Method and device for determining vehicle steering rack force, vehicle and storage medium

Abstract

This application provides a method, apparatus, vehicle, and storage medium for determining the rack force of a vehicle steering gear, applicable to the field of vehicle control technology. The method includes: acquiring the vehicle's motion parameters at the current moment, inputting the motion parameters into a pre-constructed rack force determination model, and obtaining the vehicle's steering gear rack force at the current moment. This method achieves more accurate rack force determination, which not only improves the control precision of the steering system and the stability and safety of the vehicle, but also optimizes the driving experience and energy-saving effects.

Description

Technical Field

[0001] This application relates to the field of vehicle control technology, and in particular to a method, device, vehicle, and storage medium for determining the rack force of a vehicle steering system. Background Technology

[0002] Steer-by-wire technology, representing a new era in automotive steering systems, exhibits significant technological innovation and differences compared to traditional electric power steering systems. In steer-by-wire systems, the driver's input no longer directly affects the wheels; instead, the steering column (which also acts as a hand-feel simulator in the system) captures the steering wheel's angle signal. These signals are then precisely transmitted to the steering gear, the wheel actuators of the steer-by-wire system, which drive the wheels to rotate at the corresponding angle based on the signal commands. Because there is no direct mechanical connection between the driver and the wheels, it is impossible to perceive road conditions, such as bumps and changes in friction, through traditional "feel." Therefore, simulating road feel forces, i.e., rack forces, is crucial in steer-by-wire technology.

[0003] In existing technologies, rack force is usually determined by theoretical calculations or by measuring rack force through actual vehicle testing.

[0004] However, the above methods have certain environmental limitations, and are inefficient, costly, and inaccurate, thus affecting the user's driving safety. Summary of the Invention

[0005] This application provides a method, apparatus, vehicle, and storage medium for determining the rack force of a vehicle steering system, in order to solve the problem of how to more accurately and efficiently determine the rack force of a vehicle steering system.

[0006] In a first aspect, this application provides a method for determining the rack force of a vehicle steering system, applied to a vehicle, the method comprising:

[0007] Obtain the motion parameters of the vehicle at the current moment;

[0008] The motion parameters are input into a pre-built rack force determination model to obtain the steering rack force of the vehicle at the current moment. The rack force determination model is constructed based on the vehicle's dynamic model and a particle filter. The dynamic model is constructed based on the vehicle's wheel self-centering torque, the vehicle's gravity self-centering torque, the equivalent friction torque between the vehicle's steering gear and the front wheel, the damping torque between the steering gear and at least one component, and the equivalent inertial torque between the steering gear and at least one component.

[0009] In conjunction with the first aspect, in some embodiments, before inputting the motion parameters into a pre-constructed rack force determination model to obtain the steering rack force of the vehicle at the current moment, the method further includes:

[0010] The tire lateral force is determined based on the front wheel lateral stiffness, front wheel lateral angle, and wheel vertical load of the vehicle.

[0011] The wheel return torque is determined based on the tire lateral force, the vehicle's pneumatic tire trail and mechanical trail.

[0012] The gravity-correcting torque is determined based on the kingpin inclination angle and kingpin displacement of the vehicle.

[0013] In conjunction with the first aspect, in some embodiments, the method further includes:

[0014] The state variables are determined based on the vehicle's lateral speed, yaw rate, tire lateral force, and steering rack force.

[0015] Based on the aforementioned dynamic model, the state variables at time k and time k-1, the state equation is obtained, where k is an integer greater than 2;

[0016] The observed variables are determined based on the vehicle's lateral acceleration, yaw rate, and motor output torque;

[0017] Based on the state equation and the observed variables, the observation equation is obtained;

[0018] The state equation and the observation equation are configured in the particle filter to obtain the rack force determination model.

[0019] In conjunction with the first aspect, in some embodiments, the method further includes:

[0020] Based on the relaxation model, the dynamic lateral force of the tire is obtained according to the preset relaxation length and the tire lateral force.

[0021] Accordingly, determining the wheel return torque based on the tire lateral force, the vehicle's tire trail and mechanical trail includes:

[0022] The wheel return torque is determined based on the tire dynamic lateral force, the vehicle's pneumatic tire trail and mechanical trail.

[0023] In conjunction with the first aspect, in some embodiments, before determining the tire lateral force based on the vehicle's front wheel lateral stiffness, front wheel slip angle, and wheel vertical load, the method further includes:

[0024] The front wheel sideslip angle is determined based on the distance from the front axle to the center of gravity of the vehicle, the longitudinal vehicle speed, the sideslip angle of the center of gravity, the front wheel steering angle, the yaw rate and the yaw acceleration.

[0025] The centroid sideslip angle is determined based on the vehicle's lateral speed and longitudinal speed.

[0026] In conjunction with the first aspect, in some embodiments, the lateral vehicle speed is calculated based on lateral acceleration, and the method further includes:

[0027] The yaw rate and the lateral acceleration are determined based on the rear wheel lateral stiffness, the distance from the rear axle to the center of mass, the distance from the front axle to the center of mass, the mass of the vehicle, the moment of inertia about the Z-axis, the front wheel lateral stiffness, the yaw rate, and the front wheel rotation angle.

[0028] In conjunction with the first aspect, in some embodiments, the motion parameters include the vehicle's steering wheel angle, vehicle speed, yaw rate, lateral acceleration, and steering motor output torque at the current moment.

[0029] Secondly, this application provides a device for determining the rack force of a vehicle steering system, comprising:

[0030] The acquisition module is used to acquire the motion parameters of the vehicle at the current moment;

[0031] The calculation module is used to input the motion parameters into a pre-constructed rack force determination model to obtain the steering rack force of the vehicle at the current moment. The rack force determination model is constructed based on the vehicle's dynamic model and a particle filter. The dynamic model is constructed based on the vehicle's wheel self-centering torque, the vehicle's gravity self-centering torque, the equivalent friction torque between the vehicle's steering gear and the front wheel, the damping torque between the steering gear and at least one component, and the equivalent inertial torque between the steering gear and at least one component.

