Mitigating traction steering disturbances from driver feedback torque in steer-by-wire vehicles

Abstract

In an exemplary embodiment, a system is provided that includes one or more sensors and one or more processors of a vehicle having a steering system. The one or more sensors are configured to obtain sensor data regarding the vehicle. One or more processors coupled to the one or more sensors and configured to at least facilitate determining a likelihood of the vehicle having a traction steering disturbance; and selectively adjusting a resistance of a steering wheel of the steering system in accordance with instructions provided via the one or more processors and executed via a motor coupled to the steering wheel.

Description

Technical Field

[0001] TECHNICAL FIELD The present invention relates generally to vehicles and, more particularly, to methods and systems for controlling driver feedback torque in a steering system of a vehicle. Background Art

[0002] Many vehicles today are steer-by-wire vehicles, where the vehicle's steering wheel is not physically connected to the vehicle's wheels. In such vehicles, resistance can be provided to the driver via the steering wheel. However, in certain situations, this resistance can be affected by traction steering disturbances from the driver's feedback torque.

[0003] Therefore, it is desirable to provide improved methods and systems for controlling traction steering disturbances in vehicles, such as steer-by-wire vehicles.Furthermore, other desirable features and characteristics of the present disclosure will become apparent from the subsequent detailed description and the appended claims, taken in conjunction with the accompanying drawings and the foregoing technical field and background. Summary of the Invention

[0004] According to an exemplary embodiment, a method is disclosed that includes obtaining sensor data from one or more sensors of a vehicle having a steering system; determining, via one or more processors of the vehicle, a likelihood that the vehicle has experienced a traction steering disturbance; and selectively adjusting a steering wheel resistance of the steering system based on instructions provided via the one or more processors and executed via a motor coupled to the steering wheel.

[0005] Also in the exemplary embodiment, determining the likelihood of a traction steer disturbance occurring includes generating, via the one or more processors, a scalar value for each of a plurality of parameter values from the sensor data, wherein each of the scalar values represents a respective likelihood that a respective one of the plurality of parameter values may contribute to the traction steer disturbance; aggregating, via the one or more processors, the scalar values for each of the plurality of parameter values; and calculating, via the one or more processors, an aggregate measure of the likelihood of the vehicle experiencing the traction steer disturbance based on the aggregation of the scalar values.

[0006] Also in the exemplary embodiment, each of the scalar values has a value between 0 and 1.

[0007] Also in the exemplary embodiment, the step of aggregating the scalar value includes multiplying, via the one or more processors, the scalar value for each of the plurality of parameter values.

[0008] Also in the exemplary embodiment, the method further includes: obtaining a measured steering rack load for the steering system from the sensor data; determining, via the one or more processors, a corrected steering rack load attributable to the traction steering disturbance; and determining, via the one or more processors, an adjustment to the resistance based on the corrected steering rack load; wherein the step of selectively adjusting the resistance includes implementing the adjustment via a motor coupled to the steering wheel in accordance with instructions provided via the one or more processors.

[0009] Also in the exemplary embodiment, the method further includes determining, via the one or more processors, a traction steering induced rack force estimate based on the measured steering rack load and the likelihood that the vehicle is experiencing a traction steering disturbance; wherein the determination of the corrected steering rack load is performed using the traction steering induced rack force estimate.

[0010] Also in the exemplary embodiment, the method further includes applying, via the one or more processors, frequency map-based filtering using the measured steering rack load and the likelihood that the vehicle is experiencing a traction steer disturbance; wherein the determination of the corrected steering rack load is performed using both the traction steer induced rack force estimate and the frequency map-based filtering.

[0011] In another exemplary embodiment, a system is provided that includes one or more sensors and one or more processors of a vehicle having a steering system. The one or more sensors are configured to obtain sensor data about the vehicle. The one or more processors are coupled to the one or more sensors and configured to at least facilitate determining a likelihood that the vehicle has experienced a traction steering disturbance; and selectively adjust a steering wheel resistance of the steering system based on instructions provided by the one or more processors and executed by a motor coupled to the steering wheel.

