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

Abstract

The invention provides a vehicle steering gear rack force determination method and device, a vehicle and a storage medium, and is applied to the technical field of vehicle control. The method comprises the steps that motion parameters of a vehicle at the current moment are obtained, the motion parameters are input into a pre-constructed rack force determination model, and the steering gear rack force of the vehicle at the current moment is obtained. By means of the method, more accurate determination of the rack force is achieved, the control precision of a steering system and the stability and safety of a vehicle are improved, and the driving experience and the energy-saving effect are optimized.

Description

Technical Field

[0001] The present 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 gear. Background Art

[0002] As a new era of automotive steering systems, steer-by-wire technology shows significant technological innovation and differences compared to traditional electric power steering systems. In a steer-by-wire system, the driver's control no longer directly acts on the wheels, but captures the steering wheel angle signal through the steering column (this component also plays the role of a hand-feel simulator in the steer-by-wire system). These signals are then accurately transmitted to the steering gear, that is, the road wheel actuator of the steer-by-wire system, which drives the wheels to rotate to the corresponding angle according to the signal instructions. Due to the lack of a direct mechanical connection between the driver and the wheel, it is impossible to perceive the road conditions through traditional "feel", such as road bumps, changes in friction, etc. Therefore, in steer-by-wire technology, how to simulate the road feel, that is, the rack force, is crucial.

[0003] In the prior art, the rack force is usually determined by theoretical calculation, or measured by actual vehicle testing.

[0004] However, the above method has certain environmental limitations, and is low in efficiency, high in cost, and poor in accuracy, thus affecting the driving safety of users. Summary of the invention

[0005] The present application provides a method, device, vehicle and storage medium for determining the rack force of a vehicle steering gear, so as to solve the problem of how to determine the rack force of a vehicle steering gear more accurately and efficiently.

[0006] In a first aspect, the present application provides a method for determining a steering rack force of a vehicle, which is applied to a vehicle, and the method comprises:

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

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

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

[0010] Determining tire lateral force according to the front wheel cornering stiffness, the front wheel sideslip angle, and the wheel vertical load of the vehicle;

[0011] Determining the wheel aligning torque according to the tire lateral force, the pneumatic tire trail and the mechanical trail of the vehicle;

[0012] The gravity self-aligning moment is determined according to the kingpin inclination angle and the kingpin inward displacement of the vehicle.

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

[0014] Determining state variables according to the lateral speed, yaw rate, tire lateral force and steering rack force of the vehicle;

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

[0016] Determining an observation variable according to the lateral acceleration of the vehicle, the yaw angular velocity and the motor output torque;

[0017] Based on the state equation and the observation variable, an 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 combination with the first aspect, in some embodiments, the method further includes:

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

[0021] Accordingly, determining the wheel aligning torque according to the tire lateral force, the pneumatic tire trail and the mechanical trail of the vehicle includes:

[0022] The wheel aligning torque is determined according to the tire dynamic lateral force, the pneumatic trail and the mechanical trail of the vehicle.

[0023] In combination with the first aspect, in some embodiments, before determining the tire lateral force according to the front wheel cornering stiffness, the front wheel sideslip angle, and the wheel vertical load of the vehicle, the method further includes:

[0024] Determining the front wheel slip angle based on the distance from the front axle to the center of mass of the vehicle, the longitudinal vehicle speed, the center of mass slip angle, the front wheel turning angle, the yaw rate and the yaw acceleration;

[0025] The center of mass sideslip angle is determined based on the lateral vehicle speed and the longitudinal vehicle speed of the vehicle.

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

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

[0028] In combination with the first aspect, in some embodiments, the motion parameters include the steering wheel angle, vehicle speed, yaw angular velocity, lateral acceleration, and steering motor output torque of the vehicle at the current moment.

[0029] In a second aspect, the present application provides a device for determining a steering rack force of a vehicle, comprising:

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

[0031] A 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, wherein the rack force determination model is constructed based on a dynamic model of the vehicle and a particle filter, and the dynamic model is constructed based on the wheel self-aligning torque of the vehicle, the gravity self-aligning torque of the vehicle, the equivalent friction torque between the steering gear and the front wheels of the vehicle, the damping torque between the steering gear and at least one component, and the equivalent inertia torque between the steering gear and the at least one component.

[0032] In conjunction with the second aspect, in some embodiments, the calculation module may also be used to:

[0033] Determining tire lateral force according to the front wheel cornering stiffness, the front wheel sideslip angle, and the wheel vertical load of the vehicle;

[0034] Determining the wheel aligning torque according to the tire lateral force, the pneumatic tire trail and the mechanical trail of the vehicle;

[0035] The gravity self-aligning moment is determined according to the kingpin inclination angle and the kingpin inward displacement of the vehicle.

