Vehicle control method, vehicle control system and vehicle

Abstract

The invention provides a vehicle control method, a vehicle control system and a vehicle, and relates to the technical field of vehicle control, the method comprises the following steps: obtaining road surface detection parameters of a current driving road surface of a target vehicle, the road surface detection parameters comprising a road surface adhesion coefficient; the current vehicle speed, the front wheel steering angle and the real-time yaw velocity of the target vehicle are obtained; according to the road adhesion coefficient, the current vehicle speed and the front wheel steering angle, the target yaw velocity of the target vehicle is calculated; according to the real-time yaw velocity and the target yaw velocity, the real-time yaw angle deviation of the target vehicle is determined; according to the real-time yaw angle deviation, the wheel longitudinal force of the target vehicle is adjusted, and the wheel longitudinal force comprises vehicle braking force and / or wheel driving force. According to the invention, the control of the vehicle is more accurate, so that the driving safety of the vehicle is improved.

Description

Technical Field

[0001] This application relates to the field of vehicle control technology, and more specifically, to a vehicle control method, a vehicle control system, and a vehicle. Background Technology

[0002] During vehicle operation, especially under complex or adverse road conditions, the vehicle's handling stability directly impacts driving safety and the driving experience. Yaw rate, as a crucial parameter for measuring vehicle steering response and stability, requires the system to dynamically adjust the yaw rate control target based on the current driving state and road conditions to adapt to road environments with varying coefficients of adhesion, thereby improving vehicle handling performance and driving safety.

[0003] Currently, vehicle stability control systems typically determine the yaw rate control target based on parameters such as driver steering input, vehicle speed, wheelbase, and road surface adhesion coefficient. The road surface adhesion coefficient is calculated by means of tire slip ratio, wheel speed difference, etc., or determined by using fixed empirical values.

[0004] However, existing methods cannot dynamically adjust the yaw rate based on the parameters of the actual road surface, and the accuracy of the obtained road adhesion coefficient is low, resulting in inaccurate control strategies and making the driving process more dangerous for drivers. Summary of the Invention

[0005] The purpose of this application is to address the shortcomings of the prior art by providing a vehicle control method, a vehicle control system, and a vehicle, thereby enabling more precise vehicle control and improving vehicle driving safety.

[0006] To achieve the above objectives, the technical solutions adopted in the embodiments of this application are as follows: In a first aspect, one embodiment of this application provides a vehicle control method, the method comprising: Obtain road surface detection parameters of the current road surface of the target vehicle, wherein the road surface detection parameters include: road surface adhesion coefficient; Obtain the target vehicle's current speed, front wheel steering angle, and real-time yaw rate; The target yaw rate of the target vehicle is calculated based on the road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle. The real-time yaw rate deviation of the target vehicle is determined based on the real-time yaw rate and the target yaw rate. Based on the real-time yaw angle deviation, the longitudinal force of the target vehicle's wheels is adjusted, and the longitudinal force of the wheels includes: vehicle braking force and / or wheel driving force.

[0007] Optionally, adjusting the longitudinal force of the target vehicle's wheels based on the real-time yaw angle deviation includes: If the real-time yaw angle deviation is greater than the preset minimum deviation threshold, then braking force is applied to the outer front wheel of the target vehicle. If the real-time yaw angle deviation is less than the preset minimum deviation threshold, then braking force is applied to the inner rear wheel of the target vehicle.

[0008] Optionally, adjusting the longitudinal force of the target vehicle's wheels based on the real-time yaw angle deviation further includes: If the real-time yaw angle deviation is greater than the preset minimum deviation threshold, the drive wheels of the target vehicle are controlled in the first stage, so that the driving force of the inner drive wheel of the target vehicle is greater than the driving force of the outer drive wheel. If the real-time yaw angle deviation is less than the preset minimum deviation threshold, the drive wheels of the target vehicle are subjected to a second control, such that the driving force of the outer inner drive wheel of the target vehicle is greater than the driving force of the inner drive wheel.

[0009] Optionally, the method further includes: Obtain the driving intention information of the target vehicle; Based on the driving intention information, determine whether the target vehicle is in a turning state; The step of calculating the target yaw rate of the target vehicle based on the road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle includes: If the target vehicle is turning, the target yaw rate of the target vehicle is calculated based on the road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle.

[0010] Optionally, the method further includes: If the target vehicle is traveling straight, but the front wheel steering angle indicates that the front wheels are turning, then it is determined that the target vehicle has experienced a straight-line sideslip. Based on the steering angle corresponding to the sideslip direction, braking force is applied to the wheel on the opposite side of the sideslip direction.

[0011] Optionally, the method further includes: The maximum adhesion force of each wheel is calculated based on the road surface adhesion coefficient and the vertical wheel load of each wheel in the target vehicle. The step of adjusting the longitudinal force of the target vehicle's wheels based on the real-time yaw angle deviation includes: Based on the real-time yaw angle deviation and the maximum adhesion of each wheel, the longitudinal force of the target vehicle's wheels is adjusted so that the sum of the longitudinal force and lateral force of each wheel does not exceed the maximum adhesion of the corresponding wheel.

[0012] Optionally, the road surface detection parameters further include: road surface condition parameters; the method further includes: Determine whether the current driving road surface meets the preset road driving warning conditions based on the road surface state parameters; If the preset path warning conditions are met, a driving warning message will be issued.

