Dynamic road feeling simulation algorithm for vehicle speed adhesion coefficient coupling and control method

Abstract

The invention relates to the technical field of vehicle control systems, and discloses a vehicle speed adhesion coefficient coupled dynamic road feeling simulation algorithm and a control method, and the method comprises the steps: obtaining vehicle real-time data; converting the acquired data into road adhesion coefficient data of a dynamic road feeling simulation algorithm coupled with an input vehicle speed adhesion coefficient; calculating a main torque based on the processed vehicle speed and road adhesion coefficient data; vehicle dynamic parameters are monitored in real time, whether the vehicle is in a complex working condition is judged according to the vehicle state, and compensation torque is calculated according to a preset compensation strategy under the complex working condition; and the main torque and the compensation torque are fused to generate a final dynamic road feeling modulus moment quasi-torque. The steering torque can be dynamically adjusted according to the adhesion coefficient estimated in real time and the vehicle speed, the torque compensation parameters are adjusted according to different driving working conditions, the problem of road feeling distortion caused by dynamic changes of the vehicle speed and the adhesion coefficient is solved, the controllability and safety requirements of the vehicle under different driving working conditions are met, and the driving experience is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle control systems, and in particular to a dynamic road feel simulation algorithm and a control method coupled with vehicle speed and adhesion coefficient. Background Art

[0002] With the rapid development of intelligent driving technology, steer-by-wire (SbW) systems, due to their highly electronic and decoupled nature, have gradually become the core actuating unit of smart cars. Unlike traditional mechanical steering systems, SbW systems transmit steering commands via electrical signals, eliminating the physical connection between the steering wheel and the wheels. This provides the hardware foundation for features such as variable steering ratios and autonomous driving mode switching. However, this transformation also presents significant technical challenges: the driver cannot directly perceive road conditions through mechanical feedback, disrupting the closed-loop interaction between driver, vehicle, and road that traditional driving relies on.

[0003] In this context, road feel simulation technology has become a key functional module of the steer-by-wire system. Its core goal is to dynamically reproduce the changing characteristics of the tire-road interaction force (such as adhesion coefficient, lateral force fluctuations, etc.) through motor torque feedback, providing the driver with a realistic steering wheel force feel. Existing research is mostly based on static or quasi-static models (such as linear feedback control under the assumption of a constant friction coefficient), generating road feel feedback through preset parameters (such as steering stiffness and damping coefficient). However, such methods have significant limitations:

[0004] 1. Inadequate environmental adaptability: In actual driving, the road adhesion coefficient changes dynamically with weather, tire wear, and road conditions (such as dry, wet, icy, and snowy). Traditional algorithms have fixed parameters and are unable to adapt to the needs of multiple scenarios in real time.

[0005] 2. Lack of vehicle speed coupling effect: Vehicle speed changes significantly affect tire cornering characteristics and driver force preference. Existing methods often ignore the coupling relationship between vehicle speed and adhesion coefficient, resulting in feedback force distortion under high-speed, low-adhesion road conditions.

[0006] 3. Dynamic interaction hysteresis: Under complex operating conditions (such as emergency obstacle avoidance and continuous curves), the road excitation frequency and driver operation have strong time-varying characteristics, and static models cannot achieve dynamic compensation of high-frequency responses.

[0007] In recent years, attempts have been made to address these issues by introducing adaptive control methods (such as fuzzy PID and model reference adaptation) and machine learning. However, limited by model complexity, real-time requirements, and hardware costs, a solution that balances robustness and engineering feasibility has yet to be achieved. Therefore, developing a dynamic road feel simulation algorithm based on the speed-adhesion coefficient coupling effect and constructing a coordinated control system has become an important research direction for improving steer-by-wire performance and ensuring the driving safety of intelligent vehicles. Summary of the Invention

[0008] To overcome the deficiencies of the above-mentioned prior art, the present invention provides a multi-parameter fusion algorithm that collects data information in real time through multiple sensors and can dynamically adjust relevant parameters based on changes in the vehicle under different driving conditions, thereby adapting to complex and changing driving scenarios, effectively improving the accuracy and real-time nature of road feel feedback, and thereby improving the maneuverability and safety of the wire-controlled steer system, and realizing a dynamic road feel simulation algorithm and control method coupled with vehicle speed and adhesion coefficient to achieve real-time reflection of changes in vehicle road feel under different conditions.

