Steer-by-wire system road feeling simulation main torque control method

Abstract

The invention provides a steering-by-wire system road feeling simulation main torque control method, and relates to the technical field of vehicle steering-by-wire. The method comprises the following steps: constructing a steering model by collecting relevant parameters of a steer-by-wire system; constructing a sliding-mode observer according to the steering model to estimate the main force of road feeling simulation; deducing stability conditions of observation gain according to the sliding-mode observer in combination with the Lyapunov theory; a magic tire model is introduced to calculate tire lateral force, and observation gain is corrected in a self-adaptive mode; and outputting a final road feeling simulation main torque based on the estimated value of the sliding-mode observer and the observation gain corrected by the magic tire model. According to the method, the dependence on steering model parameters can be reduced, the observation gain of the sliding-mode observer is corrected in real time, the perception accuracy of a driver on the road surface state is enhanced, and the full-scene use requirement of the steer-by-wire system is met.

Description

Technical Field

[0001] This invention relates to the field of vehicle steer-by-wire technology, and more specifically, to a method for controlling the main torque of a steer-by-wire system by simulating road feel. Background Technology

[0002] The steer-by-wire system breaks down the steering function into a steering wheel assembly subsystem and a steering actuator assembly subsystem, using electrical signals to transmit steering commands. This breaks the limitations of traditional mechanical connections and lays the foundation for vehicle handling flexibility and intelligent integration. However, the mechanical decoupling of the steer-by-wire system also brings new technical challenges: the driver cannot obtain physical feedback from the road surface through the steering wheel, resulting in a lack of driving perception. This not only weakens the driver's confidence but may also increase driving safety risks due to delayed reactions to sudden road conditions.

[0003] To solve the above problems, the existing technology mainly has two types of technical solutions: (1) By collecting parameters such as the output current and angle of the actuator motor, and designing an observer in combination with the preset steering system model, the road feel torque is calculated in reverse. However, the steering actuator assembly needs to pass through multiple mechanical parts such as the reducer and steering tie rod from the motor to the wheel end. There are unavoidable mechanical resistances (such as gear meshing resistance and rod friction resistance) inside the system. These resistances will be mistakenly included in the road feel torque by the observer, resulting in the final output road feel torque value being greater than the actual road feedback value, causing the road feel simulation to be "overweight" and deviating significantly from the real driving experience. (2) Using the sensors configured in the vehicle to collect vehicle state parameters such as longitudinal speed and lateral acceleration, and substituting them into the tire model (such as the Magic Formula tire model) to calculate the force of the road surface on the wheel, and then converting it into the road feel torque. However, the accuracy of the tire model is highly dependent on the longitudinal speed of the vehicle. Under low-speed conditions, the friction characteristics and rolling resistance of the tire and the ground are complex, and the fitting accuracy of the tire model drops significantly, directly leading to a significant increase in the estimation error of the road feel torque, which cannot provide the driver with stable and accurate road perception feedback.

[0004] In view of the above, this application is hereby submitted. Summary of the Invention

[0005] The present invention aims to provide a method for simulating the main torque of road feel in a steer-by-wire system, in order to solve the problem that existing methods are difficult to accurately simulate the main torque of road feel under all working conditions, and cannot meet the dual requirements of steer-by-wire systems for driving safety and experience.

[0006] To solve the above-mentioned technical problems, the present invention is achieved through the following technical solution: A method for controlling the main torque of a steer-by-wire system based on road feel simulation includes: Collect relevant parameters of the steer-by-wire system and construct a steering model; A sliding mode observer is constructed based on the steering model to estimate the main force of road feel simulation; Based on the sliding mode observer and Lyapunov theory, the stability condition of the observation gain is derived. A magic tire model is introduced to calculate tire lateral force, and the observation gain is adaptively corrected. The final road feel simulation torque is output based on the estimated value from the sliding mode observer and the observation gain corrected by the magic tire model.

[0007] Preferably, the relevant parameters of the steer-by-wire system include the mass of the steering nut, the damping coefficient, the steering resistance, and the angle and torque of the actuation motor.

[0008] Preferably, the formula for the steering model is: ; ; ; ; ; in, The rotational speed of the actuating motor; This refers to the angular acceleration of the actuating motor; The rotation angle of the actuating motor; The torque transmitted from the actuating motor to the steering gear; For steering resistance torque; The pitch circle radius of the gear sector; For the mass of the steering nut; The reduction ratio of the reducer; The equivalent damping coefficient of the steering nut; For screw lead; The correlation coefficient for the quality of the steering nut; The correlation coefficient is the equivalent damping coefficient of the steering nut; The correlation coefficient between screw lead and reduction ratio; This refers to the force related to steering resistance.