[0012] Also in an exemplary embodiment, the one or more processors are configured to at least facilitate generating a scalar value for each of a plurality of parameter values from the sensor data, wherein each of the scalar values represents a respective likelihood that a respective one of the plurality of parameter values may contribute to a traction steering disturbance; aggregating the scalar values for each of the plurality of parameter values; and calculating an aggregate measure of the likelihood of a traction steering disturbance occurring for the vehicle based on the aggregation of the scalar values.

[0013] Also in the exemplary embodiment, each of the scalar values has a value between 0 and 1.

[0014] Also in the exemplary embodiment, the one or more processors are configured to facilitate at least aggregating the scalar value by multiplying the scalar value for each of the plurality of parameter values.

[0015] Also in the exemplary embodiment, the one or more processors are configured to at least facilitate obtaining a measured steering rack load for the steering system from the sensor data; determining a corrected steering rack load attributable to a traction steering disturbance; determining an adjustment to the resistance based on the corrected steering rack load; and selectively adjusting the resistance by implementing the adjustment via a motor coupled to the steering wheel in accordance with instructions provided via the one or more processors.

[0016] Also in the exemplary embodiment, the one or more processors are configured to facilitate at least determining a traction steer induced rack force estimate based on the measured steering rack load and a likelihood that the vehicle is experiencing a traction steer disturbance; and determining a corrected steering rack load using the traction steer induced rack force estimate.

[0017] Also in the exemplary embodiment, the one or more processors are further configured to at least facilitate applying frequency map-based filtering using the measured steering rack load and the likelihood that the vehicle is experiencing a traction steer disturbance; and determining a corrected steering rack load using both the traction steer induced rack force estimate and the frequency map-based filtering.

[0018] In another exemplary embodiment, a vehicle is provided that includes a steering system, one or more sensors, and one or more processors. The steering system includes a steering wheel and a motor coupled thereto. The one or more sensors are configured to obtain sensor data about the vehicle. The one or more processors are coupled to the one or more sensors and configured to at least facilitate determining a likelihood of a traction steering disturbance occurring in the vehicle; and selectively adjust steering wheel resistance based on instructions provided by the one or more processors and executed by the motor coupled to the steering wheel.

[0019] Also in an exemplary embodiment, the one or more processors are configured to at least facilitate generating a scalar value for each of a plurality of parameter values from the sensor data, wherein each of the scalar values represents a respective likelihood that a respective one of the plurality of parameter values may contribute to a traction steering disturbance; aggregating the scalar values for each of the plurality of parameter values; and calculating an aggregate measure of the likelihood of a traction steering disturbance occurring for the vehicle based on the aggregation of the scalar values.

[0020] Also in the exemplary embodiment, each of the scalar values has a value between 0 and 1; and the one or more processors are configured to at least facilitate aggregating the scalar values by multiplying the scalar values of each of the plurality of parameter values.

[0021] Also in the exemplary embodiment, the steering system further includes a steering rack, and the one or more processors are configured to at least facilitate obtaining a measured steering rack load for the steering rack from the sensor data; determining a corrected steering rack load due to a traction steering disturbance; determining an adjustment to the resistance based on the corrected steering rack load; and selectively adjusting the resistance by implementing the adjustment via a motor coupled to a steering wheel in accordance with instructions provided via the one or more processors.

[0022] Also in the exemplary embodiment, the one or more processors are configured to facilitate at least determining a traction steer induced rack force estimate based on the measured steering rack load and a likelihood that the vehicle is experiencing a traction steer disturbance; and determining a corrected steering rack load using the traction steer induced rack force estimate.

[0023] Also in the exemplary embodiment, the one or more processors are further configured to at least facilitate applying frequency map-based filtering using the measured steering rack load and the likelihood that the vehicle is experiencing a traction steer disturbance; and determining a corrected steering rack load using both the traction steer induced rack force estimate and the frequency map-based filtering. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The present disclosure will be described below with reference to the following drawings, wherein like numerals represent like elements, and wherein:

[0025] Figure 1 is a functional block diagram of a vehicle including a steering system and a control system for controlling the steering system and mitigating traction steering disturbances in the vehicle according to an exemplary embodiment; and

[0026] Figure 2 is a flow chart of a process for controlling mitigation of traction steering disturbances in a vehicle according to an exemplary embodiment, and the process may be combined with Figure 1 Vehicles (including Figure 1 This is achieved by using steering systems and control systems and their components). DETAILED DESCRIPTION

[0027] The following detailed description is merely exemplary in nature and is not intended to limit the present disclosure or its application and uses. Furthermore, there is no intention to be bound by any theory presented in the preceding background or the following detailed description.