[0032] In conjunction with the second aspect, in some embodiments, the computing module can also be used for:

[0033] The tire lateral force is determined based on the front wheel lateral stiffness, front wheel lateral angle, and wheel vertical load of the vehicle.

[0034] The wheel return torque is determined based on the tire lateral force, the vehicle's pneumatic tire trail and mechanical trail.

[0035] The gravity-correcting torque is determined based on the kingpin inclination angle and kingpin displacement of the vehicle.

[0036] In conjunction with the second aspect, in some embodiments, the computing module can also be used for:

[0037] The state variables are determined based on the vehicle's lateral speed, yaw rate, tire lateral force, and steering rack force.

[0038] Based on the aforementioned dynamic model, the state variables at time k and time k-1, the state equation is obtained, where k is an integer greater than 2;

[0039] The observed variables are determined based on the vehicle's lateral acceleration, yaw rate, and motor output torque;

[0040] Based on the state equation and the observed variables, the observation equation is obtained;

[0041] The state equation and the observation equation are configured in the particle filter to obtain the rack force determination model.

[0042] In conjunction with the second aspect, in some embodiments, the computing module can also be used for:

[0043] Based on the relaxation model, the dynamic lateral force of the tire is obtained according to the preset relaxation length and the tire lateral force.

[0044] Accordingly, the calculation module determines the wheel return torque based on the tire lateral force, the vehicle's tire trail and mechanical trail, specifically for:

[0045] The wheel return torque is determined based on the tire dynamic lateral force, the vehicle's pneumatic tire trail and mechanical trail.

[0046] In conjunction with the second aspect, in some embodiments, the computing module can also be used for:

[0047] The front wheel sideslip angle is determined based on the distance from the front axle to the center of gravity of the vehicle, the longitudinal vehicle speed, the sideslip angle of the center of gravity, the front wheel steering angle, the yaw rate and the yaw acceleration.

[0048] The centroid sideslip angle is determined based on the vehicle's lateral speed and longitudinal speed.

[0049] In conjunction with the second aspect, in some embodiments, the lateral vehicle speed is calculated based on lateral acceleration, and the calculation module can also be used for:

[0050] The yaw rate and the lateral acceleration are determined based on the rear wheel lateral stiffness, the distance from the rear axle to the center of mass, the distance from the front axle to the center of mass, the mass of the vehicle, the moment of inertia about the Z-axis, the front wheel lateral stiffness, the yaw rate, and the front wheel rotation angle.

[0051] In conjunction with the second aspect, in some embodiments, the motion parameters include the vehicle's steering wheel angle, vehicle speed, yaw rate, lateral acceleration, and steering motor output torque at the current moment.

[0052] Thirdly, this application provides a vehicle, including: a vehicle body, a storage unit disposed within the vehicle body, an electronic control unit, and a communication interface;

[0053] The storage unit stores computer-executed instructions;

[0054] The electronic control unit executes the computer execution instructions stored in the storage unit to implement the method for determining the vehicle steering rack force as described in any one of the first aspects.

[0055] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method for determining the rack force of a vehicle steering system as described in any one of the first aspects.

[0056] Fifthly, this application provides a computer program product comprising a computer program that, when executed by a processor, implements the method for determining the rack force of a vehicle steering system as described in the first aspect.

[0057] The method, apparatus, vehicle, and storage medium for determining the rack force of a vehicle steering gear provided in this application acquire the vehicle's motion parameters at the current moment, input the motion parameters into a pre-constructed rack force determination model, and obtain the vehicle's steering gear rack force at the current moment. This method achieves more accurate determination of the rack force, which not only improves the control precision of the steering system and the stability and safety of the vehicle, but also optimizes the driving experience and energy-saving effects. Attached Figure Description

[0058] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0059] Figure 1 A schematic diagram of the system architecture for the method of determining the rack force of a vehicle steering system provided in this application embodiment;

[0060] Figure 2 A flowchart illustrating an embodiment of the method for determining the rack force of a vehicle steering system provided in this application.

[0061] Figure 3 A flowchart illustrating Embodiment 2 of the method for determining the rack force of a vehicle steering system provided in this application;

[0062] Figure 4 This is a diagram illustrating the tire trail of a pneumatic tire.

[0063] Figure 5 This is a schematic diagram of the mechanical drag distance;

[0064] Figure 6 A flowchart illustrating Embodiment 3 of the method for determining the rack force of a vehicle steering system provided in this application;

[0065] Figure 7 A flowchart illustrating Embodiment 4 of the method for determining the rack force of a vehicle steering system provided in this application;

[0066] Figure 8 A schematic diagram of an embodiment of the vehicle steering rack force determination device provided in this application;

[0067] Figure 9 This is a schematic diagram of the vehicle structure provided in an embodiment of this application.

