DEVICES FOR IDENTIFYING AND COMPENSATING TRAILER INFLUENCES ON STEERING DYNAMICS DURING AUTOMATIC DRIVING

Abstract

Various embodiments of methods, systems and vehicle equipment are provided.A method for adaptively controlling an electronic power steering (EPS) system, which includes sending a torque control signal to an EPS based on input control signals from a vehicle trajectory control unit and a steering assist control unit when the vehicle is coupled to a trailer performing a trailer action; configuring the steering assist control unit to generate a control signal based on an algorithm that uses an adaptive factor modeling the steering dynamics affected by the trailer while engaging in the trailer action; and modeling an adaptive damping factor by the steering assist control unit based on a support weight of a trailer coupled to a trailer hitch of the vehicle, the trailer hitch reducing a force exerted on a vehicle front axle.

Description

INTRODUCTION

[0001] The technical field relates generally to steering assist devices and, more particularly, to methods, systems and devices for estimating steering characteristics for torque control of a vehicle's electronic power steering system influenced by the tongue weight of a trailer and for performing automated, autonomous and assisted maneuvers while a trailer is attached.

[0002] In recent years, there have been significant advances in autonomous and semi-autonomous driving features in land-driven vehicles, such as Super Cruise (a hands-free semi-autonomous driver assistance feature that uses high-resolution maps and road-monitoring sensors to assist a vehicle's acceleration and deceleration), Lane Keep Assist (Lane Keeping Assist, a semi-autonomous driving feature that assists the steering to keep a vehicle within lane boundaries or in the center of the lane), and others. Vehicles can still be improved in many ways.

[0003] Sway while towing a trailer can lead to load transfer and lateral coupling forces, and the forces encountered during towing affect the tire contact patch, the self-alignment moment, and the vehicle's sideslip. Trailer movement and other stationary trailer forces result in changes in the towing vehicle's steering dynamics, such as reducing the Lane Keeping Control (LCC) directional stability and adding shimmy to the steering wheel movement. The ability to compensate for these detrimental effects on steering dynamics suffers from certain obstacles, including a lack of knowledge of trailer parameters and conditions and the difficulty of easily identifying trailer dynamics.

[0004] It is desirable to implement an adaptive model and an adaptive controller that can automatically update the steering rules and parameters when a trailer is detected.

[0005] It is desirable to enable an adaptation strategy that identifies trailer parameters, operating effort, and upcoming road geometry and can proactively modify the steering system and control architecture. This adaptation can be achieved by utilizing associated steering modeling and modifying the automatic steering's operating functions in response to the additional conditions imposed by the trailer and operating environment.

[0006] Adaptive control structures, strategies and implementations for automated and assistive steering are desirable, contributing to the desired path following and lane keeping functions and other active safety and automated driving functions.

[0007] Further desirable attributes and features of the present invention will become apparent from the following detailed description and the appended claims, considered in conjunction with the accompanying drawings and the foregoing technical field and background.

[0008] WO 2020 / 095788 A1 describes a steering control device, the steering control method, and the steering control system according to the present invention are periodic and in opposite phase to the roll motion based on information about the roll motion generated in a connected vehicle, including a vehicle and a trailer. To obtain a command to generate a yaw moment and, based on this command, output a first steering angle command to the front-wheel steering control unit to control the steering angle of the front wheels of the vehicle. The second rudder angle command is output to the rear-wheel steering control unit to suppress the roll motion.

[0009] DE 197 08 144 A1 describes a method for reducing the pendulum movement of the drawbar end of a motor vehicle trailer with wheel brakes. It involves a measuring device measuring the lateral force or lateral displacement of the drawbar. Depending on this measured value, at least one of the trailer brakes is activated to brake the corresponding wheel. This creates an additional torque on the drawbar, which counteracts the resulting lateral force or lateral movement of the drawbar end.

[0010] DE 10 2004 004 151 A1 relates to a method for stabilizing a combination consisting of a towing vehicle and a trailer, in which the transverse forces acting on at least one wheel or at least one tire are determined by means of a sensor system that detects wheel forces or tire forces, the presence of a swaying movement of the trailer is detected on the basis of the determined lateral forces, and if a swaying movement of the trailer is detected, a braking intervention and / or steering intervention is carried out. DESCRIPTION

[0011] The object of the invention is to provide better damping of trailer travel. This method step is achieved by the subject matter according to claim 1.

