Vehicle system and method for estimating road wheel angle

Abstract

Vehicle systems and methods for estimating road wheel angles. A vehicle system for determining a road wheel angle of a vehicle includes a sensor configured to detect a vehicle parameter including at least a bogie load on a bogie of the vehicle, and a control module in communication with the sensor. The control module is configured to calculate a kingpin torque based on a sensed bogie load and wheel body displacement of the vehicle, determine a roll steering angle based on the wheel body displacement of the vehicle, determine a road wheel angle of the vehicle based on the roll steering angle and the kingpin torque, and generating a signal indicative of the road wheel angle to control at least one vehicle control system. Other example vehicle systems and methods for determining road wheel angles of a vehicle are also disclosed.

Description

[0001] Introduction

[0002] The information provided in this section is for the purpose of presenting the context of the present disclosure in general. The work of the presently named inventors, to the extent it is described in this section and to the aspects that may not otherwise be counted as prior art at the time of filing, is neither expressly nor implicitly admitted to be prior art with respect to the present disclosure.

[0003] The present disclosure relates to vehicle systems and methods for estimating road wheel angles.

[0004] A vehicle includes a control system for controlling the movement of the vehicle. Such a control system can include, for example, electric all-wheel drive control, torque vectoring control, active rear steering control, stability control, etc. In many cases, the control systems and / or state estimation algorithms in a vehicle rely on various inputs for control purposes. For example, the inputs can include a road wheel angle (RWA) input, which can be used for yaw rate estimation, slip angle estimation, under-steer angle estimation, etc. Summary of the Invention

[0005] A vehicle system for determining a road wheel angle of a vehicle includes a plurality of sensors configured to detect a plurality of vehicle parameters, the plurality of vehicle parameters including at least a steering rack load on a steering rack of the vehicle; and a control module in communication with the plurality of sensors. The control module is configured to calculate a kingpin torque based on the sensed steering rack load and wheel-to-body displacement of the vehicle, determine a roll steer angle based on the wheel-to-body displacement of the vehicle, determine the road wheel angle of the vehicle based on the roll steer angle and the kingpin torque, and generate a signal indicative of the road wheel angle to control at least one vehicle control system.

[0006] In other features, the plurality of sensors includes at least one wheel-to-body sensor configured to detect the wheel-to-body displacement of the vehicle, and the control module is configured to receive the wheel-to-body displacement of the vehicle from the at least one wheel-to-body sensor.

[0007] In other features, the plurality of sensors includes at least one vertical acceleration sensor configured to detect the vertical acceleration of the vehicle, and the control module is configured to receive the vertical acceleration of the vehicle and determine the wheel-to-body displacement of the vehicle based on the vertical acceleration of the vehicle.

[0008] Among other features, the plurality of sensors includes a vehicle body-based acceleration sensor configured to detect the longitudinal acceleration of the vehicle, and the control module is configured to receive the longitudinal acceleration of the vehicle and determine the displacement of the vehicle's wheel bodies based on the vertical acceleration of the vehicle and the longitudinal acceleration of the vehicle.

[0009] Among other features, the plurality of vehicle parameters includes the steering wheel angle, and the control module is configured to determine the length of the steering arm of the vehicle based on the steering wheel angle and the displacement of the vehicle's wheel bodies, and calculate the kingpin torque based on the sensed bogie load and the steering arm length.

[0010] Among other features, the plurality of vehicle parameters includes the steering wheel angle, and the control module is configured to determine the estimated road wheel angle based on the steering wheel angle, and determine the road wheel angle of the vehicle based on the roll steer angle, the kingpin torque, and the estimated road wheel angle.

[0011] Among other features, the control module is configured to convert the kingpin torque into a compliance steering angle, apply a low-pass filter to the compliance steering angle to generate a filtered compliance steering angle, and determine the road wheel angle of the vehicle based on the filtered compliance steering angle and the roll steer angle.

[0012] Among other features, the control module is configured to determine the wheel body displacement values on the left and right sides of the vehicle, convert the wheel body displacement values into roll steer angles, apply a filter to the roll steer angles to generate filtered roll steer angles, and determine the road wheel angle of the vehicle based on the filtered roll steer angles and the filtered compliance steering angles.

[0013] Among other features, the filter is a Kalman filter.

[0014] Among other features, the control module is configured to determine the aligning torque of the vehicle based on the kingpin torque and the wheel torque, and determine the road wheel angle of the vehicle based on the roll steer angle, the kingpin torque, and the aligning torque.

[0015] Among other features, the plurality of sensors includes a vehicle speed sensor configured to detect the speed of the vehicle, and the control module is configured to receive the speed of the vehicle and determine the aligning torque of the vehicle based on the kingpin torque, the wheel torque, and the speed of the vehicle.

[0016] Among other features, the vehicle system further includes a vehicle control module in communication with the control module. The vehicle control module is configured to receive a road wheel angle signal from the control module and control at least one vehicle control system based on the road wheel angle signal.

[0017] Among other features, the vehicle includes a vehicle system configured to determine the road wheel angle of the vehicle.

[0018] A method for determining the road wheel angle of a vehicle includes determining a kingpin torque based on the bogie load and wheel body displacement of the vehicle, determining a roll steer angle based on the wheel body displacement of the vehicle, determining the road wheel angle of the vehicle based on the roll steer angle and the kingpin torque, and generating a signal indicative of the road wheel angle to control at least one vehicle control system.

[0019] Among other features, the method further includes determining the wheel body displacement of the vehicle.

[0020] Among other features, determining the wheel body displacement of the vehicle includes sensing the wheel body displacement of the vehicle via at least one wheel body sensor, or sensing the vertical acceleration of the vehicle via at least one vertical acceleration sensor, and determining the wheel body displacement of the vehicle based on the vertical acceleration of the vehicle.

[0021] Among other features, the method further includes sensing the longitudinal acceleration of the vehicle via a vehicle body-based acceleration sensor.

[0022] Among other features, determining the wheel body displacement of the vehicle includes determining the wheel body displacement based on the vertical acceleration of the vehicle and the longitudinal acceleration of the vehicle.

[0023] Among other features, the method further includes determining the steering arm length of the vehicle based on the steering wheel angle and the wheel body displacement of the vehicle.

[0024] Among other features, calculating the kingpin torque includes calculating the kingpin torque based on the bogie load and the steering arm length.

[0025] Among other features, the method further includes determining an estimated road wheel angle based on the steering wheel angle.

[0026] Among other features, determining the road wheel angle of the vehicle includes determining the road wheel angle of the vehicle based on the roll steer angle, the kingpin torque, and the estimated road wheel angle.