[0068] The accompanying drawings have illustrated specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to specific embodiments. Detailed Implementation

[0069] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0070] steer-by-wire technology, as a new era in automotive steering systems, exhibits significant technological innovation and differences compared to traditional electric power steering systems. In steer-by-wire systems, the driver's control no longer directly acts on the wheels, but rather captures the steering wheel's angle signal through the steering column (which also acts as a hand feel simulator in the steer-by-wire system). These signals are then precisely transmitted to the steering gear, the road wheel actuator of the steer-by-wire system, which drives the wheels to rotate at the corresponding angle according to the signal commands. Because there is no direct mechanical connection between the driver and the wheels, it is impossible to perceive road conditions, such as road bumps and changes in friction, through traditional "feel." Therefore, simulating road feel force, i.e., rack force, is crucial in steer-by-wire technology. In existing technologies, the estimation of the steering gear rack force can be based on the principle of rack force generation, establishing a model and using signals detected by sensors such as vehicle speed and steering wheel angle as input to calculate the rack force. Alternatively, neural networks can be trained to calculate appropriate rack forces. Another approach is to estimate the torque generated by the steering gear rack on the input shaft using an unscented Kalman filter algorithm. However, the above methods require models to be as accurate as possible, while parameters such as the lateral stiffness and wheel load of the vehicle steering system are constantly changing, making it difficult for these methods to accurately estimate torque. Furthermore, rack forces calculated using neural networks, which do not derive rack forces from the force principles of the steering system, may differ significantly from the actual rack forces and, in some cases, fail to reflect real road feel.

[0071] To address the aforementioned problems, this application provides a method, device, vehicle, and storage medium for determining vehicle rack force, thereby making rack force determination more accurate and efficient, enabling drivers to feel the real road conditions through the steering wheel and improving driving safety. Specifically, the estimation of steering rack force can be based on the principle of rack force generation, establishing a model and using signals detected by sensors such as vehicle speed and steering wheel angle as input to calculate the rack force. This method requires the model to be as accurate as possible, but parameters such as the lateral stiffness and wheel load of the vehicle steering system are constantly changing, making it difficult for the above method to achieve accurate torque estimation. Alternatively, neural networks can be trained to calculate appropriate rack forces. However, the rack force calculated using neural networks may differ significantly from the actual rack force because the neural network does not derive the rack force based on the force principle of the steering system, and in some cases, it may not reflect the true road feel. Another approach is to estimate the torque generated by the steering rack on the input shaft using an unscented Kalman filter algorithm. The aforementioned unscented Kalman filter requires both process noise and measurement noise to have a Gaussian distribution. However, the driving environment encountered by automobiles in actual driving is very complex, which will affect the steering system. Therefore, the observed noise may not necessarily have a Gaussian distribution. Considering the above problem, the inventors investigated whether it is possible to establish a dynamic model as the state equation, use the output torque of the steering motor as the observed value, and use a particle filter to estimate the steering rack force. This would achieve a more accurate calculation of the rack force, and based on this, the technical solution of this application is proposed.

[0072] Figure 1 A schematic diagram of the system architecture for the method of determining the rack force of a vehicle steering system provided in this application embodiment is shown below. Figure 1 As shown, this method can be applied to vehicle steering scenarios, where vehicle steering usually relies on the vehicle's steer-by-wire system, which mainly includes the steering gear assembly and the steering wheel assembly.

[0073] The main function of the steering gear assembly is to increase the torque from the steering wheel, making it large enough to overcome the steering resistance torque between the steering wheels and the road surface. It also reduces the speed of the steering drive shaft and rotates the steering rocker arm shaft, causing the rocker arm to swing and achieve the required displacement at its end. Alternatively, it converts the rotation of the drive gear connected to the steering drive shaft into the linear motion of the rack and pinion to achieve the required displacement. By selecting different helix directions on the screw (worm) mechanism, the steering gear assembly can also coordinate the rotation direction of the steering wheel with the rotation direction of the steering wheels. There are various types of steering gear assemblies, including rack and pinion, recirculating ball, worm crank pin, and power steering. The rack and pinion steering gear consists of a steering gear, a steering rack, a housing, and a preload adjustment device.

[0074] The steering wheel assembly is responsible for translating the steering commands input by the driver through the steering wheel into actual steering actions of the wheels. The steering wheel assembly typically contains various sensors, such as steering wheel angle sensors and torque sensors. These sensors can detect the steering wheel angle and the torque applied by the driver in real time, converting this information into electrical signals and transmitting them to the steering wheel analog motor ECU for processing. Based on the processing results, the steering wheel analog motor ECU sends commands to the steering wheel analog motor to adjust its operating state and the steering feel it provides. The steering wheel analog motor ECU can also monitor the status of the steering system and perform fault detection and diagnosis when necessary.

[0075] Depend on Figure 1 It is known that the sum of the lateral forces acting on the steering rack is the steering rack force. In a steer-by-wire system, since the mechanical connection between the steering wheel and the steering wheels is eliminated, the traditional road feel feedback transmitted through mechanical connections no longer exists. To simulate this road feel, the steer-by-wire system estimates and simulates the rack force, thereby providing the driver with a corresponding road experience.

[0076] This application does not specifically limit the form or type of the physical equipment mentioned above.

[0077] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0078] Figure 2 A flowchart illustrating an embodiment of the method for determining the rack force of a vehicle steering system provided in this application is shown below. Figure 2 As shown, this method is applied to vehicles and specifically includes:

[0079] S201: Obtain the vehicle's motion parameters at the current moment.

[0080] In this step, in order to simulate road feel based on the steering rack force in the online steering system and thus improve the driver's driving experience, it is necessary to obtain the vehicle's motion parameters in real time.

[0081] Specifically, the vehicle's operating parameters at the current moment are obtained through sensors configured in the vehicle. Optionally, the motion parameters may include the vehicle's steering wheel angle, vehicle speed, yaw rate, lateral acceleration, and steering motor output torque at the current moment.

[0082] For example, the steering wheel angle can be directly measured by a sensor. An angle sensor can be installed in the steering wheel assembly to directly measure and output the steering wheel angle signal. Alternatively, the steering wheel angle can be obtained by a steering wheel angle sensor, and then the actual steering wheel angle can be calculated based on the ratio coefficient between the steering wheel angle and the front wheel angle.