[0028] Figure 1 As described in greater detail further below, the vehicle 100 includes a steering system 104 having a control system 102 for controlling and mitigating traction steering disturbances in the steering system 104 caused by driver feedback when operating the vehicle 100, as described below in conjunction with Figure 1The vehicle 100 and Figure 2 The process 200 is further described in more detail.

[0029] In various embodiments, the vehicle 100 comprises an automobile. The vehicle 100 can be any of a variety of different types of automobiles, such as, for example, a sedan, van, truck, or sport utility vehicle (SUV), and in some embodiments can be two-wheel drive (2WD) (i.e., rear-wheel drive or front-wheel drive), four-wheel drive (4WD), or all-wheel drive (AWD), and / or various other types of vehicles. In some embodiments, the vehicle 100 can also include a motorcycle or other vehicle, such as an airplane, spacecraft, watercraft, etc., and / or one or more other types of mobile platforms (e.g., a robot and / or other mobile platforms). In various embodiments, the vehicle 100 comprises a steer-by-wire vehicle.

[0030] Vehicle 100 includes a body 105 disposed on a chassis 108. Body 105 substantially surrounds the other components of vehicle 100. Body 105 and chassis 108 may together form a frame. Vehicle 100 also includes a plurality of wheels 110. Wheels 110 are each rotationally coupled to chassis 108 near a respective corner of body 105 to facilitate movement of vehicle 100. In one embodiment, vehicle 100 includes four wheels 110, although this may vary in other embodiments (e.g., for trucks and certain other vehicles).

[0031] The drive system 106 is mounted on the chassis 108 and drives the wheels 110, for example, via axles 114. In various embodiments, the drive system 106 includes a propulsion system that includes a motor 122 (e.g., an internal combustion engine and / or an electric motor / generator coupled to a transmission thereof). In some embodiments, the drive system 106 includes or is coupled to an accelerator pedal that receives input from a driver of the vehicle 100. In the depicted embodiment, the axles 114 include a front axle 114(1) and a rear axle 114(2).

[0032] In various embodiments, the steering system 104 provides steering for the vehicle 100. Figure 1 , in various embodiments, the steering system 104 includes a steering wheel 116, a rack system 118, and a motor 120. In various embodiments, the driver of the vehicle 100 controls the steering via the steering wheel 116. Also in various embodiments, the rack system 118 utilizes input from the driver engaging the steering wheel 116 to rotate the wheels 110 of the vehicle 100 to provide steering. In some embodiments, the rack system 118 comprises a rack and pinion steering system. Furthermore, as described above, in various embodiments, the steering system 104 comprises a steer-by-wire system in which the steering wheel 116 is not physically connected to the wheels 110.

[0033] Likewise Figure 1 , in various embodiments, the steering system 104 further includes a motor 120 coupled to the steering wheel 116. In various embodiments, the motor 120 is utilized to provide and adjust resistance to the steering wheel 116, for example, so that the steering wheel 116 performs and feels as intended by the driver. In various embodiments, the motor 120 is utilized to control and mitigate traction steering disturbances to the steering wheel 116 from driver feedback (as described below), based on instructions provided by the control system 102.

[0034] Continue to refer Figure 1 In various embodiments, the control system 102 controls the operation of the steering system 104. Specifically, in various embodiments, the control system 102 controls the operation of the rack system 118, including providing steering for the vehicle 100 via the steering wheel 116 in the event of user input. Also in various embodiments, as described above, the control system 102 controls the mitigation of traction steering disturbances to the steering wheel 116 from driver feedback, including as follows in conjunction with Figure 2 The process 200 is further described in more detail.

[0035] like Figure 1 As depicted in FIG. 1 , in various embodiments, control system 102 includes a sensor array 130 and a controller 140 , as described in greater detail below according to exemplary embodiments.

[0036] In various embodiments, the sensor array 130 collects data related to the vehicle 100 and its components, including for detecting conditions related to the likelihood that a traction steering disturbance may occur with respect to the steering wheel 116. In various embodiments, the sensor data from the sensor array 130 is provided to the controller 140 for use in mitigating the traction steering disturbance, e.g., as described in further detail further below.