[0027] Among other features, the method further includes sensing the speed of the vehicle via a vehicle speed sensor, and determining the self-aligning torque of the vehicle based on the kingpin torque, the wheel torque, and the speed of the vehicle.

[0028] Among other features, determining the road wheel angle includes determining the road wheel angle of the vehicle based on the roll steer angle, the kingpin torque, and the self-aligning torque.

[0029] Among other features, the method further includes controlling at least one vehicle control system based on the generated road wheel angle signal.

[0030] A vehicle system for determining a road wheel angle of a vehicle is disclosed. The vehicle system includes: a plurality of sensors configured to detect a plurality of vehicle parameters including at least a bogie load on a bogie of the vehicle; and a control module in communication with the plurality of sensors, the control module being configured to: calculate a kingpin torque based on a sensed bogie load and a wheel body displacement of the vehicle; determine a roll steer angle based on a wheel body displacement of the vehicle; determine a road wheel angle of the vehicle based on the roll steer angle and the kingpin torque; and generate a signal indicative of the road wheel angle to control at least one vehicle control system.

[0031] In other features, the plurality of sensors includes at least one wheel body sensor configured to detect a wheel body displacement of the vehicle; and the control module is configured to receive the wheel body displacement of the vehicle from the at least one wheel body sensor.

[0032] In other features, the plurality of sensors includes at least one vertical acceleration sensor configured to detect a vertical acceleration of the vehicle; and the control module, configured to receive the vertical acceleration of the vehicle and determine the wheel body displacement of the vehicle based on the vertical acceleration of the vehicle.

[0033] In other features, the plurality of sensors includes a body-based acceleration sensor configured to detect a longitudinal acceleration of the vehicle; and the control module is configured to receive the longitudinal acceleration of the vehicle and determine the wheel body displacement of the vehicle based on the vertical acceleration of the vehicle and the longitudinal acceleration of the vehicle.

[0034] In other features, the plurality of vehicle parameters includes a steering wheel angle; and the control module is configured to determine a steering arm length of the vehicle based on the steering wheel angle and the wheel body displacement of the vehicle, and calculate the kingpin torque based on the sensed bogie load and the steering arm length.

[0035] In other features, the plurality of vehicle parameters includes a steering wheel angle; and the control module is configured to determine an estimated road wheel angle based on the steering wheel angle, and determine the road wheel angle of the vehicle based on the roll steer angle, the kingpin torque, and the estimated road wheel angle.

[0036] In other features, the control module is configured to: convert the kingpin torque to a compliant steer angle; apply a low-pass filter to the compliant steer angle to generate a filtered compliant steer angle; and determine the road wheel angle of the vehicle based on the filtered compliant steer angle and the roll steer angle.

[0037] Among other features, the control module is configured to: determine the wheel body displacement values for the left and right sides of the vehicle; convert the wheel body displacement values into roll steer angles; apply a filter to the roll steer angles to generate filtered roll steer angles; and determine the road wheel angles of the vehicle based on the filtered roll steer angles and the filtered compliance steer angles.

[0038] Among other features, the filter is a Kalman filter.

[0039] Among other features, the control module is configured to: determine the self-aligning moment of the vehicle based on the kingpin torque and the wheel torque; and determine the road wheel angles of the vehicle based on the roll steer angles, the kingpin torque, and the self-aligning moment.

[0040] Among other features, the plurality of sensors includes a vehicle speed sensor configured to detect the speed of the vehicle; and the control module is configured to receive the speed of the vehicle and determine the self-aligning moment of the vehicle based on the kingpin torque, the wheel torque, and the speed of the vehicle.

[0041] Among other features, there is also a vehicle control module in communication with the control module, the vehicle control module being configured to: receive a road wheel angle signal from the control module; and control at least one vehicle control system based on the road wheel angle signal.

[0042] A vehicle is disclosed, including the vehicle system according to claim 12 configured to determine the road wheel angles of the vehicle.

[0043] A method for determining the road wheel angles of a vehicle is disclosed, the method including: determining the kingpin torque based on the bogie load and the wheel body displacement of the vehicle; determining the roll steer angle based on the wheel body displacement of the vehicle; determining the road wheel angles of the vehicle based on the roll steer angle and the kingpin torque; and generating a signal indicative of the road wheel angles to control at least one vehicle control system.

[0044] Among other features, it also includes determining the wheel body displacement of the vehicle, wherein determining the wheel body displacement of the vehicle includes: sensing the wheel body displacement of the vehicle via at least one wheel body sensor; or sensing the vertical acceleration of the vehicle via at least one vertical acceleration sensor and determining the wheel body displacement of the vehicle based on the vertical acceleration of the vehicle.

[0045] Among other features, the method further includes sensing the longitudinal acceleration of the vehicle via a body-based acceleration sensor; and determining the wheel body displacement of the vehicle includes determining the wheel body displacement based on the vertical acceleration and the longitudinal acceleration of the vehicle.

[0046] Among other features, the method further includes determining a steering arm length of the vehicle based on a steering wheel angle and a wheel body displacement of the vehicle; and calculating a kingpin torque includes calculating the kingpin torque based on a bogie load and the steering arm length.

[0047] Among other features, the method further includes determining an estimated road wheel angle based on the steering wheel angle; and determining the road wheel angle of the vehicle includes determining the road wheel angle of the vehicle based on a roll steer angle, a kingpin torque, and the estimated road wheel angle.

[0048] Among other features, the method further includes sensing a speed of the vehicle via a vehicle speed sensor and determining a self-aligning torque of the vehicle based on the kingpin torque, a wheel torque, and the speed of the vehicle; and determining the road wheel angle includes determining the road wheel angle of the vehicle based on the roll steer angle, the kingpin torque, and the self-aligning torque.

[0049] Among other features, it further includes controlling at least one vehicle control system based on the generated road wheel angle signal.

[0050] According to the detailed description, the claims, and the drawings, further applicable fields of the present disclosure will become apparent. The detailed description and specific examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The present disclosure will be more fully understood according to the detailed description and the drawings, wherein:

[0052] Figure 1 is a functional block diagram of an example vehicle system for determining the RWA of a vehicle according to the present disclosure;

[0053] Figure 2 is a vehicle including a part of a vehicle system according to the present disclosure Figure 1 of the vehicle system;

[0054] Figure 3 is a vehicle including a Figure 1 functional block diagram of a vehicle of a vehicle system according to the present disclosure;

[0055] Figures 4 - 7 is a flowchart of an example control process for determining the RWA of a vehicle according to the present disclosure;

[0056] Figure 8 is for Figure 1 a flowchart of an example process for designing a filter for a vehicle system according to the present disclosure.