[0012] Methods, systems, and apparatus for adaptive control structures, policies, and implementation for automatic and assistive steering of a vehicle while a trailer is attached are disclosed.

[0013] In an exemplary embodiment, a method for adaptively controlling an electronic power steering (EPS) system is provided. The method includes sending, by a vehicle-mounted steering control unit, a torque command to an EPS based on input control signals from a vehicle trajectory control unit and a steering assist control unit when the vehicle is coupled to a trailer performing a trailer action; configuring the steering assist control unit to generate a control signal based on an algorithm that uses an adaptive factor that characterizes the steering dynamics influenced by the trailer while engaging the trailer action;Modeling, by the steering-assist control unit, an adaptive damping factor based on a tongue weight of a trailer coupled to a trailer hitch of the vehicle, the trailer hitch reducing a force applied to a vehicle front axle; Receiving, by the steering-assist control unit, a set of forces applied by the trailer coupled to the vehicle's trailer hitch, including at least one lateral force that affects the lateral dynamics of the vehicle and the angular movement of the vehicle while participating in the trailering action;and generating a control signal by the power steering control unit for applying torque assistance to the EPS, wherein the algorithm uses the adaptive factor to compensate for the at least one lateral force by a gain exerted by the damping factor based on a torque force modeled by a transfer function at least proportional to the support weight;

[0014] In at least one exemplary embodiment, the method includes applying a damping factor by the steering assist controller based on the transfer function to compensate for a set of unknown coupling forces and load transfers by the trailer while initiating trailer operation.

[0015] In at least one exemplary embodiment, the method includes configuring an offline algorithm for use in modeling, by the power steering controller, an adaptive damping factor based on a tongue weight of a current trailer coupled to a trailer hitch of the vehicle with a set of known tongue weights.

[0016] In at least one exemplary embodiment, the method includes configuring an offline algorithm for use by modeling an adaptive damping factor by comparing a tongue weight of a current trailer coupled to a trailer hitch of the vehicle to a set of known tongue weights determined by offline training, the vehicle currently being in a pre-production state.

[0017] In at least one exemplary embodiment, the method includes identifying, by the power steering controller, an effect of the support weight by comparing the angular velocity of the vehicle and a self-aligning torque (SAT).

[0018] In at least one exemplary embodiment, the method includes the identified effect of the support weight versus the angular velocity of the vehicle and the self-aligning torque (SAT) is performed during manufacture of the vehicle.

[0019] In at least one exemplary embodiment, the method includes calibrating a pilot control unit of the steering controller by the steering assist control unit by comparing at least the angular velocity of the vehicle and a self-aligning torque (SAT).

[0020] In at least one exemplary embodiment, the method includes using a model by the steering unit based at least on the calibrated steering control unit and the angular velocity of the vehicle.

[0021] In another exemplary embodiment, a system is provided. The system includes a processing unit disposed in a vehicle and including one or more processors configured by programming instructions encoded on non-transitory computer-readable media for adaptive electronic power steering (EPS) control to: send a torque command to the EPS based on input control signals from a vehicle trajectory control system and an adaptive EPS damping factor algorithm when the vehicle is coupled to a trailer that is in trailering action; configure the adaptive EPS damping factor algorithm to generate a control signal using an adaptive factor that characterizes the steering dynamics affected by the trailer while in trailering action;Modeling an adaptive damping factor for a tongue weight of a trailer coupled to a trailer hitch of the vehicle, the trailer hitch reducing a force acting on a vehicle front axle; receiving a set of forces exerted by the trailer coupled to the vehicle's trailer hitch, including at least one lateral force that affects the vehicle's lateral dynamics and angular motion while in towing action; and generating a control signal to apply torque assist to the EPS, wherein the adaptive EPS damping factor algorithm changes the adaptive factor to compensate for the at least one lateral force with a gain applied by the damping factor based on a torque force modeled by a transfer function at least proportional to the tongue weight.

[0022] In at least one exemplary embodiment, the system includes the processing unit configured to apply the damping factor based on the transfer function to compensate for a set of unknown coupling forces and load transfers by the trailer while engaged in trailering operation.