[0009] Preferably, the expression for the sliding mode observer is: ; in, This is an estimated value of the angular acceleration of the actuating motor; This is the estimated speed of the actuating motor; This is the estimated value of the steering disturbance, which is the main force in road feel simulation; The correlation coefficient for the quality of the steering nut; The correlation coefficient is the equivalent damping coefficient of the steering nut; The correlation coefficient between screw lead and reduction ratio; The torque transmitted from the actuating motor to the steering gear; The main force of road feel simulation The expression is: ; in, For observation gain; This is a switching function, i.e., a sign function; This refers to the rotational speed of the actuating motor.

[0010] Preferably, based on the sliding mode observer and combined with Lyapunov theory, the stability condition of the observation gain is derived as follows: First, construct the observation error equation: ; in, This represents the estimation error of the angular acceleration of the actuating motor. This represents the estimation error of the actuator motor speed; It serves as the main force for road feel simulation; Forces related to steering resistance; The correlation coefficient for the quality of the steering nut; The correlation coefficient is the equivalent damping coefficient of the steering nut; Define the sliding surface of the sliding mode observer to describe the deviation between the system state and the desired state, and its formula is: ; in, The sliding surface of the sliding mode observer; , These are the rotational speed and estimated rotational speed of the actuating motor, respectively. Design the Lyapunov function, its formula is: ; in, is a Lyapunov function used to analyze the stability of the sliding mode observer; For sliding surface The first derivative; According to Lyapunov theory, when the system is asymptotically stable, it satisfies... When the observation gain satisfies the condition: ; in, For observation gain.

[0011] Preferably, a magic tire model is introduced to calculate the tire lateral force as a reference value for the observation gain, and the expression for the tire lateral force is: ; in, This refers to the lateral force of the tire; C, D, and E are model parameters and fitting coefficients related to the vertical load; This is the tire slip angle, collected by a sensor.

[0012] Preferably, the adaptive correction of the observation gain is specifically as follows: Utilizing the lateral force of the tire As the reference value for the main observation device of the wheel-end road surface, and used as a correction term for the observation gain, the expression is: ; ; in, For observation gain Correction terms; This is the adjustment coefficient; To simulate the main torque for road feel; The pitch circle radius of the gear sector; , These are the speed of the actuating motor and the estimated speed, respectively.

[0013] The present invention also provides a road feel simulation torque control device for a steer-by-wire system, comprising: The steering model building module is used to collect relevant parameters of the steer-by-wire system and build a steering model; A sliding mode observer construction module is used to construct a sliding mode observer based on the steering model to estimate the road feel simulation force. The observation gain derivation module is used to derive the stability condition of the observation gain based on the sliding mode observer and Lyapunov theory. The correction module is used to introduce the magic tire model to calculate the tire lateral force and adaptively correct the observation gain; The output module is used to output the final road feel simulation torque based on the estimated value of the sliding mode observer and the observation gain corrected by the magic tire model.

[0014] The present invention also provides a road feel simulation torque control device for a steer-by-wire system, including a processor and a memory. The memory stores a computer program that can be executed by the processor to implement the road feel simulation torque control method for a steer-by-wire system as described above.

[0015] The present invention also provides a computer-readable storage medium storing computer-readable instructions, which, when executed by a processor of the device on which the computer-readable storage medium is located, implement a steer-by-wire system road feel simulation torque control method as described above.

[0016] In summary, compared with the prior art, the present invention has the following beneficial effects: This invention combines a sliding model observer and a magic tire model to design a steer-by-wire road feel simulation scheme. By designing a sliding model observer based on steer-by-wire using sliding model theory, the dependence on steering model parameters is reduced. The estimated road feel simulation torque value is closer to the actual road feedback value, solving the core pain point of "overly heavy road feel" in existing technologies. It restores the road feel experience that conforms to real driving habits and enhances the driver's accuracy in perceiving road conditions.

[0017] This invention combines the lateral force generated by the magic tire model as a reference value for the gain of the sliding mode observer, and corrects the observation gain of the sliding mode observer in real time. It can effectively suppress the high-frequency disturbance of the sliding mode observer. Whether the vehicle is in low-speed parking, congested following, or high-speed cruising, it can output stable and accurate road feel simulation torque, avoiding the problem of "poor accuracy at low speed" in the existing technology, and meeting the needs of the steer-by-wire system in all scenarios.

