Vehicle control method and device, computer device and storage medium

Abstract

The application relates to a vehicle control method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining target crosswind information of crosswind acting on a vehicle according to driving information of the vehicle, meteorological information of a scene where the vehicle is located and scene image information; determining a target yaw angular velocity of the vehicle according to vehicle state information of the vehicle; determining a first angular velocity difference between the target yaw angular velocity and an actual yaw angular velocity obtained through a sensor of the vehicle, and determining driving working condition information of the vehicle according to the first angular velocity difference; and obtaining target control information of the vehicle by using the first angular velocity difference and / or the target crosswind information according to the driving working condition information of the vehicle. The method can improve the driving stability of the vehicle in a crosswind environment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle control, and in particular to a vehicle control method and device, computer equipment, a storage medium and a computer program product. BACKGROUND

[0002] The crosswind phenomenon is prone to occur on a driving road such as a bridge, a tunnel exit, a mountain pass or a coastal area, and the crosswind phenomenon is prone to cause an unexpected yaw of a vehicle during driving, so that the vehicle deviates from the intended driving direction and is prone to lose stability and control.

[0003] In the traditional technology, a single actuator is mainly used to deal with the crosswind phenomenon, and the control effect of the single actuator is limited, and the vehicle cannot be well controlled to stably drive in the crosswind environment. SUMMARY

[0004] Therefore, it is necessary to provide a vehicle control method, device, computer equipment, computer readable storage medium and computer program product capable of improving the driving stability of a vehicle in a crosswind environment.

[0005] In a first aspect, the present application provides a vehicle control method. The method comprises:

[0006] obtaining target crosswind information of crosswind acting on the vehicle according to driving information of the vehicle, meteorological information of a scene where the vehicle is located and scene image information;

[0007] determining a target yaw angular velocity of the vehicle according to vehicle state information of the vehicle;

[0008] determining a first angular velocity difference between the target yaw angular velocity and an actual yaw angular velocity of the vehicle, and determining driving condition information of the vehicle according to the first angular velocity difference;

[0009] obtaining target control information of the vehicle by using the first angular velocity difference and / or the target crosswind information according to the driving condition information of the vehicle.

[0010] In one embodiment, obtaining target control information of the vehicle by using the first angular velocity difference and / or the target crosswind information according to the driving condition information of the vehicle comprises:

[0011] if the driving condition information represents a normal condition, performing suspension control on the vehicle according to the target crosswind information of the vehicle;

[0012] if the driving condition information represents a first abnormal condition, performing suspension control on the vehicle according to target crosswind information of the vehicle, and performing yaw control on the vehicle according to the first angular velocity difference;

[0013] if the driving condition information represents a second abnormal condition, performing yaw control on the vehicle according to a vehicle center of mass side slip angle and a target yaw angular velocity of the vehicle;

[0014] wherein the suspension control and the yaw control are used to reduce or offset the influence of crosswind on the vehicle.

[0015] In one embodiment, performing yaw control on the vehicle according to a vehicle center of mass side slip angle and a target yaw angular velocity of the vehicle comprises:

[0016] processing the actual yaw angular velocity according to the center of mass side slip angle and driving speed information of the vehicle to obtain a processed yaw angular velocity;

[0017] performing yaw control on the vehicle according to a second angular velocity difference between the target yaw angular velocity and the processed yaw angular velocity.

[0018] In one embodiment, performing yaw control on the vehicle comprises:

[0019] determining a state phase of the vehicle based on the first angular velocity difference or the second angular velocity difference;

[0020] if the state phase matches a preset first state phase, performing yaw control through multi-motor torque vectoring control, rear wheel steering control;

[0021] if the state phase matches a preset second state phase, performing yaw control through the rear wheel steering control, the multi-motor torque vectoring control and linear control braking control;

[0022] if the state phase matches a preset third state phase, performing yaw control through the linear control braking control, the multi-motor torque vectoring control and the rear wheel steering control;

[0023] wherein a parameter corresponding to the first state phase is less than a parameter corresponding to the second state phase; and the parameter corresponding to the second state phase is less than a parameter corresponding to the third state phase.

[0024] In one embodiment, the target crosswind information comprises target crosswind intensity information and target crosswind direction information;

[0025] performing suspension control on the vehicle according to target crosswind information of the vehicle comprises:

[0026] if it is detected that the target crosswind intensity information satisfies a preset crosswind intensity condition, obtaining air spring height adjustment information for the active suspension of the vehicle according to the target crosswind intensity information and driving speed information of the vehicle;

[0027] obtaining air spring stiffness adjustment information for the active suspension according to target crosswind direction information;

[0028] obtaining active force control information of the active suspension according to the target crosswind intensity information, the target crosswind direction information, the driving speed information, and body roll information and pitch attitude information of the vehicle;

[0029] controlling the active suspension to adjust based on the air spring height adjustment information, the air spring stiffness adjustment information, and the active force control information.

[0030] In one of the embodiments, the driving condition information of the vehicle is determined according to the first angular velocity difference, including:

[0031] if it is detected that the first angular velocity difference satisfies a preset angular velocity threshold condition, it is determined that the driving condition information of the vehicle represents the first abnormal condition;

[0032] if it is detected that the first angular velocity difference does not satisfy the angular velocity threshold condition, it is determined whether the center of mass side slip angle is greater than a center of mass side slip angle threshold value;

[0033] if it is detected that the center of mass side slip angle is greater than the center of mass side slip angle threshold value, it is determined that the driving condition information of the vehicle represents the second abnormal condition, otherwise, it is determined that the driving condition information of the vehicle represents the normal condition.

[0034] In one of the embodiments, the yaw rate prediction model includes a first yaw rate prediction model and a second yaw rate prediction model; the first yaw rate prediction model is constructed based on vehicle dynamics relationship; and the second yaw rate prediction model is constructed based on vehicle steering relationship;

[0035] the target yaw rate of the vehicle is determined according to vehicle state information of the vehicle, including:

[0036] the vehicle state information is input into the first yaw rate prediction model to obtain a first yaw rate;

[0037] the vehicle state information is input into the second yaw rate prediction model to obtain a second yaw rate;

[0038] The first yaw angular velocity and the second yaw angular velocity are fused to obtain the target yaw angular velocity.

[0039] In one of the embodiments, the target crosswind information of the crosswind acting on the vehicle is obtained according to the driving information of the vehicle, the meteorological information of the scene where the vehicle is located, and the scene image information, including:

[0040] The wind direction information and the wind speed information of the scene are obtained according to the meteorological information of the scene where the vehicle is located;

[0041] The first crosswind information is obtained according to the driving direction information, the driving speed information of the vehicle, and the wind direction information and the wind speed information;

[0042] The second crosswind information is obtained by modeling the crosswind of the scene according to the scene image information;

[0043] The target crosswind information of the crosswind acting on the vehicle is obtained by fusing the first crosswind information and the second crosswind information.

[0044] In a second aspect, the present application further provides a vehicle control device. The device includes:

[0045] A crosswind information obtaining module is configured to obtain target crosswind information of the crosswind acting on the vehicle according to driving information of the vehicle, meteorological information of a scene where the vehicle is located, and scene image information;

[0046] An angular velocity obtaining module is configured to determine a target yaw angular velocity of the vehicle according to vehicle state information of the vehicle;

[0047] A driving condition determining module is configured to determine a first angular velocity difference between the target yaw angular velocity and an actual yaw angular velocity of the vehicle, and determine driving condition information of the vehicle according to the first angular velocity difference;

[0048] A control information output module is configured to obtain target control information of the vehicle by using the first angular velocity difference and / or the target crosswind information according to the driving condition information of the vehicle.

[0049] In a third aspect, the present application further provides a computer device. The computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the following steps when executing the computer program:

[0050] The target crosswind information of the crosswind acting on the vehicle is obtained according to the driving information of the vehicle, the meteorological information of the scene where the vehicle is located, and the scene image information;

[0051] determining a target yaw rate of the vehicle according to vehicle state information of the vehicle;

[0052] determining a first angular velocity difference between the target yaw rate and an actual yaw rate of the vehicle, and determining driving condition information of the vehicle according to the first angular velocity difference;

[0053] obtaining target control information of the vehicle by using the first angular velocity difference and / or the target crosswind information according to the driving condition information of the vehicle.