[0023] In at least one exemplary embodiment, the system includes the processing unit configured to configure an offline algorithm for use in modeling an adaptive damping factor based on a tongue weight of a current trailer coupled to a trailer hitch of the vehicle with a set of known tongue weights.

[0024] In at least one exemplary embodiment, the system includes the processing unit configured to identify the tongue weight by comparing the angular velocity of the vehicle and a self-aligning torque (SAT) with an offline algorithm that models an adaptive damping factor based on the tongue weight of a current trailer coupled to a trailer hitch of the vehicle with a set of known tongue weights.

[0025] In at least one exemplary embodiment, the system includes the processing unit configured to calibrate a steering control unit for the adaptive steering control by comparing at least the angular velocity of the vehicle and a self-aligning torque (SAT).

[0026] In at least one exemplary embodiment, the system includes the processing unit configured to use a model based at least on the calibrated forward unit and the angular velocity of the vehicle.

[0027] In another exemplary embodiment, a vehicle device is provided with a steering assist unit including one or more processors and non-transitory computer-readable media encoded with programming instructions, the steering assist unit being configured to adaptively control the electronic power steering (EPS). The steering assist unit is configured to: send a torque command to the EPS based on input control signals from a vehicle trajectory control system and an adaptive EPS damping factor algorithm when the vehicle is coupled to a trailer engaging in trailer action; configure the adaptive EPS damping factor algorithm to generate a control signal using an adaptive factor that characterizes the steering dynamics influenced by the trailer while engaging in trailer action;Modeling an adaptive damping factor for a tongue weight of a trailer coupled to a trailer hitch of the vehicle, the trailer hitch reducing a force applied to a vehicle front axle; receiving a set of forces applied by the trailer coupled to the vehicle's trailer hitch, including at least one lateral force that affects the vehicle's lateral dynamics and angular motion while participating in the trailering action; and generating a control signal to apply torque assist to the EPS, wherein the adaptive EPS damping factor algorithm changes the adaptive factor to compensate for the at least one lateral force with a gain applied by the damping factor based on a torque force modeled by a transfer function at least proportional to the tongue weight.

[0028] In at least one exemplary embodiment, the vehicle device includes the steering assist unit configured to apply the damping factor based on the transfer function to compensate for a set of unknown coupling forces and load transfers by the trailer while engaged in trailering operation.

[0029] In at least one example embodiment, the vehicle device includes the steering assist unit configured to: configure for use an offline algorithm that models an adaptive damping factor based on a tongue weight of a current trailer coupled to a trailer hitch of the vehicle with a set of known tongue weights.

[0030] In at least one example embodiment, the vehicle device includes the steering assist unit configured to: identify the tongue weight by comparing the angular velocity of the vehicle and a self-aligning torque (SAT), model an offline algorithm for use that models an adaptive damping factor based on a tongue weight of a current trailer coupled to a trailer hitch of the vehicle with a set of known tongue weights.

[0031] In at least one example embodiment, the vehicle device includes the steering assist unit configured to: calibrate a steering control unit for the adaptive steering control by comparing at least the angular velocity of the vehicle and a self-aligning torque (SAT).

[0032] In at least one exemplary embodiment, the vehicle device includes the steering assist unit configured to: generate a steering control torque based at least on a set of inputs including at least predicted dynamics of the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The exemplary embodiments are described below in conjunction with the following drawings, wherein like numerals indicate like elements and wherein: Fig. 1 is a block diagram illustrating an example vehicle that may include a processor for the power steering system according to an example embodiment; Fig. 2 shows an exemplary scenario of unstable caster in a curve for the application of the steering assist system according to an exemplary embodiment; Fig. 3 is a diagram illustrating a scenario when the lane centering control (LLC) is disabled for application of the steering assist controls by the adaptive damping factor in accordance with one embodiment; and Fig. 4 shows an exemplary flowchart of the detection and compensation of trailer influences on steering dynamics by the steering assist system according to one embodiment. DETAILED DESCRIPTION

[0034] The following detailed description is merely exemplary and is not intended to limit the application and uses. Furthermore, there is no intention to be bound by any express or implied theories presented in the preceding technical field, background, summary, or the following detailed description.