[0037] In various embodiments, the sensor array 130 includes one or more rack load sensors 131, torque sensors 132, rotation sensors 133, suspension sensors 134, speed sensors 135, throttle sensors 136, steering wheel sensors 137, and friction sensors 138. In certain embodiments, the sensor array 130 may also include one or more input sensors 139.

[0038] In various embodiments, the rack load sensor 131 measures Figure 1 The load on the rack system 118.

[0039] Also in various embodiments, the torque sensor 132 measures one or more torque values of the vehicle 100 , including, in certain embodiments, propulsion torque of the front axle 114 ( 1 ) of the vehicle 100 .

[0040] In various embodiments, the rotation sensor 133 measures the rotational speed of one or more wheels 110 of the vehicle 100 , including one or more front wheels 110 thereof.

[0041] In various embodiments, the suspension sensors 134 include one or more suspension and / or pitch angle sensors that obtain sensor data regarding the pitch angle of the vehicle 100 and / or one or more other parameters related to the suspension system of the vehicle 100 .

[0042] Additionally, in various embodiments, the speed sensor 135 measures the speed of the vehicle 100 and / or information used to determine the vehicle's speed (eg, in certain embodiments, the speed sensor 135 may include a wheel speed sensor 135 that measures the wheel speeds of the vehicle 100 ).

[0043] In various implementations, the throttle sensor 136 measures or detects a position of a throttle of the vehicle 100 (eg, the propulsion system 106 ).

[0044] In various embodiments, the steering wheel sensor 137 obtains sensor data regarding the steering wheel 116 of the vehicle 100 , including regarding the angle and speed of the steering wheel 116 .

[0045] Also in certain embodiments, friction sensor 138 includes one or more sensors that measure or detect sensor data related to and / or that can be used to calculate a coefficient of road friction for a road or path on which vehicle 100 is traveling.

[0046] In various embodiments, input sensors 139 include one or more sensors that measure or detect input provided by a driver of vehicle 100. In various embodiments, input sensors 139 are coupled to the steering wheel, accelerator pedal, brake pedal, and other instruments of vehicle 100 and are configured to measure or detect driver engagement thereof.

[0047] In various embodiments, the controller 140 is coupled to the sensor array 130 and receives sensor data therefrom. In various embodiments, the controller 140 is further coupled to the steering system 104 and, in some embodiments, to one or more (and, in some embodiments, to the drive system 106 and / or other systems of the vehicle 100). In various embodiments, the controller 140 controls the steering system 104 (including mitigation of traction steering disturbances) based on the sensor data, including as follows in conjunction with Figure 2 The process 200 is further described.

[0048] In various embodiments, the controller 140 comprises a computer system (also referred to herein as computer system 140). In various embodiments, the controller 140 (and in some embodiments, the control system 102 itself) is disposed within the body 105 of the vehicle 100. In one embodiment, the control system 102 is mounted on the chassis 108. In some embodiments, the controller 140 and / or the control system 102 and / or one or more components thereof may be disposed externally to the body 105, such as on a remote server, in the cloud, or the like.

[0049] It should be understood that the controller 140 may be different from Figure 1 For example, the controller 140 may be coupled to or may otherwise utilize one or more remote computer systems and / or other control systems, such as as part of one or more of the vehicle 100 devices and systems described above.

[0050] In the depicted embodiment, the computer system of controller 140 includes a processor 142, memory 144, an interface 146, a storage device 148, and a bus 150. Processor 142 performs computational and control functions of controller 140 and may include any type of processor or multiple processors, a single integrated circuit such as a microprocessor, or any suitable number of integrated circuit devices and / or circuit boards working in conjunction to implement the functionality of a processing unit. During operation, processor 142 executes one or more programs 152 contained within memory 144 and, therefore, controls the general operation of controller 140 and the computer system of controller 140, typically in performing the processes described herein, such as Figure 2 200, and further described below in conjunction therewith.

[0051] The memory 144 can be any type of suitable memory, including various types of non-transitory computer-readable storage media. In some examples, the memory 144 is located and / or co-located on the same computer chip as the processor 142. In the depicted embodiment, the memory 144 stores the aforementioned program 152 as well as stored values 154 (e.g., lookup tables, thresholds, and / or other values regarding traction steering disturbances and their relationship to sensor data).