[0054] In a fourth aspect, the present application further provides a computer readable storage medium. The computer readable storage medium has a computer program stored thereon, and the computer program is executed by a processor to implement the following steps:

[0055] obtaining target crosswind information of crosswind acting on the vehicle according to driving information of the vehicle, meteorological information of a scene where the vehicle is located, and scene image information;

[0056] determining a target yaw rate of the vehicle according to vehicle state information of the vehicle;

[0057] determining a first angular velocity difference between the target yaw rate and an actual yaw rate of the vehicle, and determining driving condition information of the vehicle according to the first angular velocity difference;

[0058] obtaining target control information of the vehicle by using the first angular velocity difference and / or the target crosswind information according to the driving condition information of the vehicle.

[0059] In a fifth aspect, the present application further provides a computer program product. The computer program product comprises a computer program, and the computer program is executed by a processor to implement the following steps:

[0060] obtaining target crosswind information of crosswind acting on the vehicle according to driving information of the vehicle, meteorological information of a scene where the vehicle is located, and scene image information;

[0061] determining a target yaw rate of the vehicle according to vehicle state information of the vehicle;

[0062] determining a first angular velocity difference between the target yaw rate and an actual yaw rate of the vehicle, and determining driving condition information of the vehicle according to the first angular velocity difference;

[0063] obtaining target control information of the vehicle by using the first angular velocity difference and / or the target crosswind information according to the driving condition information of the vehicle.

[0064] The vehicle control method, device, computer equipment, storage medium and computer program product can accurately obtain target crosswind information acting on the vehicle by comprehensively collecting driving information, weather information and scene image information of the vehicle, and accurately estimate the target yaw rate. By comparing the first yaw rate difference between the actual yaw rate and the target yaw rate, the driving condition information can be intelligently identified, and the target control information for adjusting the crosswind moment can be generated based on the driving condition information and the crosswind influence, thereby effectively improving the driving stability and safety of the vehicle in the crosswind environment, actively compensating and controlling the crosswind disturbance, and enhancing the environmental adaptability and control performance of the vehicle. BRIEF DESCRIPTION OF DRAWINGS

[0065] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related art, the drawings needed to be used in the description of the embodiments of the present application or the related art will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other related drawings can be obtained by those skilled in the art without creative labor.

[0066] Figure 1 The flowchart of the vehicle control method in one embodiment is shown.

[0067] Figure 2 The flowchart of the step of obtaining the target control information of the vehicle in one embodiment is shown.

[0068] Figure 3 The flowchart of the vehicle control method in another embodiment is shown.

[0069] Figure 4 The flowchart of the vehicle control method in another embodiment is shown.

[0070] Figure 5 The structural block diagram of the vehicle control device in one embodiment is shown.

[0071] Figure 6 The internal structure diagram of the computer equipment in one embodiment is shown. DETAILED DESCRIPTION

[0072] In order to make the purpose, technical solutions and advantages of the present application more clear, the present application will be further described in detail below with reference to the 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.

[0073] It should be noted that the terms "first", "second", etc. used in the present application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "include" and "have" and any variations thereof used in the present application are intended to cover non-exclusive inclusion. The term "a plurality of" used in the present application means two or more. The term "and / or" used in the present application means one of the options or any combination of the options.

[0074] In one embodiment, as shown in Figure 1 A vehicle control method is provided, and the embodiment is exemplified by the method applied to a vehicle terminal. It should be understood that the method can also be applied to a server, and can also be applied to a system including a vehicle terminal and a server, and is realized through the interaction of the terminal and the server. In the embodiment, the method includes the following steps:

[0075] In step S101, target crosswind information of crosswind acting on the vehicle is obtained according to driving information of the vehicle, meteorological information of a scene where the vehicle is located, and scene image information.

[0076] The driving information refers to information describing the driving state of the vehicle. For example, the driving information includes the driving direction and the vehicle speed of the vehicle.

[0077] The meteorological information refers to various data, materials and conclusions related to the state of the atmosphere and its changes. For example, the meteorological information includes temperature, humidity, air pressure, wind speed (such as wind speed observation value), wind direction (such as standard wind direction information), precipitation, cloud cover, and visibility.

[0078] The scene image information refers to video image information collected for the driving road of the vehicle.

[0079] Exemplarily, a chassis domain controller equipped on the vehicle can obtain meteorological information (such as standard wind direction information and wind speed observation value) of a geographical location where the vehicle is located through TBOX (Telematics BOX) online. The TBOX transmits the meteorological information to the vehicle terminal through the CAN (Controller Area Network) bus. The vehicle terminal can also obtain the driving information of the vehicle, and collect video images of the driving scene of the vehicle through a vehicle camera device (such as a vehicle high-definition camera), i.e. the scene image information of the scene of the vehicle terminal. According to the driving information, the meteorological information of the scene where the vehicle is located, and the scene image information, the target crosswind information of the crosswind acting on the vehicle is comprehensively obtained.

[0080] The target crosswind information refers to information describing the crosswind acting on the vehicle. For example, the target crosswind information includes target crosswind direction information, target crosswind intensity information, and crosswind level (such as normal, weak, medium, and strong).

[0081] In step S102, the target yaw rate of the vehicle is determined according to the vehicle state information of the vehicle.

[0082] The vehicle state information refers to information describing the driving state of the vehicle. For example, the vehicle state information includes four-wheel wheel speed, vehicle speed, active suspension height, six-axis IMU (such as longitudinal acceleration, lateral acceleration, vertical acceleration, yaw rate, roll angular velocity, and pitch angular velocity), driver operation (such as throttle, brake, steering, gear, and driving mode), road information (such as road type, slope, curve, and obstacle), slip ratio, wheel load, and road adhesion coefficient. IMU (Inertial Measurement Unit) is an inertial measurement unit.

[0083] The target yaw rate refers to the yaw rate that can resist or reduce the influence of the crosswind under ideal conditions.

[0084] For example, the vehicle terminal can use at least two yaw rate prediction models to predict the yaw rate based on the vehicle state information, and obtain at least two yaw rates output by the models. Then, the at least two yaw rates are fused to obtain the target yaw rate of the vehicle.

[0085] The yaw rate prediction model refers to a model for predicting the ideal yaw rate (i.e., the target yaw rate) of the vehicle under crosswind conditions. There can be multiple yaw rate prediction models, such as a first yaw rate prediction model and a second yaw rate prediction model.

[0086] In step S103, a first angular velocity difference between the target yaw rate and the actual yaw rate of the vehicle is determined, and the driving condition information of the vehicle is determined according to the first angular velocity difference.

[0087] The driving condition information is used to describe the driving state of the vehicle. For example, the driving condition information includes understeering, oversteering, side slip drift, and normal condition.

[0088] Exemplarily, the vehicle-mounted terminal can collect the current actual yaw rate of the vehicle through the sensor of the vehicle; then calculate the yaw rate difference between the target yaw rate and the actual yaw rate (which can be the yaw rate difference obtained by subtracting the actual yaw rate from the target yaw rate, or the yaw rate difference obtained by subtracting the target yaw rate from the actual yaw rate), and set it as the first yaw rate difference; determine the driving condition information of the vehicle by comparing the size relationship between the first yaw rate difference and the threshold value (including the first threshold value and the second threshold value, which can be calibrated according to the driving style and performance experience of the vehicle, etc.).

[0089] In step S104, the target control information of the vehicle is obtained according to the driving condition information of the vehicle, by using the first yaw rate difference and / or the target crosswind information.

[0090] The target control information refers to the information describing the adjustment mode of the vehicle. The target control information indicates the adjustment information of the vehicle, so as to realize the active compensation and control of the crosswind disturbance through the adjustment information.

[0091] Exemplarily, based on the real-time driving condition information of the vehicle, the target control information of the vehicle is intelligently generated in combination with the first yaw rate difference and the target crosswind information. The target control information is used to accurately adjust the air spring height, air spring stiffness, active force control and / or PID (Proportional-Integral-Derivative) control of the active suspension of the vehicle, so as to compensate the influence of the crosswind on the stability of the vehicle, thereby improving the control stability and driving safety of the vehicle in the crosswind condition, and enhancing the adaptability of the vehicle to complex environmental changes.

[0092] Further, multiple actuators such as multi-motor torque vectoring control, line-controlled rear steering control, active suspension, etc. perform PID control according to the target yaw rate respectively, so as to improve the yaw state of the vehicle, and achieve rapid automatic repair of driving deviation and maintain the stability of the vehicle body.