[0083] Vehicle speed can be measured using gear systems or magnetoelectric sensors installed in the vehicle's drivetrain or wheels, typically displayed on the dashboard. It can also be measured using radio waves or laser technology. Furthermore, vehicle speed can be calculated using GPS data from in-car navigation systems or map applications on mobile phones. Alternatively, it can be determined by using cameras to identify the vehicle and analyze its motion to calculate its speed.

[0084] Yaw rate can be calculated by measuring the difference in angular velocity between the inner and outer wheels of a vehicle, combined with parameters such as wheel radius and vehicle width. Alternatively, it can be calculated using a formula based on the vehicle's lateral acceleration and speed. Another option is to directly measure the vehicle's yaw rate using a dedicated yaw rate sensor.

[0085] Lateral acceleration can be measured directly by installing acceleration sensors on the vehicle. Alternatively, lateral acceleration can be calculated using parameters such as vehicle speed and turning radius (or cornering radius) in conjunction with a vehicle dynamics model.

[0086] The output torque of the steering motor can be directly measured by installing a torque sensor on the steering motor or drive shaft. Alternatively, the output torque can be estimated based on parameters such as the motor's output power and angular velocity, combined with the motor's control algorithm and status monitoring. Or, the output torque can be obtained in real time through the motor controller's internal algorithms and sensor feedback.

[0087] It should be noted that the parameters mentioned above that can be obtained by sensors are acquired by the vehicle's electronic control unit through a bus, such as the I2C bus.

[0088] S202: Input the motion parameters into the pre-built rack force determination model to obtain the steering rack force of the vehicle at the current moment.

[0089] In this step, in order to more accurately determine the steering rack force, a rack force determination model is pre-built. The motion parameters obtained in the previous steps are input into the rack force determination model for calculation to obtain the steering rack force of the vehicle at the current moment.

[0090] Specifically, the rack force determination model is constructed based on the vehicle's dynamic model and the particle filter. The dynamic model is constructed based on the vehicle's wheel return torque, the vehicle's gravity return torque, the equivalent friction torque between the vehicle's steering gear and the front wheel, the damping torque between the steering gear and at least one component, and the equivalent inertial torque between the steering gear and at least one component.

[0091] For example, the rack force determination model iteratively updates and calculates based on internally preset state equations and observation equations and input motion parameters to finally obtain the steering rack force of the vehicle at the current moment.

[0092] The specific iterative update process may include: First, initializing the particle set by randomly generating a group of particles in the state space, each particle representing a possible state. Assigning an initial weight to each particle and calculating the weight of each particle based on the observation equation and the current observation value. The weight reflects the degree of closeness between the state represented by the particle and the true state. To prevent particles with excessively large weights from dominating and causing the particle set to lose diversity, resampling is performed. During resampling, a new particle set is randomly selected from the particle set based on the particle weights, making it more likely that particles with larger weights will be selected. Repeating the above process of state prediction, weight update, and resampling continues until a predetermined number of iterations is reached or a certain convergence condition is met. After the iteration ends, estimating the current state based on the particle weights and positions. The state estimation can be a weighted average of particle positions or other forms of statistical estimation. This application does not specifically limit the method. The rack force at the current moment is obtained based on the state estimation result, and the estimated rack force value is output to the vehicle's control system or other modules that need to use this information.

[0093] Optionally, the motion parameters can be preprocessed before being input into the rack force determination model. For example, the motion parameters can be filtered and calibrated to eliminate noise and errors, thereby converting the data into a format that the rack force determination model can process.

[0094] The method for determining the rack force of a vehicle steering gear provided in this embodiment obtains the vehicle's motion parameters at the current moment, inputs these parameters into a pre-constructed rack force determination model, and obtains the vehicle's steering gear rack force at the current moment. This method achieves more accurate rack force determination, which not only improves the control precision of the steering system and the stability and safety of the vehicle, but also optimizes the driving experience and fuel efficiency.

[0095] Figure 3 A flowchart illustrating Embodiment 2 of the method for determining the rack force of a vehicle steering system provided in this application is shown below. Figure 3 As shown, based on the above embodiments, the method further includes:

[0096] S301: Determine the tire lateral force based on the vehicle's front wheel lateral stiffness, front wheel lateral angle, and wheel vertical load.

[0097] In this step, the rack force is the sum of the forces acting on the steering rack, generated by components from the steering gear to the wheels. While the steer-by-wire system eliminates the mechanical connection between the steering wheel and the tires, the lateral forces acting on the tires during steering are still transmitted to the rack through the steering mechanism, thus affecting the magnitude of the rack force. Specifically, the lateral forces acting on the tires are transmitted to the steering rack through transmission components such as the steering tie rods, forming the rack force. The magnitude and direction of this rack force depend on the magnitude and direction of the lateral forces acting on the tires, as well as parameters such as the steering system's gear ratio and stiffness. Therefore, to determine the rack force, it is necessary to first determine the lateral forces acting on the vehicle's tires.

[0098] Specifically, a Dugoff tire model can be constructed based on pre-obtained front wheel lateral stiffness, front wheel lateral angle, and wheel vertical load, thereby determining the tire lateral force. The specific formula can be expressed as:

[0099] F y =-C αf tanα f f(λ)

[0100]

[0101] Among them, F y C is the lateral force of the tire. αf For the front wheel lateral stiffness, α f Let F be the front wheel slip angle, μ be the road adhesion coefficient, λ be the switching coefficient, and F be the slip angle. z This refers to the vertical load acting on the wheel.

[0102] S302: Determine the wheel return torque based on the tire lateral force, the vehicle's pneumatic tire trail, and the mechanical trail.

[0103] S303: Determine the gravity-correcting torque based on the kingpin inclination angle and kingpin displacement of the vehicle.