[0057] In the drawings, reference numerals may be repeated to identify similar and / or identical elements. DETAILED DESCRIPTION

[0058] The control system of a vehicle relies on various inputs to control different aspects of the vehicle. In many cases, one of the key inputs used by the control system and / or the state estimation algorithm is the Road Wheel Angle (RWA) input. When estimating or determining the yaw rate, slip angle, understeer angle, etc., the RWA is typically a key input in vehicle motion control. Therefore, the accuracy of the RWA is an important factor in vehicle control.

[0059] The RWA (or sometimes referred to as the road steering angle) refers to the angle of the vehicle's wheels relative to the longitudinal axis (or X-axis) of the vehicle. For example, when the wheels are not turned, the longitudinal axis of the wheel that extends radially along the diameter of the wheel and is parallel to the road surface is at 0°. When not turned, the longitudinal axis of the wheel extends parallel to the longitudinal (or X) axis of the vehicle. When the wheel is turned to the right, the longitudinal axis of the wheel forms a positive (or negative) angle relative to the longitudinal axis of the vehicle. When the wheel is turned to the left, the longitudinal axis of the wheel forms a negative (or positive) angle relative to the longitudinal axis of the vehicle.

[0060] Conventionally, the RWA is estimated by assuming a simple kinematic ratio relationship between the steering wheel angle and the RWA. For example, a fixed ratio of 1 / 10 can be adopted for all conditions. In such an example, if the sensed steering wheel angle is ten degrees (e.g., the driver rotates the steering wheel by ten degrees), the estimated RWA is one. In other examples, the kinematic ratio can be a linear or non-linear function of the steering wheel angle. However, during dynamic maneuvers, the conventional methods for estimating the RWA often result in a significant difference between the estimated kinematic RWA and the actual RWA.

[0061] The vehicle systems and methods according to the present disclosure utilize various factors that affect the RWA in addition to the steering wheel angle to generate an accurate and reliable RWA estimate for the control system in the vehicle. For example, compared with the conventional methods for RWA estimation, the vehicle systems and methods herein utilize the bogie force and the wheel body displacement signal to compensate for the compliant steering (e.g., due to kingpin torque) generated by the suspension system and the roll steer in the vehicle (e.g., due to vehicle roll motion). This technical solution based on multiple factors provides a more accurate and reliable RWA estimate for the control system in the vehicle compared with the conventional methods.

[0062] Now referring Figure 1 , a block diagram of an example vehicle system 100 for estimating or otherwise determining the RWA of a vehicle is presented. As Figure 1 shown, the vehicle system 100 generally includes a control module 102, a vehicle control module 104, a memory circuit 106 that stores one or more look-up tables 124, and various sensors for detecting or sensing vehicle parameters. In Figure 1In the example, the sensors may include one or more vertical acceleration sensors 108, longitudinal acceleration sensors 110, suspension sensors 112, one or more wheel body sensors 114, a steering wheel angle sensor 116, a vehicle speed sensor 118, and one or more wheel torque sensors 120.

[0063] Although Figure 1 the vehicle system 100 is shown as including specific modules, it should be understood that one or more other modules may be employed if desired. Additionally, while the vehicle system 100 is shown as including multiple separate modules, any combination and / or their functionality of these modules (e.g., the control module 102, the vehicle control module 104, etc.) may be integrated into one or more modules. Furthermore, although Figure 1 the vehicle system 100 is shown as including specific sensors, it should be understood that the system 100 and / or other systems may include more or fewer sensors, sensors with different functionality, etc.

[0064] In various embodiments, the modules and sensors of the vehicle system 100 may communicate with each other and may share parameters via a network 122 such as a controller area network (CAN). In such an example, the parameters may be shared via one or more data buses of the network 122. Thus, a given module and / or sensor may make various parameters available to other modules and / or sensors via the network 122.

[0065] Figure 1 the vehicle system 100 may be employed in any suitable vehicle, such as an electric vehicle (e.g., a pure electric vehicle, a plug-in hybrid electric vehicle, etc.), an internal combustion engine vehicle, etc. Additionally, the vehicle system 100 may be applicable to autonomous vehicles, semi-autonomous vehicles, etc. For example, Figure 2 depicts a vehicle 200 that includes Figure 1 the control module 102 and the vehicle control module 104, and sensors 250 (e.g., (one or more) vertical acceleration sensors 108, longitudinal acceleration sensors 110, suspension sensors 112, (one or more) wheel body sensors 114, a steering wheel angle sensor 116, a vehicle speed sensor 118, (one or more) wheel torque sensors 120, etc.) that communicate with the control module 102 and / or the vehicle control module 104.

[0066] Continuing to refer to Figure 1, the acceleration sensors 108, 110 can be accelerometers and / or other suitable sensors for generally detecting acceleration components associated with the vehicle. For example, the longitudinal acceleration sensor 110 (e.g., a body-based acceleration sensor) can optionally be used in the vehicle system 100 to detect the longitudinal acceleration of the vehicle. In other words, the sensor 110 detects the change in speed along the longitudinal axis (e.g., length) of the vehicle. The (one or more) vertical acceleration sensors 108 can optionally be used in the vehicle system 100 to detect the vertical acceleration of the vehicle near one or more corners of the vehicle. For example, the vehicle system 100 can include one of the acceleration sensors 108 near each wheel of the vehicle. In such an example, each acceleration sensor 108 detects the change in speed along the vertical axis (e.g., height) of the vehicle at its adjacent wheel.

[0067] Figure 1 The bogie force sensor 112 generally measures the forces on the axles, screws, and / or gears of the bogie in the vehicle. For example, the bogie force sensor 112 can detect the force (e.g., bogie load) transmitted from the front or rear tires of the vehicle to the bogie through a tie rod. In such an example, the transmitted force results from the interaction of the tire with the ground (e.g., road, etc.). In other examples, the bogie force can be estimated based on steering system signals (e.g., steering motor torque, motor position, and motor speed) and vehicle signals (e.g., vehicle yaw rate and vehicle speed).

[0068] The sensors 114, 116, 118, 120 generally detect additional parameters associated with the vehicle. For example, the (one or more) wheel body sensors 114 can optionally be used in the vehicle system 100 to measure the relative linear displacement between the wheels and the body (or frame) of the vehicle. Additionally, the (one or more) wheel torque sensors 120 can optionally be used in the vehicle system 100 to measure the torque at the wheels of the vehicle. For example, each wheel torque sensor 120 can measure the torque (or moment) about any suitable axis (e.g., the y-axis, etc.) around one of the wheels. In some examples, the vehicle system 100 can include one of the wheel torque sensors 120 and one of the wheel body sensors 114 near each wheel of the vehicle. In other examples, the wheel torque can be estimated based on motor or engine torque and other signals. Additionally, Figure 1 the vehicle speed sensor 118 generally measures the speed or rate along the longitudinal axis of the vehicle, and the steering wheel angle sensor 116 generally monitors the rotational position, movement, etc. of the steering wheel of the vehicle to generate a steering wheel angle.