[0093] In the above vehicle control method, the target crosswind information acting on the vehicle is accurately obtained by comprehensively considering the driving information, weather information and scene image information of the vehicle, and the target yaw rate is accurately estimated; the driving condition information is intelligently identified by comparing the first yaw rate difference between the actual yaw rate and the target yaw rate, and the target control information for adjusting the crosswind moment is generated based on the driving condition information and the crosswind influence, thereby effectively improving the driving stability and safety of the vehicle in the crosswind environment, realizing the active compensation and control of the crosswind disturbance, and enhancing the environmental adaptability and control performance of the vehicle.

[0094] In one embodiment, as Figure 2As shown, in step S104, the target control information of the vehicle is obtained according to the driving condition information of the vehicle, the first angular velocity difference and / or the target crosswind information, and specifically includes the following contents:

[0095] In step S201, if the driving condition information represents a normal condition, the suspension control of the vehicle is performed according to the target crosswind information of the vehicle.

[0096] For example, if the driving condition information of the vehicle represents a normal condition, indicating that the vehicle is in a normal driving state, the vehicle terminal can determine whether the active suspension of the vehicle needs to be adjusted to improve the windward ability of the vehicle based on the target crosswind information.

[0097] In step S202, if the driving condition information represents a first abnormal condition, the suspension control of the vehicle is performed according to the target crosswind information of the vehicle, and the yaw control of the vehicle is performed according to the first angular velocity difference.

[0098] For example, if the driving condition information of the vehicle represents a first abnormal condition, indicating that the steering of the vehicle is abnormal, in addition to adjusting the active suspension of the vehicle by using the target crosswind information, rear wheel steering control, multi-motor torque vectoring control and linear control braking control can also be performed according to the first angular velocity difference.

[0099] The rear wheel steering control refers to that when the vehicle is steering, the rear wheel not only passively follows the front wheel, but also makes a small steering action in the same direction or in the opposite direction as the front wheel, so as to improve the controllability and stability of the vehicle.

[0100] The multi-motor torque vectoring control is mainly applied to vehicles driven by multiple motors (such as double-motor and four-motor electric vehicles), and the power distribution of the left and right wheels of the vehicle is adjusted by precisely controlling the output torque of each driving motor, so as to optimize the controllability, stability and power performance.

[0101] The linear control braking control is an electronic braking system, which detects the operation (stroke and force) of the brake pedal of the driver by a sensor, calculates the required braking force by an actuator, and drives the brake pad / brake disc to work by a motor or an electro-hydraulic actuator of the vehicle.

[0102] In step S203, if the driving condition information represents a second abnormal condition, the yaw control of the vehicle is performed according to the center of mass side slip angle and the target yaw angular velocity of the vehicle.

[0103] The suspension control and the yaw control are used to reduce or offset the influence of crosswind on the vehicle.

[0104] Exemplarily, if the driving working condition information of the vehicle is the second abnormal working condition, it indicates that the vehicle has a side-slip drift anomaly, at this time, the yaw angular velocity needs to be first amplified, and then the rear wheel steering control, the multi-motor torque vectoring control and the linear control braking control are performed.

[0105] In this embodiment, based on the driving working condition information of the vehicle, accurate control of different target control information is realized: in the normal working condition, the active suspension of the vehicle is adjusted according to the target crosswind information to effectively resist the crosswind interference; when in the first abnormal working condition, the suspension control is cooperated with the yaw control based on the first angular velocity difference to comprehensively improve the vehicle stability; when in the second abnormal working condition, the yaw control is implemented according to the center of mass side slip angle and the target yaw angular velocity to focus on inhibiting the vehicle side-slip risk. The adaptive ability and the handling stability of the vehicle in different driving states are significantly improved, and the safety and the comfort are unified.

[0106] In one embodiment, the step S203 comprises the following contents: according to the center of mass side slip angle and the driving speed information of the vehicle, the actual yaw angular velocity is processed to obtain a processed yaw angular velocity; and according to the second angular velocity difference between the target yaw angular velocity and the processed yaw angular velocity, the yaw control is performed on the vehicle.

[0107] Exemplarily, the vehicle terminal processes the actual yaw angular velocity according to the center of mass side slip angle and the driving speed information, which can be that a target value is calculated according to the center of mass side slip angle, the driving speed information, the adhesion coefficient of the vehicle and the lateral acceleration of the vehicle, and then a proportional coefficient is obtained by table lookup based on the target value, the proportional coefficient is multiplied by the actual yaw angular velocity to obtain the processed yaw angular velocity; and then the second angular velocity difference between the target yaw angular velocity and the processed yaw angular velocity is calculated, so as to perform the rear wheel steering control, the multi-motor torque vectoring control and the linear control braking control based on the second angular velocity difference.

[0108] The adhesion coefficient is a parameter for describing the friction between the road surface and the tire. The adhesion coefficient is used to reflect the "grip" strength between the road surface and the tire.

[0109] In this embodiment, the actual yaw angular velocity is optimized by comprehensively considering the center of mass side slip angle and the driving speed information of the vehicle to obtain a processed yaw angular velocity which more accurately reflects the dynamic characteristics of the vehicle, and accurate yaw control is performed on the vehicle based on the second angular velocity difference between the target yaw angular velocity and the processed yaw angular velocity, which improves the reliability of the yaw angular velocity and the response accuracy of the control system, thereby improving the driving stability and safety of the vehicle in the crosswind working condition.

[0110] In one embodiment, the above steps for performing yaw control on the vehicle specifically include the following: determining a state phase of the vehicle based on the first angular velocity difference or the second angular velocity difference; if the state phase matches a preset first state phase, performing yaw control through multi-motor torque vectoring control and rear wheel steering control; if the state phase matches a preset second state phase, performing yaw control through rear wheel steering control, multi-motor torque vectoring control and linear control braking control; if the state phase matches a preset third state phase, performing yaw control through linear control braking control, multi-motor torque vectoring control and rear wheel steering control; wherein the parameter corresponding to the first state phase is less than the parameter corresponding to the second state phase; and the parameter corresponding to the second state phase is less than the parameter corresponding to the third state phase.

[0111] In the first state phase, the vehicle is in a response boundary phase. In the second state phase, the vehicle is in a performance boundary phase. In the third state phase, the vehicle is in a capability potential boundary phase.

[0112] In the rear wheel steering control, the rear wheels are actively deflected by an electronic system (rather than passively following the front wheels). The principle of the rear wheel steering control is that the actuator calculates the steering angle and direction of the rear wheels (in the same direction as the front wheels or in the opposite direction) in real time according to signals such as vehicle speed, front wheel steering angle and vehicle body attitude, and then realizes the steering of the rear wheels through electric motors, hydraulic actuators and other execution mechanisms.

[0113] In the multi-motor torque vectoring control, the power distribution technology is applied to multi-motor driven vehicles (such as dual-motor and four-motor vehicles). The principle of the multi-motor torque vectoring control is to adjust the output torque of each driving motor in real time through the actuator, so that the left and right (or front and rear) wheels of the vehicle obtain different driving forces, thereby actively changing the driving attitude of the vehicle.

[0114] In the linear control braking control, an electronic signal is used to replace the traditional mechanical or hydraulic pipeline to transmit braking instructions. The principle of the linear control braking control is that when the driver steps on the brake pedal, the pedal displacement and force are converted into electrical signals by sensors, and the electronic control unit calculates the required braking force according to the vehicle state (such as vehicle speed, wheel speed and load), and then drives the brake calipers / brake drums through electric motors or electro-hydraulic actuators to realize wheel braking.

[0115] It should be noted that the above steps S202 of performing yaw control on the vehicle according to the first angular velocity difference, and the above step S203 of performing yaw control on the vehicle according to the second angular velocity difference between the target yaw angular velocity and the processed yaw angular velocity, although the angular velocity differences involved in the two steps are different, the processes of "performing yaw control on the vehicle" are the same.

