A vehicle intelligent drift control method based on multi-actuator coordination

Abstract

The application discloses a kind of vehicle intelligent drift control methods based on multi-actuator coordination, through to the drift state data acquisition and processing, realize the vehicle state observation under the drift state;Again based on drift equilibrium state calculation combines actual vehicle state obtains drift expected data;Finally under the multi-state feedback framework, driver request torque is fused with drift control correction, combined with the actuator configuration of vehicle, call multiple actuators to assist vehicle drift, finally realize the intelligent drift auxiliary control of vehicle, so as to reduce the difficulty of ordinary driver to complete drift, improve the stability and realizability of drift control.

Description

Technical Field

[0001] This invention relates to a vehicle intelligent drift control method based on multi-actuator coordination, and more particularly to a vehicle intelligent drift control method based on multi-actuator coordination that has low drift difficulty, high drift stability and feasibility, and can reduce drift difficulty and improve drift controllability. Background Technology

[0002] Vehicle drift control relies heavily on experienced drivers' precise control of vehicle attitude, yaw rate, and torque output. It often requires a high level of driver skill to control the entire process, from initiating a drift and maintaining balance to returning to normal steering. For ordinary drivers drifting, the rapid changes in key states such as yaw rate and sideslip angle, strong nonlinear coupling, and significant condition switching during drifting make existing control strategies insufficient in terms of state acquisition, target generation, and actuator coordination to meet robustness requirements under drifting conditions. This can easily lead to difficulties in tracking the drift target, vehicle instability (such as severe tail-swing), or vehicle exiting the drift, resulting in unstable drift-assisted control and insufficient operability. Furthermore, existing technologies offer limited means for coordinated control of multiple actuators, such as the rear-wheel steering mechanism, torque vector control, braking, and forward steering, making it difficult to fully utilize the collaborative capabilities of each actuator while ensuring safety, further increasing the difficulty of drift control.

[0003] Therefore, it is necessary to propose an improvement to overcome the shortcomings of the existing technology. Summary of the Invention

[0004] The purpose of this invention is to solve the problems in the prior art, such as the difficulty in obtaining stable state during vehicle drifting, the difficulty in robustly adapting control strategies to drifting conditions, and the high difficulty of drifting due to insufficient coordinated control of actuators. This invention provides a vehicle motion control method that can reduce the difficulty for ordinary drivers to complete drifting operations, and can coordinate multiple actuators to assist drivers in completing various types of drifting, thereby improving the stability and feasibility of drift control.

[0005] The technical solution of this invention is: A vehicle intelligent drift control method based on multi-actuator coordination includes the following steps: S1, Drift state data acquisition and processing: Acquiring drift-related vehicle data and processing the data to obtain key vehicle drift state data; the drift-related vehicle data includes vehicle pitch / roll / yaw attitude angles and / or attitude changes, yaw rate, wheel speeds, and basic vehicle electrical signals; the key vehicle drift state data includes center of gravity sideslip angle, vehicle speed, four-wheel slip ratio, vehicle yaw rate, and road surface adhesion coefficient; S2, Drift state judgment: When the driver... When manually confirming entry into drift mode, a drift phase determination is performed. When both the slip ratio and yaw rate are greater than the threshold, the vehicle is determined to be in a drift state, and step S3 is executed; S3, Drift expectation data calculation: Drift expectation data is calculated based on the vehicle's real-time status data to obtain the expected yaw rate and the expected center of gravity sideslip angle; S4, Drift control: The drift control quantity is determined based on the expected yaw rate, the expected center of gravity sideslip angle, and the vehicle's actual yaw rate and actual center of gravity sideslip angle. The drift controller coordinates and distributes the drift control quantity to multiple actuators for drift assistance.

[0006] As a preferred technical solution, the following steps are also included: S5, Drift safety limit: During the vehicle drifting process, the vehicle's mechanical variables are monitored, and safety constraints are applied to the speed and power-related quantities.

[0007] As a preferred technical solution, the drift-related vehicle data in step S1 is collected through an IMU sensor and / or a wheel speed sensor; the basic vehicle electrical signals include steering angle and braking / driving torque commands; the data processing includes filtering, anomaly removal, and time synchronization.

[0008] As a preferred technical solution, in step S1, the vehicle speed is determined primarily by the front wheel speed; when calculating the centroid sideslip angle, a nonlinear tire model is used to establish tire lateral dynamics, and the nonlinear mapping relationship between tire sideslip force and slip / side slip input is obtained. Based on the tire lateral dynamics model combined with the vehicle dynamics model, the vehicle's longitudinal speed, lateral speed, and yaw rate are incorporated into a unified estimation framework.

[0009] As a preferred technical solution, in step S2, when the driver manually confirms entering drift mode, the vehicle deactivates or downgrades the vehicle stability control system; the vehicle stability control system includes ABS, VDC, and TCS.