[0009] The technical solution adopted by the present invention is: a dynamic road feel simulation algorithm coupled with vehicle speed and adhesion coefficient, comprising the following steps:

[0010] S100. Obtain the vehicle's real-time longitudinal velocity, longitudinal acceleration, lateral acceleration and yaw rate, steering wheel angle, and torque data;

[0011] S200. Using a vehicle-road adhesion coefficient estimation method based on data fusion, the acquired data is converted into road adhesion coefficient data for input into a dynamic road feel simulation algorithm coupled with a vehicle speed adhesion coefficient;

[0012] S300. Based on the processed vehicle speed and road adhesion coefficient data, the nonlinear function of the assist torque is adjusted according to the set vehicle speed and road adhesion coefficient threshold value on the real-time working condition to obtain the segmented assist torque, and the segmented assist torque of the sinusoidal curve is used to calculate the main torque;

[0013] S400 real-time monitoring of vehicle dynamic parameters, based on the vehicle state to determine whether it is in a complex working condition, in complex working conditions, according to the preset compensation strategy to calculate the compensation torque;

[0014] S500: Fusing the main torque and the compensation torque to generate a final dynamic road feel simulated torque.

[0015] In this technical solution, in step S300, the main moment T assist The calculation formula is:

[0016]

[0017] in:

[0018]

[0019] Where: T SW_start is the minimum steering wheel torque when power assist starts; G(v) is the nonlinear function of power assist torque with respect to real-time working conditions; g(T SW ) is the nonlinear function of the assist torque with respect to the steering wheel torque, T SW_max is the steering wheel force when the assist torque reaches the limit value, T assist_maxis the assist torque limit value; a is the assist characteristic parameter, F V is the road feeling factor related to vehicle speed and road adhesion coefficient, F V0 is the road feel factor reference value, v max The maximum speed at which the power assist takes effect, μ min is the minimum road adhesion coefficient for power assistance to take effect, and c and b are the power assistance characteristic parameters that jointly determine the power assistance torque limit value.

[0020] In this technical solution, when calculating the compensation torque in step S400, the damping compensation torque T is calculated according to the real-time vehicle speed and the road adhesion coefficient. damp , friction compensation torque T friction Make appropriate compensation and inertia compensation torque T inertia The calculation formula for the compensation of the soft stop limit compensation torque is:

[0021]

[0022] Where: K inertia is the compensation coefficient, K damp is the damping compensation coefficient; v damp is the speed threshold for damping compensation; μ damp The road adhesion coefficient threshold for damping compensation; is the steering wheel angle, T friction0 is the Coulomb moment, c friction is the slope coefficient; T friction0 is the Coulomb moment, c friction is the slope coefficient;

[0023] According to the above calculation, it can be seen that the dynamic road feel simulated torque T in step S500 is: T = T assist +T inertia +T damp +T friction +T limit (9).

[0024] In this technical solution, the longitudinal acceleration, lateral acceleration, yaw angular velocity and steering angle are collected through a high-precision IMU, a differential positioning system RTK and a steering wheel angle torque meter; and a speed-adhesion coefficient coupling model is established based on the collected vehicle speed data information and adhesion coefficient information and road adhesion coefficient data. The established speed-adhesion coefficient coupling model is used to calculate the basic steering torque that matches the current driving state.

[0025] A control method for dynamic road feel simulation based on vehicle speed and adhesion coefficient coupling transmits the dynamic road feel simulation torque T signal calculated by the above calculation method to the vehicle's electronic control unit. The electronic control unit adjusts the steering torque of the steering system and the braking force of the braking system in real time based on the signal to achieve accurate dynamic road feel simulation.