[0116] Exemplarily, the vehicle terminal can determine the current driving state of the vehicle through the first angular velocity difference or the second angular velocity difference, so as to adopt a corresponding yaw control strategy. First, the parameters corresponding to each state stage are determined: (1) the ability potential boundary parameters of the real-time calculation of the rear wheel steering control, the multi-motor torque vector control and the linear control braking control: the ability potential boundary parameters are used to represent the limit ability that each control (i.e. the rear wheel steering control, the multi-motor torque vector control and the linear control braking control) can achieve; the ability potential boundary parameter of the rear wheel steering control is mainly calculated according to the current steering angle of the wheel end and the maximum physical steering angle boundary of the left and right wheel ends, and the ability potential boundary parameters of the multi-motor torque vector control and the linear control braking control are mainly calculated according to the current motor torque and the maximum and minimum motor torque; the ability potential boundary parameter of the rear wheel steering control is marked as p1, the ability potential boundary parameter of the multi-motor torque vector control is marked as p2, and the ability potential boundary parameter of the linear control braking control is marked as p3. (2) the performance boundary parameters of the real-time calculation of the rear wheel steering control, the multi-motor torque vector control and the linear control braking control under the current vehicle condition: the performance boundary parameters are used to represent the upper limit of the "good" (such as high precision and high stability) ability of each control within the "able to do" range; the performance boundary parameter of the rear wheel steering control is mainly calculated according to the current steering angle and the adhesion coefficient, the lateral acceleration and the reference vehicle speed, and the performance boundary parameters of the multi-motor torque vector control and the linear control braking control are mainly calculated according to the longitudinal acceleration, the lateral acceleration, the adhesion coefficient and the reference vehicle speed; the performance boundary parameter of the rear wheel steering control is marked as q1, the performance boundary parameter of the multi-motor torque vector control is marked as q2, and the performance boundary parameter of the linear control braking control is marked as q3. (3) the response boundary parameters of the real-time calculation of the rear wheel steering control, the multi-motor torque vector control and the linear control braking control: the response boundary parameters are used to represent the ability of each control to respond and feedback as fast as possible after receiving an instruction; the response boundary parameters can be obtained by actual measurement and calibration, or by model simulation; the response boundary parameter of the rear wheel steering control is marked as s1 (rear steering), the response boundary parameter of the multi-motor torque vector control is marked as s2, and the response boundary parameter of the linear control braking control is marked as s3. Among them, the response boundary parameter < the performance boundary parameter < the ability potential boundary parameter.

[0117] Then, according to the size relationship between the response boundary parameter, the performance boundary parameter and the ability potential boundary parameter, and the first angular velocity difference or the second angular velocity difference, the state stage of the vehicle is determined, and a corresponding (multi-) actuator is adopted for yaw control in different state stages, which specifically includes: the first angular velocity difference or the second angular velocity difference is marked as ; when When s2, the first state stage, i.e. the response boundary stage, uses the multi-motor torque vectoring control to control the corresponding actuators for yaw control, when When s2 and when When (s1 + s2), at this time the multi-motor torque vectoring control and rear wheel steering control corresponding actuators are used for collaborative control, when When (s1 + s2) and when (q1 + s2), the yaw control is performed by increasing the rear wheel steering, when When (q1 + s2) and when (q1 + q2), at this time the yaw control is performed by increasing the multi-motor torque vectoring control, when When (q1 + q2) and when (q1 + q2 + q3), the second state stage, i.e. the performance boundary stage, uses the rear wheel steering control, the multi-motor torque vectoring control and the linear control braking control corresponding actuators for collaborative control; when When (q1 + q2 + q3) and when (p1 + p2 + p3), the third state stage, i.e. the capability potential boundary stage, at this time The sum of the normal multi-actuator performance boundaries has been exceeded, representing that the vehicle yaw is very large at this time, belonging to some extreme crosswind working conditions, at this time it is necessary to quickly correct and adjust, at this time, on the basis of the rear wheel steering control reaching q1, the multi-motor torque vectoring control reaching q2 and the linear control braking control reaching q3, the linear control braking control is used first to reach p3, after the linear control braking control reaches p3, the multi-motor torque vectoring control is used, and then after the multi-motor torque vectoring control reaches p2, the rear wheel steering control is used last.

[0118] In actual application, in the response boundary stage, the multi-motor torque vectoring control is used first, and then the rear wheel steering control is used, because the multi-motor torque vectoring control directly generates the yaw moment by controlling the driving force of different wheels through multiple independent motors, thereby directly adjusting the yaw angular velocity. The motor responds extremely fast, usually within a few milliseconds to produce torque changes, which can directly and accurately adjust the yaw moment, and the control of the yaw angular velocity is more direct and efficient. The rear wheel steering control indirectly adjusts the yaw angular velocity by changing the steering angle of the rear wheel to affect the vehicle's turning center, which is limited by mechanical structures (such as steering motors, transmission mechanisms), control delays and tire dynamic responses, and its response time is usually between tens of milliseconds to hundreds of milliseconds. The rear wheel steering control mainly affects the steering characteristics of the vehicle (such as understeering or oversteering), and the adjustment of the yaw angular velocity is indirect. Although the linear control braking is as fast as the multi-motor torque vectoring control, it is easy to produce deceleration, which affects the driver's experience, so it is not considered for the time being.

[0119] In the performance boundary stage, the rear wheel steering control is used preferentially, then the multi-motor torque vectoring control is used, and finally the brake-by-wire control is used, because: the rear wheel steering control has a large adjustment range and good monotony for steering characteristics when the tire has good lateral adhesion, and has less impact on perception, so the rear wheel steering control is used preferentially; the multi-motor torque vectoring control and the brake-by-wire control are used secondly because when the tire is close to the lateral boundary, a large adjustment range is still ensured by relying on the longitudinal margin, and the monotony is good when the longitudinal does not slip, but the impact on the user's perception is large, the multi-motor torque vectoring control is that the acceleration is not lost when one side of the vehicle is increased in torque and the other side is decreased in torque, but the brake-by-wire control is that one side of the vehicle is braked or different braking is performed on both sides, which produces a significant deceleration and a poor experience, so the multi-motor torque vectoring control is used preferentially secondly, and the brake-by-wire control is used preferentially thirdly.

[0120] In the embodiment, the current state phase of the vehicle is identified based on the first angular velocity difference value or the second angular velocity difference value, and a differential cooperative control strategy is dynamically called according to different state phases, so that the stability and control precision of the vehicle in various driving and steering conditions are significantly improved, and efficient, smooth and safe multi-processor cooperative control is realized.

[0121] In one embodiment, the target crosswind information includes target crosswind intensity information and target crosswind direction information. The step S201 of performing suspension control on the vehicle according to the target crosswind information of the vehicle specifically includes the following contents: if it is detected that the target crosswind intensity information satisfies a preset crosswind intensity condition, obtaining air spring height adjustment information for the active suspension of the vehicle according to the target crosswind intensity information and the driving speed information of the vehicle; obtaining air spring stiffness adjustment information for the active suspension according to the target crosswind direction information; obtaining active force control information of the active suspension according to the target crosswind intensity information, the target crosswind direction information, the driving speed information, and the body roll information and the pitch attitude information of the vehicle; and controlling the active suspension to adjust based on the air spring height adjustment information, the air spring stiffness adjustment information and the active force control information.

[0122] The crosswind intensity condition is used to determine whether the current crosswind level reaches a specified crosswind level.

[0123] The air spring height adjustment information is information describing the height of the air spring to be adjusted.

[0124] The air spring stiffness adjustment information is information describing the stiffness of the air spring to be adjusted.

[0125] The active force control information refers to information describing an active force applied on the active suspension. The active force refers to a force generated by an actuator (such as a hydraulic pump) in the active suspension, which can actively adjust the suspension state and the vehicle body posture. It should be noted that the components and technical principles of the active suspension are significantly different from those of the traditional passive suspension and semi-active suspension. The most core difference lies in that the active suspension can actively adjust the vehicle body posture by generating a power source through an actuator (such as a hydraulic pump, an electric motor, or an air compressor), and can adjust the stiffness of an elastic element (such as an air spring), the damping of a shock absorber, and the height of the vehicle body in real time to actively adapt to road conditions and driving requirements. The passive suspension and semi-active suspension do not have an actuator, and mainly rely on passive adjustment in response to road feedback and vehicle body vibration.

[0126] The vehicle body roll information refers to information describing the inclination of the vehicle body to the outside of the turning direction around the longitudinal axis of the vehicle body.

[0127] The pitch posture information refers to information describing the inclination of the vehicle body forward and backward around the transverse axis of the vehicle body.

[0128] It should also be noted that the steps S201 and S202 both involve a step of “performing suspension control on the vehicle according to the target crosswind information of the vehicle”, and their processing processes can be the same.