[0069] In various embodiments, Figure 1The vehicle system 100 can be adapted to estimate or otherwise determine the RWA of the vehicle. This determination can be based on various vehicle parameters, as further explained herein. For example, when making an RWA determination, the control module 102 can consider suspension and steering conditions. In various examples, in addition to conventional techniques that rely on the steering wheel angle, the control module 102 can also utilize these conditions to generate an accurate and reliable RWA estimate for the control system in the vehicle. Additionally, and as further explained, when determining the RWA, the control module 102 can optionally consider tire parameters.

[0070] For example, with respect to suspension effects, the control module 102 can rely on kingpin torque when making an RWA determination. For example, the control module 102 can calculate the kingpin torque of the vehicle based on the bogie load and wheel body displacement of the vehicle. In such an example, the control module 102 can receive a signal indicating the bogie load from the bogie force sensor 112.

[0071] In such an example, the wheel body displacement can be obtained in various ways, any of which can be suitable for use when making an RWA determination. For example, if there are wheel body sensors (e.g., Figure 1 one or more of the wheel body sensors 114), then the control module 102 can receive one or more signals indicating the wheel body displacement from one or more of the one or more wheel body sensors 114. In other examples, the vehicle may not include wheel body sensors. In such an example, the control module 102 can determine the wheel body displacement of the vehicle based on the vertical acceleration of the vehicle.

[0072] For example, the control module 102 can receive one or more signals from the acceleration sensors 108 located near each wheel of the vehicle. In such an example, each signal can indicate the vertical acceleration component at one of the wheels of the vehicle. Then, the control module 102 can determine the wheel body displacement based on the vertical acceleration data. For example, the control module 102 can integrate the acceleration data twice to transform the acceleration data into a velocity component and then convert it into a distance component (e.g., wheel body displacement). In various embodiments, the control module 102 can receive the vertical acceleration data after calibrating the initial ride height position of the vehicle. In some examples, the control module 102 can also reset to this position during a steady state to clear any errors.

[0073] In various embodiments, when the control module 102 transforms the vertical acceleration data into wheel body displacement due to integration, unwanted noise may be generated. In such an example, the control module 102 can apply one or more filters, such as high-pass filters, low-pass filters, band-pass filters, etc., to eliminate high-frequency and low-frequency noise from the accelerometer signal (e.g., high-frequency road texture and low-frequency sensor drift).

[0074] In some examples, wheel body displacement can be determined without sensor data. For example, when the vehicle is experiencing significant wheel body displacement, the (one or more) vertical acceleration sensors 108 may generate unwanted noise. Thus, during periods when the (one or more) vertical acceleration sensors 108 are dynamically changing, the control module 102 can perform integration based on suspension parameters and system effective inertia to estimate the relative position of the wheel body without data from the sensors (e.g., without continuous data). In such examples, the control module 102 can generally predict movement near the wheel based on the initial state of the (one or more) acceleration sensors 108 and a prediction model of the (one or more) acceleration sensors 108.

[0075] Additionally, the control module 102 can optionally rely on the vehicle's body-based acceleration to obtain a more accurate wheel body displacement. For example, the control module 102 can receive a signal indicating the longitudinal acceleration of the vehicle from the longitudinal acceleration sensor 110 and then determine the wheel body displacement of the vehicle based on the vertical acceleration of the vehicle and the longitudinal acceleration of the vehicle.

[0076] In various embodiments, the kingpin torque can be determined based in part on the steering wheel angle. For example, the control module 102 can receive a signal indicating the steering wheel angle from the steering wheel angle sensor 116 and then determine the steering arm length of the vehicle based on the received steering wheel angle of the vehicle and the wheel body displacement. In such examples, the steering arm length can represent the shortest distance between the vehicle's suspension steering axis and the bogie attachment of the vehicle to the wheel carrier. In some examples, the control module 102 can use a look-up table (e.g., one of the look-up tables 124 stored in the memory circuit 106) to determine a steering arm length value based on the corresponding steering wheel angle and wheel body displacement values in the table. In other examples, the control module 102 can apply a function to determine the steering arm length based on the steering wheel angle and wheel body displacement values. Then, once the steering arm length is obtained, the control module 102 can calculate the kingpin torque by multiplying the sensed bogie load by the steering arm length.

[0077] In addition, and as described above, when performing RWA determination, the control module 102 can rely on steering conditions. For example, with regard to steering effects, the control module 102 can rely on the roll steer angle of the vehicle when performing RWA determination. The roll steer angle can represent the steering angle of the steered wheel during a rolling action of the vehicle body caused by, for example, a turning maneuver, a collision, etc. For example, the control module 102 can calculate or otherwise determine the roll steer angle based on the wheel body displacement of the vehicle. For example, the control module 102 can obtain the wheel body displacement explained herein. Then, the control module 102 can use a look-up table (e.g., one of the look-up tables 124 stored in the memory circuit 106) to convert the wheel body displacement value into a roll steer angle value. In other examples, the control module 102 can apply a function to determine the roll steer angle based on the wheel body displacement value.

[0078] Then, the control module 102 can determine the RWA of the vehicle based on the roll steer angle and the kingpin torque. For example, in Figure 1 it, the control module 102 converts the kingpin torque into a compliant steer angle, which generally represents the amount of self-steering generated by the vehicle's suspension system when it is subjected to a turning (e.g., lateral) load. In such an example, the control module 102 can use a look-up table (e.g., one of the look-up tables 124 stored in the memory circuit 106) or apply a function to determine the compliant steer angle based on the kingpin torque value. Then, the control module 102 can combine the compliant steer angle and the roll steer angle to estimate the RWA of the vehicle. In various embodiments, the control module 102 can apply functions, weighting values, etc. to estimate the RWA of the vehicle based on the compliant steer angle and the roll steer angle.

[0079] In addition, in some embodiments, one or more filters are applied to the compliant steer angle and the roll steer angle before using such parameters to estimate the RWA of the vehicle. For example, the control module 102 can apply filters to the compliant steer angle and the roll steer angle to generate a filtered steer angle and a filtered roll steer angle. Then, the control module 102 can determine the RWA of the vehicle based on the filtered compliant steer angle and the filtered roll steer angle.