[0026] In this technical solution, in the wire-controlled steering system, the dynamic road feel simulation torque T signal is converted into a driving current or voltage signal of the motor, and the motor is controlled to generate corresponding steering assist or resistance.

[0027] In this technical solution, during vehicle driving, the actual response of the wire-controlled steering system is monitored in real time. Through the feedback control system, the actual response is compared with the target torque, and the control signal is adjusted and optimized in real time based on the error signal to ensure that the vehicle's road feel simulation effect meets expectations.

[0028] In this technical solution, the wire-controlled steer system includes a vehicle speed sensor, a steering controller, a high-precision IMU, a differential positioning system RTK, a steering wheel angle torque meter, an electric power steering motor and a brake pressure regulation module.

[0029] A control system based on dynamic road feel simulation coupled with vehicle speed and adhesion coefficient, the control system comprising:

[0030] A dynamic road feel simulator, the dynamic road feel simulator being used to collect data from external sensors according to the above-mentioned calculation method, and to calculate a dynamic road feel simulation torque T, and further being used to transmit the calculated dynamic road feel simulation torque T data to the steering system and the braking system of the actuator for execution; and

[0031] External sensors include a vehicle speed sensor for acquiring real-time vehicle longitudinal velocity, longitudinal acceleration, lateral acceleration and yaw angular velocity, steering wheel angle, and torque data; and an adhesion system detection module for converting the acquired data into road adhesion coefficient data for input into a dynamic road feel simulation algorithm coupled with vehicle speed adhesion coefficient using a vehicle road adhesion coefficient estimation method based on data fusion.

[0032] In this technical solution, the dynamic road feel simulator further includes a main torque calculation module and a compensation torque calculation module.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] The vehicle speed and adhesion coefficient coupled dynamic road feel simulation algorithm and control method and system of the present invention,

[0035] 1. Dynamically adjusts steering torque based on real-time estimated adhesion coefficient and vehicle speed, and adjusts torque compensation parameters according to different driving conditions to ensure accurate and comfortable road feel feedback, reduce the probability of danger caused by sudden changes in the driving environment, and further ensure driver safety.

[0036] 2. In the wire-controlled steering system, the integrated torque signal is converted into a driving current or voltage signal for the motor, controlling the motor to generate corresponding steering assist or resistance.

[0037] 3. During vehicle operation, the system monitors the actual response of the steer-by-wire system in real time, including the steering motor's current and speed, and the brake pressure sensor's signal. Through a feedback control system, the actual response is compared with the target torque, and the control signal is adjusted and optimized in real time based on the error signal. This ensures that the vehicle's road feel simulation meets the intended design and improves system stability and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a flow chart of a dynamic road feel simulation algorithm coupled with vehicle speed and adhesion coefficient;

[0039] Figure 2 It is a control method for dynamic road feel simulation based on the coupling of vehicle speed and adhesion coefficient;

[0040] Figure 3 This is the principle diagram of the control system for dynamic road feel simulation based on vehicle speed and adhesion coefficient coupling;

[0041] Among them: 100-dynamic road feel simulator, 110-main torque calculation module, 120-compensation torque calculation module; 200-actuator, 210-steering system, 220-braking system; 300-external sensor, 310-vehicle speed sensor, 320-adhesion system detection module. DETAILED DESCRIPTION

[0042] In order to deepen the understanding of the present invention, the present invention is further described below with reference to the accompanying drawings and examples. The examples are only used to explain the present invention and do not limit the scope of protection of the present invention.

[0043] like Figure 1 As shown, a dynamic road feel simulation algorithm coupled with vehicle speed and adhesion coefficient includes the following steps:

[0044] S100. Real-time vehicle speed information is collected via a vehicle speed sensor: the vehicle's real-time longitudinal speed, longitudinal acceleration, lateral acceleration, yaw rate, steering wheel angle, and torque are obtained. In specific implementations, real-time vehicle speed information is collected via a vehicle speed sensor. This speed sensor, mounted on the vehicle's drive shaft or wheel, accurately measures the vehicle's longitudinal speed and converts the speed signal into an electrical or digital signal. This signal is then filtered and preprocessed to remove abnormal data for use by subsequent processing modules. A high-precision IMU collects inertial information, including real-time longitudinal acceleration changes, lateral acceleration, and yaw rate. A differential positioning system provides high-precision vehicle position information and accurately calculates the vehicle's longitudinal and lateral accelerations. A steering wheel angle and torque meter provides steering wheel operation data, including angle and torque. This comprehensive data collection provides the necessary input information for subsequent road adhesion coefficient identification, converting this data into electrical or digital signals for reception and processing by a receiver.

