force, the global generalized lateral force, and the global generalized yaw moment, to obtain tire forces of each wheel, wherein the tire forces include longitudinal forces and lateral forces.

[0067] In step S105, the tire forces of each wheel are converted to a driving space, to obtain wheel rotation angles and motor torques of each wheel for driving the vehicle.

[0068] In step S101 of some embodiments, the embodiments of the present application are illustrated by a four-axle eight-wheel full-vector HWA chassis vehicle. The actual state quantities in the vehicle running process are estimated by vehicle-mounted sensors and a mechanism analysis-data driven full-scale vehicle dynamics model, including but not limited to: wheel speed, wheel rotation angle, vehicle longitudinal speed, longitudinal acceleration, vehicle lateral speed, lateral acceleration, yaw angle, yaw angular velocity and road surface friction coefficient, etc.

[0069] In step S102 of some embodiments, the vehicle longitudinal speed v x , the vehicle lateral speed v y , the vehicle lateral acceleration , the yaw speed , and the yaw angular acceleration are obtained according to the actual state quantities obtained in step S101.

[0070] In some embodiments, step S102 can include but is not limited to steps S201 to S203:

[0071] Step S201, determining the desired longitudinal speed according to the pedal state quantity in the actual state quantity;

[0072] Step S202, determining the error dynamics model according to the vehicle longitudinal speed, the vehicle lateral speed, the vehicle lateral acceleration, the yaw speed and the yaw angular acceleration in the actual state quantity based on the vehicle single-track model;

[0073] Step S203, solving the minimum performance index problem based on the error dynamics model based on the zero-center side-slip angle strategy to obtain the reference rotation angle of each axle.

[0074] Exemplarily, the desired longitudinal speed can be determined according to the pedal state quantity in the actual state quantity obtained in S101.

[0075] According to the vehicle longitudinal speed v x , the vehicle lateral speed v y , the vehicle lateral acceleration , the yaw speed , and the yaw angular acceleration obtained in step S101.

[0076]

[0077] wherein C αi is the equivalent cornering stiffness of each axle, δ i is the equivalent rotation angle of each axle, n is the mass of the whole vehicle, and l is the wheelbase.i is the distance from each axle to the center of mass, v x , v y is the longitudinal motion speed of the center of mass of the vehicle along the x-axis and the lateral motion speed along the y-axis, respectively, and is the yaw rate and the yaw acceleration, I z is the yaw moment of inertia.

[0078] An LQR control is used to design a path tracking controller for the full vector four-axle unmanned heavy-duty vehicle. Since the control strategy is based on the zero center of mass side slip angle, the heading angle θ is replaced by the yaw angle , the lateral error e d and the heading error of the vehicle in tracking the desired path are as follows:

[0079]

[0080] where, is the desired path heading angle speed.

[0081] Based on the zero center of mass side slip angle strategy, there is a certain proportional relationship between the equivalent steering angles δ i of each axle, as follows:

[0082]

[0083] where:

[0084] In the formula, L ri is the distance from each axle to the center line of the steering, L 12 , L 13 , L 14 is the distance from the first axle to the second, third and fourth axles.

[0085] Combined with formulas (1), (2), (3), the adaptive error dynamics model of the full vector four-axle unmanned heavy-duty vehicle is established with the lateral error e d , the lateral error rate , the heading error and the heading error rate as state variables as follows:

[0086]

[0087] In the formula,

[0088]

[0089] According to the vehicle error dynamics model, the performance index J is defined as follows:

[0090]

[0091] where Q, R are the weighting matrices of the controller.

[0092] To minimize J, the problem is converted to a quadratic optimal problem as follows:

[0093]

[0094] Taking the derivative of equation (6), the extreme value is obtained:

[0095] u * (t) = R -1 B T λ(t) = R -1 B T P(t)e rr (t); (7)

[0096] P(t) is the solution of Riccati equation of equation (7):

[0097] PA + A T P - PBR -1 BP T + Q = 0; (8)

[0098] To eliminate the influence of e in equation (4), both e and e rr can be set to 0. Therefore, a feedforward control is also introduced. At this time, the control law considering both feedforward and feedback is as follows:

[0099] U = -Ke rr + δ1; (9)

[0100] where: K = [K1, K2, K3, K4].

[0101] Substituting equation (9) into equation (4), we get:

[0102]

[0103] The equivalent rotation angle of axis 1 based on path tracking is obtained as follows:

[0104]

[0105] where:

[0106]

[0107] Based on the above zero side-slip angle strategy, the curves of the steering ratio of each axis to the first axis with vehicle speed are as follows: Figure 2It can be seen that when the vehicle speed is low, M2 and M3 are negative, the steering of the full-vector four-axle unmanned heavy load vehicle is reverse phase sequence steering, and greater steering flexibility is obtained; as the vehicle speed increases, M2 and M3 change from negative to positive, the full-vector four-axle unmanned heavy load vehicle changes from reverse phase sequence to same direction, greatly improving the stability during steering.