[0104] When the driver inputs steering torque through the steering wheel, this torque is converted into rack force through the steering gear, which in turn pushes the steering tie rods and other transmission components, causing the tires to lateralize. This lateralization generates a wheel return torque, which reacts on the steering system, affecting the rack force. If the wheel return torque is large, it may reduce the rack force or even cause the rack to move in the opposite direction. The gravitational return torque generated by the vehicle's own weight affects the vehicle's driving stability and handling performance. If the return torque is too large or too small, it may lead to vehicle instability or difficulty in handling. The gravitational return torque also interacts with the wheel return torque and rack force, jointly affecting the vehicle's steering performance and handling stability. Therefore, the rack force includes both the wheel return torque and the gravitational return torque related to the wheel's forces.

[0105] Specifically, in traditional steering systems, the tires, due to their positioning parameters such as caster angle and kingpin inclination angle, generate a certain self-centering torque under the lateral forces acting on the tires and the vehicle's own weight, causing the steering wheel to return to a 0-degree position. This self-centering torque is the primary source of steering wheel feel and helps maintain vehicle stability during straight-line driving, significantly improving handling stability and reducing driver fatigue. To enable a steer-by-wire system feel simulator to accurately simulate the road feel of a traditional steering system, the calculation of rack force needs to consider the self-centering torque generated by the tires. The components of the self-centering torque are as follows:

[0106] (1) Lateral force and wheel self-aligning torque generated by trailing distance

[0107] Figure 4 This is a diagram illustrating the tire trail of a pneumatic tire, as shown below. Figure 4 As shown, the uneven distribution of lateral stress causes a shift in the center of force; this shift is the tire trail. The formula is as follows:

[0108]

[0109] Where, τ p Indicates tire trail, τ p0 The tire trail is the distance of the pneumatic tire without a sideslip angle, sgn represents the sign function, and α f C represents the front wheel slip angle. αf F is the front wheel lateral stiffness, μ is the road adhesion coefficient, and F is the front wheel lateral stiffness. z This refers to the vertical load acting on the wheel.

[0110] Figure 5 This is a schematic diagram of the mechanical trailing distance, such as... Figure 5 As shown, the mechanical trailing distance is determined by the kingpin inclination angle S. w The decision is a constant. The lever arm formed by the sum of the mechanical trail and the tire trail, together with the lateral force, causes the tire to experience a self-aligning torque. The specific expression of the wheel self-aligning torque is as follows:

[0111] T trail =(τ m +τ p )F y

[0112] Among them, T trail τ represents the wheel return torque. m Indicates the mechanical trailing distance, τ p F indicates tire trail. y This refers to the lateral force of the tire.

[0113] The restoring torque generated by the vehicle's weight

[0114] (2) Gravity-correcting torque generated by the vehicle body weight

[0115] Due to the kingpin inclination angle β and kingpin displacement d, when the wheel rotates around the kingpin, it tends to rotate towards the ground in the vertical direction. This wheel rotation causes the vehicle body to lift slightly under the reaction force. Because the car has a large weight, when the driver's hands leave the steering wheel, the steering wheel will automatically return to center under the action of gravity. This torque that returns the steering wheel to center is the gravity-based return torque T generated by the weight of the vehicle body. gravity The relationship is as follows:

[0116] T gravity =F z dsin(θ f sin(β)

[0117] Among them, F z θ is the vertical load on the wheel. f Indicates the steering angle of the front wheels.

[0118] Optionally, the method further includes: obtaining the dynamic lateral force of the tire based on a relaxation model, according to a preset relaxation length and tire lateral force.

[0119] When the vehicle's slip angle changes, the resulting tire lateral force exhibits a certain time lag. This transient behavior of the tire can be represented by the relaxation length *c*, which is the distance the tire rolls during the lag time. Using the relaxation model proposed by Rajamani, the tire dynamic lateral force... The equation is:

[0120]

[0121] Among them, F y This refers to the lateral force of the tire, specifically the lateral force of the tire at the current moment calculated by the tire model described above. The dynamic lateral force of the tire calculated from the previous moment is the current moment, where c is the relaxation length and v is the lateral force. x This refers to the longitudinal vehicle speed.

[0122] Accordingly, step S302 includes: determining the wheel return torque based on the tire dynamic lateral force, the vehicle's pneumatic tire trail and mechanical trail.

[0123] The formula in step S302 above can also be:

[0124]

[0125] The method for determining the rack force of the vehicle steering system provided in this embodiment determines the tire lateral force based on the front wheel lateral stiffness, front wheel lateral angle, and wheel vertical load. Based on a relaxation model, the dynamic tire lateral force is obtained according to a preset relaxation length and the tire lateral force. The wheel return torque is determined based on the dynamic tire lateral force, the vehicle's tire trail and mechanical trail. The gravity return torque is determined based on the vehicle's kingpin inclination angle and kingpin displacement. This method effectively improves vehicle handling stability and safety, optimizes the driving experience, and enhances adaptability by comprehensively considering multiple factors to determine parameters such as tire lateral force, wheel return torque, and gravity return torque.

[0126] Figure 6 A flowchart illustrating Embodiment 3 of the method for determining the rack force of a vehicle steering system provided in this application is shown below. Figure 6 As shown, based on the above embodiments, the method further includes:

[0127] S601: Determine the state variables based on the vehicle's lateral speed, yaw rate, tire lateral force, and steering rack force.

[0128] S602: Based on the dynamic model, the state variables at time k and time k-1, the state equation is obtained, where k is an integer greater than 2.