[0045] S200. A vehicle-road adhesion coefficient estimation method based on data fusion is used to convert the acquired data into road adhesion coefficient data for a dynamic road feel simulation algorithm coupled with the input vehicle speed adhesion coefficient. During this step, the vehicle dynamic response is combined with the Dugoff tire model formula. Based on the maximum a posteriori estimation (MAP) principle and observation information, the statistical characteristics of the measurement noise are estimated online and embedded into the volumetric Kalman to construct an adaptive volumetric Kalman NACKF road adhesion coefficient estimator, thereby obtaining a high-precision real-time vehicle-road adhesion coefficient.

[0046] S300. Design the main torque: Based on the processed vehicle speed and road adhesion coefficient data, adjust the nonlinear function of the assist torque with respect to the real-time working condition according to the set vehicle speed and road adhesion coefficient thresholds to obtain the segmented assist torque, and use the segmented assist torque of the sinusoidal curve to calculate the main torque;

[0047] S400 real-time monitoring of vehicle dynamic parameters, based on the vehicle state to determine whether it is in a complex working condition, in complex working conditions, according to the preset compensation strategy to calculate the compensation torque;

[0048] S500. The main torque and the compensation torque are integrated to generate the final dynamic road feel simulated torque. This algorithm uses vehicle speed and road adhesion coefficient as input variables and steering torque as output variable. It is obtained by fitting a large amount of experimental data and can reflect the reasonable steering torque required by the driver under different working conditions.

[0049] In at least one embodiment, in step S300, the main moment T assist The calculation formula is:

[0050]

[0051] in:

[0052]

[0053] Where: T SW_start is the minimum steering wheel torque when power assist starts; G(v) is the nonlinear function of power assist torque with respect to real-time working conditions; g(T SW ) is the nonlinear function of the assist torque with respect to the steering wheel torque, T SW_max is the steering wheel force when the assist torque reaches the limit value, T assist_max is the assist torque limit value; a is the assist characteristic parameter, F V is the road feeling factor related to vehicle speed and road adhesion coefficient, F V0 is the road feel factor reference value, v max The maximum speed at which the power assist takes effect, μ min is the minimum road adhesion coefficient for the power assist to take effect, c and b are the power assist characteristic parameters that jointly determine the power assist torque limit value. min The maximum speed at which the power assist is effective is v max As a threshold, it can adjust the road feel factor in real time. By affecting the size of the assist torque at high speeds and low road adhesion, it can influence the main torque, allowing the driver to feel better controllability in different driving conditions and obtain a safer driving experience.

[0054] In at least one embodiment, when calculating the compensation torque in step S400, the damping compensation torque T is calculated based on the real-time vehicle speed and the road adhesion coefficient. damp , friction compensation torque T friction Make appropriate compensation and inertia compensation torque T inertia And the soft stop limit compensation torque compensation, thereby further improving the road feel of the wire-controlled steering system and improving driving controllability and stability.

[0055] Inertia compensation: It is mainly used to reduce the driver's sense of frustration when turning the steering wheel back and forth quickly or starting or stopping the steering suddenly. This sense of frustration is caused by the inertia of the steering system, which makes the driver feel that the steering is lagging. The inertia compensation torque T inertia The calculation formula is as follows:

[0056]

[0057] Friction compensation: When driving at high speeds and on low-adhesion roads, the damping compensation torque should be relatively large, making the steering feel slightly heavier to ensure driving safety, and also improving the self-centering performance at high speeds and low road adhesion coefficients.

