Vehicle transverse and longitudinal layered cooperative control method, system and equipment and storage medium

Abstract

The embodiment of the invention provides a vehicle transverse and longitudinal layered cooperative control method, system and device and a storage medium, and belongs to the technical field of vehicle control. According to the method, on the basis of a zero-centroid side slip angle strategy, an expected driving state quantity is determined according to an actual state quantity and an expected track, the expected driving state quantity comprises reference rotation angles of all axes, the zero-centroid side slip angle strategy is that the rotation angles of all the axes have a preset proportional relation, and then longitudinal and transverse cooperative control is conducted according to the expected driving state quantity. Global longitudinal generalized force, global generalized lateral force and global generalized yawing moment are obtained, optimal distribution of tire force is carried out on all the moments to obtain tire force of all wheels, and the tire force of all the wheels is converted into a driving space to obtain wheel rotation angles and motor torque of all the wheels of the bottom-layer driving vehicle. According to the invention, tracking control can be flexibly carried out on the vehicle, and the trajectory tracking precision and attitude stability of the vehicle in a complex environment are improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle control technology, and in particular to a method, system, device and storage medium for layered lateral and longitudinal coordinated control of a vehicle. Background Art

[0002] As the automotive industry accelerates its development towards electrification and intelligence, the chassis, as the key to vehicle driving performance, is undergoing a transformation from traditional mechanical to "wire-controlled chassis". The wire-controlled chassis controls the actuator through electrical signals, replacing the traditional mechanical connection method, greatly reducing parts and reducing costs. Especially in the field of heavy-duty transportation, traditional chassis face bottlenecks such as low transmission efficiency and complex structure, and cannot meet the modern demand for high mobility. The heavy-duty intelligent full-vector wire-controlled chassis refers to the use of full-vector driving angle module technology and intelligent networking technology. Its drive-steering integrated integrated electric wheel structure covers the vehicle's largest independent input set, and can achieve independent control of the longitudinal and lateral forces of all wheels. At the same time, it has the ability to freely combine and reconstruct intelligent collaborative capabilities, which can fully expand the vehicle's driving and use boundaries and has a very wide range of uses.

[0003] In the field of trajectory tracking algorithms for multi-axle heavy-duty vehicles, although some research has been done, due to the complex multi-axle vehicle model and the influence of extreme working conditions, related technologies still find it difficult to achieve high accuracy and robustness. In addition, due to the large volume of cargo and limited space in the work area, the vehicle has an urgent need for all-round mobility, multi-vehicle collaborative reconstruction and docking, which requires chassis control to effectively combine the expected path information and meet key tasks such as full-vector wire-controlled vehicle reconstruction and docking and formation coordination.

[0004] In the trajectory tracking control of the vehicle, the longitudinal force and lateral force generated by the tires are crucial to the vehicle's posture and dynamic performance. Especially when approaching the control limit, the nonlinear characteristics of the tire force will make the vehicle's dynamic behavior highly complex. In addition, affected by the road adhesion, the nonlinear saturation characteristics of the tires, the external characteristics of the hub motors and the limitations of the steering mechanism, the full vector wire control system of the multi-axis unmanned heavy-duty vehicle becomes a complex system with overdrive, underdetermination and multiple constraints. At present, the tracking control of such a complex system has problems such as poor flexibility and weak fault tolerance, resulting in low trajectory tracking accuracy and posture stability of the vehicle in complex environments. Summary of the invention

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

[0006] To achieve the above purpose, one aspect of an embodiment of the present application proposes a vehicle lateral and longitudinal layered coordinated control method, comprising the following steps:

[0007] Obtain the actual state quantity of the vehicle during driving;

[0008] Based on the zero-center-of-mass sideslip angle strategy, determining an expected driving state quantity according to the actual state quantity and the expected trajectory, wherein the expected driving state quantity includes an expected longitudinal speed and a reference turning angle of each axis, and the zero-center-of-mass sideslip angle strategy is that the turning angles of each axis have a preset proportional relationship;

[0009] Performing longitudinal and lateral coordinated control according to the desired driving state quantity to obtain a global longitudinal generalized force, a global generalized lateral force and a global generalized yaw moment;

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

[0011] The tire force of each wheel is converted into the driving space to obtain the wheel angle and motor torque of each wheel for the underlying driving vehicle.

[0012] In some embodiments, the method of determining the expected driving state quantity based on the zero center of mass sideslip angle strategy according to the actual state and the expected trajectory includes the following steps:

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

[0014] Based on the vehicle single track model, an error dynamics model is determined according to the vehicle longitudinal velocity, the vehicle lateral velocity, the vehicle lateral acceleration, the yaw velocity and the yaw angular acceleration in the actual state quantities;

[0015] Based on the zero center of mass 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.