[0013] Optionally, the road surface detection parameters include: two sets of road surface detection parameters collected by two road surface detection devices; each set of road surface detection parameters includes a road surface adhesion coefficient; The step of calculating the target yaw rate of the target vehicle based on the road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle includes: The target road surface adhesion coefficient is determined based on the two road surface adhesion coefficients in the two sets of road surface detection parameters. The target yaw rate of the target vehicle is calculated based on the target road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle.

[0014] Secondly, another embodiment of this application provides a vehicle control device, the device comprising: The first acquisition module is used to acquire road surface detection parameters of the road surface where the target vehicle is currently driving, and the road surface detection parameters include: road surface adhesion coefficient; The second acquisition module is used to acquire the target vehicle's current speed, front wheel steering angle, and real-time yaw rate. The calculation module is used to calculate the target yaw rate of the target vehicle based on the road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle. The determination module is used to determine the real-time yaw rate deviation of the target vehicle based on the real-time yaw rate and the target yaw rate. The adjustment module is used to adjust the longitudinal force of the target vehicle's wheels based on the real-time yaw angle deviation, wherein the longitudinal force of the wheels includes: vehicle braking force and / or wheel driving force.

[0015] Thirdly, another embodiment of this application provides a controller, including: a processor, a memory, and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the controller is running, the processor communicates with the memory via the bus, and the processor executes the machine-readable instructions to perform the steps of any of the vehicle control methods described in the first aspect above.

[0016] Fourthly, another embodiment of this application provides a storage medium storing a computer program, which, when executed by a processor, performs the steps of any of the vehicle control methods described in the first aspect above.

[0017] Fifthly, another embodiment of this application provides a vehicle control system, which includes at least: a road surface detection device, a controller, an electric braking system, a vehicle control unit, a motor controller, and an electro-hydraulic power steering system; The road surface detection device is connected to the controller and is used to collect road surface detection parameters of the road surface on which the target vehicle is currently traveling. The road surface detection parameters include the road surface adhesion coefficient. The controller is connected to the vehicle control unit to obtain the current speed of the target vehicle. The controller is also connected to the electro-hydraulic power steering system to obtain the front wheel steering angle collected by the electro-hydraulic power steering system. The controller is also used to calculate the target yaw rate of the target vehicle based on the road adhesion coefficient, the current vehicle speed and the front wheel steering angle. The electric braking system is connected to the controller to obtain the target yaw rate; the electric braking system is used to: obtain the real-time yaw rate of the target vehicle, and determine the real-time yaw rate deviation of the target vehicle based on the real-time yaw rate and the target yaw rate, and adjust the wheel braking force of the target vehicle based on the real-time yaw rate deviation. The vehicle control unit is connected to the electric braking system to obtain the real-time yaw rate. The vehicle control unit is also used to: obtain the target yaw rate from the controller; determine the real-time yaw rate deviation of the target vehicle based on the real-time yaw rate and the target yaw rate; and control the motor controller of the target vehicle based on the real-time yaw rate deviation to adjust the wheel driving force of the target vehicle.

[0018] Sixthly, another embodiment of this application provides a vehicle, which includes at least: a vehicle body and a vehicle control system on the vehicle body, wherein the vehicle control system is the vehicle control system described in the fifth aspect above.

[0019] The beneficial effects of this application are: This application provides a vehicle control method, a vehicle control system, and a vehicle. It acquires road surface detection parameters of the target vehicle's current driving surface, and obtains the target vehicle's current speed, front wheel steering angle, and real-time yaw rate. Based on the road surface adhesion coefficient, current speed, and front wheel steering angle, it calculates the target vehicle's target yaw rate; based on the real-time yaw rate and the target yaw rate, it determines the target vehicle's real-time yaw angle deviation; and based on the real-time yaw angle deviation, it adjusts the longitudinal force of the target vehicle's wheels. This application controls the longitudinal force of the target vehicle's wheels by using the target vehicle's road surface detection parameters, current speed, front wheel steering angle, and real-time yaw rate, and by determining the real-time yaw rate and the real-time yaw angle deviation. By determining the road surface adhesion coefficient, this application ensures the accuracy of the real-time yaw angle deviation, thereby ensuring the accuracy of vehicle control. Simultaneously, through closed-loop control, it dynamically adjusts the longitudinal force of the target vehicle's wheels, making the vehicle adjustment more precise and improving vehicle driving safety. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of the structure of a vehicle control system provided in an embodiment of this application; Figure 2 A schematic flowchart of a vehicle control method provided in an embodiment of this application; Figure 3 This is a schematic diagram of the process for adjusting the longitudinal force of a wheel in a vehicle control method provided in an embodiment of this application; Figure 4 A schematic diagram illustrating the process of adjusting the longitudinal force of the wheels in another vehicle control method provided in this application embodiment; Figure 5 A schematic flowchart illustrating the determination of target yaw rate in a vehicle control method provided in this application embodiment; Figure 6 This is a schematic diagram of the process of applying braking force to the wheels in a vehicle control method provided in an embodiment of this application; Figure 7 This is a schematic diagram of the process for controlling the longitudinal force of a wheel in a vehicle control method provided in an embodiment of this application; Figure 8 A schematic diagram illustrating the process of generating a warning prompt in a vehicle control method provided in an embodiment of this application; Figure 9 This is a schematic diagram of another vehicle control system provided in an embodiment of this application; Figure 10 A flowchart illustrating the determination of the target yaw rate in another vehicle control method provided in this application embodiment; Figure 11 This is a schematic diagram of another vehicle control system provided in an embodiment of this application; Figure 12 A schematic diagram of the layout of a vehicle control system provided in an embodiment of this application; Figure 13 This is a schematic diagram of the structure of a vehicle control device provided in an embodiment of this application; Figure 14 This is a structural schematic diagram of a vehicle provided in an embodiment of this application. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the accompanying drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0023] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0024] It should be noted that the term "comprising" will be used in the embodiments of this application to indicate the presence of the features declared thereafter, but does not exclude the addition of other features.