[0036] In conjunction with the second aspect, in some embodiments, the calculation module may also be used to:

[0037] Determining state variables according to the lateral speed, yaw rate, tire lateral force and steering rack force of the vehicle;

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

[0039] Determining an observation variable according to the lateral acceleration of the vehicle, the yaw angular velocity and the motor output torque;

[0040] Based on the state equation and the observation variable, an 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 calculation module may also be used to:

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

[0044] Accordingly, the calculation module determines the wheel aligning torque according to the tire lateral force, the pneumatic tire trail and the mechanical trail of the vehicle, specifically for:

[0045] The wheel aligning torque is determined according to the tire dynamic lateral force, the pneumatic trail and the mechanical trail of the vehicle.

[0046] In conjunction with the second aspect, in some embodiments, the calculation module may also be used to:

[0047] Determining the front wheel slip angle based on the distance from the front axle to the center of mass of the vehicle, the longitudinal vehicle speed, the center of mass slip angle, the front wheel turning angle, the yaw rate and the yaw acceleration;

[0048] The center of mass sideslip angle is determined based on the lateral vehicle speed and the longitudinal vehicle speed of the vehicle.

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

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

[0051] In combination with the second aspect, in some embodiments, the motion parameters include the steering wheel angle, vehicle speed, yaw angular velocity, lateral acceleration, and steering motor output torque of the vehicle at the current moment.

[0052] In a third aspect, the present application provides a vehicle, comprising: a vehicle body, a storage unit disposed in the vehicle body, an electronic control unit, and a communication interface;

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

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

[0055] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer execution instructions, and when the computer execution instructions are executed by a processor, they are used to implement the method for determining the vehicle steering rack force described in any one of the first aspects.

[0056] In a fifth aspect, the present application provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the method for determining the vehicle steering rack force described in any one of the first aspects.

[0057] The present application provides a method, device, vehicle and storage medium for determining the steering rack force of a vehicle, obtains the motion parameters of the vehicle at the current moment, inputs the motion parameters into a pre-built rack force determination model, and obtains the steering rack force of the vehicle at the current moment. Through the above method, a more accurate determination of the rack force is achieved, which not only improves the control accuracy of the steering system and the stability and safety of the vehicle, but also optimizes the driving experience and energy saving effect. BRIEF DESCRIPTION OF THE DRAWINGS

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

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

[0060] Figure 2 A schematic flow chart of a first embodiment of a method for determining a rack force of a vehicle steering gear provided in an embodiment of the present application;

[0061] Figure 3 A schematic flow chart of a second embodiment of a method for determining a vehicle steering rack force provided in an embodiment of the present application;

[0062] Figure 4 This is a schematic diagram of the pneumatic tire drag distance;

[0063] Figure 5 It is a schematic diagram of mechanical drag;

[0064] Figure 6 A schematic flow chart of a third embodiment of a method for determining a rack force of a vehicle steering gear provided in an embodiment of the present application;

[0065] Figure 7 A schematic flow chart of a fourth embodiment of a method for determining a rack force of a vehicle steering gear provided in an embodiment of the present application;

[0066] Figure 8 A schematic diagram of the structure of an embodiment of a device for determining a rack force of a vehicle steering gear provided in an embodiment of the present application;

[0067] Fig. 9 A schematic diagram of the structure of a vehicle provided in an embodiment of the present application.

[0068] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0069] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0070] As a new era of automobile steering system, steer-by-wire technology shows significant technological innovation and difference compared with traditional electric power steering system. In the steer-by-wire system, the driver's control no longer directly acts on the wheel, but captures the steering wheel angle signal through the steering column (this component also plays the role of a hand feel simulator in the steer-by-wire system). These signals are then accurately transmitted to the steering gear, that is, the road wheel actuator of the steer-by-wire system, which drives the wheel to rotate to the corresponding angle according to the signal command. Due to the lack of direct mechanical connection between the driver and the wheel, it is impossible to perceive the road conditions, such as bumps on the road, changes in friction, etc., through traditional "hand feel". Therefore, in the steer-by-wire technology, how to simulate the road feel force, that is, the rack force, is crucial. In the prior art, the estimation of the steering rack force can be based on the rack force generation principle, and a model can be established to calculate the rack force by using the signals detected by sensors such as vehicle speed and steering wheel angle as input. The neural network can also be trained by neural networks and other methods to enable it to calculate the appropriate rack force. Alternatively, the torque generated by the steering rack on the input shaft can be estimated by the unscented Kalman filter algorithm. However, the above method requires the model to be as accurate as possible, and the parameters such as the lateral stiffness and wheel load of the vehicle steering system are in a state of real-time change, so it is difficult for the above method to achieve accurate estimation of the torque. The rack force calculated by neural network and other methods, because the neural network does not obtain the rack force based on the force principle of the steering system, the calculated result may be very different from the actual rack force, and in some cases it cannot reflect the real road feel.

