Vehicle driving control methods, systems, equipment, media and vehicles
By integrating kinematic and dynamic estimation of the center of gravity sideslip angle and combining it with dual closed-loop control of feedforward slip ratio, the problem of insufficient estimation of the center of gravity sideslip angle of unmanned vehicles under extreme conditions is solved, thereby improving the stability and maneuverability of the drift state.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BYD CO LTD
- Filing Date
- 2026-03-05
- Publication Date
- 2026-06-02
AI Technical Summary
In the drift control of existing autonomous vehicles under extreme conditions, the accuracy of the center of gravity sideslip angle estimation is insufficient, and the control stability and system computing power requirements are difficult to meet the needs of mass-produced vehicles.
The sideslip angle of the center of gravity is fused using kinematic and dynamic estimation methods, and combined with the feedforward slip ratio. A dual closed-loop control structure is used to perform closed-loop control on the sideslip angle and slip ratio respectively, and the required driving torque and steering angle of the front and rear axle wheels are calculated.
It achieves precise control of key kinematic parameters of drift, improves the stability and handling ability of drift state, and enhances the control effect of vehicle under extreme conditions.
Smart Images
Figure CN122126248A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of vehicle control technology, and in particular to a vehicle driving control method, system, device, medium, and vehicle. Background Technology
[0002] With the development of autonomous driving technology, the control capability of vehicles under extreme conditions has become a research hotspot. Drift control, as a typical extreme condition control technology, can significantly improve the handling stability and trajectory tracking capability of vehicles on low-traction surfaces or during high-speed cornering. In related technologies, drift control of autonomous vehicles usually relies on a single kinematic model or a simple dynamic model to estimate the center of gravity sideslip angle, lacking a compensation mechanism for model errors under high dynamic conditions. This results in shortcomings in the accuracy of the center of gravity sideslip angle estimation, the stability of drift control, and the system's computational requirements, making it difficult to meet the control requirements of mass-produced vehicles under extreme conditions. Summary of the Invention
[0003] The present invention aims to solve at least one problem existing in the prior art.
[0004] To achieve the above objectives, a first aspect of the present invention provides a vehicle driving control method, the method comprising: acquiring vehicle state parameters, including longitudinal velocity, lateral acceleration, yaw rate, and front wheel steering angle; estimating the vehicle's center of mass sideslip angle using kinematic estimation and dynamic estimation methods respectively based on the vehicle state parameters, obtaining kinematic and dynamic center of mass sideslip angle estimates; fusing the kinematic and dynamic center of mass sideslip angle estimates according to a fusion rule to obtain a fused center of mass sideslip angle estimate; determining a target slip ratio for the rear axle wheels based on the fused center of mass sideslip angle estimate and a feedforward slip ratio, and calculating the required driving torque for the rear axle wheels based on the target slip ratio and the actual slip ratio; calculating the front wheel steering angle or front wheel steering angle increment based on the vehicle's lateral position error and yaw heading error; and calculating the required driving torque for the front axle wheels based on the current target velocity and the actual longitudinal velocity. The beneficial effects of the above scheme are as follows: by integrating kinematic estimation and dynamic estimation into a center of mass sideslip angle estimation method, and combining it with a fusion rule based on lateral acceleration and center of mass sideslip angle amplitude, a dual closed-loop control structure is adopted to perform closed-loop control on the center of mass sideslip angle and slip ratio respectively, thereby achieving precise control of key kinematic parameters of drift and improving the stability of drift state.
[0005] In conjunction with the first aspect above, in one possible implementation, the kinematic estimation method includes: calculating the rate of change of lateral velocity based on the lateral acceleration, longitudinal velocity, and yaw rate; integrating the rate of change of lateral velocity to obtain a lateral velocity estimate; and calculating a kinematic center-of-mass sideslip angle estimate based on the lateral velocity estimate and the longitudinal velocity.
[0006] In conjunction with the first aspect mentioned above, in one possible implementation, the dynamic estimation method is based on a nonlinear two-degree-of-freedom vehicle dynamics model and uses an extended Kalman filter algorithm to estimate the dynamic centroid sideslip angle.