[0058] Friction compensation isn't about completely eliminating the effects of steering system friction; rather, it's about achieving the most appropriate friction compensation torque. If the steering system is frictionless, even the slightest disturbance at high speeds or on low-adhesion surfaces can cause the steering wheel to swerve. Excessive steering friction can lead to heavy steering and increased steering effort. Therefore, setting the appropriate friction compensation torque is crucial. The formula for this is as follows:

[0059]

[0060] The soft stop limit compensation torque is calculated as follows:

[0061]

[0062] Where: K inertia is the compensation coefficient, which can be obtained through actual bench test calibration. damp is the damping compensation coefficient; v damp is the speed threshold for damping compensation; μ damp The road adhesion coefficient threshold for damping compensation; is the steering wheel angle, T friction0 is the Coulomb torque, which can be understood as the maximum value of sliding friction. In order to reduce the steering sensitivity at high speed and low road adhesion coefficient, it can be set to increase with increasing vehicle speed and increase with decreasing road adhesion coefficient; c friction is the slope coefficient, which is mainly used to adjust the speed of positive and negative changes in friction torque;

[0063] According to the above calculation, it can be seen that the dynamic road feeling analog torque T in step S500 is a comprehensive torque generated by fusing the main torque and the compensation torque. The calculation formula of the dynamic road feeling analog torque T is: T = T assist +T inertia +T damp +T friction +T limit (9).

[0064] In at least one embodiment, the longitudinal acceleration, lateral acceleration, yaw angular velocity and steering angle are collected through a high-precision IMU, a differential positioning system RTK and a steering wheel angle torque meter; and a vehicle speed-adhesion coefficient coupling model is established based on the collected vehicle speed data information and adhesion coefficient information and road adhesion coefficient data. The established vehicle speed-adhesion coefficient coupling model is used to calculate the basic steering torque that matches the current driving state.

[0065] like Figure 2As shown, a control method for dynamic road feel simulation based on vehicle speed and adhesion coefficient coupling first executes steps S100 to S500, and transmits the dynamic road feel simulation torque T signal calculated by the above calculation method to the vehicle's electronic control unit. The electronic control unit adjusts the steering torque of the steering system and the braking force of the braking system in real time based on the signal to achieve accurate dynamic road feel simulation. The comprehensive torque signal of the dynamic road feel simulation torque is converted into a steering motor drive signal and a brake pressure adjustment signal to control the electric power steering motor and achieve accurate steering torque adjustment. During the signal output process, the motor current and speed feedback signals are collected in real time and compared with the target torque. The output signal is dynamically adjusted through the PID control algorithm to ensure that the actual torque is consistent with the target torque, thereby improving system stability and reliability.

[0066] In at least one embodiment, steps S100 to S500 are first executed, and then S600 is executed to convert the dynamic road feel simulation torque T signal into a driving current or voltage signal of the motor in the wire-controlled steering system to control the motor to generate corresponding steering assist or resistance.

[0067] In at least one embodiment, steps S100 to S500 are first executed, and then S700 is executed. During vehicle driving, the actual response of the steer-by-wire system is monitored in real time. The actual response is compared with the target torque through a feedback control system, and the control signal is adjusted and optimized in real time according to the error signal to ensure that the road feel simulation effect of the vehicle meets expectations.

[0068] In at least one embodiment, the steer-by-wire system includes a vehicle speed sensor, a steering controller, a high-precision IMU, a differential positioning system (RTK), a steering wheel angle torque meter, an electric power steering motor, and a brake pressure regulation module. The vehicle speed sensor is mounted on the vehicle's drive shaft or wheel and can accurately measure the vehicle's longitudinal velocity. The high-precision IMU integrates a three-axis accelerometer and a three-axis gyroscope, with a measurement accuracy better than 0.05%, and can output the vehicle's longitudinal acceleration, lateral acceleration, and yaw rate in real time. The differential positioning system (RTK), based on satellite positioning and differential correction technology, achieves centimeter-level positioning accuracy, enabling precise calculation of vehicle trajectory and speed changes. The steering wheel angle torque meter is mounted between the steering wheel and steering column and can measure steering wheel angle and torque with an accuracy of ±0.1° and ±0.1Nm. The steering controller is a high-performance embedded controller capable of real-time signal processing and control algorithm execution. The electric power steering motor generates steering force or resistance based on controller instructions.