[0071] In view of the above problems, the present application provides a method, device, vehicle and storage medium for determining the rack force of a vehicle, so that the determination of the rack force is more accurate and efficient, so that the driver can feel the real road conditions through the steering wheel, thereby improving driving safety. Specifically, for estimating the rack force of the steering gear, a model can be established based on the principle of rack force generation, and the rack force can be calculated by taking the signals detected by sensors such as vehicle speed and steering wheel angle as input. The model established by this method needs to be as accurate as possible, and the parameters such as the lateral stiffness and wheel load of the vehicle steering system are in a state of real-time change, so it is difficult for the above method to achieve accurate estimation of the torque. The neural network can also be trained by a neural network or the like, so that it can calculate the appropriate rack force. The rack force calculated by the above-mentioned neural network or the like, because the neural network is not based on the force principle of the steering system to obtain the rack force, the calculated result may be very different from the actual rack force, and in some cases cannot reflect the real road feel. Or the torque generated by the steering rack on the input shaft is estimated by the unscented Kalman filter algorithm. The above-mentioned unscented Kalman filter requires that both process noise and measurement noise are Gaussian distributed. However, the driving environment encountered by the car in the actual driving process is very complex, which will affect the steering system. Therefore, the observation noise is not necessarily Gaussian distributed. Considering the above problems, the inventor studied whether it is possible to establish a dynamic model as a state equation, use the output torque of the steering motor of the steering gear as the observation value, and use a particle filter to estimate the steering rack force. In order to achieve a more accurate calculation of the rack force, based on this, the technical solution of this application is proposed.

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

[0073] Among them, the main function of the steering gear assembly is to increase the torque from the steering wheel to make it large enough to overcome the steering resistance torque between the steering wheel and the road surface, and to reduce the speed of the steering transmission shaft, and to rotate the steering rocker arm shaft, drive the rocker arm to swing so that its end obtains the required displacement, or convert the rotation of the driving gear connected to the steering transmission shaft into the linear motion of the gear rack to obtain the required displacement. By selecting different thread spiral directions on the screw (worm), the steering gear assembly can also achieve the coordination of the rotation direction of the steering wheel and the steering wheel. There are many types of steering gear assemblies, including gear rack type, recirculating ball type, worm crank pin type and power steering gear. Among them, the gear rack 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 converting the steering command input by the driver through the steering wheel into the actual steering action of the wheel. The steering wheel assembly usually contains a variety of 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, and convert this information into electrical signals and transmit them to the feel simulation motor ECU for processing. The feel simulation motor ECU issues instructions to the feel simulation motor based on the processing results to adjust its working state and the steering feel it provides. The feel simulation 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 can be seen that the sum of the lateral forces on the steering rack is the steering rack force. In the wire steering system, since the mechanical connection between the steering wheel and the steering wheel is eliminated, the traditional road feel feedback transmitted through the mechanical connection no longer exists. In order to simulate this road feel, the wire steering 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 and type of the physical devices mentioned above.

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

[0078] Figure 2 The flowchart of the first embodiment of the method for determining the rack force of the vehicle steering gear provided in the embodiment of the present application is as follows: Figure 2 As shown, the method is applied to a vehicle and specifically includes:

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

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

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

[0082] For example, the steering wheel angle can be directly measured by a sensor. A steering wheel angle sensor is installed in the steering wheel assembly to directly measure and output a steering wheel angle signal. The steering wheel angle can also be obtained through the steering wheel angle sensor. The actual steering wheel angle is then calculated based on the proportional coefficient between the steering wheel and front wheel angles.

[0083] Vehicle speed can be measured by a gear system or magneto-electric effect sensor installed in the vehicle's transmission system or wheels, usually mounted on the vehicle's dashboard for display. Vehicle speed can also be measured using radio waves or laser technology. The vehicle's speed can also be calculated using GPS data through the vehicle's navigation system or map application on a mobile phone. Alternatively, the vehicle can be identified by a camera and its speed can be calculated by analyzing its movement.

[0084] The yaw rate can be calculated by measuring the angular velocity difference between the inner and outer wheels of the vehicle, combined with parameters such as wheel radius and vehicle width. The yaw rate can also be calculated using the vehicle's lateral acceleration and speed through a formula. Alternatively, a dedicated yaw rate sensor can be used to directly measure the vehicle's yaw rate.