[0129] For example, the vehicle terminal determines the current crosswind level according to the target crosswind intensity information. If the current crosswind level is normal, the active suspension does not need to be adjusted. If the current crosswind level is weak, medium, or strong, the air spring lowering height and the stiffness of the air spring on both sides of the active suspension, i.e., the air spring height adjustment information and the air spring stiffness adjustment information, are obtained by looking up a table (such as a preset mapping table) according to the driving speed information and the crosswind level of the vehicle. The air spring (i.e., the air spring) is a component on the active suspension. By adjusting the height of the air spring, the height adjustment of the active suspension can be achieved. By adjusting the stiffness of the air spring, the stiffness adjustment of the active suspension can be achieved. The lowering height of the air spring is proportional to the crosswind level and inversely proportional to the driving speed information. Similarly, the stiffness adjustment of the air spring is proportional to the crosswind direction, the crosswind level, and the current speed, and the active force control value of the active suspension is mainly used to control the vehicle roll. The roll control of the active suspension is inversely proportional to the crosswind level and inversely proportional to the driving speed information.

[0130] The vehicle terminal can also obtain the driving force of the hydraulic pump of the active suspension according to the target crosswind intensity information, the target crosswind direction information, the driving speed information, and the body roll information and the pitch attitude information of the vehicle, that is, the driving force control information of the active suspension. The hydraulic pump is another component on the active suspension, and the hydraulic pump is the power source of the active suspension. Crosswind can generate a lateral aerodynamic force on the vehicle during driving, causing the vehicle body to have an attitude problem. The driving force output by the hydraulic pump can provide support force for the active suspension on the leeward side of the vehicle, thereby correcting the attitude of the vehicle body and maintaining stable driving of the vehicle. In addition, the active suspension also includes a shock absorber for quickly attenuating the vibration of the vehicle body and the wheels.

[0131] Finally, the vehicle terminal controls the active suspension to adjust in combination with the air spring height adjustment information, the air spring stiffness adjustment information, and the driving force control information.

[0132] The principle of adjusting the air spring height, stiffness, and roll control based on the driving force control information is as follows: reducing the air spring height can reduce the height of the vehicle body, thereby changing the position of the center of mass of the vehicle and the wind-affected area, and further reducing the roll moment, the aerodynamic force acting area, and the tire grip; secondly, increasing the air spring stiffness on the windward side or increasing the overall air spring stiffness of the vehicle can increase the support force of the vehicle body against crosswind, reduce the lateral displacement and roll angle, and apply the driving force of the active suspension in the opposite direction of the crosswind to cause the vehicle attitude to roll in the opposite direction of the crosswind, thereby changing the relative attack angle of the vehicle and the airflow, reducing the center of mass side slip angle, and finally offsetting the overturning moment caused by the crosswind. It should be noted that, due to the decrease in tire grip caused by the active roll of the active suspension at different driving speed information, it is a better choice to maintain zero roll at high vehicle speed, and the driving speed information can be used for table lookup control at other vehicle speed conditions.

[0133] In this embodiment, the active suspension of the vehicle is intelligently adjusted according to the target crosswind intensity information and the target crosswind direction information of the vehicle: when it is detected that the current crosswind level meets the specified crosswind level, the air spring height adjustment information, the air spring stiffness adjustment information, and the driving force control information can be obtained by comprehensively considering the target crosswind intensity information and the driving speed information. By adjusting the air spring height, the air spring stiffness, and the driving force of the active suspension, the driving stability, the anti-roll ability, and the grip performance of the vehicle in the crosswind environment are improved, and the driving safety and comfort are significantly enhanced.

[0134] In one embodiment, the step S103 determines the driving condition information of the vehicle according to the first angular velocity difference, and specifically includes the following contents: if it is detected that the first angular velocity difference satisfies a preset angular velocity threshold condition, it is determined that the driving condition information of the vehicle represents a first abnormal condition; if it is detected that the first angular velocity difference does not satisfy the angular velocity threshold condition, it is determined whether the vehicle body side slip angle is greater than a vehicle body side slip angle threshold; if it is detected that the vehicle body side slip angle is greater than the vehicle body side slip angle threshold, it is determined that the driving condition information of the vehicle represents a second abnormal condition, otherwise it is determined that the driving condition information of the vehicle represents a normal condition.

[0135] The first abnormal condition represents an abnormality of the vehicle when turning. For example, the first abnormal condition includes oversteering and understeering. Oversteering refers to a phenomenon that when the vehicle turns, the rear wheel grip is insufficient or the front wheel grip is too strong, causing the tail of the vehicle body to slide to the outside of the curve, and the turning amplitude exceeds the expected turning trajectory of the driver. Understeering refers to a phenomenon that when the vehicle turns, the front wheel grip is insufficient or the rear wheel grip is too strong, causing the vehicle head to be difficult to turn according to the expected turning trajectory.

[0136] The second abnormal condition represents an abnormality of the vehicle body state. For example, the second abnormal condition includes side slip drift, which refers to a phenomenon that the vehicle body slides or loses control in the lateral direction, and a certain degree of trajectory deviation occurs.

[0137] The angular velocity threshold condition refers to a condition for determining whether the angular velocity difference between the target yaw rate and the actual yaw rate is greater than or less than a threshold value. The threshold value includes a first threshold value and a second threshold value, and both the first threshold value and the second threshold value are positive numbers.

[0138] For example, the target yaw rate is denoted as , and the actual yaw rate is denoted as If the angular velocity difference obtained by subtracting the actual yaw rate from the target yaw rate is greater than the first threshold value, i.e. , it is determined that the driving condition information of the vehicle represents understeering; wherein the first threshold value may be calibrated according to the driving style and performance experience of the vehicle. If the angular velocity difference obtained by subtracting the target yaw rate from the actual yaw rate is greater than the second threshold value, i.e. , it is determined that the driving condition information of the vehicle represents oversteering; wherein the second threshold value may be calibrated according to the driving style and performance experience of the vehicle.

[0139] If it is detected that the first angular velocity difference value does not satisfy the angular velocity threshold condition, it indicates that the driving condition information of the vehicle does not belong to understeering, nor to oversteering, then it is continued to be judged whether the vehicle's center of mass side slip angle is greater than the center of mass side slip angle threshold. If it is detected that the center of mass side slip angle is greater than the center of mass side slip angle threshold, it indicates that the yaw rate of the vehicle is not large, but the vehicle is side slipping and drifting due to various road surfaces or operation reasons, at this time it can be confirmed that the driving condition information of the vehicle represents side slipping; if the driving condition information of the vehicle does not belong to understeering, nor to oversteering, nor to side slipping, it is confirmed that the driving condition information of the vehicle represents normal condition, that is, the vehicle is in normal driving state.

[0140] In the embodiment, by judging whether the angular velocity difference value between the target yaw rate and the actual yaw rate satisfies the preset angular velocity threshold condition, and judging whether the center of mass side slip angle exceeds the center of mass side slip angle threshold, the accurate identification of the first abnormal condition, the second abnormal condition and the normal condition of the vehicle is realized, and the hierarchical identification mechanism effectively improves the accuracy and comprehensiveness of the driving condition information judgment, provides a reliable condition identification basis for the subsequent vehicle control, thereby enhancing the timely intervention ability to abnormal driving state, and improving the driving safety and control stability.

[0141] In one embodiment, the yaw rate prediction model includes a first yaw rate prediction model and a second yaw rate prediction model; the first yaw rate prediction model is constructed based on the vehicle dynamic relationship; and the second yaw rate prediction model is constructed based on the vehicle steering relationship. The above step S102, the vehicle state information of the vehicle is input into the yaw rate prediction model to obtain the target yaw rate of the vehicle, which specifically includes the following contents: the vehicle state information is input into the first yaw rate prediction model to obtain the first yaw rate; the vehicle state information is input into the second yaw rate prediction model to obtain the second yaw rate; and the first yaw rate and the second yaw rate are fused to obtain the target yaw rate.

[0142] The first yaw rate prediction model can be a 2-DOF vehicle kinematics model. The second yaw rate prediction model can be an Ackerman steering model.

[0143] For example, the vehicle terminal uses a 2-DOF vehicle kinematics model to calculate the yaw rate under the yaw moment and set as the first yaw rate, and uses an Ackerman steering model to calculate the yaw rate under the yaw moment the first yaw rate is added to the second yaw rate to obtain a target yaw rate, i.e., (first yaw rate * a) + second yaw rate = target yaw rate; wherein a can be a weight.