[0052] The interface 146 allows communication with the computer system of the controller 140, for example, from a system driver and / or another computer system, and can be implemented using any suitable method and apparatus. In one embodiment, the interface 146 obtains various data from the sensor array 130 and other possible data sources. The interface 146 may include one or more network interfaces to communicate with other systems or components. The interface 146 may also include one or more network interfaces for communicating with technicians and / or one or more storage interfaces for connecting to storage devices (such as storage device 148).

[0053] Storage device 148 may be any suitable type of storage device, including various types of direct access storage and / or other memory devices. In one exemplary embodiment, storage device 148 includes a program product from which memory 144 may receive a program 152 that performs one or more embodiments of one or more processes of the present disclosure, such as Figure 2 The steps of process 200 are described in conjunction with and are further described below. In another exemplary embodiment, the program product can be directly stored in and / or otherwise accessed by memory 144 and / or disk (e.g., disk 156), such as described below.

[0054] The bus 150 is used to transfer programs, data, status, and other information or signals between the various components of the computer system of the controller 140. The bus 150 can be any suitable physical or logical means of connecting the computer system and components. This includes, but is not limited to, direct hard-wired connections, fiber optics, infrared, and wireless bus technologies. During operation, a program 152 is stored in the memory 144 and executed by the processor 142.

[0055] It should be understood that although the exemplary embodiment is described in the context of a fully functional computer system, those skilled in the art will recognize that the mechanisms of the present disclosure can be distributed as a program product in conjunction with one or more types of non-transitory computer-readable signal-bearing media for storing the program and its instructions and for carrying out its distribution, such as a non-transitory computer-readable medium that carries the program and contains computer instructions stored therein for causing a computer processor (such as processor 142) to execute and implement the program.

[0056] Figure 2 is a flow chart of a process 200 for controlling the mitigation of traction steering disturbances from driver feedback according to an exemplary embodiment. Figure 1 The process 200 is implemented by a vehicle 100 comprising Figure 1 The steering system 104 and the control system 102 and their components.

[0057] like Figure 2 As depicted in FIG, process 200 begins at step 202. In one embodiment, process 200 begins while vehicle 100 is being or has been operated, such as during or after a current vehicle drive. In one embodiment, once process 200 begins, the steps of process 200 are performed continuously.

[0058] At step 204, sensor data is obtained. In various embodiments, via Figure 1 Each sensor of the sensor array 130 obtains sensor data related to the vehicle. In some embodiments, the sensor data of step 204 includes the following, in addition to other possible types of sensor data: (i) information about the measurement from one or more rack load sensors 131; Figure 1 (ii) torque sensor data from one or more torque sensors 132, including propulsion torque of the front axle 114(1) of the vehicle 100; (iii) rotation sensor data from one or more rotation sensors 133, including rotational speed of one or more front wheels 110 of the vehicle 100; (iv) suspension data from one or more suspension sensors 134, including suspension data related to the pitch angle of the vehicle 100 and / or one or more other parameters related to the suspension system of the vehicle 100; (v) speed sensor data from one or more speed sensors 135, including speed of the vehicle 100 and / or used to determine the vehicle 100. (i) information about the speed of the vehicle 100 (e.g., wheel speed); (ii) information about the position of the throttle of the vehicle 100 (e.g., propulsion system 106) from one or more throttle sensors 136; (iii) information about the speed of the steering wheel 116 from one or more steering wheel sensors 137; (iv) information about the speed of the steering wheel 116 from one or more steering wheel sensors 137; and (ix) information about the coefficient of friction of the road from one or more friction sensors 138. In certain embodiments, additional sensor data may also be obtained via one or more input sensors 139, and may relate to, for example, input provided by a driver of the vehicle 100, such as via the steering wheel, accelerator pedal, brake pedal, and other instruments of the vehicle 100.

[0059] In various embodiments, the sensor data of step 204 is converted (e.g., as Figure 2206). Specifically, in various embodiments, during the combining step 206, each of the particular types of sensor data (e.g., as reflected in each respective type of sensor data signal) is converted into a respective scalar value as a representation of the likelihood that each type of sensor data (or associated parameters) may contribute to a traction steer condition of the steering wheel 116. In various embodiments, this is performed by a processor (such as Figure 1 142) for execution.