[0129] To determine the steering rack force of the steer-by-wire system, a particle filter is constructed, requiring the determination of state variables. These state variables collectively encompass key aspects of the vehicle's lateral dynamics and steering system. Lateral speed and yaw rate reflect the vehicle's overall lateral stability and handling performance, while tire lateral force directly relates to the interaction between the tire and the road surface, forming the basis of vehicle handling. The steering rack force directly reflects the driver's intention to control the vehicle and the steering system's response. Therefore, the state variables are determined based on the vehicle's lateral speed, yaw rate, tire lateral force, and steering rack force. The state variables are specifically represented as follows:

[0130] X = [v y ,ω r ,F y ,F a ] T

[0131] Among them, v y For lateral vehicle speed, ω r F is the yaw rate. y F is the lateral force of the tire. a Steering gear rack force.

[0132] Optionally, the tire lateral force in the above state variables can also be the tire dynamic lateral force, in which case the state variables are specifically represented as follows:

[0133]

[0134] It should be noted that the steering rack force F in the state variables a This is the dynamic model.

[0135] The dynamic model is constructed based on the vehicle's wheel self-centering torque, the vehicle's gravity self-centering torque, the equivalent frictional torque between the vehicle's steering gear and the front wheels, the damping torque between the steering gear and at least one component, and the equivalent inertial torque between the steering gear and at least one component. The vehicle's wheel self-centering torque and the vehicle's gravity self-centering torque are T in the aforementioned embodiment. trail and T gravity .

[0136] The equivalent frictional torque T between the steering gear and the front wheel af :

[0137]

[0138] Among them, c af b is the peak value of the equivalent frictional torque generated by components such as the steering gear and front wheels; af The corresponding slope coefficient can affect the rate of change of the equivalent frictional torque. This refers to the angular velocity of the steering wheel.

[0139] Damping torque T generated by components such as the steering gear and wheels ad :

[0140]

[0141] Among them, B ad This refers to the damping coefficient of components from the steering gear to the wheels. This refers to the angular velocity of the steering wheel.

[0142] The equivalent inertial torque generated by components such as the steering gear and wheels:

[0143]

[0144] Among them, J aiThe moment of inertia of components such as the steering wheel and steering gear; This refers to the acceleration of the steering wheel angle.

[0145] By constructing a dynamic model using the different torques described above, we obtain the equation corresponding to the steering rack force:

[0146]

[0147] Where s is the rack displacement of the motor-end gear shaft of the road wheel actuator per revolution, and T r T is the sum of the wheel self-aligning torque and the vehicle's gravity self-aligning torque. r =T trail +T gravity .

[0148] The state equation describes the change of the system state over time. Therefore, the dynamic model is determined as the state equation of a particle filter. Based on the state variables at time k and time k-1, the state equation is obtained, specifically expressed as:

[0149]

[0150] The symbols used are the same as those in the previous embodiments, and will not be repeated here.

[0151] S603: Determine the observed variables based on the vehicle's lateral acceleration, yaw rate, and motor output torque.

[0152] S604: Based on the state equation and the observed variables, the observation equation is obtained.

[0153] S605: The state equation and observation equation are configured in the particle filter to obtain the rack force determination model.

[0154] Lateral acceleration is a crucial indicator of vehicle dynamics, directly reflecting its lateral stability during driving. Monitoring lateral acceleration allows for timely detection of vehicle instability, enabling appropriate control measures to ensure driving safety. Changes in lateral acceleration during steering reflect the vehicle's steering performance and response speed. Using lateral acceleration as an observed variable provides vital feedback to the steering control system, helping it to more accurately adjust steering angle and force, improving handling and stability. Yaw rate describes the angular velocity of a vehicle's rotation around its vertical axis and is a key parameter for assessing vehicle attitude stability. Monitoring yaw rate helps determine if oversteer or understeer occurs, allowing for timely stabilization control measures. Using yaw rate as an observed variable provides a more accurate assessment of vehicle stability, offering more precise control data for the vehicle stability control system. This helps the system respond more quickly to changes in vehicle attitude, improving stability and safety. Motor output torque is a key indicator of electric vehicle power performance. Monitoring motor output torque provides real-time insight into the vehicle's power output, offering the driver a more intuitive driving experience. Using the motor's output torque as an observation variable can help the vehicle's energy management system more accurately assess the vehicle's energy consumption, thereby formulating a more reasonable energy allocation strategy.

[0155] Once the observed variables are determined, they are represented as follows:

[0156] Z = [a y ,ω r ,T m ]

[0157] Based on the state equations from the preceding steps, the observation equations are obtained:

[0158]

[0159] Where i represents the worm gear transmission ratio of the road wheel actuator.

[0160] The aforementioned state equation and observation equation are then configured in a particle filter to obtain a rack force determination model.

[0161] The method for determining the rack force of a vehicle steering gear provided in this embodiment determines the state variables based on the vehicle's lateral speed, yaw rate, tire lateral force, and steering gear rack force. Based on the dynamic model, the state variables at time k and time k-1, a state equation is obtained, where k is an integer greater than 2. Observation variables are determined based on the vehicle's lateral acceleration, yaw rate, and motor output torque. Based on the state equation and observation variables, an observation equation is obtained. The state equation and observation equation are configured in a particle filter to obtain the rack force determination model.

[0162] Figure 7 A flowchart illustrating Embodiment 4 of the method for determining the rack force of a vehicle steering system provided in this application is shown below. Figure 7 As shown, based on the above embodiments, the method further includes:

[0163] S701: Determine the front wheel slip angle based on the distance from the front axle to the center of gravity, longitudinal vehicle speed, center of gravity slip angle, front wheel steering angle, yaw rate, and yaw acceleration.

[0164] S702: Determine the centroid sideslip angle based on the vehicle's lateral and longitudinal speeds.