[0144] In actual applications, the vehicle terminal can input the vehicle mass m, the mass center side slip angle , the longitudinal vehicle speed , the front axle lateral force , the rear axle lateral force , the moment of inertia , the front axle to mass center distance , the rear axle to mass center distance , the yaw moment , the front axle side stiffness , the rear axle side stiffness , the front wheel steering angle , and the rear wheel steering angle in the vehicle state information into a 2-DOF vehicle kinematics model; the 2-DOF vehicle kinematics model includes a lateral force balance equation and a yaw moment balance equation, and the first yaw rate can be obtained by solving the lateral force balance equation and the yaw moment balance equation in linkage. The lateral force balance equation can be represented by the following formula:

[0145]

[0146] In the formula, represents the first yaw rate; represents the derivative of the mass center side slip angle.

[0147] The yaw moment balance equation can be represented by the following formula:

[0148]

[0149] In the formula, represents the derivative of the first yaw rate. The calculation formulas of the front axle lateral force and the rear axle lateral force are as follows:

[0150]

[0151] The Ackerman steering model can be represented by the following formula:

[0152]

[0153] In the formula, represents the second yaw rate; l represents the wheelbase, i.e., the distance between the front and rear axles of the vehicle; represents the characteristic vehicle speed, The simulation adaptation needs to be made according to different vehicle models; K is a coefficient, K is mainly obtained by table lookup (for example, a mapping relationship table of K and the difference between the characteristic vehicle speed and the current vehicle speed obtained through simulation experiments) according to the difference between the characteristic vehicle speed and the current vehicle speed, and K is used to distinguish different second yaw rate gains at low speed and high speed.

[0154] In the embodiment, by using the first yaw rate prediction model based on the vehicle power relationship and the second yaw rate prediction model based on the steering relationship, the first yaw rate and the second yaw rate are respectively output, and the target yaw rate is obtained through fusion processing, which effectively integrates the response characteristics of the vehicle under different dynamic mechanisms, significantly improves the prediction accuracy and robustness of the target yaw rate, provides a higher quality decision basis for the stable control of the vehicle, and thus improves the safety and driving adaptability of the vehicle control.

[0155] In one embodiment, the step S101 obtains the target crosswind information of the crosswind acting on the vehicle according to the driving information of the vehicle, the meteorological information of the scene where the vehicle is located, and the scene image information, and specifically includes the following contents: obtaining the wind direction information and the wind speed information of the scene according to the meteorological information of the scene where the vehicle is located; obtaining the first crosswind information according to the driving direction information, the driving speed information of the vehicle, and the wind direction information and the wind speed information; obtaining the second crosswind information by performing crosswind modeling processing on the scene according to the scene image information; and obtaining the target crosswind information of the crosswind acting on the vehicle by performing fusion processing on the first crosswind information and the second crosswind information.

[0156] For example, the vehicle terminal can estimate the first crosswind intensity information and the first crosswind direction information according to the wind direction information (such as standard wind direction information) and the wind speed information (such as wind speed observation value) in the meteorological information, in combination with the driving direction information and the driving speed information of the vehicle; and set the first crosswind intensity information and the first crosswind direction information as the first crosswind information. The vehicle terminal can also perform crosswind modeling processing on the driving scene of the vehicle according to the scene image information to obtain the crosswind model of the scene; and output the second crosswind intensity information and the second crosswind direction information by performing crosswind simulation processing through the crosswind model, and set the second crosswind intensity information and the second crosswind direction information as the second crosswind information.

[0157] The vehicle terminal fuses the first crosswind information and the second crosswind information, which can be weighted sum processing of the first crosswind information and the second crosswind information through the first weight corresponding to the first crosswind information and the second weight corresponding to the second crosswind information, to calculate the target crosswind information of the crosswind acting on the vehicle. In actual application, the accuracy of the crosswind model obtained by modeling is usually higher than that of the meteorological information, so the second weight can be set to be higher than the first weight; and the second crosswind information is mainly used and the first crosswind information is auxiliary to calculate the target crosswind information.

[0158] It should be noted that the target crosswind information is mainly used to provide a reference basis for the adjustment of the vehicle active suspension, so the accuracy requirement of the target crosswind information is not high, and the core control target of adjusting the moment of the crosswind acting on the vehicle is the target yaw rate.

[0159] In the embodiment, the wind direction information and the wind speed information of the scene are obtained based on the meteorological information, the driving direction information and the driving speed information of the vehicle, the first crosswind information is obtained through crosswind estimation, the scene image is used for crosswind modeling analysis to obtain another angle of crosswind estimation, and the second crosswind information is obtained, and finally the target crosswind information of the crosswind acting on the vehicle is calculated, the meteorological data and the scene image information are fused to evaluate the crosswind, and the accuracy and reliability of the crosswind evaluation are effectively improved, which provides a reliable processing basis for subsequent vehicle control.

[0160] In one embodiment, as shown in Figure 3 Another vehicle control method is provided, which is applied to a vehicle terminal as an example for illustration, including the following steps:

[0161] In step S301, the wind direction information and the wind speed information of the scene are obtained according to the meteorological information of the scene where the vehicle is located.

[0162] In step S302, the first crosswind information is obtained according to the driving direction information, the driving speed information, the wind direction information and the wind speed information of the vehicle.

[0163] In step S303, the second crosswind information is obtained by performing crosswind modeling processing on the scene according to the scene image information.

[0164] In step S304, the first crosswind information and the second crosswind information are fused to obtain the target crosswind information of the crosswind acting on the vehicle.

[0165] In step S305, the vehicle state information is input into the first yaw rate prediction model to obtain the first yaw rate.

[0166] In step S306, the vehicle state information is input into the second yaw rate prediction model to obtain the second yaw rate.

[0167] Step S307, the first yaw rate and the second yaw rate are fused to obtain a target yaw rate.

[0168] Step S308, a first angular velocity difference between the target yaw rate and an actual yaw rate of the vehicle is determined, and driving condition information of the vehicle is determined according to the first angular velocity difference.

[0169] Step S309, target control information of the vehicle is obtained according to the driving condition information of the vehicle, by using the first angular velocity difference and / or target crosswind information.

[0170] The vehicle control method can achieve the following beneficial effects: by comprehensively considering the driving information, weather information and scene image information of the vehicle, the target crosswind information acting on the vehicle can be accurately obtained, and the target yaw rate can be accurately estimated by combining the yaw rate prediction model; by comparing the first angular velocity difference between the actual yaw rate and the target yaw rate, the driving condition information can be intelligently identified, and the target control information for adjusting the crosswind moment can be generated based on the driving condition information and the crosswind influence, thereby effectively improving the driving stability and safety of the vehicle in the crosswind environment, actively compensating and controlling the crosswind disturbance, and enhancing the environmental adaptability and control performance of the vehicle.

[0171] In order to more clearly illustrate the vehicle control method provided by the embodiments of the present disclosure, the vehicle control method is specifically described below with reference to one specific embodiment. As shown in Figure 4 Another vehicle control method is provided, which can be applied to a vehicle terminal and specifically includes the following contents:

[0172] I. Crosswind intensity and direction identification

[0173] The vehicle terminal estimates first crosswind intensity information and first crosswind direction information according to the standard wind direction information and the wind speed observation value, in combination with the driving direction information and the driving speed information of the vehicle. The vehicle terminal performs crosswind modeling processing on the driving scene of the vehicle according to the scene image information to obtain a crosswind model of the scene; the second crosswind intensity information and the second crosswind direction information are output by performing crosswind simulation processing through the crosswind model. The target crosswind intensity information and the target crosswind direction information are obtained by fusing the first crosswind intensity information and the first crosswind direction information and the second crosswind intensity information and the second crosswind direction information, mainly using the second crosswind intensity information and the second crosswind direction information, and secondarily using the first crosswind intensity information and the first crosswind direction information.

[0174] II. Target yaw rate estimation

[0175] The vehicle terminal uses a 2-DOF vehicle kinematics model to calculate a first yaw rate under a yaw moment, and uses an Ackerman steering model to calculate a second yaw rate; then the target yaw rate is obtained by adding part of the first yaw rate and the second yaw rate, i.e. (first yaw rate * a) + second yaw rate = target yaw rate.

[0176] III. Driving condition information identification

[0177] The target yaw rate is marked as The actual yaw rate is marked as If the yaw rate difference obtained by subtracting the actual yaw rate from the target yaw rate is greater than a first threshold, i.e. , it is determined that the driving condition information of the vehicle represents understeering. If the yaw rate difference obtained by subtracting the target yaw rate from the actual yaw rate is greater than a second threshold, i.e. , it is determined that the driving condition information of the vehicle represents oversteering. If the driving condition information of the vehicle neither belongs to understeering nor oversteering, and the vehicle's center of mass side slip angle is greater than a center of mass side slip angle threshold, it is determined that the driving condition information of the vehicle represents side slip drift. If the driving condition information of the vehicle neither belongs to understeering nor oversteering, nor side slip drift, it is determined that the driving condition information of the vehicle represents normal condition.