[0025] To clearly describe the vehicle control method provided in the embodiments of this application, the method provided in the embodiments of this application will be described below in conjunction with several accompanying drawings. Figure 1This is a schematic diagram of the structure of a vehicle control system provided in an embodiment of this application, such as... Figure 1 As shown, the vehicle control system 100 includes at least: a road surface detection device 101, a controller 102, an electric braking system 103, a vehicle control unit 104, a motor controller 105, and an electro-hydraulic power steering system 106.

[0026] The road surface detection device 101 is connected to the controller. The road surface detection device 101 is used to collect road surface detection parameters of the road surface on which the target vehicle is currently traveling. The road surface detection parameters include the road surface adhesion coefficient.

[0027] The controller 102 is connected to the vehicle control unit 104 to obtain the current speed of the target vehicle. The controller 102 is also connected to the electro-hydraulic power steering 106 to obtain the front wheel steering angle collected by the electro-hydraulic power steering 106. The controller 102 is also used to calculate the target yaw rate of the target vehicle based on the road adhesion coefficient, the current vehicle speed and the front wheel steering angle.

[0028] The electric braking system 103 is connected to the controller 102 to obtain the target yaw rate; the electric braking system 103 is used to: obtain the real-time yaw rate of the target vehicle, and determine the real-time yaw rate deviation of the target vehicle based on the real-time yaw rate and the target yaw rate, and adjust the wheel braking force of the target vehicle based on the real-time yaw rate deviation. The vehicle control unit 104 is connected to the electric braking system 103 to obtain the real-time yaw rate. The vehicle control unit is also used to: obtain the target yaw rate from the controller 102; determine the real-time yaw rate deviation of the target vehicle based on the real-time yaw rate and the target yaw rate; and control the motor controller 105 of the target vehicle based on the real-time yaw rate deviation to drive the motor and adjust the wheel driving force of the target vehicle.

[0029] Figure 2 This is a flowchart illustrating a vehicle control method provided in an embodiment of this application, applied to the aforementioned vehicle control system, such as... Figure 2 As shown, the method includes: Step 201: Obtain the road surface detection parameters of the current road surface where the target vehicle is driving.

[0030] Among the road surface detection parameters is the road surface adhesion coefficient, which indicates the friction between the vehicle tires and the road surface.

[0031] Optionally, a road surface detection device is installed on the target vehicle. This device can determine the detection parameters of the road surface on which the target vehicle is currently traveling. The road surface detection device can be an intelligent remote sensing vehicle-mounted road surface detector, which is equipped with sensors such as LiDAR and cameras. It can acquire road surface point cloud data through LiDAR and determine the road surface adhesion coefficient based on the reflection intensity of the point cloud.

[0032] Step 202: Obtain the target vehicle's current speed, front wheel steering angle, and real-time yaw rate.

[0033] Among them, the target vehicle's current speed is the instantaneous speed of the vehicle while it is moving, the front wheel steering angle is used to indicate the angle of deflection of the vehicle's front wheels, and the real-time yaw rate refers to the angular velocity of the vehicle rotating around the longitudinal axis perpendicular to the ground.

[0034] Optionally, the target vehicle is equipped with a vehicle control unit to obtain the current vehicle speed. The target vehicle is also equipped with an electro-hydraulic power steering system to obtain the front wheel steering angle. The target vehicle is further equipped with an electric braking system to obtain the real-time yaw rate.

[0035] Step 203: Calculate the target yaw rate of the target vehicle based on the road surface adhesion coefficient, current vehicle speed, and front wheel steering angle.

[0036] The target yaw rate is used to indicate the theoretical yaw rate of the vehicle, at which the vehicle can remain stable.

[0037] Optionally, based on the road surface adhesion coefficient Current vehicle speed and front wheel steering angle Based on vehicle stability coefficient Gravitational acceleration and vehicle wheelbase The target yaw rate is obtained by using a preset yaw angle calculation formula. Among them, the vehicle stability coefficient and vehicle wheelbase Determined based on the design structural parameters of the target vehicle.

[0038]

[0039] Step 204: Determine the real-time yaw rate deviation of the target vehicle based on the real-time yaw rate and the target yaw rate.

[0040] Optionally, the difference between the real-time yaw rate and the target yaw rate is determined based on the real-time yaw rate and the target yaw rate, thereby obtaining the real-time yaw deviation of the target vehicle.

[0041] Step 205: Adjust the longitudinal force of the target vehicle's wheels based on the real-time yaw angle deviation.

[0042] Among them, the longitudinal force of the wheel includes: vehicle braking force and / or wheel driving force.

[0043] Optionally, the real-time yaw rate deviation is determined based on the real-time yaw rate and the target yaw rate. The real-time yaw rate is determined based on the yaw moment, and the yaw moment is determined based on the longitudinal forces of the inner and outer wheels of the target vehicle. By adjusting the longitudinal forces of the inner and outer wheels of the target vehicle, the real-time yaw rate can be changed, thereby changing the vehicle's real-time speed. The real-time yaw rate and the target yaw rate are then updated to obtain a new real-time yaw rate deviation until no real-time yaw rate deviation exists.