[0165] Optionally, if the lateral vehicle speed is calculated based on lateral acceleration, then the method further includes:

[0166] S703: Determine the yaw rate and lateral acceleration based on the vehicle's rear wheel lateral stiffness, the distance from the rear axle to the center of mass, the distance from the front axle to the center of mass, the vehicle's mass, moment of inertia about the Z-axis, as well as the front wheel lateral stiffness, yaw rate, and front wheel steering angle.

[0167] Based on the aforementioned embodiments, the front wheel slip angle, center of gravity slip angle, yaw acceleration, and lateral acceleration can also be determined using the following formulas.

[0168]

[0169] Where, α f The front wheel slip angle, l f ω is the distance from the front axle to the center of gravity of the car. r v is the yaw rate. x Let β be the longitudinal vehicle speed, β be the sideslip angle of the vehicle's center of gravity, and θ be the longitudinal vehicle speed. f For the front wheel steering angle, This is the yaw acceleration.

[0170]

[0171] Where β is the sideslip angle of the car's center of gravity, v y For lateral vehicle speed, v x For longitudinal vehicle speed, a y This is lateral acceleration.

[0172] By constructing a two-degree-of-freedom model, the yaw acceleration and lateral acceleration can be determined, as expressed by the following formulas:

[0173]

[0174] Among them, C αr For the rear wheel lateral stiffness, lr l is the distance from the rear axle of the car to the center of gravity of the car. f I is the distance from the front axle to the center of gravity of the car, m is the mass of the car, and I is the mass of the car. z Let be the moment of inertia about the Z-axis.

[0175] The method for determining the rack force of the vehicle steering system provided in this embodiment determines the front wheel slip angle based on the distance from the front axle to the center of gravity, longitudinal vehicle speed, center of gravity sideslip angle, front wheel steering angle, yaw rate, and yaw acceleration. It determines the center of gravity sideslip angle based on the vehicle's lateral and longitudinal speeds. Furthermore, it determines the yaw acceleration and lateral acceleration based on the rear wheel sideslip stiffness, the distance from the rear axle to the center of gravity, the distance from the front axle to the center of gravity, the vehicle's mass, moment of inertia about the Z-axis, and the front wheel sideslip stiffness, yaw rate, and front wheel steering angle. By accurately determining the front wheel sideslip angle and center of gravity sideslip angle, and accurately predicting the yaw acceleration and lateral acceleration, this method provides strong technical support for improving vehicle handling stability, optimizing control system performance, enhancing advanced driver assistance functions, and improving the vehicle's intelligence level.

[0176] Figure 8 This is a schematic diagram of the structure of an embodiment of the vehicle steering rack force determination device provided in this application, as shown below. Figure 8 As shown, the vehicle steering rack force determining device 800 includes:

[0177] The acquisition module 801 is used to acquire the vehicle's motion parameters at the current moment.

[0178] The calculation module 802 is used to input motion parameters into a pre-built rack force determination model to obtain the steering rack force of the vehicle at the current moment. The rack force determination model is constructed based on the vehicle's dynamic model and a particle filter. The dynamic model is constructed based on the vehicle's wheel self-centering torque, the vehicle's gravity self-centering torque, the equivalent frictional torque between the vehicle's steering gear and the front wheel, the damping torque between the steering gear and at least one component, and the equivalent inertial torque between the steering gear and at least one component.

[0179] Optionally, the calculation module can also be used for:

[0180] The tire lateral force is determined based on the vehicle's front wheel slip stiffness, front wheel slip angle, and wheel vertical load.

[0181] Determine the wheel return torque based on the tire lateral force, the vehicle's pneumatic tire trail, and the mechanical trail.

[0182] The gravity-correcting torque is determined based on the kingpin inclination angle and kingpin displacement of the vehicle.

[0183] In one possible implementation, the computation module can also be used for:

[0184] The state variables are determined based on the vehicle's lateral speed, yaw rate, tire lateral force, and steering rack force.

[0185] Based on the dynamic model, the state variables at time k and time k-1, the state equation is obtained, where k is an integer greater than 2;

[0186] The observed variables are determined based on the vehicle's lateral acceleration, yaw rate, and motor output torque;

[0187] Based on the state equation and the observed variables, the observation equation is obtained;

[0188] By configuring the state equation and observation equation in the particle filter, a rack force determination model is obtained.

[0189] In another possible implementation, the computation module can also be used for:

[0190] Based on the relaxation model, the dynamic lateral force of the tire is obtained according to the preset relaxation length and tire lateral force.

[0191] Accordingly, the calculation module determines the wheel return torque based on the tire lateral force, the vehicle's tire trail, and the mechanical trail, specifically for:

[0192] The wheel return torque is determined based on the tire dynamic lateral force, the vehicle's pneumatic tire trail, and the mechanical trail.

[0193] Optionally, the calculation module can also be used for:

[0194] The front wheel slip angle is determined based on the distance from the front axle to the center of gravity, longitudinal vehicle speed, center of gravity slip angle, front wheel steering angle, yaw rate, and yaw acceleration.

[0195] The sideslip angle of the center of gravity is determined based on the vehicle's lateral and longitudinal speeds.

[0196] In one possible design, the lateral vehicle speed, calculated based on lateral acceleration, can also be used by the calculation module for:

[0197] Based on the rear wheel lateral stiffness, the distance from the rear axle to the center of mass, the distance from the front axle to the center of mass, the vehicle's mass, moment of inertia about the Z-axis, as well as the front wheel lateral stiffness, yaw rate, and front wheel rotation angle, determine the yaw acceleration and lateral acceleration.

[0198] Optional motion parameters include the vehicle's steering wheel angle, vehicle speed, yaw rate, lateral acceleration, and steering motor output torque at the current moment.

[0199] The vehicle steering rack force determination device provided in the above embodiments is used to execute the vehicle steering rack force determination method in any of the aforementioned method embodiments. Its implementation principle and technical effect are similar, and will not be described again here.