[0069] like Figure 3 As shown, a control system based on dynamic road feel simulation coupled with vehicle speed and adhesion coefficient includes:

[0070] A dynamic road feel simulator 100, which is configured to collect data from an external sensor 300 according to the aforementioned calculation method and calculate a dynamic road feel simulation torque T. The dynamic road feel simulation torque T is then transmitted to a steering system 210 and a braking system 220 of an actuator 200 for execution. The signal is processed by the ECU and then transmitted to the steering and braking systems, enabling real-time adjustment of the vehicle's steering torque and brake pedal force based on vehicle speed and adhesion coefficient, thereby achieving accurate dynamic road feel simulation; and

[0071] External sensors 300 include a vehicle speed sensor 310 for acquiring real-time vehicle longitudinal velocity, longitudinal acceleration, lateral acceleration and yaw rate, steering wheel angle, and torque data, and an adhesion system detection module 320 for converting the acquired data into road adhesion coefficient data for input into a dynamic road feel simulation algorithm coupled with vehicle speed adhesion coefficient using a vehicle road adhesion coefficient estimation method based on data fusion.

[0072] In at least one embodiment, the dynamic road feel simulator 100 further includes a main torque calculation module 110 and a compensation torque calculation module 120, which are respectively used to calculate the main torque and the compensation torque and to integrate the main torque calculation module and the compensation torque calculation module to form a precise dynamic road feel simulation and control, thereby solving the road feel distortion problem caused by dynamic changes in vehicle speed and adhesion coefficient, meeting the vehicle's controllability and safety requirements under different driving conditions, and improving the driving experience.

[0073] The embodiments disclosed in the present invention are preferred embodiments, but are not limited to them. Ordinary technicians in this field can easily understand the spirit of the present invention based on the above embodiments and make different extensions and changes. As long as they do not deviate from the spirit of the present invention, they are all within the scope of protection of the present invention.

Claims

1. A dynamic road feel simulation algorithm coupled with vehicle speed and adhesion coefficient, characterized in that: The following steps are involved: S100. Obtain the vehicle's real-time longitudinal velocity, longitudinal acceleration, lateral acceleration and yaw rate, steering wheel angle, and torque data; S200. Using a vehicle-road adhesion coefficient estimation method based on data fusion, the acquired data is converted into road adhesion coefficient data for input into a dynamic road feel simulation algorithm coupled with a vehicle speed adhesion coefficient; S300. Based on the processed vehicle speed and road adhesion coefficient data, the nonlinear function of the assist torque is adjusted according to the set vehicle speed and road adhesion coefficient threshold value on the real-time working condition to obtain the segmented assist torque, and the segmented assist torque of the sinusoidal curve is used to calculate the main torque; S400 real-time monitoring of vehicle dynamic parameters, based on the vehicle state to determine whether it is in a complex working condition, in complex working conditions, according to the preset compensation strategy to calculate the compensation torque; S500: Fusing the main torque and the compensation torque to generate a final dynamic road feel simulated torque.

2. The dynamic road feel simulation algorithm coupled with vehicle speed and adhesion coefficient according to claim 1, characterized in that: In step S300, the main moment T assist The calculation formula is: in: Where: T SW_start is the minimum steering wheel torque when power assist starts; G(v) is the nonlinear function of power assist torque with respect to real-time working conditions; g(T SW ) is the nonlinear function of the assist torque with respect to the steering wheel torque, T SW_max is the steering wheel force when the assist torque reaches the limit value, T assist_max is the assist torque limit value; a is the assist characteristic parameter, F V is the road feeling factor related to vehicle speed and road adhesion coefficient, F V0 is the road feel factor reference value, v max The maximum speed at which the power assist takes effect, μ min is the minimum road adhesion coefficient for power assistance to take effect, c and b are the power assistance characteristic parameters that jointly determine the power assistance torque limit value.