[0035] As used herein, the term "module" refers to any hardware, software, firmware, electronic control component, processing logic, and / or processor device, individually or in any combination, including, but not limited to: application-specific integrated circuits (ASICs), a field-programmable gate array (FPGA), an electronic circuit, a processor (common, dedicated, or group) and memory executing one or more software or firmware programs, a combinational logic circuit, and / or other suitable components that provide the described functionality.

[0036] Embodiments of the present disclosure may be described herein in terms of functional and / or logical block components and various processing steps. Such block components may be implemented by any number of hardware, software, and / or firmware components configured to perform the specified functions. For example, an embodiment of the present disclosure may utilize various integrated circuit components, such as memory elements, digital signal processing elements, logic elements, lookup tables, or the like, capable of performing a variety of functions under the control of one or more microprocessors or other control devices.Furthermore, those skilled in the art will understand that embodiments of the present disclosure may be used in connection with any number of systems and that the systems described herein are merely exemplary embodiments of the present disclosure.

[0037] Autonomous and semi-autonomous vehicles are capable of sensing their surroundings and navigating based on the sensed environment. Such vehicles sense their surroundings using various types of sensors, such as optical cameras, radar, lidar, other image sensors, and the like. In such vehicles, the sensed data can be combined with map data and vehicle sensors (inertial measurement device, speed sensors, etc.) to determine and track the vehicle's trajectory tracking performance based on road geometry.

[0038] In various exemplary embodiments, the present disclosure describes methods, systems, and apparatus for adaptive control structure, policy, and optimization for automated and assisted steering while a trailer is attached.

[0039] In various exemplary embodiments, the present disclosure describes methods, systems, and apparatus for automated and assisted steering during trailer hitching to detect the effects of trailer dynamics on steering control, improve methods for detecting steering characteristics during hitching, and compensate for unknown trailer forces and load transfers during hitching through adaptive control structures.

[0040] Fig. 1 shows a block diagram illustrating an example vehicle that may include a processor for the power steering system according to an example embodiment.

[0041] In an exemplary embodiment, the assistive steering system 100 ("System") provides adjustments for automated and assistive steering while a trailer is connected, and identifies the effects of trailer dynamics on steering control. The assistive steering system provides a steering characteristic identification method that models steering dynamics while considering trailer effects and provides a method for compensating for unknown trailer forces and load transfers in an adaptive control structure.

[0042] The steering system 100 continuously implements automated steering functions that correspond to the driver's perception of safety and change depending on the vehicle's position within the lane and the road geometry and conditions. For example, when the vehicle is in a safe operating state, the driver perceives steering as less necessary and expects less effort to stop the vehicle. Accordingly, the system 100 reduces the driver's effort when using a convenient automated steering function. This, in turn, reduces the overall driver annoyance of manual steering control when the driver's intent differs from that of the automated driving function implemented by the system 100 when the vehicle is operating in a safe state.

[0043] In an exemplary embodiment, system 100 implements continued automatic steering functions that can correspond to the driver's perception of "safe" changes based on vehicle position and roadway conditions. When the vehicle is in a safer operating condition due to vehicle position within the lane boundaries and / or road geometry and roadway conditions, system 100 responds to the driver's perception that steering is less necessary and the expected reduction in effort required to stop. System 100 can also reduce driver effort when using other related automatic hand-steering functions to reduce the overall annoyance of hand-steering when the vehicle is in such safe conditions.

[0044] As in Fig. 1, the vehicle 10 generally includes a chassis 12, a body 14, front wheels (front axle, on which the tongue weight acts) 16, and rear wheels 18. The body 14 is mounted on the chassis 12 (with a hitch 13 coupled to a trailer tongue) and substantially encloses the components of the vehicle 10. The body 14 and the chassis 12 may together form a frame. The vehicle wheels 16, 18 are each pivotally connected to the chassis 12 near a corner of the body 14. The vehicle 10 is shown as a passenger vehicle in the illustrated embodiment. However, it should be recognized that any other vehicle, including motorcycles, trucks, sport utility vehicles (SUVs), recreational vehicles (RVs), etc., may also be used.