[0060] Specifically, as part of the combining step 206, in various embodiments: (i) the steering rack load 208 from the rack load sensor data is converted to a rack load scalar 210 (in Figure 2 Also known as K 10 ); (ii) converting the front axle propulsion torque 212 from the torque sensor data into a propulsion torque scalar 214 (in Figure 2 (iii) calculating the front axle torque change rate 216 based on the front axle propulsion torque 212 and converting it into a propulsion torque change rate scalar 218 (in Figure 2 (iv) converting the front wheel rotation increment (or change) 220 from the rotation sensor data into a rotation increment scalar 222 (in Figure 2 (v) converting the vehicle suspension pitch angle 224 from the suspension data into a pitch angle scalar 226 (in Figure 2 (vi) converting the vehicle speed 228 from the speed sensor data into a vehicle speed scalar 230 (in Figure 2 (vii) converting the throttle position 232 from the throttle sensor data into a throttle scalar 234 (in Figure 2 (viii) converting the steering wheel angle 236 from the steering wheel angle sensor data into a steering wheel angle scalar 238 (in Figure 2 (ix) converting the steering wheel speed 240 from the steering wheel speed sensor data into a steering wheel speed scalar 242 (in Figure 2 and (x) converting the road friction coefficient 244 from the road friction sensor data into a road friction coefficient scalar 246 (in Figure 2 Also known as K9 in the .

[0061] In various embodiments, each of the respective scalar values 210, 214, 218, 222, 226, 230, 234, 238, 242, and 246 is based on the current respective corresponding parameter values 208, 212, 216, 220, 224, 228, 232, 236, 240, and 244 in combination with previous or historical data related to these parameter values regarding the traction steer event (e.g., in some embodiments, related to the same vehicle 100 and / or related to other vehicles, such as may be obtained from vehicle manufacturer data, published data, shared data between different vehicles, etc.). Also in some embodiments, the previous or historical data is stored in Figure 1 The stored values 154 in the memory 144 may include, for example, functions, lookup tables, and / or other data representations.

[0062] Also in various embodiments, each of the scalar values 210, 214, 218, 222, 226, 230, 234, 238, 242, and 246 has a corresponding value between 0 and 1. Also in various embodiments, the closer the scalar value of a particular parameter is to zero ("0"), the less likely that particular parameter is contributing to a traction steering disturbance (e.g., a value of zero means that it is certain or almost certain that the current value of the particular parameter will not cause a traction steering disturbance). Conversely, also in various embodiments, the closer the scalar value of a particular parameter is to one ("1"), the more likely that particular parameter is contributing to a traction steering disturbance (e.g., a value of one means that it is certain or almost certain that the current value of the particular parameter is causing a traction steering disturbance).

[0063] In various embodiments, the corresponding scalar values are aggregated (step 248). Specifically, in various embodiments, the scalar values 210, 214, 218, 222, 226, 230, 234, 238, 242, and 246 are multiplied to generate a product 249. In various embodiments, the product 249 may also be referred to as a traction steering likelihood indicator (TSLI) 249.

[0064] like Figure 2 As depicted in FIG. 2 , in various embodiments, a traction steering induced rack force estimate is determined (step 250). In various embodiments, during step 250, the traction steering induced rack force represents the amount of rack force attributable to the traction steering disturbance. In various embodiments, during step 250, a processor (such as a Figure 1 The processor 142 ) determines the traction steering induced rack force based on the TSLI 249 and the rack load 208.

[0065] Also in various embodiments, the traction steer inducing rack force of step 250 also corresponds to a rack force offset 257 (e.g., which, in certain embodiments, can be used to correct or mitigate traction steer). In various embodiments, the rack force offset 257 corresponds to a torque that can be applied to the steering wheel 116 by the motor 120 that is equal and opposite in magnitude to the resistive torque from the driving torque force that generates the rack force, thereby mitigating traction steer of the steering wheel 116.