[0044] In this embodiment, road surface detection parameters of the target vehicle's current driving surface are obtained, along with the target vehicle's current speed, front wheel steering angle, and real-time yaw rate. Based on the road surface adhesion coefficient, current speed, and front wheel steering angle, the target yaw rate of the target vehicle is calculated. Based on the real-time yaw rate and the target yaw rate, the real-time yaw angle deviation of the target vehicle is determined. Based on the real-time yaw angle deviation, the longitudinal force of the target vehicle's wheels is adjusted. This application controls the longitudinal force of the target vehicle's wheels by using the target vehicle's road surface detection parameters, current speed, front wheel steering angle, and real-time yaw rate, and by determining the real-time yaw rate and the real-time yaw angle deviation of the target yaw rate. By determining the road surface adhesion coefficient, this application ensures the accuracy of the real-time yaw angle deviation, thereby ensuring the accuracy of vehicle control. Simultaneously, through closed-loop control, the longitudinal force of the target vehicle's wheels is dynamically adjusted, making the vehicle adjustment more precise and improving vehicle driving safety.

[0045] Based on the above embodiments, this application also provides a process for adjusting the longitudinal force of the wheels in a vehicle control method. Figure 3 This is a schematic flowchart illustrating the adjustment of longitudinal force on wheels in a vehicle control method provided in this application embodiment. Figure 3 As shown, in step 205 above, the longitudinal force of the target vehicle's wheels is adjusted based on the real-time yaw angle deviation, including: Step 301: If the real-time yaw angle deviation is greater than the preset minimum deviation threshold, apply braking force to the outer front wheel of the target vehicle.

[0046] The preset minimum deviation threshold can be 0.

[0047] Optionally, real-time yaw angle deviation For real-time yaw rate yaw rate of the target The difference. If the real-time yaw angle deviation is greater than the preset minimum deviation threshold, it indicates that the real-time yaw rate... Greater than the target yaw rate By applying braking force to the outer front wheel of the target vehicle, the resistance generated by the braking of the outer front wheel will create a counter-torque, thereby reducing the real-time yaw rate. Reduce real-time yaw rate deviation .

[0048] Step 302: If the real-time yaw angle deviation is less than the preset minimum deviation threshold, apply braking force to the inner rear wheel of the target vehicle.

[0049] Optionally, if the real-time yaw angle deviation is less than a preset minimum deviation threshold, it indicates that the real-time yaw rate is... Less than the target yaw rate By applying braking force to the inner rear wheel of the target vehicle, the resistance generated by the braking of the inner rear wheel will create a torque in the same direction, thereby increasing the real-time yaw rate. Increase real-time yaw angle deviation .

[0050] In this embodiment, if the real-time yaw angle deviation is greater than a preset minimum deviation threshold, braking force is applied to the outer front wheel of the target vehicle; if the real-time yaw angle deviation is less than the preset minimum deviation threshold, braking force is applied to the inner rear wheel of the target vehicle. By applying braking force to the outer front wheel and the inner rear wheel, this application improves the efficiency of correcting longitudinal forces on the wheels and minimizes interference with vehicle speed and ride comfort.

[0051] Based on the above embodiments, this application also provides a process for adjusting the longitudinal force of the wheels in a vehicle control method. Figure 4 This is a schematic diagram of the process for adjusting the longitudinal force of the wheels in another vehicle control method provided in this application embodiment, as shown below. Figure 4 As shown, in step 205 above, adjusting the longitudinal force of the target vehicle's wheels based on the real-time yaw angle deviation also includes: Step 401: If the real-time yaw angle deviation is greater than the preset minimum deviation threshold, perform the first control on the drive wheels of the target vehicle so that the driving force of the inner drive wheel of the target vehicle is greater than the driving force of the outer drive wheel.

[0052] Optionally, if the real-time yaw angle deviation is greater than a preset minimum deviation threshold, it indicates that the real-time yaw rate is greater than the target yaw rate, meaning the target vehicle is actually steering too fast and there is a risk of oversteering. In this case, a first control is applied to the drive wheels of the target vehicle, making the driving force of the inner drive wheel greater than the driving force of the outer drive wheel. This first control can be achieved by increasing the driving force of the inner wheel, increasing the braking force of the outer wheel, or simultaneously increasing the driving force of the inner wheel and the braking force of the outer wheel.

[0053] Step 402: If the real-time yaw angle deviation is less than the preset minimum deviation threshold, perform a second control on the drive wheels of the target vehicle so that the driving force of the outer inner drive wheels of the target vehicle is greater than the driving force of the inner drive wheels.

[0054] Optionally, if the real-time yaw angle deviation is less than a preset minimum deviation threshold, it indicates that the real-time yaw rate is less than the target yaw rate, meaning the target vehicle's actual steering is too slow and there is a risk of understeer. In this case, a second control is applied to the target vehicle's drive wheels, making the driving force of the outer inner drive wheels greater than the driving force of the inner drive wheel. This second control could involve increasing the braking force of the inner wheel; increasing the driving force of the outer wheel; or simultaneously increasing the braking force of the inner wheel and increasing the driving force of the outer wheel.

[0055] In this embodiment, if the real-time yaw angle deviation is greater than a preset minimum deviation threshold, the drive wheels of the target vehicle are subjected to first control, such that the driving force of the inner drive wheel of the target vehicle is greater than the driving force of the outer drive wheel; if the real-time yaw angle deviation is less than the preset minimum deviation threshold, the drive wheels of the target vehicle are subjected to second control, such that the driving force of the outer inner drive wheel of the target vehicle is greater than the driving force of the inner drive wheel. This application can improve the efficiency of correcting the longitudinal force of the wheels, maximize the preservation of the vehicle's power and ride comfort, and ensure the stability of the vehicle.