[0010] As a preferred technical solution, step S2, "when both slip ratio and yaw rate are greater than the threshold, it is determined that the vehicle is in a drift state," specifically means: when the slip ratio of the outer rear wheel is greater than the threshold, it is determined that the outer side of the vehicle is fully drifting; when the yaw rate of the vehicle is greater than the ideal neutral yaw rate, it is determined that the vehicle is fishtailing; the ideal neutral yaw rate is calculated as follows: when the vehicle is traveling around a circle or along a curvature, the ideal neutral yaw rate of the vehicle under the current operating conditions is calculated based on the vehicle's motion geometry; when the slip ratio of the outer rear wheel is greater than the threshold and the yaw rate of the vehicle is greater than the ideal neutral yaw rate, it is determined that the vehicle is in a drift state.

[0011] As a preferred technical solution, step S2, the drift state, also includes drift exit: when the driver exits in an emergency or the exit condition is met, the drift state is exited, and the control of the vehicle by subsequent drift steps is terminated; the driver's emergency exit includes: the driver pressing the brake pedal; the exit condition is that the following conditions are met simultaneously: the vehicle's center of gravity sideslip angle does not reach the drift threshold, the accelerator pedal opening is less than the calibrated threshold for a certain period of time, and the slip ratio of the vehicle's outer rear wheel is less than the calibrated threshold for a certain period of time.

[0012] As a preferred technical solution, the method for obtaining the desired yaw rate and desired center of gravity sideslip angle in step S3 is as follows: the desired yaw rate is determined based on the yaw dynamic characteristics of the vehicle after drifting; the desired center of gravity sideslip angle is calculated based on the drift equilibrium theory using the desired yaw rate and key vehicle drift state data; the desired yaw rate and desired center of gravity sideslip angle are input into a dual PID loop controller, which is used for error calculation of the yaw rate loop and the center of gravity sideslip angle loop, respectively, thereby performing closed-loop correction of the torque requested by the driver.

[0013] As a preferred technical solution, step S4, "determining the drift control torque based on the desired yaw rate, the desired sideslip angle, and the actual yaw rate and actual sideslip angle of the vehicle," specifically involves: determining an inner yaw rate loop and an outer sideslip angle loop based on the desired yaw rate, the desired sideslip angle, and the actual yaw rate and actual sideslip angle of the vehicle, forming an inner and outer loop control structure; the inner yaw rate loop performs feedback control based on the vehicle's yaw response; the output of the inner yaw rate loop is the drift control torque, which is superimposed on the driver's desired torque. When the actual yaw rate is greater than the desired yaw rate... At a given degree, the inner yaw rate loop triggers a torque reduction strategy based on the excessive yaw rate; the inner yaw rate loop only reduces torque based on the driver's desired torque; the outer centroid sideslip angle loop provides feedback control for the vehicle's attitude target; the outer centroid sideslip angle loop provides feedback control based on the error between the actual and desired centroid sideslip angles, and outputs a correction for the desired yaw rate: when the actual centroid sideslip angle deviates significantly from the desired value, the outer centroid sideslip angle loop uses PID control to correct the yaw target, thereby adjusting the target value of the yaw rate and indirectly driving the inner yaw rate loop to track and converge the centroid sideslip angle.

[0014] As a preferred technical solution, step S4, "the drift controller coordinates and distributes the drift control quantity to multiple actuators for drift assistance," specifically involves: converting the drift control torque quantity into executable commands for front axle torque, rear wheel steering, braking, torque vectoring, and front wheel steering as needed, and executing these commands on the corresponding actuators: Front axle torque: When a driver's large-angle counter-steering characteristic is detected, and the vehicle has entered a tail-swing state or is at risk of tail-swing instability, the front axle torque is invoked to assist in stabilizing the vehicle's attitude; Rear wheel steering: A dedicated rear wheel steering angle calibration table or mapping relationship is established; the calibration table ensures that the rear wheel steering angle maintains an opposite characteristic to the front wheel steering throughout the entire drift control process; Braking: When the vehicle is under medium-high adhesion conditions and uses an open differential structure, the braking strategy is invoked to adjust the speed of the inner wheels of the vehicle; Torque vectoring: The differential torque of the multi-motor platform is invoked to control the drift attitude; Front wheel steering: The front wheel steering actuator is invoked to achieve drift control, and the front wheel steering is adjusted in a closed loop under the driver's permission or confirmation.

[0015] This invention discloses a vehicle intelligent drift control method based on multi-actuator coordination. It collects and processes drift state data to observe the vehicle's state during drift. Then, it calculates the drift equilibrium state and combines it with the actual vehicle state to obtain desired drift data. Finally, within a multi-state feedback framework, it fuses the driver's requested torque with the drift control correction amount, and, combined with the vehicle's actuator configuration, calls multiple actuators to assist in vehicle drifting. This ultimately achieves intelligent drift-assisted control of the vehicle, reducing the difficulty for ordinary drivers to complete drifts and improving the stability and feasibility of drift control. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a specific implementation of the intelligent vehicle drift control method based on multi-actuator coordination according to the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” used in the embodiments of this invention and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. “Multiple” generally includes at least two, but does not exclude the inclusion of at least one.