[0178] IV. Generalized control quantity decomposition

[0179] If the driving condition information of the vehicle is normal condition, the vehicle terminal can determine whether to adjust the active suspension of the vehicle to improve the windward ability of the vehicle based on the target crosswind information.

[0180] If the driving condition information of the vehicle is the first abnormal condition, in addition to adjusting the active suspension of the vehicle based on the target crosswind information, rear wheel steering control, multi-motor torque vectoring control and linear control braking control can also be performed according to the first yaw rate difference.

[0181] If the driving condition information of the vehicle is the second abnormal condition, the yaw rate is first amplified, and then the second yaw rate difference between the target yaw rate and the processed yaw rate is calculated, and rear wheel steering control, multi-motor torque vectoring control and linear control braking control are performed based on the second yaw rate difference.

[0182] V. Fusion of generalized closed-loop control

[0183] The response boundary parameter, the performance boundary parameter and the capability potential boundary parameter are calculated first, and then the state stage of the vehicle is determined according to the size relationship between the response boundary parameter, the performance boundary parameter, the capability potential boundary parameter and the first angular velocity difference value or the second angular velocity difference value, and different yaw control strategies are adopted for yaw control in different state stages.

[0184] VI. Multi-actuator cooperative control

[0185] The multi-actuators such as rear wheel steering control, multi-motor torque vectoring control, rear wheel steering by wire control and active suspension perform PID control according to the yaw control strategy, so as to improve the yaw state of the vehicle and achieve rapid automatic repair of driving deviation and maintain the stability of the vehicle body.

[0186] In the embodiment, the accuracy and reliability of crosswind evaluation are effectively improved by fusing meteorological data and scene image information for crosswind evaluation; the prediction accuracy and robustness of the target yaw angular velocity are significantly improved by integrating the response characteristics of the vehicle under different dynamic mechanisms, so as to provide a higher quality decision basis for the stable control of the vehicle; and the stability and control accuracy of the vehicle under various driving and steering conditions are significantly improved through the cooperative work of the multi-actuators, so as to improve the driving stability and safety of the vehicle under crosswind conditions.

[0187] It should be understood that, although each step in the flowchart involved in each of the above embodiments is displayed in sequence according to the arrow, these steps are not necessarily executed in sequence according to the arrow. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other sequences. Moreover, as described above, at least part of the steps in the flowchart involved in each of the above embodiments can include multiple steps or stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution sequence of these steps or stages is not necessarily sequential, but can be executed in rotation or alternation with at least part of other steps or steps or stages in other steps. It can be understood that the steps in different embodiments can be freely combined as needed, and various non-contradictory schemes formed by the combination are within the scope of protection of the present application.

[0188] Based on the same inventive concept, the embodiments of the present application also provide a vehicle control device for implementing the above-mentioned vehicle control method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, so the specific limitations in one or more vehicle control device embodiments provided below can refer to the limitations of the vehicle control method described above, and will not be described here.

[0189] In one embodiment, as Figure 5As shown, a vehicle control device 500 is provided, comprising: a crosswind information obtaining module 501, an angular velocity obtaining module 502, a driving condition determining module 503 and a control information output module 504, wherein:

[0190] The crosswind information obtaining module 501 is configured to obtain target crosswind information of crosswind acting on the vehicle according to driving information of the vehicle, meteorological information of a scene where the vehicle is located and scene image information.

[0191] The angular velocity obtaining module 502 is configured to determine a target yaw angular velocity of the vehicle according to vehicle state information of the vehicle.

[0192] The driving condition determining module 503 is configured to determine a first angular velocity difference between the target yaw angular velocity and an actual yaw angular velocity of the vehicle, and determine driving condition information of the vehicle according to the first angular velocity difference.

[0193] The control information output module 504 is configured to obtain target control information of the vehicle by using the first angular velocity difference and / or the target crosswind information according to the driving condition information of the vehicle.

[0194] In one embodiment, the control information output module 504 is further configured to perform suspension control on the vehicle according to the target crosswind information of the vehicle if the driving condition information represents a normal condition, perform suspension control on the vehicle according to the target crosswind information of the vehicle and perform yaw control on the vehicle according to the first angular velocity difference if the driving condition information represents a first abnormal condition, and perform yaw control on the vehicle according to the target yaw angular velocity and a side slip angle of a center of mass of the vehicle if the driving condition information represents a second abnormal condition, wherein the suspension control and the yaw control are configured to reduce or offset the influence of the crosswind on the vehicle.

[0195] In one embodiment, the vehicle control device 500 further comprises a side-slip yaw control module configured to process the actual yaw angular velocity according to the side slip angle and driving speed information of the vehicle to obtain a processed yaw angular velocity, and perform yaw control on the vehicle according to a second angular velocity difference between the target yaw angular velocity and the processed yaw angular velocity.

[0196] In one embodiment, the vehicle control device 500 further comprises a steering and yaw control module configured to determine a state phase of the vehicle based on the first angular velocity difference or the second angular velocity difference; if the state phase matches a first preset state phase, perform yaw control through multi-motor torque vectoring control and rear wheel steering control; if the state phase matches a second preset state phase, perform yaw control through rear wheel steering control, multi-motor torque vectoring control and linear control braking control; if the state phase matches a third preset state phase, perform yaw control through linear control braking control, multi-motor torque vectoring control and rear wheel steering control; wherein the parameters corresponding to the first state phase are less than the parameters corresponding to the second state phase; and the parameters corresponding to the second state phase are less than the parameters corresponding to the third state phase.

[0197] In one embodiment, the target crosswind information comprises target crosswind intensity information and target crosswind direction information. The vehicle control device 500 further comprises a suspension control module configured to, if it is detected that the target crosswind intensity information satisfies a preset crosswind intensity condition, obtain air spring height adjustment information for an active suspension of the vehicle according to the target crosswind intensity information and vehicle running speed information; obtain air spring stiffness adjustment information for the active suspension according to the target crosswind direction information; obtain active force control information for the active suspension according to the target crosswind intensity information, the target crosswind direction information, the running speed information, and vehicle body roll information and pitch attitude information; and control the active suspension to adjust based on the air spring height adjustment information, the air spring stiffness adjustment information and the active force control information.

[0198] In one embodiment, the running condition determination module 503 is further configured to, if it is detected that the first angular velocity difference satisfies a preset angular velocity threshold condition, determine that the running condition information of the vehicle represents a first abnormal condition; if it is detected that the first angular velocity difference does not satisfy the angular velocity threshold condition, determine whether the center of mass side slip angle is greater than a center of mass side slip angle threshold; if it is detected that the center of mass side slip angle is greater than the center of mass side slip angle threshold, determine that the running condition information of the vehicle represents a second abnormal condition, otherwise, determine that the running condition information of the vehicle represents a normal condition.

[0199] In one embodiment, the yaw angular velocity prediction model comprises a first yaw angular velocity prediction model and a second yaw angular velocity prediction model; the first yaw angular velocity prediction model is constructed based on a vehicle dynamics relationship; and the second yaw angular velocity prediction model is constructed based on a vehicle steering relationship. The angular velocity obtaining module 502 is further configured to input the vehicle state information into the first yaw angular velocity prediction model to obtain a first yaw angular velocity; input the vehicle state information into the second yaw angular velocity prediction model to obtain a second yaw angular velocity; and perform fusion processing on the first yaw angular velocity and the second yaw angular velocity to obtain a target yaw angular velocity.

[0200] In one embodiment, the crosswind information obtaining module 501 is further configured to: obtain wind direction information and wind speed information of the scene according to weather information of the scene where the vehicle is located; obtain first crosswind information according to the driving direction information, the driving speed information of the vehicle, and the wind direction information and the wind speed information; perform crosswind modeling processing on the scene according to the scene image information to obtain second crosswind information; and perform fusion processing on the first crosswind information and the second crosswind information to obtain target crosswind information of the crosswind acting on the vehicle.

[0201] Each of the above vehicle control apparatuses can be implemented wholly or partially by software, hardware, or a combination thereof. Each of the above modules can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a memory in the computer device in software form, so as to be called and executed by the processor to perform operations corresponding to each of the above modules.