[0056] Based on the above embodiments, this application also provides a process for determining the target yaw rate in a vehicle control method. Figure 5 This is a flowchart illustrating the determination of a target yaw rate in a vehicle control method provided in an embodiment of this application, as shown below. Figure 5 As shown, based on steps 201-205 above, the method further includes: Step 501: Obtain the driving intention information of the target vehicle.

[0057] Among them, driving intention information can be the driver's intention to control the vehicle's movement, such as turning left, turning right, or going straight.

[0058] Optionally, the target vehicle is equipped with a steering wheel angle sensor, and the driving intention information of the target vehicle is determined based on the steering wheel angle detected by the steering wheel angle sensor.

[0059] For example, if a positive steering wheel angle is detected, the driving intention of the target vehicle is determined to be to turn left; if a negative steering wheel angle is detected, the driving intention of the target vehicle is determined to be to turn right; if a zero steering wheel angle is detected, the driving intention of the target vehicle is determined to be to go straight.

[0060] Step 502: Based on the driving intention information, determine whether the target vehicle is in a turning state.

[0061] Optionally, based on the driving intention information of turning left or right, it can be determined whether the target vehicle is in a turning state.

[0062] In step 203 above, the target yaw rate of the target vehicle is calculated based on the road surface adhesion coefficient, current vehicle speed, and front wheel steering angle, including: Step 503: If the target vehicle is turning, calculate the target yaw rate of the target vehicle based on the road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle.

[0063] Optionally, if the target vehicle is turning, the vehicle will generate a yaw rate. The target yaw rate of the target vehicle is calculated based on the road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle.

[0064] In this embodiment, the driving intention information of the target vehicle is obtained. Based on the driving intention information, it is determined whether the target vehicle is in a turning state. If the target vehicle is in a turning state, the target yaw rate of the target vehicle is calculated based on the road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle. This application determines the turning state through driving intention, avoiding misjudgment of the vehicle state. By determining the target yaw rate through the road surface adhesion coefficient, the target yaw rate can be adaptively adjusted, making the control of the vehicle more accurate.

[0065] Based on the above embodiments, this application also provides a process for applying braking force to the wheels in a vehicle control method. Figure 6 This is a schematic diagram of the process of applying braking force to the wheels in a vehicle control method provided in an embodiment of this application, as shown below. Figure 6 As shown, based on steps 501-503 above, the method further includes: Step 601: If the target vehicle is traveling straight, but the front wheel steering angle indicates that the front wheels are turning, then it is determined that the target vehicle has experienced a straight-line sideslip.

[0066] Straight-line sideslip refers to the unexpected slippage of the wheels in the lateral direction when a vehicle is traveling on a straight road.

[0067] Optionally, if the target vehicle is traveling straight, but the front wheel steering angle indicates that the front wheels are turning, it means that when the driver is controlling the vehicle to travel straight, the front wheels of the vehicle are turning in a different direction than the direction controlled by the driver, and the target vehicle is determined to have performed a sideslip.

[0068] Step 602: Apply braking force to the wheel on the opposite side of the sideslip direction according to the steering angle corresponding to the sideslip direction.

[0069] Optionally, if the positive direction of the steering angle is defined as left-side sideslip, then the negative direction of the steering angle is defined as right-side sideslip. If a positive steering angle is detected, the sideslip direction of the target vehicle is determined to be left; if a negative steering angle is detected, the sideslip direction of the target vehicle is determined to be right.

[0070] For example, if the target vehicle's sideslip direction is determined to be to the left, then braking force is applied to the right wheels; conversely, if the target vehicle's sideslip direction is determined to be to the right, then braking force is applied to the left wheels.

[0071] In this embodiment, if the target vehicle is traveling straight, but the front wheel steering angle indicates that the front wheels are turning, it is determined that the target vehicle has experienced a straight-line sideslip. Based on the steering angle corresponding to the sideslip direction, braking force is applied to the wheels on the opposite side of the sideslip direction. This application achieves precise control after determining the sideslip based on the front wheel steering angle, enabling intervention to begin before the vehicle body shows significant lateral deviation, allowing more time to control the sideslip. By applying braking force to the opposite wheels, the intervention response speed is faster, and there is no need to significantly change the vehicle speed.

[0072] Based on the above embodiments, this application also provides a process for controlling the longitudinal force of the wheels in a vehicle control method. Figure 7 This is a flowchart illustrating the longitudinal force control of wheels in a vehicle control method provided in an embodiment of this application, as shown below. Figure 7 As shown, based on steps 201-205 above, the method further includes: Step 701: Calculate the maximum adhesion force of each wheel based on the road surface adhesion coefficient and the vertical load of each wheel in the target vehicle.

[0073] Among them, the vertical load on the wheel is the force perpendicular to the ground that is transmitted from the vehicle body and the load to the wheel through the suspension system when the vehicle is stationary or moving.

[0074] Optionally, based on the road surface adhesion coefficient and the vertical load of each wheel The maximum adhesion force of each wheel was calculated. .

[0075] In step 205 above, the longitudinal force of the target vehicle's wheels is adjusted based on the real-time yaw angle deviation, including: Step 702: Based on the real-time yaw angle deviation and the maximum adhesion of each wheel, adjust the longitudinal force of the target vehicle's wheels so that the sum of the longitudinal force and lateral force of each wheel does not exceed the maximum adhesion of the corresponding wheel.

[0076] The longitudinal force of each wheel is the sum of the braking force and the driving force of the wheel, while the lateral force of each wheel is obtained through the electronic braking system on the target vehicle.