[0016] In some embodiments, the performing longitudinal and lateral coordinated control according to the desired driving state quantity to obtain the global longitudinal generalized force, the global generalized lateral force and the global generalized yaw moment comprises the following steps:

[0017] Determining a longitudinal velocity error based on the desired longitudinal velocity and the actual longitudinal velocity, and using a PID control algorithm to feed back the longitudinal velocity error to a PID controller to determine a global longitudinal generalized force;

[0018] Using a two-degree-of-freedom linear vehicle model as a reference model, determining an ideal yaw rate and an ideal center-of-mass sideslip angle according to the vehicle single-track model, the zero center-of-mass sideslip angle strategy and the reference turning angle;

[0019] Determine a yaw rate deviation according to the ideal yaw rate and the actual yaw rate, and determine a center of mass sideslip angle deviation according to the ideal center of mass sideslip angle and the actual center of mass sideslip angle;

[0020] A lateral stability sliding mode controller is adopted to determine the global generalized lateral force and the global generalized yaw moment according to the yaw rate deviation and the center of mass sideslip angle deviation.

[0021] In some embodiments, the adopting of a lateral stability sliding mode controller to determine a global generalized lateral force and a global generalized yaw moment according to the yaw rate deviation and the center of mass sideslip angle deviation comprises the following steps:

[0022] Determining a center of mass sideslip angle sliding mode surface according to the center of mass sideslip 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 approach rate according to the center of mass sideslip angle sliding mode surface and the yaw angular velocity sliding mode surface;

[0024] The global generalized lateral force and the global generalized yaw moment that enable the vehicle to reach an ideal yaw angular velocity and an ideal sideslip angle of the center of mass are determined according to the sliding mode approaching rate.

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

[0026] Determine the dynamic vertical load of each wheel using the dynamic vertical load calculation model of each wheel;

[0027] Determining the adhesion of each wheel according to the dynamic vertical load of each wheel and the road adhesion coefficient;

[0028] Determine a polyhedral friction constraint on the longitudinal and lateral forces of each tire according to the adhesion, and determine an actuator constraint on the change amount of the longitudinal and lateral forces of each tire according to the maximum torque of each tire, the maximum rate of change of the torque and the tire radius;

[0029] A tire force distribution objective function is obtained, and an optimal solution of the tire force distribution objective function is solved according to the polyhedron friction constraint, the actuator constraint and the expected generalized vector force to obtain the tire force of each wheel, wherein the expected generalized vector force includes a global longitudinal generalized force, a global generalized lateral force and a global generalized yaw moment.

[0030] In some embodiments, the tire force distribution objective function includes a first objective function for approximating the top-level generalized moment error and a second objective function for minimizing the tire load rate;

[0031] The first objective function is expressed as:

[0032]

[0033] Among them, W v is the diagonal weighted matrix of each generalized moment, B is the gain efficiency matrix, u is the tire force distribution matrix, and A is the desired generalized vector force;

[0034] The second objective function is expressed as:

[0035]

[0036] Among them, W u is the angular weighting matrix regarding the load rate of each wheel, and u is the tire force distribution matrix.

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

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

[0039] The wheel angle of the wheel according to the sideslip angle, the longitudinal speed of the vehicle, the lateral speed of the vehicle, and the yaw speed of the vehicle;

[0040] Based on the torque balance equation, the motor torque of the wheel is determined according to the longitudinal force of the wheel.

[0041] To achieve the above objectives, another aspect of the embodiment of the present application provides a vehicle lateral and longitudinal hierarchical coordinated control system, including:

[0042] The first module is used to obtain the actual state quantity of the vehicle during driving;

[0043] A second module is used to determine an expected driving state quantity according to the actual state quantity and the expected trajectory based on a zero center of mass sideslip angle strategy, wherein the expected driving state quantity includes an expected longitudinal speed and a reference turning angle of each axis, and the zero center of mass sideslip angle strategy is that the turning angles of each axis have a preset proportional relationship;

[0044] A third module is used to perform longitudinal and lateral coordinated control according to the desired driving state quantity to obtain a global longitudinal generalized force, a global generalized lateral force and a global generalized yaw moment;

[0045] a fourth module, configured to optimally distribute 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 include longitudinal forces and lateral forces;

[0046] The fifth module is used to convert the tire force of each wheel into the driving space to obtain the wheel angle and motor torque of each wheel for the underlying driving vehicle.

[0047] To achieve the above-mentioned purpose, another aspect of an embodiment of the present application proposes an electronic device, which includes a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for realizing connection and communication between the processor and the memory, and the program implements the method described in the above embodiment when executed by the processor.

[0048] To achieve the above-mentioned purpose, another aspect of an embodiment of the present application proposes a storage medium, which is a computer-readable storage medium used for computer-readable storage, and the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the method described in the above embodiment.

[0049] The vehicle lateral and longitudinal layered cooperative control method, system, device and storage medium proposed in the present application are based on the zero center of mass sideslip angle strategy, and the expected driving state quantity is determined according to the actual state quantity and the expected trajectory. The expected driving state quantity includes the expected longitudinal speed and the reference turning angle of each axis. The zero center of mass sideslip angle strategy is that the turning angle of each axis has a preset proportional relationship, and then the longitudinal and lateral cooperative control is performed according to the expected driving state quantity to obtain the global longitudinal generalized force, the global generalized lateral force and the global generalized yaw moment, and then the tire force is optimally distributed according to the global longitudinal generalized force, the global generalized lateral force and the global generalized yaw moment to obtain the tire force of each wheel, and the tire force of each wheel is converted to the driving space to obtain the wheel turning angle and motor torque of each wheel for the bottom driving vehicle. In view of the complexity of the driving behavior of vehicles with multiple driving steering axes, the present application constructs a vehicle dynamics model, and combines the zero center of mass sideslip angle control strategy to make the equivalent turning angle of the wheels of other axes proportional to the equivalent turning angle of the wheels of the reference axis, thereby improving the accuracy and efficiency of path tracking. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 is a flow chart of a vehicle lateral and longitudinal layered collaborative control method provided in an embodiment of the present application;