[0019] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0020] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0021] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a product or system comprising a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a product or system. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the product or system that includes said element.

[0022] like Figure 1 The illustration shows a specific embodiment of a vehicle intelligent drift control method based on multi-actuator coordination according to the present invention. This embodiment of a vehicle intelligent drift control method based on multi-actuator coordination includes the following steps: S1. Drift State Data Acquisition and Processing: Acquire drift-related vehicle data and process the data to obtain key vehicle drift state data; the drift-related vehicle data includes vehicle pitch / roll / yaw attitude angles and / or attitude changes, yaw rate, wheel speeds, and basic vehicle electrical signals; the key vehicle drift state data includes center of gravity sideslip angle, vehicle speed, four-wheel slip ratio, vehicle yaw rate, and road surface adhesion coefficient; S2. Drift state judgment: When the driver manually confirms entering the drift mode, the drift stage is judged. When both the slip ratio and yaw rate are greater than the threshold, the vehicle is judged to be in a drift state, and step S3 is executed. S3. Drift expectation data calculation: Calculate the drift expectation data based on the vehicle's real-time status data to obtain the expected yaw rate and the expected center of gravity sideslip angle; S4. Drift control: The drift control quantity is determined based on the desired yaw rate, the desired center of gravity sideslip angle, and the actual yaw rate and actual center of gravity sideslip angle of the vehicle. The drift controller then coordinates and distributes the drift control quantity to multiple actuators for drift assistance.

[0023] In this embodiment, to ensure the safety of the drift assist control process and the reliability of the actuator, the following steps are also included: S5, Drift Safety Limitation: During the vehicle drift process, the vehicle's mechanical variables are monitored, and safety constraints are applied to speed and power-related quantities. Step S5 remains effective after the vehicle enters drift mode, monitoring key dynamic variables during the vehicle drift process and applying safety constraints to speed and power-related quantities; on the one hand, this is used to prevent actuator overload and damage caused by torque and slippage, and on the other hand, it is used to quickly intervene to stabilize the vehicle's attitude and ensure the safety of the driver and the vehicle in the event of driver error or unexpected severe instability caused by external disturbances.

[0024] In this embodiment, to achieve continuous and accurate control during vehicle drifting, step S1, drift state data acquisition and processing, is performed first: acquiring drift-related vehicle data and processing the data to obtain key vehicle drift state data; the drift-related vehicle data includes vehicle pitch / roll / yaw attitude angles and / or attitude changes, yaw rate, wheel speeds, and basic vehicle electrical signals; the key vehicle drift state data includes center of gravity sideslip angle, vehicle speed, four-wheel slip ratio, vehicle yaw rate, and road surface adhesion coefficient.

[0025] The drift-related vehicle data mentioned in step S1 is acquired through IMU sensors and / or wheel speed sensors; the basic vehicle electrical signals include steering angle and braking / drive torque commands; the data processing includes filtering, anomaly removal, and time synchronization. That is, using IMU sensors and wheel speed sensors as the basic data source, the data acquired includes, but is not limited to: vehicle pitch / roll / yaw attitude angles or attitude changes (obtained by the IMU), yaw rate (yaw rate channel), wheel speeds (obtained by wheel speed sensors), and basic vehicle electrical signals (such as steering angle δ, braking / drive torque commands, etc.). The data preprocessing module filters, removes anomalies, and synchronizes the original sensor signals to reduce the impact of sensor noise and delay on the observation results. Through the acquisition and processing of this data, real-time observation and calculation of key vehicle drift state data are achieved. Key vehicle drift state data includes center of gravity sideslip angle, vehicle speed, four-wheel slip ratio, vehicle yaw rate, and road surface adhesion coefficient, thus providing reliable input for subsequent drift expectation calculation and dual closed-loop control.

[0026] To achieve reliable estimation of critical states under drift conditions, in this embodiment, the vehicle speed is primarily determined by the front wheel speed. When calculating the center of gravity sideslip angle, a nonlinear tire model is used to establish tire lateral dynamics, obtaining the nonlinear mapping relationship between tire lateral force and slip / side slip input. Based on the tire lateral dynamics model combined with the vehicle dynamics model, the vehicle's longitudinal speed, lateral speed, and yaw rate are incorporated into a unified estimation framework.

[0027] Specifically, this embodiment fully considers the dynamic characteristics of a vehicle during drifting: during drifting, the rear wheels are typically in a state of continuous or saturated slip for an extended period, while the front wheels maintain relatively good adhesion. Based on this difference in operating conditions, this embodiment shifts the dominant information source for vehicle speed observation from "all-wheel speed" to an observation strategy that prioritizes "front wheel speed," improving the accuracy of vehicle speed calculation. Simultaneously, since the tires operate in a nonlinear region for an extended period during drifting, the relationship between tire lateral force and slip angle cannot be represented by a linearized tire model. Therefore, this embodiment employs a nonlinear tire model to establish tire lateral dynamics, obtaining a nonlinear mapping relationship between tire lateral force and slip / side slip input. Furthermore, based on the tire lateral dynamics model combined with the vehicle dynamics model, state parameters such as vehicle longitudinal velocity, lateral velocity, and yaw rate are incorporated into a unified estimation framework. This allows for more physically accurate estimation of key states such as lateral velocity and center-of-gravity slip angle during drifting, improving the accuracy of state observation.