[0066] Furthermore, in various embodiments, the TSLI 249 from step 248 is also used for cutoff frequency mapping (step 252). Specifically, in various embodiments, when it is believed that traction steer may occur, a cutoff frequency is selected for filtering of the sensor data (particularly the rack load sensor data) that depends on the likelihood as to whether traction steer is occurring or is about to occur. In various embodiments, this is performed via a processor (such as Figure 1 Also in various embodiments, step 252 results in a specific optimized cutoff frequency "f" depending on the TSLI 249. c ”253 selection (such as Figure 2 as depicted in ).

[0067] In various embodiments, filtering is applied (step 254). Specifically, in various embodiments, during step 254, based on the optimized cutoff frequency "f c 253, filtering is applied to the measured values of the steering rack load 208. In various embodiments, filtering is performed in such a manner that the sensor data (particularly the rack load sensor data) is sufficiently filtered to remove any portion of the rack load data attributable to forces due to drive torque, thereby also mitigating traction steering disturbances. In various embodiments, this is performed by a processor (such as Figure 1 142). Also in various embodiments, a variable digital filter is used for cutoff frequency mapping. In some embodiments, the variable digital filter comprises a first-order low-pass filter. In one exemplary embodiment, the variable digital filter comprises a three-hertz (3 Hz) low-pass filter; however, this may vary in other embodiments. In various embodiments, the filtering of step 254 produces a filtered steering rack load 256 as its output.

[0068] In various embodiments, the rack force offset 257 (from step 250) and the filtered steering rack load 256 (from step 254) are aggregated in step 258. Specifically, in various embodiments, the rack force offset 257 and the filtered steering rack load 256 are added together during step 258. Also in various embodiments, this is done via a processor such as Figure 1 142) for execution.

[0069] In various embodiments, the summation of step 258 produces a traction steering correction rack load 260 as its calculation result. In various embodiments, the traction steering correction rack load 260 represents a modified or updated rack load value after any forces due to traction steering disturbances (e.g., due to propulsion torque and / or related feedback) are removed from the force value. In various embodiments, this is processed via one or more processors such as Figure 1 142) for execution.

[0070] In various embodiments, a resistance adjustment is determined (step 262). Specifically, in various embodiments, during step 262, the drag steering correction rack load is utilized to determine the drag adjustment to be applied to the vehicle. Figure 1 The motor 120 is provided to Figure 1 In various embodiments, the resistance of the steering wheel 116 is adjusted appropriately via a processor such as Figure 1 's processor 142, and / or one or more separate processors, e.g. Figure 1 The adjustment is determined by the motor 120 and / or the processor of the steering system 104. Also in various embodiments, the adjustment is determined in such a manner that the resulting adjustment to the resistance on the steering wheel 116 will be equal to and / or will appear to the driver to be equal to the resistance on the steering wheel 116 that was originally provided in the absence of the traction steering disturbance.

[0071] Also in various embodiments, an adjusted resistance is provided (step 264). In various embodiments, in implementing the determined adjustment in step 264, an adjusted resistance is provided to the steering wheel 116. In various embodiments, the steering wheel 116 is provided with an adjusted resistance according to the adjustment determined by one or more processors such as Figure 1 When the processor 142 of the control unit 100 provides instructions to the motor 120 and executes the instructions to adjust the resistance to the steering wheel 116, the adjusted resistance is automatically achieved via the motor 120. Therefore, in various embodiments, as a result, based on the current operating conditions and parameters related to the vehicle 100 and the road, the driver experiences an appropriate level of resistance from the steering wheel 116, but without unwanted traction steering interference. In other words, in various embodiments, the steering will feel more consistent with what the driver desires.

[0072] In various embodiments, process 200 then terminates at step 265 .

[0073] Thus, methods, systems, and vehicles are provided for controlling and mitigating a traction steering disturbance at the steering wheel of a vehicle. In various embodiments, sensor data is used to determine the likelihood that a traction steering disturbance is occurring or is about to occur at the steering wheel, and a motor coupled to the steering wheel and controlled according to instructions provided by a processor of a control system based on the sensor data is used to adjust the resistance of the steering wheel accordingly to mitigate the traction steering disturbance experienced by the vehicle driver.

[0074] It should be understood that the systems, vehicles, and methods may vary from those depicted in the figures and described herein. For example, Figure 1 The vehicle 100, its control system 102 and steering system 104, and / or Figure 1 The components of may vary in different embodiments. Similarly, it should be understood that the steps of process 200 may vary. Figure 2 The steps depicted in, and / or various steps of process 200 may occur simultaneously and / or in parallel. Figure 2 The sequences described in the preceding text may not occur in the same order.