[0007] In conjunction with the first aspect above, in one possible implementation, the fusion rule is as follows: ,in, This is the estimated centroid sideslip angle after fusion. This is an estimate of the sideslip angle of the kinematic center of mass. The estimated value of the dynamic center of mass sideslip angle is given by k, which is a weighting coefficient. The weighting coefficient k is set according to the magnitude of the lateral acceleration and the center of mass sideslip angle: when the absolute value of the lateral acceleration is greater than or equal to the first threshold, or when the maximum value of the estimated kinematic center of mass sideslip angle and the estimated dynamic center of mass sideslip angle is greater than or equal to the second threshold, k=0; otherwise, k=1.
[0008] In conjunction with the first aspect above, in one possible implementation, the feedforward slip ratio is obtained by steady-state drift test calibration, and the feedforward slip ratio is the wheel slip ratio corresponding to the center of gravity sideslip angle under steady-state drift conditions.
[0009] In conjunction with the first aspect above, in one possible implementation, the driving torque required by the rear axle wheels is used as the control input of the rear axle power source to achieve drift control; the driving torque required by the front axle wheels is used as the control input of the front axle power source to achieve longitudinal speed tracking control; and the front wheel steering angle or front wheel steering angle increment is used as the control input of the front wheel steering mechanism to achieve path tracking control.
[0010] Secondly, a vehicle driving control system is proposed, comprising: a sensor module for acquiring vehicle state parameters, including longitudinal velocity, lateral acceleration, yaw rate, and front wheel steering angle; a center of mass sideslip angle estimation module for estimating the vehicle's center of mass sideslip angle based on the vehicle state parameters using kinematic estimation and dynamic estimation methods respectively, obtaining kinematic and dynamic center of mass sideslip angle estimates, and fusing them according to a fusion rule to obtain a fused center of mass sideslip angle estimate; a rear axle drive torque control module for determining the target slip ratio of the rear axle wheels based on the fused center of mass sideslip angle estimate and the feedforward slip ratio, and calculating the required drive torque for the rear axle wheels based on the target slip ratio and the actual slip ratio; a front wheel steering angle control module for calculating the front wheel steering angle or front wheel steering angle increment based on the vehicle's lateral position error and yaw heading error; and a front axle drive torque control module for calculating the required drive torque for the front axle wheels based on the current target velocity and the actual longitudinal velocity.
[0011] Thirdly, a vehicle is proposed, including a vehicle driving control system as described in the second aspect.
[0012] Fourthly, an electronic device is proposed, comprising: a processor; and a memory for storing executable instructions; the processor being configured to execute the executable instructions to implement the vehicle driving control method as described above.
[0013] Fifthly, a computer-readable storage medium is proposed, on which a computer program is stored, which, when executed by a processor, implements the vehicle driving control method as described above. Attached Figure Description
[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0015] Figure 1 This is a structural block diagram of a vehicle driving control system provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the control logic of the vehicle driving control method provided in an embodiment of the present invention. Detailed Implementation
[0016] To make the technical problems to be solved, the technical solutions, and the beneficial effects of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present invention and are not intended to limit the present invention.
[0017] It should be noted that when a component is referred to as being "fixed to" or "set on" another component, it can be directly on or indirectly on that other component. When a component is referred to as being "connected to" another component, it can be directly connected to or indirectly connected to that other component.
[0018] It should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the present invention.
[0019] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.
[0020] The present invention will now describe a specific embodiment of a vehicle driving control method.
[0021] This application provides a vehicle driving control method, the method comprising: Step S100: Obtain vehicle state parameters, including longitudinal velocity, lateral acceleration, yaw rate and front wheel steering angle; Step S200: Based on the vehicle state parameters, estimate the vehicle's center of mass sideslip angle using both kinematic and dynamic estimation methods to obtain the kinematic and dynamic center of mass sideslip angle estimates. Step S300: The kinematic center of mass sideslip angle estimate and the dynamic center of mass sideslip angle estimate are fused according to the fusion rule to obtain the fused center of mass sideslip angle estimate; Step S400: Based on the fused centroid sideslip angle estimate and the feedforward slip ratio, determine the target slip ratio of the rear axle wheels, and calculate the required driving torque of the rear axle wheels based on the target slip ratio and the actual slip ratio; Step S500: Calculate the front wheel angle or front wheel angle increment based on the vehicle's lateral position error and yaw heading error; Step S600: Calculate the required driving torque for the front axle wheels based on the current target speed and the actual longitudinal speed.