[0051] Figure 2 is a graph of the steering ratios of each axle to the first axle as the vehicle speed changes, provided in an embodiment of the present application;

[0052] Figure 3 It is a schematic diagram of the 11DOF maneuvering dynamics model of a full-vector four-axis unmanned heavy-duty vehicle provided in an embodiment of the present application;

[0053] Figure 4 It is a schematic diagram of the vehicle horizontal and vertical layered collaborative control process provided by an embodiment of the present application;

[0054] Figure 5 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used 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 may be performed in a different order than the module division in the system or the order in the flowchart. The terms "first", "second", etc. in the specification, claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0057] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

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

[0059] The vehicle lateral and longitudinal layered collaborative control method, system, device and storage medium provided in the embodiments of the present application are specifically illustrated through 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 horizontal and vertical layered collaborative control method provided in the embodiment of the present application relates to the field of vehicle control technology. The vehicle horizontal and vertical layered collaborative control method provided in the embodiment of the present application can be applied to a terminal, can also be applied to a server side, and can also be software running in a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or a server cluster or a distributed system composed of multiple physical servers, and can also be configured as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the vehicle horizontal and vertical layered collaborative control method, etc., but is not limited to the above forms.

[0061] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0062] Figure 1 is an optional flow chart of the vehicle lateral and longitudinal layered collaborative control method provided in an embodiment of the present application, Figure 1 The method may include but is not limited to steps S101 to S105.

[0063] Step S101, obtaining the actual state quantity of the vehicle during driving;

[0064] Step S102, based on the zero center of mass sideslip angle strategy, determining the expected driving state quantity according to the actual state quantity and the expected trajectory, wherein the expected driving state quantity includes the expected longitudinal speed and the reference turning angle of each axis, and the zero center of mass sideslip angle strategy is that the turning angle of each axis has a preset proportional relationship;

[0065] Step S103, performing longitudinal and lateral coordinated control according to the desired driving state quantity to obtain a global longitudinal generalized force, a global generalized lateral force and a global generalized yaw moment;

[0066] Step S104, performing optimal tire force distribution according to 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 the longitudinal force and the lateral force;

[0067] Step S105, converting the tire force of each wheel into the driving space to obtain the wheel angle and motor torque of each wheel for bottom-level driving of the vehicle.

[0068] In step S101 of some embodiments, the present application embodiment is described with a four-axle eight-wheel full vector wire-controlled chassis vehicle. The actual state quantity of the vehicle during driving is estimated by on-board sensors and a full-scale vehicle dynamics model based on mechanism analysis-data drive, and the actual state quantity includes but is not limited to: wheel speed, wheel angle, vehicle longitudinal speed, longitudinal acceleration, vehicle lateral speed, lateral acceleration, yaw angle, yaw angular velocity and road friction coefficient, etc.

[0069] In step S102 of some embodiments, the longitudinal velocity v of the vehicle obtained in step S101 is x , vehicle lateral speed v y , vehicle lateral acceleration Yaw speed Yaw angular acceleration According to the vehicle single-track model, the adaptive path tracking error dynamics model is derived. Combined with the zero center of mass sideslip angle control strategy, the reference angles of each axis based on path tracking are calculated, and the expected longitudinal speed is determined.

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

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

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

[0073] Step S203, based on the zero center of mass sideslip angle strategy, solve the minimum performance index problem based on the error dynamics model to obtain the reference angle of each axis.

[0074] For example, the expected longitudinal speed may be determined according to the pedal state quantity in the actual state quantity obtained in S101 .

[0075] According to the vehicle longitudinal velocity v obtained in step S101 x , vehicle lateral speed v y , vehicle lateral acceleration Yaw speed Yaw angular acceleration The state space of the four-axle unmanned heavy-duty vehicle single track model is as follows:

[0076]

[0077] Among them, C αi is the equivalent cornering stiffness of each axis, δ i is the equivalent rotation angle of each axis, n is the vehicle mass, li is the distance from each axis to the center of mass, v x 、v y They represent the longitudinal speed of the vehicle's mass center along the x-axis and the lateral speed along the y-axis, respectively. and represents the yaw rate and yaw acceleration, I z is the yaw moment of inertia.

[0078] The path tracking controller is designed for a wire-controlled full-vector four-axis unmanned heavy-duty vehicle using LQR control. Since it is based on the zero-center-of-mass sideslip angle control strategy, the heading angle θ is expressed as the yaw angle. Instead, the lateral error e of the vehicle in tracking the desired path d and heading error as follows:

[0079]

[0080] in, is the desired path heading angular velocity.

[0081] Based on the zero center of mass sideslip angle strategy, the equivalent rotation angle of each axis δ i There is a certain proportional relationship between them, as follows:

[0082]

[0083] in:

[0084] Where, L ri is the distance from each axis to the steering centerline, L 12 , L 13 , L 14 is the distance from the first axis to the second, third, and fourth axes.