[0018] This invention, based on the error dynamics equations of a sliding mode observer, designs a Lyapunov function and clarifies the range of observation gain values, ensuring that the observer remains asymptotically stable under parameter fluctuations and external disturbances, and that the estimated road sense moment does not diverge or oscillate. Compared to existing technologies that lack explicit stability constraints, this method theoretically guarantees the long-term reliability of road sense feedback, reduces driving risks caused by instability in the observation system, and provides drivers with a continuous and consistent road perception experience. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating a road feel simulation torque control method for a steer-by-wire system, as provided in Example 1.

[0021] Figure 2 This is a framework diagram of a road feel simulation torque control method for a steer-by-wire system provided in Embodiment 1.

[0022] Figure 3 The image shows the effect of the lateral force fitting surface provided in Example 1.

[0023] Figure 4 This is a schematic diagram of a road feel simulation torque control device for a steer-by-wire system provided in Embodiment 2.

[0024] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Detailed Implementation

[0025] 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 a part of the embodiments of the present invention, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0026] Example 1 Embodiment 1 of the present invention provides a method for controlling the main torque of a steer-by-wire system by simulating road feel. This method can be implemented by a steer-by-wire system road feel simulation main torque control device (hereinafter referred to as the control device), and in particular, it can be executed by one or more processors within the control device.

[0027] In this embodiment, the control device may be an electronic device equipped with a processor, which carries a computer program for the road feel simulation torque control method of the steer-by-wire system and the computer program can be executed, such as a computer, smartphone, smart tablet, workstation, etc., which are not limited here.

[0028] like Figure 1 As shown, a method for simulating road feel and controlling main torque in a steer-by-wire system includes steps S1 to S5.

[0029] S1: Collect relevant parameters of the steer-by-wire system and construct a steering model.

[0030] This step first uses sensors in the steering actuator assembly (such as torque sensors, angle sensors, current sensors, etc.) to collect relevant parameters of the steer-by-wire system, including the mass of the steering nut, damping coefficient, steering resistance, and the angle, torque, current, and transmission ratio of the actuation motor.

[0031] The formula for the steering model that is then constructed is: ; ; ; ; ; in, The rotational speed of the actuating motor; This refers to the angular acceleration of the actuating motor; The rotation angle of the actuating motor; The torque transmitted from the actuating motor to the steering gear; For steering resistance torque; The pitch circle radius of the gear sector; For the mass of the steering nut; The reduction ratio of the reducer; The equivalent damping coefficient of the steering nut; For screw lead; The correlation coefficient for the quality of the steering nut; The correlation coefficient is the equivalent damping coefficient of the steering nut; The correlation coefficient between screw lead and reduction ratio; This refers to the force related to steering resistance.

[0032] The mechanical characteristics and power transmission relationship of the steering system are constructed to provide a theoretical basis for the subsequent design of the sliding mode observer.

[0033] S2, Construct a sliding mode observer based on the steering model to estimate the road feel simulation force.

[0034] Based on the motor's rotation angle and speed, a sliding mode observer is constructed to estimate the motor's speed and angular acceleration. The expression for the sliding mode observer is: ; in, This is an estimated value of the angular acceleration of the actuating motor; This is the estimated speed of the actuating motor; This is the estimated value of the steering disturbance, which is the main force in road feel simulation; The correlation coefficient for the quality of the steering nut; The correlation coefficient is the equivalent damping coefficient of the steering nut; The correlation coefficient between screw lead and reduction ratio; The torque transmitted from the actuating motor to the steering gear; The estimated value of the road sense main moment is derived by using observer error dynamics; the road sense simulated main moment... The expression is: ; in, For observation gain; This is a switching function, i.e., a sign function; This refers to the rotational speed of the actuating motor.

[0035] This step utilizes the robustness of the sliding mode observer to effectively suppress interference from mechanical resistance of the steering system and sensor noise, solving the problem of "mechanical resistance being mistakenly included in the main torque of road feel" in existing technologies; it does not require precise model parameters (such as the time-varying characteristics of the friction coefficient), reducing the requirements for the accuracy of system parameter calibration, and is suitable for road feel estimation under complex working conditions.