[0080] In Figure 1In an example, the filter applied to the roll steer angle can be any suitable filter. For example, the filter can be a conventional Kalman filter for removing displacement sensor noise or another suitable type of filter. In such an example, the Kalman filter can receive inputs such as the covariance of process noise and the covariance of measurement noise. The covariance of process noise can depend on, for example, vehicle design (e.g., one vehicle may have less process noise than another due to, for example, different centers of gravity, different masses, different suspensions, etc.) and active roll control and damper technology. The covariance of measurement noise can depend on, for example, the displacement sensor noise level.

[0081] In various embodiments, the filter applied to the compliance steer angle can be a low-pass filter specifically designed to capture the response from kingpin torque to RWA and obtain the kingpin torque versus RWA relationship. For example, the low-pass filter can have a first-order filter structure (e.g., a simpler form of filter) or a second-order filter structure (e.g., a more complex form of filter).

[0082] The low-pass filter can be designed in any suitable manner. For example, the control module 102 and / or another module in or external to the system 100 can obtain frequency sweep data from one or more vehicle tests or simulations. Such data can include, for example, steering wheel angle (e.g., 30 degrees, etc.), frequency sweep range (e.g., 0 - 5 Hz sweep), recorded filtered roll steer angle, compliance steer angle, front (or rear) RWA, etc. Then, a specific low-pass filter structure (e.g., first-order filter structure, second-order filter structure, etc.) is selected, and a Bode plot is obtained using a function (e.g., MATLAB tfestimate, etc.). Next, the selected low-pass filter structure can be optimized to obtain low-pass filter parameters. For example, subject to model parameter ranges (e.g., all parameters are positive), the low-pass filter structure can be optimized according to equation (1) below. In equation (1), h1 and h2 are the start and end frequencies of integration, W(h) is the weighting function (a function of frequency h), Data(h) is the magnitude / phase response (in dB) of the Bode plot from experimental data, and ModelFit(h) is the magnitude / phase response (in dB) of the selected low-pass filter structure with parameter values (e.g., T, Z, ω n ) to be determined.

[0083] Equation (1)

[0084] In various embodiments, when performing RWA determination, control module 102 may optionally utilize conventional techniques that depend on the steering wheel angle. For example, and as described above, control module 102 may receive a signal indicative of the steering wheel angle. Then, control module 102 may determine an estimated RWA based on the steering wheel angle according to conventional techniques. For example, control module 102 may determine the estimated RWA by applying the kinematic ratio relationship between the steering wheel angle and the RWA, as explained herein. Then, control module 102 may determine the RWA of the vehicle based on the roll steer angle, the compliance steer angle (e.g., based on the kingpin torque), and the estimated RWA. In such an example, control module 102 may apply functions, weighting values, etc. to determine the RWA of the vehicle, as explained herein.

[0085] Continuing to refer Figure 1 , as described above, when determining the RWA, control module 102 may optionally utilize tire parameters. For example, control module 102 may calculate tire parameters such as tire traction, lateral force, and aligning torque, as further explained herein, and then use such parameters when determining the RWA.

[0086] For example, control module 102 may determine one or more tire parameters based on the wheel torque associated with one or more wheels of the vehicle. For example, control module 102 may determine the aligning torque of the vehicle based on the kingpin torque and the wheel torque. In some examples, the aligning torque may be determined based on the speed of the vehicle (e.g., received by vehicle speed sensor 118) in addition to the wheel torque and the kingpin torque. Further, control module 102 may determine the traction of one or more tires of the vehicle. In such an example, the traction may be calculated based on, for example, the wheel torque of the tire / wheel (e.g., the torque My representing the moment about the y-axis of the wheel) and the radius of the tire. In such an example, the wheel torque may be obtained from a wheel torque sensor 120 associated with one of the wheels of the vehicle. In other examples, the wheel torque may be estimated by conventional methods such as based on known engine torque, gear ratio, and drive ratio.

[0087] In addition, control module 102 may determine other tire parameters based on the aligning torque for use in determining the RWA of the vehicle. For example, in some examples, control module 102 may determine the lateral tire force and the tire aligning torque based on the aligning torque. In such an example, the lateral tire force and the tire aligning torque may be determined based on the pneumatic trail and / or the mechanical trail of the tire in addition to the aligning torque.

[0088] Then, the control module 102 can determine the RWA of the vehicle based in part on the restoring torque, the traction force, the lateral tire force, and / or the tire restoring torque. In such an example, the control module 102 can convert such torque / force values into angular values and then determine the RWA of the vehicle based in part on the angular values. In various embodiments, the angular values can be obtained using one or more look-up tables (e.g., one or more look-up tables 124 stored in the memory circuit 106) or using implemented functions.

[0089] Continuing to refer Figure 1 , the control module 102 can determine the RWA based on the vehicle parameters referred to above. For example, the control module 102 can determine the RWA by combining two or more of the suspension parameters, the steering parameters, the tire parameters, the estimated RWA, etc. according to a desired function. In such an example, the function can be a second-order transfer function or another suitable function that compensates for dynamic delays.

[0090] Then, the control module 102 generates one or more signals indicative of the determined RWA and transmits them to the vehicle control module 104. Once received, the vehicle control module 104 can control at least one vehicle control system based on the RWA signal. For example, the vehicle control module 104 can be used to control vehicle control systems such as electric all-wheel drive control, torque vectoring control, active rear steering control, stability control, etc. based on the RWA. Additionally, in various embodiments, the vehicle control module 104 can use the RWA as an input to determine the yaw rate, the slip angle, the understeer angle, etc. for vehicle control purposes.

[0091] Figure 3 Depicts a vehicle 300 including Figure 1 system 100. As shown, system 100 includes a control module 102, a vehicle control module 104, one or more vertical acceleration sensors 108, a longitudinal acceleration sensor 110, a strut force sensor 112, one or more wheel body sensors 114, a steering wheel angle sensor 116, a vehicle speed sensor 118, and one or more wheel torque sensors 120, and Figure 1 memory circuit 106 (with one or more tables 124 stored therein). Additionally, Figure 3 system 100 includes a steering wheel 304, four wheels 350, and a suspension system 312. Although the vertical acceleration sensor 108, the wheel body sensor 114, and the wheel torque sensor 120 are shown in Figure 3 as being located at one of the wheels 350, it should be understood that the vertical acceleration sensor 108, the wheel body sensor 114, and the wheel torque sensor 120 can form a set of sensors 308 that can be located at each wheel 350.

[0092] like Figure 3 As shown in FIG. 1 , the suspension system 312 includes a bogie 320 having a bogie force sensor 112. In such an example, the position of the bogie 320 can be controlled by a control module (e.g., control module 102, vehicle control module 104, etc.) in a conventional manner. Figure 3 In the example of FIG. 3 , suspension system 312 is a front suspension system. In other examples, suspension system 312 may be a rear suspension system.