[0077] Optionally, the longitudinal force of the target vehicle's wheels is adjusted according to the maximum adhesion of the wheels, so that the sum of the longitudinal force and lateral force of each wheel does not exceed the maximum adhesion of the corresponding wheel, and at the same time, the real-time yaw angle deviation is reduced so that the yaw angle deviation is equal to a preset deviation threshold.

[0078] In this embodiment, the maximum adhesion force of each wheel is calculated based on the road surface adhesion coefficient and the vertical load of each wheel in the target vehicle. Based on the real-time yaw angle deviation and the maximum adhesion force of each wheel, the longitudinal force of the target vehicle's wheels is adjusted so that the sum of the longitudinal force and lateral force of each wheel does not exceed the maximum adhesion force of the corresponding wheel. This application controls the longitudinal force of the wheels based on their maximum adhesion force, avoiding waste or overloading of the vehicle's longitudinal force, while maintaining vehicle stability and ensuring vehicle stability.

[0079] Based on the above embodiments, the road surface detection parameters further include: road surface state parameters. This application also provides a process for generating warning prompts in a vehicle control method. Figure 8 This is a flowchart illustrating the generation of a warning prompt in a vehicle control method provided in an embodiment of this application, as shown below. Figure 8 As shown, based on steps 201-205 above, the method further includes: Step 801: Determine whether the current driving road surface meets the preset road driving warning conditions based on the road surface condition parameters.

[0080] The road surface condition parameters include: dry, wet, ice, snow, and icy-snow, as well as the ice content, water film height, road surface temperature, and snow thickness. Preset road surface warning conditions may include: slippery conditions, low-temperature road surface icing warning conditions, high-temperature road surface softening conditions, road surface damage conditions, and road surface tilt / sideslip risk conditions, etc., but this application embodiment does not impose any limitations on these.

[0081] Optionally, the road surface condition parameters can be used to determine whether the current driving road surface meets the parameter conditions in the preset road driving warning conditions.

[0082] Step 802: If the preset route warning conditions are met, a driving warning message will be issued.

[0083] Optionally, if the preset path warning conditions are met, it means that the current road surface parameters are consistent with the parameters of the preset path warning conditions. In this case, a driving warning message is issued and sent to the vehicle's instrument panel, thereby prompting the driver to drive cautiously.

[0084] Accordingly, Figure 1 The vehicle control system also includes an instrument panel. Figure 9 A schematic diagram of another vehicle control system provided in this application embodiment is shown below. Figure 9 As shown above, in the above Figure 1 In addition to the above, the vehicle control system 100 also includes an instrument panel 107, which is used to receive driving warning information.

[0085] In this embodiment, the system determines whether the current road surface meets preset road driving warning conditions based on road surface condition parameters. If the preset road warning conditions are met, a driving warning message is issued. This application, through driving warning conditions, can provide drivers with sufficient reaction time, reducing the probability of accidents from the source and preventing risks from escalating due to improper operation.

[0086] Based on the above embodiments, the road surface detection parameters include: two sets of road surface detection parameters collected by two road surface detection devices; each set of road surface detection parameters includes a road surface adhesion coefficient. This application also provides a process for determining the target yaw rate in another vehicle control method. Figure 10 A flowchart illustrating the determination of the target yaw rate in another vehicle control method provided in this application embodiment is shown below. Figure 10 As shown, in step 203 above, the target yaw rate of the target vehicle is calculated based on the road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle, including: Step 1001: Determine the target road surface adhesion coefficient based on the two road surface adhesion coefficients in the two sets of road surface detection parameters.

[0087] The two road surface detection devices are respectively installed on the left wheel and the right wheel, and the corresponding two road surface adhesion coefficients include the road surface adhesion coefficient of the left wheel and the road surface adhesion coefficient of the right wheel.

[0088] Optionally, if the road surface adhesion coefficients of the left wheel and the right wheel are the same in the two sets of road surface detection parameters, then the road surface adhesion coefficients corresponding to the road surface adhesion coefficients of the left wheel and the right wheel are taken as the target road surface adhesion coefficients.

[0089] Optionally, if the road adhesion coefficients of the left and right wheels are different in the two sets of road surface detection parameters, then the road adhesion coefficients of the left and right wheels are weighted separately to obtain the weighted road adhesion coefficient as the target road adhesion coefficient. The weights of the left and right wheel road adhesion coefficients can be determined based on the vertical load on the wheels; a larger vertical load corresponds to a larger weight.

[0090] Step 1002: Calculate the target yaw rate of the target vehicle based on the target road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle.

[0091] Optionally, the target yaw rate of the target vehicle is calculated based on the target road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle, and the target yaw rate of the corresponding target vehicle is determined by the target yaw rate calculation formula in step 203.

[0092] Correspondingly, Figure 1 The vehicle control system includes two road surface detection devices. Figure 11 This is a schematic diagram of another vehicle control system provided in an embodiment of this application, as shown below. Figure 11 As shown above, in the above Figure 1 Based on this, the road surface detection device 101 in the vehicle control system 100 also includes: road surface detection device 01 and road surface detection device 02. Road surface detection device 01 is used to obtain the road surface adhesion coefficient of the left wheel, and road surface detection device 02 is used to obtain the road surface adhesion coefficient of the right wheel.

[0093] In this embodiment, the target road surface adhesion coefficient is determined based on two road surface adhesion coefficients from two sets of road surface detection parameters; the target yaw rate of the target vehicle is calculated based on the target road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle. In this embodiment, determining the target road surface adhesion coefficient using two road surface adhesion coefficients avoids control errors of the target vehicle caused by deviations in a single parameter, improves the accuracy of determining the target yaw rate, and meets the driver's driving needs.