[0085] The lateral acceleration can be measured directly by installing an acceleration sensor on the vehicle. The lateral acceleration can also be calculated by combining parameters such as vehicle speed and steering radius (or turning radius) with the 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 the drive shaft. The output torque of the steering motor can also be estimated based on the motor's output power, angular velocity and other parameters combined with the motor's control algorithm and state monitoring. Alternatively, the output torque of the steering motor can be obtained in real time through the motor controller's internal algorithm and sensor feedback.

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

[0088] S202: Inputting the motion parameters into a 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-constructed, and the motion parameters obtained in the previous steps are input into the rack force determination model to calculate and 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 dynamics model to obtain a particle filter, and the dynamics model is constructed based on the vehicle's wheel self-aligning torque, the vehicle's gravity self-aligning torque, the equivalent friction 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 inertia torque between the steering gear and at least one component.

[0091] Exemplarily, the rack force determination model performs iterative update calculations based on internal preset state equations and observation equations and input motion parameters, and ultimately obtains the steering rack force of the vehicle at the current moment.

[0092] The specific iterative update process may include: first, initialize the particle set, randomly generate a group of particles in the state space, and each particle represents a possible state. Assign an initial weight to each particle, and calculate the weight of each particle according to the observation equation and the observation value at the current moment. Among them, the weight reflects the degree of proximity between the state represented by the particle and the actual state. In order to avoid the dominance of particles with too large weights, resulting in the loss of diversity of the particle set, resampling is performed. During the resampling process, a new particle set is randomly extracted from the particle set according to the weight of the particle, so that particles with larger weights are more likely to be extracted. Repeat the above state prediction, weight update and resampling process until a predetermined number of iterations is reached or a certain convergence condition is met. After the iteration is completed, the state at the current moment is estimated according to the weight and position of the particle. The state estimation can be a weighted average of the particle position or other forms of statistical estimation. The embodiment of the present application is not specifically limited. The rack force at the current moment is obtained according to the state estimation result, and the obtained rack force estimation value is output to the control system of the vehicle or other modules that need to use the information.

[0093] Optionally, the motion parameters may be pre-processed before being input into the rack force determination model, for example, filtering and calibrating the motion parameters to eliminate noise and errors, thereby converting the data into a format that can be processed by the rack force determination model.

[0094] The method for determining the steering rack force of a vehicle provided in this embodiment obtains the motion parameters of the vehicle at the current moment, inputs the motion parameters into a pre-built rack force determination model, and obtains the steering rack force of the vehicle at the current moment. Through the above method, a more accurate determination of the rack force is achieved, which not only improves the control accuracy of the steering system and the stability and safety of the vehicle, but also optimizes the driving experience and energy saving effect.

[0095] Figure 3 The flowchart of the second embodiment of the method for determining the rack force of the vehicle steering gear provided in the embodiment of the present application is as follows: Figure 3 As shown, based on the above embodiment, the method further includes:

[0096] S301: Determine tire lateral force according to the front wheel cornering stiffness, front wheel sideslip angle, and wheel vertical load of the vehicle.

[0097] In this step, the rack force is the sum of the forces on the steering gear rack, which is generated by the components from the steering gear to the wheel. The steer-by-wire system eliminates the mechanical connection between the steering wheel and the tire, but the lateral force on the tire during steering will still be transmitted to the rack through the steering mechanism, thereby affecting the size of the rack force. Specifically, the lateral force on the tire will be transmitted to the steering gear rack through transmission components such as the steering rod, forming a rack force. The size and direction of this rack force depends on the size and direction of the tire lateral force, as well as the transmission ratio, stiffness and other parameters of the steering system. Therefore, to determine the rack force, it is necessary to first determine the tire lateral force of the vehicle.

[0098] Specifically, the Dugoff tire model can be constructed based on the pre-acquired front wheel cornering stiffness, front wheel side slip angle, and wheel vertical load to determine 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 is the tire lateral force, C αf is the front wheel cornering stiffness, α f is the front wheel slip angle, μ is the road adhesion coefficient, λ is the switching coefficient, F z is the vertical load on the wheel.

[0102] S302: Determine the wheel aligning torque according to the tire lateral force, the pneumatic trail and the mechanical trail of the vehicle.

[0103] S303: Determine the gravity aligning moment according to the kingpin inclination angle and the kingpin inward displacement of the vehicle.

[0104] When the driver inputs steering torque through the steering wheel, this torque will be converted into rack force through the steering gear, and then push the steering rod and other transmission components to cause the tire to deviate. After the tire deviates, a wheel self-aligning torque will be generated, which will react to the steering system and affect the change of the rack force. If the wheel self-aligning torque is large, it may reduce the rack force or even cause the rack to move in the opposite direction. The gravity self-aligning torque generated by the vehicle's own gravity will affect the vehicle's driving stability and handling performance. If the self-aligning torque is too large or too small, it may cause the vehicle to be unstable or difficult to control. The gravity self-aligning torque will also interact with the wheel self-aligning torque and rack force to jointly affect the vehicle's steering performance and handling stability. Therefore, the rack force includes the wheel self-aligning torque and gravity self-aligning torque related to the wheel force.