[0036] S3. Based on the sliding mode observer and Lyapunov theory, derive the stability condition of the observation gain.

[0037] First, construct the observation error equation: ; in, This represents the estimation error of the angular acceleration of the actuating motor. This represents the estimation error of the actuator motor speed; It serves as the main force for road feel simulation; Forces related to steering resistance; The correlation coefficient for the quality of the steering nut; The correlation coefficient is the equivalent damping coefficient of the steering nut; Then, the sliding surface of the sliding mode observer is defined to describe the deviation between the system state and the desired state, and its formula is: ; in, The sliding surface of the sliding mode observer; , These are the rotational speed and estimated rotational speed of the actuating motor, respectively. Design the Lyapunov function, its formula is: ; in, is a Lyapunov function used to analyze the stability of the sliding mode observer; For sliding surface The first derivative; According to Lyapunov theory, when the system is asymptotically stable, it satisfies... When the observation gain satisfies the condition: ; in, For observation gain.

[0038] This embodiment theoretically proves the stability of the observer, clarifies the range of observation gain values, and avoids divergence or oscillation of observation values ​​due to unreasonable gain settings; it ensures that the estimated road sense moment can still converge to the true value under parameter fluctuations and external disturbances, improves the reliability of road sense simulation, and solves the problem of "unreliable stability of the observation system" in the prior art.

[0039] Observation Gain The above derivation shows that it can be infinitely large, but high-frequency disturbances will occur. The more accurate the value, the weaker the high-frequency disturbance effect. Therefore, the lateral force output by the tire model is used as... Reference values ​​are used to suppress high-frequency disturbances in the observer.

[0040] S4 introduces a magic tire model to calculate tire lateral force and adaptively corrects the observation gain.

[0041] First, parameters such as tire slip angle and vertical load are obtained through vehicle sensors.

[0042] A magic tire model is introduced to calculate the tire lateral force as a reference value for the observation gain. The expression for the tire lateral force is as follows: ; in, This refers to the lateral force of the tire; C, D, and E are model parameters and fitting coefficients related to the vertical load; This is the tire slip angle, collected by a sensor.

[0043] Tire lateral force For reference, the adaptive correction of the observation gain is as follows: Utilizing the lateral force of the tire As the reference value for the main observation device of the wheel-end road surface, and used as a correction term for the observation gain, the expression is: ; ; in, For observation gain Correction terms; Adjustment coefficient To simulate the main torque for road feel; The pitch circle radius of the gear sector; , These are the speed of the actuating motor and the estimated speed, respectively.

[0044] This embodiment utilizes the magic tire model to accurately depict the "vehicle-road interaction", providing a physically meaningful basis for correction of the observation gain; under low-speed conditions, the tire model error is compensated by lateral force feedback, solving the problem in the prior art that "the tire model accuracy decreases at low speeds, leading to an increase in road feel error", and achieving adaptive optimization of gain under all operating conditions.

[0045] S5, based on the estimated value of the sliding mode observer and the observation gain corrected by the magic tire model, output the final road feel simulation torque.

[0046] This step combines the estimated value output by the sliding model observer with the gain corrected by the magic tire model to obtain the final road feel simulation torque, which drives the torque motor of the steering wheel assembly to provide road feedback to the driver.

[0047] This embodiment combines the robustness of the sliding mode observer with the physical realism of the magic tire model to achieve accurate output of the road feel torque under all working conditions, balancing high-speed accuracy and low-speed stability. The output road feel simulated torque has high consistency with the feedback from the real road surface, improving the driver's perception of the road conditions, enhancing driving confidence, and reducing safety risks.

[0048] like Figure 2 As shown, the process of the road feel simulation torque control method for this steer-by-wire system can be broken down into three stages: model interaction, observer calculation, and strategy output. Phase 1, Model Interaction: Parameter Transfer between Trucksim (vehicle dynamics model) and Matlab / Simulink Trucksim (Vehicle Dynamics Model): Builds a vehicle dynamics model including a steer-by-wire (SBW) system, calculates the return torque (the feedback torque exerted by the road surface on the wheels, the core input for road feel simulation) in real time, and transmits it to the Matlab / Simulink module. Simultaneously, it receives the front wheel angle (the result of the vehicle's steering action) from Matlab / Simulink to simulate the vehicle's actual motion.