[0108] In step S103 of some embodiments, according to the reference steering angle obtained in step S102, the top-level reference state generator adopts a two-degree-of-freedom linear vehicle model as a reference model, and combines an 11-degree-of-freedom handling dynamics vehicle model to calculate global longitudinal generalized forces F xc , global generalized lateral forces F yc and global generalized yaw moments M zc under the expected driving state.

[0109] In some embodiments, step S103 can include but is not limited to steps S301 to S304:

[0110] Step S301, determining a longitudinal speed error according to the expected longitudinal speed and the actual longitudinal speed, and feeding back the longitudinal speed error to a PID controller to determine the global longitudinal generalized force by using a PID control algorithm;

[0111] Step S302, adopting a two-degree-of-freedom linear vehicle model as a reference model, determining an ideal yaw rate and an ideal center of mass side slip angle according to the vehicle single-track model, the zero center of mass side slip angle strategy and the reference steering angle;

[0112] Step S303, determining a yaw rate deviation according to the ideal yaw rate and the actual yaw rate, and determining a center of mass side slip angle deviation according to the ideal center of mass side slip angle and the actual center of mass side slip angle;

[0113] Step S304, adopting a lateral stability sliding mode controller to determine the global generalized lateral force and the global generalized yaw moment according to the yaw rate deviation and the center of mass side slip angle deviation.

[0114] Exemplarily, the top-level reference state generator adopts a two-degree-of-freedom linear vehicle model as a reference model, and simultaneously combines an 11-DOF handling dynamics vehicle model, which focuses on the longitudinal, lateral and yaw motion of the vehicle and the rotation of the eight wheels. The 11-DOF dynamics model of the full-vector four-axle unmanned heavy load vehicle is as follows: Figure 3 The motion equations are as follows:

[0115] The longitudinal motion differential equation is as follows:

[0116]

[0117] The lateral motion differential equation is as follows:

[0118]

[0119] The yaw motion differential equation is:

[0120]

[0121] The rotation motion differential equation is expressed as:

[0122]

[0123] Wherein: F x , F y , M z are the vehicle longitudinal resultant force, lateral resultant force, yaw moment in the vehicle body coordinate system, i = 1, 2, 3, 4; d i is the half of the wheel track of the ith axle, F xil , F xir represent the ground longitudinal force of the left and right tires of the ith axle in the vehicle body coordinate system, J i(l,r) represents the moment of inertia of the eight wheels, ω i(l,r) is the wheel rotation angular velocity, T i(l,r) is the longitudinal torque, F xwi(l,r) is the longitudinal force received by the wheel, R w is the wheel rolling radius, F yil , F yir represent the ground lateral force of the left and right tires of the ith axle in the vehicle body coordinate system, which are the force components of the tire force in the vehicle coordinate system. In the tire coordinate system, the longitudinal force of the left and right tires of the ith axle is represented as F xwil , F xwir , and the lateral force is represented as F ywil , F ywir . The relationship between the tire force in the vehicle coordinate system and the tire coordinate system is as follows:

[0124]

[0125] Wherein, δ il , δ ir are the rotation angles of the left and right wheels of each axle.

[0126] Further, the ideal mass center side slip angle β d and the ideal yaw angular velocity need to be calculated. When the automobile reaches a steady state, the mass center side slip angle of the vehicle is zero, and the yaw angular velocity is a constant value, i.e. By combining equations (1), (3), and (11), the distance L r1 from the axle 1 to the steering center line can be obtained as:

[0127]

[0128] Compared with the stability factor K of two-axle vehicle in vehicle theory, the ideal yaw rate and ideal side slip angle of four-axle full vector vehicle can be obtained as follows:

[0129]

[0130] The expression of the equivalent wheel base L' and stability factor K of four-axle full vector vehicle is as follows:

[0131]

[0132] The longitudinal control of the vehicle adopts a PID controller to realize accurate tracking of the vehicle speed, and to ensure that the vehicle speed is consistent with the expected value by adjusting the accelerator / brake pedal. The PID controller adjusts the control amount dynamically through longitudinal speed error feedback (e(t) = v x (t)-v xd (t)), so as to obtain the required global longitudinal generalized force F xc , as follows:

[0133]

[0134] where K p is the proportional gain, K i is the integral gain, and K d is the differential gain.