[0028] To improve the adaptability and stability of drift assist control at different drift stages, this embodiment uses step S2 to determine the drift state: when the driver manually confirms entering drift mode, a drift stage determination is performed. When both the slip ratio and yaw rate are greater than the threshold, the vehicle is determined to be in a drift state, and step S3 is executed. Step S2 is used to determine and manage whether the vehicle is currently in a drift condition, the stage of the drift, and whether events such as drift exit / return to normal steering have occurred. The determination results are used for the drift state observer, drift expectation calculation, and the invocation and strategy switching of the drift controller, thereby ensuring the continuous controllability of the entire intelligent drift process.

[0029] In this implementation, when the driver manually confirms entry into drift mode, the vehicle deactivates or downgrades the vehicle stability control system. The vehicle stability control system includes ABS, VDC, and TCS. It should be understood that the vehicle stability control system in this embodiment is merely an example; in practical applications, the vehicle stability control system includes, but is not limited to, ABS, VDS, and TCS, thereby ensuring that the wheel-end driving force / braking force primarily originates from the driver's request and the drift control system, avoiding interference from these systems in vehicle drifting. After entering drift mode, the vehicle executes the driver's request within a safe margin, achieving a direct response to the driver's intentions, and continuously performs drift initiation detection and stage determination. When it is determined that the vehicle is in a drifting state, drift control intervenes and proceeds to step S3.

[0030] In this embodiment, step S2, "when both the slip ratio and yaw rate are greater than the threshold, it is determined that the vehicle is in a drift state," specifically means: When the slip ratio of the outer rear wheel is greater than the threshold, it is determined that the outer side of the vehicle has completely started to drift. When the vehicle's yaw rate is greater than the ideal neutral yaw rate, it is determined that the vehicle is fishtailing. The ideal neutral yaw rate is calculated as follows: when the vehicle is traveling around a circle or along a curvature, the ideal neutral yaw rate of the vehicle under the current operating conditions is calculated based on the vehicle's motion geometry. When the slip ratio of the outer rear wheel is greater than the threshold and the yaw rate of the vehicle is greater than the ideal neutral yaw rate, the vehicle is judged to be in a drift state.

[0031] The slip ratio of the vehicle's rear wheels is monitored in real time. Considering the vehicle's lateral axle load transfer characteristics, when the slip ratio of the outer rear wheel exceeds a threshold, it indicates that the vehicle has completed drifting and entered a sufficient slip state, at which point it is judged that the outer wheel has fully drifted. Furthermore, only when the vehicle is detected to have fully drifted (i.e., the condition for determining that the outer rear wheel has fully drifted is met) is it considered a necessary condition for the vehicle to be in a drift state; if only the slip ratio condition of the inner wheel is met, it is considered that the vehicle has just begun to drift, and this time point can be used as a reference for subsequent calculations of the target vehicle's state.

[0032] Simultaneously, the vehicle's yaw rate is monitored in real time. Specifically, when the vehicle travels in a circle or along a curvature, the ideal neutral yaw rate under the current operating conditions is calculated based on the vehicle's motion geometry. When the vehicle's actual yaw rate is greater than the ideal neutral yaw rate, it indicates that the vehicle is experiencing a certain degree of drift, and the yaw rate determination condition is met. This criterion is used to capture the "drift characteristics" of yaw dynamics, thus complementing the slip ratio criterion and improving the reliability of drift detection.

[0033] When both of the above conditions are met, the vehicle is determined to be in a drift state. Subsequent drift control steps are then executed, and the driver's requested torque is intervened to correct the driver's torque, thereby achieving coordinated control of the vehicle's drift process.

[0034] In this embodiment, step S2, the drift state, further includes drift exit: when the driver exits in an emergency or the exit condition is met, the drift state exits, terminating control of the vehicle in subsequent drift steps; the driver's emergency exit includes: the driver depresses the brake pedal, and the drift state immediately exits without waiting for other conditions. This mechanism is used to respond to emergency safety intentions, ensuring that the vehicle returns to direct driver control in a controllable state. The exit condition is that the following conditions are met simultaneously: the vehicle's center of gravity sideslip angle does not reach the drift threshold, the accelerator pedal opening is less than the calibrated threshold for a certain period of time, and the slip ratio of the vehicle's outer rear wheel is less than the calibrated threshold for a certain period of time.

[0035] To effectively correct the driver's requested torque, step S3 of this embodiment calculates the drift expectation data: Based on the vehicle's real-time state data, the drift expectation data is calculated to obtain the expected yaw rate and the expected sideslip angle. Step S3 calculates the expected reference quantities required for drift control based on the relationship between the vehicle's real-time state and theoretical values. The drift expectation includes the vehicle's attitude during drifting and various vehicle state variables. The drift expectation provides a target reference for subsequent control, thereby achieving attitude coordination and yaw stability of the vehicle during the drift initiation and maintenance process.