[0049] Matlab / Simulink (steer-by-wire system): Constructs the mechanical and electrical control model of the steering-by-wire system (including the steering motor, transmission mechanism, etc.), outputs motor state parameters (such as motor current, angle, torque, etc.), and transmits them to the road feel feedback strategy module; at the same time, it receives the return torque command from Trucksim.

[0050] Phase Two: Road Feel Simulation Main Moment Calculation: Based on Magic Tire Sliding Mode Observer. This module is the core of road feel simulation, integrating vehicle state parameters (from Trucksim's self-aligning torque, vehicle motion state, etc.) and motor state parameters (from Matlab / Simulink's execution system data). Through a fusion algorithm of "Magic Tire Model + Sliding Mode Observer," it achieves accurate estimation of the road feel main moment. Magic Tire Model: Input the tire's vertical load (vehicle weight distribution) and slip angle (the angle between the front wheel steering angle and the vehicle's lateral motion), based on the "Magic Formula" ( Figure 3 The medium-color 3D curve is used to calculate the lateral force between the tire and the road surface (the lateral force exerted by the road surface on the tire), providing a physical correlation between the road surface and the tire for the road feel torque.

[0051] Sliding mode observer: Combining the dynamic model of the steer-by-wire system, the robustness of sliding mode control is introduced. The lateral force output by the "magic tire model" and the "motor state parameters (such as current and angle)" are fused and calculated to finally estimate the road feel simulation torque, which is the steering resistance torque that needs to be fed back to the driver and matched with the real road surface conditions.

[0052] Phase 3, Road Feel Feedback Strategy: Output Control Commands. Using the simulated road feel torque obtained from the sliding mode observer as the control target, a road feel feedback strategy (such as torque amplification / filtering logic) is formulated. Commands are output to the Matlab / Simulink steer-by-wire execution system, driving the steering motor to generate a counter-stress torque. This torque is then fed back to the driver through the steering wheel assembly, achieving a closed-loop road feel simulation of "road condition → steering wheel perception".

[0053] In summary, compared with the prior art, the present invention has the following beneficial effects: Traditional observers rely on precise observation models, while this invention uses a sliding mode observer based on sliding mode theory, which can effectively reduce the accuracy requirements of complex parameter models of vehicle steering systems. It can still achieve stable observation of steering resistance when there are uncertainties in model parameters, thus improving the robustness of road feel simulation torque observation.

[0054] This invention introduces a tire model that accurately represents the interaction between the vehicle and the road to constrain the observation gain of the sliding mode observer. The lateral force generated by the Magic Tire model, which has been validated through extensive tire experimental data fitting and is widely used in vehicle dynamics research, is selected as the reference value for the observation gain. This optimizes the observation gain setting, thereby improving the observation accuracy of the road feel simulation torque and making the road feel feedback closer to real road conditions.

[0055] Example 2 like Figure 4 As shown, the second embodiment of the present invention also provides a road feel simulation torque control device for a steer-by-wire system, comprising: The steering model building module is used to collect relevant parameters of the steer-by-wire system and build a steering model; A sliding mode observer construction module is used to construct a sliding mode observer based on the steering model to estimate the road feel simulation force. The observation gain derivation module is used to derive the stability condition of the observation gain based on the sliding mode observer and Lyapunov theory. The correction module is used to introduce the magic tire model to calculate the tire lateral force and adaptively correct the observation gain; The output module is used to output the final road feel simulation torque based on the estimated value of the sliding mode observer and the observation gain corrected by the magic tire model.

[0056] Example 3 The third embodiment of the present invention also provides a road feel simulation torque control device for a steer-by-wire system, which includes a memory and a processor. The memory stores a computer program, which can be executed by the processor to implement the road feel simulation torque control method for a steer-by-wire system as described above.

[0057] Example 4 The fourth embodiment of the present invention also provides a computer-readable storage medium storing computer-readable instructions. When the computer-readable instructions are executed by the processor of the device where the computer-readable storage medium is located, the computer-readable instructions implement the above-described method for steer-by-wire system road feel simulation torque control.

[0058] In the several embodiments provided in this invention, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus and method embodiments described above are merely illustrative. For example, the flowcharts in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of the invention. In this regard, each block in the flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0059] In addition, the functional modules in the various embodiments of the present invention can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0060] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, electronic device, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks. It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. In the absence of further restrictions, an element defined by the phrase "comprising a..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0061] 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” as 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.

[0062] 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.