[0135] The lateral control of the vehicle adopts a sliding mode control to realize accurate dynamic control of the vehicle and to meet the safety driving demand under heavy load conditions. The vehicle lateral and yaw state equations are as follows:

[0136]

[0137] where ξ1 and ξ2 are disturbance terms caused by internal or external factors of the vehicle control system.

[0138] The control amount deviation of the controller (side slip angle deviation e1 and yaw rate deviation e2) is as follows:

[0139]

[0140] In some embodiments, step S304 can include, but is not limited to, steps S401 to S403:

[0141] Step S401, determining a side slip angle sliding mode surface according to the side slip angle deviation, and determining a yaw rate sliding mode surface according to the yaw rate deviation and the integral term of the yaw rate deviation;

[0142] Step S402, determining a sliding mode approach rate according to the side slip angle sliding mode surface and the yaw rate sliding mode surface;

[0143] Step S403, according to the sliding mode approach rate, determine the global generalized lateral force and global generalized yaw moment to make the vehicle reach the ideal yaw rate and ideal center side slip angle.

[0144] Exemplarily, since the center side slip angle expression contains the yaw rate, the control accuracy of the yaw rate is related to M zc and F yc To reduce the cumulative error about time due to drift, the sliding mode control state variable of the yaw rate adds an integral term to form a closed-loop feedback, revises the tracking error of the yaw rate, and the sliding mode surface (the center side slip angle sliding mode surface s β and the yaw rate sliding mode surface ) is designed as follows:

[0145]

[0146] In the formula: λ1 is a coefficient (λ1>0).

[0147] To achieve dynamic sliding mode, an exponential approach law is selected, and to overcome the chattering problem caused by the discontinuous sign function sign(s), it is replaced by the continuous tanh(s) function, and the sliding mode approach rate is designed as:

[0148]

[0149] In the formula: ε is the boundary layer thickness, k is the approach rate index, ε1, ε2, k1, k2 are all positive numbers.

[0150] Further, the global generalized lateral force F yc and the global generalized yaw moment M zc required by the vehicle can be derived as follows:

[0151]

[0152] In step S104 of some embodiments, a dynamic vertical load calculation model is established, the longitudinal acceleration and vehicle lateral acceleration obtained in real time in step S101 are comprehensively considered in the middle layer tire force distribution layer to manage and distribute the tire force from the tire layer, build a target function for approximating the top layer generalized moment error and minimizing the tire load rate, and realize optimal distribution of tire lateral and longitudinal forces on the basis of global longitudinal generalized force, global generalized lateral force and global generalized yaw moment.

[0153] In some embodiments, step S104 can include but is not limited to steps S501 to S504:

[0154] Step S501, determining the dynamic vertical load of each wheel by using a dynamic vertical load calculation model of each wheel;

[0155] Step S502, determining the adhesion force of each wheel according to the dynamic vertical load of each wheel and the road adhesion coefficient;

[0156] Step S503, determining the polyhedral friction constraint on the longitudinal and lateral force of each tire according to the adhesion force, and determining the actuator constraint on the change amount of the longitudinal and lateral force of each tire according to the maximum torque, the maximum change rate of the torque, and the tire radius;

[0157] Step S504, obtaining a tire force distribution target function, and solving the optimal solution of the tire force distribution target function according to the polyhedral friction constraint, the actuator constraint, and the expected generalized longitudinal force, the expected generalized lateral force, and the expected generalized yaw moment, to obtain the tire force of each wheel.

[0158] Exemplarily, the dynamic vertical load calculation model needs to comprehensively consider the lateral acceleration and the longitudinal acceleration of the vehicle, and ignore the roll, pitch, and heave of the vehicle. The vertical force of the tire can be calculated by the static weight distribution and the load transfer corresponding to the longitudinal and lateral accelerations.

[0159] When the vehicle is stationary or moving at a constant speed, the static load of each axle is calculated as follows:

[0160]

[0161] wherein, m s is the sprung mass of the vehicle body, and g is the acceleration of gravity.

[0162] wherein:

[0163]

[0164] Assuming that the change of the vehicle attitude is not considered, the static vertical load of each tire is:

[0165]

[0166] wherein, m wi is the unsprung mass corresponding to each tire.

[0167] The dynamic change of the vertical load of the tire caused by the attitude of the vehicle body mainly reflects the load transfer of the front and rear loads of the sprung mass caused by the longitudinal and lateral accelerations when the vehicle accelerates or decelerates or turns. The change amount of the vertical load of each axle caused by the longitudinal acceleration is divided into the front axle and the rear axle with the center of mass as the dividing point, and then the front and rear load transfer amount of each tire is distributed. The vertical load change amount of the left and right wheels of the same axle is consistent, and the calculation method is as follows:

[0168]

[0169] where,

[0170] where, ziax is the vertical load shift of the i-th axle due to longitudinal acceleration, h is the height of the center of mass, a x is the longitudinal acceleration of the vehicle.