[0036] In this embodiment, the desired yaw rate and desired centroid sideslip angle are obtained in step S3 as follows: The desired yaw rate is determined based on the vehicle's yaw dynamic characteristics after it begins to drift. Specifically, near the moment in step S2 when the vehicle is determined to be in a drifting state, the desired vehicle state update logic is executed. The update and selection of the desired vehicle state requires the identification of the key time point of the vehicle's drift initiation. By identifying the key time point of the vehicle's drift initiation, it can be ensured that the time window for calculating the desired vehicle state covers the critical yaw transition process from the start of drifting to the complete drift. After the time window is determined, the necessary desired vehicle state is extracted and comprehensively calculated within this time window.

[0037] The desired yaw rate and real-time vehicle speed are used to calculate the desired sideslip angle based on drift equilibrium theory. After obtaining the desired yaw rate and key vehicle drift state data, such as real-time vehicle speed, the desired sideslip angle is further calculated based on drift equilibrium theory. Specifically, the drift equilibrium state can be calculated based on basic parameters such as vehicle mass and wheelbase to determine the vehicle's dynamic yaw balance during the drift maintenance phase. The drift equilibrium calculation can theoretically provide a pre-calibrated value for the desired sideslip angle, enabling intelligent drift control to adapt to vehicles with different parameters.

[0038] The desired yaw rate and desired sideslip angle are input into the dual PID loop controller, which is used to calculate the error of the yaw rate loop and the sideslip angle loop, respectively. This allows for closed-loop correction of the torque requested by the driver, thereby assisting the vehicle in completing and maintaining a stable drift.

[0039] To achieve stable assistance during vehicle drifting, step S4 of this embodiment, drift control, involves determining the drift control quantity based on the desired yaw rate, desired sideslip angle, and the vehicle's actual yaw rate and actual sideslip angle. The drift controller then coordinates and distributes this drift control quantity to multiple actuators for drift assistance. In this embodiment, step S4 uses the desired yaw rate and desired sideslip angle output by the drift expectation calculation module as reference targets, combined with the actual yaw rate and actual sideslip angle obtained from real-time vehicle status observations, to construct a dual closed-loop control structure for yaw dynamics, thereby achieving vehicle drift control.

[0040] In this embodiment, step S4, "determining the drift control torque based on the desired yaw rate, the desired center of gravity sideslip angle, and the actual yaw rate and actual center of gravity sideslip angle of the vehicle," specifically means: determining the inner yaw rate loop and the outer center of gravity sideslip angle loop based on the desired yaw rate, the desired center of gravity sideslip angle, and the actual yaw rate and actual center of gravity sideslip angle of the vehicle, thus forming an inner and outer loop control structure.

[0041] The inner loop of the yaw rate performs feedback control based on the vehicle's yaw response. The output of the inner loop is a drift control torque, which is superimposed on the driver's desired torque. When the actual yaw rate exceeds the desired yaw rate, the inner loop triggers a torque reduction strategy based on the excess yaw rate. The inner loop only reduces torque based on the driver's desired torque. The inner loop performs feedback control based on the vehicle's yaw response. The output of the inner loop is a drift control torque, which is superimposed on the driver's desired torque. When the actual yaw rate exceeds the desired yaw rate, it indicates that the vehicle is yawing too fast or the tendency to fishtail is increasing. In this case, the inner loop should trigger a torque reduction strategy based on the "excess yaw rate" to suppress yaw instability. Meanwhile, to meet safety requirements, this embodiment imposes directional constraints on the torque output of the inner loop of the yaw rate at the implementation level: the drift control algorithm will only reduce the torque based on the driver's desired torque and will not intervene to increase the torque, thereby avoiding the risk of loss of vehicle control caused by the control.

[0042] The outer loop of the center-of-gravity sideslip angle provides feedback control for the vehicle's attitude target. Based on the error between the actual and desired center-of-gravity sideslip angles, the outer loop outputs a correction for the desired yaw rate. When the actual sideslip angle deviates significantly from the desired value, the outer loop uses PID control to correct the yaw target, adjusting the target value of the yaw rate accordingly, indirectly driving the inner loop of the yaw rate to track and converge on the center-of-gravity sideslip angle. The outer loop provides feedback control for the vehicle's attitude target. Based on the error between the actual and desired center-of-gravity sideslip angles, the outer loop outputs not direct torque, but a correction for the desired yaw rate. When the actual sideslip angle deviates significantly from the desired value, the outer loop uses PID control to correct the yaw target, adjusting the target value of the yaw rate accordingly, thereby indirectly driving the inner loop of the yaw rate to track and converge on the center-of-gravity sideslip angle. This allows for the formation of a hierarchical structure during drifting, with an outer loop defining the attitude target and an inner loop defining the yaw response, thereby improving the efficiency of intelligent drift control.