[0022] In the above embodiments, by fusing the sideslip angle of the center of mass from both kinematic and dynamic estimation paths and employing a weight switching mechanism based on adaptive operating conditions, the robustness of state estimation under extreme drift conditions is significantly improved. At the same time, by forming a dual closed-loop structure with sideslip angle control and slip ratio control, and independently controlling the front and rear axle drive torques and front wheel steering angle, triple coordinated control of drift attitude, longitudinal speed, and lateral path is achieved, solving the technical problems of decoupling of control targets, poor stability, and hysteresis in traditional methods.
[0023] In some embodiments, the kinematic estimation method in step S200 includes: Step S210: Calculate the rate of change of lateral velocity based on lateral acceleration, longitudinal velocity, and yaw rate; Step S220: Integrate the rate of change of lateral velocity to obtain an estimated value of lateral velocity; Step S230: Calculate the estimated value of the kinematic center of mass sideslip angle based on the estimated lateral velocity and longitudinal velocity.
[0024] In some embodiments, the vehicle's center of gravity sideslip angle is estimated using both kinematic estimation and dynamic estimation methods to obtain kinematic center of gravity sideslip angle estimates. and the estimated value of the sideslip angle of the center of mass in dynamics Then, the two are fused according to the preset fusion rules to obtain the fused centroid sideslip angle estimate. .
[0025] Specifically, the kinematic estimation method is as follows: First, based on lateral acceleration... Longitudinal velocity Given the yaw rate γ, calculate the rate of change of lateral velocity. :
[0026] Then, by integrating the rate of change of the lateral velocity, the estimated value of the lateral velocity is obtained. :
[0027] Finally, based on the estimated lateral velocity... and longitudinal velocity Calculate the estimated value of the kinematic center of mass sideslip angle:
[0028] The dynamics estimation method is based on a nonlinear two-degree-of-freedom vehicle dynamics model and employs the extended Kalman filter algorithm for estimation. The constructed nonlinear two-degree-of-freedom vehicle dynamics model is as follows:
[0029] Where β is the sideslip angle of the center of mass, and γ is the yaw rate. This refers to the lateral force on the front axle of the vehicle. This refers to the lateral force on the rear axle of the vehicle. This is the distance from the vehicle's center of gravity to the front axle. Let m be the distance from the vehicle's center of gravity to the rear axle, and m be the vehicle's mass. Let be the vehicle's moment of inertia about the z-axis. The extended Kalman filter algorithm is used to perform state estimation on this nonlinear model, thus obtaining the estimated value of the dynamic center-of-mass sideslip angle. .
[0030] The fusion rule adopts a weighted average form:
[0031] Where k is the weighting coefficient, and its setting rules are as follows:
[0032] in, The lateral acceleration threshold, The threshold for the sideslip angle needs to be calibrated based on actual test results. The physical meaning of this fusion rule is that when the lateral acceleration or sideslip angle is large, the vehicle tire is in a highly nonlinear region, and the estimation accuracy of the dynamic model decreases. In this case, the kinematic estimation result should be used. Under other operating conditions, the dynamic estimation is more accurate, so the dynamic estimation result should be used.
[0033] like Figure 2 As shown, in some specific embodiments, the method mainly includes four control loops: path tracking lateral control, longitudinal speed control, centroid sideslip angle control, and slip ratio control.
[0034] First, vehicle status parameters are acquired through sensors, including longitudinal velocity, lateral acceleration, yaw rate, and front wheel steering angle.
[0035] Then, the fusion estimation method described in Example 1 is used to estimate the centroid sideslip angle of the vehicle to obtain the fused centroid sideslip angle estimate.
[0036] In the sideslip angle control loop, the fused sideslip angle estimate is used as feedback and compared with the target sideslip angle. The error is input to the sideslip angle controller, and the output is the slip ratio correction. In the slip ratio control loop, the slip ratio correction is added to the feedforward slip ratio calibrated through steady-state drift testing to obtain the target slip ratio. Using the target slip ratio as the target value and the actual slip ratio as feedback, the error is input to the slip ratio controller, and the output is the driving torque required for the rear axle wheels. This torque controls the rear axle power source, achieving drift control.
[0037] In the lateral control loop for path tracking, the lateral position error and yaw error between the vehicle's current position and the target path are used as inputs. The lateral controller calculates the front wheel angle or the front wheel angle increment, controls the front wheel steering mechanism, and achieves path tracking.
[0038] In the longitudinal speed control loop, the current target speed is used as the target value, the actual longitudinal speed is used as feedback, the error is input to the longitudinal speed controller, and the output is the driving torque required by the front axle wheels, which controls the front axle power source to achieve longitudinal speed tracking.