[0200] Figure 9 This is a structural schematic diagram of the vehicle provided in the embodiments of this application, such as... Figure 9 As shown, it includes: a vehicle body 900, a storage unit 901 disposed within the vehicle body 900, an electronic control unit 902, and a communication interface 903;

[0201] Storage unit 901 stores computer-executed instructions.

[0202] The electronic control unit 902 executes the computer execution instructions stored in the storage unit 901 to implement the method for determining the vehicle steering rack force in any of the foregoing embodiments.

[0203] Communication interface 903 is used to enable communication between different components in the vehicle.

[0204] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method for determining the vehicle steering rack force in any embodiment.

[0205] The aforementioned computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory, electrically erasable programmable read-only memory, erasable programmable read-only memory, programmable read-only memory, read-only memory, magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0206] Optionally, a readable storage medium can be coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Alternatively, the readable storage medium can be an integral part of the processor. Both the processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components within the device.

[0207] This application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium, and when the at least one processor executes the computer program, it can implement the technical solutions provided in any of the above method embodiments.

[0208] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0209] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for determining the rack force of a vehicle steering system, applied to vehicles, characterized in that, The method includes: Obtain the motion parameters of the vehicle at the current moment; The motion parameters are input into a pre-built rack force determination model to obtain the steering rack force of the vehicle at the current moment. The rack force determination model is constructed based on the vehicle's dynamic model and a particle filter. The dynamic model is constructed based on the vehicle's wheel self-centering torque, the vehicle's gravity self-centering torque, the equivalent friction torque between the vehicle's steering gear and the front wheel, the damping torque between the steering gear and at least one component, and the equivalent inertial torque between the steering gear and at least one component. The method further includes: The state variables are determined based on the vehicle's lateral speed, yaw rate, tire lateral force, and steering rack force. Based on the aforementioned dynamic model, the state variables at time k and time k-1, the state equation is obtained, where k is an integer greater than 2; The observed variables are determined based on the vehicle's lateral acceleration, yaw rate, and motor output torque; Based on the state equation and the observed variables, the observation equation is obtained; The state equation and the observation equation are configured in the particle filter to obtain the rack force determination model.

2. The method according to claim 1, characterized in that, Before inputting the motion parameters into the pre-built rack force determination model to obtain the steering rack force of the vehicle at the current moment, the method further includes: The tire lateral force is determined based on the front wheel lateral stiffness, front wheel lateral angle, and wheel vertical load of the vehicle. The wheel return torque is determined based on the tire lateral force, the vehicle's pneumatic tire trail and mechanical trail. The gravity-correcting torque is determined based on the kingpin inclination angle and kingpin displacement of the vehicle.

3. The method according to claim 2, characterized in that, The method further includes: Based on the relaxation model, the dynamic lateral force of the tire is obtained according to the preset relaxation length and the tire lateral force. Accordingly, determining the wheel return torque based on the tire lateral force, the vehicle's tire trail and mechanical trail includes: The wheel return torque is determined based on the tire dynamic lateral force, the vehicle's pneumatic tire trail, and the mechanical trail.

4. The method according to claim 2, characterized in that, Before determining the tire lateral force based on the vehicle's front wheel lateral stiffness, front wheel lateral angle, and wheel vertical load, the method further includes: The front wheel sideslip angle is determined based on the distance from the front axle to the center of gravity of the vehicle, the longitudinal vehicle speed, the sideslip angle of the center of gravity, the front wheel steering angle, the yaw rate and the yaw acceleration. The centroid sideslip angle is determined based on the vehicle's lateral speed and longitudinal speed.

5. The method according to claim 4, characterized in that, The lateral vehicle speed is calculated based on lateral acceleration, and the method further includes: The yaw rate and the lateral acceleration are determined based on the rear wheel lateral stiffness, the distance from the rear axle to the center of mass, the distance from the front axle to the center of mass, the mass of the vehicle, the moment of inertia about the Z-axis, the front wheel lateral stiffness, the yaw rate, and the front wheel rotation angle.

6. The method according to any one of claims 1 to 5, characterized in that, The motion parameters include the vehicle's steering wheel angle, vehicle speed, yaw rate, lateral acceleration, and steering motor output torque at the current moment.

7. A device for determining the rack force of a vehicle steering system, characterized in that, include: The acquisition module is used to acquire the motion parameters of the vehicle at the current moment; The calculation module is used to input the motion parameters into a pre-constructed rack force determination model to obtain the steering rack force of the vehicle at the current moment. The rack force determination model is constructed based on the vehicle's dynamic model and a particle filter. The dynamic model is constructed based on the vehicle's wheel self-centering torque, the vehicle's gravity self-centering torque, the equivalent friction torque between the vehicle's steering gear and the front wheel, the damping torque between the steering gear and at least one component, and the equivalent inertial torque between the steering gear and at least one component. The computing module is also used for: The state variables are determined based on the vehicle's lateral speed, yaw rate, tire lateral force, and steering rack force. Based on the aforementioned dynamic model, the state variables at time k and time k-1, the state equation is obtained, where k is an integer greater than 2; The observed variables are determined based on the vehicle's lateral acceleration, yaw rate, and motor output torque; Based on the state equation and the observed variables, the observation equation is obtained; The state equation and the observation equation are configured in the particle filter to obtain the rack force determination model.

8. A vehicle, characterized in that, include: The vehicle body, including storage units, electronic control units, and communication interfaces located within it; The storage unit stores computer-executed instructions; The electronic control unit executes the computer execution instructions stored in the storage unit to implement the method for determining the vehicle steering rack force as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method for determining the rack force of a vehicle steering system as described in any one of claims 1 to 6.

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