[0085] Combining formulas (1), (2), and (3), a wire-controlled full-vector four-axis unmanned heavy-duty vehicle is established with a lateral error e d , lateral error rate Heading Error and heading error rate The adaptive error dynamics model of the state variable is as follows:

[0086]

[0087] In the formula,

[0088]

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

[0090]

[0091] Where Q and R represent the weighting matrix of the controller.

[0092] In order to minimize J, the problem is converted into solving a quadratic optimal problem as follows:

[0093]

[0094] Take the derivative of formula (6) and find the extreme value:

[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 the Riccati equation in formula (7):

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

[0098] To eliminate the The impact of and e rr can be 0 at the same time. Therefore, feedforward control needs to be introduced. At this time, the control law considering both feedforward and feedback is as follows:

[0099] U=-Ke rr +δ1; (9)

[0100] In the formula: K = [K1, K2, K3, K4].

[0101] Substituting formula (9) into formula (4) yields:

[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 center of mass sideslip angle strategy, the curve of the steering ratio of each axle to the first axle as the vehicle speed changes is as follows: Figure 2It can be seen that when the vehicle speed is low, M2 and M3 are negative, and the full-vector four-axle unmanned heavy-duty vehicle turns in reverse phase sequence, which obtains greater steering flexibility; as the vehicle speed increases, M2 and M3 change from negative to positive, and the full-vector four-axle unmanned heavy-duty vehicle changes from reverse phase sequence to the same direction, which greatly improves the stability during steering.

[0108] In step S103 of some embodiments, based on the reference turning angle obtained in step S102, the top-level reference state generator uses a two-degree-of-freedom linear vehicle model as a reference model and combines it with an 11-degree-of-freedom handling dynamics vehicle model to calculate the global longitudinal generalized force F under the desired driving state. xc , global generalized lateral force F yc and the global generalized yaw moment M zc .

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

[0110] Step S301, determining a longitudinal velocity error according to the desired longitudinal velocity and the actual longitudinal velocity, and using a PID control algorithm to feed back the longitudinal velocity error to a PID controller to determine a global longitudinal generalized force;

[0111] Step S302, using a two-degree-of-freedom linear vehicle model as a reference model, and determining an ideal yaw rate and an ideal center-of-mass sideslip angle according to a vehicle single-track model, a zero center-of-mass sideslip angle strategy, and a reference turning 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 sideslip angle deviation according to the ideal center of mass sideslip angle and the actual center of mass sideslip angle;

[0113] Step S304: using a lateral stability sliding mode controller, the global generalized lateral force and the global generalized yaw moment are determined according to the yaw rate deviation and the center of mass sideslip angle deviation.

[0114] For example, when the top-level reference state generator is used, the two-degree-of-freedom linear vehicle model is used as the reference model, and the 11DOF handling dynamics vehicle model is combined, which focuses on the longitudinal, lateral and yaw motion of the vehicle and the rotation of the eight wheels. The 11DOF dynamics model of the full vector four-axis unmanned heavy-duty vehicle is as follows: Figure 3 , the equation of motion is as follows:

[0115] Differential equation of longitudinal motion:

[0116]

[0117] Differential equation for lateral motion:

[0118]

[0119] Differential equation of yaw motion:

[0120]

[0121] The differential equation of rotational motion is expressed as follows:

[0122]

[0123] Among them: F x 、F y 、M z are the longitudinal force, lateral force and yaw moment of the vehicle in the vehicle body coordinate system, i = 1, 2, 3, 4; d i is half of the track width of the i-th axle, F xil 、F xir represents the ground longitudinal force of the left and right tires of the i-th axis 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 on the wheel, R w is the wheel rolling radius, F yil 、F yir represents the ground lateral force on the left and right sides of the i-th axis in the tire-body coordinate system. They are the components of the tire force in the vehicle coordinate system. In the tire coordinate system, the longitudinal force on the left and right sides of the i-th axis is expressed as F xwil 、F xwir , the lateral force is denoted by F ywil 、F ywir , the tire force relationship between the vehicle coordinate system and the tire coordinate system is as follows:

[0124]

[0125] Among them, δ il ,δ ir are the left and right wheel turning angles of each axle respectively.

[0126] Furthermore, it is necessary to calculate the ideal center of mass sideslip angle β d and the ideal yaw rate When the car reaches a steady state, the vehicle's center of mass sideslip angle is zero and the yaw rate is a constant, that is, Combining equations (1), (3) and (11), we can get the distance L from axis 1 to the steering centerline: r1 for:

[0127]

[0128] Combining the relationship between the rear three-axis rotation angle and the axis 1 rotation angle, and comparing it with the stability factor K of a two-axle vehicle in automobile theory, the ideal yaw rate and ideal center of mass sideslip angle of a four-axis full vector vehicle can be obtained as follows:

[0129]

[0130] The expressions of the equivalent wheelbase L' and stability factor K of the four-axis full vector vehicle are as follows:

[0131]

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

[0133]

[0134] Among them, K p is the proportional gain, K i is the integral gain, K d Derivative gain.