[0093] Figures 4 - 7 Shows Figure 1 The vehicle system 100 may be used to estimate or otherwise determine a vehicle (e.g., Figure 2 200 vehicles, Figure 3 Example control processes 400, 500, 600, 700 for RWA of a vehicle 300, etc. are provided. Although the control module 102 includes Figure 1 The example control processes 400 , 500 , 600 , 700 are described with reference to the vehicle system 100 , but any of the control processes 400 , 500 , 600 , 700 may be employed by another suitable system.

[0094] exist Figure 4 , the control process 400 begins by receiving various inputs. For example, the control module 102 receives a steering wheel angle 408, a wheel displacement 410, a truck force or load 412, a wheel torque 414, and a vehicle speed 416. In such an example, the steering wheel angle 408, the truck load 412, the wheel torque 414, and the vehicle speed 416 may be provided by the steering wheel angle sensor 116, the truck force sensor 112, the wheel torque sensor 120, and the vehicle speed sensor 118, respectively, as explained herein. In addition, the wheel displacement 410 may be provided by the wheel sensor 114, if available or determined based on the vertical acceleration of the vehicle (e.g., provided by the vertical acceleration sensor 108), as explained herein.

[0095] The control process 400 then determines the RWA of the vehicle by taking into account different vehicle parameters such as suspension parameters, steering parameters, tire parameters, etc. In such an example, the control process 400 includes a control path 404, represented by a dashed box, for determining suspension and steering parameters, and an optional control path 406, represented by a dashed-dotted-dashed box, for determining tire parameters. Additionally, when determining the RWA of the vehicle, the control process 400 may include another control path 402 to account for conventional techniques for estimating RWA.

[0096] In control path 402, control module 102 estimates RWA according to conventional techniques. For example, and as described above, control module 102 can determine the estimated RWA 420 by applying the kinematic ratio relationship 418 between the received steering wheel angle 408 and the RWA.

[0097] In control path 404, the compliant steering angle and the roll steering angle are calculated for use in determining the vehicle's RWA. For example, control module 102 obtains the steering arm length 424 from the look-up table 422 based on the received steering wheel angle 408 and the wheel body displacement 410. Then, control module 102 multiplies the steering arm length 424 by the bogie load 412 (at block 426) to obtain the kingpin torque 428. Then, as shown, control module 102 obtains the compliant steering angle 432 based on the kingpin torque 428 according to the look-up table 430 (or according to the desired function). Next, control module 102 applies the filter 434 to the compliant steering angle 432 to obtain the filtered compliant steering angle 436. In such an example, the filter 434 can be a low-pass filter specifically designed to capture the relationship between the kingpin torque 428 and the RWA, as explained herein.

[0098] To determine the roll steering angle, control module 102 can implement a look-up table or a desired function. Specifically, in the Figure 4 example, control module 102 obtains the roll steering angle 440 from the look-up table 438 based on the received wheel body displacement 410. Then, control module 102 applies the filter 442 to the roll steering angle 440 to obtain the filtered roll steering angle 444. In such an example, the filter 442 can be a conventional Kalman filter or another suitable filter, as explained herein.

[0099] In the alternative control path 406, the lateral tire force, the tire self-aligning moment, and the traction force (e.g., its annular representation) are calculated for use in determining the vehicle's RWA. For example, control module 102 determines the induced traction force 448 based on the wheel torque 414 (e.g., the moment My representing the moment about the y-axis of the wheel), the tire radius, and the scrub radius. In such an example, the tire radius and the scrub radius can be stored in a memory (represented by block 446), such as the Figure 1 memory circuit 106 of. Then, at block 450, control module 102 compares the kingpin torque 428 and the induced traction force 448 and generates an output 452. In addition, control module 102 obtains the self-aligning moment percentage 456 from the look-up table 454 (or according to the desired function) based on the received vehicle speed 416. Then, control module 102 multiplies the self-aligning moment percentage 456 and the output 452 (at block 458) to obtain the self-aligning moment 460.

[0100] Next, the control module 102 calculates a lateral tire force 464 (represented by block 462) based on the restoring moment 460 and the mechanical trail and tire scrub radius, converts the lateral tire force 464 to a lateral tire angle 468, and applies one or more filters 470 to obtain a filtered lateral tire angle 472. Additionally, the control module 102 calculates a tire restoring moment 476. In such an example, the tire restoring moment 476 (represented by block 474) is determined based on the lateral tire force 464 and the tire scrub radius. Then, the control module 102 converts the tire restoring moment 476 to a tire restoring angle 480 and applies one or more filters 482 to obtain a filtered tire restoring angle 484. In such an example, the conversion to the angle value can be implemented via a look-up table 466, 478, or a desired function.

[0101] Additionally, the control module 102 calculates a traction force 487 (represented by block 486) according to a traction force function. In such an example, the traction force 487 can be calculated based on the received wheel torque 414 and the tire radius. Then, the control module 102 converts the traction force 487 to a traction angle 490 and applies one or more filters 491 to obtain a filtered traction angle 492. In such an example, the conversion to the angle value can be implemented via a look-up table 488 or a desired function.

[0102] Then, the control module 102 determines the RWA of the vehicle based on the estimated RWA 420, the filtered compliant steering angle 436, and the filtered roll steer angle 444. In some alternative embodiments, if desired, the control module 102 may also consider the filtered lateral tire angle 472, the filtered tire restoring angle 484, and the filtered traction angle 492. For example, the control module 102 may combine (represented by block 494) the estimated RWA 420, the filtered compliant steering angle 436, the filtered roll steer angle 444, the filtered lateral tire angle 472, the filtered tire restoring angle 484, and the filtered traction angle 492, and then determine the RWA according to a desired function such as a second-order transfer function 496 or another suitable function that compensates for the dynamic delay. Next, as explained herein, the control module 102 may generate one or more signals 498 indicating the determined RWA to the vehicle control module 104.

[0103] Figure 5 Depicts an example control process 500 for implementing Figure 4 a portion of the control path 404. As shown, the control process 500 includes receiving wheel body displacement values 502, 510 at the left and right front (or rear) sides of the vehicle, and Figure 4The steering wheel angle 408. The wheel body displacement values 502, 510 can be provided by a separate wheel body sensor 114, if available or determined based on the vertical acceleration of the vehicle (e.g., provided by a separate vertical acceleration sensor 108), as explained herein. Then, the control module 102 compares (at block 516) the outputs obtained from the look-up tables 512, 514 based on the wheel body displacement values 502, 510 and the steering wheel angle 408. Then, the control module 102 determines the steering arm length 424 based on this comparison. Next, the control module 102 multiplies the steering arm length 424 and the bogie load 412 (at block 426) to obtain the kingpin torque 428, as explained herein. Then, the control module 102 obtains the compliant steering angle 432 according to the look-up table 430 and applies a filter 434 to obtain the filtered compliant steering angle 436.