[0171] is the vertical load shift of the i-th axle due to lateral acceleration, and for the same axle, the left and right wheels have equal but opposite changes in load. The lateral force is assumed to be distributed on each axle in proportion to the load on each axle, and is calculated as follows:

[0172]

[0173] where, z1ay is the vertical load shift of the i-th axle due to longitudinal acceleration, B i is the wheel base of the i-th axle, a y is the lateral acceleration of the vehicle.

[0174] Therefore, the dynamic vertical load calculation model is as follows, taking into account the load shift caused by longitudinal and lateral acceleration:

[0175]

[0176] The middle tire force distribution layer needs to consider the friction circle constraint. In order to speed up the solving time, the friction circle constraint is linearized by using the circumscribed octagon, i.e. the polyhedral friction constraint is as follows:

[0177]

[0178] where, μ ij represents the road adhesion coefficient, μ ij F zij represents the adhesion force of the wheel.

[0179] At the same time, the middle tire force distribution layer needs to consider the physical constraints and the rate of change of the actuator. The amplitude and rate of change of the tire longitudinal force are limited by the output torque of the angular module motor and the brake actuator, and the tire lateral force is also limited by parameters such as the maximum tire side slip angle, so the actuator characteristic constraint is as follows:

[0180]

[0181] where, T ij,max , k xij,maxThe maximum torque and the maximum rate of change of each tire under the constraints of the motor are performed, Δt is the control step, r ij is the radius of each tire, F tyij,max , k yij,max is the maximum lateral force of the tire and its maximum rate of change, ΔF txij and ΔF tyij is the longitudinal and lateral change of the tire under the unit control step.

[0182] Next, the design of the objective function is carried out, and the expected generalized force A = [F xc , F yc , M zc ] T and the gain efficiency matrix B between the output of the middle allocation layer and the longitudinal and lateral force of the tire u = [F xwil F xwir F ywil F ywir ] T , the objective function J1 of the top layer generalized force moment error approximation is constructed. Joint formula (12), (13), (14), (16), first redefine each axle distance l i as follows:

[0183]

[0184] Then the global generalized force moment in the allocation layer, the longitudinal and lateral tire force state space equation under the conversion of the body coordinate system to the tire coordinate system can be expressed as:

[0185]

[0186] The expected global generalized force [F xc F yc M zc ] T between the top layer input and the longitudinal and lateral force [F xwil F xwir F ywil F ywir ] T of each tire output by the middle allocation layer is established Gain efficiency matrix B 3×16 as follows:

[0187] B = [B1 B2 B3] T ; (37)

[0188] Where:

[0189]

[0190] Then, the error approximation function is:

[0191]

[0192] wherein, is a diagonal weighting matrix, which can be adjusted in real time according to control needs, W ν represents the importance of the expected generalized moment in the error approximation target function.

[0193] The Dugoff tire model is established, and the longitudinal force F xwij and the lateral force F ywij of the tire under the combined action of longitudinal and lateral slip are calculated, and a target function J2 for minimizing the tire load rate is constructed. The calculation formula of the Dugoff tire model is as follows:

[0194]

[0195] wherein: S ij represents the slip rate, μ is the road adhesion coefficient, F zij is the vertical load of each wheel, C s is the longitudinal slip stiffness of the tire, C α is the tire cornering stiffness, λ ij is the tire dynamic parameter, f(λ ij ) is the tire longitudinal and lateral correction function, F xwij , F ywij are the longitudinal force and lateral force of each tire in the tire coordinate system, v wxij is the longitudinal speed of the wheel center of each tire in the tire coordinate system, and the calculation formula is as follows:

[0196]

[0197] Based on the longitudinal force F xwij and the lateral force F ywij calculated by the Dugoff tire model, the tire load rate ρ ij is defined as:

[0198]

[0199] The performance optimization function J2 is constructed as follows:

[0200]

[0201] wherein:

[0202] is a diagonal weighting matrix, λ ij is a weighting factor, representing the weight value of the corresponding wheel load rate.

[0203] The comprehensive target function for minimizing the tire load rate and the error approximation of the top-level generalized moment is constructed as follows:

[0204]

[0205] where η is a coordination factor, which ensures that the error approximation target function value is smaller in the process of solving the optimal solution, and the desired state is achieved. An optimal control allocation algorithm based on quadratic programming is used, and the aggressive set method is used for solving, and finally the expected tire longitudinal force F xwij and tire lateral force F ywij .