[0039] Through the coordinated operation of the above four control loops, the vehicle can accurately track the target path while maintaining the target speed in a drifting state, thus achieving stable control under extreme conditions.
[0040] refer to Figure 1 As shown, the present invention provides a vehicle driving control system, the system including a sensor module, a center of gravity sideslip angle estimation module, a rear axle drive torque control module, a front wheel steering angle control module, and a front axle drive torque control module.
[0041] The rear axle drive torque control module is used to implement sideslip angle control and slip ratio control. This module receives the fused sideslip angle estimate. The target slip ratio for the rear axle wheels is determined by combining the feedforward slip ratio. The feedforward slip ratio is calibrated through steady-state drift testing; that is, under steady-state drift conditions, the wheel slip ratio corresponding to different centroid sideslip angles is measured, generating a calibration table or fitted curve. Based on the current target centroid sideslip angle (given by the upper-level planning module), the corresponding feedforward slip ratio is obtained by looking up the table or calculation. The feedforward slip ratio is added to the output of the centroid sideslip angle controller to obtain the final target slip ratio. Then, based on the error between the target slip ratio and the actual slip ratio (which can be estimated by the wheel speed sensor), the required driving torque for the rear axle wheels is calculated by the slip ratio controller (e.g., a PID controller). This driving torque serves as the control input for the rear axle power source, used to achieve drift control.
[0042] The front wheel steering angle control module is used to implement lateral control for path tracking. This module receives the lateral position error and yaw rate error between the vehicle's current position and the target path, and calculates the required front wheel steering angle or front wheel steering angle increment using a lateral controller (such as a PID controller, LQR controller, etc.). This front wheel steering angle signal serves as the control input to the front wheel steering mechanism for path tracking control.
[0043] The front axle drive torque control module is used to implement longitudinal speed control. This module receives the current target speed (given by the upper-level planning module) and the actual longitudinal speed, calculates the speed error, and uses a longitudinal speed controller (e.g., a PID controller) to calculate the required drive torque for the front axle wheels. This drive torque serves as the control input to the front axle power source, enabling longitudinal speed tracking control.
[0044] The aforementioned power sources can be wheel-side drive motors, hub motors, or mechanical devices that output power from an internal combustion engine to the wheel axles via a transfer case / differential.
[0045] In some specific embodiments, the front wheel steering angle control module of the vehicle driving control system outputs commands that are executed by the steering controller, supporting incremental control and avoiding sudden changes in steering angle. The front axle drive torque control module works in conjunction with the front drive electronic control unit to achieve independent torque distribution between the front and rear axles. The system supports OTA upgrades and can dynamically update the fusion weight threshold and slip ratio calibration curve to adapt to different tire models and load conditions.
[0046] This application also provides a vehicle, including the vehicle driving control system as described above.
[0047] In some specific embodiments, the vehicle is equipped with an active air suspension and a rear-wheel steering system that work in conjunction with this control system: in drift mode, the rear-wheel steering system automatically adjusts the rear wheel angle based on the estimated center of gravity sideslip angle to enhance steering response; the air suspension reduces the body roll stiffness and increases the adjustable range of sideslip angle.
[0048] This application also provides an electronic device, including: a processor; a memory for storing executable instructions; the processor is configured to execute the executable instructions to implement the vehicle driving control method as described above.
[0049] This application also provides a computer-readable storage medium storing a computer program thereon, characterized in that the computer program, when executed by a processor, implements the vehicle driving control method as described above.
[0050] Although one or more specific embodiments of this disclosure have been shown and described, equivalent variations and modifications will occur to those skilled in the art upon reading and understanding this specification and the accompanying drawings. This disclosure includes all such modifications and variations and is limited only by the scope of the claims. In particular, with respect to the various functions performed by the components described above (e.g., elements, resources, etc.), unless otherwise indicated, the terminology used to describe such components is intended to correspond to any component (functionally equivalent) that performs the specific function of the described component, even if structurally not equivalent to the disclosed structure. Furthermore, although specific features of this disclosure may have been disclosed with respect to only one of several implementations, such features may be combined with one or more other features of other implementations, as may be desired and advantageous for any given or particular application. Moreover, with regard to the terms “comprising,” “owning,” “having,” “having,” or variations thereof as used in the specific embodiments or claims, such terms are intended to be inclusive in a manner similar to the term “including.”