[0094] The layout of the vehicle control system provided in the embodiments of this application will be described below with reference to the accompanying drawings. Figure 12 This is a schematic diagram of the layout of a vehicle control system provided in an embodiment of this application, as shown below. Figure 12As shown, the road surface detection device 01 is located at the front left side of the vehicle and is used to detect the road surface coefficient of the left wheel. The road surface detection device 02 is located at the front right side of the vehicle and is used to detect the road surface coefficient of the right wheel. The controller 102 is located in the control area below the driver's cab. The electric braking system 103 is located in the control area in the middle of the vehicle and is used to adjust the braking force of the target vehicle's wheels. The vehicle control unit 104 is located in the control area in the middle of the vehicle and is used to adjust the driving force of the target vehicle. The motor is mounted on the bearing connecting the left and right rear wheels, and the motor controller 105 is located at the rear of the vehicle and connected to the motor for controlling the motor. The electro-hydraulic power steering system 106 is mounted on the bearing connecting the left and right front wheels and is used to control the vehicle's steering and collect the front wheel steering angle. The instrument panel 107 is located in front of the driver in the driver's cab.

[0095] Based on the same inventive concept, this application also provides a vehicle control device corresponding to the vehicle control method. Since the principle of the device in this application is similar to that of the vehicle control method described above, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0096] Figure 13 This is a schematic diagram of a vehicle control device provided in an embodiment of the present application. The device includes: a first acquisition module 1301, a second acquisition module 1302, a calculation module 1303, a determination module 1304, and an adjustment module 1305; wherein, the first acquisition module 1301 is used to acquire road surface detection parameters of the current driving road surface of the target vehicle, and the road surface detection parameters include: road surface adhesion coefficient. The second acquisition module 1302 is used to acquire the target vehicle's current speed, front wheel steering angle, and real-time yaw rate. The calculation module 1303 is used to calculate the target yaw rate of the target vehicle based on the road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle. The determination module 1304 is used to determine the real-time yaw rate deviation of the target vehicle based on the real-time yaw rate and the target yaw rate. The adjustment module 1305 is used to adjust the longitudinal force of the target vehicle's wheels based on the real-time yaw angle deviation. The longitudinal force of the wheels includes the vehicle's braking force and / or the wheel's driving force.

[0097] In one possible implementation, the adjustment module 1305 is specifically used to: apply braking force to the outer front wheel of the target vehicle if the real-time yaw angle deviation is greater than a preset minimum deviation threshold. If the real-time yaw angle deviation is less than the preset minimum deviation threshold, braking force is applied to the inner rear wheel of the target vehicle.

[0098] In one possible implementation, the adjustment module 1305 is further configured to: if the real-time yaw angle deviation is greater than a preset minimum deviation threshold, perform a first control on the drive wheels of the target vehicle, so that the driving force of the inner drive wheel of the target vehicle is greater than the driving force of the outer drive wheel. If the real-time yaw angle deviation is less than the preset minimum deviation threshold, the drive wheels of the target vehicle are controlled in a second way so that the driving force of the outer inner drive wheel of the target vehicle is greater than the driving force of the inner drive wheel.

[0099] In one possible implementation, the calculation module 1303 is further configured to: acquire driving intention information of the target vehicle; Based on the driving intent information, determine whether the target vehicle is in a turning state; In one possible implementation, the calculation module 1303 is specifically used to: if the target vehicle is in a turning state, calculate the target yaw rate of the target vehicle based on the road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle.

[0100] In one possible implementation, the calculation module 1303 is further configured to: if the target vehicle is in a straight-going state, but the front wheel steering angle indicates that the front wheel is turning, then determine that the target vehicle has experienced a straight-going sideslip. Based on the steering angle corresponding to the side slip direction, apply braking force to the wheel on the opposite side of the side slip direction.

[0101] In one possible implementation, the adjustment module 1305 is further configured to: calculate the maximum adhesion force of each wheel based on the road surface adhesion coefficient and the wheel vertical load of each wheel in the target vehicle. In one possible implementation, the adjustment module 1305 is specifically used to: adjust the longitudinal force of the target vehicle's wheels based on the real-time yaw angle deviation and the maximum adhesion of each wheel, so that the sum of the longitudinal force and lateral force of each wheel does not exceed the maximum adhesion of the corresponding wheel.

[0102] In one possible implementation, the road surface detection parameters further include: road surface state parameters; the device further includes: a warning module, which is specifically used to: determine whether the current driving road surface meets the preset road surface driving warning conditions based on the road surface state parameters; If the preset route warning conditions are met, a driving warning message will be issued.

[0103] In one possible implementation, the road surface detection parameters include: two sets of road surface detection parameters collected by two road surface detection devices; each set of road surface detection parameters includes a road surface adhesion coefficient; the calculation module 1303 is specifically used to: determine the target road surface adhesion coefficient based on the two road surface adhesion coefficients in the two sets of road surface detection parameters; Calculate the target yaw rate of the target vehicle based on the target road surface adhesion coefficient, current vehicle speed, and front wheel steering angle.

[0104] The processing flow of each module in the device and the interaction flow between each module can be referred to the relevant descriptions in the above method embodiments, and will not be detailed here.

[0105] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the vehicle control method described above.

[0106] Based on the above embodiments, this application also provides a vehicle. Figure 14 This application provides a schematic diagram of the structure of a vehicle, which includes at least: a vehicle body 1401 and a vehicle control system 100 on the vehicle body. The vehicle control system 100 is as described above. Figure 1 The vehicle control system 100 in the middle.