[0135] The vehicle lateral control adopts sliding mode control to achieve precise dynamic control of the vehicle and meet the safety driving requirements under heavy load conditions. The vehicle lateral and yaw state equations are organized as follows by combining equations (13) and (14):

[0136]

[0137] Among them, ξ1 and ξ2 are interference items caused by the inside or outside of the vehicle control system.

[0138] The control quantity deviation of the controller (center of mass sideslip angle deviation e1 and yaw angular velocity deviation e2) is:

[0139]

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

[0141] Step S401, determining a center of mass sideslip angle sliding surface according to the center of mass sideslip angle deviation, and determining a yaw rate sliding surface according to the yaw rate deviation and an integral term of the yaw rate deviation;

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

[0143] Step S403, determining the global generalized lateral force and the global generalized yaw moment that enable the vehicle to reach an ideal yaw angular velocity and an ideal sideslip angle of the center of mass according to the sliding mode approaching rate.

[0144] For example, since the center of mass sideslip angle expression contains the yaw rate, the control accuracy of the yaw rate is related to M zc and F yc In order to reduce the cumulative error about time caused by drift, the sliding mode control state variable of the yaw rate is increased by an integral term to form a closed-loop feedback, and the tracking error of the yaw rate is revised. The sliding surface (the sliding surface of the sideslip angle at the center of mass) β and the yaw rate sliding surface ) is designed as follows:

[0145]

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

[0147] In order to realize dynamic sliding mode, the exponential approach law is selected. At the same time, in order to overcome the chattering problem caused by the discontinuous sign function s ign(s), it is replaced by a continuous tanh(s) function. The sliding mode approach rate is designed as:

[0148]

[0149] Where: ε is the boundary layer thickness, k is the approach rate exponent, ε1, ε2, k1, and k2 are all positive numbers.

[0150] The global generalized lateral force F required by the vehicle can then be deduced yc and the global generalized yaw moment M zc as follows:

[0151]

[0152] In step S104 of some embodiments, a dynamic vertical load calculation model is established. According to the longitudinal acceleration and vehicle lateral acceleration obtained in real time in step S101, the middle tire force distribution layer comprehensively considers the friction circle constraint, the actuator physical constraint and the change rate constraint, manages and distributes the tire force from the tire level, and constructs an objective function of approximating the top-level generalized moment error and minimizing the tire load rate, so as to achieve the optimal distribution of tire lateral and longitudinal forces based on the global longitudinal generalized force, the global generalized lateral force and the global generalized yaw moment.

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

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

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

[0156] Step S503, determining a polyhedral friction constraint on the longitudinal and lateral forces of each tire according to the adhesion, and determining an actuator constraint on the variation of the longitudinal and lateral forces of each tire according to the maximum torque of each tire, the maximum rate of torque variation and the tire radius;

[0157] Step S504, obtaining the tire force distribution objective function, and solving the optimal solution of the tire force distribution objective function according to the polyhedron friction constraint, the actuator constraint and the expected generalized vector force to obtain the tire force of each wheel, wherein the expected generalized vector force includes the global longitudinal generalized force, the global generalized lateral force and the global generalized yaw moment.

[0158] For example, to establish a dynamic vertical load calculation model, it is necessary to comprehensively consider the vehicle's lateral acceleration and longitudinal acceleration, and ignore the vehicle's roll, pitch, and heave. The tire vertical force can be calculated from 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] Among them, m s is the sprung mass of the vehicle body, and g is the acceleration due to gravity.

[0162] in:

[0163]

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

[0165]

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

[0167] The dynamic change of tire vertical load caused by vehicle body posture is mainly reflected in the longitudinal acceleration and lateral acceleration when the vehicle accelerates / decelerates or turns, causing the load on the vehicle body spring to transfer to the front and back, left and right. The change of vertical load on each axle caused by longitudinal acceleration is divided by the center of mass, with axles 1 and 2 equivalent to the front axle and axles 2 and 3 equivalent to the rear axle, and then the front and back load transfer amount of each tire is distributed. If the vertical load change of the left and right wheels on the same axis is the same, the calculation method is as follows:

[0168]

[0169] in,

[0170] Where: ΔF ziax is the change in vertical load transfer caused by the longitudinal acceleration of the tire on one side of the i-th axle, h is the height of the center of mass, and a x is the longitudinal acceleration of the vehicle.

[0171] The vertical load change caused by lateral acceleration is equal in magnitude and opposite in direction (left plus, right minus) for the left and right wheels on the same axis. At the same time, the lateral force is regarded as distributed on each axle according to the load ratio of each axle, and is calculated as follows:

[0172]

[0173] Where: ΔF z1ay B is the change in vertical load transfer caused by the longitudinal acceleration of the tire on the i-th axle. i is the wheelbase of each axle, a y is the lateral acceleration of the vehicle.

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

[0175]

[0176] The friction circle constraint needs to be considered in the middle tire force distribution layer. To speed up the solution time, the friction circle constraint uses the circumscribed octagon to obtain the linear description of the original constraint, that is, the polyhedron friction constraint is as follows:

[0177]

[0178] Among them, μ ij Represents the road adhesion coefficient, μ ij F zij Indicates the adhesion of the wheel.

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

[0180]

[0181] Where, T ij,max , k xij,maxis the maximum torque and maximum change rate of each tire under the motor execution constraint, Δt is the control step length, 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 The longitudinal and lateral changes of the tire under the unit control step length.