3. The dynamic road feel simulation algorithm coupled with vehicle speed and adhesion coefficient according to claim 2, characterized in that: When calculating the compensation torque in step S400, the damping compensation torque T is calculated based on the real-time vehicle speed and the road adhesion coefficient. damp , friction compensation torque T friction Make appropriate compensation and inertia compensation torque T inertia The calculation formula for the compensation of the soft stop limit compensation torque is: Where: K inertia is the compensation coefficient, K damp is the damping compensation coefficient; v damp is the speed threshold for damping compensation; μ damp The road adhesion coefficient threshold for damping compensation; is the steering wheel angle, T friction0 is the Coulomb moment, c friction is the slope coefficient; T friction0 is the Coulomb moment, c friction is the slope coefficient; In step S500, the dynamic road feel simulated torque T is: T=T assist +T inertia +T damp +T friction +T limit (9)。 4. The dynamic road feel simulation algorithm coupled with vehicle speed and adhesion coefficient according to claim 3, characterized in that: The longitudinal acceleration, lateral acceleration, yaw angular velocity and steering angle are collected through the high-precision IMU, differential positioning system RTK and steering wheel angle torque meter; and a speed-adhesion coefficient coupling model is established based on the collected vehicle speed data information and adhesion coefficient information and road adhesion coefficient data. The established vehicle speed-adhesion coefficient coupling model is used to calculate the basic steering torque that matches the current driving state.

5. A control method for dynamic road feel simulation based on vehicle speed and adhesion coefficient coupling, characterized by: The dynamic road feel simulation torque T signal calculated by any one of claims 1-4 is transmitted to the vehicle's electronic control unit, and the electronic control unit adjusts the steering torque of the steering system and the braking force of the braking system in real time according to the signal to achieve accurate dynamic road feel simulation.

6. The control method for dynamic road feel simulation based on vehicle speed and adhesion coefficient coupling according to claim 5, characterized in that: In the steer-by-wire system, the dynamic road feel analog torque T signal is converted into a driving current or voltage signal for the motor, controlling the motor to generate corresponding steering assist or resistance.

7. The control method for dynamic road feel simulation based on vehicle speed and adhesion coefficient coupling according to claim 5, characterized in that: During vehicle driving, the actual response of the steer-by-wire system is monitored in real time. Through the feedback control system, the actual response is compared with the target torque, and the control signal is adjusted and optimized in real time based on the error signal to ensure that the vehicle's road feel simulation effect meets expectations.

8. The control method for dynamic road feel simulation based on vehicle speed-adhesion coefficient coupling according to claim 6 or 7, characterized in that: The steer-by-wire system includes a vehicle speed sensor, a steering controller, a high-precision IMU, a differential positioning system RTK, a steering wheel angle torque meter, an electric power steering motor, and a brake pressure regulation module.

9. A control system based on dynamic road feel simulation coupled with vehicle speed and adhesion coefficient, characterized in that: The control system includes: a dynamic road feel simulator, the dynamic road feel simulator being configured to collect data from external sensors according to the calculation method of any one of claims 1 to 4, and to calculate a dynamic road feel simulation torque T, and further configured to transmit the calculated dynamic road feel simulation torque T data to a steering system and a braking system of an actuator for execution; and External sensors include a vehicle speed sensor for acquiring real-time vehicle longitudinal velocity, longitudinal acceleration, lateral acceleration and yaw angular velocity, steering wheel angle, and torque data; and an adhesion system detection module for converting the acquired data into road adhesion coefficient data for input into a dynamic road feel simulation algorithm coupled with vehicle speed adhesion coefficient using a vehicle road adhesion coefficient estimation method based on data fusion.

10. The control system for dynamic road feel simulation based on vehicle speed and adhesion coefficient coupling according to claim 9, characterized in that: The dynamic road feel simulator also includes a main torque calculation module and a compensation torque calculation module, which are respectively used to calculate the main torque and the compensation torque and integrate the main torque calculation module and the compensation torque calculation module to form accurate dynamic road feel simulation and control.

Images