[0043] Furthermore, to improve the feasibility and controllability of drift assist control, this embodiment of a vehicle intelligent drift control method based on multi-actuator coordination is not limited to a single execution channel. Instead, it can call upon and coordinate the control advantages of multiple actuators according to the actuator configuration of the entire vehicle, the vehicle dynamics characteristics, and the needs of the drift stage, thereby forming a universal drift assist control scheme for different vehicle platforms. The multi-actuator coordination, based on the rear-drive torque control requirements output by the drift controller, converts the control requirements into executable commands such as rear axle torque, front axle torque, braking, differential torque, or front wheel steering angle through actuator selection and allocation strategies. Multi-actuator coordination can more efficiently assist the vehicle in drifting. In this embodiment, step S4, "the drift controller coordinates and allocates the drift control quantity to multiple actuators for drift assistance," specifically involves converting the drift control torque quantity into executable commands such as front axle torque, rear wheel steering, braking, torque vectoring, and front wheel steering as needed, and then executing the corresponding actions on the actuators.

[0044] Front axle torque: When the algorithm detects a driver's counter-steering maneuver at a large angle, and the vehicle has entered a drift state or is at risk of drifting and instability, it will utilize front axle torque to assist in stabilizing the vehicle's attitude. This strategy is preferably used in the risk suppression phase of drift control, reducing the possibility of vehicle instability within a safety margin while maintaining the vehicle's consistent response to the driver's intentions.

[0045] Rear-wheel steering: To reduce the difficulty of initiating a drift, this invention establishes a dedicated rear-wheel steering angle calibration table or mapping relationship. This calibration table ensures that the rear-wheel steering angle maintains an opposite direction to front-wheel steering throughout the entire drift control process, making it easier for the vehicle to achieve a fishtail-like attitude response under the coupled conditions of steering geometry and lateral dynamics. By utilizing the additional lateral torque generated by rear-wheel steering, the vehicle is more likely to initiate a drift.

[0046] Braking: When the vehicle is under medium-to-high adhesion conditions and uses an open differential, this invention can activate a braking strategy to adjust the speed of the inner wheels. By controlling the braking of the inner wheels, excessive wheel speed caused by lateral load and drive / slip difference can be suppressed, thereby reducing the impact of uneven torque distribution caused by the differential on drift.

[0047] Torque vectoring: For vehicles equipped with multi-motor platforms such as three-motor or four-motor systems, this invention can utilize differential torque to enhance drift controllability and reduce the difficulty of drift control.

[0048] Front wheel steering: For vehicles with configurations that enable closed-loop control of front wheel steering angle, the drift algorithm of this invention can further invoke the front wheel steering actuator to achieve a higher degree of automated drift control. The algorithm can perform closed-loop adjustments to the front wheel steering under driver permission or confirmation, so that the vehicle achieves a more consistent drift trajectory and attitude change according to the desired yaw and center of gravity sideslip targets, thereby realizing the functional extension of "fully automatic drift" or "semi-automatic drift".

[0049] This embodiment presents a vehicle intelligent drift control method based on multi-actuator coordination. Its core control objective is to improve the stability and feasibility of the vehicle drifting process. It acquires key dynamic parameters under drifting conditions through vehicle state observation. After the driver confirms entry into drift mode, it calculates the vehicle's target attitude and yaw dynamics based on drift expectations, thereby providing safety assistance to correct the driver's requested torque, reducing the difficulty of drift control and improving the repeatability of drift effects. Specifically, this method first performs drift state observation and drift state management: it estimates state variables such as the center of gravity sideslip angle and vehicle speed using a drift condition-customized center of gravity sideslip angle and vehicle speed observer; and after entering drift mode, it uses longitudinal and lateral dual-dimensional criteria for drift initiation detection to identify whether the vehicle is in the initiation or drifting stage. Simultaneously, it continuously monitors the driver's operation and vehicle state during the drift process, exiting to the initial state after meeting preset conditions, ensuring correct timing of control intervention and a smooth and reliable exit process. Subsequently, in the drift expectation calculation module, this method latches the yaw rate characteristics during the vehicle's drift initiation process to obtain the drift expectation yaw rate; and combines the vehicle speed and drift equilibrium state theory to calculate the expected centroid sideslip angle, providing a target reference for the subsequent controller.