[0105] Specifically, for cars with traditional steering systems, their tires will generate a certain self-aligning torque due to positioning parameters such as the castor angle and the kingpin inclination angle under the lateral force exerted on the tires and the body's own gravity, causing the steering wheel to return to the 0-degree state. The wheel self-aligning torque generated by the tire is the main source of steering wheel road feel. At the same time, it helps to maintain the stability of the vehicle when driving in a straight line, which can greatly improve the handling stability of the car and reduce the driver's driving fatigue. In order for the wire control steering system feel simulator to simulate the road feel of the traditional steering system, the calculation of the rack force needs to take into account the self-aligning torque generated by the tire. The components of the self-aligning torque are as follows:

[0106] (1) Wheel self-aligning torque generated by lateral force and trail

[0107] Figure 4 It is a schematic diagram of the pneumatic tire drag distance, such as Figure 4 As shown in the figure, the center of force is offset due to uneven distribution of lateral stress, and this offset is the pneumatic tire drag. The formula is:

[0108]

[0109] Among them, τ p Indicates the pneumatic tire trail, τ p0 is the trailing distance of the pneumatic tire when there is no side slip angle, sgn represents the sign function, α f Indicates the front wheel slip angle, C αf is the front wheel cornering stiffness, μ is the road adhesion coefficient, F z is the vertical load on the wheel.

[0110] Figure 5 is a schematic diagram of mechanical drag, such as Figure 5 As shown in the figure, the mechanical drag is determined by the caster angle S w The sum of the mechanical trail and the pneumatic trail constitutes the force arm, which acts together with the lateral force to subject the tire to a self-aligning torque. The wheel self-aligning torque is specifically expressed as:

[0111] T trail =(τ m +τ p )F y

[0112] Among them, T trail is the wheel aligning torque, τ m represents the mechanical drag, τ p Indicates the trail distance of the pneumatic tire, F y is the lateral force of the tire.

[0113] The restoring torque generated by the body weight

[0114] (2) Gravity-correcting torque generated by the vehicle body’s gravity

[0115] Due to the existence of the kingpin inclination angle β and the kingpin inward displacement d, when the wheel rotates around the kingpin, it tends to rotate toward the ground in the vertical direction. This wheel rotation will cause the car body to slightly lift up under the reaction force. Since the car is heavy, when the hands leave the steering wheel, the steering wheel will automatically return to the center under the action of gravity. The torque that causes the steering wheel to return to the center is the gravity return torque T generated by the weight of the car body. gravity , the relationship is as follows:

[0116] T gravity =F z dsin(θ f )sin(β)

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

[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 the lateral force of the tire.

[0119] When the vehicle slip angle changes, the tire lateral force generated has 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 is the tire lateral force, i.e. the tire lateral force at the current moment calculated by the above tire model, is the dynamic lateral force of the tire calculated at the moment before the current moment, c is the relaxation length, v x is the longitudinal speed.

[0122] Correspondingly, step S302 includes: determining the wheel aligning torque according to the tire dynamic lateral force, the pneumatic trail and the mechanical trail of the vehicle.

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

[0124]

[0125] The method for determining the steering rack force of a vehicle provided in this embodiment determines the tire lateral force according to the front wheel lateral stiffness, front wheel side slip angle, and wheel vertical load of the vehicle, obtains the tire dynamic lateral force based on the relaxation model according to the preset relaxation length and tire lateral force, determines the wheel self-aligning torque according to the tire dynamic lateral force, the pneumatic tire trail and mechanical trail of the vehicle, and determines the gravity self-aligning torque according to the kingpin inclination angle and kingpin inward displacement of the vehicle. This method determines parameters such as tire lateral force, wheel self-aligning torque, and gravity self-aligning torque by comprehensively considering multiple factors, effectively improving the vehicle's handling stability and safety, optimizing the driving experience, and enhancing adaptability.

[0126] Figure 6 The flowchart of the third embodiment of the method for determining the rack force of the vehicle steering gear provided in the embodiment of the present application is as follows: Figure 6 As shown, based on the above embodiment, the method further includes:

[0127] S601: Determine state variables according to the lateral speed, yaw rate, tire lateral force and steering rack force of the vehicle.