[0063] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0064] The use of "first" and "second" in the embodiments is merely to distinguish similar objects and does not represent a specific ordering of objects. It is understood that "first" and "second" can be interchanged in a specific order or sequence where permitted. It should be understood that the objects distinguished by "first" and "second" can be interchanged where appropriate so that the embodiments described herein can be implemented in an order other than those illustrated or described herein.

[0065] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for controlling the main torque of a steer-by-wire system based on road feel simulation, characterized in that, include: Collect relevant parameters of the steer-by-wire system and construct a steering model; A sliding mode observer is constructed based on the steering model to estimate the main force of road feel simulation; Based on the sliding mode observer and Lyapunov theory, the stability condition of the observation gain is derived. A magic tire model is introduced to calculate tire lateral force, and the observation gain is adaptively corrected. The final road feel simulation torque is output based on the estimated value from the sliding mode observer and the observation gain corrected by the magic tire model.

2. The method for simulating road feel and controlling main torque in a steer-by-wire system according to claim 1, characterized in that... The relevant parameters of the steer-by-wire system include the mass of the steering nut, the damping coefficient, the steering resistance, and the angle and torque of the actuation motor.

3. The method for controlling the main torque of a steer-by-wire system based on road feel simulation according to claim 1, characterized in that... The formula for the steering model is: ； ； ； ； ； in, The rotational speed of the actuating motor; This refers to the angular acceleration of the actuating motor; The rotation angle of the actuating motor; The torque transmitted from the actuating motor to the steering gear; For steering resistance torque; The pitch circle radius of the gear sector; For the mass of the steering nut; The reduction ratio of the reducer; The equivalent damping coefficient of the steering nut; For screw lead; The correlation coefficient for the quality of the steering nut; The correlation coefficient is the equivalent damping coefficient of the steering nut; The correlation coefficient between screw lead and reduction ratio; This refers to the force related to steering resistance.

4. The method for controlling the main torque of a steer-by-wire system based on road feel simulation according to claim 3, characterized in that... The expression for the sliding mode observer is: ； in, This is an estimated value of the angular acceleration of the actuating motor; This is the estimated speed of the actuating motor; This is the estimated value of the steering disturbance, which is the main force in road feel simulation; The correlation coefficient for the quality of the steering nut; The correlation coefficient is the equivalent damping coefficient of the steering nut; The correlation coefficient between screw lead and reduction ratio; The torque transmitted from the actuating motor to the steering gear; The main force of road feel simulation The expression is: ； in, For observation gain; This is a switching function, i.e., a sign function; This refers to the rotational speed of the actuating motor.

5. The method for controlling the main torque of a steer-by-wire system based on road feel simulation according to claim 4, characterized in that... Based on the sliding mode observer and Lyapunov theory, the stability condition for the observation gain is derived as follows: First, construct the observation error equation: ； in, This represents the estimation error of the angular acceleration of the actuating motor. This represents the estimation error of the actuator motor speed; It serves as the main force for road feel simulation; Forces related to steering resistance; The correlation coefficient for the quality of the steering nut; The correlation coefficient is the equivalent damping coefficient of the steering nut; Define the sliding surface of the sliding mode observer to describe the deviation between the system state and the desired state, and its formula is: ； in, The sliding surface of the sliding mode observer; , These are the rotational speed and estimated rotational speed of the actuating motor, respectively. Design the Lyapunov function, its formula is: ； in, is a Lyapunov function used to analyze the stability of the sliding mode observer; For sliding surface The first derivative; According to Lyapunov theory, when the system is asymptotically stable, it satisfies... When the observation gain satisfies the condition: ； in, For observation gain.

6. The method for controlling the main torque of a steer-by-wire system based on road feel simulation according to claim 5, characterized in that, A magic tire model is introduced to calculate the tire lateral force as a reference value for the observation gain. The expression for the tire lateral force is as follows: ； in, This refers to the lateral force of the tire; C, D, and E are model parameters and fitting coefficients related to the vertical load; This is the tire slip angle, collected by a sensor.

7. The method for simulating road feel and controlling main torque in a steer-by-wire system according to claim 6, characterized in that... The adaptive correction of observation gain is specifically as follows: Utilizing the lateral force of the tire As the reference value for the main observation device of the wheel-end road surface, and used as a correction term for the observation gain, the expression is: ； ； in, For observation gain Correction terms; This is the adjustment coefficient; To simulate the main torque for road feel; The pitch circle radius of the gear sector; , These are the speed of the actuating motor and the estimated speed, respectively.

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