[0051] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the appended claims.
[0052] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.
Claims
1. A vehicle driving control method, characterized in that, Includes the following steps: Obtain vehicle state parameters, including longitudinal velocity, lateral acceleration, yaw rate, and front wheel steering angle; Based on the vehicle state parameters, the vehicle's center of mass sideslip angle is estimated using both kinematic and dynamic estimation methods, resulting in kinematic and dynamic center of mass sideslip angle estimates. The kinematic center of mass sideslip angle estimate and the dynamic center of mass sideslip angle estimate are fused according to the fusion rule to obtain the fused center of mass sideslip angle estimate. Based on the fused centroid sideslip angle estimate and the feedforward slip ratio, the target slip ratio of the rear axle wheel is determined, and the required driving torque of the rear axle wheel is calculated based on the target slip ratio and the actual slip ratio. Calculate the front wheel angle or front wheel angle increment based on the vehicle's lateral position error and yaw heading error; Calculate the required driving torque for the front axle wheels based on the current target speed and the actual longitudinal speed.
2. The vehicle driving control method according to claim 1, characterized in that, The kinematic estimation methods include: Calculate the rate of change of lateral velocity based on the lateral acceleration, longitudinal velocity, and yaw rate. Integrating the rate of change of the lateral velocity yields an estimated value of the lateral velocity; Based on the estimated lateral velocity and longitudinal velocity, calculate the estimated kinematic center of mass sideslip angle.
3. The vehicle driving control method according to claim 1, characterized in that, The dynamic estimation method is based on a nonlinear two-degree-of-freedom vehicle dynamics model and uses an extended Kalman filter algorithm to estimate the dynamic centroid sideslip angle.
4. The vehicle driving control method according to claim 1, characterized in that, The fusion rule is as follows: , in, This is the estimated centroid sideslip angle after fusion. This is an estimate of the sideslip angle of the kinematic center of mass. is the estimated side slip angle of the dynamic centroid, and k is the weighting coefficient; The weighting coefficient k is set according to the magnitude of the lateral acceleration and the sideslip angle of the center of mass: When the absolute value of the lateral acceleration is greater than or equal to the first threshold, or when the maximum value of the estimated kinematic center of mass sideslip angle and the estimated dynamic center of mass sideslip angle is greater than or equal to the second threshold, k=0; Otherwise, k=1.
5. The vehicle driving control method according to claim 1, characterized in that, The feedforward slip ratio is obtained through steady-state drift test calibration, and the feedforward slip ratio is the wheel slip ratio corresponding to the center of gravity sideslip angle under steady-state drift conditions.
6. The vehicle driving control method according to claim 1, characterized in that, The required driving torque of the rear axle wheels serves as the control input to the rear axle power source for drift control; the required driving torque of the front axle wheels serves as the control input to the front axle power source for longitudinal speed tracking control; and the front wheel steering angle or front wheel steering angle increment serves as the control input to the front wheel steering mechanism for path tracking control.
7. A vehicle driving control system, characterized in that, include: The sensor module is used to acquire vehicle state parameters, including longitudinal velocity, lateral acceleration, yaw rate and front wheel steering angle. The center of gravity sideslip angle estimation module is used to estimate the center of gravity sideslip angle of the vehicle based on the vehicle state parameters by using kinematic estimation method and dynamic estimation method respectively, to obtain the kinematic center of gravity sideslip angle estimate and the dynamic center of gravity sideslip angle estimate, and to fuse the two according to the fusion rule to obtain the fused center of gravity sideslip angle estimate. The rear axle drive torque control module is used to determine the target slip ratio of the rear axle wheels based on the fused centroid sideslip angle estimate and the feedforward slip ratio, and to calculate the required drive torque of the rear axle wheels based on the target slip ratio and the actual slip ratio. The front wheel steering angle control module is used to calculate the front wheel steering angle or the front wheel steering angle increment based on the vehicle's lateral position error and yaw heading error. The front axle drive torque control module is used to calculate the required drive torque for the front axle wheels based on the current target speed and the actual longitudinal speed.
8. A vehicle, characterized in that, Includes the vehicle driving control system as described in claim 7.
9. An electronic device, characterized in that, include: processor; Memory, used to store executable instructions; The processor is configured to execute the executable instructions to implement the vehicle driving control method as described in any one of claims 1 to 6.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the vehicle driving control method as described in any one of claims 1 to 6.