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

[0129] In order to determine the steering rack force of the steer-by-wire system, the particle filter needs to be constructed, and the state variables need to be determined. The state variables together cover the key aspects of the vehicle's lateral dynamics and steering system. The lateral vehicle speed and yaw rate reflect the overall lateral stability and handling performance of the vehicle, while the tire lateral force is directly related to the interaction between the tire and the road surface and is the basis of the vehicle's handling. The steering rack force directly reflects the driver's control intention for the vehicle and the response of the steering system. The state variables are determined based on the vehicle's lateral vehicle speed, yaw rate, tire lateral force and steering rack force. The state variables are specifically expressed as:

[0130] X=[v y ,ω r ,F y ,F a ] T

[0131] Among them, v y is the lateral speed, ω r is the yaw angular velocity, F y is the tire lateral force, F a Steering rack force.

[0132] Optionally, the tire lateral force in the above state variables may also be the tire dynamic lateral force, and the state variables are specifically expressed as:

[0133]

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

[0135] The dynamic model is constructed based on the wheel self-aligning torque of the vehicle, the gravity self-aligning torque of the vehicle, the equivalent friction torque between the steering gear and the front wheel of the vehicle, the damping torque between the steering gear and at least one component, and the equivalent inertia torque between the steering gear and at least one component. The wheel self-aligning torque of the vehicle and the gravity self-aligning torque of the vehicle are T in the above embodiment. trail and T gravity .

[0136] Equivalent friction torque T between the steering gear and the front wheel af :

[0137]

[0138] Among them, c af is the peak value of the equivalent friction torque generated by the steering gear to the front wheel and other components; b af is the corresponding slope coefficient, which can affect the changing speed of the equivalent friction torque. is the steering wheel angular velocity.

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

[0140]

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

[0142] The equivalent inertia moment generated by components such as steering gear and wheels:

[0143]

[0144] Among them, J aiThe moment of inertia of components such as the steering wheel and the steering gear; is the steering wheel angular acceleration.

[0145] The dynamic model is constructed by using the above different torques, so as to obtain the dynamic model, that is, the equation corresponding to the steering rack force:

[0146]

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

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

[0149]

[0150] The symbols used are the same as those in the above embodiments and will not be described again.

[0151] S603: Determine observation variables according to the lateral acceleration, yaw angular velocity and motor output torque of the vehicle.

[0152] S604: Obtain an observation equation based on the state equation and the observation variables.

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

[0154] Lateral acceleration is one of the important indicators of vehicle dynamic performance, which can directly reflect the lateral stability of the vehicle during driving. By monitoring lateral acceleration, it is possible to detect whether the vehicle is in an unstable state in time, so as to take corresponding control measures to ensure driving safety. During the vehicle steering process, the change of lateral acceleration can reflect the steering performance and response speed of the vehicle. Taking lateral acceleration as an observation variable can provide important feedback information for the steering control system, help the system to more accurately adjust the steering angle and steering force, and improve the vehicle's handling and stability. Yaw angular velocity is the angular velocity that describes the rotation of the vehicle around the vertical axis, and is an important parameter for evaluating the stability of the vehicle's posture. By monitoring the yaw angular velocity, it can be determined whether the vehicle is oversteering or understeering during driving, so as to take corresponding stability control measures in time. Taking yaw angular velocity as an observation variable can more accurately evaluate the stability state of the vehicle and provide a more precise control basis for the vehicle stability control system. This helps the system respond to changes in the vehicle's posture more quickly and improve the stability and safety of the vehicle. Motor output torque is one of the key indicators of electric vehicle power performance. By monitoring the motor output torque, the power output of the vehicle can be understood in real time, providing the driver with a more intuitive driving experience. Taking the motor output torque as an observed variable can help the vehicle energy management system more accurately evaluate the vehicle's energy consumption and thus formulate a more reasonable energy allocation strategy.

[0155] After the observed variables are determined, the observed variables are expressed as:

[0156] Z=[a y ,ω r ,T m ]

[0157] Based on the state equation in the previous steps, the observation equation is obtained:

[0158]

[0159] Wherein, i represents the worm gear ratio of the road wheel actuator.

[0160] Then, the above state equation and observation equation are configured in the particle filter to obtain the rack force determination model.

[0161] The method for determining the steering rack force of a vehicle provided in this embodiment determines state variables according to the lateral speed, yaw angular velocity, tire lateral force and steering rack force of the vehicle, obtains a state equation based on a dynamic model, state variables at time k and state variables at time k-1, where k is an integer greater than 2, determines observation variables according to the lateral acceleration, yaw angular velocity and motor output torque of the vehicle, obtains an observation equation based on the state equation and the observation variables, configures the state equation and the observation equation in a particle filter, and obtains a rack force determination model.