[0206] In step S105 of some embodiments, the bottom layer driving execution layer calculates the tire longitudinal force F xwij and tire lateral force F ywij combined with the dugoff tire inverse model, the conversion of the tire force to the driving space is completed, the tire force is converted into the motor torque and the wheel angle, the horizontal and longitudinal layered collaborative control of the whole vehicle is realized, and the implementation of the chassis domain control support is provided for the key tasks such as reconstruction docking and formation coordination of the full-vector steer-by-wire vehicle. Further, the real-time state information of the vehicle is returned to step S102 to repeat the method of the embodiments of the application, and the real-time control of the vehicle is realized.

[0207] In some embodiments, step S105 includes but is not limited to steps S601 to S603:

[0208] Step S601, using the Dugoff tire inverse model, calculating the side slip angle of the wheel according to the tire force of the wheel;

[0209] Step S602, according to the side slip angle, the vehicle longitudinal speed, the vehicle lateral speed, the wheel angle of the wheel;

[0210] Step S603, based on the torque balance equation, determining the motor torque of the wheel according to the longitudinal force of the wheel.

[0211] Exemplarily, the embodiments utilize the Dugoff inverse model to design the bottom layer driving execution layer, complete the conversion of the tire force to the driving space, and convert the tire force into the wheel angle δ ij and the motor torque T ij .

[0212] Integrating equations (40) to (43), the Dugoff tire inverse model can be obtained as follows:

[0213]

[0214] wherein:

[0215] Combined with the Dugoff tire inverse model, the relationship between the wheel angle δ ij and the side slip angle α ij solved by the inverse model is as follows:

[0216]

[0217] Combining equation (15), based on the torque balance equation, the tire longitudinal execution control amount is:

[0218]

[0219] In the formula: J i(l,r) represents the moment of inertia of the 8 wheels, ω i(l,r) is the wheel rotation angular velocity, T i(l,r) is the longitudinal torque, F xwi(l,r) is the longitudinal force received by the wheel, R w is the wheel rolling radius.

[0220] According to some embodiments of the present application, please refer to Figure 4 , in order to meet the dynamic demand of multi-axle heavy load vehicle in complex driving conditions, the state quantity in the vehicle running process is estimated through the vehicle-mounted sensor and the mechanism analysis-data driven full-scale vehicle dynamics model; then according to the single-track model of the vehicle, the path tracking error dynamics model is derived, the reference rotation angle and the expected longitudinal speed of each axle based on path tracking are calculated combined with the zero center of mass side slip angle control strategy; the top-level reference state generator is designed, the two-degree-of-freedom linear vehicle model is used as the reference model, combined with the 11-degree-of-freedom handling dynamics vehicle model, the global generalized side force F yc and the global generalized yaw moment M zc are calculated through the lateral stability sliding mode controller under the expected driving state; the global longitudinal generalized force F xc is calculated through the longitudinal PID speed tracking controller; then the dynamic vertical load calculation model is established, the middle layer of tire force distribution is designed, the friction circle constraint, the physical constraint of the actuator and the change rate constraint are comprehensively considered, the tire force is managed and distributed from the tire layer, the objective function of approximating the top-level generalized moment error and the lowest tire load rate is constructed, the optimal distribution of tire lateral and longitudinal force is realized; finally, the bottom layer of driving execution layer is designed, the tire lateral and longitudinal force obtained by the middle layer distribution layer is combined with the Dugoff tire inverse model, the conversion of tire force to driving space is completed, the tire force is converted into motor torque and wheel angle, and the lateral and longitudinal layered collaborative control of the whole vehicle is realized.

[0221] The embodiment of the application constructs a full-vector line control super-heavy vehicle dynamics model, and combines a zero side slip centroid angle control strategy to realize proportional control between the equivalent rotation angles of the second, third and fourth axles and the equivalent rotation angle of the first axle, thereby significantly improving the accuracy and dynamic response efficiency of path tracking. Based on a dynamic vertical load calculation model, the dynamic influence of the vehicle body posture on the tire vertical load is comprehensively considered, especially the front-back and left-right shift of the spring load caused by the longitudinal and lateral acceleration during vehicle acceleration, deceleration or turning, the dynamic behavior of the vehicle is fully captured and simulated, the evolution mechanism of the longitudinal-lateral dynamics coupling characteristics is developed, and the interaction and influence between different directional dynamics are deeply understood. The dynamic vertical load calculation model of the embodiment improves the calculation accuracy of the vertical load and is suitable for heavy load transportation under complex conditions, thereby laying a reliable foundation for the application of unmanned heavy load vehicles in high-precision dynamic control. In addition, the embodiment of the application constructs a hierarchical longitudinal-lateral coordinated motion control strategy for the complex driving requirements of the line control full-vector four-axle unmanned heavy load vehicle. By layer-by-layer decomposition of the motion control target, not only the calculation burden is effectively reduced, but also the Dugoff tire inverse model is introduced to decouple the lateral and longitudinal forces of the tire, realize independent control and hierarchical coordination. This strategy can make the vehicle accurately track the expected motion state and significantly improve the driving performance under extreme conditions.