[0104] Figure 6 Depicts an example control process 600 for implementing Figure 4 Another part of the control path 404. As shown, the control process 600 includes receiving the Figure 5 Wheel body displacement values 502, 510 on the left and right sides of the vehicle. Then, the control module 102 determines Figure 4 The roll steering angle 440 by comparing (at block 616) the outputs obtained from the look-up tables 612, 614 based on the wheel body displacement values 502, 510. Next, the control module 102 applies a filter 442 to the roll steering angle 440 to obtain the filtered roll steering angle 444, as explained herein.

[0105] Figure 7 Depicts an example control process 700 for implementing Figure 4 The control path 406. As shown, the control process 700 includes receiving the wheel torque values 714, the tire radius 702, and the vehicle speed 416 on the left and right front (or rear) sides of the vehicle. Then, the control module 102 determines the traction force difference 706 based on the wheel torque values 714 and the tire radius 702, and determines the induced traction force 448 based on the traction force difference 706 and the received scrub radius 708. In such an example, the traction force difference 706 and the induced traction force 448 can be calculated according to functions 704, 710 (e.g., conventional functions), respectively.

[0106] Next, at Figure 7In the example, the control module 102 determines the self-aligning torque 460. Specifically, the self-aligning torque 460 is calculated by multiplying the self-aligning torque percentage 456 and the output 452 of block 450 (represented by block 458). In such an example, the self-aligning torque percentage 456 is obtained by looking up in the look-up table 454 and based on the vehicle speed 416. The output 452 is obtained based on the comparison between the kingpin torque 428 and the induced traction force 448, as explained herein.

[0107] Then, the control module 102 determines the lateral tire force 464 based on the self-aligning torque 460 and the mechanical trail and tire scrub radius 712. In such an example, the control module 102 can calculate the lateral tire force 464 at block 722 in any suitable conventional manner based on the self-aligning torque 460 and the mechanical trail and tire scrub radius 712. Then, the control module 102 converts the lateral tire force 464 to a lateral tire angle 468 (via the look-up table 466) and applies one or more filters 470 to obtain the filtered lateral tire angle 472, as explained herein.

[0108] In addition, the control module 102 determines the tire self-aligning torque 476 based on the lateral tire force 464 and the tire scrub radius 716. In such an example, the control module 102 can calculate the tire self-aligning torque 476 at block 718 in any suitable conventional manner based on the lateral tire force 464 and the tire scrub radius 716. Then, the control module 102 converts the tire self-aligning torque 476 to a tire self-aligning angle 480 (via the look-up table 478) and applies one or more filters 482 to obtain the filtered tire self-aligning angle 484, as explained herein.

[0109] In addition, the control module 102 determines the traction force 487 based on the wheel torque 414 (or the wheel torque value 714) and the tire radius 702. In such an example, the control module 102 can calculate the traction force 487 at block 720 in any suitable conventional manner based on the wheel torque and the tire radius 702. Then, the control module 102 converts the traction force 487 to a traction angle 490 (via the look-up table 488) and applies one or more filters 491 to obtain the filtered traction angle 492, as explained herein.

[0110] Figure 8 An example process 800 for designing a filter for a Figure 1 vehicle system is shown. As Figure 8As shown, process 800 begins at 802, where frequency sweep data is obtained from one or more vehicle tests or simulations. As described above, the frequency sweep data can include, for example, steering wheel angle (e.g., 30 degrees, etc.), frequency sweep range (e.g., 0 - 5Hz sweep), recorded filtered roll steer angle, compliance steer angle, front (or rear) RWA, etc. Then, process 800 proceeds to 804.

[0111] At 804, a low - pass filter structure is selected. In such an example, the filter structure can be any suitable low - pass filter structure, such as a first - order filter structure, a second - order filter structure, etc. Then, process 800 proceeds to 806.

[0112] At 806, a Bode plot is obtained using one or more inputs (e.g., compliance steer angle) and outputs (e.g., front or rear RWA, filtered roll steer angle, kinematics, estimated RWA, etc.). In various embodiments, the Bode plot can be generated by using functions such as MATLAB tfestimate, as explained above. Then, process 800 proceeds to 808.

[0113] At 808, the selected low - pass filter structure is optimized and filter parameters are determined. In various embodiments, the low - pass filter structure can be optimized and the filter parameters can be determined according to Equation (1) above. Then, process 800 proceeds to 810, where the filter parameters are output for use with the selected low - pass filter structure. Then, the process ends.

[0114] The foregoing description is merely illustrative in nature and is in no way intended to limit the present disclosure, its application, or uses. The broad teachings of the present disclosure can be implemented in a variety of forms. Thus, while the present disclosure includes specific examples, the true scope of the present disclosure should not be so limited because other modifications will become apparent after studying the drawings, the specification, and the appended claims. It should be understood that, without changing the principles of the present disclosure, one or more steps within a method can be performed in a different order (or simultaneously). Additionally, although each embodiment is described above as having certain features, any one or more of those features described with respect to any embodiment of the present disclosure can be implemented in and / or combined with the features of any other embodiment, even if the combination is not explicitly described. In other words, the described embodiments are not mutually exclusive, and permutations of one or more embodiments with each other are still within the scope of the present disclosure.

[0115] The spatial and functional relationships between components (e.g., between modules, circuit components, semiconductor layers, etc.) are described using various terms including: "connected", "joined", "coupled", "adjacent", "close", "on top", "above", "below", and "disposed". Unless explicitly described as "direct", when describing the relationship between a first and a second component in the foregoing disclosure, the relationship can be a direct relationship in which no other intervening components exist between the first and second components, but can also be an indirect relationship in which one or more intervening components (spatially or functionally) exist between the first and second components. As used herein, the phrase "at least one of A, B, and C" should be interpreted to mean the logical (A or B or C), using non-exclusive logical OR, and should not be interpreted to mean "at least one of A, at least one of B, and at least one of C".

[0116] In the figures, the direction of an arrow as indicated by the arrowhead generally indicates the information flow (such as data or instructions) of interest to the illustration. For example, when element A and element B exchange multiple types of information, but the information transmitted from element A to element B is relevant to the illustration, the arrow can point from element A to element B. This one-way arrow does not mean that no other information is transmitted from element B to element A. Additionally, for the information sent from element A to element B, element B can send a request for that information or receive an acknowledgement.