[0162] Figure 7 The flowchart of the fourth embodiment of the method for determining the rack force of the vehicle steering gear provided in the embodiment of the present application is as follows: 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 mass of the vehicle, the longitudinal vehicle speed, the center of mass slip angle, the front wheel turning angle, the yaw rate and the yaw acceleration.

[0164] S702: Determine a center of mass sideslip angle based on the lateral speed and longitudinal speed of the vehicle.

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

[0166] S703: Determine the yaw acceleration and lateral acceleration based on the rear wheel cornering stiffness of the vehicle, the distance from the rear axle of the vehicle to the center of mass, the distance from the front axle of the vehicle to the center of mass, the mass of the vehicle, the moment of inertia about the Z axis, and the front wheel cornering stiffness, yaw angular velocity, and front wheel turning angle.

[0167] On the basis of the foregoing embodiment, the front wheel sideslip angle, the center of mass sideslip angle, the yaw angular acceleration and the lateral acceleration may also be determined by the following formulas.

[0168]

[0169] Among them, α f is the front wheel slip angle, l f is the distance from the front axle to the center of mass of the vehicle, ω r is the yaw angular velocity, v x is the longitudinal speed, β is the sideslip angle of the center of mass of the vehicle, θ f is the front wheel turning angle, is the yaw angular acceleration.

[0170]

[0171] Where β is the side slip angle of the center of mass of the car, v y is the lateral speed, v x is the longitudinal speed, a y is the lateral acceleration.

[0172] The yaw angular acceleration and lateral acceleration can be determined by building a two-degree-of-freedom model. The specific formula is:

[0173]

[0174] Among them, C αr is the rear wheel cornering stiffness, lr is the distance from the rear axle to the center of mass of the vehicle, l f is the distance from the front axle to the center of mass of the car, m is the mass of the car, I z is the moment of inertia about the Z axis.

[0175] The method for determining the steering rack force of a vehicle provided in this embodiment determines the front wheel slip angle based on the distance from the front axle to the center of mass of the vehicle, the longitudinal vehicle speed, the center of mass slip angle, the front wheel turning angle, the yaw angular velocity and the yaw angular acceleration, determines the center of mass slip angle based on the lateral vehicle speed and the longitudinal vehicle speed, and determines the yaw angular acceleration and the lateral acceleration according to the rear wheel slip stiffness of the vehicle, the distance from the rear axle to the center of mass of the vehicle, the distance from the front axle to the center of mass of the vehicle, the mass of the vehicle, the moment of inertia around the Z axis, and the front wheel slip stiffness, the yaw angular velocity and the front wheel turning angle. By accurately determining the front wheel slip angle and the center of mass slip angle, and accurately predicting the yaw angular acceleration and the lateral acceleration, it provides strong technical support for improving the vehicle handling stability, control system performance optimization, advanced driver assistance functions and the level of vehicle intelligence.

[0176] Figure 8 A schematic diagram of the structure of an embodiment of a device for determining a steering rack force of a vehicle provided in an embodiment of the present application is shown in FIG. Figure 8 As shown, the vehicle steering rack force determination device 800 comprises:

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

[0178] The calculation module 802 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 the particle filter. The dynamic model is constructed based on the vehicle's wheel self-aligning torque, the vehicle's gravity self-aligning torque, the equivalent friction 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 inertia torque between the steering gear and at least one component.

[0179] Optionally, the compute module can also be used to:

[0180] Determine the tire lateral force based on the vehicle's front wheel cornering stiffness, front wheel side slip angle, and wheel vertical load;

[0181] Determine the wheel aligning torque based on the tire lateral force, the pneumatic trail and the mechanical trail of the vehicle;

[0182] Determine the gravity-righting moment based on the vehicle's kingpin inclination angle and kingpin inward displacement.

[0183] In a possible implementation, the computing module may also be used to:

[0184] Determining state variables according to the lateral speed, yaw rate, tire lateral force and steering rack force of the vehicle;

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

[0186] Determine the observed variables according to the lateral acceleration, yaw rate and motor output torque of the vehicle;

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

[0188] The state equation and observation equation are configured in the particle filter to obtain the rack force determination model.

[0189] In another possible implementation, the computing module may also be used to:

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

[0191] Accordingly, the calculation module determines the wheel aligning torque according to the tire lateral force, the pneumatic tire trail and the mechanical trail of the vehicle, which is specifically used for:

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

[0193] Optionally, the compute module can also be used to:

[0194] Determine the front wheel slip angle based on the distance from the front axle to the center of mass of the vehicle, the longitudinal vehicle speed, the center of mass slip angle, the front wheel turning angle, the yaw rate and the yaw acceleration;

[0195] Based on the lateral and longitudinal speeds of the vehicle, the center of mass slip angle is determined.