[0222] The embodiment of the application also provides a vehicle longitudinal-lateral hierarchical coordinated control system, which comprises:

[0223] A first module is configured to acquire actual state quantities in the vehicle driving process.

[0224] A second module is configured to determine expected driving state quantities according to the actual state quantities and an expected trajectory based on a zero centroid side slip angle strategy, wherein the expected driving state quantities comprise an expected longitudinal velocity and reference rotation angles of each axle, and the zero centroid side slip angle strategy has a preset proportional relationship between the rotation angles of each axle.

[0225] A third module is configured to perform longitudinal-lateral coordinated control according to the expected driving state quantities to obtain a global longitudinal generalized force, a global generalized lateral force and a global generalized yaw moment.

[0226] A fourth module is configured to perform optimal distribution of tire forces according to the global longitudinal generalized force, the global generalized lateral force and the global generalized yaw moment to obtain tire forces of each wheel, wherein the tire forces comprise longitudinal forces and lateral forces.

[0227] A fifth module is configured to convert the tire forces of each wheel to a driving space to obtain wheel rotation angles and motor torques of each wheel of the bottom-layer driving vehicle.

[0228] It can be understood that the contents in the above-mentioned vehicle transverse and longitudinal layered collaborative control method embodiments are all applicable to the present system embodiment, the present system embodiment specifically implements the same functions as the above-mentioned vehicle transverse and longitudinal layered collaborative control method embodiments, and achieves the same beneficial effects as the above-mentioned vehicle transverse and longitudinal layered collaborative control method embodiments.

[0229] The present application embodiment further provides an electronic device, which comprises a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for realizing connection communication between the processor and the memory, and the program is executed by the processor to realize the above-mentioned vehicle transverse and longitudinal layered collaborative control method. The electronic device can be any intelligent terminal including a tablet computer, a vehicle-mounted computer, etc.

[0230] Please refer to Figure 5 , Figure 5 The hardware structure of the electronic device of another embodiment is illustrated, which comprises:

[0231] The processor 501 can be implemented in the form of a general CPU (Central Processing Unit), a microprocessor, an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits, etc., for executing related programs to realize the technical solutions provided by the present application embodiment;

[0232] The memory 502 can be implemented in the form of a ROM (ReadOnly Memory), a static storage device, a dynamic storage device, or a RAM (Random Access Memory), etc. The memory 502 can store an operating system and other application programs, and when the technical solutions provided by the present application embodiment are implemented by software or firmware, the related program codes are saved in the memory 502 and are called and executed by the processor 501 to realize the vehicle transverse and longitudinal layered collaborative control method of the present application embodiment;

[0233] The input / output interface 503 is used to realize information input and output;

[0234] The communication interface 504 is used to realize the communication interaction between the present device and other devices, which can realize communication through a wired manner (for example, a USB, a network cable, etc.) or a wireless manner (for example, a mobile network, WIFI, Bluetooth, etc.);

[0235] The bus 505 transmits information between various components (for example, the processor 501, the memory 502, the input / output interface 503, and the communication interface 504) of the device;

[0236] The processor 501, the memory 502, the input / output interface 503, and the communication interface 504 are communicatively connected with each other through the bus 505.

[0237] The embodiment of the present application further provides a storage medium, which is a computer readable storage medium, used for computer readable storage, and stores one or more programs, which can be executed by one or more processors to implement the vehicle longitudinal and lateral layered cooperative control method.

[0238] The memory is a non-transitory computer readable storage medium, and can be used to store non-transitory software programs and non-transitory computer executable programs. In addition, the memory can include a high-speed random access memory, and can further include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory can optionally include a memory remotely arranged relative to the processor, and these remote memories can be connected to the processor through a network. Examples of the network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0239] The embodiments described in the embodiments of the present application are used to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0240] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and can include more or fewer steps than those shown in the figures, or combine certain steps, or different steps.

[0241] The system embodiments described above are only schematic, and the units described as separate components can or can not be physically separate, that is, can be located in one place, or can be distributed on multiple network units. According to actual needs, part or all of the modules can be selected to achieve the purpose of the embodiments of the present application.