[0075] Although at least one exemplary embodiment has been presented in the foregoing detailed description, it should be understood that there are a large number of variations. It should also be understood that the exemplary embodiment or multiple exemplary embodiments are merely examples and are not intended to limit the scope, applicability, or configuration of the present disclosure in any way. On the contrary, the foregoing detailed description will provide those skilled in the art with a convenient roadmap for implementing the exemplary embodiment or multiple exemplary embodiments. It should be understood that various changes may be made to the function and arrangement of elements without departing from the scope of the present disclosure as set forth in the appended claims and their legal equivalents.

Claims

1. A method comprising: obtaining sensor data from one or more sensors of a vehicle having a steering system; determining, via one or more processors of the vehicle, a likelihood that the vehicle has experienced a traction steering disturbance; as well as The resistance of the steering wheel is selectively adjusted according to instructions provided via the one or more processors and executed via a motor coupled to a steering wheel of the steering system.

2. The method according to claim 1, wherein The step of determining said likelihood of occurrence of a traction steering disturbance comprises: generating, via the one or more processors, a scalar value for each of a plurality of parameter values from the sensor data, wherein each of the scalar values represents a respective likelihood that a respective one of the plurality of parameter values may contribute to a traction steering disturbance; aggregating, via the one or more processors, the scalar value for each of the plurality of parameter values; and An aggregate measure of the likelihood of a traction steering disturbance occurring for the vehicle is calculated based on the aggregation of the scalar values, via the one or more processors.

3. The method according to claim 2, wherein: Each of the scalar values has a value between 0 and 1.

4. The method according to claim 2, wherein: Aggregating the scalar value includes multiplying, via the one or more processors, the scalar value for each of the plurality of parameter values.

5. The method according to claim 1, further comprising: obtaining a measured steering rack load for the steering system from the sensor data; determining, via the one or more processors, a corrected steering rack load attributable to the traction steering disturbance; as well as determining, via the one or more processors, an adjustment to the resistance based on the corrected steering rack load; Wherein the step of selectively adjusting the resistance comprises effectuating the adjustment via the motor coupled to the steering wheel in accordance with the instructions provided via the one or more processors.

6. The method according to claim 5, further comprising: determining, via the one or more processors, a traction steer induced rack force estimate based on the measured steering rack load and the likelihood that a traction steer disturbance has occurred on the vehicle; wherein said determining of said corrected steering rack load is performed using said traction steering induced rack force estimate.

7. The method according to claim 6, further comprising: applying, via the one or more processors, frequency mapping based filtering using the measured steering rack load and the likelihood that the vehicle is experiencing a traction steering disturbance; wherein said determining of said corrected steering rack load is performed using both said traction steering induced rack force estimation and said filtering based on said frequency mapping.

8. A system comprising: one or more sensors of a vehicle having a steering system, the one or more sensors configured to obtain sensor data about the vehicle; as well as One or more processors of the vehicle, coupled to the one or more sensors and configured to facilitate at least: determining a likelihood of a traction steering disturbance occurring on the vehicle; as well as The resistance of the steering wheel is selectively adjusted according to instructions provided via the one or more processors and executed via a motor coupled to a steering wheel of the steering system.

9. The system according to claim 8, wherein: The one or more processors are configured to facilitate at least: generating a scalar value for each of a plurality of parameter values from the sensor data, wherein each of the scalar values represents a respective likelihood that a respective one of the plurality of parameter values may contribute to a traction steering disturbance; aggregating the scalar value for each of the plurality of parameter values; and Based on the aggregation of the scalar values, an aggregate measure of the likelihood that a traction steering disturbance will occur for the vehicle is calculated.

10. The system according to claim 8, wherein: The one or more processors are configured to facilitate at least: obtaining a measured steering rack load for the steering system from the sensor data; determining a corrected steering rack load attributable to the traction steering disturbance; determining an adjustment to the resistance based on the corrected steering rack load; as well as The resistance is selectively adjusted by implementing the adjustment via the motor coupled to the steering wheel in accordance with the instructions provided via the one or more processors.

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