[0117] In this application, including the definitions below, the term "module" or the term "controller" can be replaced with the term "circuit". The term "module" can refer to, be part of, or include: an application specific integrated circuit (ASIC); a digital, analog, or mixed analog / digital discrete circuit; a digital, analog, or mixed analog / digital integrated circuit; a combinatorial logic circuit; a field programmable gate array (FPGA); a processor circuit that executes code (shared, dedicated, or grouped); a memory circuit that stores code executed by the processor circuit (shared, dedicated, or grouped); other suitable hardware components that provide the described functionality; or a combination of some or all of the foregoing, such as in a system-on-chip.

[0118] A module can include one or more interface circuits. In some examples, the interface circuit can include a wired or wireless interface connected to a local area network (LAN), the Internet, a wide area network (WAN), or a combination thereof. The functionality of any given module of the present disclosure can be distributed among multiple modules connected via the interface circuit. For example, multiple modules can allow load balancing. In additional examples, a server (also referred to as remote or cloud) module can perform some functionality on behalf of a client module.

[0119] As used above, the term code may include software, firmware, and / or microcode, and may refer to programs, routines, functions, classes, data structures, and / or objects. The term shared processor circuit includes a single processor circuit that executes some or all of the code from multiple modules. The term group processor circuit includes a processor circuit that, in combination with additional processor circuits, executes some or all of the code from one or more modules. References to multiple processor circuits include multiple processor circuits on separate die, multiple processor circuits on a single die, multiple cores of a single processor circuit, multiple threads of a single processor circuit, or combinations of the above. The term shared memory circuit includes a single memory circuit that stores some or all of the code from multiple modules. The term group memory circuit includes a memory circuit that, in combination with additional memory, stores some or all of the code from one or more modules.

[0120] The term memory circuit is a subset of the term computer-readable medium. As used herein, the term computer-readable medium does not include transitory electrical or electromagnetic signals propagated through a medium (such as on a carrier wave); thus, the term computer-readable medium can be considered tangible and non-transitory. Non-limiting examples of non-transitory tangible computer-readable media are non-volatile memory circuits (such as flash memory circuits, erasable programmable read-only memory circuits, or mask read-only memory circuits), volatile memory circuits (such as static random access memory circuits or dynamic random access memory circuits), magnetic storage media (such as analog or digital magnetic tape or hard disk drives), and optical storage media (such as CDs, DVDs, or Blu-ray discs).

[0121] The apparatuses and methods described in this application may be implemented in part or in whole by a special-purpose computer created by configuring a general-purpose computer to execute one or more specific functions embodied in a computer program. The functional blocks, flowchart components, and other elements described above serve as software specifications, which can be translated into a computer program by routine work of a skilled technician or programmer.

[0122] A computer program includes processor-executable instructions stored on at least one non-transitory tangible computer-readable medium. The computer program may also include or rely on stored data. The computer program may include a basic input / output system (BIOS) that interacts with the hardware of the special-purpose computer, device drivers that interact with specific devices of the special-purpose computer, one or more operating systems, user applications, background services, background applications, and the like.

[0123] A computer program may include: (i) descriptive text to be parsed, such as HTML (HyperText Markup Language), XML (eXtensible Markup Language), or JSON (JavaScript Object Notation); (ii) assembly code; (iii) object code generated from source code by a compiler; (iv) source code executed by an interpreter; (v) source code compiled and executed by a just-in-time compiler, etc. By way of example only, the source code may be written using the syntax of a language including the following: C, C++, C#, Objective-C, Swift, Haskell, Go, SQL, R, Lisp, Fortran, Perl, Pascal, Curl, OCaml, HTML5 (HyperText Markup Language 5th Revision), Ada, ASP (Active Server Pages), PHP (PHP: Hypertext Preprocessor), Scala, Eiffel, Smalltalk, Erlang, Ruby, Visual Lua, MATLAB, SIMULINK, and

Claims

1. A vehicle system for determining a road wheel angle of a vehicle, the vehicle system comprising: a plurality of sensors configured to detect a plurality of vehicle parameters including at least a bogie load on a bogie of the vehicle; as well as A control module in communication with the plurality of sensors, the control module being configured to: calculating a kingpin torque based on a sensed bogie load and wheel displacement of the vehicle; Determining a roll steering angle based on wheel displacement of the vehicle; determining a road wheel angle of the vehicle based on the roll steering angle and the kingpin torque; as well as A signal indicative of a road wheel angle is generated to control at least one vehicle control system.

2. The vehicle system of claim 1, wherein: The plurality of sensors include at least one wheel sensor configured to detect wheel displacement of the vehicle; as well as The control module is configured to receive wheel displacement of the vehicle from at least one wheel sensor.

3. The vehicle system of claim 1, wherein: The plurality of sensors include at least one vertical acceleration sensor configured to detect a vertical acceleration of the vehicle; as well as The control module is configured to receive a vertical acceleration of the vehicle and determine a wheel displacement of the vehicle based on the vertical acceleration of the vehicle.

4. The vehicle system of claim 3, wherein: The plurality of sensors include a body-based acceleration sensor configured to detect longitudinal acceleration of the vehicle; as well as The control module is configured to receive the longitudinal acceleration of the vehicle and determine a wheel displacement of the vehicle based on the vertical acceleration of the vehicle and the longitudinal acceleration of the vehicle.

5. The vehicle system of claim 1, wherein: Multiple vehicle parameters include steering wheel angle; as well as The control module is configured to determine a pitman arm length of the vehicle based on a steering wheel angle and wheel displacement of the vehicle, and to calculate a kingpin torque based on a sensed truck load and the pitman arm length.

6. The vehicle system of claim 1, wherein: Multiple vehicle parameters include steering wheel angle; as well as The control module is configured to determine an estimated road wheel angle based on the steering wheel angle, and to determine a road wheel angle of the vehicle based on the roll steering angle, the kingpin torque, and the estimated road wheel angle.

7. The vehicle system of claim 1 , wherein the control module is configured to: Converts kingpin torque into compliant steering angle; applying a low pass filter to the compliance steering angle to generate a filtered compliance steering angle; and A road wheel angle of the vehicle is determined based on the filtered compliance steering angle and the roll steering angle.

8. The vehicle system of claim 7, wherein the control module is configured to: Determine the wheel displacement values ​​on the left and right sides of the vehicle; Convert wheel displacement value into roll steering angle; applying a filter to the roll steering angle to generate a filtered roll steering angle; and A road wheel angle of the vehicle is determined based on the filtered roll steer angle and the filtered compliance steer angle.

9. The vehicle system according to claim 8, wherein: The filter is a Kalman filter.

10. The vehicle system of claim 1, wherein the control module is configured to: determining a vehicle aligning torque based on the kingpin torque and the wheel torque; and The road wheel angle of the vehicle is determined based on the roll steering angle, the kingpin torque and the return moment.

Images