[0182] Next, the objective function is designed, and the expected generalized vector force A = [F xc ,F yc ,M zc ] T The tire longitudinal and lateral forces u = [F xwil F xwir F ywil F ywir ] T The gain efficiency matrix Β between them is used to construct the objective function J1 for the top-level generalized moment error approximation. Combining equations (12), (13), (14), and (16), firstly, the wheelbase l of each axis is i Redefine as follows:

[0183]

[0184] Then the state space equation of the longitudinal and lateral tire forces in the distribution layer, which is converted from the vehicle body coordinate system to the tire coordinate system, can be expressed as:

[0185]

[0186] Establish the expected global generalized moment of the top-level input [F xc F yc M zc ] T The longitudinal and lateral forces of each tire output by the middle distribution layer [F xwil F xwir F ywil F ywir ] T The gain efficiency matrix B 3×16 as follows:

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

[0188] in:

[0189]

[0190] Then, the error approximation function is:

[0191]

[0192] in, is a diagonal weighted matrix, which can be adjusted in real time according to control needs. ν Represents the importance of the expected generalized moment in the error approximation objective function.

[0193] The Dugoff tire model is established to calculate the longitudinal force F of the tire under the combined action of longitudinal and lateral slip. xwij and the lateral force F ywij , construct the objective function J2 with the lowest tire load rate. The calculation formula of the Dugoff tire model is as follows:

[0194]

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

[0196]

[0197] The longitudinal force F calculated based on the Dugoff tire model xwij and the lateral force F ywij , define tire load factor ρ ij for:

[0198]

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

[0200]

[0201] in:

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

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

[0204]

[0205] Among them, η is the coordination factor, which ensures that the error approximation objective function value is small in the process of solving the optimal solution, and the expected state is achieved. The optimal control allocation algorithm based on quadratic programming is adopted, and the active set method is used to solve it. Finally, the desired tire longitudinal force F of the 8 corner modules is calculated. xwij and tire lateral force F ywij .

[0206] In step S105 of some embodiments, the bottom layer driving execution layer converts the tire longitudinal force F obtained in step S104 into xwij and tire lateral force F ywij Combined with the Dugoff tire inverse model, the tire force is converted into the driving space, and the tire force is converted into motor torque and wheel angle to achieve the lateral and longitudinal layered coordinated control of the whole vehicle, providing chassis domain control support for the key tasks such as full vector wire-controlled vehicle reconstruction docking and formation coordination. Further, the real-time status information of the vehicle is returned to step S102 to repeat the method of the embodiment of the present application to achieve real-time control of the vehicle.

[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 to calculate the sideslip angle of the wheel according to the tire force of the wheel;

[0209] Step S602, determining the wheel angle of the wheel according to the sideslip angle, the longitudinal speed of the vehicle, the lateral speed of the vehicle, and the yaw speed of the vehicle;

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

[0211] For example, this embodiment uses the Dugoff inverse model to design the underlying drive execution layer to complete the conversion of tire force to drive space and convert the tire force into the wheel angle δ ij and motor torque T ij .

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

[0213]

[0214] in:

[0215] Combined with the Dugoff tire inverse model, the wheel angle δ ij The sideslip angle α obtained by the inverse model ij The relationship between them is as follows:

[0216]

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

[0218]

[0219] Where: 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 on the wheel, R w is the wheel rolling radius.

[0220] According to some embodiments of this application, please refer to Figure 4 In order to cope with the dynamic requirements of multi-axle heavy-load vehicles under complex driving conditions, the embodiment of the present application estimates the state quantity of the vehicle during driving through on-board sensors and a full-scale vehicle dynamics model based on mechanism analysis-data-driven; then, based on the vehicle single-track model, the path tracking error dynamics model is derived, and the reference angle and expected longitudinal speed of each axis under path tracking are calculated in combination with the zero-center-of-mass sideslip angle control strategy; a top-level reference state generator is designed, and a two-degree-of-freedom linear vehicle model is used as a reference model, combined with an 11-degree-of-freedom handling dynamics vehicle model, and the global generalized lateral force F under the expected driving state is calculated through a lateral stability sliding mode controller. yc and the global generalized yaw moment M zc , and the global longitudinal generalized force F is calculated by the longitudinal PID speed tracking controller xc ; Then, a dynamic vertical load calculation model is established, and the middle tire force distribution layer is designed. The friction circle constraint, the actuator physical constraint and the change rate constraint are comprehensively considered, the tire force is managed and distributed from the tire level, and the objective function of approximating the top-level generalized torque error and minimizing the tire load rate is constructed to achieve the optimal distribution of the tire lateral and longitudinal forces; finally, the bottom-level drive execution layer is designed to combine the tire lateral and longitudinal forces obtained by the middle distribution layer with the Dugoff tire inverse model, complete the conversion of tire force to drive space, and convert the tire force into motor torque and wheel angle, so as to realize the lateral and longitudinal layered coordinated control of the whole vehicle.