[0045] As illustrated, the vehicle 10 generally includes a drive system 20, a transmission system 22, a steering system 24, a braking system 26, a sensor system 28, an actuator system 30, at least one data storage device 32, at least one controller 34, and a communication system 36. The drive system 20, in this example, may include an electric machine, such as a permanent magnet (PM) motor. The transmission system 22 is configured to transfer the power of the drive system 20 to the vehicle wheels 16 and 18 according to selectable gear ratios.

[0046] The braking system 26 is configured to apply braking torque to the vehicle wheels 16 and 18. In various exemplary embodiments, the braking system 26 may include friction brakes, a wire brake, a regenerative braking system such as an electric machine, and / or other suitable braking systems.

[0047] The steering system 24 influences the position of the vehicle wheels 16 and / or 18. Although a steering wheel 25 is shown for illustrative purposes, the steering system 24 may not include a steering wheel in some exemplary embodiments contemplated by the present disclosure.

[0048] The sensor system 28 includes one or more sensing devices 40a-40n that sense observable conditions of the external environment and / or the internal environment of the vehicle 10 and generate sensor data related thereto.

[0049] The actuator system 30 includes one or more actuator devices 42a-42n that control one or more vehicle functions, such as, but not limited to, the drive system 20, the transmission system 22, the steering system 24, and the braking system 26. In various exemplary embodiments, the vehicle 10 may also include interior and / or exterior vehicle features that are Fig. 1 are not shown, such as various doors, a trunk, and cabin features such as air, music, lighting, touchscreen display components, and the like.

[0050] The data storage device 32 stores data for controlling the vehicle 10. The data storage device 32 may be part of the control unit 34, separate from the control unit 34, or part of the control unit 34 and part of a separate system.

[0051] The controller 34 includes at least one processor 44 (integrated into or connected to the system 100) and a computer-readable storage device or medium 46. The processor 44 may be any custom or off-the-shelf processor, a central processing unit (CPU), a graphics processing unit (GPU), an application-specific integrated circuit (ASIC) (e.g., a custom ASIC implementing a neural network), a field-programmable gate array (FPGA), an auxiliary processor among multiple processors connected to the controller 34, a semiconductor-based microprocessor (in the form of a microchip or chipset), any combination thereof, or generally any device for executing instructions. The computer-readable storage devices or media 46 may include volatile and non-volatile memories, e.g.,Read-only memory (ROM), random access memory (RAM), and keep-alive memory (KAM). KAM is a persistent or non-volatile memory used to store various operating variables while the processor 44 is powered off. The computer-readable storage device(s) 46 may be implemented using various known storage devices such as PROMs (programmable read-only memory), EPROMs (electrical PROMs), EEPROMs (electrically erasable PROMs), flash memory, or other electrical, magnetic, optical, or combination storage devices capable of storing data, some of which are executable instructions used by the controller 34 in controlling the vehicle 10.

[0052] The instructions may comprise one or more separate programs, each containing an ordered list of executable instructions for implementing logical functions. When executed by processor 44, the instructions receive and process signals (e.g., sensor data) from sensor system 28, execute logic, calculations, methods, and / or algorithms to automatically control the components of vehicle 10, and generate control signals that are transmitted to actuator system 30 to automatically control the components of vehicle 10 based on the logic, calculations, methods, and / or algorithms. Although in Fig. 1 only one controller 34 is shown, embodiments of the vehicle 10 may include any number of controllers 34 that communicate and cooperate via any suitable communication medium or combination of communication media to process the sensor signals, perform logic, calculations, methods and / or algorithms, and generate control signals to automatically control features of the vehicle 10.

[0053] For example, the system 100 may include any number of additional sub-modules embedded within the controller 34, which may be combined and / or further subdivided to implement the systems and methods described herein in a similar manner. Furthermore, inputs to the system 100 may be received from the sensor system 28, from other control modules (not shown) connected to the vehicle 10, and / or from other sub-modules (not shown) within the controller 34 of Fig. 1. In addition, the inputs can also be subjected to preprocessing, such as subsampling, denoising, normalization, feature extraction, missing data reduction, and the like.