[0242] Those skilled in the art can understand that all or some steps in the above disclosed method, the function modules / units in the system and the device can be implemented as software, firmware, hardware and their appropriate combinations.

[0243] The terms "first", "second", "third", "fourth", and the like in the description and in the claims of this application, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the use of the terms so termed is interchangeable under appropriate circumstances such that the embodiments of the application described herein are, for example, capable of orderly or chronological mundane operation, or capable of selective operation at other than any order or chronology, except where the context of use of such terms clearly dictates otherwise. It is to be understood that the terms "comprising", "including", "containing", and / or "having" when used herein, specify the presence of stated features, integers, steps, operations, elements, and / or components but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0244] It should be understood that, in the application, "at least one" means one or more, and "multiple" means two or more. "And / or" is used to describe the relationship between associated objects, which means that there can be three relationships, for example, "A and / or B" can mean: only A, only B, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects. "At least one of the following" or similar expressions means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b or c, can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0245] In several embodiments provided in the application, it should be understood that the disclosed system and method can be implemented in other ways. For example, the above-described system embodiments are only illustrative, for example, the division of the above-mentioned units is only a logical function division, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be through some interface, indirect coupling or communication connection between systems or units, which can be electrical, mechanical or other forms.

[0246] The units described above as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed on multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment of the application.

[0247] In addition, each function unit in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software function unit.

[0248] If the integrated unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application, essentially or in part, or all or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes multiple instructions used to cause a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods in the embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program storage media.

[0249] The preferred embodiments of the embodiments of the present application are described above with reference to the accompanying drawings, and the scope of the rights of the embodiments of the present application is not limited thereto. Any modifications, equivalent replacements and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of the present application shall be within the scope of the rights of the embodiments of the present application.

Claims

1. A vehicle lateral and longitudinal hierarchical cooperative control method, characterized in that, Includes the following steps: Acquire the actual state quantities of the vehicle during its operation; Based on the zero-centimeter sideslip angle strategy, the desired driving state quantity is determined according to the actual state quantity and the desired trajectory. The desired driving state quantity includes the desired longitudinal velocity and the reference rotation angle of each axis. The zero-centimeter sideslip angle strategy assumes that the rotation angle of each axis has a preset proportional relationship. Based on the desired driving state quantities, longitudinal and lateral coordinated control is performed to obtain global longitudinal generalized force, global generalized lateral force, and global generalized yaw moment; The tire force is optimally distributed based on the global longitudinal generalized force, the global generalized lateral force, and the global generalized yaw moment to obtain the tire force of each wheel, wherein the tire force includes longitudinal force and lateral force. The tire force of each wheel is converted into the drive space to obtain the wheel angle and motor torque of each wheel used for driving the vehicle at the bottom layer. The zero-centimeter sideslip angle-based strategy, which determines the desired driving state quantity based on the actual state and the desired trajectory, includes the following steps: The desired longitudinal speed is determined based on the pedal state quantity in the actual state quantity. Based on the vehicle monorail model, the error dynamics model is determined according to the vehicle longitudinal velocity, vehicle lateral velocity, vehicle lateral acceleration, yaw rate and yaw acceleration in the actual state quantities. Based on the zero centroid sideslip angle strategy, the minimum performance index problem based on the error dynamics model is solved to obtain the reference rotation angle of each axis.

2. The vehicle lateral and longitudinal hierarchical cooperative control method according to claim 1, characterized in that, The step of performing longitudinal and lateral coordinated control based on the desired driving state quantities to obtain global longitudinal generalized force, global generalized lateral force, and global generalized yaw moment includes the following steps: The longitudinal speed error is determined based on the desired longitudinal speed and the actual longitudinal speed, and a PID control algorithm is used to feed the longitudinal speed error back to the PID controller to determine the global longitudinal generalized force. A two-degree-of-freedom linear vehicle model is used as a reference model. Based on the vehicle single-track model, the zero-centroid sideslip angle strategy, and the reference rotation angle, the ideal yaw rate and the ideal centroid sideslip angle are determined. The deviation of the yaw rate is determined based on the ideal yaw rate and the actual yaw rate, and the deviation of the center of mass side slip angle is determined based on the ideal center of mass sideslip angle and the actual center of mass sideslip angle. A lateral stability sliding mode controller is used to determine the global generalized lateral force and global generalized yaw moment based on the yaw rate deviation and the centroid sideslip angle deviation.