[0221] The embodiment of the present application constructs a full-vector wire-controlled super-heavy-load vehicle dynamics model, and combines the zero-side offset center of mass angle control strategy to achieve proportional control between the equivalent turning angles of the wheels of the second, third, and fourth axles and the equivalent turning angles of the wheels of the first axle, thereby significantly improving the accuracy of path tracking and the efficiency of dynamic response. Based on the dynamic vertical load calculation model, the dynamic influence of the vehicle body posture on the vertical load of the tire is fully considered, especially during the acceleration, deceleration or turning of the vehicle, the front-to-back and left-to-right transfer of the sprung load caused by the longitudinal and lateral acceleration, and the dynamic behavior of the vehicle is fully captured and simulated. The evolution mechanism of the modular "longitudinal-lateral" dynamic coupling characteristics is carried out, and the interaction and influence between dynamics in different directions are deeply understood. The dynamic vertical load calculation model of this embodiment improves the calculation accuracy of the vertical load, is suitable for heavy-load transportation under complex working conditions, and lays a solid foundation for the application of unmanned heavy-load vehicles in high-precision dynamic control. In addition, the embodiment of the present application constructs a hierarchical longitudinal-lateral collaborative motion control strategy for the complex driving requirements of full-vector wire-controlled four-axis unmanned heavy-load vehicles. By decomposing the motion control target layer by layer, not only can the computational burden be effectively reduced, but the Dugoff tire inverse model is also introduced to decouple the lateral and longitudinal forces of the tire, achieving independent control and layered coordination. This strategy enables the vehicle to accurately track the desired motion state and significantly improve driving performance under extreme conditions.

[0222] The present application also provides a vehicle lateral and longitudinal hierarchical coordinated control system, including:

[0223] The first module is used to obtain the actual state quantity of the vehicle during driving;

[0224] The second module is used to determine the expected driving state quantity according to the actual state quantity and the expected trajectory based on the zero center of mass sideslip angle strategy, wherein the expected driving state quantity includes the expected longitudinal speed and the reference turning angle of each axis, and the zero center of mass sideslip angle strategy is that the turning angle of each axis has a preset proportional relationship;

[0225] The third module is used to perform longitudinal and lateral coordinated control according to the desired driving state quantity, and obtain the global longitudinal generalized force, the global generalized lateral force and the global generalized yaw moment;

[0226] A fourth module is used to optimally distribute 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 include longitudinal forces and lateral forces;

[0227] The fifth module is used to convert the tire force of each wheel into the driving space to obtain the wheel angle and motor torque of each wheel for the underlying driving vehicle.

[0228] It can be understood that the contents of the above-mentioned vehicle lateral and longitudinal layered collaborative control method embodiments are applicable to the present system embodiments, the functions specifically implemented by the present system embodiments are the same as those in the above-mentioned vehicle lateral and longitudinal layered collaborative control method embodiments, and the beneficial effects achieved are also the same as those achieved by the above-mentioned vehicle lateral and longitudinal layered collaborative control method embodiments.

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

[0230] See also Figure 5 , Figure 5 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:

[0231] The processor 501 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0232] The memory 502 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 502 can store an operating system and other applications. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 502, and the processor 501 calls and executes the vehicle horizontal and vertical layered cooperative control method of the embodiment of this application;

[0233] Input / output interface 503, used to implement information input and output;

[0234] Communication interface 504, used to realize communication interaction between the device and other devices, which can be realized by wired mode (such as USB, network cable, etc.) or wireless mode (such as mobile network, WIFI, Bluetooth, etc.);

[0235] A bus 505 that transmits information between the various components of the device (e.g., the processor 501, the memory 502, the input / output interface 503, and the communication interface 504);

[0236] The processor 501 , the memory 502 , the input / output interface 503 and the communication interface 504 are connected to each other in communication within the device via the bus 505 .

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

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

[0239] The embodiments described in the embodiments of the present application are intended 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 in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

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

[0241] The system embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

[0242] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0243] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0244] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural 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, c can be single or multiple.

[0245] In the several embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or units, which can be electrical, mechanical or other forms.

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

[0247] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0248] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0249] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A vehicle lateral and longitudinal layered coordinated control method, characterized in that: The following steps are involved: Obtain the actual state quantity of the vehicle during driving; Based on the zero-center-of-mass sideslip angle strategy, determining an expected driving state quantity according to the actual state quantity and the expected trajectory, wherein the expected driving state quantity includes an expected longitudinal speed and a reference turning angle of each axis, and the zero-center-of-mass sideslip angle strategy is that the turning angles of each axis have a preset proportional relationship; Performing longitudinal and lateral coordinated control according to the desired driving state quantity to obtain a global longitudinal generalized force, a global generalized lateral force and a global generalized yaw moment; Performing optimal tire force distribution according to the global longitudinal generalized force, the global generalized lateral force and the global generalized yaw moment to obtain 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 driving space to obtain the wheel angle and motor torque of each wheel for the underlying driving vehicle.

2. The vehicle lateral and longitudinal layered coordinated control method according to claim 1, characterized in that: The method based on the zero center of mass sideslip angle strategy, determining the expected driving state quantity according to the actual state and the expected trajectory, comprises the following steps: determining a desired longitudinal speed according to a pedal state quantity in the actual state quantity; Based on the vehicle single track model, an error dynamics model is determined according to the vehicle longitudinal velocity, the vehicle lateral velocity, the vehicle lateral acceleration, the yaw velocity and the yaw angular acceleration in the actual state quantities; Based on the zero center of mass 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.