[0107] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and devices described above can be referred to the corresponding processes in the method embodiments, and will not be repeated here. In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection can be through some communication interfaces; the indirect coupling or communication connection of devices or modules can be electrical, mechanical, or other forms.

[0108] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. If the functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0109] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A vehicle control method, characterized in that, The method includes: Obtain road surface detection parameters of the current road surface of the target vehicle, wherein the road surface detection parameters include: road surface adhesion coefficient; Obtain the target vehicle's current speed, front wheel steering angle, and real-time yaw rate; The target yaw rate of the target vehicle is calculated based on the road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle. The real-time yaw rate deviation of the target vehicle is determined based on the real-time yaw rate and the target yaw rate. Based on the real-time yaw angle deviation, the longitudinal force of the target vehicle's wheels is adjusted, and the longitudinal force of the wheels includes: vehicle braking force and / or wheel driving force.

2. The method according to claim 1, characterized in that, The step of adjusting the longitudinal force of the target vehicle's wheels based on the real-time yaw angle deviation includes: If the real-time yaw angle deviation is greater than the preset minimum deviation threshold, then braking force is applied to the outer front wheel of the target vehicle. If the real-time yaw angle deviation is less than the preset minimum deviation threshold, then braking force is applied to the inner rear wheel of the target vehicle.

3. The method according to claim 2, characterized in that, The step of adjusting the longitudinal force of the target vehicle's wheels based on the real-time yaw angle deviation further includes: If the real-time yaw angle deviation is greater than the preset minimum deviation threshold, the drive wheels of the target vehicle are controlled in the first stage, so that the driving force of the inner drive wheel of the target vehicle is greater than the driving force of the outer drive wheel. If the real-time yaw angle deviation is less than the preset minimum deviation threshold, the drive wheels of the target vehicle are subjected to a second control, such that the driving force of the outer inner drive wheel of the target vehicle is greater than the driving force of the inner drive wheel.

4. The method according to claim 1, characterized in that, The method further includes: Obtain the driving intention information of the target vehicle; Based on the driving intention information, determine whether the target vehicle is in a turning state; The step of calculating the target yaw rate of the target vehicle based on the road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle includes: If the target vehicle is turning, the target yaw rate of the target vehicle is calculated based on the road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle.

5. The method according to claim 4, characterized in that, The method further includes: If the target vehicle is traveling straight, but the front wheel steering angle indicates that the front wheels are turning, then it is determined that the target vehicle has experienced a straight-line sideslip. Based on the steering angle corresponding to the sideslip direction, braking force is applied to the wheel on the opposite side of the sideslip direction.

6. The method according to claim 1, characterized in that, The method further includes: The maximum adhesion force of each wheel is calculated based on the road surface adhesion coefficient and the vertical wheel load of each wheel in the target vehicle. The step of adjusting the longitudinal force of the target vehicle's wheels based on the real-time yaw angle deviation includes: Based on the real-time yaw angle deviation and the maximum adhesion of each wheel, the longitudinal force of the target vehicle's wheels is adjusted so that the sum of the longitudinal force and lateral force of each wheel does not exceed the maximum adhesion of the corresponding wheel.

7. The method according to claim 1, characterized in that, The road surface detection parameters further include: road surface condition parameters; the method further includes: Determine whether the current driving road surface meets the preset road driving warning conditions based on the road surface state parameters; If the preset path warning conditions are met, a driving warning message will be issued.

8. The method according to claim 1, characterized in that, The road surface detection parameters include: two sets of road surface detection parameters collected by two road surface detection devices; each set of road surface detection parameters includes a road surface adhesion coefficient; The step of calculating the target yaw rate of the target vehicle based on the road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle includes: The target road surface adhesion coefficient is determined based on the two road surface adhesion coefficients in the two sets of road surface detection parameters. The target yaw rate of the target vehicle is calculated based on the target road surface adhesion coefficient, the current vehicle speed, and the front wheel steering angle.

9. A vehicle control system, characterized in that, The vehicle control system includes at least: a road surface detection device, a controller, an electric braking system, a vehicle control unit, a motor controller, and an electro-hydraulic power steering system; The road surface detection device is connected to the controller and is used to collect road surface detection parameters of the road surface on which the target vehicle is currently traveling. The road surface detection parameters include the road surface adhesion coefficient. The controller is connected to the vehicle control unit to obtain the current speed of the target vehicle. The controller is also connected to the electro-hydraulic power steering system to obtain the front wheel steering angle collected by the electro-hydraulic power steering system. The controller is also used to calculate the target yaw rate of the target vehicle based on the road adhesion coefficient, the current vehicle speed and the front wheel steering angle. The electric braking system is connected to the controller to obtain the target yaw rate; the electric braking system is used to: obtain the real-time yaw rate of the target vehicle, and determine the real-time yaw rate deviation of the target vehicle based on the real-time yaw rate and the target yaw rate, and adjust the wheel braking force of the target vehicle based on the real-time yaw rate deviation. The vehicle control unit is connected to the electric braking system to obtain the real-time yaw rate. The vehicle control unit is also used to: obtain the target yaw rate from the controller; determine the real-time yaw rate deviation of the target vehicle based on the real-time yaw rate and the target yaw rate; and control the motor controller of the target vehicle based on the real-time yaw rate deviation to adjust the wheel driving force of the target vehicle.

10. A vehicle, characterized in that, The vehicle includes at least: a vehicle body and a vehicle control system on the vehicle body, wherein the vehicle control system is the vehicle control system described in claim 9.

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