[0050] At the control execution level, this embodiment employs a dual PID control structure with an inner loop for yaw rate and an outer loop for sideslip angle. The inner loop for yaw rate outputs yaw adjustment control torque based on the deviation between the actual yaw rate and the desired yaw rate, and triggers torque reduction assistance when the actual yaw rate exceeds the desired yaw rate to suppress the excess. The outer loop for sideslip angle outputs a correction amount for the desired yaw rate based on the deviation between the actual sideslip angle and the desired sideslip angle, thereby achieving consistent adjustment between yaw response and sideslip attitude target. Furthermore, this method integrates the control requirements of the dual closed-loop outputs with the driver's requested torque and follows the drift safety constraint principle, only performing torque reduction assistance based on the driver's desired torque, without torque increase intervention, to avoid unexpected instability caused by control amplification. Finally, this method is constrained by safety limitations and supports multi-actuator cooperative control: considering the vehicle's four-wheel driving state, actuator capability constraints, and drift target requirements, it can selectively invoke or coordinate multiple execution channels according to different actuator configurations, including but not limited to front axle torque stabilization, rear wheel steering / reverse steering characteristics to assist drift initiation, braking to adjust the speed of the inner wheel and distribute torque more evenly, differential torque to achieve drifting on a multi-motor platform, and front wheel steering to achieve a higher degree of automated drift control. Through the above intelligent drift control framework, this method can quickly suppress attitude disturbances, correct driving trajectory, and converge vehicle attitude in key stages such as drift initiation, drift maintenance, and drift recovery, significantly improving the ease of use and safety of assisting the driver in completing drifting operations.

[0051] This embodiment addresses the challenges of unstable state acquisition during vehicle drifting, the inability of control strategies to robustly adapt to drifting conditions, and the high difficulty of drifting due to insufficient actuator coordination control. It provides an intelligent drift control method for "assisting driver drifting." This embodiment's intelligent vehicle drift control method based on multi-actuator coordination constructs a customized centroid sideslip angle and vehicle speed observer for drifting conditions to observe the vehicle's state during drifting. Based on this, it combines the driver's requested torque with a dual-closed-loop control structure composed of centroid sideslip angle and yaw rate. In conjunction with drift safety constraints and actuator constraints, it coordinates the control of multiple actuators, including rear turn, torque vector control, braking, and forward turn, thereby reducing the difficulty for ordinary drivers to complete drifts and improving the stability and feasibility of drift control.

[0052] This embodiment presents a vehicle intelligent drift control method based on multi-actuator coordination, comprising the following steps: drift state observation, drift state management, drift expectation calculation, drift controller design, drift safety constraints, and multi-actuator coordination. The method uses basic sensor signals such as IMU and wheel speed as inputs and obtains key state quantities for drift control through a vehicle state observer; then, based on drift equilibrium state calculation combined with the actual vehicle state, it obtains the drift target; finally, under a multi-state feedback inner and outer loop control framework, it fuses the driver's requested torque with the drift control correction quantity, and, combined with the vehicle's actuator configuration, calls actuators such as rear turn to assist vehicle drifting. All control quantities must meet safety constraints, ultimately achieving intelligent drift-assisted control of the vehicle.

[0053] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of the invention. All equivalent changes and modifications made in accordance with the scope of the claims of this invention should fall within the technical scope of this invention.

Claims

1. A vehicle intelligent drift control method based on multi-actuator coordination, characterized in that: Includes the following steps: S1. Drift State Data Acquisition and Processing: Acquire drift-related vehicle data and process the data to obtain key vehicle drift state data; the drift-related vehicle data includes vehicle pitch / roll / yaw attitude angles and / or attitude changes, yaw rate, wheel speeds, and basic vehicle electrical signals; the key vehicle drift state data includes center of gravity sideslip angle, vehicle speed, four-wheel slip ratio, vehicle yaw rate, and road surface adhesion coefficient; S2. Drift state judgment: When the driver manually confirms entering the drift mode, the drift stage is judged. When both the slip ratio and yaw rate are greater than the threshold, the vehicle is judged to be in a drift state, and step S3 is executed. S3. Drift expectation data calculation: Calculate the drift expectation data based on the vehicle's real-time status data to obtain the expected yaw rate and the expected center of gravity sideslip angle; S4. Drift control: The drift control quantity is determined based on the desired yaw rate, the desired center of gravity sideslip angle, and the actual yaw rate and actual center of gravity sideslip angle of the vehicle. The drift controller then coordinates and distributes the drift control quantity to multiple actuators for drift assistance.

2. The vehicle intelligent drift control method based on multi-actuator coordination according to claim 1, characterized in that: It also includes the following steps: S5. Drift Safety Limitation: During vehicle drifting, the vehicle's mechanical variables are monitored, and safety constraints are applied to speed and power-related quantities.

3. The vehicle intelligent drift control method based on multi-actuator coordination according to claim 1, characterized in that: The drift-related vehicle data in step S1 is acquired through IMU sensors and / or wheel speed sensors; the basic vehicle electrical signals include steering angle and braking / driving torque commands; the data processing includes filtering, anomaly removal, and time synchronization.

4. The vehicle intelligent drift control method based on multi-actuator coordination according to claim 1, characterized in that: In step S1, the vehicle speed is determined primarily by the front wheel speed; when calculating the center of gravity sideslip angle, a nonlinear tire model is used to establish tire lateral dynamics, and the nonlinear mapping relationship between tire lateral force and slip / side slip input is obtained. Based on the tire lateral dynamics model combined with the vehicle dynamics model, the vehicle's longitudinal speed, lateral speed, and yaw rate are incorporated into a unified estimation framework.