[0054] Fig. Figure 2 shows an exemplary scenario of unstable caster in a curve for the application of the steering assist control system according to an exemplary embodiment. In Fig. 2 is a control adjustment for identifying and adjusting a damping factor (D f ) for forward controls (FF). The desired trajectory is represented by the dashed curve line 200 of a vehicle 210 with a trailer and trailer tongue 211. The trailer tongue 211 applies several types of dynamic forces (lateral and oblique) to the front axle of the vehicle 210, causing the trajectory tracking error. The trajectory tracking error 215 is an indicator of when the lane centering control (LCC) disengages based on road curvature, steering control, and feature condition.

[0055] Fig. 3 is a diagram illustrating a scenario in which the automatic steering function (ASF) is deactivated to apply steering assistance through the adaptive damping factor according to one embodiment. In Fig. 3 shows the diagram that the ASF switches off when the tracking error (E trk ) exceeds a threshold. Furthermore, an oscillation of the feature state is detected.

[0056] Fig. 4 shows an exemplary flowchart of the assisted steering system's identification and compensation for trailer effects on steering dynamics, in accordance with one embodiment. Flowchart 600 includes the step of enabling adaptive control of the electronic power steering (EPS) by the steering assist system ("System"). At step 605, torque control is initiated by the System to send a torque control command to an EPS to control forward or reverse torque assist for a steering system, and is based on input control signals from a vehicle trajectory controller and a steering assist controller when the vehicle is coupled to a trailer performing a trailering action.

[0057] At method step 610, the system configures a steering-assist controller to generate a control signal based on an algorithm that uses an adaptive factor that characterizes the steering dynamics influenced by the trailer while performing the trailering action. At method step 615, the system's steering-assist controller uses an adaptive damping factor based on the tongue weight of a trailer connected to a trailer hitch of the vehicle. Using the trailer hitch reduces the force acting on the vehicle's front axle.At process step 620, the steering assist control unit of the system receives a set of forces exerted by the trailer coupled to the vehicle's trailer hitch, where a lateral force affects or influences the lateral dynamics of the vehicle and may also affect the angular movement of the vehicle while towing.

[0058] At process step 625, the system's steering assist controller generates a control signal for applying torque assist to the EPS. The algorithm used by the system implements the adaptive factor to compensate for one or more lateral forces by a gain amount applied by the damping factor based on a torque force modeled by a transfer function dependent on the tongue weight. At process step 630, the system's steering assist controller applies the algorithm using the transfer function to compensate for a set of unknown coupling forces and load transfers through the trailer while initiating trailering.At method step 635, the steering assist controller is configured for use with an offline algorithm by modeling the adaptive damping factor based on a tongue weight of a current trailer coupled to a vehicle's hitch with a set of known tongue weights. At method step 640, the system configures the offline algorithm for use by modeling an adaptive damping factor by comparing a tongue weight of a current trailer coupled to a vehicle's hitch with a set of known tongue weights determined through offline training, with the vehicle currently in a pre-production state.

[0059] At method step 645, the system, through the power steering control unit, identifies a tongue weight effect by comparing the vehicle's angular velocity and a self-aligning torque (SAT). The determination of the tongue weight effect compared to the vehicle's angular velocity and the self-aligning torque (SAT) occurs during vehicle production.

[0060] At method step 650, the system calibrates, through the steering assist control unit, a steering control pilot unit by comparisons of at least the angular velocity of the vehicle and a self-aligning torque (SAT).

[0061] At method step 655, the system uses a model through the steering unit that is based at least on the calibrated steering control unit and the angular velocity of the vehicle.

[0062] According to the invention, the adaptive damping factor is implemented with a deep neural network to determine the estimated damping factors for pre-production vehicles and in production vehicles. In this case, the support weights, the models, and the algorithm would be configured as a pre-trained neural network. Therefore, in certain embodiments, the process of estimating the damping factor of the steering control system is configured in only one operating mode. For example, in various embodiments, the deep neural network is trained in a training mode before being deployed or deployed in the vehicle (or in other vehicles). Once the deep neural network is trained, it can be deployed in a vehicle (e.g., the vehicle 10 of Fig. 1) be implemented in an operating mode in which the vehicle is operated autonomously, semi-autonomously or manually.