3. The vehicle lateral and longitudinal layered coordinated control method according to claim 2, characterized in that: The longitudinal and lateral coordinated control is performed according to the expected driving state quantity to obtain the global longitudinal generalized force, the global generalized lateral force and the global generalized yaw moment, comprising the following steps: Determining a longitudinal velocity error based on the desired longitudinal velocity and the actual longitudinal velocity, and using a PID control algorithm to feed back the longitudinal velocity error to a PID controller to determine a global longitudinal generalized force; Using a two-degree-of-freedom linear vehicle model as a reference model, determining an ideal yaw rate and an ideal center-of-mass sideslip angle according to the vehicle single-track model, the zero center-of-mass sideslip angle strategy and the reference turning angle; Determine a yaw rate deviation according to the ideal yaw rate and the actual yaw rate, and determine a center of mass sideslip angle deviation according to the ideal center of mass sideslip angle and the actual center of mass sideslip angle; A lateral stability sliding mode controller is adopted to determine the global generalized lateral force and the global generalized yaw moment according to the yaw rate deviation and the center of mass sideslip angle deviation.

4. The vehicle lateral and longitudinal layered coordinated control method according to claim 3 is characterized in that: The method of using a lateral stability sliding mode controller to determine a global generalized lateral force and a global generalized yaw moment according to the yaw rate deviation and the center of mass sideslip angle deviation comprises the following steps: Determining a center of mass sideslip angle sliding mode surface according to the center of mass sideslip 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; Determining a sliding mode approach rate according to the center of mass sideslip angle sliding mode surface and the yaw angular velocity sliding mode surface; The global generalized lateral force and the global generalized yaw moment that enable the vehicle to reach an ideal yaw angular velocity and an ideal sideslip angle of the center of mass are determined according to the sliding mode approaching rate.

5. The vehicle lateral and longitudinal layered coordinated control method according to claim 4, characterized in that: The step of optimally distributing tire forces according to the global generalized longitudinal force, the global generalized lateral force, and the global generalized yaw moment to obtain tire forces of each wheel comprises the following steps: Determine the dynamic vertical load of each wheel using the dynamic vertical load calculation model of each wheel; Determining the adhesion of each wheel according to the dynamic vertical load of each wheel and the road adhesion coefficient; Determine a polyhedral friction constraint on the longitudinal and lateral forces of each tire according to the adhesion, and determine an actuator constraint on the change amount of the longitudinal and lateral forces of each tire according to the maximum torque of each tire, the maximum rate of change of the torque and the tire radius; A tire force distribution objective function is obtained, and an optimal solution of the tire force distribution objective function is solved according to the polyhedron friction constraint, the actuator constraint and the expected generalized vector force to obtain the tire force of each wheel, wherein the expected generalized vector force includes a global longitudinal generalized force, a global generalized lateral force and a global generalized yaw moment.

6. The vehicle lateral and longitudinal layered coordinated control method according to claim 5, characterized in that: The tire force distribution objective function includes a first objective function for approximating the top-level generalized moment error and a second objective function for minimizing the tire load rate; The first objective function is expressed as: Among them, W v is the diagonal weighted matrix of each generalized moment, B is the gain efficiency matrix, u is the tire force distribution matrix, and A is the desired generalized vector force; The second objective function is expressed as: Among them, W u is the angular weighting matrix regarding the load rate of each wheel, and u is the tire force distribution matrix.

7. The vehicle lateral and longitudinal layered coordinated control method according to claim 6, characterized in that: The step of converting the tire force of each wheel into the driving space to obtain the wheel angle and motor torque of each wheel for driving the vehicle at the bottom layer includes the following steps: Calculating the side slip angle of the wheel according to the tire force of the wheel using the Dugoff tire inverse model; The wheel angle of the wheel according to the sideslip angle, the longitudinal speed of the vehicle, the lateral speed of the vehicle, and the yaw speed of the vehicle; Based on the torque balance equation, the motor torque of the wheel is determined according to the longitudinal force of the wheel.

8. A vehicle lateral and longitudinal hierarchical cooperative control system, characterized in that: include: The first module is used to obtain the actual state quantity of the vehicle during driving; A second module is used to determine an expected driving state quantity according to the actual state quantity and the expected trajectory based on a zero center of mass sideslip angle strategy, wherein the expected driving state quantity includes an expected longitudinal speed and a reference turning angle of each axis, and the zero center of mass sideslip angle strategy is that the turning angles of each axis have a preset proportional relationship; A third module is used to perform longitudinal and lateral coordinated control according to the desired driving state quantity to obtain a global longitudinal generalized force, a global generalized lateral force and a global generalized yaw moment; a fourth module, configured to optimally distribute 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 include longitudinal forces and lateral forces; The fifth module is used to convert the tire force of each wheel into the driving space to obtain the wheel angle and motor torque of each wheel for the underlying driving vehicle.

9. 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 realizing connection and communication between the processor and the memory. When the program is executed by the processor, the steps of the method described in any one of claims 1 to 7 are realized.

10. A storage medium, the storage medium being a computer-readable storage medium, used for computer-readable storage, characterized in that: The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps of any one of claims 1 to 7.

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