3. The vehicle lateral and longitudinal hierarchical cooperative control method according to claim 2, characterized in that, The method employs a lateral stability sliding mode controller to determine the global generalized lateral force and global generalized yaw moment based on the yaw rate deviation and the centroid sideslip angle deviation, including the following steps: The center of mass side slip angle sliding surface is determined based on the center of mass side slip angle deviation, and the yaw rate sliding surface is determined based on the yaw rate deviation and the integral term of the yaw rate deviation. The sliding mode approach rate is determined based on the sliding mode surface with the centroid side deviation angle and the sliding mode surface with the yaw rate. The global generalized lateral force and global generalized yaw moment that enable the vehicle to achieve the ideal yaw rate and ideal center-of-gravity sideslip angle are determined based on the sliding mode approach rate.

4. The vehicle lateral and longitudinal layered cooperative control method according to claim 3, characterized in that, The process of optimally distributing tire forces based on the global longitudinal generalized force, the global generalized lateral force, and the global generalized yaw moment to obtain the tire forces of each wheel includes the following steps: The dynamic vertical load of each wheel is determined using a dynamic vertical load calculation model. The adhesion force of each wheel is determined based on the dynamic vertical load and road adhesion coefficient of each wheel. The polyhedral friction constraints on the longitudinal and lateral forces of each tire are determined based on the adhesion force, and the actuator constraints on the changes in the longitudinal and lateral forces of each tire are determined based on the maximum torque, maximum torque change rate, and tire radius of each tire. Obtain the objective function for tire force distribution, and solve for the optimal solution of the objective function for tire force distribution based on the polyhedral friction constraint, the actuator constraint, and the desired generalized vector force to obtain the tire force of each wheel. The desired generalized vector force includes the global longitudinal generalized force, the global generalized lateral force, and the global generalized yaw moment.

5. The vehicle lateral and longitudinal layered cooperative control method according to claim 4, characterized in that, The tire force distribution objective function includes a first objective function that approximates the top-level generalized torque error and a second objective function that minimizes the tire load rate. The first objective function is expressed as: ； in, Let be the diagonal weighted matrix for each generalized torque. This is the gain efficiency matrix. For tire force distribution matrix, For the desired generalized vector force; The second objective function is expressed as: ； in, This is an angle-weighted matrix with respect to the load rate of each wheel. The tire force distribution matrix.

6. The vehicle lateral and longitudinal hierarchical cooperative control method according to claim 5, characterized in that, The process of converting the tire force of each wheel into the drive space to obtain the wheel angle and motor torque of each wheel for the underlying drive vehicle includes the following steps: Using the Dugoff tire inverse model, the slip angle of the wheel is calculated based on the tire force. The wheel angle of the wheel is determined based on the sideslip angle, the vehicle longitudinal velocity, the vehicle lateral velocity, and the vehicle yaw rate. Based on the torque balance equation, the motor torque of the wheel is determined according to the longitudinal force of the wheel.

7. A vehicle lateral and longitudinal hierarchical cooperative control system, characterized in that, include: The first module is used to acquire the actual state quantities during the vehicle's operation. The second module is used to determine the desired driving state quantity based on the actual state quantity and the desired trajectory, according to the zero centroid sideslip angle strategy. The desired driving state quantity includes the desired longitudinal speed and the reference rotation angle of each axis. The zero centroid sideslip angle strategy is that the rotation angle of each axis has a preset proportional relationship. The third module is used to perform longitudinal and lateral coordinated control based on the desired driving state quantity to obtain global longitudinal generalized force, global generalized lateral force and global generalized yaw moment; The fourth module is used to perform optimal tire force distribution based on the global longitudinal generalized force, the global generalized lateral force, and the global generalized yaw moment to obtain the tire force of each wheel, wherein the tire force includes longitudinal force and lateral force; The fifth module is used to convert the tire force of each wheel into the drive space, so as to obtain the wheel angle and motor torque of each wheel used to drive the vehicle at the bottom layer. The second module is specifically used to perform the following steps: The desired longitudinal speed is determined based on the pedal state quantity in the actual state quantity. Based on the vehicle monorail model, the error dynamics model is determined according to the vehicle longitudinal velocity, vehicle lateral velocity, vehicle lateral acceleration, yaw rate and yaw acceleration in the actual state quantities. Based on the zero centroid sideslip angle strategy, the minimum performance index problem based on the error dynamics model is solved to obtain the reference rotation angle of each axis.

8. An electronic device, characterized in that, The electronic device includes a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for enabling communication between the processor and the memory, wherein the program, when executed by the processor, implements the steps of the method as described in any one of claims 1 to 6.

9. A storage medium, said storage medium being a computer-readable storage medium for computer-readable storage, characterized in that, The storage medium stores one or more programs, which can be executed by one or more processors to implement the steps of the method according to any one of claims 1 to 6.

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