[0196] In a possible design, the lateral vehicle speed is calculated based on the lateral acceleration, and the calculation module can also be used to:

[0197] The yaw acceleration and lateral acceleration are determined based on the vehicle's rear wheel cornering stiffness, the distance from the vehicle's rear axle to the center of mass, the distance from the vehicle's front axle to the center of mass, the vehicle's mass, the moment of inertia about the Z axis, and the front wheel cornering stiffness, yaw angular velocity, and front wheel turning angle.

[0198] Optionally, the motion parameters include the steering wheel angle, vehicle speed, yaw angular velocity, lateral acceleration, and steering motor output torque of the vehicle at the current moment.

[0199] The device for determining the vehicle steering rack force provided in the above embodiment is used to execute the method for determining the vehicle steering rack force in any of the above method embodiments. Its implementation principle and technical effect are similar and will not be repeated here.

[0200] Fig. 9 A schematic diagram of the structure of a vehicle provided in an embodiment of the present application, such as Fig. 9 As shown, it includes: a vehicle body 900, a storage unit 901 arranged in the vehicle body 900, an electronic control unit 902, and a communication interface 903;

[0201] The storage unit 901 stores computer-executable instructions.

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

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

[0204] An embodiment of the present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the method for determining the vehicle steering rack force in any embodiment.

[0205] The computer-readable storage medium mentioned above 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 memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special purpose computer.

[0206] Optionally, a readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0207] An embodiment of the present application also provides a computer program product, which includes a computer program. The computer program is stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium. When at least one processor executes the computer program, the technical solution provided by any of the above method embodiments can be implemented.

[0208] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0209] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for determining the steering rack force of a vehicle, applied to a vehicle, characterized in that: The method comprises: Obtaining motion parameters of the vehicle at the current moment; The motion parameters are input into a pre-constructed rack force determination model to obtain the steering rack force of the vehicle at the current moment, wherein the rack force determination model is constructed based on a dynamic model of the vehicle and a particle filter, and the dynamic model is constructed based on the wheel self-aligning torque of the vehicle, the gravity self-aligning torque of the vehicle, the equivalent friction torque between the steering gear and the front wheels of the vehicle, the damping torque between the steering gear and at least one component, and the equivalent inertia torque between the steering gear and the at least one component.

2. The method according to claim 1, characterized in that Before inputting the motion parameters into a pre-built rack force determination model to obtain the steering rack force of the vehicle at the current moment, the method further includes: Determining tire lateral force according to the front wheel cornering stiffness, the front wheel sideslip angle, and the wheel vertical load of the vehicle; Determining the wheel aligning torque according to the tire lateral force, the pneumatic tire trail and the mechanical trail of the vehicle; The gravity self-aligning moment is determined according to the kingpin inclination angle and the kingpin inward displacement of the vehicle.

3. The method according to claim 1, characterized in that: The method further comprises: Determining state variables according to the lateral speed, yaw rate, tire lateral force and steering rack force of the vehicle; Based on the kinetic model, the state variables at time k and the state variables at time k-1, a state equation is obtained, where k is an integer greater than 2; Determining an observation variable according to the lateral acceleration of the vehicle, the yaw angular velocity and the motor output torque; Based on the state equation and the observation variable, an observation equation is obtained; The state equation and the observation equation are configured in the particle filter to obtain the rack force determination model.

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

5. The method according to claim 2, characterized in that: Before determining the tire lateral force according to the front wheel cornering stiffness, the front wheel sideslip angle, and the wheel vertical load of the vehicle, the method further includes: Determining the front wheel slip angle based on the distance from the front axle to the center of mass of the vehicle, the longitudinal vehicle speed, the center of mass slip angle, the front wheel turning angle, the yaw rate and the yaw acceleration; The center of mass sideslip angle is determined based on the lateral vehicle speed and the longitudinal vehicle speed of the vehicle.

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

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

8. A device for determining the rack force of a vehicle steering gear, characterized in that: include: An acquisition module, used to acquire the motion parameters of the vehicle at the current moment; A 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, wherein the rack force determination model is constructed based on a dynamic model of the vehicle and a particle filter, and the dynamic model is constructed based on the wheel self-aligning torque of the vehicle, the gravity self-aligning torque of the vehicle, the equivalent friction torque between the steering gear and the front wheels of the vehicle, the damping torque between the steering gear and at least one component, and the equivalent inertia torque between the steering gear and the at least one component.

9. A vehicle, characterized in that: include: A vehicle body, a storage unit disposed in the vehicle body, an electronic control unit, and a communication interface; The storage unit stores computer-executable instructions; The electronic control unit executes the computer-executable 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 7 above.

10. 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 vehicle steering rack force according to any one of claims 1 to 7.

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