5. The vehicle intelligent drift control method based on multi-actuator coordination according to claim 1, characterized in that: In step S2, when the driver manually confirms entering drift mode, the vehicle deactivates or downgrades the vehicle stability control system; the vehicle stability control system includes ABS, VDC, and TCS.

6. The vehicle intelligent drift control method based on multi-actuator coordination according to claim 1, characterized in that: In step S2, "when both the slip ratio and yaw rate are greater than the threshold, determine that the vehicle is in a drift state" specifically means: When the slip ratio of the outer rear wheel is greater than the threshold, it is determined that the outer side of the vehicle has completely started to drift. When the vehicle's yaw rate is greater than the ideal neutral yaw rate, it is determined that the vehicle is fishtailing. The ideal neutral yaw rate is calculated as follows: when the vehicle is traveling around a circle or along a curvature, the ideal neutral yaw rate of the vehicle under the current operating conditions is calculated based on the vehicle's motion geometry. When the slip ratio of the outer rear wheel is greater than the threshold and the yaw rate of the vehicle is greater than the ideal neutral yaw rate, the vehicle is determined to be in a drift state.

7. The vehicle intelligent drift control method based on multi-actuator coordination according to claim 1, characterized in that: Step S2, the drift state, also includes drift exit: when the driver exits in an emergency or the exit condition is met, the drift state is exited, and the control of the vehicle by subsequent drift steps is terminated; the driver's emergency exit includes: the driver depressing the brake pedal; the exit condition is that the following conditions are met simultaneously: the vehicle's center of gravity sideslip angle does not reach the drift threshold, the accelerator pedal opening is less than the calibrated threshold for a certain period of time, and the slip ratio of the vehicle's outer rear wheel is less than the calibrated threshold for a certain period of time.

8. The vehicle intelligent drift control method based on multi-actuator coordination according to claim 1, characterized in that: The method for obtaining the desired yaw rate and desired centroid sideslip angle in step S3 is as follows: The desired yaw rate is determined based on the yaw dynamic characteristics of the vehicle after it begins to drift. The desired centroid sideslip angle is calculated based on the drift equilibrium state theory using the desired yaw rate and key vehicle drift state data. The desired yaw rate and desired sideslip angle are input into the dual PID loop controller, which is used to calculate the error of the yaw rate loop and the sideslip angle loop, respectively, thereby performing closed-loop correction of the torque requested by the driver.

9. The vehicle intelligent drift control method based on multi-actuator coordination according to claim 1, characterized in that: In step S4, "determining the drift control torque based on the desired yaw rate, desired center of gravity sideslip angle, and the vehicle's actual yaw rate and actual center of gravity sideslip angle" specifically means: determining the inner loop of the yaw rate and the outer loop of the center of gravity sideslip angle based on the desired yaw rate, desired center of gravity sideslip angle, and the vehicle's actual yaw rate and actual center of gravity sideslip angle, forming an inner and outer loop control structure. The yaw rate inner loop performs feedback control based on the vehicle's yaw response; the output of the yaw rate inner loop is the drift control torque, which is superimposed on the driver's desired torque. When the actual yaw rate is greater than the desired yaw rate, the yaw rate inner loop triggers a torque reduction strategy based on the excess yaw rate; the yaw rate inner loop only performs reduction control based on the driver's desired torque. The outer loop of the center of gravity sideslip angle provides feedback control for the vehicle's attitude target. The outer loop of the center of gravity sideslip angle provides feedback control based on the error between the actual center of gravity sideslip angle and the desired center of gravity sideslip angle. The outer loop of the center of gravity sideslip angle outputs the correction amount for the desired yaw rate. When the actual center of gravity sideslip angle deviates significantly from the desired value, the outer loop of the center of gravity sideslip angle forms a yaw target correction through PID adjustment, thereby adjusting the target value of the yaw rate and indirectly driving the inner loop of the yaw rate to achieve tracking and convergence of the center of gravity sideslip angle.

10. The vehicle intelligent drift control method based on multi-actuator coordination according to claim 1, characterized in that: In step S4, "the drift controller coordinates and distributes the drift control quantity to multiple actuators for drift assistance" specifically means: converting the drift control torque quantity into executable commands for front axle torque, rear wheel steering, braking, torque vectoring, and front wheel steering as needed, and then executing the corresponding actions on the actuators. Front axle torque: When the driver is detected to be counter-steering at a large angle and the vehicle has entered a fishtailing state or is at risk of fishtailing and instability, the front axle torque is activated to help stabilize the vehicle's attitude. Rear wheel steering: Establish a dedicated rear wheel steering angle calibration table or mapping relationship; the calibration table ensures that the rear wheel steering angle maintains an opposite direction to the front wheel steering throughout the entire drift control process; Braking: When the vehicle is under medium to high adhesion conditions and uses an open differential structure, the braking strategy is activated to adjust the speed of the inner wheel of the vehicle. Torque vectoring: The differential torque of the multi-motor platform is used to control the drift attitude; Front wheel steering: Invokes the front wheel steering actuator to achieve drift control, and performs closed-loop adjustment of the front wheel steering under the condition of driver permission or confirmation.

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