[0202] In one exemplary embodiment, a computer device is provided, which can be a vehicle terminal, and an internal structure diagram of the computer device can be as shown in Figure 6 The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, the memory, and the input / output interface are connected through a system bus, and the communication interface, the display unit, and the input device are connected to the system bus through the input / output interface. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for running of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is configured to exchange information between the processor and external devices. The communication interface of the computer device is configured to perform wired or wireless communication with external terminals, and the wireless communication can be implemented through WIFI, mobile cellular network, near field communication (NFC), or other technologies. The computer program is executed by the processor to implement a vehicle control method. The display unit of the computer device is configured to form a visually visible picture, which can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or can be a key, a trackball, or a touchpad arranged on the shell of the computer device, or can be an external keyboard, a touchpad, a mouse, or the like.

[0203] Those skilled in the art can understand that Figure 6The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0204] In one embodiment, a computer device is also provided, including a memory and a processor, the memory storing a computer program, and the processor implementing the steps in the above method embodiments when executing the computer program.

[0205] In one embodiment, a computer readable storage medium is provided, storing a computer program, and the computer program implements the steps in the above method embodiments when executed by a processor.

[0206] In one embodiment, a computer program product is provided, including a computer program, and the computer program implements the steps in the above method embodiments when executed by a processor.

[0207] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant regulations.

[0208] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when executed, can include the processes of the above-mentioned embodiment methods. Any reference to memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. The non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. The volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration but not limitation, the RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., without being limited thereto.

[0209] The technical features of the above embodiments can be combined in any manner. To make the description concise, not all possible combinations of the technical features in the above embodiments are described, but as long as the combinations of the technical features do not exist contradictions, they should be considered as the scope of the present application.

[0210] The above-described embodiments are merely illustrative of several embodiments of the present application, which are described in more detail and in a specific manner, but should not be construed as limiting the scope of the patent of the present application. It should be noted that, for those of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A vehicle control method characterized by, The method comprises: obtaining target crosswind information of crosswind acting on the vehicle according to driving information of the vehicle, meteorological information of a scene where the vehicle is located, and scene image information; determining a target yaw rate of the vehicle according to vehicle state information of the vehicle; determining a first angular velocity difference between the target yaw rate and an actual yaw rate of the vehicle, and determining driving working condition information of the vehicle according to the first angular velocity difference; if the driving working condition information represents a normal working condition, obtaining target control information of the vehicle according to the target crosswind information of the vehicle; if the driving working condition information represents a first abnormal working condition, obtaining the target control information of the vehicle according to the target crosswind information of the vehicle and according to the first angular velocity difference; if the driving working condition information represents a second abnormal working condition, obtaining the target control information of the vehicle according to a sideslip angle of a center of mass of the vehicle and the target yaw rate.

2. The method of claim 1, wherein, The method further comprises: if the driving working condition information represents the normal working condition, performing suspension control on the vehicle according to the target crosswind information of the vehicle; if the driving working condition information represents the first abnormal working condition, performing suspension control on the vehicle according to the target crosswind information of the vehicle and performing yaw control on the vehicle according to the first angular velocity difference; if the driving working condition information represents the second abnormal working condition, performing yaw control on the vehicle according to the sideslip angle of the center of mass of the vehicle and the target yaw rate. The suspension control and the yaw control are used to reduce or offset the influence of crosswind on the vehicle.

3. The method of claim 2, wherein, The yaw control on the vehicle according to the sideslip angle of the center of mass of the vehicle and the target yaw rate comprises: processing the actual yaw rate according to the sideslip angle and driving speed information of the vehicle to obtain a processed yaw rate; performing yaw control on the vehicle according to a second angular velocity difference between the target yaw rate and the processed yaw rate.

4. The method of claim 3, wherein, The yaw control on the vehicle comprises: determining a state stage of the vehicle based on the first angular velocity difference or the second angular velocity difference; if the state stage matches a preset first state stage, performing yaw control through multi-motor torque vector control and rear wheel steering control; if the state stage matches a preset second state stage, performing yaw control through the rear wheel steering control, the multi-motor torque vector control and linear control braking control; if the state stage matches a preset third state stage, performing yaw control through the linear control braking control, the multi-motor torque vector control and the rear wheel steering control; wherein a parameter corresponding to the first state stage is smaller than a parameter corresponding to the second state stage, and the parameter corresponding to the second state stage is smaller than a parameter corresponding to the third state stage.

5. The method of claim 2, wherein, The target crosswind information comprises target crosswind intensity information and target crosswind direction information. The suspension control of the vehicle according to the target crosswind information of the vehicle comprises: If it is detected that the target crosswind intensity information meets a preset crosswind intensity condition, then the air spring height adjustment information of the active suspension of the vehicle is obtained according to the target crosswind intensity information and the driving speed information of the vehicle; The air spring stiffness adjustment information of the active suspension is obtained according to the target crosswind direction information; The active force control information of the active suspension is obtained according to the target crosswind intensity information, the target crosswind direction information, the driving speed information, and the body roll information and the pitch attitude information of the vehicle; The active suspension is controlled to adjust based on the air spring height adjustment information, the air spring stiffness adjustment information, and the active force control information.

6. The method of claim 2, wherein, The driving condition information of the vehicle is determined according to the first angular velocity difference value, which comprises: If it is detected that the first angular velocity difference value meets a preset angular velocity threshold condition, then it is confirmed that the driving condition information of the vehicle represents the first abnormal condition; If it is detected that the first angular velocity difference value does not meet the angular velocity threshold condition, then it is determined whether the center of mass side slip angle is greater than a center of mass side slip angle threshold value; If it is detected that the center of mass side slip angle is greater than the center of mass side slip angle threshold value, then it is confirmed that the driving condition information of the vehicle represents the second abnormal condition, otherwise it is confirmed that the driving condition information of the vehicle represents the normal condition.

7. The method of claim 1, wherein, The target yaw rate of the vehicle is determined according to the vehicle state information of the vehicle, which comprises: The vehicle state information is input into a first yaw rate prediction model to obtain a first yaw rate; the first yaw rate prediction model is constructed based on vehicle dynamic relationship; The vehicle state information is input into a second yaw rate prediction model to obtain a second yaw rate; the second yaw rate prediction model is constructed based on vehicle steering relationship; The first yaw rate and the second yaw rate are fused to obtain the target yaw rate.

8. The method of claim 1, wherein, The target crosswind information of the crosswind acting on the vehicle is obtained according to the driving information of the vehicle, the meteorological information of the scene where the vehicle is located, and the scene image information, which comprises: The wind direction information and the wind speed information of the scene are obtained according to the meteorological information of the scene where the vehicle is located; The first crosswind information is obtained according to the driving direction information and the driving speed information of the vehicle, and the wind direction information and the wind speed information; The second crosswind information is obtained by performing crosswind modeling processing on the scene according to the scene image information; The first crosswind information and the second crosswind information are fused to obtain the target crosswind information of the crosswind acting on the vehicle.

9. A vehicle control device characterized by comprising: The device comprises: A crosswind information obtaining module is configured to obtain the target crosswind information of the crosswind acting on the vehicle according to the driving information of the vehicle, the meteorological information of the scene where the vehicle is located, and the scene image information; An angular velocity obtaining module is configured to determine the target yaw rate of the vehicle according to the vehicle state information of the vehicle. The driving condition determining module is configured to determine a first angular velocity difference between the target yaw angular velocity and an actual yaw angular velocity of the vehicle, and determine driving condition information of the vehicle according to the first angular velocity difference; The control information output module is configured to, if the driving condition information represents a normal condition, obtain target control information of the vehicle according to target crosswind information of the vehicle; if the driving condition information represents a first abnormal condition, obtain the target control information of the vehicle according to the target crosswind information of the vehicle and according to the first angular velocity difference; and if the driving condition information represents a second abnormal condition, obtain the target control information of the vehicle according to a vehicle center side slip angle and the target yaw angular velocity.

10. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that, The processor, when executing the computer program, implements the steps of the method of any one of claims 1 to 8.

11. A computer readable storage medium having stored thereon a computer program, characterized in that The computer program, when executed by the processor, implements the steps of the method of any one of claims 1 to 8.

12. A computer program product comprising a computer program, characterized in that, The computer program, when executed by the processor, implements the steps of the method of any one of claims 1 to 8.

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