[0063] According to the invention, the neural network is also implemented in a vehicle in both training mode and operating mode and trained during an initial operating period in conjunction with the operation of conditions and events or a similar methodology for torque control for the EPS and for estimating the damping factor. A vehicle can also be operated exclusively in operating mode with neural networks that have already been trained in a training mode of the same vehicle and / or other vehicles in different embodiments.

[0064] As briefly mentioned above, the various modules and systems described above can be implemented as one or more machine learning models that undergo supervised, unsupervised, semi-supervised, or reinforcement learning. Such models can be trained to perform classification (e.g., binary or multi-class classification), regression, clustering, dimensionality reduction, and / or similar tasks. Examples of such models include artificial neural networks (ANNs) (e.g., recurrent neural networks (RNNs) and convolutional neural networks (CNNs)), decision tree models (e.g., classification and regression trees (CARTs)), ensemble learning models (e.g., boosting, bootstrapped aggregation, gradient boosting machines, and random forests), Bayesian network models (e.g.,, Naive Bayes), principal component analysis (PCA), support vector machines (SVM), clustering models (such as K-nearest neighbor, K-means, expectation maximization, hierarchical clustering, etc.) and linear discriminant analysis models.

[0065] It should be noted that the process of Fig. 1-4 may include any number of additional or alternative process steps, that the process steps shown in FIGS. 1-4 need not be performed in the order shown, and that the process of FIGS. 1-4 may be integrated into a more comprehensive process or a process with additional functionality not described in detail here. In addition, one or more of the Fig. 1-4 shown process steps in an embodiment of the Fig. 1-4 may be omitted as long as the intended overall functionality is retained.

[0066] The foregoing detailed description is merely illustrative and is not intended to limit the embodiments of the subject matter or the application and uses of such embodiments. As used herein, the word "exemplary" means "serving as an example, instance, or illustration." Any implementation described herein as exemplary is not necessarily to be construed as preferred or advantageous over other implementations. Furthermore, there is no intention to be bound by any express or implied theory presented in the foregoing technical field, background, or detailed description.

[0067] Although at least one exemplary embodiment has been presented in the foregoing detailed description, it should be understood that numerous variations exist. It should also be appreciated that the exemplary embodiment or exemplary embodiments are merely examples and are not intended to limit the scope, applicability, or configuration of the disclosure in any way. Rather, the foregoing detailed description is intended to provide those skilled in the art with practical guidance for implementing the exemplary embodiment or exemplary embodiments.

[0068] It is to be understood that various changes in the function and arrangement of elements may be made without departing from the scope of the disclosure as set forth in the appended claims and their legal equivalents.

Claims

[1] A vehicle device comprising a steering assist unit comprising one or more processors and non-transitory computer-readable media encoded with programming instructions, the steering assist unit being configured for adaptive control of the electronic power steering system, EPS, to: Sending a control comprising a torque control and an angle control to the EPS based on input control signals from a vehicle trajectory control system and an adaptive EPS damping and spring factor algorithm when a vehicle (10) is coupled to a trailer that is in trailer operation; configure the adaptive EPS damping factor algorithm to generate a control signal with an adaptive factor that characterizes the steering dynamics influenced by the trailer during the trailering operation; Modelling adaptive damping and suspension factors for a nose load of a trailer coupled to a trailer coupling of the vehicle (10), the trailer coupling reducing a force exerted on the front axle of the vehicle; to receive a set of forces exerted by the trailer coupled to the vehicle's tow bar, including at least one lateral force that affects the lateral dynamics of the vehicle (10) and the angular movement of the vehicle during trailer action; and Generating the control signal for applying torque assistance to the EPS, wherein the algorithm for the adaptive EPS damping and spring factors changes the adaptive factors to compensate for at least one lateral force by a gain applied by the damping factor based on a torque force modeled by a transfer function at least proportional to the vertical load, wherein the adaptive damping factor is implemented with a deep neural network to determine the estimated damping factors for pre-production vehicles and in production vehicles, wherein the neural network is implemented in a vehicle in both training mode and operating mode and is trained during an initial operating period in conjunction with the operation of conditions and events or a similar methodology for torque control for the EPS and for estimating the damping factor, wherein the vehicle (10) is operable exclusively in the operating mode with neural networks that have already been trained in a training mode of the same vehicle and / or other vehicles in different embodiments.

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